M58 - Cross-Tissue EQTL Enrichment of Associations In Schizophrenia

Abstract

Background In the era of Big Data, genome-wide association studies (GWASs) have been the main instrument to better our understanding of the genetics behind human traits. The schizophrenia GWAS by the psychiatric genomics consortium (PGC) identified many loci plausibly involved in the etiology of the disorder [Ripke et al., 2014]. However, the picture appears to be far from complete [Lichtenstein, 2009; Polderman, 2015; Gejman, 2010; Lee, 2012]. Judging by the number of non-coding variants identified by GWASs of schizophrenia and other complex traits, many causal variants are likely to affect the regulation of the genes involved rather than severely disrupt their function. Expression quantitative trait loci (eQTLs) are genomic loci that contribute to variation in levels of mRNA. It is known [Bacanu, 2014] that many eQTLs are associated with schizophrenia, as well as other phenotypes [Nicolae, 2010]. Methods Given known pleiotropy between schizophrenia and other traits, we looked for association enrichment of eQTLs in tissues not obviously relevant to psychiatric disorders (blood, adipose, LCL, and skin [Buil, 2015]). In order to consolidate any evidence of tissue-specificity, we further looked for differential enrichment in different ENCODE functional annotation categories. We used summary p-value statistics from schizophrenia as well as body mass index, Crohn's disease, height, systolic blood pressure and type II diabetes GWASs. We matched the eQTLs to SNP sets with similar minor allele frequencies (MAF) and distances from their respective transcription start sites (TSS), and no evidence of association with expression levels of any genes. We further subdivided eQTLs into proximal and distal eQTLs, according to their position relative to the TSS or to their affiliation to promoters, and we annotated them according to their ENCODE designation. We visualized the enrichment in fold enrichment plots, screened it using Fisher tests and assessed its extent by regressing the squared association z-score against SNP affiliations and LD-score. Results Significant enrichment was seen in adipose (beta=0.24, p=2.2E-06), LCL (beta=0.27, p=4.0E-08) and skin (beta=0.23, p=2.7E-06) tissues. The enrichment was as widespread as that observed in another highly polygenic trait such as height, and more widespread than in traits such as body mass index (adipose and skin) or blood pressure (adipose). The schizophrenia association extent does not appear to depend on the eQTLs' distance from the TSS nor from their explicit affiliation to specific functional elements, as defined by ENCODE, suggesting that risk alleles for schizophrenia could frequently act in many different tissue contexts. Discussion Our results are in line with the notion that schizophrenia is a disorder involving many tissues and known pleiotropy with cardiovascular and immune diseases back our findings. The statistical power of the underlying GWAS does play a role in the detection of association enrichment of the sort we sought. Polygenicity, however, is also a major factor, as exemplified by the results for height, body mass index and blood pressure. In summary, we find that looking for functional correlates of schizophrenia risk loci in non-obvious tissues is productive, and this could be because of either pleiotropy or increased effectiveness of variants that work in many different environmental contexts. This suggests the utility of large, single tissue eQTL experiments in the study of schizophrenia in addition to smaller, multiple tissue approaches.