Mapping robust trans-associations via cross-condition mediation analyses and validating trait-associations of trans-genes for GWAS SNPs

Seminar Series

Friday, September 6, 2019 - 10:00
8065 Hock Plaza
Lin Chen, PhD

Abstract:  Trans-eQTLs explain a substantial proportion of expression variation, yet are challenging to be detected and replicated since their effects often act in a tissue-specific manner. Many trans-effects are mediated via cis-gene expression and some of those effects are shared across tissue types/conditions. In order to detect robust cis-mediated trans-associations, we proposed a Cross-Condition Mediation method (CCmed-gene). We analyzed data from multiple brain tissue types of the Genotype-Tissue Expression (GTEx) project, and identified 9,631 cis- and trans-gene pairs with gene-level trans-association and me-diation effects, many of which showed evidence of replication in other datasets.  

In order to detect trans-genes for GWAS SNPs of a complex trait, we further developed CCmed-GWAS, and applied it to identify suspected trans-genes associated with 108 known schizophrenia susceptibility loci. To validate the trait-associations of the suspected trans-genes, we conducted several validation analyses including one by a newly proposed two-sample Mendelian Randomization method, MR-Robin, in which we harnessed GWAS summary statistics from the Psychiatric Genomics Consortium and multitissue eQTL statistics from GTEx.

Lin Chen, PhD
Associate Professor
Department of Statistics
The University of Chicago