DNA methylation of circadian genes and markers of cardiometabolic risk in female hospital workers: An exploratory study
Bibliographic record
Abstract
Night shift work has been linked to increased risk of cardiovascular disease (CVD); however, the underlying mechanisms remain unclear. A compelling yet understudied mechanism involves differential DNA methylation of circadian genes. To investigate the relevance of this mechanism, we conducted an exploratory cross-sectional study of 74 female hospital personnel (38 day workers, 36 night shift workers). Sociodemographic, lifestyle, and health characteristics as well as shift work status and history were determined through self-report. Fasting blood samples were collected to measure markers of cardiometabolic risk and DNA was extracted to measure DNA methylation of 1150 cytosine-guanine (CpG) sites across 22 circadian genes. Associations between methylation levels at individual CpG sites (β-values) and markers of cardiometabolic risk were analyzed while considering effect modification by shift work status. The false discovery rate was applied to account for multiple comparisons (q ≤ 0.20). Two CpG sites [cg06758649 (CRY1) and cg06899802 (CSNK1A1)] were differentially associated with waist circumference and body mass index by shift work status, and eight CpG sites [cg26103512 (CSNK1D), cg03941313 (CSNK1E), cg18217763 (CSNK1E), cg16682686 (DEC1), cg12061096 (RORA), cg10133825 (RORA), cg19652148 (RORA), and cg22904654 (RORA)] were differentially associated with LDL cholesterol concentration by shift work status (all q ≤ 0.20). Our findings suggest that the relationship between DNA methylation of circadian genes and cardiometabolic risk differs by day and night shift worker status, which may contribute to mechanisms of increased risk of CVD observed among night shift workers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".