Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms.
BACKGROUND
Complex 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.


RESULTS
We 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.


CONCLUSIONS
Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.
The Centre for Individualized Medication, Linköping University Hospital, Linköping University, Linköping, Sweden.
Fredrik
F
Barrenäs
Sreenivas
S
Chavali
Alexessander Couto
AC
Alves
Lachlan
L
Coin
Marjo-Riitta
MR
Jarvelin
Rebecka
R
Jörnsten
Michael A
MA
Langston
Adaikalavan
A
Ramasamy
Gary
G
Rogers
Hui
H
Wang
Mikael
M
Benson
D030541:Databases, Genetic; D016222:Fibroblast Growth Factor 2 / Q000235:genetics / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D058685:Genetic Pleiotropy; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D007249:Inflammation / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D020641:Polymorphism, Single Nucleotide; D060066:Protein Interaction Maps; D034741:RNA, Small Interfering / Q000235:genetics / Q000378:metabolism; D006255:Rhinitis, Allergic, Seasonal / Q000235:genetics*; D012680:Sensitivity and Specificity
D034741:RNA, Small Interfering; D016222:Fibroblast Growth Factor 2