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In late 2011, Drexel University dermatology professor Herbert Allen was astounded to read a new research paper documenting the presence of long, corkscrew-shape bacteria called spirochetes in postmortem brains of patients with Alzheimer's disease.1 Combing data from published reports, the International Alzheimer Research Center's Judith Miklossy and colleagues had found evidence of spirochetes in 451 of 495 Alzheimer's brains. In 25 percent of cases, researchers had identified the spirochete as Borrelia burgdorferi, a causative agent of Lyme disease. Control brains did not contain the spirochetes.

The study made Allen think back to 40 years earlier, when he was an intern at Johns Hopkins University and had treated a patient diagnosed with neurosyphilis, a neurological syndrome that included dementia and resulted from the invasion of the syphilis spirochete into the brain. "The parallel between Lyme disease and syphilis had me intrigued," he says.

COURTESY OF HERBERT ALLEN Allen had recently proposed a novel role for biofilms-colonies of bacteria that adhere to surfaces and are largely resistant to immune attack or antibiotics-in eczema. He suggested that because biofilms block skin ducts and trigger innate immune responses, they may cause the stubborn skin condition. Allen knew of recent work showing that Lyme spirochetes form biofilms,² which led him to wonder if biofilms might also play a role in Alzheimer's disease. When Allen stained for biofilms in brains from deceased Alzheimer's patients, he found them in the same hippocampal locations as amyloid plaques.³ Toll-like receptor 2 (TLR2), a key player in innate immunity, was also present in the same region of the Alzheimer's brains but not in the controls. He hypothesizes that TLR2 is activated by the presence of bacteria, but is locked out by the biofilm and damages the surrounding tissue instead.

Spirochetes, common members of the oral microbiome, belong to a small set of microbes that cross the blood-brain barrier when they're circulating in the blood, as they are during active Lyme infections or after oral surgery. However, the bacteria are so slow to divide that it can take decades to grow a biofilm. This time line is consistent with Alzheimer's being a disease of old age, Allen reasons, and is corroborated by syphilis cases in which the neuroinvasive effects of spirochetes might appear as long as 50 years after primary infection.

Allen's work contributes to the revival of a long-standing hypothesis concerning the development of Alzheimer's. For 30 years, a handful of researchers have been pursuing the idea that pathogenic microbes may serve as triggers for the disease's neuropathology. Most came across the connection serendipitously, as Allen did, and some have made it their life's work, in spite of scathing criticism and related challenges in attracting funding and publishing results.

As early as the 1990s, three laboratories in different countries, each studying different organisms, had each implicated human pathogens in the etiology of Alzheimer's disease.

"There have been all these observations over time," says Miklossy. Although she says she's been dismissed as an "idiot" and denied funding, she continues to pursue spirochetes as an instigating factor in Alzheimer's disease. "I'm a physician who believes in the Hippocratic Oath," she says. "We have to do everything we can."

And the Alzheimer's field seems primed for a fresh look at a theory that might account for the disease's pathogenesis. Researchers still cannot say with confidence which features of the disease, such as neuroinflammation, tau tangles, and amyloid plaques, are involved in disease progression and thus would make effective targets for treatment. So far, most drugs that have made it to clinical testing have targeted the amyloid-β peptide, the main component of the amyloid plaques that characterize Alzheimer's brains. The idea is that a build-up of amyloid-β causes the neuropathology and that removing amyloid-β-by decreasing its production, impeding aggregation, or aiding removal of the molecule from the brain-will improve, or at least stall, symptoms of dementia. But so far, researchers have come up empty-handed.

Last November, for example, a Phase 3 trial of Eli Lilly's amyloid-targeting antibody solanezumab revealed no improvement in patients in early stages of the disease. This costly and crushing failure was followed up a few months later with another, when Merck halted its clinical trial of the small-molecule drug verubecestat, which blocks the enzyme that yields amyloid-β, in patients with mild to moderate disease. A trial using verubecestat in the earliest diagnosable stage of the disease is still underway.

And these are just the latest in a string of experimental drugs for Alzheimer's disease that have failed to show any benefit in clinical trials. Some blame the trials themselves for these high-profile flops. "The quality of the clinical trials has been low," says John Hardy, a molecular neuroscientist at the University College London, pointing out that a couple of the drugs didn't even make it into the brain.4 But other researchers question the underlying theory.

In light of continued failures to develop effective drugs, some researchers, such as Harvard neurobiologist Rudolph Tanzi, think it's high time that more effort and funding go into alternative theories of the disease. "Any hypothesis about Alzheimer's disease must include amyloid plaques, tangles, inflammation-and, I believe, infection."

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Herpes simplex virus type 1 (HSV1) can acutely infect the brain and cause a rare but very serious encephalitis. In the late 1980s, University of Manchester molecular virologist Ruth Itzhaki noticed that the areas of the brain affected in HSV1 patients were the same as those damaged in patients with Alzheimer's disease. Knowing that herpes can lie latent in the body for long periods of time, she began to wonder if there was a causal connection between the infection and the neurodegenerative disorder.

Itzhaki began looking for HSV1 DNA in the brains of Alzheimer's patients-and found it. But the viral DNA also turned up in the brains of age-matched controls. Using PCR, still a new technique at the time, was fraught with difficulty, and Itzhaki's findings were challenged as resulting from contamination. Itzhaki repeated her work with great care and consistently found that two-thirds to three-quarters of elderly people harbor HSV1 in their brains, whether they had Alzheimer's or not. So she searched for a genetic difference that might explain why only some HSV1-infected individuals develop dementia. Finally, in 1997, she reported that having both HSV1 in the brain and the apolipoprotein E gene variant APOE4 accounted for 60 percent of the Alzheimer's cases she considered-much higher than either factor alone. ⁵ But most Alzheimer's researchers still dismissed her work. Itzhaki says her detractors have been set in their ways-and perhaps too wedded to scenarios involving plaques and tangles. "They don't know anything about viruses," she says, especially the fact that herpes can linger in the body and brain. "If we say the virus causes this, they imagine the scenario is fast. It's incredibly naive."

Around the same time, neuropathologist Miklossy, then at the University of Lausanne in Switzerland, was detailing the brain damage caused by spirochetes-both in neurosyphilis and neuroborrelia, a syndrome caused by Lyme bacteria. She happened upon a head trauma case with evidence of bacterial invasion and plaque formation, and turned her attention to Alzheimer's. She isolated spirochetes from brain tissue in 14 Alzheimer's patients but detected none in 13 age-matched controls. In addition, monoclonal antibodies that target the amyloid precursor protein (APP)-which, when cleaved, forms amyloid-β-cross-reacted with the spirochete species found, suggesting the bacteria might be the source of the protein.⁶

Although Miklossy says she received some positive reactions to her findings when she published them in 1993, she, like Itzhaki, also faced her fair share of skepticism. The critiques included comments that the work was "foolish, unorthodox, and crazy," she adds.

Meanwhile, in the U.S., a third line of evidence linking Alzheimer's to microbial infection began to emerge. While serving on a fraud investigation committee, Alan Hudson, a microbiologist then at MCP-Hahnemann School of Medicine in Philadelphia, met Brian Balin, who studied neuropathological processes at the Philadelphia College of Osteopathic Medicine. Soon, Balin began to send Hudson Alzheimer's brain tissue to test for intracellular bacteria in the Chlamydia genus. Some samples tested positive for C. pneumoniae: specifically, the bacteria resided in microglia and astrocytes in regions of the brain associated with Alzheimer's neuropathology, such as the hippocampus and other limbic system areas. Hudson had a second technician repeat the tests before he called Balin to unblind the samples. The negatives were from control brains; the positives all had advanced Alzheimer's disease.7 "We were floored," Hudson says.

The paper that Balin, Hudson, and colleagues wrote to announce the findings received worldwide press coverage, says Hudson, now professor emeritus at Wayne State University School of Medicine. But when the authors went to the Alzheimer's disease meeting, he says, "nobody talked to us."

Thus, as early as the 1990s, three laboratories in different countries, each studying different organisms, had each implicated human pathogens in the etiology of Alzheimer's disease. But the suggestion that Alzheimer's might have some microbial infection component was still well outside of the theoretical mainstream.

Last year, Itzhaki, Miklossy, Hudson, and Balin, along with 29 other scientists, published a review in the Journal of Alzheimer's Disease to lay out the evidence implicating a causal role for microbes in the disease.⁸ The paper opens with a plea: "We are researchers and clinicians working on Alzheimer's disease . . . and we write to express our concern that one particular aspect of the disease has been neglected."

REPRINTED WITH PERMISSION FROM D.K.V. KUMAR ET AL., SCI TRANSL MED, 8:340RA72, 2016.

George Perry, editor of the journal and an Alzheimer's researcher at the University of Texas at San Antonio, not only agreed to publish the article, he signed on as an author too. " The Journal of Alzheimer's Disease promotes all sorts of different ideas," he says. "We don't care about popularity."

And, slowly but surely, Alzheimer's researchers finally seem to be giving the pathogen hypothesis a good, hard look. Harvard's Tanzi, one of the newer microbial theorists, has been a prominent figure in the Alzheimer's field for decades. He contributed to the 1987 discovery of APP, the first Alzheimer's disease gene. Recently, Tanzi and his colleagues showed that amyloid-β inhibits the in vitro growth of pathogenic bacteria, including Candida albicans, E. coli, and Staphylococcus aureus, suggesting the Alzheimer's-linked peptide was acting as an antimicrobial.9 Tanzi's working hypothesis is that microbes trigger an innate immune response, in which amyloid-β plays a key role. The peptide surrounds the site of infection to shield healthy tissue from the invaders. Too much clumping, however, can cause problems of its own-the very processes by which plaques trigger neuronal death.

A subsequent study by Tanzi's group found that amyloid-β binds to microbes and links together with more amyloid-β to entrap the invaders and keep them from interacting with host cells. Indeed, in a transgenic mouse model of Alzheimer's disease, Salmonella infection seeded amyloid plaques in the brain.10 "The plaques are generated in the hippocampus and temporal cortex-the regions most susceptible to blood-brain barrier breach," Tanzi says, suggesting that those areas are where pathogens would first gain entry. "It makes perfect sense to me."

Tanzi is well aware of the work by Miklossy and others and the criticism that they've received. Expecting to get their own dose of criticism, Tanzi says, "we wanted to do everything right, do every control. We spent eight years on this paper." But to his surprise, the backlash didn't come. "To our delight, the field looked at what we did," he says-a sign, perhaps, that the Alzheimer's research community is finally ready to consider the microbe theory.

© KIMBERLY BATTISTA

Proponents of this idea still face skepticism, however. Elaine Bearer, a molecular neurobiologist at the University of New Mexico Health Sciences Center, received mixed responses when she began publishing and presenting her work linking HSV1 to Alzheimer's neuropathology. As is a familiar story by now, Bearer had stumbled onto the microbe theory serendipitously.

Her main research interest is how molecular motors pick up cargo in the giant squid axon, and she uses HSV1 as experimental cargo because it's known to travel in both directions along axonal transport routes. During infection, HSV1 travels from sensory nerve endings to nerve cell bodies where the virus can hole up. When activated, HSV1 travels back out to synapses, reinfects epithelial cells, and voilà-cold-sore recurrence.

In 2006, Bearer found that HSV1 uses APP to attach to axonal transport machinery.¹¹ And as a result, HSV1 redistributes APP within the neuron, she says. That means APP can pile up in ways that don't happen in uninfected cells. More recently, Bearer showed that "the virus does something to APP," she says. "In epithelial cells, it induces a 25-fold increase in the protein," suggesting synthesis of the protein also responds to infection.¹²

Bearer has also produced evidence that HSV1 is trapped in amyloid plaques in human brains. (She has presented this work, but not published it.) This mirrors Tanzi's findings of Salmonella within amyloid plaques in an animal model, and those of Allen, who found bacterial biofilms colocalized with amyloid-β in human brain tissue.

Despite the increase in evidence supporting the microbial theory of Alzheimer's disease, however, funding for such research remains difficult to procure. And scientists working in this area also continue to face skepticism from the Alzheimer's research community. University College London's Hardy, squarely in the amyloid hypothesis camp, is aware of the work of Itzhaki, Tanzi, and some of the others, but he says he's still "not convinced."

Hardy's main objections are twofold: the idea that microbes cause Alzheimer's neuropathology doesn't fully explain the hereditary aspects of the disease, and it doesn't explain the characteristic anatomical distribution of plaques and tangles in diseased brains. He thinks distribution would be more widespread in the brain with blood-borne disease. "It just doesn't ring right," he says. "It doesn't fit the epidemiology, the neuropathology, or the genetics." To get him to change his tune, Hardy says, he'd need to see more experimental evidence "to show some element of cause and effect: infect mice, infect primates, and show disease."

The microbe theorists freely admit that their proposed microbial triggers are not the only cause of Alzheimer's disease. In Itzhaki's case, some 40 percent of cases are not explained by HSV1 infection. Of course, the idea that Alzheimer's might be linked to infection isn't limited to any one pathogen; the hypothesis is simply that, following infection, certain pathogens gain access to brain, where immune responses result in the accumulation of amyloid-β, leading to plaque formation. In the meantime, with Alzheimer's patients representing a huge unmet medical need, and experimental drugs often failing in late-stage trials, even Hardy admits that there are more questions than answers at this point in terms of the causative factors in Alzheimer's. "The pathology is a mess. The brain has been diseased for a long time by the time we see it," Hardy says. "We're looking at the end product and trying to determine how it got that way."

Perry agrees: "Most of the resources in this field are spent on a few biomarkers. All the evidence shows that amyloid is important. But causality and centrality are two different things."

Jill U. Adams is a freelance science journalist living in Albany, New York.

1. J. Miklossy, "Alzheimer's disease - a neurospirochetosis. Analysis of the evidence following Koch's and Hill's criteria," J Neuroinflamm, 8:90, 2011.

2. E. Sapi et al., "Characterization of biofilm formation by Borrelia burgdorferi in vitro," PLOS ONE, 7:e48277, 2012.

3. H.B. Allen et al., "Alzheimer's disease: A novel hypothesis integrating spirochetes, biofilm, and the immune system," J Neuroinfect Dis, 7:200, 2016.

4. E. Karran, J. Hardy, "A critique of the drug discovery and phase 3 clinical programs targeting the amyloid hypothesis for Alzheimer disease," Ann Neurol, 76:185-205, 2014.

5. R.F. Itzhaki et al., "Herpes simplex virus type 1 in brain and risk of Alzheimer's disease," Lancet, 349:241-44, 1997.

6. J. Miklossy, "Alzheimer's disease - a spirochetosis?" Neuroreport, 4:841-48, 1993.

7. B.J. Balin et al., "Identification and localization of Chlamydia pneumoniae in the Alzheimer's brain," Med Microbiol Immunol, 187:23-42, 1998.

8. R.F. Itzhaki et al., "Microbes and Alzheimer's disease," J Alzheimer's Dis, 51: 979-84, 2016.

9. S.J. Soscia et al., "The Alzheimer's disease-associated amyloid β-protein is an antimicrobial peptide," PLOS ONE, 5:e9505, 2010.

10. D.K.V. Kumar et al., "Amyloid-β peptide protects against microbial infection in mouse and worm models of Alzheimer's disease," Sci Transl Med, 8:340ra72, 2016.

11. P. Satpute-Krishnan et al., "A peptide zipcode sufficient for anterograde transport within amyloid precursor protein," PNAS, 103:16532-37, 2006.

12. S.-B. Cheng et al., "Herpes simplex virus dances with amyloid precursor protein while exiting the cell," PLOS ONE, 6:e17966, 2011.

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Do Microbes Trigger Alzheimer's Disease?

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© ISTOCK.COM/KIRSTYPARGETER In late 2011, Drexel University dermatology professor Herbert Allen was astounded to read a new research paper documenting the presence of long, corkscrew-shape bacteria called spirochetes in postmortem brains of patients with Alzheimer's disease.1 Combing data from published reports, the International Alzheimer Research Center's Judith Miklossy and colleagues had found evidence of spirochetes in 451 of 495 Alzheimer's brains.

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Inflammation drives progression of Alzheimer's

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Inflammation drives progression of Alzheimer's

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Credit: CC0 Public Domain

Dementia with Lewy bodies has a unique genetic profile, distinct from those of Alzheimer's disease or Parkinson's disease, according to the first large-scale genetic study of this common type of dementia.

The genome-wide association study, conducted by a UCL-led collaboration of 65 academics in 11 countries and funded by Alzheimer's Society and the Lewy Body Society, is published today in The Lancet Neurology.

"Dementia with Lewy bodies accounts for 10-15% of dementia cases, yet our understanding of it lags beyond the more well-known Alzheimer's disease, partly because it's commonly misdiagnosed. Our findings clarify the disease's distinctive genetic signature, which should, in the future, help improve clinical trials, and lead to more targeted treatments," said the study's lead author, Dr Jose Bras (UCL Institute of Neurology and Alzheimer's Society senior research fellow).

The research team genotyped 1,743 patients with dementia with Lewy bodies (DLB) - including both clinical samples and 1,324 pathological samples assessed post-mortem - and 4,454 controls.

Two of the genetic loci that were found to be significantly associated with DLB, APOE and GBA, bore the same associations to DLB as they do to Alzheimer's and Parkinson's, respectively. Another one of the loci identified, SNCA, is also associated with Parkinson's, but differently - the researchers found that a different part of the gene is linked to DLB. They also found preliminary evidence for a gene locus that had not been previously associated with DLB, but the results did not reach significance.

The team also found that a few loci that are associated with Alzheimer's and Parkinson's do not appear to be associated with DLB.

The researchers were able to identify a heritability estimate of DLB for the first time, at 36%, which is similar to that of Parkinson's. The heritability was particularly high for four specific chromosomes, suggesting that further research could focus on those chromosomes to identify novel loci.

"As the gene loci that had previously been associated with DLB were also implicated in Alzheimer's and Parkinson's, it was unclear if DLB's genetic roots were simply a combination of the other two diseases. We've confirmed that instead, it has its own unique genetic profile," explained the study's first author, Dr Rita Guerreiro (UCL Institute of Neurology and Alzheimer's Society senior research fellow).

"The selection of study participants has been a substantial challenge in dementia trials. Our findings can be used to identify more clearly which type of dementia each person has, so that they can take part in the right clinical trial, which could lead to better treatments and diagnostic tools," she said.

The researchers also hope that by advancing the understanding of which genes play a role in DLB, their results will aid in the development of targeted therapies.

"DLB and Parkinson's have many similarities, as people with DLB often develop Parkinson's symptoms, and Parkinson's often leads to dementia. By understanding the genetic underpinnings, we can more effectively target treatments to the different groups," said Dr Bras.

Dr Doug Brown, Director of Research at Alzheimer's Society who funded the study, said: "Dementia with Lewy bodies (DLB) is often misunderstood as being a mixture of Alzheimer's and Parkinson's, but this confirms it's actually a unique condition.

"Despite DLB being one of the most common forms of dementia in older people, until now there simply hasn't been enough information on its causes, so the finding that up to 36% of cases might be genetically inherited is a real revelation.

"As the largest and most detailed study of its kind, these results will be invaluable in future research, and it's a great milestone on the road towards our goal of understanding and treating all forms of dementia."

More information: Rita Guerreiro et al, 'Investigating the genetic architecture of dementia with Lewy bodies: a two-stage genome-wide association study,' The Lancet Neurology (2017). www.thelancet.com/journals/lan ... ulltext?elsca1=tlxpr

Anyone with concerns about DLB can call the National Dementia Helpline on 0300 222 1122 or visit alzheimers.org.uk for information and support.

Provided by: University College London

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Dementia with Lewy bodies: Unique genetic profile identified

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Dementia with Lewy bodies has a unique genetic profile, distinct from those of Alzheimer's disease or Parkinson's disease, according to the first large-scale genetic study of this common type of dementia. The genome-wide association study, conducted by a UCL-led collaboration of 65 academics in 11 countries and funded by Alzheimer's Society and the Lewy Body Society, is published today in The Lancet Neurology.

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Inflammation drives progression of Alzheimer's

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Inflammation drives progression of Alzheimer's

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"According to a study by scientists of the German Center for Neurodegenerative Diseases (DZNE) and the University of Bonn now published in the journal Nature, inflammatory mechanisms caused by the brain's immune system drive the progression of Alzheimer's disease."

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Globs of an inflammation protein beckon an Alzheimer's protein and cause it to accumulate in the brain, a study in mice finds. The results, described in the Dec. 21/28 Nature, add new details to the relationship between brain inflammation and Alzheimer's disease.

Researchers suspect that this inflammatory cycle is an early step in the disease, which raises the prospect of being able to prevent the buildup of amyloid-beta, the sticky protein found in brains of people with Alzheimer's disease.

"It is a provocative paper," says immunologist Marco Colonna of Washington University School of Medicine in St. Louis. Finding an inflammatory protein that can prompt A-beta to clump around it is "a big deal," he says.

Researchers led by Michael Heneka of the University of Bonn in Germany started by studying specks made of a protein called ASC that's produced as part of the inflammatory response. (A-beta itself is known to kick-start this inflammatory process.) Despite being called specks, these are large globs of protein that are created by and then ejected from brain immune cells called microglia when inflammation sets in. A-beta then accumulates around these ejected ASC specks in the space between cells, Haneke and colleagues now propose.

Splotchy brains

A-beta can directly latch on to ASC specks, experiments in lab dishes revealed. The two proteins were also caught in close contact in brain tissue taken from people with Alzheimer's disease. Researchers didn't see any ASC specks mingling with A-beta in the brains of people without the disease.

Mice engineered to produce lots of A-beta had telltale signs of its accumulation in their brains at 8 and 12 months of age, roughly comparable to middle age in people. But in mice that also lacked the ability to produce ASC specks, this A-beta brain load was much lighter, and these mice performed better on a memory test. Similar reductions in A-beta loads came when researchers used an antibody to prevent A-beta from sticking to ASC specks, results that suggest the specks are needed for A-beta to clump up.

The details show "a quite new and specific mechanism" that's worth exploring for potential treatments, says Richard Ransohoff, a neuroinflammation biologist at Third Rock Ventures, a venture capital firm in Boston.

To be effective as a treatment, an antibody like the one in the study that kept A-beta from sticking to ASC would need to be able to enter the brain and persist at high levels - a big challenge, Ransohoff says. Still, the results are promising, he says. "I like the data. I like the line of experimentation."

Many questions remain. The results are mainly from mice, and it's not clear whether ASC specks and A-beta have similar interactions in human brains. Nor is it obvious how to stop the A-beta from accumulating around the specks without affecting the immune system more generally.

What's more, the role of the microglia immune cells that release ASC specks is complex, Colonna says. In some cases, microglia serve as brain protectors by surrounding and sequestering sticky A-beta plaques in the brain ( SN: 11/30/13, p. 22). But the current results suggest that by releasing ASC specks, the same cells can also make A-beta accumulation worse. The dueling roles of the cells - protective in some cases and potentially harmful in others - make it challenging to figure out how to tweak their behavior therapeutically, Colonna says.

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Specks in the brain attract Alzheimer's plaque-forming protein

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Globs of an inflammation protein beckon an Alzheimer's protein and cause it to accumulate in the brain, a study in mice finds. The results, described in the Dec. 21/28 Nature, add new details to the relationship between brain inflammation and Alzheimer's disease.

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It's an alarming statistic. The Centers for Disease Control and Prevention (CDC) reports deaths from Alzheimer's disease surged 55% from 1999 to 2014.

So, what exactly are we to take from that, given that estimates of future Alzheimer's cases are also rising, since the aging population is growing at a fast pace?

The CDC lists several reasons for the sharp rise in deaths. First, the aging population is growing. The first Baby Boomers turn 70 years-old this year, and each year after another group of Boomers passes the 65 year-old mark, a milestone for the development of Alzheimer's.

People are also living longer, meaning they aren't dying from other diseases. Alzheimer's is a fatal form of dementia, and if someone lives long enough, their chance of developing it -- and dying from it -- increases.

Attributed to other causes

In recent years, doctors have done a better job of diagnosing Alzheimer's. In the past, it is possible people died from Alzheimer's but their deaths were attributed to other causes.

So it doesn't necessarily mean more people are developing the disease than they otherwise would, there are simply more people now who are at risk.

Dr. Anne Schuchat, CDC's acting director, says there's another statistic that should stand out. The number of people with Alzheimer's who died at home jumped from 14% to 25% over the same period. That means caregivers -- primarily a spouse or child -- is bearing a heavy burden.

Burden on caregivers

"As the number of older Americans with Alzheimer's disease rises, more family members are taking on the emotionally and physically challenging role of caregiver than ever before," Schuchat said. "These families need and deserve our support."

Christopher Taylor, Ph.D., lead author of the study, says caregiving becomes even more important in the latter stages of the disease.

"Caregivers and patients can benefit from programs that include education about Alzheimer's disease, how to take care of themselves and their loved one, and case management to lessen the burden of care," he said. "Supportive interventions can lessen the burden for caregivers and improve the quality of care for people with Alzheimer's disease."

Early intervention and diagnosis may also slow development of the disease. People 65 and over should be aware of symptoms such as memory loss, difficulties with problem solving, or misplacing objects. The CDC says an early diagnosis can allow patients and their families to better prepare for medical and caregiving needs at all stages of the disease.

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Why Alzheimer's disease deaths are sharply rising

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It's an alarming statistic. The Centers for Disease Control and Prevention (CDC) reports deaths from Alzheimer's disease surged 55% from 1999 to 2014. So, what exactly are we to take from that, given that estimates of future Alzheimer's cases are also rising, since the aging population is growing at a fast pace?

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Improved understanding of progression rates in Parkinson's and Alzheimer's disease, and schizophrenia - ANSTO

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ANSTO researchers have conducted research into an improved data analysis method for estimating changes in physiological parameters over time. This work has made it possible for certain parameters to be applied to a broader range of experimental conditions and disease states than previously possible, and is enabling researchers to better understand the extent to which changes in these parameters are due to a disease's progression or are a response to treatments.

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Predicting Alzheimer's disease by classifying 3D-Brain MRI images using SVM and other well-defined classifiers

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Predicting Alzheimer's disease by classifying 3D-Brain MRI images using SVM and other well-defined classifiers

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A prospective cohort study

Bushra Imtiaz, MD, MPH, Marjo Tuppurainen, MD, PhD, Toni Rikkonen, PhD, Miia Kivipelto, MD, PhD, Hilkka Soininen, MD, PhD, Heikki Kröger, MD, PhD, and Anna-Maija Tolppanen, PhD

Abstract

Objective:

To explore the association between postmenopausal hormone therapy (HT) and Alzheimer disease (AD).

Methods:

Twenty-year follow-up data from the Kuopio Osteoporosis Risk Factor and Prevention study cohort were used. Self-administered questionnaires were sent to all women aged 47-56 years, residing in Kuopio Province starting in 1989 until 2009, every 5th year. Register-based information on HT prescriptions was available since 1995. Probable AD cases, based on DSM-IV and National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria, were identified from the special reimbursement register (1999-2009). The study population included 8,195 women (227 cases of incident AD).

Results:

Postmenopausal estrogen use was not associated with AD risk in register-based or self-reported data (hazard ratio/95% confidence interval 0.92/0.68-1.2, 0.99/0.75-1.3, respectively). Long-term self-reported postmenopausal HT was associated with reduced AD risk (0.53/0.31-0.91). Similar results were obtained with any dementia diagnosis in the hospital discharge register as an outcome.

Conclusions:

Our results do not provide strong evidence for a protective association between postmenopausal HT use and AD or dementia, although we observed a reduced AD risk among those with long-term self-reported HT use.

Alzheimer disease (AD), the most common form of dementia, accounts for 60%-80% of cases. Women have AD more often than men either due to their increased life expectancy or decline in sex steroid hormone levels around menopause, although some small studies have not detected this sex difference. Neuroprotective effects of estrogen have been observed in experimental animals, but clinical trials on postmenopausal hormone therapy (HT) use have not been successful, including the largest clinical trial to date, the Women's Health Initiative Memory Study (WHIMS). Observational studies support use of HT against AD if initiated around menopause in some but not all studies. Similarly, register-based studies have yielded conflicting results. Results from the Leisure World cohort revealed that the reduced risk of AD among HT users was a function of dose and duration.

The aim of our study is to investigate the association of self-reported and register-recorded postmenopausal HT use with AD in a longitudinal prospective cohort, while taking into account various socioeconomic and lifestyle-related AD risk factors.

METHODS

Study population.

The present study is based on the 20-year follow-up of the population of the Kuopio Osteoporosis Risk Factor and Prevention study cohort. A self-administered baseline postal questionnaire was sent to all women aged 47-56 years who were residents of Kuopio Province, Eastern Finland (n = 14,220), in February 1989. A total of 13,100 (92.1%) women responded. The reasons for nonresponse were lack of address or residence not detected (n = 119) and death (n = 4). In addition, 947 women did not respond for other reasons and 50 returned a blank form. The 5-year follow-up in 1994, 10-year follow-up in 1999, 15-year follow-up in 2004, and 20-year follow-up in 2009 was mailed to the 13,100, 12,562, 12,075, and 11,420 women, respectively. A total of 11,954 (91.2%), 11,538 (91.8%), 10,926 (90.4%), and 8,195 (71.8%) women responded to the 5-, 10-, 15-, and 20-year follow-ups, respectively. The questionnaires were sent to women who had responded to the baseline inquiry, were alive, and had a valid postal address at that time.

The baseline questionnaire covered demographics, lifestyle, medical issues, and other characteristics such as age, height, weight, smoking, alcohol consumption, health disorders diagnosed by a physician, reproductive history, type and duration of HT use, operations, occupation, and physical activity. These questionnaires were repeated in the follow-up inquiries.

The present study included those 8,195 women who had complete data on confounders and self-reported exposure. Outcome data and register-based exposure data were available for all participants.

Outcomes.

The main outcome of our study was clinically verified AD diagnosis. These diagnoses from 1999-2009 were identified from the Finnish special reimbursement register maintained by the Social Insurance Institution (SII). The register contains information on the reimbursed drugs used for chronic illnesses such as AD. The Finnish special reimbursement register possesses high validity and positive predictive value for AD diagnosis. The Finnish Current Care Guideline recommends that all persons with AD are treated with antidementia drugs unless there is a specific contraindication (such as gastric ulcer/intestinal tract operation <6 months ago or severe asthma or chronic obstructive pulmonary disease for acetylcholinesterase inhibitors). In Finland, the diagnosis of probable AD is based on DSM-IV criteria for AD and National Institute of Neurologic and Communicative Disorders and Stroke-Alzheimer Disease and Related Disorders Association. The main diagnostic criteria were progressive decline in memory and cognition and exclusion of other reasons. Diagnosis of AD was supported by abnormal MRI or CSF biomarker findings typical for AD.

To be eligible for reimbursed AD medication (acetylcholinesterase inhibitors or memantine), a medical statement of a clinically verified AD diagnosis needs to be submitted to SII. Thus, case identification is carried out in clinics but is reconfirmed by SII. Summary of anamnestic information from the patients and family, as well as findings, e.g., MRI/CT, laboratory tests, and Consortium to Establish a Registry for Alzheimer's Disease, are submitted to the SII, where a geriatrician/neurologist systematically evaluates the diagnostic evidence for each AD case and confirms whether the prespecified criteria are met excluding possible alternative diagnoses for memory impairment such as severe depression, metabolic disturbances, and other forms of dementia such as vascular dementia without AD-like symptoms.

We also performed sensitivity analyses with dementia as an outcome. These data were extracted from the National Hospital Discharge register using the following ICD-10 codes: F00-F03 (F00, dementia in Alzheimer disease; F01, vascular dementia; F02, dementia in other diseases classified elsewhere; F03, unspecified dementia) and G30 (Alzheimer disease, early/late onset). This register includes all inpatient admissions. Diagnosis codes for each admission are recorded by attending physician. All Finnish citizens/long-term residents are covered by tax-supported public health service.

Use of HT.

Self-reported HT use was recorded as lifetime use in years (and indication of use) at the baseline inquiry in 1989. In all follow-up questionnaires, numbers of months per year of estrogen use were reported and the duration of self-reported estrogen use was calculated on basis of these questionnaires. Current medication prescribed by a physician, duration and purpose of use, and name of tablets used were asked in all inquiries. To exclude the possibility of recall bias in the self-reported questionnaires, we accessed the prescription register data to ascertain HT use. Vaginal products were excluded. HT was defined from the registry as those preparations having systemic estrogenic properties belonging to the following codes of ATC classification: G03C (estrogens), G03F (estrogen and progesterone) excluding oral contraceptives. Self-reported use of estrogen was categorized into postmenopausal HT based on use after the onset of menopause.

Covariates.

Baseline menopause status was categorized to 5 categories: (1) menstruating, no HT; (2) true menopause; (3) menstruating, HT 1-30 years; (4) hysterectomy and HT, no oophorectomy; (5) unclear (hysterectomy, no data on oophorectomy or HT use). When categorizing the self-reported HT to postmenopausal use, a woman was considered postmenopausal if ≥12 months had passed since her natural menstrual cycle, if she had undergone surgical menopause through bilateral oophorectomy with or without hysterectomy, or if the time since menopause and the history of HT use could be clarified from the follow-up questionnaire. For the present study, we used data on natural menopause (i.e., date of last menstruation, collected through self-reports at baseline and 5-year follow-up assessments). Over 90% of women were postmenopausal at the second follow-up. Missing information was collected from participants by telephone. Body mass index (BMI) was calculated as the ratio of weight in kilograms to height in meters squared and was based on self-reporting.

Physical activity was inquired through self-reported data in 3 ways at baseline and in all follow-up surveys as follows: leisure time physical activity as well as asking about how physically demanding work was in the last year; ambulatory status as capability and extent of movement, need of aids in movement, and history of joint degeneration; and amount of physical activity, including winter and summer activities, amount of current regular physical activity, and its duration (hours per week). Of these 3 categories, the amount of physical activity was the most predictive of AD and thus was included in the analyses.

Data on education were obtained in self-reported data only from a subcohort undergoing bone marrow density measurement. Education was categorized into 4 groups: compulsory schooling, compulsory schooling + maximum 2 years of supplementary school or occupational training, high school + minimum 2 years of supplementary school or professional training, and university degree. To assess whether the adjustment for education affected the results, we conducted a separate sensitivity analyses in the subcohort for whom we had education data (n = 2,383). History of ever/never smoking was asked in all self-reported questionnaires along with regularity of smoking, number of years of smoking, and number of cigarettes smoked per day.

Data on self-reported occupation were gathered under 9 different categories (managers; professionals; technicians and associate professionals; clerical support workers; service and sales workers; skilled agricultural, fish, and forestry; crafts and related trades workers; plant and machine operators; other occupation; and housewife/pensioner/caregiver/no occupation) but converted into a dichotomous variable (employed and unemployed) for the analyses. Alcohol consumption was inquired in questionnaires as the amount of alcohol beverages consumed during a 1-month period and converted into grams of alcohol intake per month.

At baseline, women were asked in questionnaire about the age at menarche, age at menopause, number of pregnancies, number of live births, and abortions. Abortion was inquired in questionnaire as "Number of times interrupting pregnancies due to abortion/miscarriage." A history of any gynecologic operations (caesarian sections and sterilizations) was also obtained, as well as what, if anything, was removed in these operations (uterus, ovary, part of both, cervix, or other parts of genitals).

Standard protocol approvals, registrations, and patient consents.

The study design was approved by the Ethics Committee of Kuopio University Hospital and written informed consent was obtained from all participants.

Statistical analysis.

Statistical analysis was carried out with Stata 12.0 (Stata Corp LP, College Station, TX). The characteristics of women with respect to AD incidence were compared using χ ² test for categorical variables and t test for continuous variables. Correlation between confounders and exposure were investigated with the Spearman correlation coefficient. As expected, hysterectomy and oophorectomy were strongly correlated ( r = 0.561) and were thus combined into one variable (surgery). There were no other indications of collinearity ( r < 0.4).

Cox proportional hazard models were used to evaluate the association between HT use and AD incidence. Separate analyses were carried out for different durations of use and different types of HT. Hazard ratios and 95% confidence intervals were estimated with age-adjusted model and model adjusted for age, BMI, alcohol, smoking, physical activity, occupation status, number of births, menopause status, any cancer, and surgery. Since the education data were available for only a subset of participants, sensitivity analyses were conducted in this group separately. Association between HT and dementia was studied similarly.

We studied whether the association between HT and AD was different among women who had undergone oophorectomy or hysterectomy by assessing the interaction of hysterectomy or oophorectomy and self-reported and register-recorded HT use. There was no evidence for effect modification by these surgeries (All p values for interaction were >0.6) and thus stratified analyses were not performed.

RESULTS

Average age at AD diagnosis was 72.3 years (range 59.2-78.6 years). Women who later developed AD were significantly older than women without AD. They also reported less physical activity and were more likely to be unemployed than women who were not diagnosed with AD during the follow-up. Number of childbirths, abortions, and pregnancies was similar between groups, but women who developed AD were more likely to be menopausal at baseline than those who were not diagnosed with AD. Register-reported HT or oophorectomy/hysterectomy was not associated with AD in these univariable analyses (table e-1 at Neurology.org).

shows the relative risk of AD according to both register-based and self-reported HT use (yes/no). Neither register-based nor self-reported HT use was associated with AD risk. The results were similar in the sensitivity analyses conducted among those with data on education (n = 2,383; tables e-2 and e-3), i.e., no association was detected between HT use (any HT, estrogen, or combination therapy; either register-based or self-reported) and AD.

Table 1

HT use when categorized according to duration register-based HT use was not associated with AD (). However, when self-reported data were used, those with longest self-reported HT use >10 years had lower risk of AD in comparison to nonusers () also after adjusting for lifestyle and socioeconomic confounders and variables related to estrogen status. Sensitivity analyses with any dementia as an outcome produced similar results to those shown in , although the association between >10 years HT use and AD was attenuated and its confidence also included 1 in the sensitivity analyses (tables e-4 to e-6).

