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How to measure and model cardiovascular aging

Lookup NU author(s): Dr Luke Spray, Professor Gavin RichardsonORCiD, Laura Booth, Professor Konstantinos StellosORCiD, Dr Simon Tual-ChalotORCiD, Professor Ioakim SpyridopoulosORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Most acquired cardiovascular diseases are more common in older people, and the biological mechanisms and manifestations of aging provide insight into cardiovascular pathophysiology. Measuring aging within the cardiovascular system may help to better understand risk profiles for specific individuals and direct targeted preventative therapy. In this review, we explore telomere attrition, cellular senescence, epigenetic modifications, and mitochondrial dysfunction as key molecular mechanisms of aging. These phenomena are associated with cardiovascular disease through endothelial dysfunction and systemic inflammation, which are measurable in clinical practice with a variety of clinical, laboratory, and imaging techniques. Finally, we discuss that the next tools for modelling cardiovascular aging must be capable of incorporating a vast amount of diverse data from a given patient, pointing to recent developments in artificial intelligence and machine learning.


Publication metadata

Author(s): Spray L, Richardson GD, Booth LK, Haendeler J, Altschmied J, Bromage DI, Wallis SB, Stellos K, Tual-Chalot S, Spyridopoulos I

Publication type: Review

Publication status: Published

Journal: Cardiovascular Research

Year: 2025

Volume: 121

Issue: 10

Pages: 1489-1508

Online publication date: 28/08/2025

Acceptance date: 14/06/2025

ISSN (print): 0008-6363

ISSN (electronic): 1755-3245

URL: https://doi.org/10.1093/cvr/cvaf138

DOI: 10.1093/cvr/cvaf138


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