Gastrointestinal Consequences of Type 2 Diabetes Mellitus and Impaired Glycemic Homeostasis: A Mendelian Randomization Study
Bibliographic record
Abstract
OBJECTIVE: We conducted a Mendelian randomization (MR) study to examine the associations of type 2 diabetes and glycemic traits with gastrointestinal diseases (GDs). RESEARCH DESIGN AND METHODS: Uncorrelated genetic variants associated with type 2 diabetes (n = 231), fasting insulin (n = 38), fasting glucose (n = 71), and hemoglobin A1c (n = 75) at the genome-wide significance were selected as instrument variables. Genetic associations with 23 common GDs were obtained from the FinnGen and UK Biobank studies and other large consortia. RESULTS: Genetic liability to type 2 diabetes was associated with the risk of 12 GDs. Per 1-unit increase in the log-transformed odds ratio (OR) of type 2 diabetes, the OR was 1.06 (95% CI, 1.03-1.09) for gastroesophageal reflux disease, 1.12 (95% CI, 1.07-1.17) for gastric ulcer, 1.11 (95% CI, 1.03-1.20) for acute gastritis, 1.07 (95% CI, 1.01-1.13) for chronic gastritis, 1.08 (95% CI, 1.03-1.12) for irritable bowel syndrome, 1.04 (95% CI, 1.01-1.07) for diverticular disease, 1.08 (95% CI, 1.02-1.14) for acute pancreatitis, 1.09 (95% CI, 1.05-1.12) for cholelithiasis, 1.09 (95% CI, 1.05-1.13) for cholelithiasis with cholecystitis, 1.29 (95% CI, 1.17-1.43) for nonalcoholic fatty liver disease, 1.12 (95% CI, 1.03-1.21) for liver cirrhosis, and 0.93 (95% CI, 0.89-0.97) for ulcerative colitis. Genetically predicted higher levels of fasting insulin and glucose were associated with six and one GDs, respectively. CONCLUSIONS: Associations were found between genetic liability to type 2 diabetes and an increased risk of a broad range of GDs, highlighting the importance of GD prevention in patients with type 2 diabetes.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".