# data[].attributes.attachment_link.title
Systemic Lupus Erythematosus: Primary Care Approach to Diagnosis and Management - American Family Physician

# data[].attributes.attachment_link.description
Systemic lupus erythematosus is an autoimmune disease that affects many systems, including the skin, musculoskeletal, renal, neuropsychiatric, hematologic, cardiovascular, pulmonary, and reproductive systems. Family physicians should be familiar with the manifestations of lupus to aid in early diagnosis, monitoring patients with mild disease, recognizing warning signs that require referral to a rheumatologist, and helping to monitor disease activity and treatment in patients with moderate to severe disease.

# data[].attributes.attachment_link.readable_text
Patient selection and sample collection

Patient CS was a 52-year-old African-American female with long-standing SLE clinically characterized by World Health Organization type IV glomerulonephritis, photosensitive rash, and symmetrical nonerosive polyarthritis. Serologically the patient had high titer antinuclear Ab with strongly positive anti-dsDNA and anti-Sm Abs. At the time that serum and cell samples were obtained for this study, the patient was being treated only with hydroxychloroquine and nonsteroidal anti-inflammatory drugs. Previously, she had received six courses of monthly i.v. cyclophosphamide followed by 1 additional year of i.v. cyclophosphamide administered every 3 mo. Altogether, cyclophosphamide therapy had been discontinued 10 mo before samples were obtained. At that time, the patient's blood cell counts were normal except for moderate absolute lymphopenia (950 lymphocytes/μl).

Construction of an IgG1/κ combinatorial library

A combinatorial library of randomly assorted heavy chains of the IgG1 isotype and κ light chains was constructed as previously described according to established protocols ( 10). Briefly, after informed consent was obtained, 50 ml of peripheral blood was collected from our patient and mononuclear cells were isolated by Ficoll-Hypaque gradient (Sigma, St. Louis, MO). Total RNA was extracted from 2 × 10 ⁷ cells and 5 μg of RNA was reverse transcribed using RNaseH − reverse transcriptase and random hexamer primers (Pharmacia, Piscataway, NJ). The resulting ds-cDNA was used as template for the PCR amplification of the Fd fragment of IgG1 heavy chains and full-length κ light chains. Sense primers were designed to amplify all of the known human V H and V κ families ( 10) and contained appropriate restriction sites ( SacI for light chains and XhoI for heavy chains) required for directional cloning in the phagemid pComb3 (kindly provided by D. Burton and C. Barbas, The Scripps Research Foundation) ( 11, 12). The restriction sites generated by the antisense primers were SpeI for the heavy chain and Xba I for the light chain.

Library screening and generation of soluble Fab fragments

The recombinant library was panned against an affinity-purified preparation of the Sm Ag containing both the B/B′ and D polypeptides (ImmunoVision, Springdale, AR). Briefly, individual microtiter wells (Costar, Cambridge, MA) were coated overnight at 4°C with the Sm preparation at 20 μg/ml in 0.1 M sodium bicarbonate (pH 8.6), washed with PBS (pH 7.4), and then blocked with 3% BSA/PBS for 2 h at 37°C. Approximately 10 ¹¹ PFU of the recombinant library were applied to each of the blocked wells, unbound phage was removed by vigorously washing 10 times with PBS/0.05% Tween 20, and the remaining phage was eluted with 50 μl of 0.1 M glycine/HCl (pH 2.2) and neutralized immediately with 2 M Tris. The eluate was used to reinfect XL-1Blue Escherichia coli cells followed by superinfection with VCS-M13 helper phage. This enrichment process was monitored by comparing the number of phage eluted in each round with the phage eluted in the previous round. After four rounds of panning, phagemid DNA was isolated from the rounds with higher enrichment and the sequence encoding the minor coat protein (cpIII) was removed by digesting with SpeI and Nhe I to produce soluble Fab fragments. After religation, phagemid DNA was used to transform XL-1 Blue cells. Randomly selected individual colonies were grown in Super Broth with 50 μg/ml carbenicillin and protein production was induced with 1 mM IPTG (Boehringer Mannheim, Indianapolis, IN). The supernatant from these cultures was used without further purification to determine anti-Sm reactivity by conventional ELISA as described below

Purification of recombinant Fab proteins

Ab Fab fragments were obtained from individual bacterial cultures induced with 1 mM IPTG. The Fab protein was purified from the bacterial pellets by affinity chromatography as previously described ( 10), and the concentration of purified Fab was estimated by sandwich ELISA using as standard a commercially available IgG Fab preparation of known concentration (Pierce, Rockford, IL).