Table 2

Table 3

DISCUSSION

The findings from our large prospective cohort study do not provide strong evidence for an association between postmenopausal HT use and AD or dementia, although a protective association between long-term (>10 years) self-reported use of HT and AD was observed. This finding indirectly favors the effectiveness of HT if started in the early postmenopausal period (critical window theory). Another explanation for this association can be reverse causation, i.e., AD (or more precisely, its preclinical symptoms) affecting the exposure to HT (or reporting of HT duration in the self-reported data), or a chance finding. The association with longer duration of HT use was only found in self-reported postmenopausal estrogen use, not for register-based HT use after 1995, and the association was less evident when all dementia diagnoses instead of clinically verified AD diagnosis were used as an outcome. One explanation for the different results with self-reported and register-based exposure could be different time period as register data were not available before 1995, which is 7 years after the baseline inquiry. Thus, the register-based data after 1995 would misclassify those who discontinued HT use before 1995 as nonusers. It is unlikely that this misclassification was differential in those who later developed AD and those who did not. Therefore it would lead to an underestimation of the association between HT use and AD with the register-based data after 1995. An alternative explanation is recall bias, but this is unlikely as previous validation study from the same cohort showed that a postal inquiry is a reliable method of recording long-term HT use in Finnish postmenopausal women.

Our result is in line with the extended follow-up of the Cache County Study, which detected a reduced AD risk if HT was started within 5 years of menopause and continued for more than 10 years. The largest clinical trial on HT-all cause dementia association, i.e., WHIMS, assessed cognitive performance of women >65 years old, assigned to conjugated equine estrogen (CEE; unopposed therapy) vs placebo or continuous CEE + medroxyprogesterone acetate (CEE + MPA; opposed therapy) vs placebo. The use of opposed HT increased the dementia risk, but this did not occur with unopposed HT. In the WHIMS trial, women were randomized to receive opposed therapy as CEE combined with MPA. In Finland, estradiol in combination with norethisterone or levonorgestrel (not MPA) is used among women with intact uterus and only estradiol is used mainly among women undergoing hysterectomy. The difference between these 2 studies may be attributable to the differences in the effects exerted by the different estrogen preparations. In addition, the women in our cohort were around 10 years younger than women in the WHI trial, and the main outcome in our study was AD, while it was all-cause dementia in WHIMS.

One cohort study reported that an early initiation of HT around menopause was protective against AD. Similar findings were reported from the Multi-Institutional Research in Alzheimer Genetic Epidemiology study, where HT use in the youngest age tertiles (50-63 years) protected against AD in comparison to those in the older age tertiles.

The lack of association in our cohort between any HT use (all users of HT, not taking into account either the time of initiation or the duration of therapy) and AD/dementia is consistent with previous observational studies where HT was categorized as former or current use and lifetime estrogen exposure was taken into account. Postmenopausal estrogen therapy was not protective against AD in 2 of the case-control studies. This discrepancy in observational studies is explained by differences in outcome measurement, number of observations, duration, type, and the time of initiation of HT use.

The strengths of our study include its large sample size, long follow-up time, relatively homogenous population, clinically verified AD cases, prescription-based validation of HT use, and control for various important comorbidities. Confounders and exposures were measured with the same questions during the follow-up. In addition, the positive predictive value of AD diagnosis in the Special Reimbursement Register is high. However, it is likely that this register does not capture all AD cases, or persons with other forms of dementia. Therefore we conducted sensitivity analysis with any dementia as an outcome. Despite these strengths, our study has some limitations: first, information was collected by self-reported postal inquiries, which may be subject to recall bias; second, the effect of healthy user bias among the long-term users cannot be overlooked; third, register data on HT use and AD diagnosis were available from 1995 to 1999 onwards, respectively; fourth, we cannot eliminate the chance of a survival bias contributing to the protective association observed among the longest HT users; fifth, we were not able to control the results for genetic predisposition to AD ( APOE status and familial AD). However, it is unlikely that these genetic factors would influence start of HT use and thus it is unlikely that the results are confounded by genetic background.

Misclassification of outcome (i.e., undiagnosed AD or dementia cases) is possible and this would dilute our estimates towards the null. However, the proportion of misclassified persons is likely to be small. Due to our outcome data source in sensitivity analyses for dementia, we captured only those persons with dementia who required inpatient admission (due to dementia or other disease/accident). The diagnostic process for dementia often begins in an outpatient setting, but these settings were not included in the hospital discharge register. Therefore, those persons with dementia who did not have any hospital admissions or antidementia medications were misclassified.

Our study examined a homogenous population (residents of Kuopio Province, all accessed via the national social security system), thus decreasing the chances of selection bias or confounding by socioeconomic-related factors. Some previous observational studies carried out in sociodemographic homogenous populations have observed decreased risk of AD among HT users. Estrogen replacement therapy was protective against AD in these studies and sociodemographic heterogeneity may account for the contrasting results obtained in the 2 observational studies.

Our results based on 2 decades of follow-up of a large homogenous population did not provide strong evidence for a protective association between postmenopausal HT use and AD or dementia.

ACKNOWLEDGMENT

The authors thank Seija Oinonen for technical help regarding data extraction.

GLOSSARY

AUTHOR CONTRIBUTIONS

Dr. Imtiaz: planned the research project, drafted the first version of the manuscript, performed statistical analyses, acts as guarantor, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions. Dr. Tuppurainen: planned the research project, participated in data collection, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions. Dr. Rikkonen: participated in data analysis, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions. Prof. Kivipelto: accepted the submitted version of the manuscript and made important intellectual contribution to draft versions. Prof. Soininen: planned the research project, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions. Prof. Kröger: planned the research project, participated in data collection, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions. Dr. Tolppanen: planned the research project, supervised data analyses and the research project, accepted the submitted version of the manuscript, and made important intellectual contribution to draft versions.

STUDY FUNDING

Supported by Kuopio Osteoporosis Risk Factor and Prevention (OSTPRE) grant 250707. A.M.T. acknowledges funding from European Regional Development Fund (regional council of Pohjois Savo), M.K. is a recipient of Academy of Finland and Center for Innovative Medicine (CIMED), and H.S. received funding from the University of Eastern Finland for UEF Brain. B.I. acknowledges The Finnish Cultural Foundation (central fund) and funding by Doctoral Program of Molecular Medicine, University of Eastern Finland.

DISCLOSURE

The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.

REFERENCES

1. Alzheimer's Association. 2016 Alzheimer's disease facts and figures. Alzheimers Dement 2016;12.

7. Brinton RD, Chen S, Montoya M, Hsieh D, Minaya J. The estrogen replacement therapy of the Women's Health Initiative promotes the cellular mechanisms of memory and neuronal survival in neurons vulnerable to Alzheimer's disease. Maturitas 2000;34(suppl 2):S35-S52.

26. Quick Reference to the Diagnostic Criteria From DSM-IV-TR. Washington, DC:American Psychiatric Association; 2000.

# data[].attributes.attachment_link.title
Postmenopausal hormone therapy and Alzheimer disease: A prospective cohort study

# data[].attributes.attachment_link.description
A prospective cohort study Bushra Imtiaz, MD, MPH, Marjo Tuppurainen, MD, PhD, Toni Rikkonen, PhD, Miia Kivipelto, MD, PhD, Hilkka Soininen, MD, PhD, Heikki Kröger, MD, PhD, and Anna-Maija Tolppanen, PhD To explore the association between postmenopausal hormone therapy (HT) and Alzheimer disease (AD).

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Abstract

Keywords: Traumatic brain injury, Posttraumatic stress disorder, Alzheimer's disease, Vietnam veterans, Mild cognitive impairment

1. Introduction

Alzheimer's disease (AD) is characterized by the presence of amyloid plaques and tau fibrils, which are associated with synaptic loss and neurodegeneration, leading to cognitive impairments and dementia. After age, family history, and apolipoprotein E ( APOE) ε4 risk allele [1], traumatic brain injury (TBI) has been reported as a risk factor in many [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33] but not all [13] epidemiological studies (reviewed in [34], [35], [36]). Some studies have suggested that a history of TBI is associated with earlier onset of AD [3], [6], [13], [18], [20], [34], [35], [37]. Others, but not all, have shown an interaction of TBI with the APOE ε4 allele [5], [6], [15], [17], [38], [39], [40], [41], [42], [43], [44], [45], [46]. After TBI, young subjects appear to have had Aβ pathology in postmortem brain tissue [47], [48]. A comprehensive consensus analysis of the literature concluded that there was some evidence for a relationship between TBI in males and future development of AD (odds ratio 2.29 [1.47-3.58]) [20]. One study [33], which showed a significantly increased risk of developing AD after TBI, used information provided by the US Department of Defense to identify and prospectively enroll subjects with nonpenetrating head injury suffered during WWII and the Korean War, and non-head-injured controls. Recently, one study from the Mayo Clinic Study of Aging [49] suggested that MCI, but not cognitively normal subjects, who reported a history of concussion had higher brain Aβ levels, measured with Aβ positron emission tomography (PET) scans, than noninjured MCI participants. With the exception of one publication [50], studies of the effects of TBI on AD have used "self-report" information to determine a history of concussion; few studies have used imaging and cerebrospinal fluid biomarkers to investigate the relationship of TBI to AD.

Posttraumatic stress disorder (PTSD) is an anxiety disorder following exposure to traumatic stress [51]. The prevalence of combat-related PTSD in US military Veterans since the Vietnam War ranges from 10% to 15% [52], [53]. PTSD is associated with worse cognitive functioning [50], [54], [55], [56], [57], [58], [59], [60], [61], [62]. Furthermore, PTSD is associated with alterations in the hippocampus [63], [64], [65], [66], [67], anterior cingulate [65], and prefrontal structures [63], [64], [65], [66], [67], [68], [69], whereas improvement of symptoms is associated with less-progressive atrophy [67]. The relationship of PTSD to impaired cognitive function and hippocampal abnormalities suggests that PTSD could be a risk factor for the development of AD. A study of the national Veterans Administration (VA) clinical database showed that Veterans with PTSD are twice as likely to develop a dementia diagnosis compared to Veterans without PTSD, even when controlling for known risk factors for dementia [70]. Aside from magnetic resonance imaging (MRI) studies, to our knowledge, there are no reports of the use of Aβ PET scans or other biomarkers to examine whether the mechanism accounting for the higher risk for dementia in PTSD is related to AD pathology.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a large, multisite study, aimed at validating biomarkers for AD clinical trials. ADNI has enrolled over 1500 subjects at 57 sites in the United States and Canada and followed them longitudinally with clinical/cognitive testing, genetic analysis, MRI, lumbar puncture for cerebrospinal fluid (CSF) analysis, ¹⁸F-fluorodeoxyglucose PET, Aβ PET, and most recently tau-PET (reviewed in [71]). To investigate the relationship of a past history of TBI and PTSD on the development of AD, the Department of Defense funded three proposals: (1) Effects of Traumatic Brain Injury (TBI) and Posttraumatic Stress Disorder on Alzheimer's Disease in Veterans Using Imaging and Biomarkers in the AD Neuroimaging Initiative; (2) Effects of Traumatic Brain Injury and Posttraumatic Stress Disorder on Alzheimer's Disease in Veterans with Mild Cognitive Impairment Using the Alzheimer's Disease Neuroimaging Initiative; and (3) Effects of Traumatic Brain Injury and Posttraumatic Stress Disorder and Alzheimer's Disease on Brain Tau in Vietnam Veterans Using ADNI. These studies are collectively termed "DOD ADNI," and aim to enroll approximately 400 elderly Veterans who served in Vietnam.

The initial DOD ADNI grant enrolled Vietnam Veterans with PTSD and/or TBI, as well as controls with service-connected disorders not related to PTSD or TBI who met criteria for normal cognition. The second grant expanded the original study to include subjects who also met criteria for MCI. The study now includes cohorts of Vietnam Veterans, both with and without MCI, who have histories of TBI, PTSD, and both TBI and PTSD, as well as controls without PTSD/TBI. Potential subjects are initially contacted by mail, prescreened for eligibility by telephone and those meeting criteria for one of the cohorts are referred for clinical examination, cognitive tests, Aβ PET using ¹⁸F-labeled florbetapir, MRI (structural, diffusion tensor, and resting state functional), lumbar puncture for CSF markers of tau, phosphorylated tau (p-tau ₁₈₁), β-amyloid (Aβ42), and blood collection for genetic analysis. The clinical/cognitive battery and MRI is repeated after 1 year, and tau-PET scans are obtained at baseline and after 1 year. Results from the CSF assays and tau-PET imaging are pending and will not be reported in this article.

This interim report uses baseline data to determine the extent to which a prior history of TBI and/or documented past history and present diagnosis of PTSD increase the risk of developing AD. Our primary a priori hypothesis is that Vietnam Veterans with a history of TBI or presence of ongoing PTSD will have lower cognitive functioning and increased prevalence of brain AD pathology (measured by Aβ florbetapir PET and medial temporal lobe atrophy) after accounting for effects of age and presence of the APOE ε4 allele.

2. Methods

2.1. Identification of potential study subjects

For this study, we used an operational definition of TBI as head injury with loss of consciousness for more than 5 minutes, and/or having amnesia, and/or being dazed and confused for more than 24 hours. Using military and VA Compensation and Pension records, as well as VA Health records, and/or response to advertisements, Vietnam Veterans with a service connection related to a possible traumatic head injury and/or a history of at least one moderate/severe TBI and/or evidence of ongoing PTSD, and demographically comparable Veteran controls without PTSD/TBI were identified. Because TBI was not a common diagnostic code during the Vietnam War, the study requested a sample of subjects from the Veteran Benefits Administration who were service-connected for several diagnostic codes that might be related to a traumatic brain injury (traumatic brain disease, posttrauma headache, acute posttrauma headache, chronic posttrauma headache, post-concussion syndrome, brain hemorrhage, limited motion of the jaw, and other head-related injuries). We also obtained separate samples of subjects who are service-connected for PTSD as well as a sample of controls who were service-connected for something other than PTSD or TBI. Study invitation letters, brochures, and response postcards were mailed to Veterans who met these initial broad criteria and who lived within 150 miles of the closest ADNI clinic.

2.2. Initial telephone prescreening recruitment calls

To include all subjects who may have a history of a TBI and to confirm whether or not the TBI-related diagnostic codes were related to a head injury, all subjects were contacted by telephone, and verbal consent was obtained for the administration of screening questions which determined eligibility criteria for current PTSD symptoms and history of a TBI. The Ohio State University TBI Identification Method-Interview Form [72] was used to ask about head injuries at three separate times in a subject's life: before, during, and after Vietnam. This ensured we included TBIs that may have occurred before or after a subject's military service. In addition, a safety assessment ruled out subjects who were not safe to participate in the study procedures. The purpose of the initial telephone prescreening recruitment call was both to (1) rule out exclusions such as dementia, history of psychosis or bipolar affective disorder, history of schizophrenia ( Diagnostic and Statistical Manual of Mental Disorders, 4th edition criteria), history of alcohol or substance abuse/dependence within the past 5 years, MRI-related exclusions (metal in the body, pacemakers), contraindications for lumbar puncture, PET scan, or other procedures in this study and (2) assess placement in study cohorts. During this initial screen, MCI was assessed using an adapted version of the AD8 (70, 71) and the Telephone Interview for Cognitive Status, as the latter contains a 10-word list recall which combined with the AD8 can help to identify cognitive impairment [73], [74]. Subjects meeting inclusion criteria were then mailed a written consent form for the telephone psychiatric assessment (clinical interview) portion of the study and audio recording, with a stamped addressed return envelope and the following self-report questionnaires: (1) MRI safety, (2) Medical history, (3) Current medications, (4) Symptom Check List 90 (revised) for general psychopathology [75], (5) Pittsburgh Sleep Quality [76], (6) Smoking/Life Time Smoking, (6) SF-12 Health Survey [77], and (7) Combat Exposure Scale [78].

After documented consent was received, all self-report questionnaires described previously were reviewed as well as the subjects' VA medical records to ensure that there were no medical problems or exclusionary medications that the subject failed to report and to ensure that proper cohort assignment had been determined. VA medical records were reviewed for any documentary evidence of a TBI at anytime in a subject's life regardless of whether or not a subject reported a TBI during the administration of the Ohio State University TBI Identification Method-Interview Form. If the medical records specifically mentioned a TBI incident or a service connection related to a TBI (as indicated by the diagnostic codes discussed previously), or if a subject self-reported a TBI (that met the operational criteria of TBI discussed previously) during anytime in the subject's life, this subject was not placed in the control group.

2.3. SCID CAPS evaluation by telephone

All eligible subjects were next referred to the telephone clinical evaluation which used the Structured Clinical Interview 1 of the Diagnostic and Statistical Manual of Mental Disorders, Version IV, (Axis 1)-Text Revision (SCID) and the Clinician Administered PTSD Scale for DSM-IV (CAPS) [79] to assess current and lifetime PTSD and to rule out psychosis and/or drug and alcohol issues. SCID CAPS, as well as the Life Stressor Checklist [80] and the Addiction Severity Index Lite [81], was conducted by telephone by the PTSD Core at the San Francisco Veterans Administration Medical Center.

2.4. Assignment of subjects to cohorts

After completing the SCID CAPS, eligible subjects were placed into one of eight cohorts, four with no MCI and four who met initial criteria for MCI, as described in the following:

* TBI only: Subjects with no service connection for PTSD, no history of lifetime, and/or current PTSD on SCID CAPS (scores of <30 for each) but with a service connection for a TBI-related diagnostic code, medical documentation of a TBI-related incident, and/or a self-report of a TBI which met the operational definition of TBI described previously.

* PTSD only: Subjects who were service-connected for PTSD and who scored ≥40 for both lifetime and current PTSD, with no self-report history of TBI, no diagnostic service connection related to TBI, and no medical documentation of TBI.

* Both TBI + PTSD: Subjects who scored ≥30 for either lifetime and/or current PTSD and had a service connection related to TBI, medical documented evidence of a TBI-related incident, and/or a self-report history of TBI meeting the operational criteria of TBI described previously.

* Controls: Subjects with no service connection for PTSD, no history of lifetime, and/or current PTSD on SCID CAPS (scores of <30 for each), and no service connection for TBI-related diagnostic codes, no medical documentation of a TBI-related incident, and no self-report of a TBI that met the operational definition of TBI.

Eligible subjects were next referred to one of the 19 ADNI Clinic sites to sign a clinic consent and complete study procedures.

2.5. Clinical evaluation, neuropsychological testing, MRI, and Aβ florbetapir PET scans

After the clinical telephone interview, subjects were referred to the closest ADNI site for in-person studies using the identical methods used by ADNI. These include clinical evaluation, neuropsychological testing, lumbar puncture (results not available at this time), genetic sampling for the APOE ε4 allele, structural MRI at 3T, and Aβ florbetapir PET scans. These methods have been widely reported [82], [83], [84], [85], [86]. Longitudinal data and tau-PET scan results will be reported at a later time.

2.6. Power analysis

Our original study was designed to have 80% power to detect a minimum difference in means of 0.55 standard deviations, assuming 65 participants in each group, an alpha of 0.025, and a two-sided test. In this interim report, we have not yet achieved our desired sample size in each group, particularly in the TBI and TBI + PTSD groups. For comparison of the TBI group ( n = 22) with the no TBI/PTSD group ( n = 63), we have 80% power to detect a difference as small as 0.78 standard deviations (0.68 standard deviations for the TBI + PTSD vs. no TBI/PTSD group). Minimum detectable differences are larger for the imaging outcomes, where sample sizes are even smaller.

2.7. Statistical analysis

Means and standard deviations were computed for all continuous variables of interest (age, education, neuropsychological testing, MRI volumetrics, and florbetapir standardized uptake value ratio [SUVR]), whereas percentages were calculated for categorical variables (gender, race/ethnicity, diagnosis, APOE ε4 status). Analysis of variance or Fisher's exact test was used to compare groups (PTSD, TBI, both, neither) on demographic and clinical characteristics. Linear regression was used to compare groups on most neuropsychological testing scores and MRI volumetrics. Volume of white-matter hyperintensities was transformed with natural log to meet the assumptions of the models. Poisson regression [87] was used to compare groups on the clinical dementia rating (CDR) Sum of Boxes because this outcome did not meet the assumptions of linear regression. Mini-Mental State Examination (MMSE) was rescaled as the number of errors (30 MMSE) and analyzed with a negative binomial regression due to overdispersion. Finally, logistic regression was used to compare amyloid positivity based on Aβ florbetapir cortical SUVR across the groups. All models were adjusted for age, education, and APOE ε4 status by including these variables in the models. Primary comparisons of interest for all analyses were between the patient groups (PTSD, TBI, both) and the control group (no PTSD or TBI). All analyses were conducted using SAS software version 9.4 [88] with a P-value <.05 considered statistically significant.

3. Results

3.1. Description of the recruitment assessment process

The number of subjects contacted by mailing brochures, the initial telephone screening effort, including number of subjects called and screened, the numbers of consents mailed and SCID evaluations by telephone, and finally the number of completed baseline clinic visits and 12-month follow-up visits are outlined in .

3.2. Brain structure measured by MRI

describes the brain regional volumes and volume of white-matter hyperintensities across the groups. There were no significant differences between the groups in models adjusted for age, education, and APOE ε4 allele status except in the superior parietal region ( P = .046), which had a slightly lower volume in the TBI + PTSD group than in the control group ( P = .04). A further analysis that considered a measure of PTSD (CAPS) rather than the specific exposure groups found no association between level of PTSD and hippocampal volume ( P > .7) or superior parietal volume ( P > .3) for either the current CAPS or lifetime CAPS, in a model that included age, education, and APOE ε4 allele status.

3.3. β amyloid florbetapir positron emission tomography

and illustrate the distribution of Aβ florbetapir cortical SUVR across the groups. When categorized according to amyloid positivity using a previously validated cutoff of 1.11 [89], there was a significant difference by group ( P = .04) in a model adjusted for age, education, and APOE ε4 allele status, with the PTSD group having significantly lower odds of being amyloid positive (odds ratio: 0.21; 95% CI: 0.05-0.93; P = .04) than the controls. The proportion of controls in this study classified as amyloid positive was comparable to previous ADNI studies (data not shown).

4. Discussion

The major findings of this project are as follows: (1) worse cognitive functioning as measured by the CDR Sum of Boxes in the PTSD and both TBI + PTSD groups relative to the controls; (2) a trend for worse global cognitive functioning (ADAS-Cog, MMSE) in the PTSD group relative to the controls; (3) slightly lower superior parietal volume in the group with both TBI + PTSD relative to controls; (4) lower odds of amyloid positivity based on cortical amyloid SUVR in the PTSD group relative to the controls; and (5) no evidence for increased brain amyloid associated with TBI and no evidence for medial temporal lobe atrophy in those with PTSD and/or TBI relative to the controls. Taken together, these results do not support the hypothesis that prior TBI or PTSD is associated with increased brain amyloid. Furthermore, the worse cognitive functioning in the PTSD and TBI + PTSD groups is not associated with increased brain amyloid. Overall, this interim analysis of an ongoing study does not support the view that TBI or PTSD is associated with increased development of AD.

Our first finding of worse cognitive functioning in the PTSD group confirms previous reports [90], [91], [92], [93], [94]. Furthermore, at least one previous study indicates that PTSD is associated with an increased incidence of dementia [95]. However, there are no autopsy reports demonstrating increased AD pathology in Veterans with PTSD. Moreover, levels of white-matter hyperintensities did not differ among groups suggesting that the worsening cognitive function in the PTSD group is not explained by cerebrovascular disease. Therefore, the cause of cognitive decline or dementia in Veterans with PTSD is not known. The interim results of our ongoing study do not show increased brain amyloid in the PTSD group compared to controls. In fact, there is a trend for reduced brain amyloid in the PTSD group. Although these results are preliminary, they suggest that the cognitive impairment and dementia associated with PTSD may not be due to AD pathology.

Hippocampal atrophy has been associated with PTSD in some studies [66], [96], [97], [98], but not others [99], [100], [101], [102]. Hippocampal atrophy is typically found in AD dementia but is not specific for this condition [103]. Therefore, our failure to detect hippocampal atrophy in the PTSD or TBI + PTSD group in this study further suggests that the cognitive impairments in the PTSD subjects are not due to AD pathology.

Thus far, our study shows no evidence for increased brain amyloid load in subjects with prior history of TBI or TBI + PTSD in contrast with previous reports of TBI as a risk factor for AD. In contrast to most of these reports which used "self-reported" TBI, we identified subjects from the VA records who receive VA compensation for diagnostic codes that might be related to a traumatic brain injury as well as by self-report of TBI before, during, and after Vietnam. In addition, there are no previous studies using Aβ florbetapir PET to determine brain amyloid load, or MRI to detect hippocampal atrophy in elders with a past history of TBI. One study reported greater amyloid deposition in MCI subjects measured by amyloid PET using Pittsburgh compound B but head trauma was again self-reported [49]. Although AD is considered an amyloid-mediated tauopathy, and we have yet to analyze CSF tau levels or tau-PET imaging results, our findings thus far lead us to conclude that we have not found evidence of a connection between past history of TBI and development of amyloid pathology characteristic of AD. The present study suggests that TBI may be associated with cognitive decline unrelated to AD and is, in this regard, consistent with a report [104] instead showing an association of TBI with an increased risk of Parkinson's disease.

5. Limitations of the study

We wish to emphasize the limitations of this interim report. The first limitation is the small sample size of the TBI group. Many Veterans who were contacted did not return our calls, declined to participate, or were unable to participate for a variety of reasons. Compared to subjects who were excluded or declined, the baseline subjects were slightly younger, and there were more Caucasians, fewer African Americans, and more Latinos. Furthermore, for unknown reasons, African American Veterans had a higher "passive refusal rate" (less likely to answer the phone, return phone calls, keep an appointment, return consent forms, etc.). These results reflect a combination of factors including willingness to participate and comorbidities which led to exclusions. Therefore, the population which was studied in the clinic differs considerably from the population of subjects who were initially contacted for this project. Despite our efforts to contact and enroll all Vietnam Veterans receiving compensation from the VA diagnostic codes that may be related to TBI, we found that a very high proportion of Veterans with history of TBI had comorbidities which prevented them from enrolling in the study. In particular, we found that large numbers of these Veterans reported metal in the body, which prevented MRI examinations. The prevalence of this exclusion was much higher than we have experienced in civilian populations studied in ADNI. However, to increase the number of subjects, the decision was recently made to waive the MRI for subjects in the TBI/both cohorts, if the only reason for exclusion was that MRI was unsafe. In addition, Veterans with both TBI and PTSD had exclusions for many other reasons and overall the "screen fail" rate in this study is much higher than we have experienced with ADNI. These findings serve to emphasize the well-known observation that clinical research studies which impose strict inclusion/exclusion criteria to eliminate comorbidities run the risk of studying a sample that does not resemble the "general population." Furthermore, research studies which include biomarker measurements such as MRI, PET scans, and lumbar punctures also run the risk of reducing generalizability.

A second limitation is that our selection of cognitively normal and MCI participants able to be followed over the timeframe of the study, rather than of Veterans already exhibiting dementia, may automatically eliminate Veterans susceptible to the development of AD. The remaining cohort may represent a portion of the population that does not develop AD as a result of TBI and/or PTSD.

It is important to emphasize that this is an interim analysis of an ongoing study. In addition to our continued enrollment and baseline assessments, we are obtaining 12-month follow-up data. We are also performing tau-PET imaging at baseline and 12-month follow-up. Our preliminary results do not support the hypothesis that either TBI or PTSD increases the risk for AD measured with biomarkers. Subjects with PTSD do appear to have worse cognition, but this is not associated with increased amounts of brain amyloid measured by Aβ florbetapir PET scans. In the present study, we controlled for APOE genotype, the strongest genetic risk factor for late onset AD. In the future, genome-wide genotyping will be available so that other major candidate genes for AD, PTSD, and TBI can be assessed. When we complete enrollment, we will test the major hypotheses again, and the large sample size will provide sufficient statistical power for additional hypothesis testing and data exploration. Longitudinal data and tau-PET data will also be reported.

6. Conclusions

Epidemiological studies have inconsistently linked history of TBI or PTSD as risk factors for AD although few have investigated the relationship using imaging or CSF biomarkers. The study aims to determine the relationship between a history of TBI and/or PTSD and AD pathology. This preliminary report includes results from baseline clinical examinations, cognitive tests, structural MRI, and Aβ florbetapir PET imaging. Despite finding lower cognitive functioning in the PTSD and TBI + PTSD groups, and lower superior parietal volume in the TBI + PTSD group relative to controls, there was no evidence to suggest that the observed cognitive decline or atrophy was related to amyloid deposition. The study was limited by the small sample size of the TBI group and does not include results from ongoing tau-PET imaging or CSF biomarker analysis. However, we conclude that these interim results do not support the hypothesis that either TBI or PTSD increases the risk for AD as measured by biomarkers.

Systematic review: The authors reviewed literature pertaining to the associations between traumatic brain injury, posttraumatic stress disorder, and cognitive decline, and the incidence and prevalence of these risk factors in military populations using traditional sources such as PubMed.

Interpretation: Although we observed worse cognitive functioning in veterans with traumatic brain injury (TBI) and/or posttraumatic stress disorder, these risk factors did not increase AD risk measured by amyloid positron emission tomography (PET). Limitations include difficulty in recruitment due to exclusions resulting in a small sample size of TBI subjects and a study population that does not resemble the "general population."

Future directions: The study will continue to enroll participants and performed follow-up assessments of existing participants. Tau-PET imaging at baseline and 12 months will be performed and major hypotheses will be tested again.

Acknowledgments

Department of Defense Grants: Effects of Traumatic Brain Injury (TBI) and Post-Traumatic Stress Disorder (PTSD) on Alzheimer's Disease (AD) in Veterans Using Imaging and Biomarkers in the (AD) Neuroimaging Initiative (ADNI), W81XWH-12-2-0012. Effects of Traumatic Brain Injury and Post-Traumatic Stress Disorder on Alzheimer's Disease (AD) in Veterans with Mild Cognitive Impairment (MCI) Using the Alzheimer's Disease Neuroimaging Initiative (ADNI), W81XWH-13-1-0259. Effects of Traumatic Brain Injury and Post-Traumatic Stress Disorder and Alzheimer's Disease on Brain Tau in Vietnam Veterans Using ADNI, W81XWH-14-1-0462.

The authors very greatly appreciate the efforts of the clinical sites which recruited and assessed the subjects in this study. The principal investigators and study coordinators of the clinical sites are as follows: University of California, San Francisco, Howard Rosen, MD, Samuel Stark; Georgetown University, Brigid Reynolds, RN, MS, NP, Maysa Jawdat; University of Rochester Medical Center; Anton Porsteinsson, MD, Kim Martin, Nancy Kowalski; Banner Sun Health Research Institute, Edward Zamrini, MD, Sherye Sirrel; University of California, San Diego, James Brewer, MD, PhD, Helen Vanderswag; Rush University Medical Center, Debra Fleischman, PhD, Jamie Plenge, David Sedillo; Duke University Medical Center, P. Murali Doraiswamy, MD, Cammie Hellegers; University of Wisconsin, Madison, Sterling Johnson, PhD, Paul Cary; Brigham and Women's Hospital, Gad Marshall, MD, Lidya Poni; University of Southern California, Lon Schneider, MD, Mauricio Becerra, Karen Stevens-Dagerman; Liberty Teodoro, Sonia Pawluczyk, MD; Stanford University, Jerome Yesavage, MD, Michael Nolasco, Joy Taylor, PhD, Steven Chao, MD, Ann-Mary Salib; University of California, Irvine School of Medicine, Gaby Thai, MD, Beatriz Yanez; Mount Sinai Medical Center, Wien Center, Ranjan Duara, MD, Maria Greig, MD; Columbia University, Yaakov Stern, PhD, Siobhan Lawless; University of Washington Medical Center, Elaine Peskind, MD, Anita Ranta; Premiere Research Institute, Carl Sadowsky, MD, FAAN, Daisy Acevedo, Theresa Villena, MD; Howard University, Thomas Obisesan, MD, Saba Wolday; The Weill Cornell Memory Disorders Program, Michael Tai-ju-Lin, MD, David Kwak; Medical University of South Carolina, Jacobo Mintzer, MD, MBA, Courtney O'Neill.

The authors would like to thank San Francisco Veterans Administration Medical Center recruiters Laura Aronow, Morgan Blackburn, Viktoriya Bourakova, Lauren Chang, Diane Chao, Jason Falamino, Shannon Finley, Stacy Hatcher, Winnie Kwang, Cynthia Leo, Esther Rah, and Omar Rutledge.

Michael W. Weiner has served on the scientific advisory boards for Lilly, Araclon and Institut Catala de Neurociencies Aplicades, Gulf War Veterans Illnesses Advisory Committee, VACO, Biogen Idec, and Pfizer; has served as a consultant for AstraZeneca, Araclon, Medivation/Pfizer, Ipsen, TauRx Therapeutics Ltd., Bayer Healthcare, Biogen Idec, Exonhit Therapeutics, SA, Servier, Synarc, Pfizer, and Janssen; has received funding for travel from NeuroVigil, Inc., CHRU-Hopital Roger Salengro, Siemens, AstraZeneca, Geneva University Hospitals, Lilly, University of California, San Diego-ADNI, Paris University, Institut Catala de Neurociencies Aplicades, University of New Mexico School of Medicine, Ipsen, CTAD (Clinical Trials on Alzheimer's Disease), Pfizer, AD PD meeting, Paul Sabatier University, Novartis, Tohoku University; has served on the editorial advisory boards for Alzheimer's & Dementia and MRI; has received honoraria from NeuroVigil, Inc., Insitut Catala de Neurociencies Aplicades, PMDA/Japanese Ministry of Health, Labour, and Welfare, and Tohoku University; has received commercial research support from Merck and Avid; has received government research support from DOD and VA; has stock options in Synarc and Elan; and declares the following organizations as contributors to the Foundation for NIH and thus to the NIA funded Alzheimer's Disease Neuroimaging Initiative: Abbott, Alzheimer's Association, Alzheimer's Drug Discovery Foundation, Anonymous Foundation, AstraZeneca, Bayer Healthcare, BioClinica, Inc. (ADNI 2), Bristol-Myers Squibb, Cure Alzheimer's Fund, Eisai, Elan, Gene Network Sciences, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson & Johnson, Eli Lilly & Company, Medpace, Merck, Novartis, Pfizer Inc., Roche, Schering Plough, Synarc, and Wyeth.

Dr. Jack has provided consulting services for Eli Lily and Pfizer and owns stock in Johnson and Johnson. He receives research funding from the National Institutes of Health (R01-AG011378, RO1-AG041851, U01-AG06786, U01-AG024904, R01-AG37551, R01-AG043392, R01-NS092625), and the Alexander Family Alzheimer's Disease Research Professorship of the Mayo Clinic.

Dr. Landau has consulted for Genentech and Biogen.

Dr. Neylan serves on the Scientific Advisory Board for Resilience Therapeutics.Dr Petersen's consults for Roche, Inc., Merck, Inc., Genentech, Inc., Biogen, Inc. and Eli Lilly and Company: consultant/adviser.

Dr. Saykin received support from multiple NIA, NCI, NSF and DOD grants, Eli Lilly (collaborative research project), Avid Radiopharmaceuticals (AV1451 precursor), and Arkley BioTek (SBIR grant).

References

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Effects of traumatic brain injury and posttraumatic stress disorder on development of Alzheimer's disease in Vietnam Veterans using the Alzheimer's Disease Neuroimaging Initiative: Preliminary report

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Keywords: Traumatic brain injury, Posttraumatic stress disorder, Alzheimer's disease, Vietnam veterans, Mild cognitive impairment Alzheimer's disease (AD) is characterized by the presence of amyloid plaques and tau fibrils, which are associated with synaptic loss and neurodegeneration, leading to cognitive impairments and dementia.

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The crowdsourcing (the sourcing model whereby individuals use contributions from Internet users to obtain needed services and ideas) is also intended to be call for the global scientific and medical community to push forward with research intended to identify breakthrough new technologies that can assist with brain health. This includes artificial intelligence, bio-technology, precision pharmaceuticals, physics, and video games and brain hacking, each of which has shown some success in the treatment of Alzheimer's or aided an earlier detection of the neurological diseases. There is currently no cure for Alzheimer's disease, a condition that affects some 50 million people worldwide. The rate of the disease is expected to accelerate given the ageing global population.

With the focus of the group on treatment and detection, this is with acknowledgement that the neurodegeneration associated with Alzheimer's disease starts years before symptoms of dementia appear. The group will also focus in establishing a cure. With this aim, the cause of Alzheimer's disease is poorly understood; research suggests that 70 percent of the risk is believed to be genetic with many genes usually involved. However, there are other risk factors including a history of head injuries, depression, or hypertension. Additionally, the disease process is associated with plaques and tangles in the brain.

Commenting on the new approach, Dr. Ken Dychtwald, who is the founder of Age Wave and of the new body, which is called Alzheimer's Breakthrough, said: "With unprecedented global aging, unless Alzheimer's disease is stopped-and stopped soon-it will become the health, social and financial sinkhole of the 21st century."

The Alzheimer's Breakthrough proposals were conceived by Dr. Dychtwald together with Dr. Peter H. Diamandis, who is the Founder and Executive Chairman of the XPRIZE Foundation. XPRIZE is a non-profit organization that designs and manages public competitions intended to encourage technological development that could benefit humanity.

To date some 100 leading neuroscientists, advocates and exponential technology experts have contributed their ideas and insights to the process. These people have the goal of getting "launched" at the XPRIZE summit in October 2017. XPRIZES are monetary rewards to incentivize three primary goals:

Attract investment from outside the sector that takes new approaches to difficult problems. Create significant results that are real and meaningful. Competitions have measurable goals, and are created to promote adoption of the innovation. Cross national and disciplinary boundaries to encourage teams around the world to invest the intellectual and financial capital required to solve difficult challenges.

According to Alzheimer's News Today, the Alzheimer's team proposal will compete with four others focused on clean air, cybersecurity, democracy and industrial waste.

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Crowdsourcing innovations to tackle Alzheimer's

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The crowdsourcing (the sourcing model whereby individuals use contributions from Internet users to obtain needed services and ideas) is also intended to be call for the global scientific and medical community to push forward with research intended to identify breakthrough new technologies that can assist with brain health.

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On a cool September evening, Judy Johanson curled up on her living room sofa with her iPad, carefully examining mouse brains. Her husband, Steve, slept just a few feet away. It was granular work, especially for a woman who for 24 years ran a daycare center. Judy scrolled through hundreds of slides, searching them, one by one, for tiny black spots. The task might have appeared deeply tedious-but Judy was in the zone. While Steve dreamed, she was joining thousands of amateur scientists in the search for a cure for his disease.

When Steve was diagnosed with younger-onset Alzheimer's disease six years ago, at age 58, he told Judy: "We can choose to be sad or we can choose to be happy." So they chased happiness: The Johansons worked with the Alzheimer's Association and began lobbying local and federal politicians for more research funding. Until last November, Steve was part of a promising 18-month clinical trial for a drug intended to slow his cognitive decline. Judy felt certain that the drug was working, but earlier this year researchers concluded it was ineffective.

