Z-G Shen1, J-L Guo, D-S Li. 1. Department of Emergency Surgery, Tongji Hospital, Shanghai, China. zugangshen22@hotmail.com.
Abstract
OBJECTIVES: Severe sepsis after trauma still associated with a high mortality rate in intensive care units (ICU). In this study we aimed to identify genes related to multiple trauma complicated by severe sepsis. MATERIALS AND METHODS: The gene expression profile dataset GSE12624 including 36 samples of traumatic patients not complicated by sepsis and 34 traumatic patients complicated by sepsis was downloaded from GEO (Gene Expression Omnibus) database. The limma package in R was applied to identify differentially expressed genes (DEGs) between these two groups of samples. All the DEGs were divided into up- and down-regulation groups according to the changes of their expression value, which were then subjected to GO enrichment analysis. Two genes with largest changes among the up- and down-regulation groups were selected. Interaction networks based on these two genes were constructed using HitPredict software and then pathway enrichment analysis for the networks were performed by WebGestalt software. RESULTS: A total of 21 up-regulated genes and 37 down-regulated genes were obtained, which were mainly related to GO terms "endopeptidase inhibitor activity" and "response to wounding", respectively. The |logFC| of genes PLAU (urokinase-type plasminogen activator) and MMP8 (matrix metalloproteinase-8) ranked first in down-regulated or up-regulated list. There were 18 genes which can interact with PLAU at a high degree of confidence while there were 5 genes with MMP8. Further analysis showed that PLAU was closely associated with the pathway "complement and coagulation cascades". CONCLUSIONS: PLAU and MMP8 may act as potential targets for diagnosis and therapy of trauma complicated by sepsis.
OBJECTIVES: Severe sepsis after trauma still associated with a high mortality rate in intensive care units (ICU). In this study we aimed to identify genes related to multiple trauma complicated by severe sepsis. MATERIALS AND METHODS: The gene expression profile dataset GSE12624 including 36 samples of traumaticpatients not complicated by sepsis and 34 traumaticpatients complicated by sepsis was downloaded from GEO (Gene Expression Omnibus) database. The limma package in R was applied to identify differentially expressed genes (DEGs) between these two groups of samples. All the DEGs were divided into up- and down-regulation groups according to the changes of their expression value, which were then subjected to GO enrichment analysis. Two genes with largest changes among the up- and down-regulation groups were selected. Interaction networks based on these two genes were constructed using HitPredict software and then pathway enrichment analysis for the networks were performed by WebGestalt software. RESULTS: A total of 21 up-regulated genes and 37 down-regulated genes were obtained, which were mainly related to GO terms "endopeptidase inhibitor activity" and "response to wounding", respectively. The |logFC| of genes PLAU (urokinase-type plasminogen activator) and MMP8 (matrix metalloproteinase-8) ranked first in down-regulated or up-regulated list. There were 18 genes which can interact with PLAU at a high degree of confidence while there were 5 genes with MMP8. Further analysis showed that PLAU was closely associated with the pathway "complement and coagulation cascades". CONCLUSIONS:PLAU and MMP8 may act as potential targets for diagnosis and therapy of trauma complicated by sepsis.