Work

Clustering of Cardiovascular Risk Factors in Midlife Forms Trajectories That Affect Heart Aging Biomarker and Incidence of Cardiovascular Disease

Year: 2026

Type: article

Abstract: Objective: To (1) identify multivariable longitudinal midlife patterns of systolic and diastolic blood pressure, body mass index, and non-high density lipoprotein cholesterol and (2) assess whether electrocardiogram derived heart age acceleration (δ-age) mediates their associations with incident myocardial infarction (MI), stroke, and all-cause mortality. Patients and Methods: -scores were modeled with quadratic B-splines and grouped using K-means clustering to identify joint multivariable life-course risk profiles. δ-Age was derived from 12-lead electrocardiograms using a validated neural network. Natural-effects models decomposed hazard ratios between clusters and clinical events (follow-up to 2021) into direct and δ-age mediated components. Results: Four distinct clusters were identified: stable low-risk (cluster 1, n=1604, 30.6%), dyslipidemia (cluster 2, n=1340, 25.6%), hypertension (cluster 3, n=1476, 28.1%), and high-risk trajectory (cluster 4, n=824, 15.7%). Each 1-SD increment in δ-age was associated with 27% to 30% of excess MI, stroke, and death, independent of age and sex. Clusters 3 and 4 carried the greatest excess risk of clinical events, whereas mediation by δ-age was modest (4%-8% of total effect for MI and stroke) and not statistically significant. Conclusion: Joint multivariable life-course clustering of conventional risk factors identified clinically distinct long-term cardiovascular risk phenotypes. Although δ-age adds independent prognostic information, it explained little of the excess risk associated with chronic hypertension, dyslipidemia, or obesity, indicating it functions primarily as a parallel marker and not a causal mediator.

Source: Mayo Clinic Proceedings Digital Health

DOI: 10.1016/j.mcpdig.2026.100425