Cardiovascular disease risk prediction using genetic information (gene scores): is it really informative?

Curr Opin Lipidol. 2008 Apr;19(2):128-32. doi: 10.1097/MOL.0b013e3282f5283e.

Abstract

Purpose of review: DNA-based tests for assessment of genetic predisposition to coronary heart disease need to provide information over and above that of conventional risk factors. The efficacy of selected 'candidate' gene loci in risk algorithms, to improve the predictive accuracy for coronary heart disease, remains to be demonstrated.

Recent findings: Although many candidate genes for coronary heart disease have been tested, the optimal set of risk genotypes has yet to be identified. There is only a relatively modest risk to be expected in association with any single genotype, published estimates are in the range of 1.12-1.73. Thus the risk associated with any one genotype is modest, but, in combination, selected genotypes may be associated with a clinically significant risk. Since the allele frequency for many of these variants is high, many individuals will carry several 'risk alleles'. A small number of selected single nucleotide polymorphisms should complement the conventional risk factors to identify high-risk individuals in whom correction of 'modifiable risk factors' through lifestyle interventions or medication would be most beneficial.

Summary: As our understanding of how genetic variation impacts on common diseases advances, the novel loci identified by genome-wide association scans associated with disease risk will rapidly improve these risk algorithms.

Publication types

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

MeSH terms

  • Algorithms
  • Alleles
  • Cardiovascular Diseases / genetics*
  • Humans
  • Polymorphism, Single Nucleotide
  • Risk Factors