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This article is part of the supplement: Seventh International Conference on Bioinformatics (InCoB2008)

Open Access Research

A protein interaction based model for schizophrenia study

Pei-Chun Hsu1, Ueng-Cheng Yang12*, Kuan-Hui Shih1, Chih-Min Liu3, Yu-Li Liu4 and Hai-Gwo Hwu3

  • * Corresponding author: Ueng-Cheng Yang

  • † Equal contributors

Author Affiliations

1 Institute of Biomedical Informatics, National Yang-Ming University, Taiwan

2 Center for Systems and Synthetic Biology, National Yang-Ming University, Taiwan

3 Department of Psychiatry, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan

4 Division of Mental Health and Substance Abuse Research, National Health Research Institute, Taipei, Taiwan

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BMC Bioinformatics 2008, 9(Suppl 12):S23  doi:10.1186/1471-2105-9-S12-S23

Published: 12 December 2008



Schizophrenia is a complex disease with multiple factors contributing to its pathogenesis. In addition to environmental factors, genetic factors may also increase susceptibility. In other words, schizophrenia is a highly heritable disease. Some candidate genes have been deduced on the basis of their known function with others found on the basis of chromosomal location. Individuals with multiple candidate genes may have increased risk. However it is not clear what kind of gene combinations may produce the disease phenotype. Their collective effect remains to be studied.


Most pathways except metabolic pathways are rich in protein-protein interactions (PPIs). Thus, the PPI network contains pathway information, even though the upstream-downstream relation of PPI is yet to be explored. Here we have constructed a PPI sub-network by extracting the nearest neighbour of the 36 reported candidate genes described in the literature. Although these candidate genes were discovered by different approaches, most of the proteins formed a cluster. Two major protein interaction modules were identified on the basis of the pairwise distance among the proteins in this sub-network. The large and small clusters might play roles in synaptic transmission and signal transduction, respectively, based on gene ontology annotation. The protein interactions in the synaptic transmission cluster were used to explain the interaction between the NRG1 and CACNG2 genes, which was found by both linkage and association studies. This working hypothesis is supported by the co-expression analysis based on public microarray gene expression.


On the basis of the protein interaction network, it appears that the NRG1-triggered NMDAR protein internalization and the CACNG2 mediated AMPA receptor recruiting may act together in the glutamatergic signalling process. Since both the NMDA and AMPA receptors are calcium channels, this process may regulate the influx of Ca2+. Reducing the cation influx might be one of the disease mechanisms for schizophrenia. This PPI network analysis approach combined with the support from co-expression analysis may provide an efficient way to propose pathogenetic mechanisms for various highly heritable diseases.