Use of Selective Phenotyping to Increase Power of Genetic Association Studies of Quantitative Biomarkers

• Activity Number: 359
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Yunfei Wang*+ and Ethan M. Lange
• Companies: The University of North Carolina and The University of North Carolina
• Keywords: biomarkers ; simulated annealing ; statistical power ; genetic association ; SNPs

Abstract

Blood-based biomarkers are often used as intermediate outcomes for identifying genetic risk factors associated with cardiovascular disease (CVD). Measuring biomarkers, however, is typically expensive and time consuming. Genome-wide genetic data on single-nucleotide polymorphisms (SNPs) are now routinely available for tens of thousands of samples from large population-based cohorts. Given the expense of measuring biomarkers, it would be desirable to identify a subset of subjects that could be phenotyped for the biomarker of interest in order to optimize statistical power under fixed cost constraints. For any specific SNP and a fixed sample size, power is typically optimized when genotypes are partitioned equally between homozygotes for the major and minor allele. When trying to optimize power across multiple SNPs, using a selection strategy that optimizes power for one specific SNP does not benefit other SNPs of interest. We describe a simulated annealing-based algorithm that identifies an optimal selection of subjects to be phenotyped based on the weighted or unweighted average power across a group of SNPs.