Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes

Genet Epidemiol. 2022 Feb;46(1):51-62. doi: 10.1002/gepi.22434. Epub 2021 Oct 21.

Abstract

Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.

Keywords: Mendelian randomization; genetics; metabolic syndrome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Coronary Artery Disease* / epidemiology
  • Coronary Artery Disease* / genetics
  • Diabetes Mellitus, Type 2* / complications
  • Diabetes Mellitus, Type 2* / epidemiology
  • Diabetes Mellitus, Type 2* / genetics
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Humans
  • Mendelian Randomization Analysis
  • Polymorphism, Single Nucleotide
  • Risk Factors