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Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 21, 2016; 22(3): 949-960
Published online Jan 21, 2016. doi: 10.3748/wjg.v22.i3.949
Application of computational methods in genetic study of inflammatory bowel disease
Jin Li, Zhi Wei, Hakon Hakonarson
Jin Li, Hakon Hakonarson, Center for Applied Genomics, Abramson Research Center, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
Zhi Wei, Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, United States
Hakon Hakonarson, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
Hakon Hakonarson, Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
Author contributions: All authors wrote, edited the manuscript and approved the final version.
Conflict-of-interest statement: The authors have no conflict of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Zhi Wei, PhD, Associate Professor, Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, United States. zhiwei04@gmail.com
Telephone: +1-973-6424497 Fax: +1-973-596577
Received: September 2, 2015
Peer-review started: September 2, 2015
First decision: October 14, 2015
Revised: November 4, 2015
Accepted: November 24, 2015
Article in press: November 24, 2015
Published online: January 21, 2016
Processing time: 135 Days and 11.7 Hours
Abstract

Genetic factors play an important role in the etiology of inflammatory bowel disease (IBD). The launch of genome-wide association study (GWAS) represents a landmark in the genetic study of human complex disease. Concurrently, computational methods have undergone rapid development during the past a few years, which led to the identification of numerous disease susceptibility loci. IBD is one of the successful examples of GWAS and related analyses. A total of 163 genetic loci and multiple signaling pathways have been identified to be associated with IBD. Pleiotropic effects were found for many of these loci; and risk prediction models were built based on a broad spectrum of genetic variants. Important gene-gene, gene-environment interactions and key contributions of gut microbiome are being discovered. Here we will review the different types of analyses that have been applied to IBD genetic study, discuss the computational methods for each type of analysis, and summarize the discoveries made in IBD research with the application of these methods.

Keywords: Inflammatory bowel disease; Computational methods; Genome-wide association study; Pathway analysis; Gene-gene interaction; Gene-environment interaction; Pleiotropy; Risk prediction

Core tip: Computational methods have rapidly progressed during the last a few years, which rendered us the ability to analyze genotype data on a genome-wide level. The application of these methods in inflammatory bowel disease (IBD) genetic study yielded productive results. We discuss the major types of analyses in genome-wide study, and the different computational methods used in each type of analysis. We also show how these computation methods were used in the IBD genetic study and the major findings achieved.