The news was crushing. Since then, Steve's experienced a significant decline. His mobility is limited; Judy converted their living room into a bedroom so that he doesn't have to use the stairs. One day this summer, he walked straight into the swimming pool that he'd constructed in their backyard nine years earlier. As Steve's symptoms have worsened, it's become harder to find trials for which he qualifies; at times, a treatment can feel impossibly far away. He no longer remembers telling Judy they should "choose to be happy."

But Judy has found solace in sorting through the slides of tiny mouse brains that might hold the key to Steve's recovery. She's one of six thousand people who have logged time playing Stall Catchers, a game that helps researchers investigate how treating the impaired cerebral blood flow associated with Alzheimer's can help reverse memory loss. (In mice, lab researchers have found, it can.) By turning the research into an online game, its creators hope to speed up lab research-and hopefully lead to a treatment for the disease in a few years, as opposed to a few decades.

Stall Catchers is part of a long legacy of crowdsourced science projects, also known as "citizen science." The practice dates back to well before the internet era: Since 1900, for instance, birdwatchers across North America have participated in a Christmas census of bird populations, and in 1956, the Smithsonian Astrophysical Observatory recruited thousands of people to help professional scientists spot the first artificial satellites. But the internet has allowed for a veritable explosion of citizen science projects; today there are more than one thousand efforts underway, with more than a million volunteers offering up their uncompensated time and resources to help search for signs of extraterrestrial intelligence, diagnose malaria, and track damage from hurricanes like Harvey, Irma, and Maria.

Stall Catchers is a little different. Yes, plenty of its players are the same quirky enthusiasts and retirees that go gaga for crowdsourced astronomy and history projects (and sometimes even wind up with their names on scientific papers). But at the game's heart is a community of people like Judy Johanson, who have watched a loved one struggle with Alzheimer's and are desperate for some way to feel like they are doing something concrete to fight the disease. Frustrated by high nonprofit overheads and the glacial pace of research, they've leapt at an opportunity to take things into their own hands. And though a true cure for Alzheimer's is still distant, Stall Catchers has already proven an effective treatment for one of the disease's most insidious symptoms: helplessness.

At the rate that Nozomi Nishimura and Chris Schaffer's research was going, it was going to take decades to bring a treatment to market. The Cornell biomedical engineering professors had spent eight years investigating the relationship between impaired blood flow in the brain and Alzheimer's disease. They'd figured out how to examine the smallest blood vessels in the brains of mice that were genetically modified to mimic Alzheimer's. They'd discovered that they were able to reverse some memory loss with a drug to improve blood flow. But that drug also destroyed the mice's ability to fight infections, making it unfit for humans. Now, the lab is trying to find a drug that can tackle "stalls"-places where blood flow has been cut off-without compromising patients' immune systems. That means that for every drug they test, they need to examine images of the mice's brains and search for stalls, which show up on the slides as small black spots and indicate that the drug isn't working. But testing a new drug requires that some 30,000 images be examined-a process that would take the lab as long as a year for each new experiment.

Enter Pietro Michelucci. The director of the Human Computation Institute had spent years studying collective intelligence systems, which harness the wisdom of crowds in decision-making, and he'd created the nonprofit to apply that crowd power to real-world problems. A colleague put Michelucci in touch with Schaffer. The Cornell lab's mountain of visual data reminded Michelucci of Stardust@Home, a pioneering citizen science project that deputized amateurs to analyze interstellar dust collected during NASA's 1999 Stardust sample mission. Michelucci was sure he could apply the virtual microscope used to catalogue space dust to the Schaffer-Nishimura lab's images. (The creator of Stardust@Home, Andrew Westphal, had lost his father to Alzheimer's and didn't take much convincing.)

But Nishimura and Schaffer were skeptical. They'd spent a long time individually training undergraduates to analyze the images properly. How could thousands of amateurs with little to no background in science possibly be trusted to get it right?

The key, it turned out, was an algorithm that Michelucci developed to tap the wisdom of the crowd. It counts every "stall" identified by a volunteer as a vote-either in favor of or against that image representing a genuine disruption in blood flow. A critical mass of votes produces a verdict with similar accuracy to one from a trained scientist. Michelucci calls this the "magic number," and he's managed to bring it down from 20 to 7 through a weighted system that gives more credence to votes from volunteers who've been playing for longer.

The crowdsourcing is already leading to results in the lab. Earlier this month, Michelucci announced that the Stall Catchers crowd had helped determine that stalls in blood flow are not associated with the amyloid plaques that are a hallmark of Alzheimer's disease-a finding that will help the Cornell researchers narrow down their exploration of treatment options. Michelucci and his team have held "catch-a-thons" across the world, and recruited players from over 14 countries. At peak moments of productivity, Stall Catchers players have completed a week's worth of lab research in a single hour.

It's still slow work; "disappointingly slow," Nishimura says. A cure won't emerge tomorrow. With the help of Stall Catchers, the lab might be able to offer a treatment in a fraction of the time it would otherwise-but still, we're talking years. For people like Judy and Steve Johanson, however, that could make a difference.

The Johansons never saw their lives going in this direction when they met 42 years ago, at a Boys & Girls club. Judy was 12, Steve was 22, and Judy harbored a crush on him for six years before they began dating. Seven years later, they moved into the house in Watertown, Massachusetts where they still live today, sharing a backyard with Judy's mother and sister. They raised a daughter and a son. Steve's brother married one of Judy's sisters. Steve worked as a construction project manager, and he constantly made additions to their property: He built the inground pool, and added on a townhouse, where their daughter and her husband now live. While Judy ran a daycare, Steve managed $20 million projects at Northeastern University, across the Charles River.

Six years ago, Steve got an unusually negative performance review at work- and five months later, he received his devastating diagnosis. At one point, he told Judy that he wished he had a brain tumor, because then at least there might be treatment options. In a journal entry composed shortly after his diagnosis, Steve reflected: "As a construction manager and a carpenter, I have always been able to put the pieces together to build beautiful and safe places for my family, friends, co-workers. I suspect my tools will lay, unused and layered with ever-deepening layers of dust."

These days, Steve and Judy wake as early as three or five in the morning, and Judy helps him shower, dress, and brush his teeth. Three days a week Judy drives him to a daycare program, where he plays trivia games, listens to music, or catches up on the news. Lately, Steve has found the news distressing: He worries that Donald Trump is going to come and harm his children; he's become convinced that the hurricanes ravaging Texas, Florida, and the Caribbean are going to reach Massachusetts. He wants to know when the family is going to evacuate. That has effectively quashed Judy's desire to catch up on current events. So in her rare moments of free time, she turns to those black-and-white, grainy stills of mouse brains.

Stall Catchers is hardly Candy Crush. The images can be difficult to parse, and analyzing them can sometimes feel more like homework for a high-school science class than an entertaining game. Still, it's become something of a family tradition in the Johanson household. Judy's sister, Kelly Corrigan, plays incessantly-while on the stairmaster at the gym; in the waiting room at the dentist's office or the DMV; or in lieu of watching TV in the evening. The Johanson's two oldest grandchildren-Nathan, who's 7 years old, and Caleb, who's 9-have become adept at catching stalls, too, and sometimes even outscore Judy, who says she's more prone to becoming trigger-shy when she's missed a stall or two. Together, Kelly and Judy have recruited nearly 100 people to join them on the leaderboard.

They describe themselves as addicted to the game, and though it may be difficult to believe that picking through mouse brains could be addictive, they're not alone. By adding in the simple element of a scoreboard, the game's creators have tapped into players' competitive instincts-and the more you play, the more points you get for every correctly spotted stall. The game is a hit among kids-at Lake Hazel Middle School in Boise, Idaho, for instance, a teacher named Erin Davies recruited 240 students to play, and many of them have cracked the top 50 on the leaderboard. None have come close, however, to unseating Michael Capraro, a retired chemical engineer living in Riverview, Michigan who plays Stall Catchers for a solid hour and a half every day in order to maintain his #1 spot on the leaderboard, where he boasts a score of 285,778,531 (for context, your first few stall catches will earn you just 10 points each).

Judy and Kelly are full of tips and tricks for mastering Stall Catchers-number one, play it on a computer or an iPad, not on your phone-and the family will often gather in a room with Steve and spend an afternoon or evening catching stalls. "It's something we can all do together, when there's a lot of things we can't do together anymore," says Judy. "There's nothing, really nothing you can do for this disease. This is hope in a video game."

In an ideal world, no one would need to spend unpaid hours examining mouse brains. Stall Catchers is a workaround. Alzheimer's research has long been underfunded: In 2016, the federal government spent $986 million on research, when the Alzheimer's Association has long maintained that researchers need $2 billion per year in order to treat the disease effectively. There was some positive progress on that front earlier this month, when the Senate Labor, Health and Human Services, and Education Appropriations Subcommittee approved $414 million in new spending for research on Alzheimer's disease, bringing the total that the NIH will spend on the disease this year up to $1.8 billion. That was heartening for Judy: When she and Steve first started advocating for more funding four years ago, the budget was at just $504 million.

The Johansons are realistic. They know that no amount of stall catching will necessarily help Steve. For their close friend Sheryl Teti, it's already too late: Her father died nearly two years ago, at the age of 85, after spending five years wrestling with Alzheimer's. Stall Catchers didn't exist when Teti's father was struggling-but she now finds herself playing it nearly every day, sometimes for as many as three hours. "You don't have to wait for the walk or the triathlon to do this," she says. "You can do this whenever you need to."

It can be difficult, Judy says, to be hopeful for a cure yet accepting of the fact that one might not come soon enough. When the hopefulness feels particularly out of reach, she borrows a phrase coined by her grandkids: "When life gives you Alzheimer's, make lemonade." Her grandchildren literally make lemonade, donating the proceeds to the Alzheimer's Association. And Judy? She catches stall, after stall, after stall.

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Why Thousands of People Are Addicted to Examining Mouse Brains | Backchannel

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On a cool September evening, Judy Johanson curled up on her living room sofa with her iPad, carefully examining mouse brains. Her husband, Steve, slept just a few feet away. It was granular work, especially for a woman who for 24 years ran a daycare center.

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Crowdsourcing Alzheimer’s Data through New “EyesOnALZ” Game Will Accelerate Research, BrightFocus Foundation Says

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Crowdsourcing Alzheimer’s Data through New “EyesOnALZ” Game Will Accelerate Research, BrightFocus Foundation Says

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Clarksburg, MD-BrightFocus Foundation today lauded a new, innovative citizen science project, which recently launched an online game- Stall Catchers -to engage the public in helping researchers analyze Alzheimer's data in the hopes of more quickly discovering ways to prevent and treat the disease.

Developed by Human Computation Institute, in collaboration with scientists at Cornell, Berkeley, Princeton, WiredDifferently, and SciStarter, Stall Catchers is the first of two new efforts to use experiences similar to on-line gaming to advance science. Organizers believe that the crowdsourcing of time-consuming data analysis could significantly speed up the research process.

"BrightFocus is proud to support such bold, innovative research. This study is a promising way to tap the power of the crowd to accelerate research to better understand, and one day stop, Alzheimer's," said BrightFocus President and CEO Stacy Pagos Haller.

Funded by BrightFocus, the game will assist Alzheimer's research at Cornell's Schaffer-Nishimura Laboratory. Scientists there have examined blood vessels in the brain, and searched for "stalls," which are clogged capillaries where blood is no longer flowing. In mouse models, researchers were able to reverse Alzheimer's symptoms such as memory loss by reducing the number of stalls.

Scientists believe that identifying and reducing these stalls in humans could eventually slow the progression of the disease. Project leaders, concerned that analysis of stalls to develop treatment targets will be quite time-consuming, are hopeful that this new citizen science project could speed up the process by many years. The Stall Catchers game, in which players help detect and retrieve data on stalls, is open to all.

"All you need to participate in the project is a laptop, a tablet, or a smartphone, and the desire to fight Alzheimer's," said EyesOnALZ principal investigator, Dr. Pietro Michelucci. "We are pleased to partner with such a forward-thinking organization as BrightFocus, and honored to add EyesOnALZ to their legacy of game-changing innovations."

BrightFocus Foundation funds research and promotes awareness to end Alzheimer's disease, macular degeneration and glaucoma. The nonprofit is currently managing a global portfolio of 150 projects, efforts that were recommended by scientific review committees of leading experts. For more information, visit www.brightfocus.org.

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Crowdsourcing Alzheimer's Data through New "EyesOnALZ" Game Will Accelerate Research, BrightFocus Foundation Says

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BrightFocus Foundation today lauded a new, innovative citizen science project, EyesOnALZ, which recently launched an online game - Stall Catchers - to engage the public in helping researchers analyze Alzheimer's data in the hopes of more quickly discovering ways to prevent and treat the disease.

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Monitoring Editor: Gunther Eysenbach

Reviewed by Bei Yu, Tanjir Rashid Soron, and Itzhak Tabatchnik

Daniel Robert Bateman, MD, ¹ 2, 3, ⁴ Erin Brady, MSc, PhD, 1, 3, ⁵ David Wilkerson, LICSW, PhD, 1, 3, ⁶ Eun-Hye Yi, MSW, 1, 3, ⁶ Yamini Karanam, BS, ⁵ and Christopher M Callahan, MD 1, 3, 4, ⁷

Abstract

Background

In the United States, over 15 million informal caregivers provide unpaid care to people with Alzheimer disease (AD). Compared with others in their age group, AD caregivers have higher rates of stress, and medical and psychiatric illnesses. Psychosocial interventions improve the health of caregivers. However, constraints of time, distance, and availability inhibit the use of these services. Newer online technologies, such as social media, online groups, friendsourcing, and crowdsourcing, present alternative methods of delivering support. However, limited work has been done in this area with caregivers.

Objective

The primary aims of this study were to determine (1) the feasibility of innovating peer support group work delivered through social media with friendsourcing, (2) whether the intervention provides an acceptable method for AD caregivers to obtain support, and (3) whether caregiver outcomes were affected by the intervention. A Facebook app provided support to AD caregivers through collecting friendsourced answers to caregiver questions from participants' social networks. The study's secondary aim was to descriptively compare friendsourced answers versus crowdsourced answers.

Methods

We recruited AD caregivers online to participate in a 6-week-long asynchronous, online, closed group on Facebook, where caregivers received support through moderator prompts, group member interactions, and friendsourced answers to caregiver questions. We surveyed and interviewed participants before and after the online group to assess their needs, views on technology, and experience with the intervention. Caregiver questions were pushed automatically to the participants' Facebook News Feed, allowing participants' Facebook friends to see and post answers to the caregiver questions (Friendsourced answers). Of these caregiver questions, 2 were pushed to crowdsource workers through the Amazon Mechanical Turk platform. We descriptively compared characteristics of these crowdsourced answers with the friendsourced answers.

Results

In total, 6 AD caregivers completed the initial online survey and semistructured telephone interview. Of these, 4 AD caregivers agreed to participate in the online Facebook closed group activity portion of the study. Friendsourcing and crowdsourcing answers to caregiver questions had similar rates of acceptability as rated by content experts: 90% (27/30) and 100% (45/45), respectively. Rates of emotional support and informational support for both groups of answers appeared to trend with the type of support emphasized in the caregiver question (emotional vs informational support question). Friendsourced answers included more shared experiences (20/30, 67%) than did crowdsourced answers (4/45, 9%).

Conclusions

We found an asynchronous, online, closed group on Facebook to be generally acceptable as a means to deliver support to caregivers of people with AD. This pilot is too small to make judgments on effectiveness; however, results trended toward an improvement in caregivers' self-efficacy, sense of support, and perceived stress, but these results were not statistically significant. Both friendsourced and crowdsourced answers may be an acceptable way to provide informational and emotional support to caregivers of people with AD.

Keywords: Alzheimer disease, Alzheimer disease and related dementias, caregivers, mobile health, social media, crowdsourcing, friendsourcing, emotional support, informational support, online support

Introduction

Studies predict that the worldwide prevalence of dementia will reach 48.1 million people by the year 2020 [ 1]. Alzheimer disease (AD) accounts for the majority of cases of dementia in the United States [ 2]. Unlike for many other diseases, to date there are no disease-modifying agents to slow down or stop the progression of AD. Until disease-modifying agents become available, psychosocial and psychoeducational interventions remain the intervention of choice for addressing treatment needs of patients and caregivers. Informal, unpaid caregivers deliver the majority of care received by people with AD [ 3]. Estimates for 2013 put the value of this informal, unpaid care for people with AD and other dementias in the United States at US $470 billion [ 3]. Fiscal estimates do not account for the mental and physical health burdens endured by many AD caregivers. Besides the inherent detriment to caregivers, higher caregiver burden and lower caregiver subjective health ratings adversely affect patients with AD. Higher caregiver burden results in earlier nursing home placement, while lower caregiver subjective health is associated with higher mortality in people with AD [ 4]. Prior work showed that AD caregivers receive health benefits from psychosocial and psychoeducational interventions [ 5]. Yet many caregivers' needs remain unmet due to multiple barriers, including time and distance. Social media offers an opportunity to provide support to AD caregivers while overcoming some of these barriers [ 5].

Caregivers have a higher incidence of mental illness and benefit from emotional support. These mental illnesses include anxiety [ 6- 8], depression [ 6, 9- 15], poor sleep quality [ 7, 8], and substance abuse or dependence [ 16]. Caregiving also affects the work force, with caregivers displaying greater absenteeism [ 6, 7], higher rates of poor physical health [ 17- 19], and higher mortality [ 20, 21]. Studies show that strategies of problem-focused coping, acceptance, and social-emotional support improve caregiver mental health and depression [ 3, 22- 26].

Caregivers receive emotional and informational support from many sources, but these existing sources have limitations. In-person social support groups can meet caregiver support needs including emotional support and self-appraisal [ 27], but they present limitations based on the logistical issues of scheduling, traveling, and finding alternative supervision for the person with dementia while the caregiver is absent. Membership in online health communities can address logistical barriers to service utilization, and caregivers often seek emotional and informational support from their peers [ 28]. However, cautions about the reliability of health care information being shared [ 29], the tendency of participants to lurk by browsing rather than contributing content [ 30, 31], and participation inequalities [ 32] point to limitations that interfere with the ability of online communities to support caregivers in the process of coping.

Other systems may provide individualized support for the caregiver, supplementing the benefits of traditional forums. However, any technological system designed to provide just-in-time personalized support to caregivers requires a large number of people who are online and available to respond to their questions. Systems that connect a caregiver to a clinician or trained social worker are unlikely to scale well, due to the limited size of the clinician population. For this study, we investigated crowdsourcing and friendsourcing as alternatives to soliciting appropriate and supportive feedback to questions from caregivers.

Crowdsourcing is a way to leverage remote workers to perform small tasks, either for financial compensation or on a voluntary basis [ 33]. In crowdsourced systems, a task is broken up into parts and distributed to remote workers, who can complete the sections in parallel or build on the work of others. The answers provided by these workers can be aggregated and used to create systems that leverage human intelligence in novel ways. Crowdsourcing systems have been used to provide emotional support to individuals by collecting empathetic responses or cognitive reappraisals of stressful situations [ 34]. While online forums are used by many to seek information, crowdsourcing can be a more efficient and reliable way of seeking information. Drawbacks of traditional crowdsourcing include financial costs and variable quality of answers, depending on the expertise and experience of the crowd workers.

Friendsourcing is a paradigm that combines social media information seeking with crowdsourcing [ 35]. In friendsourcing, individuals use their friends and contacts online as a resource for crowdsourcing information or help. While friendsourcing can be used to identify specific information that only your network would know [ 35], as people gain stronger trust in the information their friends or families provide, they often leverage these social networks to seek information that might be available to them in other places [ 36]. Prior work has shown that as many as 50% of social media users have friendsourced a question to their online networks before [ 36], and that social media can have significant impacts on health-related behavior change and well-being [ 37, 38]. There are often benefits to providing this information as well. People answering questions have improved self-efficacy, build a sense of reciprocity with the question asker, and appreciate the opportunity to show off their expertise [ 36, 39].

Online peer support activities can help AD caregivers reduce the stress of caregiving and enhance hands-on knowledge and self-efficacy. A common model of online peer support involves the use of online discussion forums. Drawbacks of the online discussion forum model include low user content contribution and limited efficiency for accessing correct information.

We designed this pilot study to explore alternative online methods to address caregiver needs through online peer support. This research conducted by an interdisciplinary team aimed to overcome previously mentioned drawbacks by adapting friendsourcing, within a closed Facebook group. To our knowledge, our work is the first to use friendsourcing to provide support to AD caregivers. The underpinning theory of this intervention is that social support moderates caregiver burden and stress. We hypothesized that the study intervention would be acceptable to AD caregivers as a method for obtaining online support, that friendsourced and crowdsourced answers to caregiver questions would be of high-quality content, and that friendsourced answers would have higher rates of shared experiences in comparison with crowdsourced answers.

The contributions of this study include (1) an assessment of the feasibility of online support delivery to AD caregivers through social media and friendsourcing, (2) an evaluation and comparison of friendsourced and crowdsourced answers to caregiver questions in terms of content quality, acceptability, and rates of shared experiences, and (3) suggestions for future research directions for online support delivery to AD caregivers through social media.

Methods

Study Participants and Recruitment

Potential participants were nonpaid family caregivers of people with AD. We distributed a recruiting advertisement across the United States through organizational webpages, including the Alzheimer's Association webpage and newsletter, Indiana University Purdue University Indianapolis's online newsletter News at IUPUI, radio interviews, and social media, including Twitter (Twitter, Inc, San Francisco, CA, USA) and Facebook (Facebook, Inc, Menlo Park, CA, USA), from July through September 2016. Potential participants gained access to the study through the study website. The website provided study information, inclusion and exclusion criteria, links to the online survey, and a PDF of the informed consent form. This study was approved by the Indiana University Institutional Review Board (# 160317338) through expedited review.

Study inclusion criteria for participation were as follows: the participant must (1) be 18 years or older, (2) live in the United States, (3) be able to read, comprehend, and write in English, (4) be the caregiver of an individual with AD who lives at home with the caregiver, (5) provide at least 8 hours of caregiving for the person with AD per week, (6) have a Facebook account with at least 40 Facebook friends, (7) have posted or commented on Facebook on average at least twice per week for the past month, (8) have ready access to the Internet, and (9) agree to give his or her informed consent to participate in this research. Exclusion criteria were a psychiatric hospitalization or suicide attempt in the past year. We chose age 18 years as the cutoff so that all participants were legal adults. The requirement of 40 Facebook friends was arbitrarily chosen as a cutoff to indicate the participant had a preexisting online social network before joining the study.

Design

This study used a pretest-posttest design with mixed methods. We sequentially allotted participating nonpaid family caregivers of people with AD to 3 closed Facebook groups to receive the intervention over the course of 6 weeks (September 29, 2016 to October 10, 2016). As this trial is ongoing, the results of this paper are restricted to the first group of study participants. The study was composed of 4 parts: (1) the preintervention portion, where participants completed consent, an online survey, a semistructured interview, and installation of the study Facebook app; (2) the 6-week intervention; (3) the postintervention portion, where participants were asked to complete a postintervention survey, semistructured interview, and optional reflection group; and (4) the follow-up portion, where participants were asked to complete an online role transformation survey 6 weeks after completion of the intervention.

All participants provided written informed consent through the online survey page. Once participants met screening criteria and consented to the study online, they could proceed to the online survey preintervention portion of the study. The survey included questions on demographic information and required completion of 7 standardized scales (described below). Once we identified an applicant's completion of the survey, one of the research team members conducted a semistructured telephone interview and guided the participant in installation of the study app.

The intervention comprised 2 major components: interaction within a closed Facebook online support group and posting of anonymous questions about caregiving to each participant's Facebook News Feed through the study app. Participants interacted with other group members within the private Facebook online support group by posting and responding to each other's comments. We facilitated group introductions and discussion through weekly prompts. These prompts requested participants to discuss emotional or informational support questions that the group chose to share with their social network (Facebook friends). We observed and moderated postings and participation. Moderation included sending reminder prompts to post information for participants who did not respond to the initial prompts to post information, answering technical and study activity questions, and monitoring for comments that could cause harm to the participants.

Through the study app, selected questions were automatically posted to the Facebook News Feed of each participant so that his or her Facebook friends could review and post responses to the caregiver questions (). These answers from Facebook friends were then reposted into the private Facebook group for group members to read as a way to leverage their impact on peer social support.

By posting each question to the News Feed of each caregiver, we were able to expand the number of people available to provide support at any point. shows how the support network size is increased by using friends from multiple networks as potential question answerers. Prior work on social microvolunteering has shown that this use of multiple networks can approximate the speed of crowdsourcing in collecting answers to questions [ 39].

After finishing the 6-week intervention, participants were asked to complete the postsurvey and semistructured telephone interview. They were then offered the opportunity to participate in an optional reflection group and role transformation survey. Participants received compensation for their time and effort in the form of electronic gift cards.

Data and Measures

We collected both quantitative and qualitative data at multiple time periods during the study. We gathered demographic variables, including age, sex, living arrangement, level of education, employment status, income, type of residential area, and relationship with the care recipient, through the preintervention survey. We also gathered qualitative data from preintervention and postintervention interviews and follow-up reflection group interviews. Additionally, comments were collected from the automatic posts made in each participant's Facebook News Feed. These comments included those made by the participants and those made by their social network (Facebook friends) in response to posted caregiver questions.

The preintervention and postintervention online surveys included 7 standardized self-reported caregiving-related instruments: the Zarit Burden Interview Short Form (ZBI-12) [ 40], the Perceived Stress Scale-14 (PSS-14) [ 41], the Revised Scale for Caregiving Self-Efficacy [ 42], the Medical Outcomes Study (MOS) Social Support Survey [ 43], the Dementia Severity Rating Scale [ 44], the Neuropsychiatric Inventory Questionnaire [ 45], and the Facebook Intensity Scale (FBI) [ 46]. Below we describe 3 of the scales that capture caregiver needs, social support, and views on technology.

The ZBI-12 [ 40] measures caregivers' perceived burdens of their caregiving roles. The measurement consists of 12 items in 2 main domains: personal strain and role strain. Each question asks about the frequency at which a caregiver experiences certain types of caregiving difficulties. It is scored in a 5-point Likert-type scale from 0 (never) to 4 (nearly always).

The MOS Social Support Survey measures the availability and frequency of different types of support [ 43]. The scale is composed of 19 items with 3 subsections-8 emotional and informational support sections, 4 tangible support sections, and 6 affectionate support sections-and 1 additional item. It is scored on a 5-point Likert scale from 1 (none of the time) to 5 (all the time).

The FBI is composed of 8 items about the level of familiarity with Facebook: 6 items were scored using a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) [ 46], and 2 open-ended questions assessed the user's Facebook behavior regarding the total number of Facebook friends and the average hours per day of availability to use Facebook.

Crowdsourcing Using Amazon Mechanical Turk

Through a separate study approved by the Indiana University Institutional Review Board (# 1609570045), we posted 2 of our caregiver questions to the Amazon Mechanical Turk (Amazon.com, Inc, Seattle, WA, USA). Amazon Mechanical Turk is a traditional crowdsourcing platform where a vast pool of workers can select tasks to complete for small payments [ 33]. Mechanical Turk is frequently used as an input to academic crowdsourcing systems, including those supporting emotional health [ 34] and those evaluating health literacy [ 47].

We posted our questions on Mechanical Turk with the goal of comparing these answers with the answers provided by our caregivers' online social networks. We recruited Masters-level Turkers, who have met specific qualifications indicating their experience level with using the platform. Workers who accepted the task on Mechanical Turk were presented with an example question, shown in the same Facebook post format as was posted to the caregivers' News Feed (). They were asked how they would respond in the comments to that post.

The workers were paid US $3 for their response. While this is a higher payment rate than in many other Amazon Mechanical Turk studies [ 48], it is in line with worker expectations of payment on Amazon Mechanical Turk as a labor marketplace [ 49].

Data Analysis

Survey results helped characterize participants through measures of caregiving stress, self-efficacy, familiarity with Facebook, care recipient symptoms, and illness severity. We audio recorded and transcribed participant interviews and then conducted a deductive thematic analysis of these transcriptions focused on participants' access to support [ 50]. Interviews were open coded and themes were identified across participants and reported via prevalence.

We evaluated the Facebook friend (friendsourcing) answers to caregiving questions. Answers were reviewed by 2 content experts (DRB and DW) for acceptability, shared experiences, emotional support, and informational support. Agreement was obtained through a process of adjudication. Answers were described qualitatively. We used the same rating process for the crowdsourced answers obtained through Amazon Mechanical Turk. Acceptability was defined as an answer that, without further information or advice, would be unlikely to cause harm to a caregiver and care recipient, if it were to be read. We used definitions for "emotional support messages" and "informational support messages" from Wang et al [ 51]. Emotional support messages provide or show understanding, encouragement, affirmation, sympathy, or caring [ 51]. Informational support messages deliver advice, referrals, or knowledge [ 51].

Results

Participants

A total of 12 potential participants accessed the online study survey. Of these, 6 participants completed the online survey and semistructured telephone interview, and 4 of these 6 agreed to participate in the group activity portion of the study. Only 1 of the 6, P6, declined to participate, because she felt she did not need any extra support. Her MOS Social Support Survey results were consistent with this reasoning. Another participant, P5, declined, citing limited time as a result of caregiving obligations as the main reason for nonparticipation. She estimated her hours of caregiving at 148 hours per week, 128 hours longer than the next closest participant (). Participants' ages ranged from 34 to 74 years, with a mean age of 58 years. Of the 6 participants, 5 had completed some college, with 2 participants having obtained advanced degrees. The hours of caregiving provided per week ranged from 16 to 148, with a mode of 20. Duration of caregiving ranged from 7 to 36 months, with a mean of 20 months. Half (n=3) of the caregivers were either a spouse or partner to the care recipient. All 5 of the care recipients (people with AD) were female. Participant ZBI-12 scores ranged from 12 to 30 (range 0-48) with a mean of 21.83 (SD 5.81) ().

Table 1

Table 2

Deductive Thematic Analysis

Limitations of Current Support Resources

All 4 participants in the group portion of the study had access to some type of support for their caregiving, but these resources were limited in significant ways. All of our participants reported insufficient access to in-person support.

In-Person Support

Family was the most commonly referenced source of support, with all 4 participants describing family members who had provided them with emotional support. A total of 3 participants were geographically isolated from most of their family members, meaning that the burden of caregiving fell primarily on them. They also had to explicitly contact family members for emotional support. The caregivers were often the only family members with enough contextual information to make health decisions for their care recipient, meaning they could not rely on family members for informational support. Primary caregivers often instead provided support to those family members:

I think a lot of it is, I have a lot of family members that are in [state] that are not medical and sometimes don't understand what is going on with her. They ask me a lot of questions...I just want to keep her comfortable and they don't always understand that. I think that's hard for me to justify all of my actions with her.

Many participants experienced a change in their ability to leave their home as a result of their caregiving, which meant they had less access to social or emotional support from friends in workplace or recreational settings. Indeed, 2 participants had cut back or left their jobs to focus on caregiving full-time, while others gave up existing hobbies or social activities, so as not to leave their care recipient alone. These changes may have led to a smaller network of support immediately available to them.

All 4 caregivers relied on their loved one's doctors as a primary resource for informational support.

The doctors observed macro-level changes in the patients' behavior and health, rather than day-to-day issues. Support from physicians was infrequently available. For example, P4 specified that he interacted with his wife's doctor only once every 3 months. Some caregivers also used medical professionals as a source of emotional support, and 2 participants sought formal emotional support through therapy. As with informational support, professional emotional support was highly valued by the caregivers who accessed it. However, long intervals occurred between visits, and caregivers expressed a wish to have access to additional emotional support.

Online Support

To join our study, participants were required to have an active Facebook account with at least 40 friends, meaning that our participants were likely to have significant technological experience. All participants reported having both computers and smartphones through which they accessed the Internet. Despite this baseline level of technology and social media use, we found a variety of use patterns and technology acceptance among our participants.

Two caregivers, P1 and P4, had small networks on Facebook (80 and 40 estimated friends, respectively; ). Both primarily used the sites to catch up with friends and family. While P4 had not previously used Facebook to access emotional support, P1 shared how his family used Facebook to encourage him during his caregiving:

One day my daughter posted on Facebook what a great job I was doing taking care of her mom and so on.

The other 2 participants, P2 and P3, had large networks on Facebook (900 and 1000 estimated friends, respectively; ) and used the site both to socialize and to access news or information about AD. P3 described how she valued Facebook as a resource for her friendships and for learning:

I look up sports there [on Facebook] and I follow three different Alzheimer's things. I try to mix work there so that way I will look at it. It's like a one-stop news place for me. Equal half for friends and information.

While all participants except P4 used other social network sites, like Twitter or Pinterest, all participants reported that Facebook was the site that they used with the highest frequency.

Caregivers used a variety of online resources to access informational support. Some of that information was acquired passively, by following or subscribing to updates from AD organizations via Facebook or email. Others sought information actively by researching specific informational questions. While participants used online forums to research information support questions, none had posted on online forums or discussion groups related to caregiving themselves. P4 reported that he had browsed one of these forums for information, but had not yet posted his own questions:

I read them. I have thought of posting on it. I'm still new on it. So I'm kind of reading other experiences, because there is so much good information in there. For example, a lady posted that her dad keeps wandering away from the house or another posts about how their mom does not sleep at night. How to handle that. I read that to see their responses. It's been very helpful. Yes, reading about other people's experiences [is] very helpful.

I'm not sure. I tend to be a private person. I would not be comfortable opening up with people [I] don't know with the exception of Facebook. There is this thing about the Internet where I may never meet that person.

Our participants' responses indicate a need for additional support, as well as a familiarity with Facebook that might make it a more appealing source of support than anonymous forums or crowdsourcing platforms.

Activity During Facebook Online Support Group

During the online Facebook group portion of the study, we posted 4 online prompts (). There were a total of 12 replies (postings) by group members in response to our prompts. The group participants had 20 spontaneous voluntary posts or replies to other members of the group.

Table 3

Friendsourcing Results

We pushed 3 caregiver questions to the participants' Facebook News Feed, allowing participants' Facebook friends to see and reply to the caregiver questions. The total number of Facebook friend responses was 44 (). The range of total number of Facebook friend responses per participant varied between 6 and 19.

Friendsourcing and crowdsourcing answers had high and similar rates of acceptability, as judged by content experts: 90% (27/30) and 100% (45/45), respectively (). This study lacked the power to draw quantitative conclusions from these data. Friendsourced answers contain shared experiences at a higher rate than Amazon Mechanical Turk answers: 67% (20/30) and 9% (4/45), respectively. Rates of emotional support and informational support messages present in friendsourcing and crowdsourcing answers were similar, and appeared more dependent on the type of question asked rather than the group answering the question.

Table 4

Effects of the Intervention

Our small sample prevented the use of parametric statistics; thus, we used Wilcoxon signed rank tests to compare preintervention and postintervention measures. This nonparametric method considers scores as ranks to measure changes between 2 periods. We calculated both medians and means. None of the pretest-posttest comparisons showed a statistically significant difference (). However, caregiver burden (measured by ZBI-12) showed a trend toward improvement in overall caregiver burden. There were trends toward an increase in emotional and informational support, tangible support, and total social support, but these results were not statistically significant. FBI showed a near doubling of the level of familiarity with Facebook. The number of Facebook friends and time available to use Facebook also increased. The median and mean scores of PSS-14 frequencies (having emotional problems in the last month) decreased, although the change was not statistically significant. The Revised Scale for Caregiving Self-Efficacy, a measure of confidence regarding caring activities, showed a trend toward improved confidence.

Table 5

Discussion

Feasibility of the Intervention

We evaluated the feasibility of soliciting acceptable answers to informational and emotional questions through the Facebook News Feeds of caregivers. Based on participation and qualitative feedback from participants, our study found friendsourcing to be a feasible Web-based intervention for AD caregivers. Our online support group and app successfully facilitated "pushing" caregiver questions to the Facebook News Feed of participants, allowing their Facebook friends to see and answer these questions. We compared friendsourcing versus crowdsourcing answers to caregiver questions. Both provided acceptable answers as judged by content experts, as well as similar rates of informational and emotional support messages. However, we consistently found that friendsourcing provided significantly higher rates of shared experiences as compared with crowdsourcing.

While this approach was feasible to collect acceptable answers in the short term, sustainability is an important concern for social-microvolunteering systems [ 39]. For this system to succeed in a full deployment, it would require a reliable set of answerers, and the quality of responses would need to be maintained despite the potential for answerer fatigue. This needs to be explored further in future studies.

Central to obtaining support and responding to demands for coping is the shared experience of group membership. Shared experience has been identified as the basis for engagement in peer support groups, because peers can provide a level of support that may be unavailable through natural supports like family and friends [ 52]. We designed our Web-based support intervention to include friendsourcing rather than crowdsourcing, for reasons of greater financial affordability and greater potential for shared experiences.

Limitations

Low sample size was a drawback of this study and limits the generalizability of our results. Our study was too small to determine the effectiveness of the intervention on caregiver outcomes. However, we noted that data trended toward an improvement in caregiver self-efficacy, sense of support, and perceived stress.

The generalizability of the populations who provided the friendsourced and crowdsourced answers may also be limited. Members of crowdsourcing platforms, specifically those on Mechanical Turk, are likely to be more educated than the average US population [ 53]. Any of a user's Facebook friends are most likely to be the same age as the user, demonstrating the homophily of networks around age [ 54]. As a result, a caregiver's network may be composed of more adults with an age demographic more likely to deal with AD in their spouses or parents. Users of Mechanical Turk have traditionally skewed younger [ 55, 56], and recent estimates found that 88% of workers were 49 years or younger [ 55]. Thus, these workers may not have as much experience with AD.

The duration of this study was relatively brief at 6 weeks. It is unclear whether a longer trial of an online support group and friendsourced answers would provide a greater benefit for AD caregivers. However, Rains and Young's 2009 meta-analysis of peer support group outcomes suggest a longer trial would provide greater benefits to caregivers [ 57].

Friendsourcing Versus Crowdsourcing

To the best of our knowledge, our study is the first to examine friendsourcing and crowdsourcing as a tool to support caregivers of people with AD. Studies have looked at medical and behavioral science applications of crowdsourcing. Yu et al found that medical pictogram responses from the crowdsourcing platform Mechanical Turk were comparable with responses solicited in laboratory studies [ 47]. They concluded that the platform could be used as a low-cost alternative to traditional experimental studies. Other work has found similar results in using Mechanical Turk as a venue to collect survey responses [ 58], run behavioral experiments [ 59], collect natural language samples [ 60], and build more complex algorithms that leverage human computation [ 61].

