The association between clock gene polymorphisms and type 2 diabetes: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Misalignment of the endogenous circadian system may contribute to the risk of type 2 diabetes. This systematic review and meta-analysis examined the association between clock gene polymorphisms and glycemic parameters and type 2 diabetes. METHODS: Embase, Medline, and Web of Science databases were searched from inception to August 20, 2024. Empirical studies examining the association between core clock gene polymorphisms and type 2 diabetes and glycemic parameters, and studies examining non-core clock genes with information on environmental factors were included. A multi-level meta-analytical approach was used, and a weighted odds ratio was reported (PROSPERO, CRD42022337706). RESULTS: In total, 37 studies comprising 535,063 participants were included. CRY2 was associated with higher fasting blood glucose (OR: 1.07, 95 % CI: 1.03-1.11) and impaired glucose tolerance (OR: 1.02, CI: 1.00-1.04). Polymorphisms in MTNR1B were associated with a greater risk of type 2 diabetes. CLOCK was associated with lower risk of type 2 diabetes (OR: 0.94, CI: 0.89-1.00), and PER3 was associated with lower fasting insulin (OR: 0.94, CI: 0.91-0.97) and lower risk of insulin resistance (OR: 0.92, CI: 0.88-0.95). These associations reflect pooled variant-level effects within genes, and the effects of certain variants were modified by diet, alcohol consumption, physical activity, sleep, and length of daylight. CONCLUSIONS: Specific polymorphisms in circadian genes, including CRY2, MTNR1B, CLOCK, and PER3, were associated with glycemic parameters and type 2 diabetes risk. These associations may be influenced by lifestyle and environmental factors, and interventions targeting circadian alignment could potentially modify diabetes risk, although further research is needed.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".