NOVEL AUTOANTIBODIES IDENTIFIED IN THE ANTIPHOSPHOLIPID SYNDROME
Bibliographic record
Abstract
O047 / #343 Topic:AS03 - Antiphospholipid Syndrome ABSTRACT CONCURRENT SESSION 08: RECENT ADVANCES IN LUPUS BIOMARKERS 23-05-2025 1:40 PM - 2:40 PM Background/Purpose The antiphospholipid syndrome (APS) is a systemic autoimmune disease characterized by arterial, venous, or microvascular thrombosis, recurrent pregnancy morbidity, or nonthrombotic manifestations in the setting of persistent antiphospholipid antibodies (aPL), namely anti-β2 glycoprotein-I antibody (aβ2GPI), anticardiolipin antibody (aCL), and lupus anticoagulant (LAC). Around one-third of the APS patients had an isolated LAC positivity lacking aβ2GPI and aCL. This study aimed to identify novel autoantibodies in APS using protein microarray technology. Methods Sera from APS patients, disease controls (DCs), and healthy controls (HCs) were applied to the HuProt™ Human Proteome Microarray v4.0 for the discovery of novel autoantibodies. Candidate autoantibodies were then validated using ELISA in an additional 372 sera samples, comprising 189 primary APS patients, 87 secondary APS patients, 48 SLE patients, and 48 HCs. Results During the discovery phase, HuProt microarrays were incubated with serum samples (5:1 mixture) from APS patients, DCs, and HCs to identify APS-associated autoantigens. Approximately 20 autoantigens were identified for subsequent validation. These potential autoantigens include proteins involved in or associated with ubiquitination and deubiquitination (UBE3A, ATXN3), proteasome (PSME3), microtubule (MAP9), vesicular transport (ASAP2), ribosome (NPM1, RPLP2), amino acid modification (PRMT7), DNA and RNA (RBM38, IRX2, AGO1), inflammation (WDR54, IRAK4, ACVR2B, N4BP1, MX1), metabolism (ACSBG1, SULT2B1, HK1, GLOD4), coagulation factor (SERPINB2), and others. In the validation phase, 6 proteins (SULT2B1, NPM1, AGO1, SERPINB2, ACVR2B, IRAK4) were selected and validated using ELISA. Anti-SULT2B1 and anti-AGO1 autoantibodies were significantly higher in primary APS patients. Anti-SULT2B1, anti-AGO1, and anti-NPM1 were also significantly higher in secondary APS patients. Anti-NPM1 positive patients exhibited a significantly higher incidence of SLE (50.9% vs 33.7%, p=0.013), cardiac valve involvement (16.3% vs 6.1%, p=0.031), and triple positivity (53.1% vs 33.5%, p=0.010) compared to anti-NPM1 negative patients. Validation of other autoantibodies is ongoing (Figure). Figure. Conclusions We identified novel autoantibodies targeting proteins involved in a broad range of biological processes in APS. Anti-SULT2B1, anti-AGO1, and anti-NPM1 autoantibodies were identified in APS patients, demonstrating diagnostic and clinical value. Further validation of additional autoantibodies in larger APS cohorts is ongoing.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".