Social Media for Caregivers and Emotional Support

With the changes brought by Web 2.0, social media became another means of collecting health care information [ 62]. Facebook remains the most widely used social media platform among the 73% of online adults who use a social networking website [ 63]. A few of the benefits of using social media as reported by adults seeking health care information are interactions with others with the same condition, increased availability of information, and emotional support [ 52, 64]. Tailoring information and experience to suit personal needs is another benefit that draws users [ 52]. Caregiver use of the Internet and social media is greater than that of noncaregivers. In a survey of caregivers' online health behaviors, caregivers used the Internet to obtain health information more than noncaregivers, at 72% and 50%, respectively [ 65]. In the same survey, 52% of caregivers participated in online social activity as compared with 33% of noncaregivers. [ 65].

Online peer support groups provide caregivers with a common platform to address emotional needs [ 66, 67]. In addition to being able to share personal problems and stories and to seek advice in an easy-to-access venue, caregivers also feel empowered by the group experience that affords intimacy and bonding [ 67]. Colvin et al reported that the anonymity afforded by Internet-based social support made users more comfortable with using online support groups as compared with their face-to-face alternatives [ 68]. Also, the asynchronous and immediate availability of information or answers to questions accommodate caregiving needs, such as not having to leave the care recipient and finding answers faster.

Ethical Considerations

The collaborative nature of social media leads to information collated from disparate sources, which could be inconsistent with a health care professional's knowledge and opinions. Peer-to-peer communication does not ensure the regulation and validity of information. Users often report that they crosschecked information online or waited for consensus to develop in a group before they regard a piece of information as credible [ 69]. The task of processing large volumes of online information and deriving insights falls on the users. Medical providers often express concerns that inaccurate health information will be shared in online communities [ 70]. Most online communities address this issue through online moderation.

For many online communities, moderation is limited to policing of requests for answers to clinical questions. In these situations, moderators will typically close a post and indicate to a user that he or she should see his or her doctor to address this question or a "SeeDoc" thread [ 29]. Downsides to this approach include missed opportunities for sharing of experiences, informational support, and emotional support. Some authors argue that peers offer an expertise distinct from the medical expertise of health care professionals [ 71].

In unmoderated online peer support groups, nonparticipation or reading-without-posting behavior has been identified as a drawback that reduces overall group interaction and the development of mutual aid [ 30]. With our study design, we showed that an online social media peer support group was feasible. Moderation in our study reduced reading-without-posting behavior.

Future Research

Work presented here included the limited analysis of the first group of our study cohort. Following completion of the project (2 more groups), we hope to gain further insights into how member interaction is influenced by friendsourced answers. We are also interested in learning how caregiver outcomes may be modified by an online support group and friendsourced support.

A similar study with a larger sample size and longer intervention is needed to determine the effectiveness of the intervention on caregiver outcomes and the overall sustainability of the intervention. Determination of effectiveness would also allow for comparisons with other existing caregiver interventions. We believe there would be value in adding caregiver mental health outcomes to future studies, as a modification of these outcomes by either crowdsourcing or friendsourcing could have wide implications. Additionally, it would be helpful to redesign the study to allow for a systematic comparison of support received from crowdsourcing, friendsourcing, and interactions between group members. Further study of the extended networks and the impact of ad hoc supportive members is also needed. In future work, we plan to complete a qualitative analysis of the open-ended questions answered in the preintervention and postintervention study interviews.

Friendsourcing and crowdsourcing offer new opportunities for caregivers of people with AD to receive informational and emotional support; however, concerns still exist around delivery of inaccurate health information. More work needs to be done to assess the quality of information received through these platforms. The growth of social media and online health community participation in the United States make the need for this work even more important, as people are likely to continue to use these online venues.

Conclusions

We found this asynchronous, online, closed group on Facebook to be generally acceptable by the peer support group studied as a means to deliver support to AD caregivers. Implications could be wide reaching if larger studies find a significant impact on caregiver outcomes, as a similar intervention could be applied to caregivers of other diseases, such as cancer, serious mental illness, and developmental disabilities.

Both friendsourcing and crowdsourcing displayed potential as novel delivery methods of emotional and informational support to AD caregivers. Friendsourced answers demonstrated higher rates of shared experiences, which suggests that friendsourcing may be superior.

Acknowledgments

This work was funded by an Innovations grant from The Regenstrief Institute. We would like to especially thank Bill Bennett, Alita Pinto, Richard Holden PhD, and Hugh Hendrie MB ChB DSc.

Abbreviations

Footnotes

Conflicts of Interest: None declared.

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Comparing Crowdsourcing and Friendsourcing: A Social Media-Based Feasibility Study to Support Alzheimer Disease Caregivers

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Monitoring Editor: Gunther Eysenbach Reviewed by Bei Yu, Tanjir Rashid Soron, and Itzhak Tabatchnik Daniel Robert Bateman, MD, 1 2, 3, 4 Erin Brady, MSc, PhD, 1, 3, 5 David Wilkerson, LICSW, PhD, 1, 3, 6 Eun-Hye Yi, MSW, 1, 3, 6 Yamini Karanam, BS, 5 and Christopher M Callahan, MD 1, 3, 4, 7 In the United States, over 15 million informal caregivers provide unpaid care to people with Alzheimer disease (AD).

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Abstract

Alzheimer disease (AD), Frontotemporal lobar degeneration (FTD), Amyotrophic lateral sclerosis (ALS) and Parkinson disease (PD) have a certain degree of clinical, pathological and molecular overlap. Previous studies indicate that causative mutations in AD and FTD/ALS genes can be found in clinical familial AD. We examined the presence of causative and low frequency coding variants in the AD, FTD, ALS and PD Mendelian genes, in over 450 families with clinical history of AD and over 11,710 sporadic cases and cognitive normal participants from North America. Known pathogenic mutations were found in 1.05% of the sporadic cases, in 0.69% of the cognitively normal participants and in 4.22% of the families. A trend towards enrichment, albeit non-significant, was observed for most AD, FTD and PD genes. Only PSEN1 and PINK1 showed consistent association with AD cases when we used ExAC as the control population. These results suggest that current study designs may contain heterogeneity and contamination of the control population, and that current statistical methods for the discovery of novel genes with real pathogenic variants in complex late onset diseases may be inadequate or underpowered to identify genes carrying pathogenic mutations.

Author summary

In this study we provide further genetic evidence of the clinical, pathological and molecular overlap between neurodegenerative diseases. We screened the known Mendelian genes in Alzheimer disease (AD), Frontotemporal Dementia (FTD), Parkinson disease (PD) and Amyotrophic Lateral Sclerosis (ALS) disease in over 13,292 individuals. We report the presence of known pathogenic mutations in AD, FTD and PD genes in both sporadic and familial late onset AD cases and even cognitively normal individuals, pointing to contamination of control cohorts with asymptomatic cases. We also observed an enrichment, although not statistically significant, in most of AD, FTD and PD genes, reinforcing the idea of pathologic crossover among these diseases. However, the fact that genes carrying known pathogenic mutation do not show significant association calls for a reevaluation of current statistical methods.

Introduction

Neurodegenerative diseases like Alzheimer Disease (AD), Frontotemporal dementia (FTD), Parkinson disease (PD) and Amyotrophic Lateral Sclerosis (ALS) share clinical and pathologic features. Dementia is characteristic of AD and FTD, but may also present in PD and ALS [ 1]. In all these diseases we can observe two types of manifestations, either a rare and following Mendelian inheritance, or a more common seemingly non-familial representation [ 2]. All these diseases share the pathologic hallmark of presenting protein aggregates in different areas of the central nervous system. The rare familial forms have been key to our understanding of each disease's pathology; these are well characterized by a dominant pathologic protein aggregate in a specific location within the nervous system caused by the impairment of a specific set of genes [ 2]. However, a clinical, and pathological crossover has been observed in the idiopathic forms [ 3] allowing for the assumption that different types of dementia may have overlapping genetic causes.

AD is the most common neurodegenerative disease affecting over 5.5 million Americans [ 4]. AD's main pathologic hallmark is the extracellular deposit of β-amyloid plaques, followed by the presence of intracellular aggregates of neurofibrillary tangles of phosphorylated tau protein ( MAPT). Pathogenic variants in APP, PSEN1 and PSEN2 were thought to exclusively cause early onset familial AD (EOFAD) [ 5], but the screening of some late onset families and even sporadic cases, revealed that the contribution of familial genetic variants in APP, PSEN1 and PSEN2 in idiopathic cases cannot be neglected [ 6- 8].

Intracellular aggregates of hyperphosphorylated tau (encoded by MAPT) is the second neuropathological hallmark of AD. Tau aggregates also characterize a subgroup of FTD cases (FTD-Tau) in which genetic linkage to MAPT was found [ 9]. The discovery of the gene involved in tau deposits stimulated a series of studies seeking association between polymorphisms within MAPT and AD. Preliminary studies investigating the genetic relationship between MAPT and AD produced contradictory results [ 10, 11] although the latest reports provide more compelling evidence that common variants in the MAPT region confer risk for AD, particularly in cases who are non-carriers of the APOE ε4 allele [ 11- 15]. Other familial FTD cases that are negative for tau protein aggregates present ubiquitin inmunoreactivity (FTD-U), which was initially associated with genetic variants in GRN [ 16]. Together with MAPT, GRN genetic variants cause up to 50% of familial FTD cases, but GRN genetic variants have also been regarded as risk factors for AD [ 17- 20]. Other familial genes later associated with FTD-U subtypes are C9ORF72, TARDBP, VCP, CHMP2B, UBQLN2 and FUS [ 21]. A hexanucelotide repeat expansion in C9ORF72 was identified as major risk factor for FTD [ 22, 23] although its pathogenicity towards ubiquitin reactive deposits is not well understood. C9ORF72 is also the most common risk factor for familial ALS [ 24, 25] and multiple studies have reported clinical AD cases with the full C9ORF72 expansion [ 26- 29], extending the possible genetic continuum from AD to FTD and ALS. Shared genetic variants between FTD and ALS have been found in TARDBP, VCP, UBQLN2 and FUS [ 30- 35] but their association with AD has not yet been reported. Other than the shared variants with FTD, the majority of familial ALS is caused by mutations in SOD1 [ 36, 37]. Recently, mutations in OPTN, and PFN1 have been reported in ALS kindreds [ 37]. No associations have yet been reported between ALS genes and AD pathology, despite some attempts to demonstrate an association between common SOD1 variants and AD under the paradigm of a common oxidative stress pathway [ 38].

Finally, although AD is primarily characterized by cognitive deficits and PD by motor impairment, a clinical and pathological cross-over has been identified in several instances by the presence of dementia in PD patients [ 39] and motor symptoms in AD patients [ 40]. Pathologically, tau aggregates can be present to different degrees in sporadic PD [ 41] and more than 50% of people with AD show α-synuclein aggregates [ 41]. Lewy bodies, composed of α-synuclein aggregates, the pathological hallmark of PD, are attributed to pathogenic variants in the SNCA gene; although genetic variants in LRRK2, PARK2, PARK7 and PINK1 have also been linked to familial PD [ 42]. Combined meta-analysis of AD and PD GWAS revealed the lack of variants that increase the risk of developing both diseases [ 43]; although later on, a genetic overlap between AD and PD at the MAPT locus was detected [ 44] and recent studies have detected pathogenic PARK2 mutations in sporadic early onset AD cases [ 15].

A genetic overlap among all these neurodegenerative diseases cannot be ignored, and may certainly be underestimated since most of the previous studies performed either two by two gene/disease analysis, which does not cover the full spectrum of genes, or GWAS, which does not cover genetic variants across the frequency spectrum.

In a previous work we reported an enrichment of known pathogenic and novel rare variants in APP, PSEN1, PSEN2, GRN and MAPT in LOAD families [ 45]. In this work, we expanded our analysis to a thorough examination of all genes known to cause Mendelian forms of AD, FTD, ALS, and PD. We evaluate the presence of rare and nonsynonymous genetic variants in these 30 genes not only in a large independent familial dataset (467 families), but also in two large sporadic cohorts, 851 in-house sporadic AD cases and controls and in the sporadic ADSP (Alzheimer Disease Sequencing Project) dataset ( https://www.niagads.org/adsp/content/home, accessed August 2016).

Results

We identified 36 reported pathogenic Mendelian variants in 11 genes ( APP, PSEN1, PSEN2, GRN, MAPT, TARDBP, VCP, C9ORF72, LRRK2, PARK2, and PINK1) across the three datasets examined (). Fifteen variants were found in 41 subjects (2.6%) from 19 different families; 9 variants across 17 individuals (2.59% of cases and 1.59% of controls) from the Knight-ADRC-NIA-LOAD (KANL) sporadic dataset; and 25 variants across 85 individuals (0.94% of cases and 0.63% of controls) from the ADSP sporadic dataset (). The prevalence of genetic variants between the sporadic and familial datasets tends to be higher in cases with strong family history compared to the sporadic. In the AD genes 1.56% of the families, 0.94% of the KANL sporadic cases, 0.27% of the KANL sporadic controls, 0.30% of the ADSP sporadic cases and 0.13% of the ADSP sporadic controls carried a previously reported pathogenic variant. It was similar for FTD genes in which 0.88% families, 0.24% of the KANL sporadic cases, 0.24% of the KANL sporadic controls, 0.24% of the ADSP sporadic cases and 0.02% of the ADSP sporadic controls carried a pathogenic variant. The C9ORF72 mutation is an intronic hexanucleotide repeat that cannot be called by WES or WGS; therefore, we could not use the sequence data to call this variant. We genotyped this variant by repeat-primed PCR in a subset of unrelated 819 AD cases and 502 controls from the Knight-ADRC and in 872 unrelated familial AD cases from the NIA-LOAD dataset. We found the repeat expansion in 0.85% of the unrelated cases and 0.57% of the families (10 individuals in total) carry the C9ORF72 repeat expansion. Interestingly, reported pathogenic mutations in PD genes were found as much or even more frequent than AD mutations, especially within the ADSP dataset. These mutations were found in eight families (1.77%), seven (0.87%) sporadic KANL, and up to 46 (0.42%) individuals from the sporadic ADSP.

Table 1

In order to evaluate whether there was a differential finding of pathogenic variants between cohorts, KANL and ADSP, we performed Chi-Squared and Fisher statistics. We used the unrelated KANL dataset and the sporadic ADSP to run association and Fisher analysis for the variants in using Plink1.9. None of the examined variants showed differential frequency between datasets except for PARK2 p.(Glu34fs), which was nominally more frequent in the unrelated dataset ( S2 Table). Using the familial dataset, we could evaluate the segregation pattern and penetrance of these variants ().

Table 2

Known AD pathogenic variants

Mutations in Mendelian AD genes are known to be autosomal dominant with complete penetrance; but we found that the variants identified in this study did not always present complete penetrance or segregate perfectly with disease status (). First, the pathogenic variant PSEN1 p.(Ala79Val) [ 46] was detected in a 67 yrs control from a large family with several affected members and an average AAO around the seventies (Fam #1). Genotyping of the mutation in up to 19 members of the family indicated incomplete penetrance (), given the presence of phenocopies and some non-affected carriers, possible presymptomatic cases. In addition, this variant was found in seven cases from the ADSP dataset with an average AAO of 68 yrs. The pathogenic variant PSEN1 p.(Leu85Pro) [ 47] was detected in a family of four affected and two non-demented individuals (Fam #2), but only one of the affected individuals was a carrier of the genetic variant. The pathogenic variant PSEN1 p.(Gly206Ala) [ 48] was found in one case of an AAO 55 yrs, self-reported Caribbean origin (Fam #3). This variant was originally reported in 194 families of Caribbean Hispanic origin [ 48, 49]. We also detected this variant in four cases from the sporadic ADSP dataset, one of European American origin (AAO = 63) and three with Hispanic ethnicity (mean AAO = 70). Variant PSEN2 p.(Asn141Ile), also pathogenic [ 51], was detected in one family (Fam #5) and in one sporadic case (AAO = 53) of the KANL cohort. However, after further examination of the clinical history of this participant we detected a reported family history of dementia (Supplementary results). Variant PSEN2 p.(Met174Val) [ 52] was detected in two families: Fam #6 was composed of six affected individuals and one diagnosed as non-demented. Only one affected and the cognitively-normal family members were carriers of the variant (). Similarly, Fam #7 has five affected members and three cognitively normal members, in which only one cognitively normal member (the marry-in) was a carrier of the reported pathogenic variant. This variant was also observed in one control of the KANL sporadic dataset (ALA = 72) and in two cases (mean AAO = 82) and four cognitively normal (64, 63, 84 and 85 yrs ALA) individuals from the sporadic ADSP dataset.

Together these results suggest that previously reported pathogenic variants in Mendelian AD genes may present imperfect segregation, given the existence of phenocopies (Fam #1, Fam #6); and/or incomplete penetrance due to the presence of older cognitive normal carriers that may carry additional modifying factors. Also, their finding within the sporadic cohorts calls for a reexamination of the non-affected carriers as possible presymptomatic individuals.

Known pathogenic variants in these genes were also observed exclusively within the "sporadic" datasets. Two affected individuals of the sporadic KANL cohort with age at onset (AAO) in their 50s were carriers of a known pathogenic APP variant, p.(Ile716Val) [ 53]; and variant APP p.(Val717Phe) [ 54] was found in one affected individual (AAO = 70) of the ADSP cohort. The PSEN1 variant p.(Leu226Arg) [ 55] was detected in one affected participant (AAO = 51) of the KANL cohort; variants PSEN1 p.(His214Tyr) [ 56] and p.(Val412Ile) [ 57] were found in two cases (85 yrs and 84 yrs AAO) and variant p.(Ala409Thr) [ 58] was found in one cognitively normal participant (ALA = 89) of the ADSP cohort. PSEN2 variant p.(Ala85Val) [ 59] was detected in one cognitively normal participant (ALA = 89) and variant p.(Leu238Pro) [ 60] was found in two cases (80 and 63 yrs AAO) of the ADSP cohort.

Known FTD pathogenic variants

Mutations in FTD genes are also known to segregate in a dominant pattern. Among the seven FTD genes examined, we observed four pathogenic variants in GRN, three pathogenic variants in MAPT, two variants in TARDBP and one pathogenic variant in VCP. We also found the repeat expansion C9ORF72 in several unrelated cases (0.85%) and in 10 individuals with family history.

The GRN variant p.(Arg110*) [ 61] was present in three siblings and one cousin of a family with a history of reported AD (Fam #8, ), but only three of the affected members were carriers of the genetic variant. This variant was also detected in one affected participant (AAO = 74) of the ADSP cohort. The GRN variant p.(Thr382fs) [ 62] was detected in a female AAO 60 yr with an AD diagnosis from the sporadic dataset. After examination of her clinical history it was discovered that she had two siblings and one cousin diagnosed with dementia (Fam #9). Genotyping of this variant in six family members revealed that the genetic variant was present in all members affected by dementia, and one young cognitively normal participant (ALA = 65). Pathology reports available indicated that the index individual had AD pathology and Pick bodies with a frontotemporal lobar atrophy pattern consistent with Pick's disease; and the two siblings were later pathologically diagnosed as FTD and as non-AD dementia. Two other variants in GRN p.(Arg493*) [ 63] and p.(Cys521Tyr) [ 64] were detected in the sporadic ADSP cohort: GRN p.(Arg43*) was found in 4 affected participants (average AAO = 73) and p.(Cys521Tyr) was found in 2 affected participants (average AAO = 82.5). The incomplete penetrance observed for GRN within the families can be the result of phenocopies (Fam #8) or presymptomatic cases (Fam #9).

The MAPT variant p.(Gly389Arg) [ 65] was found in one cognitively normal participant (ALA = 91) from the ADSP cohort. MAPT variant p.(Arg406Trp) [ 66] was detected in two participants of the sporadic dataset, both cognitively normal in their 60s with no symptoms of presymptomatic AD (not by imaging or CSF Aβ levels). MAPT variant p.(Gln424Lys) (personal communication in 2005 by Brice to AD&FTDMDB Curator) was detected in one family (Fam #10) in which three of the five affected members were carriers of the variant.

Variants in TARDBP were exclusively found in the ADSP cohort. Variant p.(Asn267Ser) [ 67] was detected in two affected members (Average AAO = 77) and variant p.(Asn390Ser) [ 68] was detected in one affected member with AAO 74 yrs.

The VCP variant p.(Arg155His) [ 69] was detected in Fam #11 but segregation could not be performed since DNA was only available for one of the affected members.

Known PD pathogenic variants

Mutations in PD genes present different patterns of segregation; SNCA and LRKK2 are known to cause dominantly inherited PD, whereas PARK2, PARK7 and PINK1 are known to cause early onset PD with a recessive inheritance mode [ 70]. We detected 10 different known pathogenic PD variants in LRKK2, PARK2 and PINK1, in 70 different carriers, all of whom were heterozygous for the variant. One LRRK2 variant, p.(Gly2019Ser) [ 71], was only present in two families (Fam #12, Fam #13). Fam #12 includes five members, four diagnosed with AD (two carriers) and one cognitively normal (a carrier heterozygous for p.(Gly2019Ser)). Fam #13 is composed of two affected individuals (one carrier) and two cognitively normal (no carriers). Mutations in the LRRK2 gene are the most common genetic cause of PD; but this gene is also known to have pleomorphic pathology [ 72] and the penetrance of the variant p.(Gly2019Ser) is known to vary in different populations and ages [ 73], so, the incomplete penetrance observed here is not surprising.

Seven variants were detected in PARK2: p.(Gln34fs) [ 74] was found in one case (AAO = 79) from Fam #14 although the other case was a non-carrier, in two affected participants (AAO of 31 and 82 yrs) of the KANL sporadic dataset, and in three cases (average AAO = 83) and three cognitive normal participants (average ALA = 86) from ADSP. PARK2 variant p.(Pro113fs) [ 75] was present in four of 10 cases from three families (Fam #15, Fam #16, Fam #17) and in two cases (AAO 73 and 83 yrs) and two cognitively normal (ALA 64 and 87) participants of the ADSP cohort. In our study, variant PARK2 p.(Met192Leu) [ 76] was the most common of the PD mutations. All four members from Fam #18 (three cases and one control) were carriers of the genetic variant, as was the case from Fam #19 (AAO = 55). Within the KANL this variant was found in one affected (AAO = 64) and one cognitively normal (ALA = 68) member. Up to 13 affected carriers (Average AAO = 88±7) and 11 cognitively normal carriers (average ALA = 84±5) were detected in the ADSP cohort. Four other variants in PARK2 were exclusively found in the sporadic cohorts. Variant p.(Thr240Met) [ 77] was detected in one affected (AAO = 77) and one cognitively normal (ALA = 64) member of the KANL sporadic cohort, and in three affected (average AAO = 82±10) and two cognitively normal (average ALA = 88) members of the ADSP sporadic cohort. PARK2 variants p.(Leu238Pro) [ 78] and p.(Gly430Asp) [ 76] were found in the same cognitively normal individual of the ADSP cohort (ALA = 68), whereas PARK p.(Arg366Trp) [ 79] was found in two non-affected carriers (average ALA = 65) from the KANL sporadic cohort.

Finally, two variants were detected in PINK1. Variant p.(Arg464His) was found in one affected (AAO = 86) participant of the ADSP cohort. Variant p.(Arg492*) [ 80] was present in only one case (AAO = 68) and one cognitively normal (ALA = 73) member from Fam #20, and in one affected (AAO = 65) and three non-affected (ALA 73,86,88) individuals from the ADSP cohort.

Mutations in PARK2 and PINK1 are known to cause early onset PD (AAO range 12-58 yr) with a recessive pattern of inheritance. Segregation could not be determined in our study due to lack of familial stages. With the exception of the case in Fam #20 (AAO of 55), the individuals reported here all had an AAO > 60, suggesting that these PARK2 and PINK1 variants would be modifiers rather than causative of AD. For a full description of all known pathogenic variants detected, see Supplementary Results.

Gene based analysis

Once we confirmed that known pathogenic mutations in the AD, FTD and PD genes can be found in sporadic as well as in late-onset familial samples, we wanted to determine if an overall increase of low frequency non-synonymous coding variants can be found in these genes in AD cases compared to cognitively normal participants. We performed this analysis in our unrelated dataset and in the sporadic ADSP dataset. The cases in the unrelated KANL dataset present a larger enrichment of rare pathogenic variants compared to the cases of the sporadic ADSP dataset (). In both datasets, the enrichment increases when we focus on very rare non-synonymous variants (). None of these enrichments was significant after multiple test correction, but we observe some suggestive and nominally significant results.

Within the unrelated KANL cohort we found CHMP2B (OR = 2.24, P = 0.06) and VPS35 (OR = 6.77, P = 0.05) to have suggestive significance-values, and EIF4G1 (OR = 1.71, P = 0.01) to be nominally significant for rare variants, those with minor allele frequency below 1% and a predicted high or moderate effect on the final protein (MAF≤1% HM). Also, the global effect of AD genes ( APP, PSEN1 and PSEN2) was nominally significant (OR = 2.31, P = 0.028) if we considered only very rare variants, those with just one allele count in the population and a predicted high or moderate effect on the final protein (AC1 HM).

The enriched effect of CHMP2B remained significant when we considered only APOE ε4 carriers; some of the AD genes became nominally significant (e.g. APP and PSEN2) and the global effect of AD genes resulted in nominal significance for rare variants and significant after multiple test correction (Total AD, OR = 14.76, P = 1.83×10 −4) when we considered very rare variants ( S3 Table). EIF4G1 remained nominally significant (OR = 2.01, P = 0.02) for the set of APOE ε4 non-carriers; FBXO7 became nominally significant (OR = 3.09, P = 0.03) and VPS35 gained suggestive significance (OR = 7.05, P = 0.06) within the set of rare variants (MAF≤1% HM). In addition, the global effect of very rare variants (AC1 HM) from FTD genes was also nominally significantly associated (OR = 1.84, P = 0.04) with APOE ε4 non-carriers ( S4 Table).

Within the sporadic ADSP cohort, none of the enriched genes presented significant p-values (). However, PSEN1 resulted in nominally significant association with the APOE ε4 non-carrier for both sets, rare (OR = 2.14, P = 0.05) and very rare variants (OR = 2.76, P = 0.02) ( S3 Table).

Because the lack of significant associations could be due to the sample size, we decided to perform gene-based analyses comparing all the unrelated KANL cases (n = 672) or the sporadic ADSP cases (N = 5,679) with the non-Finnish European (NFE) ExAC population as a cognitive normal dataset (n = 33,000). The coverage of the tested genes in ExAC and in our population is comparable. PSEN1 appeared as nominally significantly enriched in these two cohort cases for the set of rare variants (MAF≤1% HM); and it was statistically significant for sporadic ADSP cases within the very rare set of variants (OR = 3.134, P = 3.34×10⁻⁵). Interestingly, PINK1 appeared as significantly associated with the unrelated cases examined regardless of the set of variants tested. EIF4G1 also remained significantly associated with unrelated KANL cases within the rare variants subset (OR = 1.69, P = 8.96×10 −4) and for sporadic ADSP cases within the very rare set of variants ( S5 Table). No statistical association was found for the overall AD, FTD and PD genes in either the KALN or ADSP dataset ( S5 Table).

Discussion

Recent reports indicate that rare variants in AD Mendelian genes, APP, PSEN1 and PSEN2, cause, contribute and modify risk for AD [ 12, 45]. Given the clinical and pathologic overlap between AD and other common neurodegenerative diseases, a genetic contribution toward AD risk by genes involved in other diseases has been sought for some time now. However, because of their rarity, contributions towards disease at a genome-wide level of significance are difficult to achieve without large cohorts and well characterized populations. This is the first study that thoroughly screens for pathogenic mutations in known neurodegenerative genes and evaluates the contribution of low frequency variants in these genes towards AD in a large cohort of sporadic and densely affected LOAD families.

In previous studies, we sequenced APP, PSEN1, PSEN2, GRN, MAPT and C9ORF72 in late-onset families and detected known pathogenic mutations in 2.9% of the families [ 45, 81]. In this study, we detected 10 families (2.2%) with carriers of a known pathogenic mutation in APP, PSEN1, PSEN2, GRN or MAPT, and an additional 0.57% of the families with the C9ORF72 repeat. Overall, 0.82% fLOAD participants carried a mutation in AD genes, and 0.63% of them carried a mutation in FTD genes.

This study extends previous findings to sporadic cases, from two different cohorts: sporadic cases from the Knight-ADRC (KANL) and late-onset cases and cognitively normal participants from the ADSP. We found that 0.87% of the KANL participants carry a known pathogenic mutation in AD (0.94% of cases and 0.27% of controls) and FTD (0.24% of cases and 0.27% of controls) genes, and 0.36% of the ADSP participants carry a known pathogenic mutation in AD (0.30% of cases and 0.13% of controls) and FTD (0.24% of cases and 0.02% of controls%) genes. This suggests that it is possible to find known pathogenic mutations of AD and FTD genes in familial LOAD as well as sporadic AD with the same probability. Another important finding is that we found a similar portion of cases and families with a mutation in the AD genes vs the FTD genes. Mutations in AD genes were found in 0.82% of fLOAD participants and FTD genes in 0.63% of that population. It is important to note that we found that 0.85% of the sporadic KANL cases had the C9ORF72 expansion repeat that had to be genotyped independently, because current sequencing methods are not able to capture this variant. Nonetheless, the proportion of individuals with FTD genes in the ADSP dataset is underestimated because we could not screen for the C9ORF72 repeat. It is also important to note that known pathogenic mutations were found in the cognitive normal participants. For this analysis, we only focused on known and well characterized pathogenic mutations. Those variants were classified as pathogenic because they were initially found in early-onset cases, segregated with disease status, were not present in the general population and/or functional analyses confirmed that those variants are pathogenic.

The clinical complexity of dementias has raised speculation that many other neurological diseases are misdiagnosed as AD [ 82]. In several previous studies there has been the suspicion for FTD to masquerade clinically as AD [ 57, 83]; therefore it could be argued that the detection of known FTD pathogenic variants ( GRN-p.(Arg110*) and GRN- p.(Thr382fs)), or C9ORF72 in the KANL cohort is due to the presence of misclassified FTD cases. Autopsy reports from some members of these families describe pathological variability among the affected carriers, with some members presenting with AD and Pick body pathology, and others presenting with "frontotemporal nonspecific neuropathology". Hence, instead of misclassified cases, we may be facing a pleomorphic pathology of these GRN variants, an issue observed previously, specifically in familial FTD [ 84]. This pleomorphism is expanded by the recent association of GRN rare variants in autopsy confirmed cases with Lewy Body dementia (LBD) [ 85].

Pleomorphic pathology has also been described in several instances for LRKK2 genetic variants [ 42, 71] which, other than being the most common cause for autosomal late onset PD, has also been associated with tau pathology and AD [ 86, 87]. The finding here of a LRRK2 genetic variant p.(Gly2019Ser) (Fam #13) in a clinically diagnosed AD case would amplify the pleomorphic range of LRRK2 variants. Alternatively, it could be that the pathogenic PD variants observed in LRRK2, PARK2 and PINK1 could be misdiagnosed cases of LBD. LBD may initially present with cognitive impairment and be misdiagnosed as AD, or as PD if it starts with parkinsonism. In addition, Lewy bodies, sometimes present in AD, are hallmarks of DLB and PD, and Aβ plaques and Tau tangles often coexist in LBD and PD, for which a synergy and a genetic correlation among these three conditions has been suggested [ 88- 90].

We have observed that variants usually regarded as causing pure early onset forms of AD, FTD, PD or ALS can be associated with a wide pathological spectrum. They may also present to different extent in families with a late onset. Both highly penetrant variants ( GRN-p.(Arg110*)), and others with mild penetrance ( PSEN2 -p.(Met174Val)) have been observed. Incomplete penetrance can be (in some instances) explained by the presence of pre-symptomatic cases; but the presence of phenocopies also suggests that the penetrance may not be as high as previously thought. (, Fam #6). There are reported cases in which autosomal dominant AD variants present with a later AAO and clinically mimic LOAD [ 91]. The observed genetic overlap of AD with other neurodegenerative diseases suggests that future studies focused on gene discovery for AD using late onset families should not rely solely on segregation patterns; additional methods that take into account endophenotypes, gene-networks and pathway analysis need to be developed and implemented in routine analysis.

The confirmation that pathogenic variants in causal Mendelian genes are found in late onset individuals, with or without family history, serves to model the system and alert us as to what we might expect of other genes that potentially carry pathogenic mutations. We observed an enrichment, although not statistically significant, in most of AD, FTD and PD genes in both KANL and ADSP cohorts. The pathological cross-over with ALS genes would not be so obvious despite the significant association reported between ADSP cases when compared to ExAC population. Nevertheless, from the results of this study we can observe that there are certainly molecular crossovers between AD, FTD, PD and ALS that point towards common etiologic pathways. These gene-based analyses performed suggest an enrichment of non-synonymous rare variants in these Mendelian genes in the cases of both cohorts, KANL and ADSP; this enrichment is stronger when we only consider very rare variants (AC1 HM), although none of the analysis was statistically significant. Only PSEN1 and PINK1 showed a consistent and steady association pattern when we compared the cases from KANL or ADSP against ExAC as cognitive normals. Therefore, the lack of genome-wide significant p-value could be due to power, but other alternative explanations exist. One possibility is that given the late onset appearance of the disease we may be including many potential asymptomatic cases among the cognitively normal cohorts, as we see in some of the families evaluated (Fam #1) and by the identification of sporadic cognitive normals below 70 yrs who are carriers of pathogenic mutations (e.g. APP variants p.(Ile716Val) and p.(Val717Phe)). This leads to a reevaluation of current study designs; first, more pathologically confirmed elderly cognitive normals should be incorporated and prioritized. Second, more extensive preliminary screenings should be in place for proper genetic counselling and screening of families before incorporating individuals into studies looking for novel genetic causes. Another possibility is that current analytical and statistical methods are inadequate to detect real causal genes involved in the disease. In this study, we have shown that despite having in our cohort individuals carrying known and causal pathogenic variants, current gene-based analysis would have not detected these genes as implicated in the disease. On the other hand current gene-based methods have been able to find genome-wide p-values for genes enriched for risk, but not pathogenic variants such as APOE, TREM2, PLD3, ABCA7 and SORL1 [ 92- 95].

Study limitations

We would like to conclude by reinforcing that despite the limitations of this study the results obtained are sound and in the expected direction. First, this research is based on clinical AD participants and cognitive normals, so we cannot rule out the presence of presymptomatic cases, comorbidities, phenotypic changes with disease evolution, or even misdiagnoses, as we have already stated. This limits the power of this study to establish causality of the detected pathogenic variants and it could as well be limiting our statistical power and enrichment. Second, sporadic and familial AD are categorically different entities, despite the fact that we believe the genetic architecture and molecular load are largely similar [ 91]. However, the complex and heterogeneous presentation of AD makes it difficult to recruit large cohorts with good phenotypic characterization. Therefore, despite our effort to increase our sample size by creating an unrelated cohort, we are still underpowered to detect significant association for genes that we know are directly involved in the pathogenicity of the disease. Nonetheless, these findings highlight the need to join efforts to gather large sample sizes. Finally, we are also aware that the comparison against ExAC data has some methodological flaws. We even acknowledge the possible presence of pre-symptomatic cases within the Exac database. That is why we only consider those results as illustrative of what could be the genetic load when a larger dataset of cognitive normal participants is available.

Material and methods

Washington University cohort

Samples from the Washington University School of Medicine (WUSM) site included in this study were recruited by either the Charles F. and Joanne Knight Alzheimer's Disease Research Center (Knight-ADRC) at the Washington University School of Medicine in Saint Louis or the National Institute on Aging Genetics Initiative for Late-Onset Alzheimer's Disease (NIA-LOAD). From this point onwards, we will refer to these samples as KANL (Knight-ADRC-NIA-LOAD). This study was approved by each recruiting center's Institutional Review Board. Research was carried out in accordance with the approved protocol. Written informed consent was obtained from participants and their family members by the Clinical and Genetics Core of the Knight ADRC. The approval number for the Knight ADRC Genetics Core family studies is 201104178.

All the cases received a diagnosis of dementia of the Alzheimer's type (DAT), using criteria equivalent to the National Institute of Neurological and Communication Disorders and Stroke-Alzheimer's Disease and Related Disorders Association for probable AD [ 96, 97]. Cognitively normal participants received the same assessment as the cases, and were deemed non-demented. Written consent was obtained from all participants.

ADSP cohort

The Alzheimer's Disease Sequencing Project (ADSP) is a collaborative work of five independent groups across the USA that aims to identify new genomic variants contributing to increased risk for LOAD. ( https://www.niagads.org/adsp/content/home). During the discovery phase, they generated WGS data from members of multiplex AD families and whole exome sequence WES data collected in a large case-control cohort. These data are available to qualified researchers through the database of Genotypes and Phenotypes ( https://www.ncbi.nlm.nih.gov/gap Study Accession: phs000572.v7.p4).

Sequencing

Samples coming from the KANL site were sequenced using either whole-exome sequencing (WES, 83.53%) or whole-genome sequencing (WGS, 16.46%). Exome libraries were prepared using Agilent's SureSelect Human All Exon kits V3 and V5 or Roche VCRome. Both, WES and WGS samples were sequenced on a HiSeq2000 with paired ends reads, with a mean depth of coverage of 50x to 150x for WES and 30x for WGS.

Bioinformatic analysis and QC

We performed joint analysis and quality control (QC) for all samples coming from the KANL site as well as for the ADSP familial study-design downloaded from dbGAP. Whether we started from BAM files or SRA files, all were converted to fastq files. Alignment was conducted against GRCh37.p13 genome reference. Variant calling was performed separately for WES and WGS following GATK's 3.6 Best Practices ( https://www.broadinstitute.org/gatk/) and restricted to Agilent's V5 kit plus a 100 bp of padding added to each capture target end. WGS data was filtered to remove low complexity regions, and regions with excessive depth. Only those variants and indels that fell within the above 99.9% confidence threshold were considered for analysis; additional variant filters included allele-balance (AB = 0.3-0.7), quality depth (QD ≥5 for indels and QD≥2 for SNPs), and missingness (geno = 0.05). Variants out of Hardy Weinberg equilibrium ( P<1x10-6) or with differential missingness between cases and controls, WES and WGS or different sequencing platforms were removed from analysis. In addition, individuals with more than 10% of missing variants and whose genotype data indicated a sex discordant from the clinical database were removed from dataset. Finally, individual and familial relatedness was confirmed using PLINK1.9 ( https://www.cog-genomics.org/plink2/ibd) and an existing GWAS dataset for these individuals. Functional impact and population frequencies of variants were annotated with SnpEff [ 100]. At this point we separated familial from sporadic KANL datasets and generated the unrelated dataset.

