13 technologies were identified although the categorisation of these is interesting and there is some overlap between the groups such as ncRNomics and transcriptomics.

I agreed with everyone that this paper is more of a list and doesn’t integrate the information very well, but some sections are contextualised better than others.

Lots of these studies were in silico modelling looking for overlap in analysis. These studies may benefit from standardised study design and data to improve integration. 

Would it also be possible in the future to use the information gathered by this paper to design more targeted multi omics investigations looking specifically at those genes and pathways involved in pathogenesis?

The discussion is disjointed and although the paper pulls together a lot of information on PD they fail to discuss the impact or future possibilities of this information. The discussion is also quite limited in its caveats to analysis – barely touching upon methodologies of most of the omics technologies discussed. 

They have however successfully created a comprehensive resource on PD omics studies so far and I did think it was interesting that they identified the top 40 implicated pathways in PD and listed many genes that were identified across multiple omics platforms. I think this will be a useful resource for more targeted research into PD biomarkers and therapeutics.

The 107 articles found in their search were classified into 13 omics groups. It is interesting to hear about other omics beyond the ones we have already learned about in this module.

It was also discussed that some omics types were not included due to the rapid development and extensiveness of studies into Parkinson’s disease, such as functional genomics, RNA-editomics, nutrigenomics, and metagenomics.

The presentation of the omics as separate paragraphs, although I imagine the easiest way for them to structure the paper, does not fully reflect how integrated the omics are. Many of the omics affect and correlate with each other, for example ncRNomics must significantly affect transcriptomics and proteomics. To fully understand a disease such as Parkinson’s disease, the omics need to be considered as a whole.

The integromics section seems to attempt to link omics together, but only by looking at other studies which have done the overlapping rather than finding links between the separate omics studies mentioned in this paper. The integromics studies included also only link genomics-DNA, transcriptomics, proteomics and interactomics, so links between other omics have not been considered at all.

A wider range of omics could be considered, though I appreciate the ones chosen are probably the ones with the largest databases (for in silico studies) and are the most relevant and interconnected. The studies could have increased scale and standardisation.

The conclusions do not clearly enough reflect the need to integrate the omics. However, this paper is a step towards that in bringing all the current information on the different omics information together in one place, so further links can potentially be made between the different omics studies. I agree that further multilayer studies should be conducted.

It is interesting that some genes are implicated in Parkinson’s disease through omics such as environmental omics and pharmacogenetics but not currently through omics such as genomics-DNA level and transcriptomics, it would be interesting to see whether further study in the areas of genomics-DNA level and/or transcriptomics also suggests the connection of such genes.

How many omics technologies did they find in their literature search?

In total 107 articles were explored for omics data, the studies discovered 13 omics groups including new omics not learned in the module. 

What do you think of the way they presented the results of each omics individually?

It does not consider omics as a whole, by separating them it classifies them individually and doesn’t take into consideration the various links between the different omics and that they can have effects on each other. By integrating the different omics, it could help in understanding Parkinson’s disease better.
 
 

How might you have improved on the integrated omics studies that have been conducted? 

 

The study could have increased its size and followed a standardised design to improve on integrating omics.
 

What did you think of the conclusions that the authors drew from their research? 

 

I think the conclusion is somewhat brief, it’s quite basic and doesn’t reflect what they have found or all the different types if omics especially on how to integrate them together, I feel like they’ve only described what they’ve done and mainly focused on various future interests of study without discussion of limitations or future studies in detail however their suggests were interesting, also it doesn’t say how its impacted the omics research community and what it means for development and treatment of diseases. 

 

Francesca Carvalho 

The conclusion didn't use future possibilities to tackle, Yet, they demonstrated that with OMICS we can protect our patients in advance of the disease which will enable us to innovate personalized medicines for these patients that could solve there genetic cause. However, they only seem to focus on what they had demonstrated in the study rather than detailing the effects of future research in order to detect the main symptoms in an individual patient much better in advance. Overall, their conclusion was briefly written and the author should've provided a more detailed one for a better understanding of effective diagnosis and prognosis of PD. 

They found 107 articles that contained different omics procedures. They sorted them into 13 omics subgroups.

But they are aware that not all published studies are included in their review due to selection of keywords for literature screening.

