AUTOANTIBODIES IN A MULTIINSTITUTIONAL INDIAN INCEPTION COHORT (INSPIRE): PREVALENCE, CLUSTER ANALYSIS AND PHENOTYPE ASSOCIATION
Bibliographic record
Abstract
PV189a / #296 Poster Topic: AS22 - SLE Heterogeneity Background/Purpose In SLE the prevalence of autoantibodies is variable across different ethnic group and data on Indian population is limited. Thus, we assessed the prevalence and association of different autoantibody clusters with clinical features in an Indian SLE inception cohort for research. Methods INSPIRE cohort is a cohort with 2503 patients accrued till October 2022 and currently 6 monthly follow-up is ongoing. At inclusion antibodies were assayed using Immunoline (Euroimmune, Germany) or ELISA. To determine autoantibody clusters, an unsupervised random forest algorithm was built with 10000 trees and the resulting proximity matrix was used to generate a distance matrix between individual autoantibodies. Odds ratios were used to identify associations between autoantibody/autoantibody clusters and clinical manifestations. Results A total of 2503 patients (mean age 27.69±10.19 years, 2292 [91.57%] females) were enrolled in the cohort. At the baseline, organ involvement (%) was as follows: constitutional features (68.23), alopecia (77.82), oral ulcers (49.74), acute cutaneous lupus (59.41), subacute/discoid lupus (12.4), arthritis (68.27), pleural effusion (20.94), pericarditis (12.39), nephritis as per active sediments and/or proteinuria (41.23), delirium (1.31), psychosis (2.27), seizures (7.39), autoimmune haemolysis (14.54), leukopenia (31.2), thrombocytopenia (24.85). Proliferative nephritis (class III, IV or combination of III/IV and V) was seen in 396, and non-proliferative lupus nephritis in 235. The median SLEDAI at baseline was 12 (IQR 6-18). Antibodies to the DNA nucleosome complex were the most common with anti-dsDNA in 70.19%, anti-nucleosome in 42.02% and anti-histone in 35.6%. This was followed by antibodies to the ribonuclear complex with anti-Sm (32.16%), anti-RNP (52.01%), anti-Ro52 (37.95%), anti-Ro60 (42.14%) and anti-La (12.26%). Other positive antibodies included anti-Ribosomal P (32.16%), anti-AMA-M2 (8.35%), anti-Scl70 (2.83%) anti-PCNA (4.55%), anti-PM/Scl (2.16%), anti-CENP-B (1.48%) and anti Jo-1 (0.99%). IgG autoantibodies (>40 GPL) to anticardiolipin and β2 glycoprotein1 were present in (10.06%) and (8.4%) patients respectively and 8.86% had lupus anticoagulant. Antibodies to dsDNA, histones and nucleosomes showed association with proliferative nephritis, oral ulcers and arthritis, anti-Ro antibodies had association with alopecia and serositis, antibodies to Sm, RNP and Ribosomal P showed association with mucocutaneous disease. Antibodies to Sm, nRNP, Ro and La were protective for proliferative nephritis. Four clusters of autoantibodies were identified. Cluster 1 had antibodies to dsDNA, histone and nucleosome and accounted for 932 (45.84%) patients. Cluster 2 had antibodies to Sm, nRNP, Ro52, Ro60 and Ribosomal P and accounted for 989 (48.65%) patients. Cluster 3 had autoantibodies to cardiolipin, β2GP1, lupus anticoagulant, La as well as AMA-M2 and accounted for 98 (4.62%) patients. Cluster 4 was a predominantly negative cluster which included antibodies to Scl-70, Jo-1, PCNA, PM-SCL and CENP-B and accounted for 18 (0.89 %) patients. Cluster 1 was associated (odds ratio) with clinically significant proteinuria (1.54) and proliferative lupus nephritis (2.06), pleural effusion (1.29), leukopenia (1.37) and with reduced risk of pericarditis (0.72). Cluster 2 was associated with increased seizures (1.36) and pericarditis (1.52) as well as lower risk of proteinuria (0.74), proliferative nephritis (0.56), leukopenia (0.82) and thrombocytopenia (0.78). Cluster 3 was associated with lower risk of proteinuria (0.57), proliferative nephritis (0.36), pleural effusion (0.41) and leukopenia (0.52). Conclusions The prevalence of anti-Sm and Ribosomal P antibodies is higher in Indian population, and they show association with mucocutaneous disease. While antibodies and Cluster 1 associated with DNA had an association with nephritis. Acknowledgment: The study was funded by a grant from the Department of Biotechnology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".