For the ADSP case-control dataset we downloaded plink file after alignment, variant calling and QC had been performed to which we performed additional QC. Briefly, we checked for allele-balance (AB = 0.3-0.7) and differential missingness between cases and controls. We used the entire dataset for discovery of pathogenic variants but we later restricted our analysis to individuals with self-reported non-hispanic white ethnicity that we corroborated with PCAs.

Selection of candidate genes, variants and analysis

We focused our analysis on genes and variants reported as pathogenic and causing disease in a Mendelian pattern in AD, FTD, PD or ALS. For AD and FTD we restricted our analysis to those genes listed in the AD&FTD mutation database ( http://www.molgen.vib-ua.be/ADMutations/, accessed November, 2016); particularly, we focused on APP, PSEN1 and PSEN2 for AD and CHMP2B, FUS, GRN, MAPT, TARDBP, TBK1 and VCP for FTD. For PD we started off with those genes and variants listed in the PD mutation database ( http://www.molgen.vib-ua.be/PDMutDB/, accessed November, 2016), namely, LRRK2, PARK2, PARK7, PINK1 and SNCA; we also included UCHL1, ATP13A2, GIGYF2, HTRA2, PLA2G6, FBXO7, VPS35, EIF4G1 and DNAJC16 for being reported as causative of Mendelian PD in several occasions [ 103, 104]. To our knowledge, there is no ALS mutation database so we restricted our analysis to those genes consistently reported in the literature as causative of familial ALS, i.e. SOD1, OPTN, UBQLN2 and PFN1 [ 37]; other familial ALS genes like FUS, VCP, UBQLN2 and SQSTM1 are included as FTD causing.

Acknowledgments

We thank the contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible. This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, and the Departments of Neurology and Psychiatry at Washington University School of Medicine. Members of the National Institute on Aging Late-Onset Alzheimer Disease/National Cell Repository for Alzheimer Disease (NIA-LOAD NCRAD) Family Study Group include the following: Richard Mayeux, MD, MSc; Martin Farlow, MD; Tatiana Foroud, PhD; Kelley Faber, MS; Bradley F. Boeve, MD; Neill R. Graff-Radford, MD; David A. Bennett, MD; Robert A. Sweet, MD; Roger Rosenberg, MD; Thomas D. Bird, MD; Carlos Cruchaga, PhD; and Jeremy M. Silverman, PhD.

Funding Statement

This work was supported by grants from the National Institutes of Health (R01-AG044546, P01-AG003991, and RF1AG053303), the Alzheimer Association (NIRG-11-200110, BAND-14-338165 and BFG-15-362540) and the JPB Foundation. The recruitment and clinical characterization of research participants at Washington University were supported by NIH P50-AG05681, P01-AG03991, and P01-AG026276. Samples from the National Cell Repository for Alzheimer's Disease (NCRAD), which receives government support under a cooperative agreement grant (U24-AG21886) awarded by the National Institute on Aging (NIA), were used in this study. NIALOAD samples were collected under a cooperative agreement grant (U24 AG026395) awarded by the National Institute on Aging. Members of the National Institute on Aging Late-Onset Alzheimer Disease/National Cell Repository for Alzheimer Disease (NIA-LOAD NCRAD) Family Study Group include the following: Richard Mayeux, MD, MSc; Martin Farlow, MD; Tatiana Foroud, PhD; Kelley Faber, MS; Bradley F. Boeve, MD; Neill R. Graff-Radford, MD; David A. Bennett, MD; Robert A. Sweet, MD; Roger Rosenberg, MD; Thomas D. Bird, MD; Carlos Cruchaga, PhD; and Jeremy M. Silverman, PhD. The Alzheimer's Disease Sequencing Project (ADSP) is comprised of two Alzheimer's Disease (AD) genetics consortia and three National Human Genome Research Institute (NHGRI) funded Large Scale Sequencing and Analysis Centers (LSAC). The two AD genetics consortia are the Alzheimer's Disease Genetics Consortium (ADGC) funded by NIA (U01 AG032984), and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) funded by NIA (R01 AG033193), the National Heart, Lung, and Blood Institute (NHLBI), other National Institute of Health (NIH) institutes and other foreign governmental and non-governmental organizations. The Discovery Phase analysis of sequence data is supported through UF1AG047133 (to Drs. Schellenberg, Farrer, Pericak-Vance, Mayeux, and Haines); U01AG049505 to Dr. Seshadri; U01AG049506 to Dr. Boerwinkle; U01AG049507 to Dr. Wijsman; and U01AG049508 to Dr. Goate and the Discovery Extension Phase analysis is supported through U01AG052411 to Dr. Goate and U01AG052410 to Dr. Pericak-Vance. Data generation and harmonization in the Follow-up Phases is supported by U54AG052427 (to Drs. Schellenberg and Wang). The ADGC cohorts include: Adult Changes in Thought (ACT), the Alzheimer's Disease Centers (ADC), the Chicago Health and Aging Project (CHAP), the Memory and Aging Project (MAP), Mayo Clinic (MAYO), Mayo Parkinson's Disease controls, University of Miami, the Multi-Institutional Research in Alzheimer's Genetic Epidemiology Study (MIRAGE), the National Cell Repository for Alzheimer's Disease (NCRAD), the National Institute on Aging Late Onset Alzheimer's Disease Family Study (NIA-LOAD), the Religious Orders Study (ROS), the Texas Alzheimer's Research and Care Consortium (TARC), Vanderbilt University/Case Western Reserve University (VAN/CWRU), the Washington Heights-Inwood Columbia Aging Project (WHICAP) and the Washington University Sequencing Project (WUSP), the Columbia University Hispanic- Estudio Familiar de Influencia Genetica de Alzheimer (EFIGA), the University of Toronto (UT), and Genetic Differences (GD). The CHARGE cohorts, with funding provided by 5RC2HL102419 and HL105756, include the following: Atherosclerosis Risk in Communities (ARIC) Study which is carried out as a collaborative study supported by NHLBI contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), Austrian Stroke Prevention Study (ASPS), Cardiovascular Health Study (CHS), Erasmus Rucphen Family Study (ERF), Framingham Heart Study (FHS), and Rotterdam Study (RS). CHS research was supported by contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and grants U01HL080295 and U01HL130114 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided by R01AG023629, R01AG15928, and R01AG20098 from the National Institute on Aging (NIA). A full list of principal CHS investigators and institutions can be found at CHS-NHLBI.org. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The three LSACs are: the Human Genome Sequencing Center at the Baylor College of Medicine (U54 HG003273), the Broad Institute Genome Center (U54HG003067), and the Washington University Genome Institute (U54HG003079). Biological samples and associated phenotypic data used in primary data analyses were stored at Study Investigators institutions, and at the National Cell Repository for Alzheimer's Disease (NCRAD, U24AG021886) at Indiana University funded by NIA. Associated Phenotypic Data used in primary and secondary data analyses were provided by Study Investigators, the NIA funded Alzheimer's Disease Centers (ADCs), and the National Alzheimer's Coordinating Center (NACC, U01AG016976) and the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS, U24AG041689) at the University of Pennsylvania, funded by NIA, and at the Database for Genotypes and Phenotypes (dbGaP) funded by NIH. This research was supported in part by the Intramural Research Program of the National Institutes of health, National Library of Medicine. Contributors to the Genetic Analysis Data included Study Investigators on projects that were individually funded by NIA, and other NIH institutes, and by private U.S. organizations, or foreign governmental or nongovernmental organizations. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

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Analysis of neurodegenerative Mendelian genes in clinically diagnosed Alzheimer Disease

# data[].attributes.attachment_link.description
Alzheimer disease (AD), Frontotemporal lobar degeneration (FTD), Amyotrophic lateral sclerosis (ALS) and Parkinson disease (PD) have a certain degree of clinical, pathological and molecular overlap. Previous studies indicate that causative mutations in AD and FTD/ALS genes can be found in clinical familial AD.

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Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels

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Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels

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Abstract

Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from ¹⁸F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from ¹⁸F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative. An independent component analysis was applied to the RS-fMRI, followed by template matching to identify neuronal components (NC). A regional brain activity measurement was constructed based on the variation of the RS-fMRI signal of these NC. The standardized glucose uptake values of several brain regions relative to the cerebellum (SUVR) were measured from partial volume corrected FDG-PET images. Comparing the AD and NEC groups, the mean brain activity metric was significantly lower in the accumbens, while the glucose SUVR was significantly lower in the amygdala and hippocampus. The RS-fMRI brain activity metric was positively correlated with cognitive measures and amyloid β ₁₋₄₂ cerebral spinal fluid levels; however, these did not remain significant following Bonferroni correction. There was a significant linear correlation between the brain activity metric and the glucose SUVR measurements. This proof of concept study demonstrates that this novel and easy to implement RS-fMRI brain activity metric can differentiate a group of healthy elderly controls from a group of people with AD.

Introduction

Alzheimer disease is considered to be a progressive neurodegenerative condition clinically characterized by cognitive dysfunction and memory impairments [ 1] that appear to result from the pathological accumulation of amyloid plaques and neurofibrillary tangles [ 2, 3]. Brain atrophy measured by magnetic resonance imaging (MRI) has been established as an important biomarker associated with disease progression and treatment response [ 4- 6]. Another established biomarker is reduced regional uptake of ¹⁸F labeled fluorodeoxyglucose (FDG) measured using positron emission tomography (PET) [ 7], indicating lower glucose metabolism in Alzheimer's disease [ 8, 9].

Neuronal activity can also be inferred from blood oxygen level dependent (BOLD) contrast as exploited in functional MRI (fMRI). More recently, resting state fMRI (RS-fMRI) measures of spontaneous low frequency fluctuations (< 0.1 HZ) in the BOLD signal have been used to identify functionally connected brain regions (networks) without the performance of an overt task [ 10, 11]. Previous studies [ 12, 13] have shown that several resting state networks can be identified, and may be altered in Alzheimer's disease. For example, multiple studies have found RS-fMRI can be used to show disrupted connectivity between the hippocampus and other brain regions in Alzheimer disease [ 13- 15]. Furthermore, the interconnectivity of brain regions can be used to classify subjects with Alzheimer disease, amnestic mild cognitive impairment, and healthy elderly [ 16].

A number of different statistical and mathematic approaches have been used to infer functional connectivity from RS-fMRI data. One common approach is to use the a-priori selection of a seed region of interest (ROI) [ 17- 19] to determine the correlation between the mean BOLD signal time course within the ROI and the BOLD signal time courses of all other pixels in the brain. However the requirement for a-priori seed selection makes it difficult to examine the functional connectivity across the whole brain. Another popular multivariate technique for analyzing whole brain connectivity is independent component analysis (ICA) [ 20- 22]. This approach does not require a-priori information and decomposes the BOLD signal into a set of spatial and temporal components that are maximally statistically independent [ 23]. The ICA method is also an efficient approach to extract scanner noise, as well as physiological and motion artifacts from the BOLD signal [ 24]. One of the major challenges with the ICA technique is to determine which components represent physiologically relevant networks, and which components represent noise. However methods now exist to differentiate neuronal from non-neuronal components [ 25].

Brain regions associated with the default mode network (DMN) have been repeatedly implicated in the pathogenesis of Alzheimer's disease [ 13, 26]. FDG-PET studies have shown reduced glucose metabolism in the medial temporal cortex, hippocampus, and posterior cingulate cortex [ 27- 29]. Decreased functional connectivity in the DMN has also been associated with increased amyloid deposition measured using Pittsburgh compound B PET [ 30, 31]. In addition, several studies in healthy controls have shown a relationship between glucose metabolism measured by PET and the RS-fMRI signal. For example, Di et. al. showed that metabolic activity was correlated with independent component (IC) maps of the BOLD signal in regions that are functionally connected [ 32]. Similarly, Tomasi et. al. [ 33] measured the amplitude of the RS-fMRI signal and glucose metabolism by FDG-PET and demonstrated that higher metabolism was correlated with a higher amplitude of the RS-fMRI signal in the cerebellum, occipital, and parietal cortices. Finally, Riedl et. al. [ 34] found a correlation between local brain activity in specific regions of interest measured from FDG-PET data and functional connectivity measured by RS-fMRI using seed-based methods.

Previous RS-fMRI studies have shown a reduction in functional connectivity between structures based on the strength of the correlation in the BOLD signal [ 18, 35]. Here, we define a novel metric of brain activity based on a first-order texture feature defined as the standard deviation of the magnitude of the BOLD fluctuation. The purpose of this study was to determine whether this new metric could be used to accurately differentiate healthy elderly individuals from people with mild Alzheimer disease. Our hypothesis was that the fluctuation of the magnitude of the BOLD signal as a function of time is related to neuronal activity and therefore will also correlate with FDG-PET measures of glucose metabolism. Our goal was to demonstrate the efficacy of a new indicator of Alzheimer's disease based on the fluctuation of the magnitude of the RS-fMRI signal. Furthermore, we examined the association between the fluctuation magnitude of the neuronal derived RS-fMRI signal and FDG-PET.

Theory

In this study, we propose a brain activity measurement derived directly from the RS-fMRI signal. The RS-fMRI signal can be represented as an i x v matrix, where i represents each pixel, and v represents the number of volumes acquired in the fMRI acquisition. The ICA method decomposes the RS-fMRI signal into: 1) an i x n matrix of independent component spatial maps, where n represents the number of components, and 2) an n x v matrix of mixing weights ( W) or IC time-courses. Here, the number ( k) of legitimate ICs was identified using a goodness-of-fit (GoF) calculation, a multiple template matching method and a support vector machine (SVM) classifier [ 25] that included only the neuronal components ( NC) (). The weighting function for each neuronal component, W(t) is then multiplied (Hadamard product, Eq 1, ) with the equal length vector given by the RS-fMRI time series for each pixel, S(t), generating a new vector of equal length BSA( t):

where BSA represents the BOLD signal amplitude ( BSA) for each neuronal component k in pixel i. Then, the standard deviation (SD) is calculated for BSA and is multiplied with the neuronal component ( NC) (). The sum of this metric ( Eq 2, ) for all neuronal components in a pixel represents the neuronal activity and is used to produce a neuronal activity map.

Materials and methods

Study subjects

Data used in the preparation of this article ( S1 and S2 Tables) were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging, positron emission tomography, other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment and early Alzheimer's disease. Written informed consent for participation in the study was obtained from each participant, or their family. Data acquisition was approved by the local ethics review board at each participating site.

To test the algorithm, this study included data from 15 normal elderly controls (NEC) and 15 subjects with probable Alzheimer disease of mild severity obtained from the ADNI database. We included participants that had 3.0 Tesla T ₁-weighted anatomical scans and 10-minute RS-fMRI data acquisitions. A subset of this group (13 NEC, and 11 subjects with mild Alzheimer disease) also had an FDG-PET scan available. Structural T ₁-weighted images were obtained using a sagittal 3D magnetization-prepared rapid acquisition with a gradient echo MP-RAGE sequence with pixel size 1mm×1mm×1.2mm; flip angle ~9°; TE ~4 ms; TR ~7 ms; matrix, 256x256; 170 slices [ 36]. The RS-fMRI scans were acquired using a single shot echo planer imaging (EPI) pulse sequence with pixel size 3.3mm×3.3mm×3.3mm; flip angle 80.0°; TE 30 ms; TR ~3000 ms; matrix = 64x64; 48 slices [ 37]. FDG-PET images were acquired using similar protocols on all PET scanners but varied somewhat in resolution, spacing, and dimension. However images were normalized and motion corrected [ 38] prior to analysis. The FDG-PET scans consisted of six-5 minute frames acquired starting 30 minutes after FDG injection [ 38]. All frames were registered to the first frame and then averaged to produce a single static image. All subjects were also evaluated with the mini mental state examination (MMSE) [ 39] to assess cognition. In addition, CSF biomarkers including total Tau protein (Tau), phosphorylated Tau protein (P-Tau) and amyloid-β (Aβ ₁₋₄₂) were obtained for all subjects ( https://ida.loni.usc.edu/).

RS-fMRI analysis

The brain was extracted from the RS-fMRI data and the anatomical T ₁-weighted images using the brain extraction tool (BET) in the FSL software (functional MRI of the brain (FMRIB) Software Library, Department of Clinical Neurosciences, University of Oxford, UK, http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL). The brain extracted fMRI data were preprocessed, aligned and co-registered to the MNI-152 space using the fMRI expert analysis tool (FEAT) in FSL. An initial smoothing (full-width half-maximum of 6 mm), and band-pass temporal filtering (0.01 Hz-0.1 Hz) were applied before ICA decomposition. The ICA method (30 components) was performed using the group ICA of the fMRI toolbox (GIFT) [ 40]. The ICA was followed by a previously described three-step process [ 25] to identify neuronal components in each RS-fMRI data set, all implemented in-house by Demertzi and et. al. [ 25]. First, a goodness of fit (GoF) calculation was used to measure the similarity value between a component and established resting state networks [ 25]. Second, the multiple templates matching method was applied. Then, a template had to be assigned to one of the 30 components [ 25]. Thirdly, a support vector machine was used to label each component as neuronal, non-neuronal, or undefined [ 25].

Following identification of the neuronal components, a brain activity map was constructed from these components as described in the Theory section and co-registered to the MNI-152 standard image using linear and non-linear registration methods. Co-registration of the brain activity map to the anatomical image was conducted using Statistical Parametric Mapping (SPM8, Wellcome Department of Neurology, London, UK; www.fil.ion.ucl.ac.uk/spm). ROIs were defined in the MNI-152 image using the structural segmentation method called FMRIB's integrated registration and segmentation tool (FIRST) in FSL because it is easily accessible to the research community and automated. Finally, the mean intensity from each ROI in the brain activity map was measured. A schematic representation of the steps involved in making the brain activity measurements is provided in .

Volumetric analysis

The FSL software was used to measure the volumes of the accumbens, amygdala, hippocampus, caudate nucleus, thalamus, pallidum, putamen, and whole brain from the T ₁-weighted image of each subject using a method similar to that previously described [ 41]. The volumes were normalized to the whole brain volume in each subject.

FDG-PET analysis

The brain was also extracted from the FDG-PET images using the BET tool in FSL. A partial volume correction method was applied to each data set using the partial volume correction structural functional synergistic resolution recovery (PVC_SFSRR) software [ 42]. This software performs pre-processing steps including co-registration of the FDG-PET with the structural image, segmentation and smoothing (8 mm), and finally partial volume correction. The corrected FDG-PET image was co-registered to the MNI-152 template. The predefined ROIs in the MNI-152 image were applied to the co-registered FDG-PET image. The standardized uptake value (SUV) of each ROI was then normalized to the mean SUV of the cerebellum to obtain the SUV ratio (SUVR) as this has been previously shown [ 43] to be unchanged in healthy subjects and at the early stages of Alzheimer disease.

Statistical analysis

Prism GraphPad (Prism, version 6.00; GraphPad Software, San Diego, CA) and Matlab toolbox (version R2010a) were used for the statistical analyses. One-way ANOVA was used to compare brain activity between the NEC and Alzheimer disease groups ( p< 0.05 considered significant). If a significant group effect was observed, the p-values associated with follow-up group comparisons between brain regions were Bonferroni corrected for multiple comparisons. The association between the brain activity measured from the RS-fMRI, MMSE score, and CSF biomarkers were evaluated using linear regression. The significance of these associations was Bonferroni corrected for multiple comparisons. The Pearson correlation coefficient was used to measure the association between the brain activity in gray matter obtained from RS-fMRI and the glucose uptake from FDG-PET ( p < 0.05 considered significant).

Classification model

To determine if the RS-fMRI derived brain activity measurement was a suitable biomarker to differentiate patients with mild Alzheimer disease and healthy elderly controls, a SVM classifier was used. Specifically, a linear SVM [ 44] was trained and tested on the feature space. Regions of interest were selected based on the observed differences between groups for either the brain activity metric or FDG-PET measured glucose metabolism. A leave-one-out-test was used as a cross-validation to predict the label for each test subject (not involved in the training phase). The accuracy, sensitivity, and specificity were determined after each subject was assessed as the test subject. In the first analysis, RS-fMRI brain activity in the hippocampus and accumbens, FDG-PET in the hippocampus, and hippocampal volume were evaluated separately. In a second analysis, FDG-PET and RS-fMRI modalities were evaluated independently incorporating data from both the hippocampus and amygdala. In a third analysis, we combined the volumetric and RS-fMRI information from the hippocampus and accumbens.

Results

Brain maps of neuronal activity and glucose metabolism

Demographic characteristics are provided in for all 30 subjects ( S1 and S2 Tables). There was no difference between group mean ages (healthy elderly subjects age range: 65-80 years; subjects with Alzheimer disease age range: 63-79 years), however as expected, there was a significant difference in the MMSE score ( p< 0.0001, two-tailed t-test) between the two groups. Montreal neurological institute-152 (MNI-152) template T ₁-weighted images ( Fig 3A and 3B ) in coronal, sagittal, and axial planes are shown with corresponding standardized uptake value ratio (SUVR) glucose metabolism maps from the FDG-PET scan in one healthy elderly subject () and the healthy elderly group average (); as well as one subject with Alzheimer disease () and the Alzheimer disease group average (). Corresponding brain activity maps measured from the RS-fMRI in the same subjects ( Fig 3E and 3F ) and group averages ( Fig 3I and 3J ) are also provided. There is a visible decrease in signal in the subject with Alzheimer disease throughout the brain measured by both modalities.

Comparison of regional brain activity and glucose metabolism

The average brain activity measured from RS-fMRI () is shown for the cerebellum, amygdala, thalamus, accumbens, caudate, pallidum, hippocampus, and putamen regions for the NEC and Alzheimer disease groups. Similarly, the average relative rate of glucose metabolism () is provided for the same regions measured by FDG-PET for the NEC and Alzheimer disease groups. A one-way ANOVA indicated that there was a significant difference between the two groups in RS-fMRI brain activity ( p<0.0001) and FDG-PET measured glucose metabolism ( p<0.0001). In follow-up comparisons, the difference in brain activity measured by RS-fMRI in both sides of the accumbens (adjusted p = 0.04) and differences in relative glucose metabolism measured using FDG-PET in the amygdala (adjusted p = 0.02), and hippocampus (adjusted p = 0.006) remained significant following Bonferroni correction. A one-way ANOVA indicated that there was also a significant difference between these groups in the Tau, P-Tau and Aβ ₁₋₄₂ cerebral spinal fluid (CSF) levels ( p<0.0001). Follow-up comparisons showed that there were significant differences in both Tau (adjusted p<0.0001), and Aβ ₁₋₄₂ (adjusted p = 0.006) following Bonferroni correction for multiple comparisons. As expected, a one-way ANOVA also showed a significant difference in normalized brain volumes between the NEC and Alzheimer disease groups ( p<0.0001). Follow-up comparisons showed significant differences in normalized volume measured using MRI in the hippocampus ( p = 0.01) between the two groups.

Association between neuronal activity and glucose metabolism

A voxel by voxel correlation between gray matter RS-fMRI brain activity and the rate of glucose metabolism from the FDG-PET is shown in for one NEC (r = 0.81, p<0.0001) and subject with Alzheimer disease (r = 0.77, p<0.0001). Correlations were similar in all subjects ( S1 and S2 Figs). The average r-value ± SD associated with the correlation between gray matter activity measured using RS-fMRI and the rate of glucose metabolism measured using FDG-PET was 0.77 ± 0.04 for the NEC group and 0.73 ± 0.03 for the Alzheimer disease group. The average y-intercept ± SD for the NEC group was 0.23 ± 0.03 and for the Alzheimer disease group was 0.23 ± 0.03.

Comparison of neuronal components in NEC and Alzheimer disease

The average ± SD of the number of neuronal components was 6.4 ± 1.5 for the NEC group and 5.0 ± 1.2 for the Alzheimer disease group. Unpaired t-test (two-tailed) showed significantly fewer neuronal components in the Alzheimer disease group compared to the NEC group ( p = 0.007). Pooling all subjects, the average number of neuronal components was positively correlated with MMSE score (r = 0.30, p = 0.002) ( S3 Fig). The average ± SD of the RS-fMRI neuronal activity ( Eq 2) summed across all neuronal components in whole brain was 54.8 ± 18.3 in the NEC group and 40.6 ± 10.4 in the Alzheimer disease group. Unpaired t-test (two-tailed) showed significantly lower neuronal activity in the Alzheimer disease group compared to the NEC group ( p = 0.01) ( S4 Fig).

Association between neuronal activity and cognitive function

The relationship between RS-fMRI brain activity and clinical cognitive measurement is shown for several brain regions in when pooling all groups. However, the correlations between the MMSE score and brain activity in the cerebellum (r = 0.50, p = 0.007), amygdala (r = 0.47, p = 0.009), thalamus (r = 0.42, p = 0.02), accumbens (r = 0.48, p = 0.008), caudate (r = 0.41, p = 0.02), pallidum (r = 0.44, p = 0.01), hippocampus (r = 0.44, p = 0.01), and putamen (r = 0.41, p = 0.02) were not significant following Bonferroni correction.

Association between neuronal activity and amyloid beta₁₋₄₂

The relationship between RS-fMRI brain activity and Aβ ₁₋₄₂ CSF level is shown for several brain regions in for all subjects. However, the correlations between the RS-fMRI brain activity and Aβ ₁₋₄₂ in the cerebellum (r = 0.40, p = 0.03), amygdala (r = 0.51, p = 0.004), accumbens (r = 0.37, p = 0.04), pallidum (r = 0.41, p = 0.02), and putamen (r = 0.41, p = 0.02) were not significant following Bonferroni correction.

Comparison of classification accuracy

The classification accuracy of subjects using brain activity measured by RS-fMRI and relative glucose metabolism rate measured using FDG-PET is provided in . The greatest classification accuracy, sensitivity, and specificity were obtained when using FDG-PET measurement from the hippocampus. The classification model that used glucose metabolism in the hippocampus measured by FDG-PET achieved 85% average accuracy, 84% sensitivity and 85% specificity (). The models that used brain activity in the hippocampus or accumbens resulted in a lower accuracy, sensitivity, and specificity (). However, the model that combined normalized hippocampal volume and neuronal activity of RS-fMRI from the hippocampus achieved 80% average accuracy, 72% sensitivity and 89% specificity, providing a similar accuracy and specificity to that observed with FDG-PET glucose metabolism in the hippocampus.

Discussion

In this study we define a new metric related to neuronal activity based on the square root of the temporal standard deviation of the RS-fMRI signal summed across all neuronal components within a pixel. As a proof of principle, this new RS-fMRI based metric was used to compare brain activity in normal elderly subjects and patients with mild Alzheimer disease. The brain activity measurement is dependent on both the number of neuronal components and the temporal fluctuation associated with each component. Overall lower brain activity was observed in the mild Alzheimer disease group, particularly within the accumbens. A similar comparison in the same subjects using FDG-PET also showed overall group differences indicating lower glucose metabolism in the amygdala, and hippocampus. In a pixel-by-pixel analysis, brain activity derived from RS-fMRI was found to be strongly correlated with glucose metabolism measured by FDG-PET in gray matter.

The FDG-PET results from the current study are consistent with previous FDG-PET studies that have shown reduced glucose metabolism in subjects with Alzheimer disease [ 28, 45]. Reduced glucose metabolism has also been observed in the posterior cingulate, temporal, parietal lobes and later the frontal lobe [ 28, 46]. Mosconi et. al. [ 47] showed that glucose metabolism in the hippocampus and the entorhinal cortex is also reduced in the preclinical stage of Alzheimer disease. In addition, Jagust et. al. [ 48] has demonstrated that medial temporal and parietal glucose metabolism predicts cognitive decline. Glucose consumption measured by FDG-PET is also linearly associated with neuronal activity [ 49]. Therefore glucose consumption is considered an important indicator of presymptomatic Alzheimer disease [ 50].

A few RS-fMRI studies have also examined functional network activity in healthy subjects compared to people with Alzheimer disease. Seed based analyses [ 17, 18] have shown decreased functional connectivity (FC) in the medial temporal cortex, prefrontal cortex, precuneus, posterior cingulate, hippocampus, and thalamus in people with Alzheimer disease. Similar studies using ICA methods demonstrated reduced FC in precuneus, posterior cingulate, and parietal lobe in people with amnestic mild cognitive impairment (aMCI) [ 51] while Zhou et. al. [ 52] showed decreased FC in the default mode network including the hippocampus and the medial temporal lobe in people with Alzheimer disease. In the current study we did not examine functional connectivity, but instead used the RS-fMRI neuronal signal fluctuation to define a new indicator of brain activity. When examining activity in specific brain regions, the newly defined measurement of neuronal activity showed trends toward correlation with the MMSE score and Aβ ₁₋₄₂, but these associations did not remain significant following Bonferroni correction.

The new RS-fMRI metric related to brain activity showed regional differences between NEC and Alzheimer disease subjects that were different than those observed with FDG-PET. Previous studies have found that cerebral blood flow is closely coupled with brain metabolism [ 53, 54], and that both are decreased in people with Alzheimer's disease [ 55- 59]. Previous studies have also shown that there is an association between the resting brain activity and resting brain metabolism [ 60]. The strong correlation observed between RS-fMRI measured gray matter activity and FDG-PET measured glucose consumption in the current study is consistent with the notion that glucose metabolism is tightly coupled to the RS-fMRI measured brain activity. This result is also consistent with a recent study by Aiello et. al. [ 61] who showed a voxel-wise relationship between functional connectivity maps from RS-fMRI and glucose uptake measured by simultaneous FDG-PET in healthy subjects. Another recent study by Nugent et. al. [ 62] demonstrated that the correlation between functional connectivity maps derived from RS-fMRI and glucose metabolism measured by FDG-PET was lower in temporal lobe epilepsy patients compared to control subjects.

The group differentiation accuracy achieved using the brain activity metric in the accumbens measured by RS-fMRI was lower than that found when using FDG-PET measured glucose metabolism in the hippocampus (0.85). However, when combining hippocampal volume with brain activity from RS-fMRI in the hippocampus, the classification accuracy increased to 0.80, which is comparable to the FDG-PET results and significantly greater than using hippocampal volume alone. The specificity achieved when using the combined MRI-based measurements (0.89) was also greater than that achieved by FDG-PET and hippocampal volume alone. These results suggest that the combination of these MRI-based features could help to discriminate between a group of healthy elderly subjects and people with AD.

This proof of concept study demonstrates that decreased resting-state brain activity is associated with decreased brain glucose metabolism in mild Alzheimer disease. Furthermore, we demonstrated group classification based on a first-order textural feature (standard deviation) of the RS-fMRI neuronal signal. There are several limitations of the current study that should be considered. First, the sample size was limited by the availability of subjects with both ten-minute RS-fMRI data and FDG-PET. Regardless, the new metric was still able to differentiate between NEC and mild Alzheimer disease groups. Another limitation of this study is that we did not perform gray atrophy correction for either the RS-fMRI or FDG-PET signal changes. Therefore gray matter volume reduction in the hippocampus may partly explain the reduced RS-fMRI and FDG-PET measured brain activity. However, Mosconi et. al. [ 63] showed FDG-PET measured hypometabolism in the hippocampus despite atrophy correction in hippocampus. Gray matter atrophy measurements in the current study did show significant differences in the hippocampus between the two groups. However a classification model that included both the hippocampal volume and RS-fMRI brain activity showed an improved result to classification using either metric alone. Therefore, including this straightforward measurement of neuronal activity by RS-fMRI with existing markers of neurodegeneration may increase the reliability of detecting Alzheimer's disease. Future studies will evaluate the potential to identify people with mild cognitive impairment that progress to AD and whether this metric shows improvement following treatment.

Supporting information

S1 Fig
The association between RS-fMRI and FDG-PET SUVR in the healthy elderly group.
The scatter plots represent the voxel by voxel correlation of pixel intensity in the gray matter of healthy elderly subjects between brain activity using RS-fMRI and corrected glucose metabolism using FDG-PET SUVR. Each graph represents the results from a different individual.

(TIF)

S2 Fig
The association between RS-fMRI and FDG-PET SUVR in the Alzheimer disease group.
The scatter plots represent the voxel by voxel correlation of pixel intensity in the gray matter of Alzheimer disease subjects between brain activity using RS-fMRI and corrected glucose metabolism using FDG-PET SUVR. Each graph represents the results from a different individual.

(TIF)

S3 Fig
The relationship between the number of neuronal components and cognition function measured by the MMSE score.
The 95% confidence intervals for the regressions are shown as dotted lines. A significant correlation was found between MMSE score and the number of neuronal components (r = 0.30, p = 0.002).

(TIF)

S4 Fig
Component specific brain activity maps in one healthy elderly subject and one subject with Alzheimer disease.
Each image represents the square root of the standard deviation of the magnitude of the BOLD signal fluctuation. In this example, data from each identified neuronal component is provided in a different row. Eight neuronal components were identified in the healthy subject while only six neuronal components were identified in the subject with AD.

(TIF)

S1 Table
Healthy elderly control subjects.
(DOCX)

S2 Table
People with Alzheimer's disease.
(DOCX)

Acknowledgments

Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.ucla.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.

Funding Statement

This study was funded by the Canadian Institute of Health Research ( www.cihr-irsc.gc.ca/) with grant CSE 133350. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability

We obtained all data for this manuscript from a third party: the Alzheimer's Disease Neuroimaging Initiative. The data are available to all researchers using an online application that can be found at the following website: http://adni.loni.usc.edu/datasamples/access-data/. In the revised manuscript, we have included a listing of all subject ID numbers and scan dates (S1 and S2 Tables) used in the current manuscript. These ID numbers can be used to identify the data used in the current study within the ADNI database. We would appreciate your advice on any further information that is needed regarding data accessibility.

References

# data[].attributes.attachment_link.title
Spontaneous low frequency BOLD signal variations from resting-state fMRI are decreased in Alzheimer disease

# data[].attributes.attachment_link.description
Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal.

# data[].attributes.attachment_link.readable_text
Carol Brayne, Academic Editor

Abstract

Background

Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction.

Methods and findings

Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer's Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10 −5). We then integrated these AD-associated SNPs into a Cox proportional hazard model using genotype data from a subset of 6,409 AD patients and 9,386 older controls from Phase 1 of the Alzheimer's Disease Genetics Consortium (ADGC), providing a polygenic hazard score (PHS) for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in multiple independent cohorts (ADGC Phase 2, National Institute on Aging Alzheimer's Disease Center [NIA ADC], and Alzheimer's Disease Neuroimaging Initiative [ADNI], total n = 20,680). Within the ADGC Phase 1 cohort, individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate. Among APOE ε3/3 individuals, the PHS modified expected age of AD onset by more than 10 y between the lowest and highest deciles (hazard ratio 3.34, 95% CI 2.62-4.24, p = 1.0 × 10 −22). In independent cohorts, the PHS strongly predicted empirical age of AD onset (ADGC Phase 2, r = 0.90, p = 1.1 × 10 −26) and longitudinal progression from normal aging to AD (NIA ADC, Cochran-Armitage trend test, p = 1.5 × 10 −10), and was associated with neuropathology (NIA ADC, Braak stage of neurofibrillary tangles, p = 3.9 × 10 −6, and Consortium to Establish a Registry for Alzheimer's Disease score for neuritic plaques, p = 6.8 × 10 −6) and in vivo markers of AD neurodegeneration (ADNI, volume loss within the entorhinal cortex, p = 6.3 × 10 −6, and hippocampus, p = 7.9 × 10 −5). Additional prospective validation of these results in non-US, non-white, and prospective community-based cohorts is necessary before clinical use.

Conclusions

We have developed a PHS for quantifying individual differences in age-specific genetic risk for AD. Within the cohorts studied here, polygenic architecture plays an important role in modifying AD risk beyond APOE. With thorough validation, quantification of inherited genetic variation may prove useful for stratifying AD risk and as an enrichment strategy in therapeutic trials.

Author summary

Why was this study done?

Across the United States, late-onset Alzheimer's disease (AD) is the most common form of dementia.

There is a strong need for in vivo markers for AD risk stratification and cohort enrichment in therapeutic trials.

Although numerous studies have identified several genetic risk factors, including the ε4 allele of apolipoprotein E ( APOE), genetic variants have not been integrated with genetic epidemiology for quantifying age of AD onset.

What did the researchers do and find?

Using genotype data from over 70,000 AD patients and normal elderly controls, we evaluated the feasibility of combining AD-associated SNPs and APOE status into a continuous measure-a polygenic hazard score (PHS)-for predicting the age-specific risk for developing AD.

Using a survival model framework, we integrated single nucleotide polymorphisms associated with increased risk for AD into a PHS for each participant. By combining population-based incidence rates and the genotype-derived PHS for each individual, we derived estimates of instantaneous risk for developing AD, based on genotype and age, and tested replication in two independent cohorts.

Individuals in the highest PHS quartile developed AD at a considerably lower age and had the highest yearly AD incidence rate.

In independent cohorts, we found that the PHS strongly predicted empirical age of AD onset and longitudinal progression from normal aging to AD, and associated strongly with neuropathology and in vivo markers of AD neurodegeneration.

Additional prospective validation of these results on non-US, non-white, and prospective community-based cohorts is necessary before clinical use.

What do these findings mean?

Genetic variants can be integrated within an epidemiology framework to derive a polygenic score that can quantify individual differences in age-specific genetic risk for AD, beyond APOE.

Quantification of inherited genetic variation may prove useful for AD risk stratification and for therapeutic trials.

Introduction

Late-onset Alzheimer disease (AD), the most common form of dementia, places a large emotional and economic burden on patients and society. With increasing health care expenditures among cognitively impaired elderly individuals [ 1], identifying individuals at risk for developing AD is of utmost importance for potential preventative and therapeutic strategies. Inheritance of the ε4 allele of apolipoprotein E ( APOE) on Chromosome 19q13 is the most significant risk factor for developing late-onset AD [ 2]. APOE ε4 has a dose-dependent effect on age of onset, increases AD risk 3-fold in heterozygotes and 15-fold in homozygotes, and is implicated in 20%-25% of AD cases [ 3].

