Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

Mathias Chamaillard,Finja Büchel,Thomas Gasser,Andreas Zell,Clemens Wrzodek,Florian Mittag,Manu Sharma

doi:10.1371/journal.pone.0078577

Abstract

Genome-wide association studies (GWAS) led to the identification of numerous novel loci for a number of complex diseases. Pathway-based approaches using genotypic data provide tangible leads which cannot be identified by single marker approaches as implemented in GWAS. The available pathway analysis approaches mainly differ in the employed databases and in the applied statistics for determining the significance of the associated disease markers.So far, pathway-based approaches using GWAS data failed to consider the overlapping of genes among different pathways or the influence of protein–interactions. We performed a multistage integrative pathway (MIP) analysis on three common diseases - Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) - incorporating genotypic, pathway, protein- and domain-interaction data to identify novel associations between these diseases and pathways. Additionally, we assessed the sensitivity of our method by studying the influence of the most significant SNPs on the pathway analysis by removing those and comparing the corresponding pathway analysis results. Apart from confirming many previously published associations between pathways and RA, CD and T1D, our MIP approach was able to identify three new associations between disease phenotypes and pathways. This includes a relation between the influenza-A pathway and RA, as well as a relation between T1D and the phagosome and toxoplasmosis pathways. These results provide new leads to understand the molecular underpinnings of these diseases.The developed software herein used is available at http://www.cogsys.cs.uni-tuebingen.de/software/GWASPathwayIdentifier/index.htm.

Highlights

Genome-wide association studies (GWAS) typically focus on single marker statistics to obtain top hits [1]
A total of 361,963 SNPs for Crohn’s disease (CD), 362,229 SNPs for rheumatoid arthritis (RA), and 362,548 SNPs for type 1 diabetes (T1D) encompassing 16,820 genes were included in the study
We identified the influenza-A pathway for RA as well as the phagosome and toxoplasmosis pathway for T1D, which represent as-yet unknown genotypic links to the disease phenotype

Summary

Introduction

GWAS typically focus on single marker statistics to obtain top hits [1]. This approach led to the identification of new candidate regions/SNPs in multiple disorders. In the National Human Genome Research Institute catalogue of September 2012, only 4,392 out of 8,965 studies reported a p-value smaller than 1028, a common statistical threshold required for genome-wide significance. This argues in favor of applying new methodologies to unravel the complex architecture of common diseases [2]. Pathway-based studies are preformed because risk alleles for any given phenotype are more likely to be distributed among certain groups of genes whose functionalities are closely related [3]

Methods

Results

Conclusion