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A network analysis of the single nucleotide polymorphisms in acute allergic diseases
Author(s) -
Renkonen J.,
Mattila P.,
Parviainen V.,
Joenväärä S.,
ToppilaSalmi S.,
Renkonen R.
Publication year - 2010
Publication title -
allergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.363
H-Index - 173
eISSN - 1398-9995
pISSN - 0105-4538
DOI - 10.1111/j.1398-9995.2009.02101.x
Subject(s) - single nucleotide polymorphism , gene , snp , biology , interaction network , genetics , computational biology , proteome , allergy , bioinformatics , immunology , genotype
Abstract Background: Genetics of acute allergies has focused on identifying single nucleotide polymorphisms (SNPs) within genes relevant in the pathogenesis. In this study, we begin a systems biology analysis of the interconnectivity and biological functions of these genes, their transcripts and their corresponding proteins. Methods: The literature (Pubmed) was searched for SNPs within genes relevant in acute allergic diseases. The SNP‐modified genes were converted to corresponding proteins and their protein–protein interactions were searched from six different databases. This interaction network was analysed with annotated vocabularies (ontologies), such as Gene Ontology, Reactome and Nature pathway interaction database. Time‐series transcriptomics was performed with nasal epithelial cells obtained from allergic patients and their healthy control subjects. Results: A total of 39 genes with SNPs related to acute allergic diseases were found from a literature search. The corresponding proteins were then hooked into a large protein–protein interaction network with the help of various databases. Twenty‐five SNP‐related proteins had more than one interacting protein and a network contained 95 proteins, and 182 connections could be generated. This network was 10‐fold enriched with protein kinases and proteins involved in the host–virus interaction compared with background human proteome. Finally, eight of the 95 nodes on our network displayed nasal epithelial transcriptomal regulation in a time‐series analysis collected from birch allergic patients during the spring pollen season. Conclusions: Signal transduction with special reference to host–virus interactions dominated in the allergy‐related protein interaction network. Systems level analysis of allergy‐related mutation can provide new insights into pathogenetic mechanisms of the diseases.