DNAmScore identified residual biological risk beyond PREVENT-like clinical predictors, with strong independent mortality associations and modest, consistent improvements in cross-fitted prediction performance, which support development and external validation of CVD-specific DNAm biomarkers.
Abstract
Background: Contemporary cardiovascular disease (CVD) risk equations may not fully capture cumulative biological aging or long-term exposure burden. DNA methylation (DNAm) biomarkers may capture aging- and exposure-related biology, but their incremental prognostic value beyond clinical risk-factor models like PREVENT remains uncertain. To our knowledge, no prior study has benchmarked DNAm-based biomarkers with PREVENT. Methods: In a population-based cohort study, we analyzed NHANES 1999-2002 participants with DNAm biomarkers and mortality follow-up. We derived a DNAmScore from candidate DNAm biomarkers using elastic-net Cox regression with repeated nested cross-validation. A PREVENT-like clinical model was defined as a Cox model fit in NHANES using PREVENT predictors. Weighted Cox models estimated the association between DNAmScore and mortality after adjustment for PREVENT-like clinical predictors. We then compared the PREVENT-like clinical model, DNAmScore alone, and a combined model (PREVENT-like clinical predictors plus DNAmScore) using cross-fitted C-index, time-dependent AUC, calibration, and Brier score. Results: Our cohort included 2,282 participants; 597 and 937 deaths occurred by 10 and 15 years, respectively. After adjustment for PREVENT-like clinical predictors, the cross-fitted DNAmScore was strongly associated with all-cause mortality (HR per 1-SD increase, 2.43; 95% CI, 1.97?2.99). At 10 years, AUCs were 0.791 for the PREVENT-like model, 0.791 for DNAmScore, and 0.803 for the combined model. At 15 years, corresponding AUCs were 0.825, 0.822, and 0.835. Compared with the PREVENT-like model, the combined model improved AUC by 0.013 (95% CI, 0.006?0.020) at 10 years and 0.010 (95% CI, 0.004?0.015) at 15 years. The combined model had lower Brier scores at all three horizons with similar calibration. DNAmScore remained associated with CVD mortality after clinical adjustment. Conclusions: DNAmScore identified residual biological risk beyond PREVENT-like clinical predictors, with strong independent mortality associations and modest, consistent improvements in cross-fitted prediction performance. These findings support development and external validation of CVD-specific DNAm biomarkers.
Background: DNA methylation (DNAm) signatures capture cumulative lifestyle exposures and biological aging. This prospective study evaluated whether DNAm-based scores and epigenetic aging clocks are associated with clinical outcomes and mortality in a multinational cohort of patients with heart failure (HF). Methods: We studied 2,594 patients with HF from 40 countries in the Global Congestive Heart Failure (G-CHF) registry with whole-blood DNAm data. Fifteen published DNAm-based scores and epigenetic aging clocks reflecting lifestyle, environmental and physiological exposures, inflammation, frailty, mortality risk, and biological aging were derived. Associations with HF hospitalization, cardiovascular death, and all-cause death were assessed using multivariable Cox regression adjusted for age, sex, ancestry, the MAGGIC risk score, and NT-proBNP. Incremental prognostic value was compared to MAGGIC score and NT-proBNP. Extreme DNAm profiles were defined as scores or clocks exceeding {+/-}1.5 standard deviations (s.d.) from the population mean. Results: Mean age was 62.7{+/-}14.0 years, 66.2% were male, and mean left ventricular ejection fraction was 40.1{+/-}14.1%. During a median follow-up of 3.0 years, 338 patients were hospitalized for HF, 349 died from cardiovascular causes, and 565 died from any cause. Higher epigenetic age and DNAm scores for CRP, frailty, and mortality were associated with increased risk, whereas higher diet-related DNAm scores were inversely associated. For all-cause death, adjusted hazard ratios per 1-s.d. were 1.36 (95% CI, 1.24-1.50) for GrimAge, 1.27 (95% CI, 1.17-1.38) for the DNAm score for CRP, 1.44 (95% CI, 1.28-1.63) for the DNAm score for frailty, and 1.48 (95% CI, 1.32-1.65) for the DNAm score for mortality, compared with 0.81 (95% CI, 0.75-0.88) and 0.86 (95% CI, 0.79-0.94) for the DNAm scores for Alternative Healthy Eating Index and Mediterranean Diet Score. These patterns were directionally consistent for cardiovascular death and weaker for HF hospitalization and were more pronounced among patients with lower clinical risk (MAGGIC<17, Pinteraction<0.05), particularly for all-cause death. Patients with 4-5 extreme-high DNAm scores or clocks had more than twice the risk of death (HR, 2.27; 95% CI, 1.65-3.13). Conclusions: DNAm-based scores and epigenetic aging clocks reflect multiple dimensions of biological vulnerability in HF and are associated with clinical outcomes and mortality beyond clinical risk factors.
P. Meyre, M. Chong, E. Shemesh et al.· medRxiv· 0 citations
DNA methylation-based signatures were associated with incident ASCVD and modestly improved risk prediction beyond that of traditional risk factors, and an agnostic probe reliability-based approach was developed.
A. Barad, D. Khodasevich, P. F. Kho et al.· medRxiv· 0 citations
Although associations with fibrosis-related outcomes varied according to fibrosis definitions, DNAm aging algorithms may provide additional biological information for mortality risk stratification among individuals with CLD-related phenotypes.