Anti-Sm ELISAs

Dose-dependent reactivity of the recombinant Fabs with either the Sm-B/B′-D Ag or a panel of irrelevant control Ags was determined by conventional titration ELISA using 1 μg of the corresponding Ag/well of polysterene 96-well plates (Costar) as previously described ( 4). Both serum samples and mAbs were tested in duplicate. The ability of either Sm or various control Ags in fluid phase to block the binding of recombinant Abs to immobilized Sm was also tested by ELISA in competitive inhibition assays. Purified Fabs were used at 75% of the concentration previously determined to provide optimum binding in standard titration assays. The relative affinity constant of each Fab was calculated according to Friguet et al. ( 13) as the concentration of soluble competing Ag providing 50% inhibition of maximum binding to Sm. Competing Ags, including Sm itself, were tested at concentrations ranging from 10 −6 to 10 −10 M.

Epitope mapping

Overlapping octapeptides spanning the coding regions of Sm-B′ and Sm-D1 were constructed on a solid-phase support system as previously described in detail ( 4). These overlapping octapeptides were simultaneously synthesized on radiation-derivatized polyethylene pins (Chiron Technologies, Clayton, Victoria, Australia). Positive and negative control pins were synthesized from known antigenic and nonantigenic regions of Sm B′.

Octapeptides were tested for reactivity with whole patient sera or purified Fab fragments of various mAbs, including Fati-1, F-17, F-14, and F-4. First, octapeptides were blocked with 3% low fat milk in PBS for 1 h at room temperature. Second, primary Ab, either patient sera (1:100 dilution) or purified Fab mAbs (at ∼1 ng/well) in 3% milk/PBS with 0.05% Tween 20 (PBST) were allowed to incubate overnight at 4°C. Pins were then washed four times with PBST and then reacted with a 1:1000 dilution of antihuman IgG (Fab′) ₂ raised in a goat, affinity-purified and conjugated to alkaline phosphatase (Pierce) for 2 h at room temperature. p-Nitrophenyl phosphate disodium was used as a substrate for alkaline phosphatase, and plates were read at 405 nm with a MicroELISA Reader (Dynatech, Alexandria, VA). Results for each plate were then standardized by comparison to positive control pins.

After completion of an assay, pins were sonicated for 2 h in sonication buffer ( 4), washed in hot water, and boiled in methanol for 2 min. Pins were then allowed to air dry and were either stored with desiccant or used for another assay ( 4).

DNA sequencing and analysis

Heavy and light chain nucleotide sequences were determined by automated sequencing of both DNA strands using a fluorescent dideoxy terminator cycle sequencing kit (Perkin-Elmer/Cetus, Norwalk, CT ). The sequencing was performed in an Taq Applied Biosystems PRISM 377 automatic sequencer (Perkin-Elmer/Cetus) by the Oligonucleotide and DNA Sequencing Core Laboratory of the University of Rochester. The germline counterparts of the rearranged V H and V κ sequences were determined on-line using the V-BASE search program (http://www.mrc-cpe.cam.ac.uk; Medical Research Council Center for Protein Engineering, Cambridge, U.K.), and the degree of similarity between the corresponding sequences was established using the MegAlign program of the DNAstar sequence analysis software (DNAstar, Madison, WI). Complementarity-determining regions were assigned according to the definition of Kabat ( 14). Ag-contact loops were defined according to Chotia et al. ( 14).

Size and complexity of the combinatorial library

As estimated by the efficiency of transformation of XL1-Blue E. coli competent cells, the IgG1/κ library made by in vitro pairing of the Ab heavy and light chains expressed in the PBMCs of SLE patient CS contained ∼2 × 10 ⁷ primary clones. The representation of all V H families in the library was ensured by the successful PCR amplification obtained with all of the primer combinations described above and confirmed by a combination of dot blot hybridization experiments using V H family-specific oligonucleotide probes and random sequencing of bacterial colonies isolated from consecutive rounds of panning against the Sm Ag (results not shown).

Isolation and characterization of recombinant anti-Sm mAbs

A 20-fold increase in the titer of eluted phage was obtained after three rounds of panning against Sm and an additional 10-fold increase was observed after the fourth round, strongly suggesting a significant enrichment in phage particles bearing specific anti-Sm Abs. To further evaluate these clones, phagemid DNA purified from the last round of panning was modified as described and used to generate E. coli colonies that secreted soluble Fab fragments. Four of 10 randomly picked colonies produced significant binding to Sm and were selected for detailed analysis. The characteristics of the recombinant Abs produced by these bacterial clones constitute the focus of this paper. Fab fragments were purified from large-scale cultures induced with IPTG and used for conventional titration ELISA to determine binding against Sm and a panel of irrelevant control Ags (Fig. 1). All four Fabs demonstrated very high binding against Sm in a dose-dependent fashion, with low binding against other Ags and low background binding. The binding specificity for the Sm Ag was also confirmed by competitive ELISA in which a set of soluble Ags, including Sm itself, were used to compete against immobilized Sm (Fig. 2). These experiments show that only Sm produced significant inhibition as compared with control Ags. Using the method of Friguet et al. ( 13), the relative affinity constants of the recombinant anti-Sm Abs was estimated in the range of 2 × 10 −8 to 1 × 10 −8 M.

