SMUT: Multi-SNP Mediation Intersection-Union Test

• Activity Number: 679 - Variable Selection and Prediction Models for Genomic Data
• Type: Contributed
• Date/Time: Thursday, August 2, 2018 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Wujuan Zhong* and Cassandra Spracklen and Karen Mohlke and Xiaojing Zheng and Jason P Fine and Yun Li
• Companies: University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill
• Keywords: mediation analysis; multiple SNPs; intersection-union test

Abstract

Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in regions resulting in no protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing mediation effects of multiple correlated SNPs via a mediator (for example, the expression of a gene in the neighborhood) on phenotypic outcome. We propose SMUT, multi-SNP Mediation intersection-Union Test to fill in the methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 77%, power gains over alternative methods. In addition, SMUT was able to confirm known mediators in a real dataset of Finns for plasma adiponectin level, while many alternative methods failed to generate significant results. We believe SMUT will become a useful tool to shed light on mechanisms underlying GWAS variants, facilitating functional follow-up.