Polygenic risk assessment reveals pleiotropy between sarcoidosis and inflammatory disorders in the context of genetic ancestry.

Sarcoidosis is a complex disease of unknown etiology characterized by the presence of granulomatous inflammation. Though various immune system pathways have been implicated in disease, the relationship between the genetic determinants of sarcoidosis and other inflammatory disorders has not been characterized. Herein, we examined the degree of genetic pleiotropy common to sarcoidosis and other inflammatory disorders to identify shared pathways and disease systems pertinent to sarcoidosis onset. To achieve this, we quantify the association of common variant polygenic risk scores from nine complex inflammatory disorders with sarcoidosis risk. Enrichment analyses of genes implicated in pleiotropic associations were further used to elucidate candidate pathways. In European-Americans, we identify significant pleiotropy between risk of sarcoidosis and risk of asthma (R2=2.03%; P=8.89 × 10-9), celiac disease (R2=2.03%; P=8.21 × 10-9), primary biliary cirrhosis (R2=2.43%; P=2.01 × 10-10) and rheumatoid arthritis (R2=4.32%; P=2.50 × 10-17). These associations validate in African Americans only after accounting for the proportion of genome-wide European ancestry, where we demonstrate similar effects of polygenic risk for African-Americans with the highest levels of European ancestry. Variants and genes implicated in European-American pleiotropic associations were enriched for pathways involving interleukin-12, interleukin-27 and cell adhesion molecules, corroborating the hypothesized immunopathogenesis of disease.

An interaction quantitative trait loci tool implicates epistatic functional variants in an apoptosis pathway in smallpox vaccine eQTL data.

Expression quantitative trait loci (eQTL) studies have functionalized nucleic acid variants through the regulation of gene expression. Although most eQTL studies only examine the effects of single variants on transcription, a more complex process of variant-variant interaction (epistasis) may regulate transcription. Herein, we describe a tool called interaction QTL (iQTL) designed to efficiently detect epistatic interactions that regulate gene expression. To maximize biological relevance and minimize the computational and hypothesis testing burden, iQTL restricts interactions such that one variant is within a user-defined proximity of the transcript (cis-regulatory). We apply iQTL to a data set of 183 smallpox vaccine study participants with genome-wide association study and gene expression data from unstimulated samples and samples stimulated by inactivated vaccinia virus. While computing only 0.15% of possible interactions, we identify 11 probe sets whose expression is regulated through a variant-variant interaction. We highlight the functional epistatic interactions among apoptosis-related genes, DIABLO, TRAPPC4 and FADD, in the context of smallpox vaccination. We also use an integrative network approach to characterize these iQTL interactions in a posterior network of known prior functional interactions. iQTL is an efficient, open-source tool to analyze variant interactions in eQTL studies, providing better understanding of the function of epistasis in immune response and other complex phenotypes.