<i>PRKCZ</i>methylation is associated with sunlight exposure in a North American but not a Mediterranean population
Bibliographic record
Abstract
Sunlight exposure has been shown to alter DNA methylation patterns across several human cell-types, including T-lymphocytes. Since epigenetic changes establish gene expression profiles, changes in DNA methylation induced by sunlight exposure warrant investigation. The purpose of this study was to assess the effects of sunlight exposure on CD4+ T-cell methylation patterns on an epigenome-wide scale in a North American population of European origin (n=991). In addition, we investigated the genetic contribution to epigenetic variation (methylQTL). We used linear regression to test the associations between methylation scores at 461,281 cytosine-phosphate-guanine (CpG) sites and sunlight exposure, followed by a genome-wide association analysis (methylQTL) to test for associations between methylation at the top CpG locus and common genetic variants, assuming an additive genetic model. We observed an epigenome-wide significant association between sunlight exposure and methylation status at cg26930596 (p=9.2×10(-8)), a CpG site located in protein kinase C zeta (PRKCZ), a gene previously shown to be entrained by light. MethylQTL analysis resulted in significant associations between cg26930596 and two intergenic single nucleotide polymorphisms on chromosome 3, rs4574216 (p=1.5×10(-10)) and rs4405858 (p=1.9×10(-9)). These common genetic variants reside downstream of WWTR1, a transcriptional co-activator of PRKCZ. Associations observed in the North American population, however, did not replicate in an independent Mediterranean cohort. Our preliminary results support the role of sunlight exposure in epigenetic processes, and lay the groundwork for future studies of the molecular link between sunlight and physiologic processes such as tumorigenesis and metabolism.
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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 | 0.001 |
| 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".