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Testing association between disease and multiple SNPs in a candidate gene

✍ Scribed by W. James Gauderman; Cassandra Murcray; Frank Gilliland; David V. Conti

Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
437 KB
Volume
31
Category
Article
ISSN
0741-0395

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✦ Synopsis

Abstract

Current technology allows investigators to obtain genotypes at multiple single nucleotide polymorphism (SNPs) within a candidate locus. Many approaches have been developed for using such data in a test of association with disease, ranging from genotype‐based to haplotype‐based tests. We develop a new approach that involves two basic steps. In the first step, we use principal components (PCs) analysis to compute combinations of SNPs that capture the underlying correlation structure within the locus. The second step uses the PCs directly in a test of disease association. The PC approach captures linkage‐disequilibrium information within a candidate region, but does not require the difficult computing implicit in a haplotype analysis. We demonstrate by simulation that the PC approach is typically as or more powerful than both genotype‐ and haplotype‐based approaches. We also analyze association between respiratory symptoms in children and four SNPs in the Glutathione‐S‐Transferase P1 locus, based on data from the Children's Health Study. We observe stronger evidence of an association using the PC approach (p = 0.044) than using either a genotype‐based (p = 0.13) or haplotype‐based (p = 0.052) approach. Genet. Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.

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