Designing candidate gene and genome-wide case-control association studies

Abstract

This protocol describes how to appropriately design a genetic association case-control study, either focusing on a candidate gene (CG) or region or implementing a genome-wide approach. The steps described involve: (i) defining the case phenotype in adequate detail; (ii) checking the heritability of the disease in question; (iii) considering whether a population-based study is the appropriate design for the research question; (iv) the appropriate selection of controls; (v) sample size calculations and (vi) giving due consideration to whether it is a de novo or replication study. General guidelines are given, as well as specific examples of a CG and a genome-wide association study into type 2 diabetes. Software and websites used in this protocol include the International HapMap Consortium website, Genetic Power Calculator, CaT, and SNPSpD. Running each of the programs takes only a few seconds; the rate-limiting steps involve thinking through the designs and parameters in the disease models.

Fig 1

Required number of cases (=number of controls) to detect varying disease allele frequencies and GRRs with 80% power in a) a CG scenario with indirect association assuming either 18 independent tagSNPs (solid lines; per-SNP type I error rate = 0.0028) or 11 independent tagSNPs (dashed lines; per-SNP type I error rate = 0.0046) and b) a GWA scenario assuming either 500,000 independent tagSNPs (solid lines; per-SNP type I error rate= 1×10⁻⁷) or 300,000 independent tag SNPs (dashed lines; per-SNP type I error rate= 1.67×10⁻⁷). A multiplicative model was assumed (GRR_AA = (GRR_Aa²)) and numbers were adjusted for a mean r² of 0.97 (Caucasians) between a common tagSNP and common disease allele.