A protein interaction network associated with asthma.
Identifying candidate genes related to complex diseases or traits and mapping their relationships require a system-level analysis at a cellular scale. The objective of the present study is to systematically analyze the complex effects of interrelated genes and provide a framework for revealing their relationships in association with a specific disease (asthma in this case). We observed that protein-protein interaction (PPI) networks associated with asthma have a power-law connectivity distribution as many other biological networks have. The hub nodes and skeleton substructure of the result network are consistent with the prior knowledge about asthma pathways, and also suggest unknown candidate target genes associated with asthma, including GNB2L1, BRCA1, CBL, and VAV1. In particular, GNB2L1 appears to play a very important role in the asthma network through frequent interactions with key proteins in cellular signaling. This network-based approach represents an alternative method for analyzing the complex effects of candidate genes associated with complex diseases and suggesting a list of gene drug targets. The full list of genes and the analysis details are available in the following online supplementary materials: http://biosoft.kaist.ac.kr:8080/resources/asthma_ppi.
Hwang
Sohyun
S
Department of Bio and Brain Engineering, KAIST, 373-1 Guseong-dong, Yuseong-gu, Deajeon, Republic of Korea. winnie79@biosoft.kaist.ac.kr
Son
Seung-Woo
SW
Kim
Sang Cheol
SC
Kim
Young Joo
YJ
Jeong
Hawoong
H
Lee
Doheon
D
D001249:Asthma / Q000235:genetics / Q000378:metabolism* / Q000473:pathology; D002468:Cell Physiological Phenomena; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D011485:Protein Binding; D025941:Protein Interaction Mapping; D049490:Systems Biology