Development and validation of an epigenetic signature of allostatic load
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Bibliographic record
Abstract
The allostatic load (AL) concept measures physiological dysregulation in response to internal and external stressors that accumulate across the life course. AL has been consistently linked to chronic disease risk across studies. However, there is considerable variation in its operationalization. In the present study, DNA methylation (DNAm) data (using the Illumina Infinium MethylationEPIC BeadChip array) from the Swiss Kidney Project on Genes in Hypertension (SKIPOGH) cohort, a Swiss-based family cohort study, were used in a discovery epigenome-wide association study to identify cytosine-guanine nucleotide sites associated with phenotypic measures of AL. Elastic net linear regression models were used to estimate an epigenetic signature of AL (methAL), including an Illumina HumanMethylation450K (HM450K) assay-compatible signature (methALT). The methALT signature was validated in the 1936 Lothian Birth Cohort (LBC1936), population-based prospective cohort study. We found that the methAL signature was positively associated with the clinical phenotype of AL in both the SKIPOGH (R2 = 0.59) and LBC1936 (R2 = 0.16) cohorts. In the validation cohort, a one standard deviation increase in methALT signature was associated with 25% higher odds of reported history of cardiovascular disease (CVD) (odd ratio [OR] = 1.25, 95% confidence interval [CI] = 1.05-1.50), and a nearly two-fold increase in all-cause mortality rate at the beginning of follow-up (hazard ratio = 1.68, 95% CI = 1.33-2.13) when adjusting for all potential confounders. In conclusion, the epigenetic signature for AL not only correlated well with phenotype-based AL scores but also exhibited a stronger association with the history of CVD and all-cause mortality compared with AL scores. The methAL signature could help assuage issues of comparison across studies.
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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 | 0.000 | 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