Power Gains Using Phenotyped but Ungenotyped Relatives in Genetic Association Studies of Dichotomous Traits

• Activity Number: 588
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Wei Vivian Zhuang*+ and Joanne M. Murabito and Kathryn Lunetta
• Companies: Boston University and Framingham Heart Study and Boston University
• Keywords: Missing Data ; Statistical Genetics ; Association Studies

Abstract

In longitudinal studies, some subjects with phenotype data die before providing DNA, but genotyped relatives can be used to impute missing genotypes. We use weighted least square and meta-analysis to explore the power gain for including subjects with missing genotypes in binary-trait-SNP association tests for the case of one SNP and type of relative. The non-centrality-parameter ratio for the association tests including versus excluding ungenotyped subjects depends on the phenotypic correlation and relationship coefficient between the genotyped and ungenotyped relatives, the allele frequency and the variance of the trait given the SNP. Simulations for pedigrees of 2 parents and 2 children using Linear Mixed Effect and Generalized Estimating Equations models yield consistent findings. While the median power ratio increases, the power for a study may decrease when ungenotyped subjects are included. As the proportion of variance explained by the SNP decreases, the probability that the test statistic is decreased increases. For a dichotomous trait, the inclusion of the ungenotyped but phenotyped subjects improves power in most situations and does not inflate type I error rates.