A concise history of genome-wide association studies

Genome-wide association studies (GWASs) have had a tremendous impact on the pace of genomic research of common diseases. The number of identified genetic variants associated has grown exponentially. For some diseases, such as coronary heart disease (CHD), the number of known susceptibility genes has...

Full description

Bibliographic Details
Main Authors: Bobby P. C. Koeleman, Amein Al-Ali, Sander W van der Laan, Folkert W Asselbergs
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2013-01-01
Series:Saudi Journal of Medicine and Medical Sciences
Subjects:
Online Access:http://www.sjmms.net/article.asp?issn=1658-631X;year=2013;volume=1;issue=1;spage=4;epage=10;aulast=Koeleman
Description
Summary:Genome-wide association studies (GWASs) have had a tremendous impact on the pace of genomic research of common diseases. The number of identified genetic variants associated has grown exponentially. For some diseases, such as coronary heart disease (CHD), the number of known susceptibility genes has grown from a handful to more than 45. A substantial number of genes point to unexpected mechanism involved, and functional data from the "Encyclopedia of Deoxyribonucleic Acid Elements" (ENCODE) project is helpful in uncovering the functional relevance to diseases. The rapidly evolving techniques have made the shift from family-based linkage studies to GWASs possible. Advanced single nucleotide polymorphism (SNP) arrays containing hundreds of thousands of variants efficiently assess the extent of genome-wide disease-associated genetic variation. Along with SNP arrays came breakthroughs in statistical analyses and study designs leading to the exponential growth of the GWAS catalog. Pathway analyses of GWASs results with manually curated software programs have been insightful. Next-generation sequencing (NGS) of the exome or even the whole genome will undoubtedly shift the balance in focus from common variants to more rare variations impacting common diseases. Moreover, the combined power of GWASs, sequencing, pathway analysis, and functional data to study common disease shall only be limited by our ability to comprehend.
ISSN:1658-631X