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Genetic variation in coronary heart disease and myocardial infarction: methodological overview and clinical evidence

B R Winkelmann1, J Hager

  • 1Herzzentrum Ludwigshafen, Germany. winkelmb@klilu.de

Pharmacogenomics
|March 22, 2001
PubMed

Insights

Understanding the genetic basis of coronary artery disease (CAD) and myocardial infarction (MI) remains challenging. Complex interactions between genetic variations and environmental factors contribute to these conditions, with most gene roles still unknown.

Area of Science:

  • Cardiovascular Genetics
  • Molecular Medicine
  • Genomics

Background:

  • Coronary artery disease (CAD) and myocardial infarction (MI) are complex genetic disorders influenced by intricate interactions between environmental factors and multiple genes.
  • The precise molecular mechanisms underlying CAD and MI pathogenesis are not fully elucidated, despite extensive knowledge of risk factors.

Purpose of the Study:

  • To review the current understanding of genetic variations contributing to CAD and MI.
  • To highlight the challenges and limitations in identifying genes responsible for these complex cardiovascular diseases.

Main Methods:

  • Review of genetic association studies and linkage analysis for identifying disease-related genes.
  • Discussion of advancements in human genome sequencing and SNP identification, including genome-wide association studies (GWAS).

Main Results:

  • Genetic variations in susceptibility genes, alongside environmental impact, form the basis of CAD/MI molecular mechanisms.
  • Except for specific lipid gene polymorphisms (e.g., apolipoprotein E) and rare variations (e.g., LDL receptor), the role of most gene polymorphisms in CAD/MI is controversial or unknown.
  • Progress in mapping and identifying genes for complex traits like CAD/MI has been modest despite technological advancements.

Conclusions:

  • Dissecting the genetic architecture of CAD/MI as complex traits presents a significant challenge for 21st-century medical research.
  • Lack of precise clinical phenotyping, functional characterization of gene variants, and the large number of undetected genes contribute to the slow progress.

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