Genetic Predictors of Benign Course of Ulcerative Colitis—A North American Inflammatory Bowel Disease Genetics Consortium Study
Bibliographic record
Abstract
BACKGROUND: A subset of patients with ulcerative colitis (UC) have a benign course and an overall favorable prognosis. Early identification of these low-risk patients may allow for a less aggressive therapeutic approach and possible reduction of therapy-associated risks. The aim of this project was to identify the genetic predictors of benign UC phenotype. METHODS: UC patients were selected from the National Institute of Diabetes and Digestive and Kidney Diseases Inflammatory Bowel Disease Genetics Consortium. Benign phenotype was defined as no need for immunomodulatory or biological therapy, hospitalizations, or colectomy. The association between benign UC phenotype and known loci linked to the risk of inflammatory bowel disease (IBD) was evaluated. The results for 156 index single-nucleotide polymorphisms (SNPs) from the known IBD loci were extracted for the main analysis. The association of the benign phenotype to a genetic burden score was also evaluated. RESULTS: None of the index SNPs from the IBD loci reached the predefined threshold of 1 × 10. In the exploratory analysis of the remaining Immunochip SNPs and imputed major histocompatibility complex data, 5 distinct suggestive association signals are identified (rs1697950, rs2523639, rs17836409, rs11742854, and rs75001121). CONCLUSIONS: No SNPs from IBD susceptibility loci were found to be associated (at our predefined threshold of 1 × 10) with a benign UC disease course. The rs11742570 variant on chromosome 5 was the one with the greatest association to benign disease although the association did not reach the predefined significant threshold. Given the modest power of our study, the findings suggested on the exploratory analysis merit extension to larger discovery cohorts.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".