Multi-Marker Test For Genetic Association

• 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): Lingzhi Li*+ and Weihua Guan
• Companies: University of Minnesota and University of Minnesota
• Keywords: genetic association ; multi-marker test ; stepwise selection

Abstract

We consider the association test between a phenotype and multiple single nucleotide polymorphisms (SNPs) within a gene or region. Due to the low effect sizes of causal variants for many complex diseases, single-locus association tests may not have sufficient power to detect such disease predisposing variants. Here we proposed a new multi-locus approach that sums the genotype scores of a subset of SNPs selected by stepwise selection method, and assesses the significance of summed score through permutation test. The new approach focuses on the SNPs that are more likely to be associated with the disease than other SNPs in the region, and selects the SNPs based on multi-locus regression rather than single-locus tests. We compare our approach with the sum test suggested by Pan et al. [2010], which combines all markers in the region for disease-marker association. The simulation results show that our proposed approach can achieve greater power than the sum test while still maintains correct false-positive rate. We apply our method a multi-center cohort study to identify genes predisposing to different endpoints of kidney transplantation. We hope our method can facilitate the identificati