A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-biobank and multi-ethnic study of atherosclerosis
Year: 2025
Type: article
Abstract: AIMS: Current models predicting cardiovascular biological age rely on radiomics or complex large feature sets including T1 and strain. We developed and validated a machine learning-based cardiovascular biological age estimate (HeartAge) using cardiovascular-magnetic-resonance (CMR) phenotypes and assessed the prognostic value of its deviation from chronological age (HeartAge-gap) for cardiovascular outcomes and mortality. METHODS AND RESULTS: HeartAge was developed using gradient-boosting regression in 3760 healthy UK-Biobank participants based on readily extractable CMR phenotypes. HeartAge-gap was defined as the difference between HeartAge and chronological age. The association of HeartAge-gap with prevalent cardiovascular conditions and composite cardiovascular outcome or all-cause mortality was tested in 31 784 UK-Biobank participants (64 ± 7 years; 16 640 females) and validated in 897 Multi-Ethnic Study of Atherosclerosis (MESA) participants (60 ± 10 years; 472 females) using logistic and Cox regression, respectively. Over a median 5.5-year follow-up (IQR: 4.7-7.1), 2316 (7.3%) and 363 (1.1%) participants experienced the composite cardiovascular outcome and all-cause mortality, respectively. Each one-year increase in HeartAge-gap, was associated with the composite cardiovascular outcome in females (HR: 1.022, 95% CI: 1.001-1.044, P = 0.048) and males (HR: 1.017, 95% CI: 1.002-1.033, P = 0.027) independently of chronological age and confounders including, body-mass-index, ischaemic heart disease, diabetes, and hypertension. In females only, increased HeartAge-gap predicted all-cause mortality (HR: 1.061, 95% CI: 1.007-1.118, P = 0.027), regardless of chronological age. In female MESA participants only, increased HeartAge-gap predicted the cardiovascular outcome (HR: 1.113, 95% CI: 1.025-1.210, P = 0.011) independently of chronological age and other confounders. CONCLUSION: A biologically older cardiovascular system was independently associated with adverse cardiovascular outcomes across both sexes. In females, advanced cardiovascular ageing also predicts all-cause mortality, irrespective of chronological age.
Authors: Pier-Giorgio Masci, Gianni Andreozzi, Esther Puyol-Anton, Ashkan Abdollahi, Richard Mospan, Bram Ruijsink, Marina Cecelja, Phillip J Chowienczyk, Aqeel T Mohamed, Alistair Young, Bharath Ambale, Amedeo Chiribiri, Geoff Tison, Claire J Steves, Joao A C Lima, Reza Razavi, Valentina Lorenzoni, Andrew King
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,203
Awards: G1261793039, MESA, G1276754516, G1294553593, G1539384734, G1640378483, G1803853571, G1983464145, G2095942735, G2144938473, G22458031, MESA, G2580996367, G2726417417, MESA, G2837638605, G290884426, G291913881, SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--EBCT READING, G3570589137, G3595232572, G370977179, MESA, TITLE: MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA), G4309390892, G4563812999, G4590187187, OPTION 3. 4/1/2014 - 3/31/2015. MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA) - READING CENTER, NHLBI, MESA, G4986157935, G5075046117, G5108002584, G514410172, SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-ULTRASOUND, G5653954166, Institute for Clinical and Translational Research, MESA, G66341962, G6856766826, G7166352866, MESA, G78770644, Clinical and Translational Science Award, G8145863542, G8761005068, G94668252, G991334795
OpenAlex ID: W4417014801