4.8 Article

Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function

Journal

NATURE GENETICS
Volume 54, Issue 6, Pages 783-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41588-022-01083-2

Keywords

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Funding

  1. National Institute for Health Research Integrated Academic Training program
  2. Wellcome Trust [203553/Z/16/Z]
  3. British Heart Foundation [PG/14/89/31194]
  4. 'SmartHeart' Engineering and Physical Sciences Research Council program grant [EP/P001009/1]
  5. Oxford National Institute for Health Research Biomedical Research Centre
  6. Oxford British Heart Foundation Centre of Research Excellence
  7. Medical Research Council [MR/L016311/1]
  8. Welsh Assembly Government
  9. British Heart Foundation
  10. National Heart, Lung, and Blood Institute
  11. NHLBI [75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003]
  12. The NHLBI [N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-00004, UL1-TR-001079 UL1-TR-001420]
  13. NIH
  14. National Heart, Lung, and Blood Institute [N02-HL-64278]
  15. National Center for Advancing Translational Sciences [UL1TR001881]
  16. National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center [DK063491]
  17. National Institutes of Health [K24 HL103844, R01 HL086719]

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This study conducted genome-wide association analyses using a deep learning algorithm on cardiovascular magnetic resonance images of UK Biobank participants, and identified 25 unique loci associated with right ventricular structure and function. The findings were validated in a meta-analysis, and revealed associations between RV polygenic risk scores and dilated cardiomyopathy and coronary artery disease.
Right ventricular (RV) structure and function influence the morbidity and mortality from coronary artery disease (CAD), dilated cardiomyopathy (DCM), pulmonary hypertension and heart failure. Little is known about the genetic basis of RV measurements. Here we perform genome-wide association analyses of four clinically relevant RV phenotypes (RV end-diastolic volume, RV end-systolic volume, RV stroke volume, RV ejection fraction) from cardiovascular magnetic resonance images, using a state-of-the-art deep learning algorithm in 29,506 UK Biobank participants. We identify 25 unique loci associated with at least one RV phenotype at P < 2.27 x10(-8), 17 of which are validated in a combined meta-analysis (n = 41,830). Several candidate genes overlap with Mendelian cardiomyopathy genes and are involved in cardiac muscle contraction and cellular adhesion. The RV polygenic risk scores (PRSs) are associated with DCM and CAD. The findings substantially advance our understanding of the genetic underpinning of RV measurements. Genome-wide analyses of cardiovascular magnetic resonance images identify variants associated with right ventricular structure and function. Polygenic scores for these traits are associated with dilated cardiomyopathy and coronary artery disease.

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