Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease

• Type of Material: Article
• Authors: Urko M. Marigorta, Georgia Institute of Technology; Lee A. Denson, Cincinnati Children's Hospital Medical Center; Jeffrey S. Hyams, Connecticut Children's Medical Center; Kajari Mondal, Emory University; Jarod Prince, Emory University; Thomas D. Walters, University of Toronto; Anne Griffiths, University of Toronto; Joshua D. Noe, Medical College of Wisconsin; Wallace V. Crandall, Ohio State University; Joel R. Rosh, Goryeb Children's Hospital; David R. Mack, Children's Hospital of Eastern Ontario; Richard Kellermayer, Texas Children's Hospital; Melvin B. Heyman, University of California San Francisco; Susan S. Baker, University at Buffalo; Michael C. Stephens, Mayo Clinic; Robert N. Baldassano, University of Pennsylvania; James F. Markowitz, Northwell Health; Mi-Ok Kim, Cincinnati Children's Hospital Medical Center; Marla C. Dubinsky, Mount Sinai Hospital; Judy Cho, Mount Sinai Hospital; Bruce Aronow, Cincinnati Children's Hospital Medical Center; Subra Kugathasan, Emory University; Greg Gibson, Georgia Institute of Technology
• Language: English
• Date: 2017-10-01
• Publisher: Nature Publishing Group
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
• Final Published Version (URL): http://dx.doi.org/10.1038/ng.3936
• Title of Journal or Parent Work: Nature Genetics
• ISSN: 1061-4036
• Volume: 49
• Issue: 10
• Start Page: 1517
• End Page: +
• Grant/Funding Information: This research was supported by Project 3 (G.G., PI) of the NIH program project “Statistical and Quantitative Genetics” grant P01-GM0996568 (B. Weir, University of Washington, Director) as well as research grants from the Crohn's and Colitis Foundation of America (CCFA), New York, to the individual study institutions participating in the RISK study.
• Keywords: VARIANTS; Science & Technology; GENOME-WIDE ASSOCIATION; SUSCEPTIBILITY LOCI; INFLAMMATORY-BOWEL-DISEASE; Genetics & Heredity; GENE-EXPRESSION; QUANTITATIVE TRAIT LOCI; INTESTINE; Life Sciences & Biomedicine; CHILDREN; COLOCALIZATION; INFECTION
• Research Categories: Biology, Genetics

Abstract

Gene expression profiling can be used to uncover the mechanisms by which loci identified through genome-wide association studies (GWAS) contribute to pathology1,2. Given that most GWAS hits are in putative regulatory regions and transcript abundance is physiologically closer to the phenotype of interest2, we hypothesized that summation of risk-alleleassociated gene expression, namely a transcriptional risk score (TRS), should provide accurate estimates of disease risk. We integrate summary-level GWAS and expression quantitative trait locus (eQTL) data with RNA-seq data from the RISK study, an inception cohort of pediatric Crohn's disease3,4. We show that TRSs based on genes regulated by variants linked to inflammatory bowel disease (IBD) not only outperform genetic risk scores (GRSs) in distinguishing Crohn's disease from healthy samples, but also serve to identify patients who in time will progress to complicated disease. Our dissection of eQTL effects may be used to distinguish genes whose association with disease is through promotion versus protection, thereby linking statistical association to biological mechanism. The TRS approach constitutes a potential strategy for personalized medicine that enhances inference from static genotypic risk assessment.