Correlation of DNA methylation levels in blood and saliva DNA in young girls of the LEGACY Girls study
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Bibliographic record
Abstract
Many epidemiologic studies of environmental exposures and disease susceptibility measure DNA methylation in white blood cells (WBC). Some studies are also starting to use saliva DNA as it is usually more readily available in large epidemiologic studies. However, little is known about the correlation of methylation between WBC and saliva DNA. We examined DNA methylation in three repetitive elements, Sat2, Alu, and LINE-1, and in four CpG sites, including AHRR (cg23576855, cg05575921), cg05951221 at 2q37.1, and cg11924019 at CYP1A1, in 57 girls aged 6-15 years with blood and saliva collected on the same day. We measured all DNA methylation markers by bisulfite-pyrosequencing, except for Sat2 and Alu, which were measured by the MethyLight assay. Methylation levels measured in saliva DNA were lower than those in WBC DNA, with differences ranging from 2.8% for Alu to 14.1% for cg05575921. Methylation levels for the three repetitive elements measured in saliva DNA were all positively correlated with those in WBC DNA. However, there was a wide range in the Spearman correlations, with the smallest correlation found for Alu (0.24) and the strongest correlation found for LINE-1 (0.73). Spearman correlations for cg05575921, cg05951221, and cg11924019 were 0.33, 0.42, and 0.79, respectively. If these findings are replicated in larger studies, they suggest that, for selected methylation markers (e.g., LINE-1), methylation levels may be highly correlated between blood and saliva, while for others methylation markers, the levels may be more tissue specific. Thus, in studies that differ by DNA source, each interrogated site should be separately examined in order to evaluate the correlation in DNA methylation levels across DNA sources.
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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) | 0.000 | 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 it