| Title: | Computational estimates of annular diameter reveal genetic determinants of mitral valve function and disease |
| Journal: | JCI Insight |
| Published: | 8 Feb 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35132965/ |
| DOI: | https://doi.org/10.1172/jci.insight.146580 |
| URL: | http://insight.jci.org/articles/view/146580/files/pdf |
| Citations: | 12 (10 in last 2 years) as of 8 Aug 2024 |
Publication 7195
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
The fibrous annulus of the mitral valve plays an important role in valvular function and cardiac physiology, while normal variation in the size of cardiovascular anatomy may share a genetic link with common and rare disease. We derived automated estimates of mitral valve annular diameter in the 4-chamber view from 32,220 MRI images from the UK Biobank at ventricular systole and diastole as the basis for GWAS. Mitral annular dimensions corresponded to previously described anatomical norms, and GWAS inclusive of 4 population strata identified 10 loci, including possibly novel loci (GOSR2, ERBB4, MCTP2, MCPH1) and genes related to cardiac contractility (BAG3, TTN, RBFOX1). ATAC-Seq of primary mitral valve tissue localized multiple variants to regions of open chromatin in biologically relevant cell types and rs17608766 to an algorithmically predicted enhancer element in GOSR2. We observed strong genetic correlation with measures of contractility and mitral valve disease and clinical correlations with heart failure, cerebrovascular disease, and ventricular arrhythmias. Polygenic scoring of mitral valve annular diameter in systole was predictive of risk mitral valve prolapse across 4 cohorts. In summary, genetic and clinical studies of mitral valve annular diameter revealed genetic determinants of mitral valve biology, while highlighting clinical associations. Polygenic determinants of mitral valve annular diameter may represent an independent risk factor for mitral prolapse. Overall, computationally estimated phenotypes derived at scale from medical imaging represent an important substrate for genetic discovery and clinical risk prediction.16 Authors
- Mengyao Yu
- Catherine Tcheandjieu
- Adrien Georges
- Ke Xiao
- Helio Tejeda
- Christian Dina
- Thierry Le Tourneau
- Madalina Fiterau
- Renae Judy
- Noah L. Tsao
- Dulguun Amgalan
- Chad J. Munger
- Jesse M. Engreitz
- Scott M. Damrauer
- Nabila Bouatia-Naji
- James R. Priest
Enabling scientific discoveries that improve human health