In addition to the single nucleotide polymorphism (SNP) in APOE, recent genome-wide association studies (GWASs) have identified numerous AD-associated SNPs, most of which have a small effect on disease risk [ 4, 5]. Although no single polymorphism may be informative clinically, a combination of APOE and non- APOE SNPs may help identify older individuals at increased risk for AD. Despite their detection of novel AD-associated genes, GWAS findings have not yet been incorporated into a genetic epidemiology framework for individualized risk prediction.

Building on a prior approach evaluating GWAS-detected genetic variants for disease prediction [ 6] and using a survival analysis framework, we tested the feasibility of combining AD-associated SNPs and APOE status into a continuous-measure polygenic hazard score (PHS) for predicting the age-specific risk for developing AD. We assessed replication of the PHS using several independent cohorts.

Methods

Participant samples

International genomics of Alzheimer's project

To select AD-associated SNPs, we evaluated publicly available AD GWAS summary statistic data ( p-values and odds ratios) from the International Genomics of Alzheimer's Project (IGAP) (Stage 1; for additional details see S1 Appendix and [ 4]). For selecting AD-associated SNPs, we used IGAP Stage 1 data, from 17,008 AD cases and 37,154 controls drawn from four different consortia across North America and Europe (including the United States of America, England, France, Holland, and Iceland) with genotyped or imputed data at 7,055,881 SNPs (for a description of the AD cases and controls within the IGAP Stage 1 sub-studies, please see and [ 4]).

Alzheimer's disease genetics consortium

To develop the survival model for the PHS, we first evaluated age of onset and raw genotype data from 6,409 patients with clinically diagnosed AD and 9,386 cognitively normal older individuals provided by the Alzheimer's Disease Genetics Consortium (ADGC) (Phase 1, a subset of the IGAP dataset), excluding individuals from the National Institute of Aging Alzheimer's Disease Center (NIA ADC) and Alzheimer's Disease Neuroimaging Initiative (ADNI) samples. To evaluate replication of the PHS, we used an independent sample of 6,984 AD patients and 10,972 cognitively normal older individuals from the ADGC Phase 2 cohort (). The genotype and phenotype data within the ADGC datasets has been described in detail elsewhere [ 7, 8]. Briefly, the ADGC Phase 1 and 2 datasets (enrollment from 1984 to 2012) consist of case-control, prospective, and family-based sub-studies of white participants with AD occurrence after age 60 y derived from the general community and Alzheimer's Disease Centers across the US. Participants with autosomal dominant ( APP, PSEN1, and PSEN2) mutations were excluded. All participants were genotyped using commercially available high-density SNP microarrays from Illumina or Affymetrix. Clinical diagnosis of AD within the ADGC sub-studies was established using NINCDS-ADRDA criteria for definite, probable, and possible AD [ 9]. For most participants, age of AD onset was obtained from medical records and defined as the age when AD symptoms manifested, as reported by the participant or an informant. For participants lacking age of onset, age at ascertainment was used. Patients with an age at onset or age at death less than 60 y and individuals of non-European ancestry were excluded from the analyses. All ADGC Phase 1 and 2 control participants were defined within individual sub-studies as cognitively normal older adults at time of clinical assessment. The institutional review boards of all participating institutions approved the procedures for all ADGC sub-studies. Written informed consent was obtained from all participants or surrogates. For additional details regarding the ADGC datasets, please see [ 7, 8].

National institute of aging Alzheimer's disease centers

To assess longitudinal prediction, we evaluated an ADGC-independent sample of 2,724 cognitively normal elderly individuals. Briefly, all participants were US based, evaluated at National Institute of Aging-funded Alzheimer's Disease Centers (data collection coordinated by the National Alzheimer's Coordinating Center [NACC]) and clinically followed for at least two years (enrollment from 1984 to 2012, evaluation years were 2005 to 2016) [ 10]. Here, we focused on older individuals defined at baseline as having an overall Clinical Dementia Rating score of 0.0. To assess the relationship between polygenic risk and neuropathology, we assessed 2,960 participants from the NIA ADC samples with genotype and neuropathological evaluations. For the neuropathological variables, we examined the Braak stage for neurofibrillary tangles (NFTs) (0, none; I-II, entorhinal; III-IV, limbic; and V-VI, isocortical) [ 11] and the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score for neuritic plaques (none/sparse, moderate, or frequent) [ 12]. Finally, as an additional independent replication sample, we evaluated all NIA ADC AD cases with genetic data who were classified at autopsy as having a high level of AD neuropathological change ( n = 361), based on the revised National Institute of Aging-Alzheimer's Association AD neuropathology criteria [ 13]. The institutional review boards of all participating institutions approved the procedures for all NIA ADC sub-studies. Written informed consent was obtained from all participants or surrogates.

Alzheimer's disease neuroimaging initiative

To assess the relationship between polygenic risk and in vivo biomarkers, we evaluated an ADGC-independent sample of 692 older controls and participants with mild cognitive impairment or AD from the ADNI (see S1 Appendix). Briefly, the ADNI is a multicenter, multisite longitudinal study assessing clinical, imaging, genetic, and biospecimen biomarkers from US-based participants through the process of normal aging to early mild cognitive impairment, to late mild cognitive impairment, to dementia or AD (see S1 Appendix). Here, we focused specifically on participants from ADNI 1 with cognitive, imaging, and cerebrospinal fluid (CSF) assessments from 2003 to 2010. In a subset of ADNI 1 participants with available genotype data, we evaluated baseline CSF level of Aβ ₁₋₄₂ and total tau, as well as longitudinal Clinical Dementia Rating Sum of Boxes (CDR-SB) scores. In ADNI 1 participants with available genotype and quality-assured baseline and follow-up MRI scans, we also assessed longitudinal subregional change in medial temporal lobe volume (atrophy) on 2,471 serial T ₁-weighted MRI scans (for additional details see S1 Appendix).

Statistical analysis

We followed three steps to derive the PHS for predicting age of AD onset: (1) we defined the set of associated SNPs, (2) we estimated hazard ratios for polygenic profiles, and (3) we calculated individualized absolute hazards (see S1 Appendix for a detailed description of these steps).

Using the IGAP Stage 1 sample, we first identified a list of SNPs associated with increased risk for AD, using a significance threshold of p < 10 −5. Next, we evaluated all IGAP-detected AD-associated SNPs within the ADGC Phase 1 case-control dataset. Using a stepwise procedure in survival analysis, we delineated the "final" list of SNPs for constructing the PHS [ 14, 15]. Specifically, using Cox proportional hazard models, we identified the top AD-associated SNPs within the ADGC Phase 1 cohort (excluding NIA ADC and ADNI samples), while controlling for the effects of gender, APOE variants, and the top five genetic principal components (to control for the effects of population stratification). We utilized age of AD onset and age of last clinical visit to estimate age-specific risks [ 16] and derived a PHS for each participant. In each step of the stepwise procedure, the algorithm selected the one SNP from the pool that most improved model prediction (i.e., minimizing the Martingale residuals); additional SNP inclusion that did not further minimize the residuals resulted in halting of the SNP selection process. To prevent overfitting in this training step, we used 1,000× bootstrapping for model averaging and estimating the hazard ratios for each selected SNP. We assessed the proportional hazard assumption in the final model using graphical comparisons.

To assess for replication, we first examined whether the predicted PHSs derived from the ADGC Phase 1 cohort could stratify individuals into different risk strata within the ADGC Phase 2 cohort. We next evaluated the relationship between predicted age of AD onset and the empirical (actual) age of AD onset using cases from ADGC Phase 2. We binned risk strata into percentile bins and calculated the mean of actual age of AD onset in that percentile as the empirical age of AD onset. In a similar fashion, we additionally tested replication within the NIA ADC subset classified at autopsy as having a high level of AD neuropathological change [ 13].

Because case-control samples cannot provide the proper baseline hazard [ 17], we used previously reported annualized incidence rates by age estimated from the general US population [ 18]. For each participant, by combining the overall population-derived incidence rates [ 18] and the genotype-derived PHS, we calculated the individual's "instantaneous risk" for developing AD, based on their genotype and age (for additional details see S1 Appendix). To independently assess the predicted instantaneous risk, we evaluated longitudinal follow-up data from 2,724 cognitively normal older individuals from the NIA ADC with at least 2 y of clinical follow-up. We assessed the number of cognitively normal individuals progressing to AD as a function of the predicted PHS risk strata and examined whether the predicted PHS-derived incidence rate reflected the empirical progression rate using a Cochran-Armitage trend test.

We examined the association between our PHS and established in vivo and pathological markers of AD neurodegeneration. Using linear models, we assessed whether the PHS associated with Braak stage for NFTs and CERAD score for neuritic plaques, as well as CSF Aβ ₁₋₄₂ and CSF total tau. Using linear mixed effects models, we also investigated whether the PHS was associated with longitudinal CDR-SB score and volume loss within the entorhinal cortex and hippocampus. In all analyses, we co-varied for the effects of age and sex.

Results

Polygenic hazard score: Model development, relationship to APOE, and independent replication

From the IGAP cohort, we found 1,854 SNPs associated with increased risk for AD at p < 10 −5. Of these, using the Cox stepwise regression framework, we identified 31 SNPs, in addition to two APOE variants, within the ADGC cohort for constructing the polygenic model (). illustrates the relative risk for developing AD using the ADGC Phase 1 case-control cohort. The graphical comparisons among Kaplan-Meier estimations and Cox proportional hazard models indicate that the proportional hazard assumption holds for the final model ().

Table 2

To quantify the additional prediction provided by polygenic information beyond APOE, we evaluated how the PHS modulates age of AD onset in APOE ε3/3 individuals. Among these individuals, we found that age of AD onset can vary by more than 10 y, depending on polygenic risk. For example, for an APOE ε3/3 individual in the tenth decile (top 10%) of the PHS, at 50% risk for meeting clinical criteria for AD diagnosis, the expected age of developing AD is approximately 84 y (); however, for an APOE ε3/3 individual in the first decile (bottom 10%) of the PHS, the expected age of developing AD is approximately 95 y (). The hazard ratio comparing the tenth decile to the first decile is 3.34 (95% CI 2.62-4.24, log rank test p = 1.0 × 10 −22). Similarly, we also evaluated the relationship between the PHS and the different APOE alleles (ε2/3/4) (first figure in S1 Appendix). These findings show that, beyond APOE, the polygenic architecture plays an integral role in affecting AD risk.

To assess replication, we applied the ADGC Phase 1-trained model to independent samples from ADGC Phase 2. Using the empirical distributions, we found that the PHS successfully stratified individuals from independent cohorts into different risk strata (). Among AD cases in the ADGC Phase 2 cohort, we found that the predicted age of onset was strongly associated with the empirical (actual) age of onset (binned in percentiles, r = 0.90, p = 1.1 × 10 −26; ). Similarly, within the NIA ADC subset with a high level of AD neuropathological change, we found that the PHS strongly predicted time to progression to neuropathologically defined AD (Cox proportional hazard model, z = 11.8723, p = 2.8 × 10 −32).

Predicting population risk of Alzheimer disease onset

To evaluate the risk for developing AD, combining the estimated hazard ratios from the ADGC cohort, allele frequencies for each of the AD-associated SNPs from the 1000 Genomes Project, and the disease incidence in the general US population [ 18], we generated population baseline-corrected survival curves given an individual's genetic profile and age (panels A and B of second figure in S1 Appendix). We found that PHS status modifies both the risk for developing AD and the distribution of age of onset (panels A and B of second figure in S1 Appendix).

Given an individual's genetic profile and age, the corrected survival proportion can be translated directly into incidence rates (; Tables and S1). As previously reported in a meta-analysis summarizing four studies from the US general population [ 18], the annualized incidence rate represents the proportion (in percent) of individuals in a given risk stratum and age who have not yet developed AD but will develop AD in the following year; thus, the annualized incidence rate represents the instantaneous risk for developing AD conditional on having survived up to that point in time. For example, for a cognitively normal 65-y-old individual in the 80th percentile of the PHS, the incidence rate (per 100 person-years) would be 0.29 at age 65 y, 1.22 at age 75 y, 5.03 at age 85 y, and 20.82 at age 95 y (; ); in contrast, for a cognitively normal 65-y-old in the 20th percentile of the PHS, the incidence rate would be 0.10 at age 65 y, 0.43 at age 75 y, 1.80 at age 85 y, and 7.43 at age 95 y (; ). As independent validation, we examined whether the PHS-predicted incidence rate reflects the empirical progression rate (from normal control to clinical AD) (). We found that the PHS-predicted incidence was strongly associated with empirical progression rates (Cochran-Armitage trend test, p = 1.5 × 10 −10).

Table 3

Age (years)

Population baseline*

PHS 1st percentile (95% CI)

PHS 20th percentile (95% CI)

PHS 80th percentile (95% CI)

PHS 99th percentile (95% CI)

APOE ε4+ (95% CI)

APOE ε4− (95% CI)

Association of polygenic hazard score with known markers of Alzheimer disease pathology

We found that the PHS was significantly associated with Braak stage of NFTs (β-coefficient = 0.115, standard error [SE] = 0.024, p-value = 3.9 × 10 −6) and CERAD score for neuritic plaques (β-coefficient = 0.105, SE = 0.023, p-value = 6.8 × 10 −6). We additionally found that the PHS was associated with worsening CDR-SB score over time (β-coefficient = 2.49, SE = 0.38, p-value = 1.1 × 10 −10), decreased CSF Aβ ₁₋₄₂ (reflecting increased intracranial Aβ plaque load) (β-coefficient = −0.07, SE = 0.01, p-value = 1.28 × 10 −7), increased CSF total tau (β-coefficient = 0.03, SE = 0.01, p-value = 0.05), and greater volume loss within the entorhinal cortex (β-coefficient = −0.022, SE = 0.005, p-value = 6.30 × 10 −6) and hippocampus (β-coefficient = −0.021, SE = 0.005, p-value = 7.86 × 10 −5).

Discussion

In this study, by integrating AD-associated SNPs from recent GWASs and disease incidence estimates from the US population into a genetic epidemiology framework, we have developed a novel PHS for quantifying individual differences in risk for developing AD, as a function of genotype and age. The PHS systematically modified age of AD onset, and was associated with known in vivo and pathological markers of AD neurodegeneration. In independent cohorts (including a neuropathologically confirmed dataset), the PHS successfully predicted empirical (actual) age of onset and longitudinal progression from normal aging to AD. Even among individuals who do not carry the ε4 allele of APOE (the majority of the US population), we found that polygenic information was useful for predicting age of AD onset.

Using a case-control design, prior work has combined GWAS-associated polymorphisms and disease prediction models to predict risk for AD [ 19- 24]. Rather than representing a continuous process where non-demented individuals progress to AD over time, the case-control approach implicitly assumes that normal controls do not develop dementia and treats the disease process as a dichotomous variable where the goal is maximal discrimination between diseased "cases" and healthy "controls." Given the striking age dependence of AD, this approach is clinically suboptimal for estimating the risk of AD. Building on prior genetic estimates from the general population [ 2, 25], we employed a survival analysis framework to integrate AD-associated common variants with established population-based incidence [ 18] to derive a continuous measure, the PHS. We note that the PHS can estimate individual differences in AD risk across a lifetime and can quantify the yearly incidence rate for developing AD.

These findings indicate that the lifetime risk of age of AD onset varies by polygenic profile. For example, the annualized incidence rate (risk for developing AD in a given year) is considerably lower for an 80-y-old individual in the 20th percentile of the PHS than for an 80-y-old in the 99th percentile of the PHS (; ). Across the lifespan (panel B of second figure in S1 Appendix), our results indicate that even individuals with low genetic risk (low PHS) develop AD, but at a later peak age of onset. Certain loci (including APOE ε2) may "protect" against AD by delaying, rather than preventing, disease onset.

Our polygenic results provide important predictive information beyond APOE. Among APOE ε3/3 individuals, who constitute 70%-75% of all individuals diagnosed with late-onset AD, age of onset varies by more than 10 y, depending on polygenic risk profile (). At 60% AD risk, APOE ε3/3 individuals in the first decile of the PHS have an expected age of onset of 85 y, whereas for individuals in the tenth decile of the PHS, the expected age of onset is greater than 95 y. These findings are directly relevant to the general population, where APOE ε4 accounts for only a fraction of AD risk [ 3], and are consistent with prior work [ 26] indicating that AD is a polygenic disease where non- APOE genetic variants contribute significantly to disease etiology.

We found that the PHS strongly predicted age of AD onset within the ADGC Phase 2 dataset and the NIA ADC neuropathology-confirmed subset, demonstrating independent replication of our polygenic score. Within the NIA ADC sample, the PHS robustly predicted longitudinal progression from normal aging to AD, illustrating that polygenic information can be used to identify the cognitively normal older individuals at highest risk for developing AD (preclinical AD). We found a strong relationship between the PHS and increased tau-associated NFTs and amyloid plaques, suggesting that elevated genetic risk may make individuals more susceptible to underlying AD pathology. Consistent with recent studies showing correlations between AD polygenic risk scores and markers of AD neurodegeneration [ 22, 23], our PHS also demonstrated robust associations with CSF Aβ ₁₋₄₂ levels, longitudinal MRI measures of medial temporal lobe volume loss, and longitudinal CDR-SB scores, illustrating that increased genetic risk may increase the likelihood of clinical progression and developing neurodegeneration measured in vivo.

From a clinical perspective, our genetic risk score may serve as a "risk factor" for accurately identifying older individuals at greatest risk for developing AD, at a given age. Conceptually similar to other polygenic risk scores (for a review of this topic see [ 27]) for assessing coronary artery disease risk [ 28] and breast cancer risk [ 29], our PHS may help in predicting which individuals will test "positive" for clinical, CSF, or imaging markers of AD pathology. Importantly, a continuous polygenic measure of AD genetic risk may provide an enrichment strategy for prevention and therapeutic trials and could also be useful for predicting which individuals may respond to therapy. From a disease management perspective, by providing an accurate probabilistic assessment regarding the likelihood of AD neurodegeneration, determining a "genomic profile" of AD may help initiate a dialogue on future planning. Finally, a similar genetic epidemiology framework may be useful for quantifying the risk associated with numerous other common diseases.

There are several limitations to our study. We primarily focused on individuals of European descent. Given that AD incidence [ 30], genetic risk [ 25, 31], and likely linkage disequilibrium in African-American and Latino individuals is different from in white individuals, additional work will be needed to develop a polygenic risk model in non-white (and non-US) populations. The majority of the participants evaluated in our study were recruited from specialized memory clinics or AD research centers and may not be representative of the general US population. In order to be clinically useful, we note that our PHS needs to be prospectively validated in large community-based cohorts, preferably consisting of individuals from a range of ethnicities. The previously reported population annualized incidence rates were not separately provided for males and females [ 18]. Therefore, we could not report PHS annualized incidence rates stratified by sex. We note that we primarily focused on genetic markers and thus did not evaluate how other variables, such as environmental or lifestyle factors, in combination with genetics impact age of AD onset. Another limitation is that our PHS may not be able to distinguish pure AD from a "mixed dementia" presentation since cerebral small vessel ischemic/hypertensive pathology often presents concomitantly with AD neurodegeneration, and additional work will be needed on cohorts with mixed dementia to determine the specificity of our polygenic score. Finally, we focused on APOE and GWAS-detected polymorphisms for disease prediction. Given the flexibility of our genetic epidemiology framework, it can be used to investigate whether a combination of common and rare genetic variants along with clinical, cognitive, and imaging biomarkers may prove useful for refining the prediction of age of AD onset.

In conclusion, by integrating population-based incidence proportion and genome-wide data into a genetic epidemiology framework, we have developed a PHS for quantifying the age-associated risk for developing AD. Measures of polygenic variation may prove useful for stratifying AD risk and as an enrichment strategy in clinical trials.

Acknowledgments

We thank the Shiley-Marcos Alzheimer's Disease Research Center at the University of California, San Diego, the UCSF Memory and Aging Center, and the UCSF Center for Precision Neuroimaging for continued support; IGAP for providing summary results data for these analyses; and ADGC and ADNI for providing data for these analyses. Please see S1 Acknowledgments for more details about the contributions of IGAP, NIA ADS, ADGC, ADNI, and NACC.

Abbreviations

ADGC

Alzheimer's Disease Genetics Consortium

ADNI

Alzheimer's Disease Neuroimaging Initiative

CDR-SB

Clinical Dementia Rating Sum of Boxes

CERAD

Consortium to Establish a Registry for Alzheimer's Disease

CSF

cerebrospinal fluid

GWAS

genome-wide association studies

IGAP

International Genomics of Alzheimer's Project

NACC

National Alzheimer's Coordinating Center

NFTs

neurofibrillary tangles

NIA ADC

National Institute on Aging Alzheimer's Disease Center

PHS

polygenic hazard score

SNP

single nucleotide polymorphism

Funding Statement

This work was supported by grants from the National Institutes of Health (NIH-AG046374, K01AG049152, R01MH100351), National Alzheimer's Coordinating Center Junior Investigator Award (RSD), Radiological Society of North America Resident/Fellow Award (RSD), Foundation of the American Society of Neuroradiology Alzheimer's Imaging Grant (RSD), the Research Council of Norway (#213837, #225989, #223273, #237250/EU JPND), the South East Norway Health Authority (2013-123), Norwegian Health Association, and the KG Jebsen Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

2. Farrer LA, Cupples LA, Haines JL, Hyman B, Kukull WA, Mayeux R, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA. 1997;278(16):1349-56.

10. Beekly DL, Ramos EM, Lee WW, Deitrich WD, Jacka ME, Wu J, et al. The National Alzheimer's Coordinating Center (NACC) database: the Uniform Data Set. Alzheimer Dis Assoc Disord. 2007;21:249-58. doi: 10.1097/WAD.0b013e318142774e

16. Klein JP, Houwelingen HC, Ibrahim JG, Scheike TH, editors. Handbook of survival analysis. London: Chapman and Hall/CRC; 2013.

17. Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 3rd ed Philadelphia: Lippincott Williams & Wilkins; 2008.

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Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score

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Carol Brayne, Academic Editor Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction.

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professional classroom training | alzheimer's association

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Professional Classroom Training | Alzheimer's Association

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Professional Classroom Training | Alzheimer's Association

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Second Wind Dreams ® | Virtual Dementia Tour®

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These are just some of the quotes we've heard about the Virtual Dementia Tour (VDT) , the original, ground-breaking, evidence-based, and scientifically proven method of building a greater understanding of dementia. The VDT uses patented sensory tools and instruction based on research conducted by P.K.

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For most people, virtual reality's promise of transporting us to a different world in a heartbeat is a great novelty. But for those who cannot travel freely, it's a lifeline.

Sonya Kim, a physician in the San Francisco Bay area, has been taking virtual-reality headsets to seniors as a part of their medical treatment. Her therapy program, Aloha VR, lets seniors use the headsets to bring variety into their days, relax and get away to a virtual tropical locale.

High-tech and seniors may not go together in many people's minds. But virtual reality is actually just the latest in technologies helping them. Nintendo Wii's motion gaming technology, in its heyday, was a hit in nursing homes, as a way to get residents to exercise. Kinect, Microsoft's motion gaming sensor, has been used to help patients recover from painful operations. And many wearable and smart appliance technologies are being developed to help older people live in their own homes, rather than go to nursing homes.

Virtual-reality applications have been mostly focused on gaming, but their role in therapy is being examined by a handful of medical professionals, such as Kim.

Kim's company, One Caring Team, checks in with lonely seniors - partially to stave off the potentially debilitating depression that grips many older adults who live on their own. A woman, who heard Kim speak about her company, asked Kim to help her mother, who had dementia and couldn't carry on a conversation.

"That gave me a new homework assignment," said Kim, who began researching technologies that could help those patients. She was particularly struck by the potential for VR therapy to help seniors with loneliness after trying it out at a game developer's conference. Kim then worked to develop Aloha VR.

"It's a new solution for an old problem," Kim said. "It lifts the moods of those patients who are so anxious and bored or depressed because they think no one cares about them. We've brought beautiful places to seniors who can't go anywhere."

Aloha VR is getting some dramatic results. In many cases, seniors who've withdrawn from the rest of the world because of dementia or depression have had their overall behavior greatly altered by their digital trips to the beach. Kim has seen patients who were unresponsive or even violent completely change after a few VR sessions.

One male patient with dementia stands out in Kim's mind. At 6-foot-2, this patient was always hunched over and constantly anxious, she said. He never participated in group sessions, preferring to sit in a corner. But when he used the VR headset, he became alert, relaxed and engaged with the scenes he saw, his caregivers said. When his wife saw a video of him reacting to the therapy, Kim said, she nearly began to cry.

"She was so moved to see this therapy bring happiness and joy to her husband, who was trapped in this demented body," Kim said. In subsequent sessions, he even began to sing and flap his fingers when he saw a bird fly by in the program. "It was amazing to watch this transformation," Kim said.

Kim's company has received several testimonials from patients' relatives and caregivers who said the relaxing effects of the virtual-reality sessions have lasted for weeks. In the case of the dementia patient who started singing during his virtual-reality session, his family told Kim that they no longer worry about him hitting his caregivers or pulling their hair.

Why does it work? Even Kim is not completely sure, but she does have a theory: Immersing some patients in a virtual world stimulates their brains in a variety of ways. "I think VR allows patients' neural pathways to be reactivated - some have dormant pathways - because of the power of presence, of having something right in front of them without any distraction," she said.

Kim is now trying to raise money for One Caring Team and Aloha VR to expand the programs, make them more cost-effective and work with other organizations that are looking at different ways to use virtual reality.

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This physician is using virtual reality to treat patients with dementia

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For most people, virtual reality's promise of transporting us to a different world in a heartbeat is a great novelty. But for those who cannot travel freely, it's a lifeline. Sonya Kim, a physician in the San Francisco Bay area, has been taking virtual-reality headsets to seniors as a part of their medical treatment.

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In 2015, Wolfgang Kampbartold met a Berlin-based professor-turned-inventor in his efforts to diagnose dementia. Kampbartold listened as the professor turned over a crude collection of cardboard and screws in his hands, explaining how the contraption of his own making was designed to test basic skills in at-risk groups.

Dementia is already one of the biggest health challenges the world is facing, with 850,000 people suffering from the disease in the UK and 130 million estimated to be diagnosed globally by 2050. Loss of navigational skills are increasingly being recognised as an earlier, and potentially better, signal of the disease than memory loss. But there is no standard benchmark test, or even enough data to generalise what is "normal". This, is why Kampbartold, the vice president of marketing at Deutsche Telekom, found himself in Berlin handling the curious device the professor had fashioned.

Alzheimer's disease and dementia: what's the difference?

The professor explained that he would be lucky to get 40 people in a trial for his system. "To me, as an economist, if you have 40 people you don't even wake up in the morning - you cannot derive any significant conclusion from a sample size of 40. Dementia is one of the world's biggest killer and mankind doesn't know anything. It's crazy."

Kampbartold says his firm wanted to "add a purpose" to what it does, and in this instance, to use its global reach to do that. Together with neuroscientists from University College London and the University of East Anglia, it helped produce and distribute a mobile game that measures spatial navigational skills. Sea Hero Quest, developed by games studio Glitchers, launched last autumn and has been downloaded almost three million times, generating the equivalent of 12,000 years of lab research.

"We're not just trying to sell rate plans," says Kampbartold. Extraordinarily, that sense of corporate obligation, which may have started out as a PR soundbite, has led to the production of an unprecedented global data set of human spatial navigational skills, that could form the beginnings of the first early warning diagnostics test for dementia.

"If you were trying to do this traditionally in the lab you would need a ludicrous amount of money to reach the same level," says Hugo Spiers of UCL, who has been leading the data analysis. "And even when you capably test 100 people, you just can't fully understand how everyone behaves in that environment. Certain alleys aren't explored. But if three million people are involved, we know what a million people do in a given millisecond - all of this comes together to give this unprecedented precision in this task."

"As far as we are aware, this is the biggest dementia study ever run. It's the first time on a global level any human skill has been measured."

Read next

Spiers is visibly thrilled by the opportunity this data set has given him and his team. That set is about to expand with the launch of a VR version today, available from the Oculus Store, but Spiers and his colleagues have already discovered significant results from the mobile data. For instance, they found Nordic countries came top of the league for navigating, despite other nations starting out top for gameplay. His team believes it has some evidence for why this is, but they are in the process of submitting the study to journals so for now details remain under wraps. "As a scientist it shows this is not just a gimmick - it's a genuinely valuable, exciting endeavour."

The original game was carefully crafted to account for different abilities and gaming experience, taking gamers through different levels to ensure the right skills get tested. Spiers points out that unlike memory tests, the current gold standard for clinical diagnosis of dementia, the game can be run anywhere despite language barriers. The game was translated into 17 languages, but players did just as well when it wasn't translated into their language. The hope is a VR version will be even more intuitive - and help more older generations engage when playing alongside families (currently, the team needs more data from older players). One of the minigames involves navigating a boat to find a flare, then aiming that flare back to the point you began - looking around in 360 helps translate this simple spatial skill.

The VR game should help the team validate its existing data, as well as add even more precise information (Spiers says the data gathered in VR is 15 times more precise). "Fundamentally VR immerses people in a world that will be more akin to a real situation so the results might give a more accurate reflection," he says. "But it's also the precision that the mobile phones that run VR have - we can look at where they are looking from every degree."
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The team believes it is on its way to creating the first global benchmark in history for one of the earliest known symptoms of dementia. But what then? There is no known cure for the disease, and as Kampbartold even points out, for the sufferer, foreknowledge can be worse than the disease itself.

"To go back to the professor in Berlin, he explained what happened to patients when they start developing dementia. They are driven nuts because they realise that they are going to lose everything they have. It's not so much of an issue when they have dementia because then they are gone. But this process of losing your, how can I say this? Your human beingness. And you realise how you deteriorate. That's the hardest thing."

Because of a lack of a definitive test, it can take years of watching and measuring that painful decline before a diagnosis is made. Spiers, and all the collaborators involved in Sea Hero Quest, believe if we can start to catch the disease earlier, understand it more fully, we will be in a better position to tackle it. For Kampbartold, the goal is simple. "By 2020 I want a device that will be able to diagnose dementia on a broad scale. My clock is ticking, so hurry up.

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In 2015, Wolfgang Kampbartold met a Berlin-based professor-turned-inventor in his efforts to diagnose dementia. Kampbartold listened as the professor turned over a crude collection of cardboard and screws in his hands, explaining how the contraption of his own making was designed to test basic skills in at-risk groups.

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Scientists have developed a virtual reality computer game as part of the world's biggest dementia research experiment.

It is designed to test one of the first things to go with dementia - the ability to navigate.

The original smartphone app had 3 million players, but the move to virtual reality should allow scientists to investigate in greater detail.

Alzheimer's Research UK says the goal is a new way of diagnosing the disease.

In the virtual world of Sea Hero Quest VR you captain a boat.

The challenge is to use your sense of direction to chart a course through complex waterways, desert islands and icy oceans.

And even feed hotdog-loving sea monsters.

But it is not only a game. While you play, anonymous data will be collected and, later, assessed by neuroscientists.

Max Scott-Slade, from the computer game developers Glitchers, worked with research scientists at University College London, University of East Anglia and ETH Zurich.

He told the BBC: "It's interesting to try to make something that's normally quite a boring subject matter, and lab-based, and bring it to the public and make it as fun as possible.

"The value for us is to create this much richer dataset, we're capturing 15 times more data from the VR version because we're separating out where the head looks and where the boat's moving."

The findings of the first game were presented at an international meeting of neuroscientists in 2016.

It showed someone's sense of direction declines consistently after their teenage years.

The data also suggested men have a slightly better sense of direction than women and that the Nordic nations outperform the rest of the world, although it is not yet clear why.

Prof Christophe Hoelscher, chairman of cognitive science at ETH Zurich, said: "No project ever has collected data from 3 million people of real interactions in this depth.

"That allows us to do a number of analyses that you would never be able to do with classical studies."

The group does not expect the same number of people to take up the virtual reality update - VR headsets are not as popular as smartphones.

However, they do expect to get far more data than would ever be possible in the laboratory.

Dementia test

The project, which is funded by Deutsche Telekom, has a long way to go, but the ultimate aim is a test that can pick up dementia in its earliest stages.

Eight-hundred-and-fifty-thousand people are already living with the disease in the UK. That figure is forecast to reach 2 million by 2051.

Most will have had the disease for more than a decade before their symptoms appear.

Dr David Reynolds, of Alzheimer's Research UK, said: "What we really want to be doing is identifying people with dementia 10 or 15 years earlier than we do at the moment.

"A game like Sea Hero Quest and understanding how we navigate will help us get to that much earlier diagnosis."

There are currently no drugs that can prevent or slow dementia. But it is widely accepted that any future treatment will work only if doctors can get it to patients long before symptoms appear and the brain is irreversibly damaged.

Follow James on Twitter.

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Scientists have developed a virtual reality computer game as part of the world's biggest dementia research experiment. It is designed to test one of the first things to go with dementia - the ability to navigate. The original smartphone app had 3 million players, but the move to virtual reality should allow scientists to investigate in greater detail.

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WebMD offers helpful resources related to Alzheimer's disease.

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Resources and information that provide products, services, and other support for people with Alzheimer's disease and their families.

On this page, you'll find:

Find Professional Services

Legal Assistance

Financial Assistance

Federal Government Programs and Services

Prescription Assistance Programs

Safety and Home Healthcare

Travel

Caregiving and Caregiver Support

Long-Term Care and Living Options

Hospice Care

Find Professional Services

American Academy of Neurology. Provides its Find a Neurologist service by subspecialty, name, or area.
http://patients.aan.com/findaneurologist
1-800-879-1960

Legal Assistance

Financial Assistance

Federal Government Programs and Services

Center for Medicare and Medicaid Services (CMS), U.S. Department of Health & Human Services. Provides the latest information and resources on government-sponsored health programs, including:

Medicare, which is a federal program that provides some coverage for people who meet certain qualifications. Alzheimer's disease is not listed as a specific condition covered, but many aspects of treatment may be covered.

Medicaid programs, which are run by individual states.

Social Security Administration (SSA), which may also provide certain benefits to qualified individuals.

Veterans Benefit Programs, those who served in the armed services may qualify for certain Veterans Administration program benefits.

To find out what services are covered by Medicare, Medicaid, Social Security, or Veterans programs, visit www.brightfocus.org/alzheimers/financial-aid or call:
CMS at 1-800-633-4227
SSA at 1-800-772-1213
Veterans Benefits at 1-800-827-1000

Prescription Assistance Programs

Safety and Home Healthcare

Travel

Caregiving and Caregiver Support

Dementia Friendly America. A multi-sector, national collaborative to foster communities that are equipped to support people with dementia and their family and friend caregivers by becoming "dementia friendly."
www.dfamerica.org

Long-Term Care and Living Options

Hospice Care

Caring Connections. CaringInfo provides free resources to help people make decisions about end-of-life care and services before a crisis. Topics addressed include advanced directives, and hospice and palliative care, among others.
www.caringinfo.org
1-800-658-8898
Multilingual Helpline: 1-877-658-8896
Disclaimer: The information provided is a public service of BrightFocus Foundation and is not intended to constitute medical advice. Please consult your physician for personalized medical advice; all medications and supplements should only be taken under medical supervision. BrightFocus Foundation does not endorse any medical product or therapy. The organizations listed are not affiliated with BrightFocus Foundation. In addition, BrightFocus Foundation is not responsible for the content of these websites, and does not endorse any particular programs offered by these organizations.

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Helpful Resources for People Living with Alzheimer's Disease

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Resources and information that provide products, services, and other support for people with Alzheimer's disease and their families. On this page, you'll find: Find Professional Services Legal Assistance Financial Assistance Federal Government Programs and Services Prescription Assistance Programs Safety and Home Healthcare Travel Caregiving and Caregiver Support Long-Term Care and Living Options Hospice Care American Academy of Neurology.

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We are compiling information for families who are just learning about Alzheimer's and for individuals looking for more information about the disease and related types of dementia. If you are looking for additional help or support, visit our forums and become part of our community.

The most up to date numbers about Alzheimer's and how it impacts people globally. Read more >>

Find information about Alzheimer's clinical trials, including tools to locate trials in your area. Read more >>

Find and learn about Alzheimer's research centers and organizations that support Alzheimer's research. Read more >>

Dementia care is a daunting task, but may not be as challenging as you expect. Read more >>

Discover how Alzheimer's and Dementia are remarkably different. Read more >>

Learn about the various causes and symptoms of types of dementia. Read more >>

Explore our directory of additional Alzheimer's resources for caregivers and seniors. Read more >>

The Alzheimer's Association reports that the estimated progression rate of Alzheimer's in the U.S. from 2000-2050 will increase by 193%. Read more >>

About the symptoms, therapies and prognosis of frontal lobe dementia - also known as frontal temporal dementia. Read more >>

Pick's disease is a rare type of age-related dementia that affects the frontal lobes of the brain and causes speech problems like aphasia and behavior difficulties. Read more >>

How to obtain guardianship for a loved one with Alzheimer's disease. Read more >>

Learn about the stages of Alzheimer's disease from the beginning to it's end. Read more >>

Definitions and the latest research about Alzheimer's Disease. Read More >>

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We are compiling information for families who are just learning about Alzheimer's and for individuals looking for more information about the disease and related types of dementia. If you are looking for additional help or support, visit our forums and become part of our community.

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Alzheimer's Resources | Pierce County, WA - Official Website

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Services: Home visits to assess and give advice to family members on making client / family safer and more comfortable. Also operates several support groups and facilitates respite placement for up to 10 days in an Adult Family Home, an Assisted Living facility or a Skilled Nursing Facility if caregiver is unable to provide care (provided funding available).

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For physicians, resources on Alzheimer's and dementia, including patient and family educational materials and professional guides.

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Taking care of yourself-physically and mentally-is one of the most important things you can do as a caregiver. This could mean asking family members and friends to help out, doing things you enjoy, or getting help from a home health care service. Taking these actions can bring you some relief. It also may help keep you from getting ill or depressed.

Ways to Take Care of Yourself

Here are some ways you can take care of yourself:

Asking for Help

Everyone needs help at times. However, many caregivers find it hard to ask for help. They may feel they should be able to do everything themselves, or that it's not all right to leave the person in their care with someone else. Or maybe they can't afford to pay someone to watch the person for an hour or two.

Here are some tips about asking for help:

Remind yourself that it's okay to ask for help from family, friends, and others. You don't have to do everything yourself.

Ask people to help out in specific ways, like making a meal, visiting the person, or taking the person out for a short time.

Call for help from home health care or adult day care services when needed. To find providers in your area, contact Eldercare Locator.

Use national and local resources to find out how to pay for some of this help or get respite care services.

