Association of a 62 Variants Type 2 Diabetes Genetic Risk Score With Markers of Subclinical Atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2D) and cardiovascular disease share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes mellitus. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA. METHODS AND RESULTS: In a cross-sectional analysis, including ≤9210 European Americans, 3773 African Americans, 1446 Hispanic Americans, and 773 Chinese Americans without known cardiovascular disease and enrolled in the Framingham Heart Study, Coronary Artery Risk Development in Young Adults, Multi-Ethnic Study of Atherosclerosis, and Genetic Epidemiology Network of Arteriopathy studies, we tested a 62 T2D-loci genetic risk score for association with measures of SCA, including coronary artery or abdominal aortic calcium score, common and internal carotid artery intima-media thickness, and ankle-brachial index. We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors-adjusted model (significance, P<0.01=0.05/5, number of traits analyzed). An inverse association with coronary artery calcium score in Multi-Ethnic Study of Atherosclerosis Europeans (fully-adjusted P=0.004) and with common carotid artery intima-media thickness in the Framingham Heart Study (P=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance genetic risk sub-scores in the Framingham Heart Study and in the Coronary Artery Risk Development in Young Adults. CONCLUSIONS: SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and cardiovascular disease risk loci.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".