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Complex trait variation is likely to be explained by the combined effects of genes, environmental factors, and gene × environment (G × E) interaction. The authors introduce a novel 2-step method for detecting a G × E interaction in a genome-wide association study (GWAS) of case-parent trios. The method utilizes 2 sources of G × E information in a trio sample to construct a screening step and a testing step. Across a wide range of models, this 2-step procedure provides substantially greater power to detect G × E interaction than a standard test of G × E interaction applied genome-wide. For example, for a disease susceptibility locus with minor allele frequency of 15%, a binary exposure variable with 50% prevalence, and a GWAS scan of 1 million markers in 1,000 case-parent trios, the 2-step method provides 87% power to detect a G × E interaction relative risk of 2.3, as compared with only 25% power using a standard G × E test. The method is easily implemented using standard software. This 2-step scan for G × E interaction is independent of any prior scan that may have been conducted for genetic main effects, and thus has the potential to uncover new genes in a GWAS that have not been previously identified. [ABSTRACT FROM PUBLISHER]

In genetic association studies, investigators compare allele or genotype frequencies in unrelated case and control subjects or examine preferential allele transmissions from parents to affected offspring. In many genetic case-control studies, the collection of DNA material extends to relatives such as parents of cases. Thus, case-control and case-parent trio association analyses are possible. Whereas the goal of collecting genetic information from family members in a study initially designed as a case-control study is to enrich the genetic analysis, increase power, or address concern about population structure bias, methods of combining genetic data from unrelated case and control subjects with genetic trio data from the same study population are not well known. A number of hybrid approaches have been developed that utilize such data together. In this paper, the authors describe key features of genetic case-control and case-parent trio studies and review commonly used methods of genetic analysis for case-parent trio designs. In addition, they provide a pragmatic review of statistical methods and available software for existing hybrid approaches that combine various components of case-control and genetic trio data. The application of all methods is illustrated using a candidate gene study of childhood leukemia that included case-control subjects and their parents. [ABSTRACT FROM PUBLISHER]