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Blood-based epigenetic instability linked to human aging and disease [MDS_CML]

ABSTRACT: The abundance, dynamics, and context-dependent heterogeneity of DNA methylation, where a pattern considered abnormal in one cell type may be normal in another, complicate the identification of early methylation changes that drive or signal disease development. This complexity can obscure early markers of increased disease risk, making it challenging to detect and intervene in disease processes at their inception. Here, we report 31,744 CpG sites exhibiting highly consistent methylation profiles in the blood of young, healthy individuals. We assess alterations at these epigenetically stable loci in 8,886 individuals across 29 diverse cohorts, including those with hematological cancers (n = 3,159), cardiovascular complications (n = 2,788), and healthy controls (n = 2,939). Our findings reveal methylation pattern disruption in myeloid and lymphoid malignancies, correlating with clonal burden dynamics and mutation frequency throughout leukemia treatment. In non-cancer cohorts, we observe that methylation levels at epigenetically stable loci become increasingly variable with age, a shift linked to higher cardiovascular disease risk and lower survival rates. This study highlights DNA methylation instability as a blood-based biomarker for both hematological cancer and cardiovascular disease and uncovers a mechanistic link between methylation dynamics and the expansion of maladaptive hematopoietic clones.

ORGANISM(S): Homo sapiens

PROVIDER: GSE315451 | GEO | 2026/01/06

REPOSITORIES: GEO

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Project description:Background: Identifying individuals at heightened cardiovascular risk is a priority for reducing the global burden of cardiovascular disease. Aspirin is widely used to prevent cardiovascular events, though with variable results. Therefore, we hypothesized that aspirin exposure would reveal novel biological pathways relevant to the development of cardiovascular events. Methods: We administered aspirin, followed by peripheral blood RNA microarray profiling, in a discovery cohort of healthy volunteers (n = 50, HV1), followed by two validation cohorts of healthy volunteers (n = 53, HV2) or outpatient cardiology (OPC, n = 25) patients, in conjunction with platelet function testing with the platelet functions score (PFS, HV1 and HV2) or the VerifyNow Asprin (VN, OPC) test. Sets of coexpressed genes, or “Factors” were identified via Bayesian sparse factor analysis and associated with platelet function in HV1 and validated in HV2 and OPC. Validated factors were associated with death/MI in observational (n = 191) and case:control (n = 447) patient cohorts with available RNA data collected at the time of cardiac catheterization. Results: Factor analysis yielded 20 Factors, of which one, Factor 14, contained 60 genes and was associated with PFS in HV1 (r = -0.31, p-value = 0.03). Factor 14 was associated with platelet function with the same strength and direction in HV2 (r = -0.34, p-value = 0.02) and OPC (one-sided p-value for aspirin resistant vs. aspirin sensitive = 0.046), thus validating the association. Factor 14 was associated with death/MI in the two patient cohorts, odds ratio (OR) = 1.2, 95% CI [1.02-1.4], p-value = 0.01 and hazard ratio = 1.5, [1.2-1.9], p = 0.001, respectively, independent of known cardiovascular risk factors (combined OR = 1.2, CI = [1.02, 1.4], p = 0.03). Factor 14 and the expression of the Factor 14 transcript most highly correlative of PFS, ITGA2B, improved reclassification compared to traditional risk factors (category-free net reclassification index = 31% and 37%, p ≤ 0.0002 for both). Conclusions: By challenging humans subjects with aspirin, a medication used for cardiovascular risk reduction, we elucidated genes and pathways that may underlie platelet function and mechanisms responsible for cardiovascular death/MI. This accession represents the OPC cohort microarray data 26 subjects selected for microarray analysis were divided into three groups: aspirin resistant (AR, n=8, >550 ARU), high normal (HN, n=9, ARU 500-549) and aspirin sensitive (AS, n=9, ARU<500)

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Blood-based epigenetic instability linked to human aging and disease [MDS_CML]

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