SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease
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Le résumé fourni par la source
Abstract 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 disease of two types of genes: genes whose regulation is driven by enhancer regions as opposed to promoter regions (enhancer-related) and genes that regulate other genes in trans (candidate 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 N case =13K across 6 autoimmune diseases, average N =443K across 5 blood cell traits). First, several characterizations of enhancer-related 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, candidate master-regulator genes defined using trans-eQTL in blood are also conditionally informative for autoimmune disease heritability. Third, integrating enhancer-related and candidate 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 ( τ * ) = 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 τ * values) than conventional window-based S2G strategies. We conclude that our characterizations of enhancer-related and candidate 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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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease
- Date Crossref
- 03/09/2020
- Éditeur
- openRxiv
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
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Harvard University pays non établi dans la noticeUniversité ou école supérieure
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Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science pays non établi dans la noticeUniversité ou école supérieure
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Broad Institute pays non établi dans la noticeOrganisation à but non lucratif
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Lucile Packard Children's Hospital pays non établi dans la noticeÉtablissement de santé
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Stanford University Lucile Packard Children’s Hospital pays non établi dans la noticeUniversité ou école supérieure
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Harvard T. H. Chan School of Public Health Department of Epidemiology pays non établi dans la noticeUniversité ou école supérieure
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Harvard T.H. Chan School of Public Health Department of Biostatistics pays non établi dans la noticeUniversité ou école supérieure
Harvard University, Department of Electrical Engineering and Computer Science — Massachusetts Institute of Technology et Broad Institute, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.