035. CANDIDATE BIOMARKERS IN ANCA-ASSOCIATED VASCULITIS IDENTIFIED USING A PROTEOMIC APPROACH
Bibliographic record
Abstract
Background: Concentrations of many circulating proteins are elevated during severe, active ANCA- associated vasculitis (AAV). Finding biomarkers associated with milder disease, a more clinically relevant need, has proved challenging. In addition, some biomarkers may be directly affected by glucocorticoids. Methods: 30 patients with AAV participating in a longitudinal cohort were studied. Serum samples from 2 visits were used for this study: i) a visit during active disease and when off prednisone; and ii) a visit approximately 3 months later when in clinical remission and on prednisone. A proteomic platform (SomaLogic) was used to measure more than 1300 circulating proteins simultaneously. Wilcoxon signed rank tests were used to analyze 2000 sub-cohorts of 15 patients each resulting from 1000 permutations, with median P < 0.01 regarded as significant. Results: The cohort included 23 patients with GPA, 5 with EGPA, and 2 with MPA. Mean age was 52, and 18 were female. Thirteen were taking a non-steroid immunosuppressive drug at the time of flare, and 21 afterward. Disease activity was relatively low: physician global assessment of severity on a 0-10 scale had a mean of 3.2 (median 3, range 1-7), and only 7 patients had a “major” manifestation by BVAS/WG. Sixteen proteins were associated with active disease: MMP-12, thrombospondin-4, MIP-5, prolactin, MMP-1, FABP3, CD23/FceR, MDC/CCL22, IL-23, PAPP-A, afamin, seprase, MMP-3, RET, complement factor B, and CD5L. Of 77 proteins previously reported to be associated with active AAV, only one met criteria for a significant association in this study, and only 5 others had median P < 0.05. Conclusion: In a cohort of patients with active but relatively mild AAV, 16 serum proteins were associated with significant change after successful treatment with prednisone. Fifteen of these markers have not been reported in AAV. These proteins, all of which are measurable by commercial immunoassays, are candidates for further study in real-world cohorts of partially-treated patients with AAV and mildly active disease. Disclosures: ReveraGen is a for-profit pharmaceutical company. The three authors who are employees of ReveraGen are identified. The other authors do not have a financial interest in ReveraGen. This work was sponsored by the Vasculitis Clinical Research Consortium and received support from the National Institutes of Health (U54 AR057319, RC1 AR 058303, P60 AR047785, and N01 AI15416) and from ReveraGen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".