Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS

Amanda Dobbyn,Solveig K Sieberts,Pamela Sklar,Benjamin S Glicksberg,Kiran Girdhar,Thanneer M Perumal,Claudia Giambartolomei,Dalila Pinto,Yan Jiang,Panos Roussos,Bernie Devlin,Robin Kramer,Towfique Raj,Enrico Domenici,Douglas M Ruderfer,Gabriel E Hoffman,Eli A Stahl,James Boocock,Schahram Akbarian,Laura Sloofman ,Laura Huckins

doi:10.1016/j.ajhg.2018.04.011

Abstract

Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up.

Highlights

Significant advances in understanding the genetic architecture of schizophrenia (MIM: 181500) have occurred within the last 10 years
Expression quantitative trait loci, which are responsible for a significant proportion of variation in gene expression, could serve as a link between the numerous non-coding genetic associations that have been identified in genome-wide association study (GWAS) and susceptibility to common diseases directly through their association with gene expression regulation.[1,2,3,4]
We found that 40 loci contained genes with strong evidence of co-localization between Expression quantitative trait loci (eQTL) and GWAS signatures, with posterior probability of H4 (PPH4) R 0.8 (Table 2)

Summary

Introduction

Significant advances in understanding the genetic architecture of schizophrenia (MIM: 181500) have occurred within the last 10 years. For common variants identified in genome-wide association studies (GWASs), the success in locus identification is not yet matched by an understanding of their underlying basic mechanism or effect on pathophysiology. Expression quantitative trait loci (eQTL), which are responsible for a significant proportion of variation in gene expression, could serve as a link between the numerous non-coding genetic associations that have been identified in GWASs and susceptibility to common diseases directly through their association with gene expression regulation.[1,2,3,4] results from eQTL mapping studies have been successfully utilized to identify genes and causal variants from GWASs for various complex phenotypes, including asthma (MIM: 600807), body mass index (MIM: 601665), celiac disease (MIM: 212750), and Crohn disease (MIM: 266600).[5,6,7,8]. Recent findings indicating that conditionally independent eQTL are widespread[9,10,11,12] motivate examination of the extent to which considering conditional eQTL may provide additional power to identify likely causal genes in a GWAS locus. Recent reports provide evidence that conditional eQTL are less frequently shared across tissues than primary

Methods

Results

Conclusion