Wellcome Trust Genome-Wide Association Study of Ischemic Stroke

Abstract

Twin and family history studies suggest that genetic risk factors are important for ischemic stroke.1,2 However, identifying the underlying genes has proved challenging. Until recently, the main technique used was the candidate gene method. In this, genetic variants, usually single nucleotide type polymorphisms (SNPs), are identified in a proposed candidate gene, which is thought to be involved in stroke risk. The frequency of the SNP in patients with stroke compared with controls is then determined. Many candidate gene studies have been published in stroke, but the results of these have been disappointing with few replicable associations. This situation is common with the genetics of many other complex diseases, and the reasons for lack of success include small sample sizes, a failure to adequately phenotype stroke subtypes, and a lack of primary replication of positive associations.3 An additional problem with candidate gene studies is that associations can only be identified in genes already known about and implicated in stroke risk; therefore, completely novel genes cannot be identified. The genetics of complex diseases such as stroke, in which multiple genes interact with environmental risk factors to increase risk, has been revolutionized by the Genome-Wide Association Study (GWAS) approach. This uses microarray technology to genotype up to ≥1 million SNPs, which span the whole genome. A case–control methodology is used to compare the frequency of individual SNPs between cases and controls. This is combined with rigorous multiple comparison techniques to account for the many associations tested. A great advantage of the GWAS approach, in contrast to the candidate gene method, is that it allows associations between completely novel chromosomal loci and disease to be identified. This technology has been combined with much improved study design with both very large sample sizes and replication of positive associations before publication. GWAS …