Background: Epigenetic clocks derived from DNA methylation estimate biological aging and have been associated with cardiometabolic death. We evaluated whether substituting epigenetic age for chronologic age within PREVENT altered associations with all-cause and cardiovascular mortality or improved discrimination. Methods: We analyzed National Health and Nutrition Examination Survey 1999-2002 data linked to National Death Index follow-up through December 31, 2019. Adults aged 50-79 years without baseline cardiovascular disease and with DNA methylation data were included. PREVENT is a primary-prevention framework incorporating demographic, cardiometabolic, renal, and treatment factors. Exposures were PREVENT estimates calculated using chronologic age or 8 epigenetic ages substituted for chronologic age, with other inputs unchanged. Survey weighted Cox models estimated associations with all-cause and cardiovascular mortality per 5-percentage-point higher predicted risk. Weighted Harrell C statistics assessed discrimination; 95% CIs were obtained by bootstrap resampling. Results: The cohort included 1,516 participants (weighted mean age, 60.3 years; SD, 8.0) with a mean follow-up of 17.35 years; 507 participants died, including 140 cardiovascular deaths. Each 5-percentage-point increase in chronologic PREVENT risk was associated with all-cause mortality (HR, 1.57; 95% CI, 1.45-1.70) and cardiovascular mortality (HR, 1.66; 95% CI, 1.501.84). Biologic variants showed similar associations for all-cause mortality (HR range, 1.391.57) and cardiovascular mortality (HR range, 1.47-1.67). Chronologic PREVENT showed higher discrimination for all-cause mortality (C, 0.74; 95% CI, 0.72-0.77) than biologic variants (C range, 0.66-0.73) and for cardiovascular mortality (C, 0.78; 95% CI, 0.73-0.84) than biologic variants (C range, 0.71-0.77). Conclusions: Biologic PREVENT variants were associated with mortality but did not improve discrimination compared with chronologic PREVENT, suggesting biological aging metrics may complement rather than replace chronological age in cardiovascular risk prediction.
Ramzi Ibrahim, B. Tamarappoo, Kwan S. Lee et al.· Circulation. Population heal...· 0 citations
Higher urinary DETP was associated with greater heart disease mortality in middle-aged and older adults, and in vitro experiments provided hypothesis-generating support—most directly for inflammatory signaling—rather than confirmation of the epidemiological pathway.
Yun-Li Song, Li-Hui Liang, Jing Hao et al.· Frontiers in Public Health· 0 citations
Summary Background Guideline-recommended clinical risk scores such as AusCVDRisk underestimate cardiovascular disease (CVD) risk in a substantial proportion of individuals who later experience events, with up to 65% initially classified as low or intermediate risk. This limitation is most consequential in the intermediate-risk group, where treatment decisions are uncertain and additional risk refinement could alter management. Circulating lipid species and inherited genetic variation capture complementary molecular aspects of atherosclerotic risk that are not fully reflected by conventional clinical variables, but are not routinely incorporated into primary-care risk assessment. We investigated whether selective integration of lipidomic and genomic risk signals into AusCVDRisk improves 5-year CVD prediction and reclassification, with a focus on individuals at intermediate clinical risk. Methods A lipidomic score comprising 689 lipid species measured by liquid chromatography–tandem mass spectrometry was derived using regularised Cox regression in 8082 participants from the Australian Diabetes, Obesity and Lifestyle Study (1999–2000). A genome-wide coronary artery disease polygenic score (PGS002048; 762,124 variants) was optimised in 3328 participants from the Busselton Health Study (1994–95). Each score was adjusted for AusCVDRisk predictors to isolate independent effects and incorporated into Cox models retaining the AusCVDRisk linear predictor as a fixed offset, generating lipidomic-enhanced (L.CVDRisk), genomic-enhanced (G.CVDRisk), and combined (LG.CVDRisk) scores. Internal and external validation was performed across five Australian cohorts totalling 13,521 adults without baseline CVD. Discrimination (Harrell’s concordance index; C-statistic), calibration, categorical net reclassification improvement (NRI), and decision-curve analyses were assessed. Findings LG.CVDRisk showed modest gains in discrimination compared with AusCVDRisk (pooled ΔC among intermediate-risk individuals 0.071, 95% CI 0.033–0.109; overall 0.012, 95% CI 0.000–0.024). Risk classification improved substantially (pooled NRI in the intermediate-risk group 0.305, 95% CI 0.212–0.397; overall 0.080, 95% CI 0.031–0.129), with net event and non-event reclassification of 38.2% (95% CI 29.3–47.0%) and −6.8% (95% CI −9.3 to −4.2%) among intermediate-risk individuals. Decision-curve analysis showed the greatest net benefit when molecular profiling was selectively applied to individuals with intermediate AusCVDRisk (5–<10%). In a coronary imaging cohort, LG.CVDRisk reclassified 17 (41%) of 41 intermediate-risk individuals with extensive coronary calcification into the high-risk category. Interpretation Selective augmentation of an established clinical risk algorithm with lipidomic and genomic information improves cardiovascular risk stratification among individuals at intermediate baseline risk. This approach supports targeted molecular testing within existing primary-care pathways to inform personalised prevention. Funding National Heart Foundation, Australia, Australian Government Medical Research Future Fund, National Health and Medical Research Council, Victorian Government.
Aleksandar Dakic, Jing-Qin Wu, Tingting Wang et al.· EClinicalMedicine· 0 citations
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