The listing of each omics separately may have been easier to deliver the results of each group properly, which was clear and concise.

Like what everyone is saying, increasing the sample size & perhaps combining certain multi-omics technique together and adding other approaches as in the field of functional genomics, RNA-editomics, nutrigenomics, and metagenomics.

Conclusion was short and talked about how more studies exploring the disease are necessary.

Thank you
Aljowhara Alageel

 

They grouped the studies into 13 different layers of omics: “genomics–DNA level (22 articles), transcriptomics (16 articles), epigenomics (1 article), proteomics (3 articles), ncRNomics (10 articles), interactomics (5 articles), metabolomics (5 articles), glycomics (1 article), lipidomics (1 article), phenomics (3 articles), environmental omics (6 articles), pharmacogenomics (30 articles), and integromics (4 articles)” so 107 articles in total.

ncRNomics - study of non-coding RNA (more on here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802278/)

interactomics - The study of the interactions between proteins and other components of a cell (more here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657177/)

glycomics - systematic study of all glycan structures of a given cell type or organism (more here: https://www.ncbi.nlm.nih.gov/books/NBK453015/)

lipidomics - large-scale study of pathways and networks of cellular lipids (more here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5085849/)

phenomics - systematic study of phenotypes (more here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760679/)

environmental omics - “applications of omics technologies including genomics, transcriptomics, proteomics, and metabolomics to better understand the environmental and genetic factors, toxicity mechanisms, and modes of action in response to both acute and chronic exposure to environmental chemical” - there is a really good figure here: https://www.researchgate.net/publication/273992382_Environmental_OMICS_Current_Status_and_Future_Directions 

pharmacogenomics - the study of the role of the genome in drug response (more on here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5682947/)

integromics - data-integration issues associated with genomic research (more on this here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC139396/) 

I personally found it quite helpful, but it seemed quite disjointed in a way. I agree with the others saying that a more in-depth figure showing how different omics fields interact with each other in PD.

I think a larger sample size and standardisation would be helpful for this. They did use in silico modelling, so I wonder how these have been validated?

I thought that the conclusion was short and lacked a little bit in that they did not mention future research in this field and methods used (apart from how more studies should explore PD in general).

Vik

My thoughts for the last journal club: 

·       How many omics technologies did they find in their literature search?

The researchers grouped the study into 13 omics layer (transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics  environmental omics, pharmacogenomics, integromics) and each layer uses different technologies (WGS Illumina, NGS RNAseq, microarry analysis, RT-qPCR etc.) 
 

·       What did you think of the way they presented the results of each omics individually? 
They present the discovered studies in a very descriptive way. Rather than highlighting the most relevant finding of each layer or study, they only list them one after another. 

 

·       How might you have improved on the integrated omics studies that have been conducted?

From the 13 omics layers mentioned in the papers, integrated omics studies only used up to three layers. Combining more omics layers into a statistical analysis could help to reveal the underlying processes and risk factors of Parkinson’s disease. 

·       What did you think of the conclusions that the authors drew from their research?

The conclusion does not really answer the proposal put forward, yet the paper seems useful for someone who is looking for a list of studies on Parkinson. Perhaps the finding that there are only 4 integromics analyses done so far should serve as an incentive for scientists to integrate more omics layers into their future studies. 

BW 

Clara 

                They included approximately 107 articles in their findings and grouped them into 13 ‘omics’ groups. Of these, we’ve already seen genomics, transcriptomics, epigenomics, proteomics, and metabolomics in this course. The rest I hadn’t yet heard of! 

                I did find that the paper was clear in its division of the different omics, which is helpful for finding specific/relevant information. However, this module has given me a greater understanding of the relationships between the various ‘omics’ and I would have liked to see more of that reflected in this paper.

                Similar to my last answer, I think greater analysis and reflection within the studies is necessary to understand the connections between the integrated omics. Regarding study design, larger sample size with a greater degree of standardization is necessary. 

                No reflection on what the limitations of their review and these studies might have in terms of impact on results. In addition, I believe one of the larger purposes of literature reviews like this is to analyze and extrapolate from available studies, and therefore identify gaps in the research and areas of future focus, which they failed to do. However, I do believe this is a good resource for just reviewing the studies that have been done so far, and a good jumping-off point for researchers that do want to look for gaps or analyse the connections between the fields more. 

