The linkage between electronic health records (EHRs) and genotype data makes it plausible to study the genetic susceptibility of a wide range of disease phenotypes. Despite that EHR-derived phenotype data are subjected to misclassification, it has been shown useful for discovering susceptible genes, particularly in the setting of phenome-wide association studies (PheWAS). It is essential to characterize discovered associations using gold standard phenotype data by chart review. In this work, we propose a genotype stratified case-control sampling strategy to select subjects for phenotype validation. We develop a closed-form maximum-likelihood estimator for the odds ratio parameters and a score statistic for testing genetic association using the combined validated and error-prone EHR-derived phenotype data, and assess the extent of power improvement provided by this approach. Compared with case-control sampling based only on EHR-derived phenotype data, our genotype stratified strategy maintains nominal type I error rates, and result in higher power for detecting associations. It also corrects the bias in the odds ratio parameter estimates, and reduces the corresponding variance especially when the minor allele frequency is small.
[1]Univ Penn, Perelman Sch Med, Dept Biostat Epidemiol & Informat, 423 Guardian Dr, Philadelphia, PA 19104 USA.
[2]Hosp Univ Penn, Div Vasc Surg & Endovasc Therapy, 3400 Spruce St, Philadelphia, PA 19104 USA.
[3]Corporal Michael Crescenz VA Med Ctr, Dept Surg, Philadelphia, PA USA.
[4]Fudan Univ, Inst Biostat, Shanghai, Peoples R China.
[5]Sidwell Friends Sch, Washington, DC USA.
[6]Univ Penn, Perelman Sch Med, Inst Biomed Informat, Philadelphia, PA 19104 USA.
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