You may want to join a support group of Alzheimer's disease caregivers. These groups meet in person or online to share experiences and tips and give each other support. Ask your doctor, check online, or contact the local chapter of the Alzheimer's Association.

It is important to have a plan in case of your own illness, disability, or death.

Consult a lawyer about setting up a living trust, durable power of attorney for health care and finances, and other estate planning tools.

Consult with family and close friends to decide who will take responsibility for the person with Alzheimer's. You also may want to seek information about your local public guardian's office, mental health conservator's office, adult protective services, or other case management services. These organizations may have programs to assist the person with Alzheimer's in your absence.

Maintain a notebook for the responsible person who will assume caregiving. Such a notebook should contain the following information:

Preview board and care or long-term care facilities in your community and select a few as possibilities. Share this information with the responsible person. If the person with Alzheimer's disease is no longer able to live at home, the responsible person will be better able to carry out your wishes for long-term care.

Coping with Emotions and Stress

Caring for a person with Alzheimer's takes a lot of time and effort. Your job can become even harder when the person gets angry with you, hurts your feelings, or forgets who you are. Sometimes, you may feel discouraged, sad, lonely, frustrated, confused, or angry. These feelings are normal.

Here are some things you can say to yourself that might help you feel better:

I'm doing the best I can.

What I'm doing would be hard for anyone.

I'm not perfect, and that's okay.

I can't control some things that happen.

Sometimes, I just need to do what works for right now.

I will enjoy the moments when we can be together in peace.

Even when I do everything I can think of, the person with Alzheimer's disease will still have problem behaviors because of the illness, not because of what I do.

I will try to get help from a counselor if caregiving becomes too much for me.

Share this infographic and help spread the word about caring for yourself while caring for others.

Some caregivers find that going to a church, temple, or mosque helps them cope with the daily demands placed on them. For others, simply having a sense that larger forces are at work in the world helps them find a sense of balance and peace.

Getting Professional Help

Mental health professionals and social workers help you deal with any stress you may be feeling. They help you understand feelings, such as anger, sadness, or feeling out of control. They can also help you make plans for unexpected or sudden events.

Mental health professionals charge by the hour. Medicare, Medicaid, and some private health insurance plans may cover some of these costs. Ask your health insurance plan which mental health counselors and services it covers. Then check with your doctor, local family service agencies, and community mental health agencies for referrals to counselors.

More Tips for Self-Care

Here are other things to keep in mind as you take care of yourself:

Understand that you may feel powerless and hopeless about what's happening to the person you care for.

Understand that you may feel a sense of loss and sadness.

Understand why you've chosen to take care of the person with Alzheimer's disease. Ask yourself if you made this choice out of love, loyalty, a sense of duty, a religious obligation, financial concerns, fear, a habit, or self-punishment.

Let yourself feel day-to-day "uplifts." These might include good feelings about the person you care for, support from other people, or time spent on your own interests.

Read about this topic in Spanish. Lea sobre este tema en español.

For More Information About Caring for Yourself

NIA Alzheimer's and related Dementias Education and Referral (ADEAR) Center
800-438-4380 (toll-free)
adear@nia.nih.gov
www.nia.nih.gov/alzheimers
The National Institute on Aging's ADEAR Center offers information and free print publications about Alzheimer's disease and related dementias for families, caregivers, and health professionals. ADEAR Center staff answer telephone, email, and written requests and make referrals to local and national resources.

This content is provided by the NIH National Institute on Aging (NIA). NIA scientists and other experts review this content to ensure it is accurate and up to date.

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Alzheimer's Caregiving: Caring for Yourself

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Taking care of yourself-physically and mentally-is one of the most important things you can do as a caregiver. This could mean asking family members and friends to help out, doing things you enjoy, or getting help from a home health care service. Taking these actions can bring you some relief.

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AFA's Membership and Screening Portal | Alzheimer's Foundation of America

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Proton pump inhibitors (PPIs) are medicines commonly prescribed to treat acid-related digestive problems, including gastroesophageal reflux disease (or GERD). As of 2011, up to 1 in 5 older adults reported using a PPI. Although healthcare practitioners have long believed that PPIs are safe, recent studies have linked PPIs to potential risks, including fractures and kidney disease. Some studies also have linked PPIs to an increased risk for dementia among older adults. However, several experts have suggested that these studies may not correctly measure the connection.

In a new research article published in the Journal of the American Geriatrics Society, scientists were able to conclude that developing dementia or Alzheimer's disease (the most common form of dementia) did not appear to be linked to taking PPIs.

The researchers reviewed information from the Adult Changes in Thought (ACT) study, which included 3,484 adults aged 65 and older. Participants did not have dementia at the beginning of the study and were followed for an average of about 7.5 years.

Researchers tested participants for dementia at the beginning of the study and then every two years. Those who tested positive were given complete evaluations to measure their abilities to think and make decisions. Researchers gave the participants who were diagnosed with dementia follow-up tests to confirm the diagnosis.

Researchers used information from the ACT study to learn how many participants took PPIs and for how long. Overall, almost 24 percent of study participants developed dementia. Of these individuals, just 670 people developed possible or probable Alzheimer's disease. While other safety concerns with long-term PPI use exist, the researchers conluded that results from this study suggest that dementia is not linked to taking a PPI.

Journal Reference:

Shelly L. Gray, Rod L. Walker, Sascha Dublin, Onchee Yu, Erin J. Aiello Bowles, Melissa L. Anderson, Paul K. Crane, Eric B. Larson. Proton Pump Inhibitor Use and Dementia Risk: Prospective Population-Based Study. Journal of the American Geriatrics Society, 2017; DOI: 10.1111/jgs.15073

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alzheimer's research; healthy aging; gastrointestinal problems; heartburn; alzheimer's; dementia; disorders and syndromes; caregiving

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Taking proton pump inhibitors not linked to higher dementia risk

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Proton pump inhibitors (PPIs) are medicines commonly prescribed to treat acid-related digestive problems, including gastroesophageal reflux disease (or GERD). As of 2011, up to 1 in 5 older adults reported using a PPI. Although healthcare practitioners have long believed that PPIs are safe, recent studies have linked PPIs to potential risks, including fractures and kidney disease.

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Several studies have reported associations between proton-pump inhibitor (PPI) use and dementia. New research published on July 18 in Gastroenterology, the official journal of the American Gastroenterological Association (AGA), puts these claims to rest. The study authors report that there is no convincing evidence to support the suggestion that PPI use increases dementia risk. These findings are based on an analysis of 13,864 participants from the Nurses' Health Study II who completed testing on cognitive function, which is key predictor of the risk of dementia later in life.

PPIs are widely prescribed for the treatment of acid-related upper gastrointestinal disorders, such as gastroesophageal reflux disease (GERD). While PPIs are known to effectively treat these conditions, they have received negative publicity in recent years as research has associated PPIs with several adverse outcomes.

"One of the most common questions gastroenterologists receive from their patients is whether PPIs are safe to use, based on the troubling headlines linking PPIs to everything from hip fracture, to dementia, to death," said study author Andrew T. Chan, MD, MPH, an expert of the American Gastroenterological Association from Massachusetts General Hospital and Harvard Medical School, Boston. "Our new research should provide some reassurance to individuals who require these highly effective medications for long-term treatment."

This research directly responds to a 2016 pharmacoepidemiologic analysis conducted using a large German health insurance database, which identified an association between dementia and long-term PPI use; however, these findings could not illustrate that PPIs caused dementia. Despite the attention this article received at the time, AGA expressed its concerns on this research at the time of publication .
Three important reminders for patients taking PPIs:
1. Talk to your doctor before making any changes to your medication. You have been prescribed PPIs for a reason, to treat a diagnosed medical condition. You and your doctor can discuss the reason for your prescription, the dose and the timeframe for treatment.

2. Consider life-style modifications that may reduce or eliminate the need for PPIs for long-term use. These may include weight loss, avoiding tobacco or a change in your eating patterns. Your doctor can help you determine the changes that are right for you.

3. Keep in touch with your doctor. Research continues to be done on PPI use. While the latest research and headlines on PPIs may seem scary, current research still recommends that patients who have a diagnosed condition that is helped by PPIs should stay on them, as benefits can outweigh risks.

Journal Reference:

Paul Lochhead, Kaitlin Hagan, Amit D. Joshi, Hamed Khalili, Long H. Nguyen, Francine Grodstein, Andrew T. Chan. Association Between Proton Pump Inhibitor Use and Cognitive Function in Women. Gastroenterology, 2017; DOI: 10.1053/j.gastro.2017.06.061

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alzheimer's research; healthy aging; pharmacology; today's healthcare; alzheimer's; dementia; disorders and syndromes; depression

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Setting the record straight: PPIs do not cause Dementia

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Several studies have reported associations between proton-pump inhibitor (PPI) use and dementia. New research puts these claims to rest, experts say. The study authors report that there is no convincing evidence to support the suggestion that PPI use increases dementia risk.

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You may not have heard of it, but frontotemporal degeneration (FTD) accounts for 20 to 50 percent of dementia cases in people under the age of 65. FTD ravages an individual's quality of life by dramatically altering their language, personality, behavior, cognition and motor function. But it doesn't end there.

Research led by Florida Atlantic University, in collaboration with the Association for Frontotemporal Degeneration and Emory University, is the first to capture the economic burden of FTD in the United States and the results are staggering. The study, published in Neurology ®, the medical journal of the American Academy of Neurology, reveals that costs associated with FTD are twice that of Alzheimer's disease (AD). The researchers also found that costs for FTD were greater in the U.S. than in studies originating in other countries and the implications for patients and their caregivers are dire.

"Frontotemporal degeneration is associated with substantial direct and indirect costs, diminished quality of life, and increased caregiver burden," said James E. Galvin, M.D., M.P.H., lead author, associate dean for clinical research in FAU's Charles E. Schmidt College of Medicine, and a leading international expert on AD, Lewy Body Dementia (LBD), and FTD. "Most patients with this disease are working age and have to leave the labor force during their peak earning years. Caregivers of these patients also may need to alter their careers to provide care. Combined, these factors contribute to substantial decrease in household income."

Patients with FTD and their caregivers are typically in their prime earning years, they have dependent children and they have difficulty accessing services developed for older adults primarily with dementia. Although symptoms from this neurodegenerative disease differ, it causes progressive loss of function and independence over the course of two to 20 years.

Findings from the study show that the overall household income 12 months before FTD diagnosis ranged from $75,000 to $99,000, but declined after diagnosis from $50,000 to $59,999. Total direct costs associated with FTD (value of goods and services for which there are explicit monetary payments) were $47,916 and total indirect costs were $71,737; combined annual costs were $119,654.

Men had higher indirect costs because they were more likely to use unpaid care and to have stopped working because of the disease. Women had higher direct costs, mainly because they were more likely to live in nursing homes or assisted living facilities. Patients with severe or terminal stages of disease incurred higher direct costs ($54,000).

For the study and to quantify the socioeconomic burden of this disease, the researchers conducted a web-based survey (674 out of 956 individuals completed the survey) to characterize the patient and caregiver experience with FTD-related resource use, health-related quality of life, and per-patient annual costs. The patients were divided into four groups based on the caregiver's assessment: mild, moderate, severe, or terminal. The majority of caregiver respondents were female spouses, while the majority of patients were men.

At the time of the survey, 45 percent of caregivers still worked, while 37 percent were no longer employed after the patient's FTD diagnosis. Seventy-four percent of the caregivers worked full-time and only 3.3 percent of the patients were still working. Caregivers reported lost days of work due to patient health issues (25.6 percent) or caregiver health issues (21.6 percent). Caregivers who were still working full-time reported a median loss of seven days over the previous four weeks due to FTD-related matters.

In addition, the researchers found that 67 percent of the caregivers reported a notable decline in their own health and that 53 percent reported increased personal health care costs. On average, caregivers had seven clinician visits and slightly less than one inpatient admission per year. On average, patients had six overnight respite stays, 16 daytime respite stays, 35 clinician visits, and two hospital or emergency room visits. About 32 percent of respondents needed to hire a paid caregiver several times per week.

Caregivers also reported patient-related crises during the prior year: 19 percent required an emergency department visit; 8 percent required urgent psychiatric care; 6 percent required police intervention; and 6 percent required contacting a lawyer for various reasons such as bankruptcy, loss of business, loss of home or legal guardianship.

"We hope that our study will provide a better understanding of the substantial socioeconomic burden of frontotemporal degeneration and deliver the needed evidence to help inform health care policy, drive research agendas, and enhance targeted allocation of resources that will lead to timely and accurate diagnosis as well as effective treatments where none exist today," said Galvin.

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patient education and counseling; today's healthcare; alzheimer's research; diseases and conditions; alzheimer's; dementia; disorders and syndromes; caregiving

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Staggering economic burden of dementia in younger people, study reveals: First-of-its-kind study on frontotemporal degeneration

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Frontotemporal degeneration (FTD) -- the most common dementia for people under age 60 -- inflicts a significantly higher economic burden on both patients and their caregivers, a new study shows. While the social and economic cost of Alzheimer's is well documented, the study found that the average annual costs associated with FTD to total $119,654, nearly two times the reported annual cost of Alzheimer's.

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In a comfortable armchair, glass of sherry at her side, Elspeth Ford is getting to grips with her 3D goggles. "Maybe I'll go another other way now," she says, looking left, right, up, down. She breaks into a cheery rendition of the Lambeth Walk.

Elspeth, 79, is a resident at Langham Court, a dementia care home in Surrey, and today she is trialling a virtual reality project, Wayback, that has been designed especially for those living with dementia. Peering into her headset, Elspeth is temporarily transported to 2 June 1953, and a street party for the Queen's coronation. She is enjoying a children's fancy-dress competition. "I love that boy dressed as an Oxo cube," she laughs.

This is the first in what will become a series of virtual reality films set at historic moments, and available free for those with dementia, their families and carers to enjoy together through a mobile phone and a pair of inexpensive 3D goggles. The idea was developed by three advertising creatives with family experience of dementia. For Camilla Ford, Elspeth's daughter, it is an exciting concept. "It gave Mum a huge amount of pleasure and really engaged her," she says. Anxiety - "about what she is meant to be doing" - often stops Elspeth getting involved in activities. "Dementia is debilitating in so many ways; you always need creative ways to give positive experiences. She was immersed in this and it took her back to a time of happy memories, when she was productive and emotionally fulfilled."

Elspeth has had vascular dementia for seven years, and finding a point of contact increasingly involves moving to where she is, rather than trying to bring her into the present, says Camilla. "If she is in a place she can identify with, and we can see it too, we are somehow equalised. We are at a stage where we aren't trying to create memories but to relish positive emotions, dropping the expectation of who Mum was and just being with the person in front of us."

Elspeth sets off for lunch with her son Dominic, still smiling. It is unlikely, says Camilla, that her mother will remember what has made her feel happy. "The point is that she feels uplifted, not necessarily that she knows why."

Dan Cole, one of Wayback's creators, agrees. "If the film can open some memories, start a conversation or bring a smile, that's a success," he says. The idea began to form after a drive around Camden, north London, with his father, then in the early stages of Alzheimer's. "It was his old stomping ground and he kept recognising places and telling me little tales; the pub his dad drank in, where he hung about with his mates, even an alley where he once got into a scrap," says Dan. "In that fleeting moment it was so clear in his mind. I could ask questions. He could tell me things."

The effects on his father's mood, and on Dan's sense of connection with him, lasted longer. "It was the idea you could move forward by going back, maybe use those memories as a starting point for a shared experience." The resulting film was made over two days in a north-London street (satellite dishes and other modern trappings digitally removed) with a volunteer cast and crew of 187 and painstakingly sourced period props, costumes and menu (fish-paste sandwiches, notes one Langham Court resident approvingly). Dan's father, who died three years ago, is among the dedications at the end. The music - beyond the Lambeth Walk - is by Frankie Laine and Guy Mitchell. "My dad's favourites," says Dan.

Married couple Ronald and Anne Graham-Clarke are watching the film together. "Oh, this is fun. I feel as if I'm at the party," says Ronald, 89. Both he and Anne, 84, are chuckling. She taps her foot to the music. Afterwards, Anne tells Sarah Hoare, one of Langham Court's directors, about watching the coronation at home in Scotland with her parents and sister. "My family bought a TV for the first time to watch it. It was my parents' wedding anniversary too. It was a great party."

Anne's response, says Hoare, is a wonderful example of virtual reality's potential. "She completely came out of herself because she was relaxed and enjoying herself. I have never actually seen her laugh before."

Langham Court's philosophy is based on the Butterfly Household model, devised by Dr David Sheard, a dementia specialist and CEO of Dementia Care Matters, who is supporting Wayback. "People living with dementia become more feeling beings than thinking beings," he says. "Feelings endure and are more to be trusted when facts diminish." Facilitating a trip back in time - "to their undamaged longer-term memories" -can, he says, unlock the happy emotions that accompany them. "Wayback offers the opportunity to live in the moment, to go back in time and to just 'be' again and to feel validated."

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'Oh, this is fun. I feel as if I'm at the party.' Anne and Ronald Graham-Clarke. Photograph: Richard Saker for the Guardian

Reminiscence, using music, photographs, props and role play for instance, is a well-established model of dementia care. Virtual reality, Sheard believes, could provide a useful tool alongside this.

"The biggest risk to someone living with dementia is to lose self-esteem, to feel not connected. Years ago, it was thought to be ethical to remind people of the facts, but how do you put back what is gone from a person's brain? Eventually activities that tax the brain and short-term memory create stress and ill being."

The best measure of dementia care, Sheard believes, is wellbeing. "Dementia takes people back to the past as a way to make sense of the now. The feelings generated by an experience can stay for a very long time afterwards."

Daphne Padfield, 93, is taking her turn with the goggles. "I felt I was really there," she exclaims, when the film finishes. Did she attend a street party for the coronation, asks Hoare. Daphne's detailed response is a surprise. "I was actually there," she says. "My mother, sisters and I had seats on a very good stand. We all had new dresses. They were all dying to tell her about it when we got back to school." Daphne happily recounts her experiences of the day for some time. "It was such a thrill. I shall never forget," she says, rather poignantly. "It is forever imprinted in my memory."
To watch the film in full VR, search for The Wayback VR on YouTube's mobile app. The Wayback App is coming soon. For more information please visit thewaybackvr.com

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How virtual reality is taking dementia patients back to the future

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In a comfortable armchair, glass of sherry at her side, Elspeth Ford is getting to grips with her 3D goggles. "Maybe I'll go another other way now," she says, looking left, right, up, down. She breaks into a cheery rendition of the Lambeth Walk.

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A Japanese research group has revealed that elderly people with mild cognitive impairment (MCI) have a particularly weakened ability to memorize human faces in the short term when compared to healthy elderly people. MCI patients also had a different gaze behavior when trying to memorize a face. This research may lead to the early detection of dementia.

Alzheimer's disease is considered to be the most common type of dementia, and early detection of preliminary stages is important to halt its progression into a more serious form of the disease. MCI, which is thought to be a preliminary stage of Alzheimer's, is a state in which cognitive functions, such as memory or thinking ability, decrease at a level that do not affect daily life.

Brain imaging studies show that areas of the brain for memory and visually processing human faces in people with MCI are structurally and functionally transformed. To investigate these specific and yet unstudied areas, a research group from Kumamoto University in Japan conducted comparative experiments with normal elderly subjects and MCI patients (18 each) using a delayed-matching task with face and house stimuli in independent blocks. In each block, they asked subjects to remember a single image and then, after a short delay, select a memorized image from a set new of images. The researchers also recorded subject gaze trends during the image memorization process.

Their experiments revealed that the memorization performance of MCI patients was lower for facial images than for house images, but found no performance difference in normal subjects. The research also showed that, during the memorization process, MCI patient gaze concentration on the eyes of an image decreased but the time spent looking at the mouth increased in comparison to normal subjects. In essence, MCI patients had reduced short-term memorization ability and a different gaze pattern for faces when compared to normal people.

"Looking at the eyes is important for remembering the entirety of the face," said Emeritus Professor Kaoru Sekiyama. "MCI patients probably have an abnormality in the cognitive processing of faces due to the deterioration of brain function. It is possible that the distributed gaze pattern is compensation for this decreased function. We hope to shed some light on this possibility in future work."

This research result was posted online in the journal Scientific Reports on 30 October 2017.
Story Source:
Materials provided by Kumamoto University

. Note: Content may be edited for style and length.

Journal Reference:

Toshikazu Kawagoe, Masateru Matsushita, Mamoru Hashimoto, Manabu Ikeda, Kaoru Sekiyama. Face-specific memory deficits and changes in eye scanning patterns among patients with amnestic mild cognitive impairment. Scientific Reports, 2017; 7 (1) DOI: 10.1038/s41598-017-14585-5

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alzheimer's research; healthy aging; elder care; today's healthcare; dementia; perception; intelligence; alzheimer's

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Preliminary stages of dementia reduce human face memorization ability

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Scientists have revealed that elderly people with mild cognitive impairment (MCI) have a particularly weakened ability to memorize human faces in the short term when compared to healthy elderly people. MCI patients also had a different gaze behavior when trying to memorize a face. This research may lead to the early detection of dementia.

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Using 'Raman' optical technology, scientists of the University of Twente in The Netherlands, can now produce images of brain tissue that is affected by Alzheimer's disease. The images include the surrounding areas, already showing changes.

Alzheimer's disease is associated with areas of high protein concentration in brain tissue: plaques and tangles. Raman imaging is now used to get sharp images of these affected areas. It is an attractive technique, because it shows more than the specific proteins involved. The presence of water and lipids, influenced by protein presence, can also be detected. Using this technique, the researchers have studied brain tissue of four brain donors, three of them with Alzheimer's disease.
Transition
The affected area can, in this way, be shown in a sharp and clear way. After image processing, even an area appears that is in transition between healthy and affected tissue: this may give an indication how the disease is spreading in the brain. Even in the brain tissue of the healthy person, a small area is detected with protein activity. This can be a first sign of a neurodegenerative disease.

Raman microscopy uses a laser beam for the detection of chemical substances. The energy of the reflected and scattered light gives an indication of the substances present in a sample. In each of the four brain samples, 4096 spectra were examined in this way. A major advantage of Raman is that the chemicals don't need a pretreatment, it is 'label free'. In chemical analysis, Raman has proven to be a powerful technique.
Cell level and smaller
In this case, Raman was used to examine brain tissue outside the body, but it could even be used 'in vivo' for detecting specific areas during surgery. Compared to MRI, PET and CT imaging, Raman is able to detect areas, smaller than cells, with very high precision. In this way, it can be a very valuable extra technique. The Raman images now show protein activity at neural cell level, but the sensitivity is high enough for detecting areas that are even smaller -- as is the case with the brain sample of the healthy person.

Cees Otto, of the Medical Cell Biophysics group of UT, published his work in Scientific Reports, together with colleagues from Leiden University and from Spain and Austria.

Journal Reference:

Ralph Michael, Aufried Lenferink, Gijs F. J. M. Vrensen, Ellen Gelpi, Rafael I. Barraquer, Cees Otto. Hyperspectral Raman imaging of neuritic plaques and neurofibrillary tangles in brain tissue from Alzheimer's disease patients. Scientific Reports, 2017; 7 (1) DOI: 10.1038/s41598-017-16002-3

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medical devices; nervous system; brain tumor; alzheimer's research; alzheimer's; intelligence; brain-computer interfaces; brain injury

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Imaging technique shows progress Alzheimer's disease

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Using 'Raman' optical technology, scientists of the University of Twente in The Netherlands, can now produce images of brain tissue that is affected by Alzheimer's disease. The images include the surrounding areas, already showing changes. Alzheimer's disease is associated with areas of high protein concentration in brain tissue: plaques and tangles.

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The health advantages of high-intensity exercise are widely known but new research from McMaster University points to another major benefit: better memory.

The findings could have implications for an aging population which is grappling with the growing problem of catastrophic diseases such as dementia and Alzheimer's.

Scientists have found that six weeks of intense exercise -- short bouts of interval training over the course of 20 minutes -- showed significant improvements in what is known as high-interference memory, which, for example, allows us to distinguish our car from another of the same make and model.

The study is published in the Journal of Cognitive Neuroscience.

The findings are important because memory performance of the study participants, who were all healthy young adults, increased over a relatively short period of time, say researchers.

They also found that participants who experienced greater fitness gains also experienced greater increases in brain-derived neurotrophic factor (BDNF), a protein that supports the growth, function and survival of brain cells.

"Improvements in this type of memory from exercise might help to explain the previously established link between aerobic exercise and better academic performance," says Jennifer Heisz, an assistant professor in the Department of Kinesiology at McMaster and lead author of the study.

"At the other end of our lifespan, as we reach our senior years, we might expect to see even greater benefits in individuals with memory impairment brought on by conditions such as dementia," she says.

For the study, 95 participants completed six weeks of exercise training, combined exercise and cognitive training or no training (the control group which did neither and remained sedentary). Both the exercise and combined training groups improved performance on a high-interference memory task, while the control group did not.

Researchers measured changes in aerobic fitness, memory and neurotrophic factor, before and after the study protocol.

The results reveal a potential mechanism for how exercise and cognitive training may be changing the brain to support cognition, suggesting that the two work together through complementary pathways of the brain to improve high-interference memory.

Researchers have begun to examine older adults to determine if they will experience the same positive results with the combination of exercise and cognitive training.

"One hypothesis is that we will see greater benefits for older adults given that this type of memory declines with age," says Heisz. "However, the availability of neurotrophic factors also declines with age and this may mean that we do not get the synergistic effects."

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fitness; alzheimer's research; medical education and training; healthy aging; dementia; memory; educational psychology; intelligence

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High-intensity exercise boosts memory, new research suggests

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The health advantages of high-intensity exercise are widely known but new research points to another major benefit: better memory. The findings could have implications for an aging population which is grappling with the growing problem of catastrophic diseases such as dementia and Alzheimer's.

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New mechanisms found of cell death in neurodegenerative disorders

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New mechanisms found of cell death in neurodegenerative disorders

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People who have a high body mass index (BMI) are more likely to develop dementia than those with a normal weight, according to a new UCL-led study.

The study, published in the Alzheimer's & Dementia journal, analysed data from 1.3 million adults living in the United States and Europe. The researchers also found that people near dementia onset, who then go on to develop dementia, tend to have lower body weight than their dementia-free counterparts.

"The BMI-dementia association observed in longitudinal population studies, such as ours, is actually attributable to two processes," said lead author of the study, Professor Mika Kivimäki (UCL Institute of Epidemiology & Health). "One is an adverse effect of excess body fat on dementia risk. The other is weight loss due to pre-clinical dementia. For this reason, people who develop dementia may have a higher-than-average body mass index some 20 years before dementia onset, but close to overt dementia have a lower BMI than those who remain healthy."

"The new study confirms both the adverse effect of obesity as well as weight loss caused by metabolic changes during the pre-dementia stage."

Past research on how a person's weight influences their risk of dementia has produced conflicting results. Some findings have suggested that being obese poses a higher dementia risk, but other studies have linked lower weight to increased dementia incidence.

In this study, researchers from across Europe pooled individual-level data from 39 longitudinal population studies from the United States, the United Kingdom, France, Sweden, and Finland. A total of 1,349,857 dementia-free adults participated in these studies and their weight and height were assessed. Dementia was ascertained using linkage to electronic health records obtained from hospitalisation, prescribed medication and death registries.

A total of 6,894 participants developed dementia during up to 38 years of follow-up. Two decades before symptomatic dementia, higher BMI predicted dementia occurrence: each 5-unit increase in BMI was associated with a 16-33% higher risk of this condition (5 BMI units is 14.5kg for a person 5'7" (170cm) tall, approximately the difference in weight between the overweight and normal weight categories or between the obese and overweight categories). In contrast, the mean level of BMI during pre-clinical stage close to dementia onset was lower compared to that in participants who remained healthy.

In 2015, the number of people with dementia reached almost 45 million, two times more than in 1990. This study suggests that maintaining a healthy weight could prevent, or at least delay, dementia.

Journal Reference:

Mika Kivimäki, Ritva Luukkonen, G. David Batty, Jane E. Ferrie, Jaana Pentti, Solja T. Nyberg, Martin J. Shipley, Lars Alfredsson, Eleonor I. Fransson, Marcel Goldberg, Anders Knutsson, Markku Koskenvuo, Eeva Kuosma, Maria Nordin, Sakari B. Suominen, Töres Theorell, Eero Vuoksimaa, Peter Westerholm, Hugo Westerlund, Marie Zins, Miia Kivipelto, Jussi Vahtera, Jaakko Kaprio, Archana Singh-Manoux, Markus Jokela. Body mass index and risk of dementia: Analysis of individual-level data from 1.3 million individuals. Alzheimer's & Dementia, 2017; DOI: 10.1016/j.jalz.2017.09.016

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obesity; alzheimer's research; diet and weight loss; healthy aging; dementia; alzheimer's; dieting and weight control; disorders and syndromes

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People who have a high body mass index (BMI) are more likely to develop dementia than those with a normal weight, according to a new UCL-led study. The study, published in the Alzheimer's & Dementia journal, analysed data from 1.3 million adults living in the United States and Europe.

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Gene variant that protects against Alzheimer's disease identified

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Gene variant that protects against Alzheimer's disease identified

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Alzheimer's: Second phase 3 study results for tau aggregation inhibitor

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Alzheimer's: Second phase 3 study results for tau aggregation inhibitor

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TauRx Therapeutics Ltd today reported the full results from its second Phase 3 clinical study of LMTX®, the first tau aggregation inhibitor in Alzheimer's disease, published online in the Journal of Alzheimer's Disease.

Results from this study (TRx-237-005) are consistent with those from the first Phase 3 study, recently published in The Lancet [(TRx-237-015) Gauthier et al. 20161] in mild to moderate Alzheimer's disease, in supporting the hypothesis that LMTX® might be effective as monotherapy at a dose as low as 4 mg twice daily. The latest study (TRx-237-005) investigated the efficacy and safety of LMTX® in 800 patients with mild Alzheimer's disease at a dose of either 100 mg or 4 mg (intended as the control dose) twice daily over an 18-month treatment period.

The results of the earlier study showed significant differences in favour of two higher doses of LMTX® (75 mg and 125 mg twice daily) when taken as monotherapy compared with the intended 4 mg control dose taken as monotherapy or as add-on therapy to currently approved treatments for Alzheimer's disease in prespecified post hoc analyses. In a further analysis, the same difference in favour of monotherapy compared with add-on treatment was found in patients taking the 4 mg twice daily dose. Therefore, prior to database lock and unblinding, the primary analyses of TRx-237-005 were modified to compare 100 mg LMTX® twice daily as monotherapy with the intended control, and 4 mg twice daily as monotherapy compared with the same dose as add-on therapy as non-randomised cohort analyses. The aim was to test whether the findings from the first study could be confirmed as primary outcomes in a second independent study with strong controls against statistical error. Results of the second study showed the same significant differences in favour of LMTX® monotherapy at the required statistical threshold of p < 0.025 in both comparisons on the co-primary clinical efficacy endpoints for the cognitive (ADAS-cog) and functional (ADCS-ADL) outcomes.

In both the LMTX® monotherapy and add-on therapy groups, whole brain atrophy (measured via MRI scans) initially progressed as expected for patients with mild Alzheimer's disease. However, after 9 months of treatment, the annualised rate of whole brain atrophy in monotherapy patients reduced significantly and became typical of that reported in normal elderly controls without Alzheimer's disease. The comparable rate seen in the add-on therapy group progressed as reported for patients with mild Alzheimer's disease.

Similarly, additional findings from FDG-PET scans in TRx-237-005 indicated that the decline in temporal lobe glucose uptake in those patients receiving LMTX monotherapy was significantly less than that typically reported for patients with mild Alzheimer's disease. When the various analyses were corrected for potential differences in severity or diagnosis at baseline between monotherapy and add-on therapy cohorts, the results remained robustly significant.

"While the monotherapy subgroups in the first and second Phase 3 LMTX studies remain small -- 15% and 20% respectively -- the confirmation of the same pattern of results in the second independent study means they are unlikely to be a chance finding," said Prof. Claude Wischik, of Aberdeen University and executive chairman of TauRx Therapeutics Ltd.

"The overall retention rates in the second study were similar in both monotherapy and add-on treatment groups, so differential withdrawal rates cannot be the explanation. Likewise, seeing the same results in the second study conducted only in North America, Western Europe and Australia means that the first study was not atypical in some way through its inclusion of non-western countries. Finding the same pattern of results in the clinical and imaging outcomes also means that they cannot be explained as placebo effects in patients coming into a treatment setting for the first time."

Prof. Wischik went on to comment: "Although these results come from non-randomised cohort analyses, a number of things point to real treatment effects and not just differences between patients taking or not taking the standard treatments. The analysis showing a slow-down in the brain atrophy rate is a before-and-after analysis in which the monotherapy patients were their own controls, and so does not depend on a comparison with add-on therapy patients. We are also starting to understand the pharmacologic basis of the negative interaction between LMTX® and the standard treatments since we have now seen the same thing happening in an animal model of tau protein aggregation."

"These highly significant results support further validation of tau-based therapy in Alzheimer's disease," said George Perry, Dean of Sciences, University of Texas at San Antonio and Editor-in-Chief of the Journal of Alzheimer's Disease.

The lead author of the study, Gordon Wilcock, Emeritus Professor of Geratology and Honorary Clinical Senior Research Fellow in the Nuffield Department of Clinical Neurosciences at the University of Oxford, commented: "These data indicate the need for a further randomised controlled trial to evaluate efficacy of low dose LMTX® in patients not taking current treatments."

Further randomised controlled studies of LMTX® are set to commence shortly in which the 4 mg twice daily dose will be compared with placebo in patients with Alzheimer's disease who are not receiving other approved treatments for this condition (cholinesterase inhibitors and/or memantine).

Journal Reference:

Gordon K. Wilcock, Serge Gauthier, Giovanni B. Frisoni, Jianping Jia, Jiri H. Hardlund, Hans J. Moebius, Peter Bentham, Karin A. Kook, Bjoern O. Schelter, Damon J. Wischik, Charles S. Davis, Roger T. Staff, Vesna Vuksanovic, Trevor Ahearn, Luc Bracoud, Kohkan Shamsi, Ken Marek, John Seibyl, Gernot Riedel, John M.D. Storey, Charles R. Harrington, Claude M. Wischik. Potential of Low Dose Leuco-Methylthioninium Bis(Hydromethanesulphonate) (LMTM) Monotherapy for Treatment of Mild Alzheimer's Disease: Cohort Analysis as Modified Primary Outcome in a Phase III Clinical Trial. Journal of Alzheimer's Disease, 2017; 61 (1): 435 DOI: 10.3233/JAD-170560

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alzheimer's research; healthy aging; diseases and conditions; elder care; alzheimer's; dementia; disorders and syndromes; caregiving

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Alzheimer's: Second phase 3 study results for tau aggregation inhibitor

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TauRx Therapeutics Ltd today reported the full results from its second Phase 3 clinical study of LMTX®, the first tau aggregation inhibitor in Alzheimer's disease, published online in the Journal of Alzheimer's Disease. Results from this study (TRx-237-005) are consistent with those from the first Phase 3 study, recently published in The Lancet [(TRx-237-015) Gauthier et al.

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You may not have heard of it, but frontotemporal degeneration (FTD) accounts for 20 to 50 percent of dementia cases in people under the age of 65. FTD ravages an individual's quality of life by dramatically altering their language, personality, behavior, cognition and motor function. But it doesn't end there.

Research led by Florida Atlantic University, in collaboration with the Association for Frontotemporal Degeneration and Emory University, is the first to capture the economic burden of FTD in the United States and the results are staggering. The study, published in Neurology ®, the medical journal of the American Academy of Neurology, reveals that costs associated with FTD are twice that of Alzheimer's disease (AD). The researchers also found that costs for FTD were greater in the U.S. than in studies originating in other countries and the implications for patients and their caregivers are dire.

"Frontotemporal degeneration is associated with substantial direct and indirect costs, diminished quality of life, and increased caregiver burden," said James E. Galvin, M.D., M.P.H., lead author, associate dean for clinical research in FAU's Charles E. Schmidt College of Medicine, and a leading international expert on AD, Lewy Body Dementia (LBD), and FTD. "Most patients with this disease are working age and have to leave the labor force during their peak earning years. Caregivers of these patients also may need to alter their careers to provide care. Combined, these factors contribute to substantial decrease in household income."

Patients with FTD and their caregivers are typically in their prime earning years, they have dependent children and they have difficulty accessing services developed for older adults primarily with dementia. Although symptoms from this neurodegenerative disease differ, it causes progressive loss of function and independence over the course of two to 20 years.

Findings from the study show that the overall household income 12 months before FTD diagnosis ranged from $75,000 to $99,000, but declined after diagnosis from $50,000 to $59,999. Total direct costs associated with FTD (value of goods and services for which there are explicit monetary payments) were $47,916 and total indirect costs were $71,737; combined annual costs were $119,654.

Men had higher indirect costs because they were more likely to use unpaid care and to have stopped working because of the disease. Women had higher direct costs, mainly because they were more likely to live in nursing homes or assisted living facilities. Patients with severe or terminal stages of disease incurred higher direct costs ($54,000).

For the study and to quantify the socioeconomic burden of this disease, the researchers conducted a web-based survey (674 out of 956 individuals completed the survey) to characterize the patient and caregiver experience with FTD-related resource use, health-related quality of life, and per-patient annual costs. The patients were divided into four groups based on the caregiver's assessment: mild, moderate, severe, or terminal. The majority of caregiver respondents were female spouses, while the majority of patients were men.

At the time of the survey, 45 percent of caregivers still worked, while 37 percent were no longer employed after the patient's FTD diagnosis. Seventy-four percent of the caregivers worked full-time and only 3.3 percent of the patients were still working. Caregivers reported lost days of work due to patient health issues (25.6 percent) or caregiver health issues (21.6 percent). Caregivers who were still working full-time reported a median loss of seven days over the previous four weeks due to FTD-related matters.

In addition, the researchers found that 67 percent of the caregivers reported a notable decline in their own health and that 53 percent reported increased personal health care costs. On average, caregivers had seven clinician visits and slightly less than one inpatient admission per year. On average, patients had six overnight respite stays, 16 daytime respite stays, 35 clinician visits, and two hospital or emergency room visits. About 32 percent of respondents needed to hire a paid caregiver several times per week.

Caregivers also reported patient-related crises during the prior year: 19 percent required an emergency department visit; 8 percent required urgent psychiatric care; 6 percent required police intervention; and 6 percent required contacting a lawyer for various reasons such as bankruptcy, loss of business, loss of home or legal guardianship.

