DOP16 Anti-integrin αvβ6 autoantibodies predate Ulcerative Colitis diagnosis by up to 10 years and are associated with adverse disease-related outcomes
Bibliographic record
Abstract
Abstract Background Biomarkers for predicting the development of Ulcerative Colitis (UC) and disease-related complications are lacking. Anti-integrin αvβ6 IgG autoantibodies (anti-αvβ6) have been recently described in patients diagnosed with UC. Here, we sought to determine if anti-αvβ6 autoantibodies predate UC development and to study associations between anti-αvβ6 and disease outcomes in newly diagnosed UC patients. Methods In a unique pre-clinical IBD cohort from the PRoteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects (PREDICTS), anti-αvβ6 were measured in longitudinal pre-diagnosis serum samples from 82 subjects who later developed UC as well as in 82 matched subjects that did not develop IBD (HC). Sample A was at the time of UC diagnosis, Sample B was at a median of 2 years before Sample A, Sample C was at a median of 4 years before Sample A and Sample D was at a median of 10 years before Sample A. In a distinct, external validation cohort (the Crohn’s and Colitis Canada Genetics Environment Microbial (GEM) Project), we tested samples from 12 subjects who later developed UC and compared those with 49 matched subjects who remained asymptomatic. Further, anti-αvβ6 were measured in 2 incident IBD cohorts (COMPASS, n=55 and OSCCAR, n=104 UC subjects) and associations between anti-αvβ6 and adverse UC-outcomes were defined using Cox proportional-hazards model. Results Anti-αvβ6 were significantly higher in the PREDICTS cohort among individuals who developed UC compared to HC up to 10 years prior to diagnosis (Figure 1A). The anti-αvβ6 seropositivity was 12.2% 10 years before diagnosis and increased to 52.4% at the time of diagnosis in subjects who developed UC compared with 2.7% in controls across the 4 timepoints. Additionally, the predictive performance of anti-αvβ6 autoantibodies as assessed via area under the receiver operator curves (AUROC) with 10-fold cross validation was at least 0.8 up to 10 years before diagnosis (Figure 1B). Elevated levels of anti-αvβ6 in pre-clinical UC samples were further validated in the GEM cohort (Figure 1C). Finally, high anti-αvβ6 were associated with a composite of adverse UC-outcomes including hospitalization, disease extension, colectomy, systemic steroid use and/or escalation to biologic therapy in both incident cohorts (Figure 1D). Conclusion Anti-integrin αvβ6 autoantibodies precede the clinical diagnosis of UC by up to 10 years and are associated with adverse UC-related outcomes.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".