Epitope mapping of the Smith-B/B′ and -D polypeptides

The fine specificity of the recombinant Fabs was defined by ELISA in which the Abs were tested against all of the possible overlapping octapeptides derived from the amino acid sequence of the Sm-B/B′ and -D1 polypeptides (233 and 112 octapeptides, respectively). These assays were also performed with serum samples obtained from patient CS concomitantly with the cells used for the construction of the combinatorial library. The results of these experiments are presented in Figs. 3 and 4. Overall, the recombinant Fabs showed very restricted specificity and reacted mainly with only 1 or 2 of the 345 octapeptides tested (the only exception, mAb F-14, will be discussed below). As a rule, they recognized the same epitopes also recognized by the patient's serum Abs. Thus, mAb FATI-1 only recognized the two major and earliest epitopes of the anti-Sm response, the recurrent PPPGMRPP and the similar and overlapping PPPGMRGP sequence with a reactivity of 5 and 14 SDs, respectively, over background levels (Fig. 5). Despite its monovalent nature, the reactivity of this Fab fragment with Sm epitopes was equivalent to that of a whole anti-Sm mAb derived from autoimmune mice, KSm5 ( 15). In turn, mAb F-17 exquisitely recognized another octapeptide sequence (MAPPPGMR) but not the overlapping PPPGMRPP octapeptide. Neither one of these mAbs showed any reactivity with Sm-D octapeptides. The reactivity of the third and fourth mAbs was concentrated on the Sm-D polypeptide. Interestingly, both mAbs F-4 and F-14 recognized the same octapeptides 12-15 derived from the amino terminus of the Sm-D molecule (spanning residues 12-22, ¹²HETVTIELKNG ²²) with a reactivity >10 SD above the normal mean. A similar, partially overlapping sequence (octapeptide 17, ¹⁷IELKNGTQ ²⁴) was also recognized by the patient's serum. In addition, F4 gave minor reactivity (2-3 SD above the mean) with octapeptides 76-78 ( ⁷⁶LDTILVDVEP ⁸⁵). This sequence has partial overlap with the main peak obtained with the patient's serum (octapeptide 79, ⁷⁹ILVDVEPK ⁸⁶). F-14 also recognized a carboxyl-terminal epitope which contains the GRG repeat characteristic of this part of the Sm-D molecule (octapeptide 105, ¹⁰⁵GRGRGRGR ¹¹²) ( 16). Interestingly, this mAb displayed some significant degree of cross-reactivity with the region encompassed by overlapping octapeptides 144-151 and 150-157 ( ¹⁴⁴PQGRGTVAAAAAAA ¹⁵⁷) as well as with multiple epitopes of Sm-B/B′.

Genetic analysis of recombinant anti-Sm autoantibodies

DNA sequencing analysis of the genes encoding the variable regions of both heavy and light chains revealed a remarkable restriction in the use of V H genes. Thus, all four mAbs were encoded by different members of the V H4 family (V H4-30.1/31,V H4-34, V H4-61, and V H4-59). In contrast, the light chains were encoded by genes derived from the V κ1 and V κ3 families. Both heavy and light chain genes displayed characteristics of Ag-selected somatic hypermutation with a degree of similarity with the corresponding germline sequences ranging from 92 to 98%. A detailed analysis of these sequences will be published elsewhere. ⁴

View Abstract

# data[].attributes.attachment_link.title
Delineation of the Human Systemic Lupus Erythematosus Anti-Smith Antibody Response Using Phage-Display Combinatorial Libraries

# data[].attributes.attachment_link.description
The anti-Smith (Sm) autoantibody response is highly specific for systemic lupus erythematosus and is predominantly targeted to the Sm-B/B′ and -D1 polypeptides. In all animal species thus far studied, anti-Sm Abs initially recognize proline-rich epitopes in the carboxyl terminus of the Sm-B/B′ protein and subsequently to multiple other epitopes in B/B′ and D.

# data[].attributes.attachment_link.title
Log in through your library or institution - ProQuest

# data[].attributes.attachment_link.description
Alternatively, your institution may be listed but may not have access to ProQuest because they do not have an account or they have not signed up for this type of access with us.

# data[].attributes.attachment_link.description
The online version of Measuring Immunity by Michael T. Lotze and Angus W. Thomson on ScienceDirect.com, the world's leading platform for high quality peer-reviewed full-text books.

# data[].attributes.attachment_link.title
Log in through your library or institution - ProQuest

# data[].attributes.attachment_link.description
Alternatively, your institution may be listed but may not have access to ProQuest because they do not have an account or they have not signed up for this type of access with us.

# data[].attributes.attachment_link.title
Log in through your library or institution - ProQuest

# data[].attributes.attachment_link.description
Alternatively, your institution may be listed but may not have access to ProQuest because they do not have an account or they have not signed up for this type of access with us.

# data[].attributes.body
http://www.medicalcriteria.com/site/home/79-rheumatology/335-reusledai.html

# data[].attributes.attachment_link.title
NTU Single sign-on - CAS - Central Authentication Service

# data[].attributes.attachment_link.title
Systemic Lupus Erythematosus - ScienceDirect

# data[].attributes.attachment_link.description
The online version of Systemic Lupus Erythematosus by George C. Tsokos on ScienceDirect.com, the world's leading platform for high quality peer-reviewed full-text books.

