Clinical correlates and heritability of cardiac mechanics: The HyperGEN study

Academic Article

Abstract

  • © 2018 Elsevier B.V. Background: Indices of cardiac mechanics are sensitive markers of subclinical myocardial dysfunction. Improved understanding of the clinical correlates and heritability of cardiac mechanics could result in novel insight into the acquired and genetic risk factors for myocardial dysfunction. Therefore, we sought to determine the clinical correlates and heritability of indices of cardiac mechanics in whites and African Americans (AAs). Methods: We examined 2058 participants stratified by race (1104 whites, 954 AA) in the Hypertension Genetic Epidemiology Network (HyperGEN), a population- and family-based study, and performed digitization of analog echocardiograms with subsequent speckle-tracking analysis. We used linear mixed effects models to determine the clinical correlates of indices of cardiac mechanics (longitudinal, circumferential, radial strain; early diastolic strain rate; and early diastolic tissue velocities). Heritability estimates for cardiac mechanics were calculated using maximum-likelihood variance component analyses in Sequential Oligogenic Linkage Analysis Routine (SOLAR), with adjustment for clinical and echocardiographic covariates. Results: Several clinical characteristics and conventional echocardiographic parameters were found to be associated with speckle-tracking traits of cardiac mechanics. Male sex, blood pressure, and fasting glucose were associated with worse longitudinal strain (LS) (P < 0.05 for all) after multivariable adjustment. After adjustment for covariates, LS, e′ velocity, and early diastolic strain rate were found to be heritable; LS and e′ velocity had higher heritability estimates in AAs compared to whites. Conclusions: Indices of cardiac mechanics are heritable traits even after adjustment for clinical and conventional echocardiographic correlates. These findings provide the basis for future studies of genetic determinants of these traits that may elucidate race-based differences in heart failure development.
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    Author List

  • Khan SS; Kim KYA; Peng J; Aguilar FG; Selvaraj S; Martinez EE; Baldridge AS; Sha J; Irvin MR; Broeckel U
  • Start Page

  • 208
  • End Page

  • 213
  • Volume

  • 274