Network analysis of single nucleotide polymorphisms in asthma

Jutta Renkonen^1,2, Sakari Joenväärä^1,2, Ville Parviainen^1,2, Pirkko Mattila^1,2, Risto Renkonen^1,2
1Transplantation Laboratory and Infection Biology Research Program, Haartman Institute, University of Helsinki, Helsinki; ²HUSLAB, Helsinki University Central Hospital, Helsinki, Finland

Background: Asthma is a chronic inflammatory disease of the airways with a complex genetic background. In this study, we carried out a meta-analysis of single nucleotide polymorphisms (SNPs) thought to be associated with asthma.
Methods: The literature (PubMed) was searched for SNPs within genes relevant in asthma. The SNP-modified genes were converted to corresponding proteins, and their protein–protein interactions were searched from six different databases. This interaction network was analyzed using annotated vocabularies (ontologies), such as the Gene Ontology and Nature pathway interaction databases.
Results: In total, 127 genes with SNPs related to asthma were found in the literature. The corresponding proteins were then entered into a large protein–protein interaction network with the help of various databases. Ninety-six SNP-related proteins had more than one interacting protein each, and a network containing 309 proteins and 644 connections was generated. This network was significantly enriched with a gene ontology entitled "protein binding" and several of its daughter categories, including receptor binding and cytokine binding, when compared with the background human proteome. In the detailed analysis, the chemokine network, including eight proteins and 13 toll-like receptors, were shown to interact with each other. Of great interest are the nonsynonymous SNPs which code for an alternative amino acid sequence of proteins and, of the toll-like receptor network, TLR1, TLR4, TLR5, TLR6, TLR10, IL4R, and IL13 are among these.
Conclusions: Protein binding, toll-like receptors, and chemokines dominated in the asthma-related protein interaction network. Systems level analysis of allergy-related mutations can provide new insights into the pathogenetic mechanisms of disease.

Keywords: asthma, network, pathway pathogenesis, single nucleotide polymorphisms