| Title: | 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 |
| Journal: | European Heart Journal - Cardiovascular Imaging |
| Published: | 4 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41343376/ |
| DOI: | https://doi.org/10.1093/ehjci/jeaf337 |
| URL: | https://academic.oup.com/ehjcimaging/advance-article-pdf/doi/10.1093/ehjci/jeaf337/65757013/jeaf337.pdf |
Publication 16745
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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.</p>
METHODS AND RESULTS: HeartAge was developed using gradient-boosting regression in 3,760 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), 2,316 (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.</p>
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.</p>
18 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
1 Application
| Application ID | Title |
|---|---|
| 82189 | Whole-body MRI-based ageotype as a holistic proxy of biological ageing: a transformative approach to age-related diseases |
Enabling scientific discoveries that improve human health