Identification of genes and signaling pathways associated with arthrogryposis‑renal dysfunction‑cholestasis syndrome using weighted correlation network analysis

  • Authors:
    • Miao Chai
    • Liju Su
    • Xiaolei Hao
    • Meng Zhang
    • Lihui Zheng
    • Jiabing Bi
    • Xiao Han
    • Bohai Yu
  • View Affiliations

  • Published online on: July 12, 2018     https://doi.org/10.3892/ijmm.2018.3768
  • Pages: 2238-2246
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Abstract

The present study aimed to identify the molecular basis of the arthrogryposis‑renal dysfunction‑cholestasis (ARC) syndrome, which is caused by mutations in the vacuolar protein sorting 33 homolog B (VPS33B) gene. The microarray dataset GSE83192, which contained six liver tissue samples from VPS33B knockout mice and four liver tissue samples from control mice, was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were screened by the Limma package in R software. The DEGs most relevant to ARC were selected via weighted gene co‑expression network analysis to construct a protein‑protein interaction (PPI) network. In addition, module analysis was performed for the PPI network using the Molecular Complex Detection function. Functional and pathway enrichment analyses were also performed for DEGs in the PPI network. Potential drugs for ARC treatment were predicted using the Connectivity Map database. In total, 768 upregulated and 379 downregulated DEGs were detected in the VPS33B knockout mice, while three modules were identified from the PPI network constructed. The DEGs in module 1 (CD83, IL1B and TLR2) were mainly involved in the positive regulation of cytokine production and the Toll‑like receptor (TLR) signaling pathway. The DEGs in module 2 (COL1A1 and COL1A2) were significantly enriched with respect to cellular component organization, extracellular matrix‑receptor interactions and focal adhesion. The DEGs in module 3 (ABCG8 and ABCG3) were clearly associated with sterol absorption and transport. Furthermore, mercaptopurine was identified to be a potential drug (connectivity score=‑0.939) for ARC treatment. In conclusion, the results of the current study may help to further understand the pathology of ARC, and the DEGs identified in these modules may serve as therapeutic targets.
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October-2018
Volume 42 Issue 4

Print ISSN: 1107-3756
Online ISSN:1791-244X

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Spandidos Publications style
Chai M, Su L, Hao X, Zhang M, Zheng L, Bi J, Han X and Yu B: Identification of genes and signaling pathways associated with arthrogryposis‑renal dysfunction‑cholestasis syndrome using weighted correlation network analysis. Int J Mol Med 42: 2238-2246, 2018
APA
Chai, M., Su, L., Hao, X., Zhang, M., Zheng, L., Bi, J. ... Yu, B. (2018). Identification of genes and signaling pathways associated with arthrogryposis‑renal dysfunction‑cholestasis syndrome using weighted correlation network analysis. International Journal of Molecular Medicine, 42, 2238-2246. https://doi.org/10.3892/ijmm.2018.3768
MLA
Chai, M., Su, L., Hao, X., Zhang, M., Zheng, L., Bi, J., Han, X., Yu, B."Identification of genes and signaling pathways associated with arthrogryposis‑renal dysfunction‑cholestasis syndrome using weighted correlation network analysis". International Journal of Molecular Medicine 42.4 (2018): 2238-2246.
Chicago
Chai, M., Su, L., Hao, X., Zhang, M., Zheng, L., Bi, J., Han, X., Yu, B."Identification of genes and signaling pathways associated with arthrogryposis‑renal dysfunction‑cholestasis syndrome using weighted correlation network analysis". International Journal of Molecular Medicine 42, no. 4 (2018): 2238-2246. https://doi.org/10.3892/ijmm.2018.3768