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Can genetic pleiotropy replicate common clinical constellations of cardiovascular disease and risk?

Omri Gottesman1, Esther Drill, Vaneet Lotay

  • 1The Charles Bronfman Institute for Personalized Medicine, Mount Sinai School of Medicine, New York, New York, United States of America. omri.gottesman@mssm.edu

Plos One
|October 3, 2012
PubMed

Insights

This study explored genetic links between obesity, diabetes, and cardiovascular disease (CVD). Shared genetic variants were found, confirming common pathophysiology, especially when including diverse populations.

Area of Science:

  • Genetics and Genomics
  • Cardiovascular Disease Research
  • Metabolic Disease Research

Background:

  • Established clinical, epidemiological, and pathophysiological links exist between obesity, diabetes, hyperlipidemia, hypertension, kidney disease, and cardiovascular disease (CVD).
  • Limited synthesis of genetic data currently exists to explain the underlying shared relationship between these commonly co-existing conditions.
  • Genome-Wide Association Studies (GWAS) have identified numerous genetic variants associated with individual conditions.

Purpose of the Study:

  • To investigate the overlap of genetic variants associated with CVD and its common comorbidities and risk factors.
  • To determine if shared genetic variants support a common pathophysiology and risk across these conditions.
  • To identify pleiotropic genes involved in similar biological processes underlying these interconnected diseases.

Main Methods:

  • Utilized the NHGRI GWAS catalog to identify relevant studies.
  • Analyzed 107 GWAS studies related to CVD and its comorbidities/risk factors.
  • Employed pathway-based analyses to detect pleiotropic genes and assigned genes based on positional mapping of associated signals.

Main Results:

  • Identified 44 positional genes shared across at least two CVD-related phenotypes, replicating established relationships when non-European population data were included.
  • Seven genes showed pleiotropy across three or more phenotypes, primarily involved in lipid transport and metabolism.
  • Observed limited functional connections between many identified genes, suggesting complexity beyond simple shared pathways.

Conclusions:

  • Successfully reproduced established relationships between CVD risk factors using GWAS findings, highlighting the importance of diverse population data.
  • Interpretation of biological pathways underlying observed genetic pleiotropy was limited.
  • Further research is needed to link genetic variation to gene expression and elucidate novel biological pathways for a comprehensive understanding.

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