# data[].attributes.attachment_link.title
NTU Single sign-on - CAS - Central Authentication Service

# data[].attributes.body
http://www.aafp.org/afp/2003/1201/p2179.html

# data[].attributes.attachment_link.title
NTU Single sign-on - CAS - Central Authentication Service

# data[].attributes.attachment_link.title
Neuropsychiatric systemic lupus erythematosus: Tools for the diagnosis

# data[].attributes.attachment_link.description
Neurological involvement is considered to be a serious complication of systemic lupus erythematosus (SLE). Neuroimaging plays an important role in det...

# data[].attributes.attachment_link.readable_text
1. Departments of*Pathology and

2. ‡Nephrology, College of Medicine, Hanyang University, Seoul, Korea; and

3. †Division of Biomedical Informatics, Seoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea

Present Address and Correspondence:
Dr. Moon Hyang Park, Department of Pathology, Konyang University Hospital, 158 Gwanjeodong, Seo-Gu, DaeJeon, 302-718, Korea. Email: parkmh{at}hanyang.ac.kr

Summary

Background and objectives Previous studies showed that the accuracy of IgG subclasses (ISs) in differentiating membranous lupus nephritis (MLN) from primary membranous nephropathy (PMN) is <80%. This study hypothesized that diagnostic accuracy of ISs would be increased if renal compartment measurements and decision tree analysis are applied.

Design, setting, participants, & measurements Renal biopsy specimens from 41 patients with MLN and 59 patients with PMN between October 2004 and March 2010 were examined, and immunofluorescence staining against IgG1, IgG2, IgG3, and IgG4 as well as C3, C1q, and C4 was evaluated in five different renal compartments (glomerular capillary walls, mesangium, tubules, interstitium, and blood vessels). From IS data, a decision tree to differentiate MLN from PMN was produced (IS decision tree) and its accuracy was compared with that of previous studies. Diagnostic accuracy of the IS decision tree was also compared with that of the complement decision tree as a reference.

Results The demographic information and patterns of IS deposition were similar to those of previous studies. The IS decision tree had, as decision markers, IgG1 in the mesangium and IgG2 and IgG4 along the glomerular capillary wall. The IS decision tree showed higher accuracy (88%) than that of previous studies (<80%) and also that of the complement decision tree (81%).

Conclusions Accuracy of ISs was increased due to the study methods, but the same methodology was less effective using complement measurements. Appropriate data analysis may enhance diagnostic value, but the analysis alone cannot achieve the ideal diagnostic value.

Introduction

Human IgG protein consists of four distinct subclasses (IgG1, IgG2, IgG3, and IgG4) made from each of the four different constant regions of the Ig heavy chain on human chromosome 14 ( 1, 2). These IgG subclasses are different in structure and biologic properties, differently expressed depending on type, degree, and onset of inflammatory response ( 3- 5), and are also associated with several human diseases, including immunodeficiencies and allergic and autoimmune diseases ( 6- 10).

The different patterns of expression of IgG subclasses in lupus nephritis (LN), including membranous LN (MLN) and primary membranous nephropathy (PMN), have been studied. By scoring the glomerular immunofluorescence staining intensities and serum concentration of each member of the IgG subclasses, researchers found that IgG1, IgG2, and IgG3 tended to be highly expressed in LN, whereas IgG1 and IgG4 tended to be highly expressed in PMN ( 11- 14). These findings, however, do not directly indicate that IgG subclasses can be used as a marker differentiating MLN from PMN without considering the diagnostic accuracy. The diagnostic accuracy of IgG subclasses from the data of Imai et al. ( 11) is 80% if the interactions between the markers are not considered. Improved diagnostic accuracy using IgG subclasses can be obtained by applying better methodologies.

First, diagnostic accuracy can be improved if the immunofluorescence staining intensities of each of the IgG subclasses are measured in five different tissue compartments of the kidney parenchyma: glomerular capillary walls (GCWs), mesangium, tubules (tubular basement membrane [TBM]), interstitium, and blood vessels. In previous studies, it was not considered and only the overall glomerular immunofluorescence intensity was scored ( 11- 14). Different levels of immune complex deposits in the different compartments of the kidney reflect the different mechanisms of action with regard to renal injuries ( 15).

Second, more accurate decision rules to differentiate MLN from PMN can be obtained by applying data-driven classification models. One of these methods is decision tree analysis, which is a classification tool that uses a tree-like model of decisions on the multivariate data ( 16, 17). The diagnostic accuracy of IgG subclasses may be increased using decision tree analysis.

