Epigenome-wide DNA methylation association study of CHIP provides insight into perturbed gene regulation
Bibliographic record
Abstract
With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed CHIP. How these mutations result in increased risk for numerous age-related diseases remains poorly understood. We conduct a multiracial meta-analysis of EWAS of CHIP in the Framingham Heart Study, Jackson Heart Study, Cardiovascular Health Study, and Atherosclerosis Risk in Communities cohorts (N = 8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. We functionally validate the EWAS findings using human hematopoietic stem cell models of CHIP. We then use expression quantitative trait methylation analysis to identify transcriptomic changes associated with CHIP-associated CpGs. Causal inference analyses reveal 261 CHIP-associated CpGs associated with cardiovascular traits and all-cause mortality (FDR adjusted p-value < 0.05). Taken together, our study reports the epigenetic changes impacted by CHIP and their associations with age-related disease outcomes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".