DNA methylation is differentially associated with environmental cadmium exposure based on sex and smoking status
Bibliographic record
Abstract
The adverse health effects of cadmium (Cd) are well known in human populations; however, much of what is known about biological mechanisms of Cd comes from in vitro and animal studies. The adverse health outcomes due to high levels of Cd exposure in the population of Mae Sot, Thailand have been extensively characterized. Here, for the first time, this population is being studied in an epigenetic context. The objective of this study was to characterize the association between DNA methylation markers and Cd exposure, taking into account sex and smoking differences, in an adult population at an increased risk of experiencing adverse health outcomes from high body burden of Cd. One hundred and sixty-nine residents from known exposure areas of Mae Sot, Thailand and one hundred residents from non-exposed areas nearby were surveyed in 2012. Urine and blood samples were collected for measurement of urinary Cd (UCd) and DNA methylation of Cd-related markers (DNMT3B, MGMT, LINE-1, MT2A). UCd levels were 7 times higher in the exposed compared to the unexposed populations (exposed median: 7.4 μg/L, unexposed median: 1.0 μg/L, p < 0.001). MGMT hypomethylation was associated with increasing levels of UCd in the total population. Sex-specific associations included MT2A and DNMT3B hypomethylation in women and LINE-1 hypermethylation in men with increasing UCd. Upon subanalysis, these associations separated by smoking status. In summary, environmental Cd exposure is associated with gene-specific DNA methylation in a sex and smoking dependent manner.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".