A functional genomics predictive network model identifies regulators of inflammatory bowel disease

Lauren A. Peters, Jacqueline Perrigoue, Arthur Mortha, Alina Iuga, Won Min Song, Eric M. Neiman, Sean R. Llewellyn, Antonio Di Narzo, Brian A. Kidd, Shannon E. Telesco, Yongzhong Zhao, Aleksandar Stojmirovic, Jocelyn Sendecki, Khader Shameer, Riccardo Miotto, Bojan Losic, Hardik Shah, Eunjee Lee, Minghui Wang, Jeremiah J. FaithAndrew Kasarskis, Carrie Brodmerkel, Mark Curran, Anuk Das, Joshua R. Friedman, Yoshinori Fukui, Mary Beth Humphrey, Brian M. Iritani, Nicholas Sibinga, Teresa K. Tarrant, Carmen Argmann, Ke Hao, Panos Roussos, Jun Zhu, Bin Zhang, Radu Dobrin, Lloyd F. Mayer, Eric E. Schadt

Research output: Contribution to journalArticlepeer-review

151 Scopus citations

Abstract

A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.

Original languageEnglish (US)
Pages (from-to)1437-1449
Number of pages13
JournalNature Genetics
Volume49
Issue number10
DOIs
StatePublished - Oct 1 2017

ASJC Scopus subject areas

  • Genetics

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