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Identification of risk factors for sepsis-associated mortality by gene expression profiling analysis

  • Authors:
    • Yan Qi
    • Xinxin Chen
    • Na Wu
    • Chuihui Ma
    • Xueling Cui
    • Zhonghui Liu

  • View Affiliations

  • Published online on: January 25, 2018     https://doi.org/10.3892/mmr.2018.8491
  • Pages: 5350-5355
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
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Abstract

Sepsis is a common cause of mortality due to systemic infection. Although numerous studies have investigated this life-threatening condition, there remains a lack of suitable markers to evaluate the severity of sepsis. The present study focused on the identification of risk factors for sepsis‑associated mortality by genome‑wide expression profiling. Initially, the GEO2R web tool was used to identify the differentially expressed genes (DEGs) between sepsis survivors and nonsurvivors. It was identified that the upregulated DEGs in the nonsurvivors compared with survivors were highly enriched in the type I interferon (IFN‑I) signaling pathway. Furthermore, the associations of the upregulated genes were analyzed by STRING and the results demonstrated that a set of proteins in IFN‑I signaling pathway closely interacted with each other. To further investigate whether the IFN‑I signaling pathway is dysregulated in a subset of patients with a high risk of mortality due to sepsis, in this case neonates, the DEGs between the cord blood mononuclear cells of neonates and adult peripheral blood mononuclear cells were analyzed. It was identified that DEGs were not enriched in IFN‑I signaling in the blood of untreated neonates and adults; however, IFN‑I signaling was upregulated in the lipopolysaccharide (LPS)‑treated cord blood mononuclear cells of healthy neonates compared with the LPS‑treated peripheral blood mononuclear cells of adults. In addition, these data revealed that the proteins involved in the IFN‑I signaling pathway possessed a higher number of interacting partners. These results indicated that upregulated IFN‑I signaling may be a high-risk factor for mortality due to sepsis.
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April-2018
Volume 17 Issue 4

Print ISSN: 1791-2997
Online ISSN:1791-3004

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  • Journal Metrics
  • Impact Factor: 3.4
  • Ranked Medicine Research and Experimental
    (total number of cites)
  • CiteScore: 7.6
  • CiteScore Rank: Q1: #82/347 Biochemistry, Genetics and Molecular Biology
  • Source Normalized Impact per Paper (SNIP): 0.647
  • SCImago Journal Rank (SJR): 0.781
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Spandidos Publications style
Qi Y, Chen X, Wu N, Ma C, Cui X and Liu Z: Identification of risk factors for sepsis-associated mortality by gene expression profiling analysis. Mol Med Rep 17: 5350-5355, 2018.
APA
Qi, Y., Chen, X., Wu, N., Ma, C., Cui, X., & Liu, Z. (2018). Identification of risk factors for sepsis-associated mortality by gene expression profiling analysis. Molecular Medicine Reports, 17, 5350-5355. https://doi.org/10.3892/mmr.2018.8491
MLA
Qi, Y., Chen, X., Wu, N., Ma, C., Cui, X., Liu, Z."Identification of risk factors for sepsis-associated mortality by gene expression profiling analysis". Molecular Medicine Reports 17.4 (2018): 5350-5355.
Chicago
Qi, Y., Chen, X., Wu, N., Ma, C., Cui, X., Liu, Z."Identification of risk factors for sepsis-associated mortality by gene expression profiling analysis". Molecular Medicine Reports 17, no. 4 (2018): 5350-5355. https://doi.org/10.3892/mmr.2018.8491