Contribution of enhancer-driven and master-regulator genes to autoimmune disease revealed using functionally informed SNP-to-gene linking strategies
Gene regulation is known to play a fundamental role in human disease, but mechanisms of regulation vary greatly across genes. Here, we explore the contributions to the disease of two types of genes: genes whose regulation is driven by enhancer regions as opposed to promoter regions (Enhancer-driven) and genes that regulate many other genes in trans (Master-regulator). We link these genes to SNPs using a comprehensive set of SNP-to-gene (S2G) strategies and apply stratified LD score regression to the resulting SNP annotations to draw three main conclusions about 11 autoimmune diseases and blood cell traits (average Ncase=13K across 6 autoimmune diseases, average N=443K across 5 blood cell traits). First, several characterizations of Enhancer-driven genes defined in blood using functional genomics data (e.g. ATAC-seq, RNA-seq, PC-HiC) are conditionally informative for autoimmune disease heritability, after conditioning on a broad set of regulatory annotations from the baseline-LD model. Second, Master-regulator genes defined using trans-eQTL in blood are also conditionally informative for autoimmune dis- ease heritability. Third, integrating Enhancer-driven and Master-regulator gene sets with protein-protein interaction (PPI) network information magnified their disease signal. The resulting PPI-enhancer gene score produced >2x stronger conditional signal (maximum standardized SNP annotation effect size (tau-star) = 2.0 (s.e. 0.3) vs. 0.91 (s.e. 0.21)), and >2x stronger gene-level enrichment for approved autoimmune disease drug targets (5.3x vs. 2.1x), as compared to the recently proposed Enhancer Domain Score (EDS). In each case, using functionally informed S2G strategies to link genes to SNPs that may regulate them produced much stronger disease signals (4.1x-13x larger tau-star values) than conventional window-based S2G strategies. We conclude that our characterizations of Enhancer-driven and Master-regulator genes identify gene sets that are important for autoimmune disease, and that combining those gene sets with functionally informed S2G strategies enables us to identify SNP annotations in which disease heritability is concentrated.
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