Rheumatoid arthritis and the risk of major cardiometabolic diseases: a Mendelian randomization study
Bibliographic record
Abstract
Rheumatoid arthritis (RA) is suggested to be implicated in the development of cardiometabolic diseases. We conducted a Mendelian randomization (MR) study to assess potential causality for associations of RA with the risk of cardiometabolic diseases, including type 2 diabetes (T2D), coronary artery disease (CAD), and ischaemic stroke. Seventy independent single-nucleotide polymorphisms (SNPs) associated with RA were identified as instrumental variables from a genome-wide association study (GWAS) of 58 284 European subjects. Summary-level data for the associations of the 70 genetic variants with T2D, CAD, and ischaemic stroke were taken from three GWASs with a total of 1 529 131 participants. Inverse-variance weighted (IVW) MR was used in the main analyses. The main IVW MR analysis showed that genetically determined RA was associated with higher risks of T2D [odds ratio (OR): 1.04, 95% confidence interval (CI) 1.02–1.05; p < 0.001] and CAD (OR: 1.02, 95% CI 1.00–1.03; p = 0.012), but not ischaemic stroke (OR: 1.00, 95% CI 0.99–1.02; p = 0.961). Sensitivity analyses with multiple MR methods confirmed these associations. MR-Egger regression showed no evidence of pleiotropy in the association between genetically determined RA and the risk of T2D, CAD, and ischaemic stroke. Leave-one-out sensitivity analysis showed that the association between genetically determined RA and the risk of T2D, CAD, and ischaemic stroke was not driven by any individual SNP. Genetically determined RA was associated with increased risks of T2D and CAD, suggesting that RA plays a crucial role in the pathogenesis of T2D and CAD.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".