"We hope that our study will provide a better understanding of the substantial socioeconomic burden of frontotemporal degeneration and deliver the needed evidence to help inform health care policy, drive research agendas, and enhance targeted allocation of resources that will lead to timely and accurate diagnosis as well as effective treatments where none exist today," said Galvin.

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patient education and counseling; today's healthcare; alzheimer's research; diseases and conditions; alzheimer's; dementia; disorders and syndromes; caregiving

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Staggering economic burden of dementia in younger people, study reveals: First-of-its-kind study on frontotemporal degeneration

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Frontotemporal degeneration (FTD) -- the most common dementia for people under age 60 -- inflicts a significantly higher economic burden on both patients and their caregivers, a new study shows. While the social and economic cost of Alzheimer's is well documented, the study found that the average annual costs associated with FTD to total $119,654, nearly two times the reported annual cost of Alzheimer's.

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Tiny air pollution particles -- the type that mainly comes from power plants and automobiles -- may greatly increase the chance of dementia, including Alzheimer's disease, according to USC-led research.

Scientists and engineers found that older women who live in places with fine particulate matter exceeding the U.S. Environmental Protection Agency's standard are 81 percent more at risk for global cognitive decline and 92 percent more likely to develop dementia, including Alzheimer's.

If their findings hold up in the general population, air pollution could be responsible for about 21 percent of dementia cases, according to the study.

"Microscopic particles generated by fossil fuels get into our body directly through the nose into the brain," said University Professor Caleb Finch at the USC Leonard Davis School of Gerontology and co-senior author of the study. "Cells in the brain treat these particles as invaders and react with inflammatory responses, which over the course of time, appear to exacerbate and promote Alzheimer's disease.

"Although the link between air pollution and Alzheimer's disease is a new scientific frontier, we now have evidence that air pollution, like tobacco, is dangerous to the aging brain."

The adverse effects were stronger in women who had the APOE4 gene, a genetic variation that increases the risk for Alzheimer's.

"Our study -- the first of its kind conducted in the U.S. -- provides the inaugural scientific evidence of a critical Alzheimer's risk gene possibly interacting with air particles to accelerate brain aging," said Jiu-Chiuan Chen, co-senior author of the study and an associate professor of preventive medicine at the Keck School of Medicine of USC. "The experimental data showed that exposure of mice to air particles collected on the edge of USC damaged neurons in the hippocampus, the memory center that is vulnerable to both brain aging and Alzheimer's disease."

Their study, published Jan. 31 in the Nature journal Translational Psychiatry, adds to an emerging body of research from around the world that links air pollution to dementia. The offending pollutants -- known as PM2.5 -- are fine, inhalable particles with diameters 2.5 micrometers or smaller. A human hair is about 70 micrometers in diameter, making it 30 times larger than the largest PM2.5.

The research was a collaboration between USC Davis, the Keck School of Medicine and the USC Viterbi School of Engineering.
Combining human data and lab experiments
The researchers analyzed data of 3,647 65- to 79-year-old women from the Women's Health Initiative Memory Study (WHIMS). These women lived across 48 states and did not have dementia when they enrolled.

The researchers adjusted for potential bias associated with geographic region, race or ethnic background, education, socioeconomic status, lifestyle and medical conditions.

Constantinos Sioutas, the Fred Champion Professor of Civil and Environmental Engineering at USC Viterbi, invented the technology to collect air particles for controlled exposure of mouse models.

USC scientists chronically exposed female mice carrying the APOE4 gene to nano-sized air pollution for 15 weeks. Compared to the control group, mice predisposed to Alzheimer's disease accumulated as much as 60 percent more amyloid plaque, the toxic clusters of protein fragments that further the progression of Alzheimer's.

"Our state-of-the-art aerosol technologies, called particle concentrators, essentially take the air of a typical urban area and convert it to the air of a freeway or a heavily polluted city like Beijing," said Sioutas, co-author of the study. "We then use these samples to test exposure and assess adverse neuro-developmental or neuro-degenerative health effects."

Worldwide, nearly 48 million people suffer from dementia, and there are 7.7 million new cases every year, according to the World Health Organization.

"Our study has global implications as pollution knows no borders," said Finch, holder of the ARCO/William F. Kieschnick Chair in the Neurobiology of Aging.

USC researchers and others in this field said more research is needed to confirm a causal relationship and to understand how air pollution enters and harms the brain. Accurate pollution monitors are important for this task.

Less than one-third of all counties in the United States have ozone or particle pollution monitors, according to the American Lung Association. Ambient monitoring data from the EPA are critical for scientists conducting research on air pollution and public health, Chen said.

"We analyzed data of high PM2.5 levels using standards the EPA set in 2012," Chen said. "We don't know whether the lower PM2.5 levels of recent years have provided a safe margin for older Americans, especially those at risk for dementia."

Six of the top 10 most polluted cities in the nation by PM2.5 are in California, including Los Angeles, Long Beach and Fresno, according to the American Lung Association.

Yet certain areas have seen cleaner air in recent decades. Reducing PM2.5 in the air we breathe coincides with fewer cases of dementia, the researchers pointed out, referencing the data of others.
The insidious effects of PM2.5
"Many studies have suggested that early life adversities may carry into later life and affect brain aging," Chen said. "If this is true, then maybe long-term exposure to air pollution that starts a downward spiral of neurodegenerative change in the brain could begin much earlier and rev up in later life."

In other studies, Chen and his colleagues linked long-term exposure to high PM2.5 levels to smaller gray and white matter volumes in important areas such as the frontal lobe, which carries out thinking, decision-making and planning.

For every 3.5 micrograms of PM2.5 per cubic meter of air, white matter (insulated nerve fibers that connect different brain regions) decreased by 6 cubic centimeters, according to one earlier study.

The new study in Translational Psychiatry examined only women and female mice. Future studies will include both sexes to evaluate generalizability to men as well as examine how PM2.5 interacts with cigarettes and other pollutants.

Finch and Chen in 2010 developed the AirPollBrain Network and have recruited 20 USC faculty into this new research area.

The air pollution study, the Women's Health Initiative and WHIMS are collectively supported by the National Institute on Aging of the National Institutes of Health; the Southern California Environmental Health Sciences Center; the National Heart, Lung, and Blood Institute; the U.S. Department of Health and Human Services; Wyeth Pharmaceuticals Inc.; St. Davids, PA, and the Wake Forest School of Medicine; and the Cure Alzheimer's Fund.

The nationwide Women's Health Initiative Memory Study is coordinated by the Wake Forest School of Medicine in North Carolina. The WHIMS was begun in 1996 to analyze how postmenopausal hormone treatment affects cognitive impairment and brain aging.

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alzheimer's research; healthy aging; menopause; dementia; alzheimer's; disorders and syndromes; air quality; air pollution; pollution

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Air pollution may lead to dementia in older women: Tiny, dirty airborne particles called PM2.5 invade the brain and wreak havoc, study suggests

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Tiny air pollution particles -- the type that mainly comes from power plants and automobiles -- may greatly increase the chance of dementia, including Alzheimer's disease. Scientists and engineers found that older women who live in places with fine particulate matter exceeding the US Environmental Protection Agency's standard are 81 percent more at risk for global cognitive decline and 92 percent more likely to develop dementia, including Alzheimer's.

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A new Tel Aviv University study reveals that hyperbaric oxygen treatments may ameliorate symptoms experienced by patients with Alzheimer's disease.

"This revolutionary treatment for Alzheimer's disease uses a hyperbaric oxygen chamber, which has been shown in the past to be extremely effective in treating wounds that were slow to heal," says Prof. Uri Ashery of TAU's Sagol School of Neuroscience and the Faculty of Life Sciences, who led the research for the study. "We have now shown for the first time that hyperbaric oxygen therapy can actually improve the pathology of Alzheimer's disease and correct behavioral deficits associated with the disease.

"This research is extremely exciting as it explores a new therapy that holds promise as a treatment of Alzheimer's disease," Prof. Ashery says.

The research was conducted by PhD student Ronit Shapira of TAU's Faculty of Life Sciences; Prof. Beka Solomon and Dan Frenkel of TAU's Sagol School of Neuroscience and Faculty of Life Sciences; and Prof. Shai Efrati of TAU's Sackler Faculty of Medicine, Sagol School of Neuroscience and Assaf-Harofeh Medical Center. It was published in the journal Neurobiology of Aging.

Patients who undergo hyperbaric oxygen therapy for different conditions breathe in pure oxygen in a pressurized room or chamber. In this chamber, the air pressure is increased to twice that of normal air. Under these conditions, oxygen solubility in the blood increases and is transported by blood vessels throughout the body. The added oxygen stimulates the release of growth factors and stem cells, which themselves promote healing.

The TAU scientists used a mouse model of Alzheimer's disease and built a custom-made hyperbaric oxygen chamber suitable for small animals. Then, over the course of 14 days, the team administered hyperbaric oxygen treatment to the mice for one hour per day. After 14 days, the mice underwent a series of behavioral tests as well as tissue biochemical tests to understand how hyperbaric oxygen treatment affects the pathological hallmarks associated with Alzheimer's disease.

The treatment reduced behavioral deficiencies compared to the non-transgenic control mice, reduced plaque pathology by 40%, and reduced neuroinflammation by about 40%.

"There are serious clinical implications to this research," says Shapira, principal investigator of the study. "Hyperbaric oxygen treatment is a well-tolerated and safe therapy used in clinics around the world for various medical conditions, including neurological disorders. Although further research is needed to elucidate the underlying beneficial mechanisms of the therapy and to evaluate its beneficial effects in various Alzheimer patient populations, it holds great potential for the treatment of Alzheimer's disease."

"In this hallmark study, the beneficial physiological effects of hyperbaric oxygen therapy were directly demonstrated on Alzheimer-affected brain tissue," says Prof. Efrati. "We assume that the main challenge in human use will be to initiate the treatment at early stages before significant amount of brain tissue is lost."

The researchers are currently testing the effectiveness of hyperbaric oxygen treatment on an additional mouse model of Alzheimer's disease to investigate the mechanisms underlying its impact on the disease.

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alzheimer's research; healthy aging; copd; diseases and conditions; alzheimer's; caregiving; dementia; disorders and syndromes

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Hyperbaric oxygen therapy may alleviate symptoms of Alzheimer's Disease: Treatment has potential to correct behavioral and physical deficits associated with the disease

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A new Tel Aviv University study reveals that hyperbaric oxygen treatments may ameliorate symptoms experienced by patients with Alzheimer's disease. "This revolutionary treatment for Alzheimer's disease uses a hyperbaric oxygen chamber, which has been shown in the past to be extremely effective in treating wounds that were slow to heal," says Prof.

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In the December featured basic science article in The Journal of Nuclear Medicine, Belgian researchers report on the first large-scale longitudinal imaging study to evaluate BACE1 inhibition with micro-PET in mouse models of Alzheimer's disease. PET imaging has been established as an excellent identifier of the amyloid plaque and tau tangles that characterize Alzheimer's disease. Now it is proving to be an effective way to gauge treatment effectiveness.

The tracer makes it possible to image the effects of chronic administration of an inhibitor for an enzyme, called beta (β)-site amyloid precursor protein-cleaving enzyme 1 (BACE1), which cuts off protein fragments that can lead to amyloid-β development and is more prevalent in brains affected by Alzheimer's. It does this by binding to BACE1.

The study compared control mice with those genetically-altered to have Alzheimer's, and tested ¹⁸F-florbetapir ( ¹⁸F-AV45) along with two other tracers, ¹⁸F-FDG PET and ¹⁸F-PBR111. The mice received the BACE inhibitor at 7 weeks, then brain metabolism, neuroinflammation and amyloid-β pathology were measured using a micro-PET (μPET) scanner and each of the tracers. Baseline scans were done at 6-7 weeks and follow-up scans at 4,7 and 12 months. ¹⁸ F-AV45 uptake was measured at 8 and 13 months of age. After the final scans, microscopic studies were performed.

While all three tracers detected pathological differences between the genetically modified mice and the controls, only ¹⁸ F-AV45 showed the effects of inhibitor treatment by identifying reduced amyloid-β pathology in the genetically modified mice. This was confirmed in the microscopic studies.

The team of the Molecular Imaging Center Antwerp, Belgium, however warns, "This study clearly showed that accurate quantification of amyloid-beta tracers is critically important and that the non-specific uptake in the brain of subjects might be underestimated for some existing Alzheimer's tracers that have fast metabolization profiles. The aim of this translational research is advancing results discovered at the bench so that they can be applied to patients at the bedside."

The statistics on Alzheimer's are sobering. Approximately 10 percent of people 65 and older have Alzheimer's dementia, according to the Alzheimer's Association. More than 5 million Americans are living with the disease, and that number could rise to 16 million by 2050.

Journal Reference:

Steven Deleye, Ann-Marie Waldron, Jeroen Verhaeghe, Astrid Bottelbergs, Leonie Wyffels, Bianca Van Broeck, Xavier Langlois, Mark Schmidt, Sigrid Stroobants, Steven Staelens. Evaluation of Small-Animal PET Outcome Measures to Detect Disease Modification Induced by BACE Inhibition in a Transgenic Mouse Model of Alzheimer Disease. Journal of Nuclear Medicine, 2017; 58 (12): 1977 DOI: 10.2967/jnumed.116.187625

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alzheimer's research; healthy aging; medical devices; elder care; alzheimer's; dementia; caregiving; disorders and syndromes

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PET tracer gauges effectiveness of promising Alzheimer's treatment

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Researchers report on the first large-scale longitudinal imaging study to evaluate BACE1 inhibition with micro-PET in mouse models of Alzheimer's disease. PET imaging has been established as an excellent identifier of the amyloid plaque and tau tangles that characterize Alzheimer's disease. Now it is proving to be an effective way to gauge treatment effectiveness.

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About 15 million Americans will have either Alzheimer's dementia or mild cognitive impairment by 2060, up from approximately 6.08 million this year, according to a new study by researchers at the UCLA Fielding School of Public Health.

The findings highlight the need to develop measures that could slow the progression of the disease in people who have indications of neuropathological changes that could eventually lead to Alzheimer's dementia, said Ron Brookmeyer, professor of biostatistics at the UCLA Fielding School of Public Health and the study's lead author. The country's population is aging and with it comes a growing number of people with Alzheimer's disease.

The study was published in the peer-reviewed Alzheimer's and Dementia: The Journal of the Alzheimer's Association. The study is the first of its kind that has estimated the numbers of Americans with preclinical Alzheimer's disease or mild cognitive impairment.

"There are about 47 million people in the U.S. today who have some evidence of preclinical Alzheimer's, which means they have either a build-up of protein fragments called beta-amyloid or neurodegeneration of the brain but don't yet have symptoms," Brookmeyer said. "Many of them will not progress to Alzheimer's dementia in their lifetimes. We need to have improved methods to identify which persons will progress to clinical symptoms, and develop interventions for them that could slow the progression of the disease, if not stop it all together."

The researchers examined the largest studies available on rates of progression of Alzheimer's disease and used that information in a computer model they built that took into account the aging of the U.S population. The model projected the numbers of people in preclinical and clinical disease states.

They found that by 2060 about 5.7 million Americans will have mild cognitive impairment and another 9.3 million will have dementia due to Alzheimer's. Of the latter group, about 4 million Americans will need an intensive level of care similar to that provided by nursing homes. Mild cognitive impairment is an intermediate clinical stage that does not yet meet the threshold for dementia. Brookmeyer estimates that today about 2.4 million Americans are living with mild cognitive impairment due to Alzheimer's disease.

"Estimates by disease state and severity are important because the resources needed to care for patients vary so much over the course of the illness," Brookmeyer said.

There are some sources of uncertainty in the findings. Participants in the studies the researchers examined may not represent all demographics. Also, there are other types of dementia, such as vascular dementia, that were not examined but could have an impact on these numbers.

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alzheimer's research; healthy aging; elder care; diseases and conditions; alzheimer's; dementia; disorders and syndromes; caregiving

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Population of Americans with Alzheimer's will more than double by 2060: 47 million Americans already demonstrate some evidence of susceptibility to the disease

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About 15 million Americans will have either Alzheimer's dementia or mild cognitive impairment by 2060, up from approximately 6.08 million this year. The findings highlight the need to develop preventive measures that could slow the progression of the disease in at risk for Alzheimer's dementia.

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from research organizations

In the largest and most conclusive study of its kind, researchers have analysed blood samples to create a novel and non-invasive way of helping to diagnose Alzheimer's disease and distinguishing between different types of neurodegenerative disorders.

Following this breakthrough discovery, Alzheimer's sufferers may now have an additional test to improve the accuracy of diagnosis in order to better tailor appropriate treatment.

The research also offers a valuable opportunity to monitor the progression of the disease.

The international study in the Proceedings of the National Academy of Sciences USA used sensor-based technology with a diamond core to analyse approximately 550 blood samples.

By passing light through the diamond and observing its interactions with the blood plasma, researchers were able to identify specific chemical bonds within the blood. This biochemical data was used to compare blood samples from cases of Alzheimer's disease and other neurodegenerative diseases with those from healthy controls.

The ground-breaking scientific investigation was carried out by researchers at Lancaster University, the University of Central Lancashire (UCLan), the University of Manchester and the Federal University of Rio Grande do Norte, Brazil.

Professor David Allsop from Lancaster University has been collaborating for many years with Professor David Mann at Manchester University in searching for diagnostic markers for neurodegenerative disease in blood plasma.

They provided all of the plasma samples for the study, along with supporting clinical and genetic information, and expertise in Alzheimer's and other neurodegenerative conditions.

Professor Allsop said: "A particularly exciting aspect of the study was the ability to distinguish accurately between Alzheimer's disease and Lewy body dementia, which are conditions that both result in dementia and can be difficult to separate from each other based on clinical information and symptoms. By reduction of misdiagnosed cases and administration of appropriate treatment, many people could benefit from this type of blood test in the future."

Alzheimer's diagnosis currently involves careful medical evaluation including clinical history, memory testing and brain scans, yet the only conclusive diagnosis is determined by post-mortem examination. This new blood test offers a non-invasive, more accurate and relatively cost-effective method of diagnosis, which will ensure the correct management of the condition.

Professor Francis Martin, principal investigator of the study and Biosciences theme lead at UCLan, said: "We have an aging population, meaning that the incidence and prevalence of Alzheimer's is increasing, as is the need for accurate diagnosis. The ability to identify different neurodegenerative diseases through the analysis of blood offers a faster and accurate way of establishing the most effective treatment plan as well as disease monitoring."

This new approach could also offer potential for carrying out tests to identify and monitor early signs of mild cognitive impairment, meaning that the onset of Alzheimer's and other types of neurodegenerative diseases could be detected early and intervention measures could be put in place earlier to slow the progress of these diseases.

Professor Martin added: "For those suffering with Alzheimer's disease, the damage is already well advanced once conventionally diagnosed, but this new method offers a potentially effective early screening tool when patients are only demonstrating signs of mild cognitive impairment. This is a potentially significant breakthrough for the prevention of different debilitating and chronic neurological diseases."
Story Source:
Materials provided by Lancaster University. Note: Content may be edited for style and length.

Journal Reference:

Maria Paraskevaidi, Camilo L. M. Morais, Kássio M. G. Lima, Julie S. Snowden, Jennifer A. Saxon, Anna M. T. Richardson, Matthew Jones, David M. A. Mann, David Allsop, Pierre L. Martin-Hirsch, Francis L. Martin. Differential diagnosis of Alzheimer's disease using spectrochemical analysis of blood. Proceedings of the National Academy of Sciences, 2017; 201701517 DOI: 10.1073/pnas.1701517114

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Below are relevant articles that may interest you. ScienceDaily shares links and proceeds with scholarly publications in the TrendMD network.

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alzheimer's research; healthy aging; diseases and conditions; heart disease; alzheimer's; dementia; caregiving; disorders and syndromes

# data[].attributes.attachment_link.title
New diagnosis for Alzheimer's: Alzheimer's sufferers may now have an additional test to improve the accuracy of diagnosis in order to better tailor appropriate treatment

# data[].attributes.attachment_link.description
In the largest and most conclusive study of its kind, researchers have analyzed blood samples to create a novel and non-invasive way of helping to diagnose Alzheimer's disease and distinguishing between different types of neurodegenerative disorders. Following this breakthrough discovery, Alzheimer's sufferers may now have an additional test to improve the accuracy of diagnosis in order to better tailor appropriate treatment.

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In a comprehensive analysis of samples from 107 aged human brains, researchers at the Allen Institute for Brain Science, UW Medicine and Kaiser Permanente Washington Health Research Institute have discovered details that will help researchers better understand the biological bases for Alzheimer's disease and dementia in older populations. The analysis also highlights surprising variability in the aged brain, including examples of donors with resilience to pathology. The research is published this month in the journal eLife, and the data underlying the research are publicly available as part of the suite of open data resources at the Allen Brain Atlas portal.

"Since the population of individuals over 90 years of age is rapidly increasing, understanding both healthy aging and age-related disease is essential," says Ed Lein, Investigator at the Allen Institute for Brain Science. "This means we must discover how cognitive decline correlates with the brain pathologies we typically attribute to diseases like Alzheimer's in aged brains, as well as the biology underlying individual vulnerability and resilience to disease." In this analysis, researchers sought to understand whether associations previously identified between cognitive status, gene expression and brain pathologies -- such as the plaques and tangles typically found in Alzheimer's disease -- held true in a well characterized, aged population. To achieve this goal, researchers developed a state of the art approach combining traditional and quantitative measures to probe the relationships between gene expression and age-related neurodegeneration.

"Several studies exist that compare expression in donor brains aged 60-85 years, but few in the more aged cohort we were able to study here," says Jeremy Miller, Ph.D., Senior Scientist I at the Allen Institute for Brain Science and lead author on the publication. "We found that the more aged brains still showed a correlation between cognitive decline and the Alzheimer's-associated plaques and tangles, although the relationship was not as strong as in younger cohorts."

In addition, the research revealed a surprising relationship between dementia and decreased quality of RNA -- a key player in gene expression -- in the more aged brain.

"One factor that is not always taken into account when studying gene expression in the aged brain is the quality of the genetic material itself," says Miller. "This variable is not necessarily related to any specific pathology or disease, but these results highlight the importance of properly controlling for RNA quality when studying the aged brain and indicate that degradation of genetic material may be an underappreciated feature of neurodegeneration or dementia."

All of the data underlying the research is part of the Aging, Dementia and TBI resource, freely available through the Allen Brain Atlas data portal. "We want to promote a model of systematic, collaborative, multidimensional study of the diseased brain and open access to data and tools to facilitate discovery across the entire basic and biomedical research community," says Lein.

"We anticipate that this dataset and research model will inform and help shape future brain aging research to propel a deeper understanding of the mechanisms driving neurological disease for improved diagnostic approaches and effective therapeutic strategies," says C. Dirk Keene, M.D., Ph.D., study co-author and Director of UW Medicine Neuropathology.

The study samples come from the Adult Changes in Thought (ACT) study, a longitudinal research effort led by Eric B. Larson, M.D., M.P.H., and Paul K. Crane, M.D., M.P.H., of the Kaiser Permanente Washington Health Research Institute (KPWHRI) (formerly known as Group Health Research Institute) and the University of Washington School of Medicine to collect data on thousands of aging adults, including detailed information on their health histories and cognitive abilities.

"This collaboration with the Allen Institute for Brain Science has allowed us to gain insights never before possible into the relationships between neuropathology, gene expression, RNA quality, and clinical features tracked in the ACT study over more than 20 years," says Larson, who has led the National Institute of Aging-supported study from its start in 1986 and is Vice President for Research and Health Care Innovation at Kaiser Permanente Washington. "We are grateful to the thousands of volunteer subjects who worked with us and those who donated their brains to science. The results are transformative in improving our understanding of the aging brain, a theme of the ACT study, which aims to learn ways to reduce the burden of dementia for individuals and society overall."
Story Source:
Materials provided by Allen Institute. Note: Content may be edited for style and length.

Journal Reference:

Jeremy A Miller, Angela Guillozet-Bongaarts, Laura E Gibbons, Nadia Postupna, Anne Renz, Allison E Beller, Susan M Sunkin, Lydia Ng, Shannon E Rose, Kimberly A Smith, Aaron Szafer, Chris Barber, Darren Bertagnolli, Kristopher Bickley, Krissy Brouner, Shiella Caldejon, Mike Chapin, Mindy L Chua, Natalie M Coleman, Eiron Cudaback, Christine Cuhaciyan, Rachel A Dalley, Nick Dee, Tsega Desta, Tim A Dolbeare, Nadezhda I Dotson, Michael Fisher, Nathalie Gaudreault, Garrett Gee, Terri L Gilbert, Jeff Goldy, Fiona Griffin, Caroline Habel, Zeb Haradon, Nika Hejazinia, Leanne L Hellstern, Steve Horvath, Kim Howard, Robert Howard, Justin Johal, Nikolas L Jorstad, Samuel R Josephsen, Chihchau L Kuan, Florence Lai, Eric Lee, Felix Lee, Tracy Lemon, Xianwu Li, Desiree A Marshall, Jose Melchor, Shubhabrata Mukherjee, Julie Nyhus, Julie Pendergraft, Lydia Potekhina, Elizabeth Y Rha, Samantha Rice, David Rosen, Abharika Sapru, Aimee Schantz, Elaine Shen, Emily Sherfield, Shu Shi, Andy J Sodt, Nivretta Thatra, Michael Tieu, Angela M Wilson, Thomas J Montine, Eric B Larson, Amy Bernard, Paul K Crane, Richard G Ellenbogen, C Dirk Keene, Ed Lein. Neuropathological and transcriptomic characteristics of the aged brain. eLife, 2017; 6 DOI: 10.7554/eLife.31126

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healthy aging; alzheimer's research; brain tumor; diseases and conditions; dementia; alzheimer's; intelligence; brain-computer interfaces

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New details on aged brain, Alzheimer's and dementia: Robust analysis of samples from 107 human brains highlights features of healthy and diseased aging

# data[].attributes.attachment_link.description
In a comprehensive analysis of samples from 107 aged human brains, researchers at the Allen Institute for Brain Science, UW Medicine and Kaiser Permanente Washington Health Research Institute have discovered details that will help researchers better understand the biological bases for Alzheimer's disease and dementia in older populations.

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Scientists at the Massachusetts General Hospital (MGH), in collaboration with colleagues at the University California, San Diego (UCSD), have characterized a new class of drugs as potential therapeutics for Alzheimer's disease and discovered a piece in the puzzle of how they would work. Their study, using disease-related animal and cellular models, shows that treatment with a representative compound of this class of gamma-secretase modulators leads to a reduction of the Alzheimer's-associated beta-amyloid. The study has been online published in EBioMedicine, an open-access journal jointly published by Cell Press and The Lancet.

"Our study explores the mechanism by which gamma-secretase modulators reduce levels of amyloid-beta 42, the primary pathological driver of Alzheimer's disease," says Can (Martin) Zhang, MD, PhD, of the Genetics and Aging Research Unit in the MassGeneral Institute for Neurodegenerative Disease (MGH-MIND), co-corresponding author of the EBioMedicine paper. "These findings will be useful in the ongoing effort to develop molecules that may be effective for the treatment and prevention of Alzheimer's disease."

The most common neurodegenerative disorder, Alzheimer's disease is characterized by the buildup of amyloid plaques and neurofibrillary tangles in several brain regions. The leading hypothesis for its pathogenesis is the amyloid cascade -- which suggests that the amyloid beta-protein, and particularly the amyloid-beta 42 peptide, initiates the disease process. An imbalance between the production and clearance of amyloid-beta results in the protein's aggregation into larger plaques that lead to the death of brain cells and the cognitive symptoms seen in Alzheimer patients. Several potential treatments have been developed that specifically target amyloid, but none have been effective in halting disease progression.

Amyloid-beta is produced by the cleavage of the larger amyloid precursor protein (APP) by an enzyme called gamma-secretase. Previous research led to the development of gamma-secretase inhibitors that totally block the function of the enzyme, but in clinical trials these drugs produced serious side effects through their effects on the processing of other proteins.

Rudolph Tanzi, PhD, director of the MGH Genetics and Aging Research Unit, and Steven Wagner, PhD, of the USCD Department of Neurosciences -- co-corresponding authors of the current study -- first developed the concept of gamma-secretase modulators (GSMs), which change but do not totally suppress the enzyme's activity, back in 2000. More recently their teams developed a group of soluble GSMs, one of which -- SGSM-36 -- appeared to be a promising candidate for clinical development.

In the current study, the researchers showed that three days of treatment with SGSM-36 reduced levels of amyloid-beta 42 in the brains and plasma of a validated mouse model of inherited Alzheimer's without affecting the processing of APP by other enzymes. In cellular models -- including the three-dimensional "Alzheimer's in a dish" system developed by Tanzi's team -- they compared the action of SGSM-36 to that of the semagacestat, one of the gamma-secretase inhibitors that failed in clinical trials. While SGSM-36 treatment only reduced levels of the toxic amyloid-beta 40 and 42 peptides, semagacestat reduced all form of amyloid as well as gamma-secretase processing of other proteins, including the important signaling protein Notch, reduction of which may have caused the toxic effects of gamma-secretase inhibitor treatment.

In order to understand better understand how SGSM-36 alters the gamma-secretase enzyme and its function. The team used fluorescence lifetime imaging microscopy to examine the molecule, identifying a site where SGSM-36 enlarges the space between three characteristic loops of the protein, conferring a more open conformation that has been shown to be associated with lowering production of the toxic forms of amyloid-beta.

"Genetic, biochemical, molecular biological and pathological evidence all support the hypothesis that excessive accumulation of amyloid-beta -- particularly amyloid-beta 42 -- is the primary event leading to Alzheimer's related pathology," says Zhang, who is an assistant professor of Neurology at Harvard Medical School (HMS). "In our future studies, we will be testing SGSM-36 against similar molecules that may have equal or higher potency in reducing amyloid-beta 42 and further investigating its molecular mechanisms in animal models, with the eventual goal of testing its potential in clinical trials."

Along with Tanzi, the Joseph. P. and Rose F. Kennedy Professor of Neurology at HMS, and Wagner, a professor at the USCD School of Medicine, co-authors of the EBioMedicine paper are co-lead authors Frank Raven and Joseph Ward, MGH Genetics and Aging Research Unit; as well as Yu Wan, MD, Se Hoon Choi, PhD, Xunuo Shen and Sean Miller, MGH Genetics and Aging Research Unit; Katarzyna Zoltowska and Oksana Berezovska, PhD, Alzheimer's Research Unit, MGH-MIND; and Kevin Rynearson, PhD, UCSD.

This research was funded by National Institutes of Health grants P01 AG015379 and U01 NS074501 and the Cure Alzheimer's Fund. While Tanzi and Wagner worked with TorreyPines Therapeutics on the early development of gamma-secretase modulators, the intellectual property for the compounds now in development is owned by the MGH and UCSD.

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alzheimer's research; healthy aging; vitamin a; pharmacology; alzheimer's; dementia; caregiving; disorders and syndromes

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One step closer toward a treatment for Alzheimer's disease? Novel class of drugs more precisely blocks production of toxic forms of beta-amyloid

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Scientists at the Massachusetts General Hospital (MGH), in collaboration with colleagues at the University California, San Diego (UCSD), have characterized a new class of drugs as potential therapeutics for Alzheimer's disease and discovered a piece in the puzzle of how they would work.

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from research organizations

McGill University researchers have discovered a cellular mechanism that may contribute to the breakdown of communication between neurons in Alzheimer's disease.

Their study, published in Nature Communications, homes in on the role of RNA molecules involved in synaptic transmission -- the process through which neurons communicate with each other. In the brain tissue of Alzheimer's patients, the RNAs that encode synaptic proteins are degraded more rapidly than in healthy brain cells, the researchers found. They also discovered that a protein that helps stabilize these RNAs was less abundant in the neurons of Alzheimer's patients.

Taken together, these findings indicate that inadequate levels of the protein, known as RBFOX1, may be a factor in the faulty connections that are a hallmark of Alzheimer's disease, says Hamed S. Najafabadi, senior author of the paper and an assistant professor in McGill's Department of Human Genetics.
A new piece of the puzzle
Although Alzheimer's is by far the most common form of dementia, its underlying mechanisms aren't fully understood, and there are currently no treatments to stop its progression. The McGill study reveals a new piece of the puzzle, which could provide leads for new therapeutic approaches.

Human cells produce thousands of different types of RNAs to carry genetic information. RNAs also decay constantly, and the balance between production and degradation determines how much of a given RNA is present in the cell. Yet scientists know relatively little about how RNA decay is controlled, largely because methods of measuring degradation have been expensive and not applicable to human tissues.

Previous research by Najafabadi had shown that RNA degradation is involved in different human diseases. Most of those findings came from studies in cell line models of diseases, however. "We wanted to directly measure the RNA degradation rate in human tissues, but available methods weren't able to do that," Najafabadi explains. So his team hit on a way to get around that problem. "We realized that by modeling the process of RNA production and decay, we could devise a mathematical method to calculate RNA degradation using existing genomics technologies."
Measuring RNA decay
To test their new approach, the McGill researchers enlisted the help of scientists at the University of California, San Francisco. The California team, led by Hani Goodarzi, grew cells in a lab, and measured the rate of RNA degradation using a conventional method. At the same time, the McGill researchers estimated the rate using their mathematical method. The two results matched up, validating the mathematical framework.

Najafabadi and McGill graduate student Rached Alkallas then applied the mathematical method to analyze publicly available data on the brain tissues of people who died from Alzheimer's. They also analyzed brain tissues from people who didn't suffer from Alzheimer's. Comparing those two groups revealed the rapid rate of RNA degradation and short supply of RBFOX1 protein in the Alzheimer's patients.

"There's still a lot to learn about the role of RNA degradation in Alzheimer's and other diseases," Najafabadi says. "For example, why is there a reduction of RBFOX1 in Alzheimer's? Is the reduced amount of this protein a risk factor, or a feature of the later stages of the disease? And can we restore at least part of the normal function of the neurons by controlling the activity of RBFOX1?"

Journal Reference:

Rached Alkallas, Lisa Fish, Hani Goodarzi, Hamed S. Najafabadi. Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease. Nature Communications, 2017; 8 (1) DOI: 10.1038/s41467-017-00867-z

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alzheimer's research; human biology; healthy aging; genes; alzheimer's; dementia; disorders and syndromes; brain-computer interfaces

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New mechanism detected in Alzheimer's disease: Rate of RNA decay could be a key to breakdown in communication between neurons

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Researchers have discovered a cellular mechanism that may contribute to the breakdown of communication between neurons in Alzheimer's disease. In the brain tissue of Alzheimer's patients, the RNAs that encode synaptic proteins are degraded more rapidly than in healthy brain cells, the researchers found.

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Alzheimer's disease is the most common form of dementia and neurodegeneration worldwide. A major hallmark of the disease is the accumulation of toxic plaques in the brain, formed by the abnormal aggregation of a protein called beta-amyloid inside neurons.

Still without cure, Alzheimer's poses a significant burden on public health systems. Most treatments focus on reducing the formation of amyloid plaques, but these approaches have been inconclusive. As a result, scientists are now searching for alternative treatment strategies, one of which is to consider Alzheimer's as a metabolic disease.

Taking this line of thought, Johan Auwerx's lab at EPFL looked at mitochondria, which are the energy-producing powerhouses of cells, and thus central in metabolism. Using worms and mice as models, they discovered that boosting mitochondria defenses against a particular form of protein stress, enables them to not only protect themselves, but to also reduce the formation of amyloid plaques.

During normal aging and age-associated diseases such as Alzheimer's, cells face increasing damage and struggle to protect and replace dysfunctional mitochondria. Since mitochondria provide energy to brain cells, leaving them unprotected in Alzheimer's disease favors brain damage, giving rise to symptoms like memory loss over the years.

The scientists identified two mechanisms that control the quality of mitochondria: First, the "mitochondrial unfolded protein response" (UPRmt), which protects mitochondria from stress stimuli. Second, mitophagy, a process that recycles defective mitochondria. Both these mechanisms are the key to delaying or preventing excessive mitochondrial damage during disease.

While we have known for a while that mitochondria are dysfunctional in the brains of Alzheimer's patients, this is the first evidence that they actually try to fight the disease by boosting quality control pathways. "These defense and recycle pathways of the mitochondria are essential in organisms, from the worm all the way to humans," says Vincenzo Sorrentino, first author of the paper. "So we decided to pharmacologically activate them."

The team started by testing well-established compounds, such as the antibiotic doxycycline and the vitamin nicotinamide riboside (NR), which can turn on the UPRmt and mitophagy defense systems in a worm model ( C. elegans) of Alzheimer's disease. The health, performance and lifespan of worms exposed to the drugs increased remarkably compared with untreated worms. Plaque formation was also significantly reduced in the treated animals.

And most significantly, the scientists observed similar improvements when they turned on the same mitochondrial defense pathways in cultured human neuronal cells, using the same drugs.

The encouraging results led the researchers to test NR in a mouse model of Alzheimer's disease. Just like C. elegans, the mice saw a significant improvement of mitochondrial function and a reduction in the number of amyloid plaques. But most importantly, the scientists observed a striking normalization of the cognitive function in the mice. This has tremendous implications from a clinical perspective.

According to Johan Auwerx, tackling Alzheimer's through mitochondria could make all the difference. "So far, Alzheimer's disease has been considered to be mostly the consequence of the accumulation of amyloid plaques in the brain," he says. "We have shown that restoring mitochondrial health reduces plaque formation -- but, above all, it also improves brain function, which is the ultimate objective of all Alzheimer's researchers and patients."

The strategy provides a novel therapeutic approach to slow down the progression of neurodegeneration in Alzheimer's disease, and possibly even in other disorders such as Parkinson's disease, which is also characterized by profound mitochondrial and metabolic defects.

The approach remains to be tested in human patients. "By targeting mitochondria, NR and other molecules that stimulate their 'defense and recycle' systems could perhaps succeed where so many drugs, most of which aim to decrease amyloid plaque formation, have failed," says Vincenzo Sorrentino.

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alzheimer's research; healthy aging; diseases and conditions; alzheimer's; dementia; disorders and syndromes; mice; cell biology; molecular biology

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Healthy mitochondria could stop Alzheimer's

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Alzheimer's disease is the most common form of dementia and neurodegeneration worldwide. A major hallmark of the disease is the accumulation of toxic plaques in the brain, formed by the abnormal aggregation of a protein called beta-amyloid inside neurons.