Considering those backgrounds, it would be necessary to re-evaluate the diagnostic accuracy of IgG subclasses after applying better methodologies. We therefore hypothesized that diagnostic accuracy of IgG subclasses in differentiating MLN from PMN would be increased if renal compartment measurements and decision tree analysis are applied. Furthermore, the significance of our methodologies would be further clarified if a reference marker is introduced for comparisons with IgG subclasses. Thus, our additional hypothesis is that even with the introduction of the better methodologies, not all markers are powerful as IgG subclasses. We selected complement components (C1q, C3, and C4) as a reference because they are conventional markers used for differential diagnosis in immunofluorescence. Then, as a reference, we can compare the diagnostic accuracies between IgG subclasses and complement components after the same methodologies were applied. Overall, the effects and the significances of selection of the methodologies were investigated in this research.

Materials and Methods

The overall research scheme was designed in three parts. First, experimental data for IgG subclasses and complements for each renal compartment were generated. Second, the patterns of data were explored using various visualization methods such as heatmaps and scattergrams for more subtle pattern recognition. Finally, using decision tree analysis, we tested whether the accuracy of IgG subclasses was improved compared with the previous study and whether diagnostic accuracy of IgG subclasses was higher than that of complements.

Experimental Procedures for IgG Subclass and Complement Profiles

Visualization and Descriptive Statistical Analyses

To explore the patterns of distribution of IgG subclasses in MLN and PMN, descriptive statistical methods were used and data were displayed using various visualization methods, including a heatmap ( 19) and a scattergram. In making a heatmap, a dendrogram was accompanied. The dendrogram shows grouping of patients at various scales according to the similarity of IgG subclass profile. The IgG subclass profile of each patient was represented as a 20-dimensional vector, with each immunofluorescence intensity as a value. The similarity between two patients is determined by the distance between the corresponding vectors; thus, each of the patients is grouped with the most similar case. Each of these two groups is then grouped according to the similarity between groups. This process was repeated until one big group is made. The mean immunofluorescence intensities of the 20 markers (4 subclasses × 5 renal compartments) were compared with the t test, between MLN and PMN (R2.14.1; R Development Core Team, Vienna). We investigated sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of each diagnostic criteria generated by changing the range of the intensities of each marker ( Supplemental Appendix 1). Accuracy for each diagnostic criterion is defined as the proportion of correctly classified patients over the total cases.

Decision Tree Analysis

Two decision trees using the C5.0 algorithm (Clementine 12.0; SPSS, CA) ( 16, 17) were made each using data from IgG subclasses and complements. Mean diagnostic accuracies were also calculated by 10-fold cross-validation. Improvement of diagnostic accuracy of IgG subclasses by the introduction of decision tree analysis was investigated. Then diagnostic accuracies between two decision trees were compared with test marker dependency of the decision tree analysis.

The diagnostic accuracies of the previous study were not explicitly described, but obtaining those values from data published by Imai et al. were straightforward ( 11). Because immunofluorescence intensity of each marker was semiquantitatively measured from 0 to 4, we could exhaustively generate all of the possible diagnostic criteria of one disease by changing the range of intensities of each marker, making the diagnostic criteria of the other disease automatically determined. For each diagnostic criterion, diagnostic accuracies were calculated by calculating the proportion of accurately classified patients over the total cases. All of the diagnostic accuracies were ≤80%.

Ten-fold cross-validation is a statistical estimation using the current data set on how accurately a predictive model will perform in an independent data set ( 16). The original data are randomly partitioned into 10 parts. Nine subsamples are designated as training sets, which will make a model, and the remaining subsample is designated as a test set, which will test the model. Another nine subsamples and the remaining subsample then become a training set and a test set, respectively. These processes are repeated until all of the 10 subsamples are used as a test set. For each of these steps, the performance of each model can be measured and we can obtain the distribution of them. The other K-fold cross-validation can be applied to this problem, but 10-fold cross-validation is the most commonly used method.

Results

IgG Subclass and Complement Profiles

Visualization and Descriptive Statistical Analyses

Decision Tree Analyses

Decision tree analysis was performed in two datasets (IgG subclass profile, complement profile) ( Figure 4, A and B). The decision tree using IgG subclass profile was computationally produced by the C5.0 algorithm and the decision rules were set as follows (the decision rules are equivalent to that shown in Figure 4A). A patient is diagnosed with MLN if ( 1) IgG1 is positive in the mesangium or ( 2) IgG1 is negative in the mesangium, and IgG2 is positive and IgG4 is negative along the GCW. A patient is diagnosed with PMN if ( 3) IgG1 is negative in the mesangium and IgG2 is negative or ( 4) IgG1 is negative in the mesangium, and IgG2 and IgG4 are positive along the GCW.

After 10-fold cross-validation, the mean accuracies were estimated to be 88% with 3.3% of SEM, which is higher than the highest diagnostic accuracy of IgG subclasses in the previous study (80%) ( 11). The decision tree using complements showed lower estimated accuracy (81.0%±3.8%) than that of the decision tree using IgG subclasses, which were statistically significant ( P=0.0004) ( Table 3). When the combined IgG subclass and complement profile was used to make a decision tree, the accuracy (92.0±3.3) was more increased than that of IgG subclasses alone, but it was statistically insignificant ( Table 3 and Supplemental Appendix 4).

