Related Experiment Video
Updated: Jun 16, 2025

Simultaneous Isolation and Culture of Atrial Myocytes, Ventricular Myocytes, and Non-Myocytes from an Adult Mouse Heart
Published on: June 14, 2020
Genetics of Cardiac Aging Implicate Organ-Specific Variation
James Brundage1, Joshua P Barrios1,2, Geoffrey H Tison1,2,3,4
1Division of Cardiology, University of California San Francisco, San Francisco, CA, USA.
Insights
A new deep learning model accurately estimates cardiac age acceleration using heart-specific MRI data. This cardiac age acceleration is heritable and linked to lifestyle, genetics, and adverse health outcomes.
Area of Science:
- Cardiology
- Medical Imaging
- Genetics
Background:
- Cardiac aging varies among individuals, prompting interest in estimating cardiac age acceleration.
- Existing methods for cardiac age estimation lack specificity or feature richness, hindering research into genetic contributions.
- Deep learning (DL) on cardiac-masked MRI offers a potential solution for precise cardiac aging assessment.
Purpose of the Study:
- To develop and validate a video-based DL model for estimating cardiac age acceleration using heart-masked cardiac MRI data.
- To investigate the associations of cardiac age acceleration with cardiac function, lifestyle factors, serum proteins, and brain MRI characteristics.
- To explore the heritability and genetic underpinnings of cardiac age acceleration.
Main Methods:
- A video-based DL model was trained on cardiac MRI data from 61,691 UK Biobank participants, excluding non-cardiac pixels.
- Cardiac age acceleration was calculated as the difference between predicted heart age and calendar age.
- Genome-wide association studies (GWAS) and Mendelian randomization were employed to identify genetic loci and protein associations.
Main Results:
- The DL model explained 71.1% of calendar age variance with a mean absolute error of 3.3 years.
- Cardiac age acceleration correlated with adverse cardiac geometry, dysfunction, lifestyle factors, specific serum proteins, and brain MRI findings.
- Cardiac age acceleration was found to be heritable (h2g 26.6%), with GWAS identifying 24 associated loci, 21 novel for cardiac age acceleration.
Conclusions:
- A novel DL approach provides a cardiac-specific measure of aging.
- Cardiac age acceleration is influenced by genetic, lifestyle, and environmental factors, and is associated with increased risk of cardiovascular disease and mortality.
- These findings highlight the importance of heart- and vascular-specific factors in cardiac aging.
Abstract:
Heart structure and function change with age, and the notion that the heart may age faster for some individuals than for others has driven interest in estimating cardiac age acceleration. However, current approaches have limited feature richness (heart measurements; radiomics) or capture extraneous data and therefore lack cardiac specificity (deep learning [DL] on unmasked chest MRI). These technical limitations have been a barrier to efforts to understand genetic contributions to age acceleration. We hypothesized that a video-based DL model provided with heart-masked MRI data would capture a rich yet cardiac-specific representation of cardiac aging. In 61,691 UK Biobank participants, we excluded noncardiac pixels from cardiac MRI and trained a video-based DL model to predict age from one cardiac cycle in the 4-chamber view. We then computed cardiac age acceleration as the bias-corrected prediction of heart age minus the calendar age. Predicted heart age explained 71.1% of variance in calendar age, with a mean absolute error of 3.3 years. Cardiac age acceleration was linked to unfavorable cardiac geometry and systolic and diastolic dysfunction. We also observed links between cardiac age acceleration and diet, decreased physical activity, increased alcohol and tobacco use, and altered levels of 239 serum proteins, as well as adverse brain MRI characteristics. We found cardiac age acceleration to be heritable (h2g 26.6%); a genome-wide association study identified 8 loci related to linked to cardiomyopathy (near TTN, TNS1, LSM3, PALLD, DSP, PLEC, ANKRD1 and MYO18B) and an additional 16 loci (near MECOM, NPR3, KLHL3, HDGFL1, CDKN1A, ELN, SLC25A37, PI15, AP3M1, HMGA2, ADPRHL1, PGAP3, WNT9B, UHRF1 and DOK5). Of the discovered loci, 21 were not previously associated with cardiac age acceleration. Mendelian randomization revealed that lower genetically mediated levels of 6 circulating proteins (MSRA most strongly), as well as greater levels of 5 proteins (LXN most strongly) were associated with cardiac age acceleration, as were greater blood pressure and Lp(a). A polygenic score for cardiac age acceleration predicted earlier onset of arrhythmia, heart failure, myocardial infarction, and mortality. These findings provide a thematic understanding of cardiac age acceleration and suggest that heart- and vascular-specific factors are key to cardiac age acceleration, predominating over a more global aging program.
More Related Videos
08:03Simultaneous Assessment of Cardiomyocyte DNA Synthesis and Ploidy: A Method to Assist Quantification of Cardiomyocyte Regeneration and Turnover
Published on: May 23, 2016
12:49Isolation, Culture, and Functional Characterization of Adult Mouse Cardiomyoctyes
Published on: September 24, 2013
Related Concept Videos
Aging
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
Pathophysiology of Heart Failure
Pathophysiology of Cardiac Performance
Mitochondria