AI Article Synopsis

  • * Researchers used a Bayesian multi-trait approach to analyze 10 cardiac traits from a large group of individuals and found significant genetic variants linked to heart function.
  • * They identified three new variants in the genes RGS3, CHD3, and MRPL38 that affect various cardiac traits, with RGS3 showing a notable impact on multiple heart measurements and its role in inhibiting TGF-beta signaling related to heart issues.

Article Abstract

Heart failure is a major cause for premature death. Given the heterogeneity of the heart failure syndrome, identifying genetic determinants of cardiac function and structure may provide greater insights into heart failure. Despite progress in understanding the genetic basis of heart failure through genome wide association studies, the heritability of heart failure is not well understood. Gaining further insights into mechanisms that contribute to heart failure requires systematic approaches that go beyond single trait analysis. We integrated a Bayesian multi-trait approach and a Bayesian networks for the analysis of 10 correlated traits of cardiac structure and function measured across 3387 individuals with whole exome sequence data. While using single-trait based approaches did not find any significant genetic variant, applying the integrative Bayesian multi-trait approach, we identified 3 novel variants located in genes, RGS3, CHD3, and MRPL38 with significant impact on the cardiac traits such as left ventricular volume index, parasternal long axis interventricular septum thickness, and mean left ventricular wall thickness. Among these, the rare variant NC_000009.11:g.116346115C > A (rs144636307) in RGS3 showed pleiotropic effect on left ventricular mass index, left ventricular volume index and maximal left atrial anterior-posterior diameter while RGS3 can inhibit TGF-beta signaling associated with left ventricle dilation and systolic dysfunction.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458140PMC
http://dx.doi.org/10.1038/s41598-019-41362-3DOI Listing

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