PLoS ONE (Jan 2012)

Identification of gene networks and pathways associated with Guillain-Barré syndrome.

  • Kuo-Hsuan Chang,
  • Tzi-Jung Chuang,
  • Rong-Kuo Lyu,
  • Long-Sun Ro,
  • Yih-Ru Wu,
  • Hong-Shiu Chang,
  • Chin-Chang Huang,
  • Hung-Chou Kuo,
  • Wen-Chuin Hsu,
  • Chun-Che Chu,
  • Chiung-Mei Chen

DOI
https://doi.org/10.1371/journal.pone.0029506
Journal volume & issue
Vol. 7, no. 1
p. e29506

Abstract

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BACKGROUND: The underlying change of gene network expression of Guillain-Barré syndrome (GBS) remains elusive. We sought to identify GBS-associated gene networks and signaling pathways by analyzing the transcriptional profile of leukocytes in the patients with GBS. METHODS AND FINDINGS: Quantitative global gene expression microarray analysis of peripheral blood leukocytes was performed on 7 patients with GBS and 7 healthy controls. Gene expression profiles were compared between patients and controls after standardization. The set of genes that significantly correlated with GBS was further analyzed by Ingenuity Pathways Analyses. 256 genes and 18 gene networks were significantly associated with GBS (fold change ≥2, P<0.05). FOS, PTGS2, HMGB2 and MMP9 are the top four of 246 significantly up-regulated genes. The most significant disease and altered biological function genes associated with GBS were those involved in inflammatory response, infectious disease, and respiratory disease. Cell death, cellular development and cellular movement were the top significant molecular and cellular functions involved in GBS. Hematological system development and function, immune cell trafficking and organismal survival were the most significant GBS-associated function in physiological development and system category. Several hub genes, such as MMP9, PTGS2 and CREB1 were identified in the associated gene networks. Canonical pathway analysis showed that GnRH, corticotrophin-releasing hormone and ERK/MAPK signaling were the most significant pathways in the up-regulated gene set in GBS. CONCLUSIONS: This study reveals the gene networks and canonical pathways associated with GBS. These data provide not only networks between the genes for understanding the pathogenic properties of GBS but also map significant pathways for the future development of novel therapeutic strategies.