Discussion

In this study, we proved that previously described diagnostic accuracy of IgG subclasses in differentiating MLN from PMN can be increased by applying immunofluorescence intensity measurement for each renal compartment and decision tree analysis. This result signifies that the diagnostic value of IgG subclasses has been underestimated and that appropriate methodologies can recover their real diagnostic value. We also demonstrated that this enhancement might be dependent on the marker by showing that the diagnostic accuracy of IgG subclasses was higher than that of complements even when the same methodologies were applied.

Selection of appropriate markers and analytical methods resulted in these significant results. Previous research showing the distinct patterns of IgG subclasses between MLN and PMN ( 11- 14) led us to select these markers. Decision tree analysis was selected because complex patterns can be easily simplified in this approach, the results are easy to understand, and it is computationally feasible. Because markers and analytical methods were not thoroughly investigated, we cannot exclude the possibility that there might be better combinations of markers and analytical methods than those presented in this study. For this, further research will be required.

The decision tree results of the IgG subclasses are consistent with the pathogenesis of MLN and PMN. First, immune deposits can be found only along the GCW in PMN; however, they can be found in some amount in the mesangium as well in MLN. In the decision trees, the node that was positive for markers in the mesangium was diagnosed as MLN (node 6 in Figure 4). Second, a mixed T H1 and T H2 response is predominant in LN, whereas a T H2 response is predominant in PMN and these responses are mediated by IgG subclasses ( 20, 21). IgG2 and IgG3 were known to be produced in T H1 response and IgG4 in T H2 response ( 20, 21). In the decision trees, nodes positive for T H1-related isotypes or negative for T H2-related isotypes were diagnosed as MLN (node 4 in Figure 4), whereas nodes positive for T H2-related isotypes or negative for T H1-related isotypes were diagnosed as PMN (nodes 2 and 5 in Figure 4). The consistency of the decision tree results with the current understanding of the pathogenesis of MLN and PMN in relation to IgG subtype and localization of immune deposits support our conclusions.

Most LN patients other than class V (MLN) showed similar patterns of IgG subclass profiles as shown in MLN, exhibiting strong positive immunofluorescence staining for IgG1, IgG2, and IgG3 and negative for IgG4 in the subendothelial portion along the GCW and in the mesangium as well. Deposition of these markers in extraglomerular locations such as TBM, interstitium, and blood vessels was rarely found in patients with MLN compared with class IV patients. No extraglomerular IgG subclass deposits were seen in PMN patients.

Our decision tree of IgG subclasses can be applicable in certain clinical situations. Patients with early stage MLN were found to be antinuclear antibody-negative in 35% of cases ( 22). There are no definitive diagnostic procedures for these patients. In this background, the usefulness of IgG subclass deposition can be tested in further studies. The possibility of ethnic dependence of IgG subclass deposition should be considered. In African-American and Caucasian patients with LN, interstitial inflammation was more common in African Americans than Caucasians ( 23). In this study, IgG staining was present in the TBM in 62% of patients and in the vascular walls in 48% of patients compared with 20% and 12% of patients with MLN in our Korean patients, respectively. These results should prompt research on IgG subclass profiles in common renal diseases among different ethnic groups.

In conclusion, we showed that the diagnostic value of IgG subclass deposition in LN and PMN is enhanced if immunofluorescence intensity is measured separately in each renal compartment and decision tree analysis is applied. The immunofluorescence intensities for IgG1 in the mesangium and IgG2 and IgG4 along the GCW were found to be markers effectively differentiating MLN from PMN. Furthermore, this enhanced accuracy could not be achieved by the use of complements although the same methodologies were applied. These results imply that appropriate selection of analysis methods may be as important as the appropriate selection of markers. Our methods have a wide range of applications in nephrology and renal pathology. Further study should be undertaken to find better combinations of markers and analysis methods to aid in clinical decision making.

Disclosures

None.

Acknowledgments

We thank Dr. James Robinson Hackney for critical review of this article.

# data[].attributes.attachment_link.title
Differential Diagnosis of Lupus and Primary Membranous Nephropathies by IgG Subclass Analysis

# data[].attributes.attachment_link.description
Departments of*Pathology and ‡Nephrology, College of Medicine, Hanyang University, Seoul, Korea; and †Division of Biomedical Informatics, Seoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea Present Address and Correspondence: Dr. Moon Hyang Park, Department of Pathology, Konyang University Hospital, 158 Gwanjeodong, Seo-Gu, DaeJeon, 302-718, Korea.

# data[].attributes.attachment_link.title
SAGE Journals: Your gateway to world-class journal research

# data[].attributes.attachment_link.description
Subscription and open access journals from SAGE Publishing, the world's leading independent academic publisher.

# data[].attributes.attachment_link.title
Microarray based on autodisplayed Ro proteins for medical diagnosis of systemic lupus erythematosus (SLE)

# data[].attributes.attachment_link.description
A microarray-based immunoassay for the detection of autoantibodies against Ro protein was developed using Escherichia coli with autodisplayed Ro prote...

