Oral Abstract
Pier-Giorgio Masci, MD, PhD
Consultant Cardiologist
School of Biomedical Engineering & Imaging Sciences
Faculty of Life Sciences & Medicine | King’s College London
, United Kingdom
Pier-Giorgio Masci, MD, PhD
Consultant Cardiologist
School of Biomedical Engineering & Imaging Sciences
Faculty of Life Sciences & Medicine | King’s College London
, United Kingdom
Gianni Andreozzi, MSc
Research Assistant
Scuola Superiore Sant’Anna, Italy
Esther Puyol-antòn, PhD
King's College London, United Kingdom
Marina Cecilja, PhD
Research Fellow
King's College London, United Kingdom
Phil Chowienczyk, MD, PhD
Professor of Clinical Cardiovascular Pharmacology
King's College London, United Kingdom
Aqeel Mohamed, N/A
Medical Student
King's College London, United Kingdom
Alistair A. Young, PhD
Professor
King's College London, United Kingdom
Amedeo Chiribiri, MD PhD FHEA FSCMR
Professor of Cardiovascular Imaging; Consultant Cardiologist
King's College London, United Kingdom
Claire J. Steves, MD, PhD
Professor of Ageing and Heath
King's College London, United Kingdom
Reza Razavi, MD
Professor of Paediatric Cardiovascular Science
King's College London, United Kingdom
Valentina Lorenzoni, PhD
Assistant Professor
Scuola Superiore Sant’Anna, Italy
Andrew P. King, PhD
Senior Reader
King's College London, United Kingdom
Background Addressing cardiovascular aging emerges as an innovative approach to mitigate cardiovascular diseases. However, its integration into clinical practice and research is impeded by the absence of reliable proxies for the biological age of the cardiovascular system, as chronological age is a notoriously poor proxy for the physiological processes underpinning cardiovascular aging.
Methods:
Objectives We aim to develop and validate a novel estimate of cardiovascular biological age (HeartAge) and its deviation from chronological age (HeartAge-gap) by leveraging a supervised machine-learning model informed by readily extractable cardiovascular magnetic-resonance-imaging (MRI) phenotypes.
Methods HeartAge and HeartAge-gap were estimated in 31,784 UK Biobank participants (16,640 females, 64±7 years). A positive HeartAge-gap indicates an older cardiovascular system, conversely a negative HeartAge-gap indicates a younger one. Logistic regression models assessed the association of HeartAge-gap with prevalent age-dependent cardiovascular conditions. Cox regression proportional hazard-ratio models evaluated the association of HeartAge-gap with the composite cardiovascular outcome (cardiovascular death, heart failure, ischemic heart disease, ischemic stroke, and cardiac rhythm disorders) and all-cause mortality during follow-up.
Results:
Results Cross-sectional analysis revealed that HeartAge-gap was associated with prevalent age-dependent conditions, including hypertension, diabetes, and ischemic heart disease in both females and males after correction for chronological age (P< 0.05 for all). Over a median follow-up of nearly 6 years, an increased HeartAge-gap predicted the composite cardiovascular outcome in females (HR:1.022, 95%CI:1.000-1.044, P=0.048) and males (HR:1.017, 95%CI:1.002-1.033, P=0.027) independently of chronological age and other major confounders at baseline including, body-mass-index, ischemic heart disease, diabetes, and hypertension. In females, an increased HeartAge-gap also predicted all-cause mortality (HR:1.061, 95%CI:1.007-1.118, P=0.027) independently of chronological age. Conclusion Our framework provides bespoke measures of cardiovascular biological aging. An older cardiovascular system, as indicated by a higher HeartAge-gap, predicted adverse cardiovascular outcomes independently of chronological age and other major confounders. In females, advanced cardiovascular aging was also independently associated with all-cause mortality.
Conclusion:
The composite cardiovascular outcome is an aggregate of cardiovascular death, ischaemic heart disease, ischaemic stroke, heart failure and cardiac rhythm abnormalities. C-MRI: Cardiovascular Magnetic Resonance Imaging; RA: Right atrium; LA: Left atrium; Asc Ao: Ascending aorta; RV: Right ventricle; LV: Left ventricle.