A Joint Test for Detecting Mean and Variance Heterogeneity Adjusting for Family Relatedness

• Activity Number: 185
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 11:15 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Ying Cao*+ and Taylor Maxwell and Peng Wei
• Companies: University of Texas Health Science Center at Houston and University of Texas Health Science Center at Houston and University of Texas School of Public Health
• Keywords: variance heterogeneity ; QTL ; linear mixed model ; family data ; BLUP

Abstract

Traditional quantitative trait locus(QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has identified loci associated with phenotype variance heterogeneity(vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated subjects, there is not yet vQTL test for related subjects. We propose a likelihood ratio test for identifying mean and variance heterogeneity simultaneously or either effect alone, adjusting for covariates and family relatedness using a linear mixed model approach. The test statistic for normally distributed traits follows chi-square distribution. Parametric bootstrap is used for non-normally distributed traits after removing the best linear unbiased prediction of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We applied our method to detect loci associated with body mass index variability using the Framingham Heart Study data.