Shared Genetics of Migraine and Gastrointestinal Disorders Implicates Underlying Neurologic Mechanisms Yet Heterogeneous Etiologies
Bibliographic record
Abstract
Background and Objectives: Migraine is strongly comorbid with irritable bowel syndrome (IBS), one of several gastrointestinal (GI) conditions that are distinguished by symptomatic profiles that are partly overlapping. Potential shared mechanisms of migraine and the GI conditions were investigated by assessing shared genetics on a genome-wide basis. Methods: Analyses leveraged genome-wide summary statistics from large-scale genetic studies for migraine, including by aura status, IBS, peptic ulcer disease (PUD), gastrointestinal reflux (GERD), functional dyspepsia (FD), diverticular disease (DD), and the immune-related inflammatory bowel disease (IBD) or its constituents, ulcerative colitis (UC) and Crohn disease (CD). Genetic correlation was evaluated on a genome-wide basis and at independent local regions, including those related to therapeutic targeting of serotonin and the calcitonin gene-related peptide. Genetic correlation was assessed for enrichment at genes according to tissue specificity of gene expression. Potential causality between migraine and the GI conditions was assessed by Mendelian randomization. Results: ) on migraine, but not of migraine on any GI condition. Discussion: of migraine with both DD and the immune-related disorders suggests potential benefit to these conditions from repurposed migraine therapeutics targeting CGRP.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".