Disease Gene Interaction Pathways: A Potential Framework for How Disease Genes Associate by Disease-Risk Modules

Tobias Eckle,Lina Chen,Wan Li,Jingxie Tai,Liangcai Zhang,Xia Li,Weiming He,Hong Wang,Xu Li

doi:10.1371/journal.pone.0024495

Tobias Eckle, Lina Chen + Show 7 more

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https://doi.org/10.1371/journal.pone.0024495

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Abstract

BackgroundDisease genes that interact cooperatively play crucial roles in the process of complex diseases, yet how to analyze and represent their associations is still an open problem. Traditional methods have failed to represent direct biological evidences that disease genes associate with each other in the pathogenesis of complex diseases. Molecular networks, assumed as ‘a form of biological systems’, consist of a set of interacting biological modules (functional modules or pathways) and this notion could provide a promising insight into deciphering this topic.Methodology/Principal FindingsIn this paper, we hypothesized that disease genes might associate by virtue of the associations between biological modules in molecular networks. Then we introduced a novel disease gene interaction pathway representation and analysis paradigm, and managed to identify the disease gene interaction pathway for 61 known disease genes of coronary artery disease (CAD), which contained 46 disease-risk modules and 182 interaction relationships. As demonstrated, disease genes associate through prescribed communication protocols of common biological functions and pathways.Conclusions/SignificanceOur analysis was proved to be coincident with our primary hypothesis that disease genes of complex diseases interact with their neighbors in a cooperative manner, associate with each other through shared biological functions and pathways of disease-risk modules, and finally cause dysfunctions of a series of biological processes in molecular networks. We hope our paradigm could be a promising method to identify disease gene interaction pathways for other types of complex diseases, affording additional clues in the pathogenesis of complex diseases.

Highlights

Complex diseases are caused by disease risk genes in the form of biological modules or pathways in molecular networks [1,2,3]
According to results from enriched Gene Ontology (GO, http://www.geneontology.org/) functions [43], we found that 167 (91.8%) interaction relationships in the disease gene interaction pathway for coronary artery disease (CAD) shared at least one common function (Figure 6 and Table S2), which suggested that disease genes associated by virtue of interacting disease-risk modules with shared functions, leading to multiple dysfunctions of biological processes in the pathogenesis of complex diseases
We considered function similarities of proteins in a Protein-protein interaction networks (PPINs), and introduced a novel disease gene interaction pathway representation and analysis paradigm

Summary

Introduction

Complex diseases are caused by disease risk genes in the form of biological modules or pathways in molecular networks [1,2,3]. With the accumulation of high-throughput datasets, other computational algorithms have been developed to detect disease-related gene modules or dysfunctional pathways based on the literature or global characteristics of the interactome coupled with gene expression data [1,11]. These methods have effectively identified some disease-risk modules or dysfunctional pathways, it is not clear how biological modules control each other in a cooperative manner and lead to the dysfunctions of multiple biological processes. Molecular networks, assumed as ‘a form of biological systems’, consist of a set of interacting biological modules (functional modules or pathways) and this notion could provide a promising insight into deciphering this topic

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Conclusion