# data[].attributes.attachment_link.title
Log in through your library or institution - ProQuest

# data[].attributes.attachment_link.description
Alternatively, your institution may be listed but may not have access to ProQuest because they do not have an account or they have not signed up for this type of access with us.

# data[].attributes.body
Basics of Lupus - symptoms and diagnostics

# data[].attributes.attachment_link.title
NTU Single sign-on - CAS - Central Authentication Service

# data[].attributes.attachment_link.readable_text
Statistics from Altmetric.com

Systemic lupus erythematosus (SLE) is a protean autoimmune disease where autoantibodies are frequently targeted against intracellular antigens of the cell nucleus (double and single stranded DNA (dsDNA and ssDNA, respectively), histones, and extractable nuclear antigens (ENAs). Most of these autoantibodies are not specific for SLE and might be produced non-specifically as a result of polyclonal B cell activation. This article will focus on the evidence base for the most commonly used laboratory assays for the detection of these autoantibodies. Updated American Rheumatism Association (ARA) criteria for the diagnosis of SLE include several autoantibodies (table 1). SLE is likely if four of 11 criteria are met over any time period. Importantly, the methods for detecting these antibodies are not specified by the ARA, and this article aims to highlight the fact that the particular assay used will crucially influence the interpretation of the test (table 2). Autoantibodies are usually polyclonal-of mixed isotype, affinity, and avidity-and are often directed against multiple targets. Different assays detect particular antibody properties, which are often quite different, and the clinical importance of this for pathogenesis or diagnosis is rarely fully understood. The use of laboratory tests in SLE is a perfect example of this dilemma. The prevalence of autoantibodies varies widely in cross sectional studies, perhaps partly as a result of such differences (table 3). Immunodiffusion (ID) detects high affinity antibodies, immunofluorescence (IIF) moderate and high affinity antibodies, and enzyme linked immunosorbent assay (ELISA) low and high affinity antibodies. Purified antigens might have contaminants, or might not contain the full complement of native proteins. Recombinant antigens might lack certain epitopes, have altered glycosylation or tertiary structure, or contain contaminating bacterial antigens. All assays require careful validation to determine whether they perform adequately for detecting human autoantibodies. An ideal test would be specific (detects only those with disease), sensitive (detects all those with disease), have a high positive predictive value (PPV)-where most positives have disease, and a high negative predictive value (NPV)-where most negatives do not have disease. In addition, assay results may reflect disease activity, correlate with organ involvement, or predict relapse, thus allowing pre-emptive treatment. No test or test panel can currently perform all these tasks because increases in specificity usually lead to reciprocal decreases in sensitivity, and because some of the clinical features of SLE are not antibody mediated. Therefore, the information obtained from any test will reflect the types of antibody detected, the prevalence of the disease in the population being tested, and the question being asked of the test.

Anti-DNA antibodies

dsDNA antibodies are associated with systemic lupus and nephritis, but not subacute cutaneous lupus or discoid lupus. The best method for detecting anti-dsDNA remains controversial (table 4). The most common techniques in the UK are dsDNA ELISA, Crithidia luciliae IIF (CLIF), or Farr immunoprecipitation assays (table 2). Specific assays should be used for diagnosis, whereas sensitive assays might be more useful for monitoring. There are several difficulties in the detection of anti-dsDNA, which apply to other autoantibodies, including:

1. Substrate differences: many sources of mammalian and non-mammalian DNA are used, but each might detect a different set of antibodies.

2. The isotype of antibody detected: assays might detect different antibody isotypes (IgG, IgA, IgM, or any combination). All isotypes are detected by Farr assays, ELISA, or CLIF, which use polyspecific antisera. A positive polyspecific assay might have a different clinical relevance to that of an IgG specific assay. IgM anti-dsDNA detected by ELISA might not be specific for SLE.

3. Antibody affinity: high affinity anti-dsDNA might be more relevant to SLE pathogenesis, particularly in nephritis. Low affinity antibodies are not detected by Farr assays, but are detected by ELISA.

4. Assay specific parameters: each assay has known causes of false positivity. For example, C reactive protein (CRP) or ssDNA contamination in the Farr; lipoprotein-IgG complexes in CLIF; antibodies to linkers in ELISA. Contamination with ssDNA leads to overestimation of anti-dsDNA titres, because anti-dsDNA antibodies regularly bind ssDNA, but ssDNA antibodies are not specific for SLE. This might not be important for monitoring disease activity because ssDNA might reflect the overall antinucleosome immune responses, but it might reduce the diagnostic usefulness of an assay because ssDNA antibodies are not specific for SLE.

5. Problems with standardisation and calibration: an assay has to be precise (give the same result on the same serum every time) to enable successful monitoring of serial titres. An assay should be accurate and produce the same result as other assays on all serum samples to enable comparison between different centres. An international reference preparation (IRP) for anti-dsDNA (Wo80) is available to improve standardisation between assays (table 6), but there remains poor correlation between dsDNA assays in EQA schemes, even within a single technology. All laboratories should participate in EQA schemes and maintain adequate internal quality control procedures.

