Clustering of Cardiovascular Risk Factors in Midlife Forms Trajectories That Affect Heart Aging Biomarker and Incidence of Cardiovascular Disease
6 affiliations
- 1Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- 2Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, Campus Ahus, University of Oslo, Norway
- 3University Hospital of North Norway, Tromsø, Norway
- 4Department of Cardiovascular Medicine and Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN
- 5Department of Noncommunicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
- 6Department of Psychology, University of Oslo, Norway
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: We analyzed 5244 participants from the observational cohort study, the Tromsø Study, who were free of MI or stroke at baseline (Tromsø7, 2015-2016) and attended at least 3 surveys (Tromsø3-7, 1986-2016). Age-standardized risk factor z -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.
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BibTeX
@article{aryapanthalanickalvijayakumar2026clustering,
title = {{Clustering of Cardiovascular Risk Factors in Midlife Forms Trajectories That Affect Heart Aging Biomarker and Incidence of Cardiovascular Disease}},
author = {Arya Panthalanickal Vijayakumar, MS and Tom Wilsgaard, PhD and Henrik Schirmer, MD, PhD and Haakon Lindekleiv, MD, PhD and Zachi I. Attia, PhD and Francisco Lopez-Jimenez, MD, MSc, MBA and David A. Leon, PhD and Olena Iakunchykova, PhD},
journal = {Mayo Clinic Proceedings: Digital Health},
year = {2026},
month = oct,
doi = {10.1016/j.mcpdig.2026.100425},
url = {https://doi.org/10.1016/j.mcpdig.2026.100425},
note = {CC BY},
}
RIS
TY - JOUR
TI - Clustering of Cardiovascular Risk Factors in Midlife Forms Trajectories That Affect Heart Aging Biomarker and Incidence of Cardiovascular Disease
AU - Arya Panthalanickal Vijayakumar, MS
AU - Tom Wilsgaard, PhD
AU - Henrik Schirmer, MD, PhD
AU - Haakon Lindekleiv, MD, PhD
AU - Zachi I. Attia, PhD
AU - Francisco Lopez-Jimenez, MD, MSc, MBA
AU - David A. Leon, PhD
AU - Olena Iakunchykova, PhD
PY - 2026
DA - 2026/10/05
JO - Mayo Clinic Proceedings: Digital Health
DO - 10.1016/j.mcpdig.2026.100425
UR - https://doi.org/10.1016/j.mcpdig.2026.100425
AB - 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: We analyzed 5244 participants from the observational cohort study, the Tromsø Study, who were free of MI or stroke at baseline (Tromsø7, 2015-2016) and attended at least 3 surveys (Tromsø3-7, 1986-2016). Age-standardized risk factor z -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.
SN - 2949-7612
ER -