| Title: | Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass |
| Journal: | Nature Communications |
| Published: | 21 Mar 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36944631/ |
| DOI: | https://doi.org/10.1038/s41467-023-37173-w |
| URL: | https://www.nature.com/articles/s41467-023-37173-w.pdf |
Publication 11228
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Abstract
Left ventricular mass is a risk marker for cardiovascular events, and may indicate an underlying cardiomyopathy. Cardiac magnetic resonance is the gold-standard for left ventricular mass estimation, but is challenging to obtain at scale. Here, we use deep learning to enable genome-wide association study of cardiac magnetic resonance-derived left ventricular mass indexed to body surface area within 43,230 UK Biobank participants. We identify 12 genome-wide associations (1 known at TTN and 11 novel for left ventricular mass), implicating genes previously associated with cardiac contractility and cardiomyopathy. Cardiac magnetic resonance-derived indexed left ventricular mass is associated with incident dilated and hypertrophic cardiomyopathies, and implantable cardioverter-defibrillator implant. An indexed left ventricular mass polygenic risk score ≥90th percentile is also associated with incident implantable cardioverter-defibrillator implant in separate UK Biobank (hazard ratio 1.22, 95% CI 1.05-1.44) and Mass General Brigham (hazard ratio 1.75, 95% CI 1.12-2.74) samples. Here, we perform a genome-wide association study of cardiac magnetic resonance-derived indexed left ventricular mass to identify 11 novel variants and demonstrate that cardiac magnetic resonance-derived and genetically predicted indexed left ventricular mass are associated with incident cardiomyopathy.</p>
16 Authors
- Shaan Khurshid
- Julieta Lazarte
- James P. Pirruccello
- Lu-Chen Weng
- Seung Hoan Choi
- Amelia W. Hall
- Xin Wang
- Samuel F. Friedman
- Victor Nauffal
- Kiran J. Biddinger
- Krishna G. Aragam
- Puneet Batra
- Jennifer E. Ho
- Anthony A. Philippakis
- Patrick T. Ellinor
- Steven A. Lubitz
1 Application
| Application ID | Title |
|---|---|
| 17488 | Understanding the Genetic Basis of Cardiac Arrhythmias |
Enabling scientific discoveries that improve human health