DIAGNOSIS

Farr assays are quite specific and well documented, but also detect high affinity IgM anti-dsDNA. IgG specific ELISA or CLIF methods are commonly used in UK laboratories, and may produce similar results to Farr assays. Polyspecific ELISAs also detect low affinity IgM antibodies of dubious clinical relevance and are less useful. ELISA results (particularly those detecting IgM) should be confirmed by IgG specific CLIF or Farr assays. CLIF is less likely than ELISA to detect low affinity anti-dsDNA of uncertain clinical relevance, especially if IgG specific conjugates are used. Local validation of each assay is essential to ensure adequate diagnostic performance.

MONITORING OF DISEASE

Anti-ssDNA activity might be useful in monitoring activity, but it is not clear that this offers any advantage over anti-dsDNA measurements and no EQA/IRP for ssDNA is available.

Antihistone antibodies

Around 50-80% of patients with SLE have IgG and IgM antihistone antibodies detectable by immunoblotting (IB) or ELISA. ELISAs are described that detect antibodies to total histones or to subfractions (H1, H2a, H2b, H3, and H4), but the clinical specificity is not well established for any subfraction. Titres of antihistone antibody might reflect disease activity, but are not specific for SLE and cannot distinguish drug induced SLE from idiopathic SLE. Drug induced antibodies are often IgM and occur without any clinical manifestations.

Antibodies to ENAs

Diagnosis

Monitoring

There is little evidence that anti-ENA specificity or titres reflect SLE activity, but anti-Ro is associated with cutaneous involvement in subacute cutaneous lupus erythematosus, and with congenital heart block (CHB). Anti-Ro52 in isolation is associated with CHB but is not detected by assays containing only Ro-60, such as HEp-2000 cells.

Neonatal SLE and CHB

ANTIBODIES TO SM/rnp

Diagnosis

Monitoring

There are insufficient data on the more rare ENA specificities to justify routine clinical use.

Acute phase proteins/cytokines

The erythrocyte sedimentation rate is a sensitive but non-specific indicator of activity in SLE, and is slow to reflect changes in disease activity. CRP has a short half life and rapidly reflects acute inflammation. A high CRP can distinguish bacterial infection from active SLE, where the CRP is usually low, but CRP might be raised in severe lupus serositis. Soluble interleukin 2 receptor or tumour necrosis factor receptor values might reflect disease activity, but are not specific for SLE, and are of uncertain clinical relevance.

Anti-C1q antibodies

Anti-endothelial cell antibodies

Anti-endothelial cell antibodies may reflect disease activity, but are poorly characterised.

Antineutrophil cytoplasmic antibodies

Antineutrophil cytoplasmic antibodies of all types are found in SLE and are not clinically relevant.

Summary

ANA IIF is an effective screening assay in patients with clinical features of SLE and will detect most anti-ssDNA, anti-dsDNA, ENAs, and other autoantibodies. False positives are common. The clinical importance cannot be extrapolated from the ANA titre or pattern, although higher titres (> 1/160) are more likely to be important. HEp-2 cells are the most sensitive substrate for ANA detection, but this must be balanced against an increased incidence of insignificant positivity.

For monitoring, a precise, quantitative assay is required. It is unclear whether the detection of IgM or low affinity antibodies has a role here. A combination of anti-dsDNA, C3, C4, CRP, and ESR assays provides the most useful clinical information. Anti-ssDNA assays are likely to be useful, and are potentially more robust than anti-dsDNA assays, but require more validation.

Local validation of individual assays and EQA participation is essential. Not all assays that apparently measure the same antibody specificities have equal clinical relevance, even within a single technology. Insufficient international or national reference preparations are currently available for many antibody specificities to enable effective standardisation. Quality assurance schemes reveal large differences in units reported by different assays for some analytes, even when calibrated against an IRP or equivalent reference preparation. Serial results can therefore only be compared from the same laboratory at present. Most autoantibodies increase during active disease, but few prospective data are currently available to justify treatment on the basis of rising titres. Further randomised prospective studies are required to examine the importance of antibody isotype and affinity in the monitoring of SLE by individual assay methods. The most important aspect of the appropriate use of laboratory assays is to become familiar with the limitations of the technology currently in use in your local laboratory, and to consult with your clinical immunologist in cases of doubt, preferably before commencing serological screening.

View Abstract

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center's RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

# data[].attributes.attachment_link.title
The use of laboratory tests in the diagnosis of SLE

# data[].attributes.attachment_link.description
Systemic lupus erythematosus (SLE) is a protean autoimmune disease where autoantibodies are frequently targeted against intracellular antigens of the cell nucleus (double and single stranded DNA (dsDNA and ssDNA, respectively), histones, and extractable nuclear antigens (ENAs). Most of these autoantibodies are not specific for SLE and might be produced non-specifically as a result of polyclonal B cell activation.