Lack of genetic support for shared aetiology of Coronary Artery Disease and Late-onset Alzheimer's disease

Sci Rep. 2018 May 8;8(1):7102. doi: 10.1038/s41598-018-25460-2.

Abstract

Epidemiological studies suggest a positive association between coronary artery disease (CAD) and late-onset Alzheimer's disease (LOAD). This large-scale genetic study brings together 'big data' resources to examine the causal impact of genetic determinants of CAD on risk of LOAD. A two-sample Mendelian randomization approach was adopted to estimate the causal effect of CAD on risk of LOAD using summary data from 60,801 CAD cases from CARDIoGRAMplusC4D and 17,008 LOAD cases from the IGAP Consortium. Additional analyses assessed the independent relevance of genetic associations at the APOE locus for both CAD and LOAD. Higher genetically determined risk of CAD was associated with a slightly higher risk of LOAD (Odds Ratio (OR) per log-odds unit of CAD [95% CI]: 1.07 [1.01-1.15]; p = 0.027). However, after exclusion of the APOE locus, the estimate of the causal effect of CAD for LOAD was attenuated and no longer significant (OR 0.94 [0.88-1.01]; p = 0.072). This Mendelian randomization study indicates that the APOE locus is the chief determinant of shared genetic architecture between CAD and LOAD, and suggests a lack of causal relevance of CAD for risk of LOAD after exclusion of APOE.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Alzheimer Disease / complications
  • Alzheimer Disease / epidemiology
  • Alzheimer Disease / genetics*
  • Alzheimer Disease / physiopathology
  • Coronary Artery Disease / complications
  • Coronary Artery Disease / epidemiology
  • Coronary Artery Disease / genetics*
  • Coronary Artery Disease / physiopathology
  • Female
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study
  • Humans
  • Male
  • Mendelian Randomization Analysis*
  • Middle Aged
  • Phenotype
  • Polymorphism, Single Nucleotide / genetics
  • Risk Assessment
  • Risk Factors