The authors also state “so no definite biomarker for predicting the risk for the occurrence of PD or for predicting the course of the disease was identified.” Which is not true, there is strong evidence for imaging and clinical biomarkers perhaps they should have clarified this statement further. doi: 10.3389/fnins.2018.00612 / https://doi.org/10.1016/S1474-4422(19)30024-9

Claire

They progressed from DNA (genomics) level down metabolomics, phenomics and integrative omics. In the review, they tried to link each layer as they moved down the list. 

The lack of overlap in gene expression along the different omics layers makes it difficult to pinpoint biomarkers for Parkinson’s disease.

13 omics layers were found in the literature.

Main message was on how gene expression was regulated in PD at different omics layer and how they interact each other with regards to phenotype.

Data interpretation and analysis by integrative models should address the signalling pathways leading to PD. 

Application of multi-omics approach for particular disease at a personal level can formulate the prevention or treatment which can tailor the individual needs.

The authors discuss 13 different omics layers, ranging from genomics and transcriptomics to environmental- and pharmacogenomics. They reviewed a total of 107 articles. 

 This structure made it easier to read at first (especially when the reader isn’t familiar with many of the omic layers discussed) but gave a fairly fragmented view of PD mechanisms. 

The integromics and discussion sections provide some more information about AD-associated genes involving multiple layers, however I believe a more integrated structure would have benefited this review. 

Clearly, more studies are needed that integrate multiple omic techniques to investigate PD mechanisms. As others have mentioned, most integromic studies reviewed here were performed in silico only and may benefit from in vitro or in vivo confirmation. Further

functional studies are necessary to uncover important causal mechanisms of PD. 

I don’t think there was sufficient discussion of the limitations of omic techniques reviewed, as well as their actual relevance to disease. Overall, the review provided some useful insight into the different types of omics used in PD research but did not provide many novel interpretations or suggestions for future research. 

 

Best wishes,

Johanna 

13 different omic technologies were reviewed in the literature search.

In terms of the actual layout of the paper, it was easy to follow. However, as we have learned in the past, all omics disciplines are interconnected. To have a better flow in the paper, the authors could have structured it in a way where the proceeding omics technology merged into the succeeding one. 

Going on from what I mentioned in the previous answer, a way to improve this literature search would be to connect all the omic 'dots'. There needs to be a more comprehensive literature search with larger cohorts. Also, instead of regurgitating what has been claimed by previous research, the authors could have identified areas which needed more attention. However, for what it is worth, this review is a good paper which has a lot of the up-to-date research compiled in one place.

What is interesting is despite the authors indirectly implying limitations in the study, there was no explicit reflection of the same. Also, all this review did was that it compiled research into one paper. Although that is useful, it is, in a way, incomplete. The research question posed at the start was not answered, and it yielded no clinically relevant conclusions. 

There are 13 different omics technologies found in the literature search of this paper, with a total of 107 articles.

·       What did you think of the way they presented the results of each omics individually? 

The layout of the paper is so easy to follow especially for readers who are not specialist with a focus on the function of genomics at the end. However, this paper was not critical and concise enough, but rather descriptive. Moreover, it has not shown a full clear picture of the relationship between the different omics. 

·        How might you have improved on the integrated omics studies that have been conducted?

One way to improve the conducted integrated omics studies is to increase the sample size while including a broader variety of omics technologies. 

·       What did you think of the conclusions that the authors drew from their research? 

Compared to the study conducted, the conclusion was relatively short and repeating what has been said in the study before, it also lacked direction for future research. 

How many omics technologies did they find in their literature search?

The literature research they performed found 107 articles alongside 13 omics technologies 

What did you think of the way they presented the results of each omics individually?

I thought that the results of each omics technology were presented well and with clarity but the entangled web of how these omics technologies interconnect was not clearly investigated and to better and more clearly show this the paper could have linked them better.

How might you have improved on the integrated omics studies that have been conducted?

A way to improve upon the presentation could be to involve a larger set of omics technologies and data as well as the previously mentioned connection of the different technologies.

What did you think of the conclusions that the authors drew from their research?

Whilst the research in the paper collated together significant information it did not answer what was posed at the start of the paper, there was no complete conclusion found and no implications for future research and further compilation of the research should occur.