The genome-wide association study--a new era for common polygenic disorders

J Cardiovasc Transl Res. 2010 Jun;3(3):173-82. doi: 10.1007/s12265-010-9178-6. Epub 2010 Mar 27.

Abstract

This review covers the advances made in the last decade utilizing the high-density single-nucleotide microarrays to screen the entire human genome for genetic risk variants and outlines future strategies to draw deeper into the human genetic front. The sequence of the human genome provides the blueprint for life, while its variation provides the spice of life. Approximately 99.5% of the human genome DNA sequence is identical among humans with 0.5% of the genome sequence (15 million bps) accounting for all individual differences including susceptibility for disease. The new technology of the computerized chip array containing up to millions of SNPs as DNA markers makes possible genome-wide association studies to detect genetic predisposition to common polygenic disorders such as coronary artery disease (CAD). The sample sizes required for these studies are massive and large; worldwide consortiums such as CARDIoGRAM have been formed to accommodate this requirement. The progress has been remarkable with the identification of 9p21 followed by several others within the past 2 years. It is expected that most of the common variants (minor allele frequency, MAF >5%) will be identified for CAD within the next 2 to 3 years. Rare variants (MAF <5%) will require direct sequencing which will be delayed somewhat. The ultimate objective for the future is the sequencing and functional analysis of the causative polymorphisms. This will require a new approach involving several disciplines, namely, bioinformatics, high-throughput cell expression, and animal models.

Publication types

  • Review

MeSH terms

  • Animals
  • Chromosomes, Human, Pair 9
  • Coronary Artery Disease / genetics*
  • Databases, Genetic
  • Gene Expression Profiling / methods
  • Gene Frequency
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study*
  • Humans
  • Meta-Analysis as Topic
  • Multifactorial Inheritance
  • Oligonucleotide Array Sequence Analysis
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Risk Assessment
  • Risk Factors
  • Sample Size