Causal relationship between Alzheimer's disease and unstable angina: a bidirectional Mendelian randomization analysis

Yu-Hang Chen1, Cong-Ying Ren2, Cao Yu3

  • 1Department of Operations Management, Chongqing Mental Health Center, Chongqing, China.

PubMed

Insights

Alzheimer's disease (AD) significantly increases the risk of unstable angina (UA), according to Mendelian randomization. However, unstable angina does not appear to causally affect Alzheimer's disease risk.

Area of Science:

  • Genetics
  • Neurology
  • Cardiology

Background:

  • Observational studies suggest a link between Alzheimer's disease (AD) and cardiovascular disease (CVD).
  • The precise genetic underpinnings of AD and coronary heart disease, specifically unstable angina (UA), remain unclear.
  • Mendelian randomization (MR) is employed to investigate potential causal genetic relationships.

Purpose of the Study:

  • To conduct a bidirectional MR analysis to determine the causal relationship between AD and UA.
  • To evaluate the impact of AD on the risk of developing UA.
  • To assess if UA genetically influences the risk of AD.

Main Methods:

  • Utilized genome-wide association studies (GWAS) from European populations to identify genetic instrumental variables for AD.
  • Employed the inverse variance weighted (IVW) approach for primary causal inference.
  • Performed sensitivity analyses, including heterogeneity and horizontal pleiotropy assessments, to ensure result validity.

Main Results:

  • Genetically predicted AD was associated with an elevated risk of UA (IVW: OR=3.439, P=0.002).
  • No significant evidence supported a causal genetic link from UA to AD risk (IVW: OR=0.998, P=0.190).
  • Sensitivity analyses confirmed the robustness of findings, showing no significant heterogeneity or horizontal pleiotropy.

Conclusions:

  • Alzheimer's disease is identified as a risk factor for unstable angina.
  • Further research into the molecular mechanisms connecting AD and UA is warranted.
  • Potential for developing personalized treatments based on genetic data is highlighted.
Abstract

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