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Ganau A, Orrù M, Floris M, Saba PS, Loi F, Sanna GD, Marongiu M, Balaci L, Curreli N, Ferreli LAP, Loi F, Masala M, Parodi G, Delitala AP, Schlessinger D, Lakatta E, Fiorillo E, Cucca F. Echocardiographic heart ageing patterns predict cardiovascular and non-cardiovascular events and reflect biological age: the SardiNIA study. Eur J Prev Cardiol 2024; 31:677-685. [PMID: 37527539 PMCID: PMC11025036 DOI: 10.1093/eurjpc/zwad254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/04/2023] [Accepted: 07/28/2023] [Indexed: 08/03/2023]
Abstract
AIMS Age is a crucial risk factor for cardiovascular (CV) and non-CV diseases. As people age at different rates, the concept of biological age has been introduced as a personalized measure of functional deterioration. Associations of age with echocardiographic quantitative traits were analysed to assess different heart ageing rates and their ability to predict outcomes and reflect biological age. METHODS AND RESULTS Associations of age with left ventricular mass, geometry, diastolic function, left atrial volume, and aortic root size were measured in 2614 healthy subjects. Based on the 95% two-sided tolerance intervals of each correlation, three discrete ageing trajectories were identified and categorized as 'slow', 'normal', and 'accelerated' heart ageing patterns. The primary endpoint included fatal and non-fatal CV events, and the secondary endpoint was a composite of CV and non-CV events and all-cause death. The phenotypic age of the heart (HeartPhAge) was estimated as a proxy of biological age. The slow ageing pattern was found in 8.7% of healthy participants, the normal pattern in 76.9%, and the accelerated pattern in 14.4%. Kaplan-Meier curves of the heart ageing patterns diverged significantly (P = 0.0001) for both primary and secondary endpoints, with the event rate being lowest in the slow, intermediate in the normal, and highest in the accelerated pattern. In the Cox proportional hazards model, heart ageing patterns predicted both primary (P = 0.01) and secondary (P = 0.03 to <0.0001) endpoints, independent of chronological age and risk factors. Compared with chronological age, HeartPhAge was 9 years younger in slow, 4 years older in accelerated (both P < 0.0001), and overlapping in normal ageing patterns. CONCLUSION Standard Doppler echocardiography detects slow, normal, and accelerated heart ageing patterns. They predict CV and non-CV events, reflect biological age, and provide a new tool to calibrate prevention timing and intensity.
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Affiliation(s)
- Antonello Ganau
- Department of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy
| | - Marco Orrù
- Armando Businco Hospital, Azienda Ospedaliera Brotzu, Cagliari 09047, Italy
| | - Matteo Floris
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Pier Sergio Saba
- Cardiac Thoracic Vascular Department, Azienda Ospedaliero Universitaria, Sassari 07100, Italy
| | - Federica Loi
- Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, Padova 35128, Italy
| | - Giuseppe D Sanna
- Cardiac Thoracic Vascular Department, Azienda Ospedaliero Universitaria, Sassari 07100, Italy
| | - Michele Marongiu
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Lenuta Balaci
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Niccolò Curreli
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Liana A P Ferreli
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Francesco Loi
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Marco Masala
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Guido Parodi
- Department of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy
| | - Alessandro P Delitala
- Department of Medicine, Surgery, and Pharmacy, University of Sassari, Via Istria12, 07100 Sassari, Italy, Italy
| | - David Schlessinger
- Laboratory of Genetics & Genomics, NIH/National Institute of Ageing, Bethesda, MD, USA
| | - Edward Lakatta
- Laboratory of Cardiovascular Science, NIH/National Institute of Ageing, Bethesda, MD, USA
| | - Edoardo Fiorillo
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
| | - Francesco Cucca
- Department of Biomedical Sciences, University of Sassari, Sassari 07100, Italy
- Institute of Genetics and Biomedical Research, National Research Council, Monserrato, Cagliari 09042, Italy
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