Monogenic and Polygenic Models of Coronary Artery Disease

Curr Cardiol Rep. 2021 Jul 1;23(8):107. doi: 10.1007/s11886-021-01540-0.

Abstract

Purpose of the review: Coronary artery disease (CAD) is a common disease globally attributable to the interplay of complex genetic and lifestyle factors. Here, we review how genomic sequencing advances have broadened the fundamental understanding of the monogenic and polygenic contributions to CAD and how these insights can be utilized, in part by creating polygenic risk estimates, for improved disease risk stratification at the individual patient level.

Recent findings: Initial studies linking premature CAD with rare familial cases of elevated blood lipids highlighted high-risk monogenic contributions, predominantly presenting as familial hypercholesterolemia (FH). More commonly CAD genetic risk is a function of multiple, higher frequency variants each imparting lower magnitude of risk, which can be combined to form polygenic risk scores (PRS) conveying significant risk to individuals at the extremes. However, gaps remain in clinical validation of PRSs, most notably in non-European populations. With improved and more broadly utilized genomic sequencing technologies, the genetic underpinnings of coronary artery disease are being unraveled. As a result, polygenic risk estimation is poised to become a widely used and powerful tool in the clinical setting. While the use of PRSs to augment current clinical risk stratification for optimization of cardiovascular disease risk by lifestyle change or therapeutic targeting is promising, we await adequately powered, prospective studies, demonstrating the clinical utility of polygenic risk estimation in practice.

Keywords: Coronary artery disease; Genetics; Heart disease; Polygenic risk assessment.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Coronary Artery Disease* / genetics
  • Genetic Predisposition to Disease
  • Humans
  • Multifactorial Inheritance / genetics
  • Prospective Studies
  • Risk Factors