Microarray technology and applications in the arena of genome-wide association

Clin Chem. 2008 Jul;54(7):1116-24. doi: 10.1373/clinchem.2008.105395. Epub 2008 May 22.

Abstract

Background: there is a revolution occurring in single nucleotide polymorphism (SNP) genotyping technology, with high-throughput methods now allowing large numbers of SNPs (10(5)-10(6)) to be genotyped in large cohort studies. This has enabled large-scale genome-wide association (GWA) studies in complex diseases, such as diabetes, asthma, and inflammatory bowel disease, to be undertaken for the first time.

Content: the GWA approach serves the critical need for a comprehensive and unbiased strategy to identify causal genes related to complex disease, and is rapidly replacing the more traditional candidate gene studies and microsatellite-based linkage mapping approaches that have dominated gene discovery attempts for common diseases. As a consequence of employing array-based technologies, over the last 3 years dramatic discoveries of key variants involved in multiple complex diseases and related traits have been reported in the top scientific literature and, most importantly, have been largely replicated by independent investigator groups. As a consequence, several novel genes have been identified, most notably in the metabolic, cardiovascular, autoimmune, and oncology disease areas, that are clearly rooted in the biology of these disorders. These discoveries have opened up new avenues for investigators to address novel molecular pathways that were not previously linked to or thought of in relation with these diseases.

Summary: this review provides a synopsis of recent advances and what we may expect to still emerge from this field.

Publication types

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

MeSH terms

  • Cardiovascular Diseases / genetics
  • Diabetes Mellitus, Type 2 / genetics
  • Genetic Variation
  • Genome, Human*
  • Humans
  • Immune System Diseases / genetics
  • Neoplasms / genetics
  • Nervous System Diseases / genetics
  • Obesity / genetics
  • Oligonucleotide Array Sequence Analysis*