Abstract
BackgroundComplex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.ResultsWe identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.ConclusionsModules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.
Highlights
Complex diseases are associated with altered interactions between thousands of genes
We examined whether the disease-specific core Suceptibility Module (SuM) were enriched for genes harboring diseaseassociated singlenucleotide polymorphism (SNP) by analyzing complex diseases for which gene expression microarray data from relevant cells or tissues were available in the public domain, and where genome-wide association study (GWAS) had identified genes harboring disease-associated SNPs
We found that increasingly stringent cutoffs for core SuMs were associated with stronger enrichment of GWAS genes (Figure 2b)
Summary
Complex diseases are associated with altered interactions between thousands of genes. Complex diseases show considerable comorbidity and are associated with altered interactions between thousands of genes This suggests a need to find generally applicable principles to study multiple diseases and genes. We hypothesized that modules containing the most interconnected complex disease-associated genes would be enriched for disease-associated SNPs (note that highly interconnected disease genes have many interactions with other disease genes, while hub genes have interactions with any other gene). This hypothesis was based on recent discoveries in network medicine
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