Genome‐wide Association Studies: The Success, Failure and Future

Autor: Chia Kee-Seng, Loy En Yun, Ku Chee‐Seng, Pawitan Yudi
Rok vydání: 2009
Předmět:
Zdroj: eLS
DOI: 10.1002/9780470015902.a0021995
Popis: It is the fifth year of genome-wide association studies (GWAS) after the first study was published in 2005 which identified the association between complement factor H and age-related macular degeneration. The publication of this landmark study also marked the start of a new era in the genetic studies of human complex diseases. Since then more than 350 GWAS have been published and the associations of greater than 1500 SNPs (single nucleotide polymorphisms) or genetic loci were also reported. Notably, genome-wide association studies have contributed to significant advances in our knowledge and understanding of the genetic basis of complex diseases and traits compared to the pregenome-wide era where linkage mapping and candidate gene association studies were broadly applied. Nevertheless, most of the inherited risk remains to be explained for all the phenotypes that have been investigated so far. This suggests that we still have a long way to go to decipher the genetic basis of human complex traits. Key concepts The primary aim of genome-wide association studies (GWAS) is to identify novel genetic variants to elucidate the disease biological pathways and eventually lead to identification of new molecular markers for diagnostic application, or drug targets for therapeutic intervention. GWAS is a comprehensive and biologically agnostic approach in searching for unknown disease variants; this method has been very successful in identifying novel genetic loci for various human complex traits. The GWAS findings have also provided new insights into the molecular pathways of complex diseases even when most of the disease causative variants remain to be discerned from the neighbouring correlated markers. Most of the risk alleles that have been identified by GWAS are common (allele frequency >5%) and conferred small effect sizes (odds ratio, OR
Databáze: OpenAIRE