Trans-Ethnic Meta-Analysis of Metabolic Syndrome in a Multi-Ethnic Study

• Activity Number: 237 - SPEED:Statistical Methods for GWAs, Genetics, Genomics, and Other Omics Studies, Part 1
• Type: Contributed
• Date/Time: Monday, July 29, 2019 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Emileigh L. Willems* and Jia Y. Wan and Trina M. Norden-Krichmar and Karen L. Edwards and Stephanie A. Santorico
• Companies: University of Colorado Denver and University of California Irvine and University of California Irvine and University of California Irvine and University of Colorado Denver
• Keywords: meta-analysis; trans-ethnic; genome-wide association; metabolic syndrome; allelic heterogeneity

Abstract

Genome-wide association studies (GWAS) have been used to find several genetic associations across many phenotypes. To improve the power of GWAS and generalize associations across ethnic groups, trans-ethnic meta-analysis methods are used to combine GWAS results from diverse ancestries. The goal of our study is to find genetic associations for eight metabolic syndrome traits using a trans-ethnic meta-analysis. Traits were measured in the GENetics of Non-Insulin dependent Diabetes mellitus (GENNID) Study which consists of African-, European-, Japanese-, and Mexican-American samples. GWAS results from the four ethnic groups were combined using four meta-analysis methods: fixed effects, random effects, TransMeta, and MR-MEGA. We empirically compare the meta-analysis methods using the GENNID results, discuss which types of loci are better detected by each of the methods, and validate our results using previous genetic studies. We will provide a more detailed comparison of the two trans-ethnic methods, TransMeta and MR-MEGA. Time allowing, results from a simulation study will be provided comparing the four methods.