bioRxivBioinformaticsPreprint
Bioinformatics and next generation data analysis reveals the potential role of inflammation in sepsis and its associated complications
Basavaraj Mallikarjunayya VastradiD, Chanabasayya Mallikarjunayya VastradiD
Abstract
Sepsis is the leading systemic inflammatory response syndrome in worldwide, yet relatively little is known about the genes and signaling pathways involved in sepsis progression. The current investigation aimed to elucidate potential key candidate genes and pathways in sepsis and its associated complications. Next generation sequencing (NGS) dataset (GSE185263) was downloaded from the Gene Expression Omnibus (GEO) database, which included data from 348 sepsis samples and 44 normal control samples. Differentially expressed genes (DEGs) were identified using t-tests in the DESeq2 R package. Next, we made use of the g:Profiler to analyze gene ontology (GO) and REACTOME pathway. Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Furthermore, we constructed miRNA-hub gene regulatory network and TF-hub gene regulatory network among hub genes utilizing miRNet and NetworkAnalyst online databases tool and Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis of hub genes through the pROC package in R statistical software. In total, 958 DEGs were identified, of which 479 were up regulated and 479 were down regulated. GO and REACTOME results showed that DEGs mainly enriched in regulation of cellular process, response to stimulus, extracellular matrix organization and immune system. The hub genes of PRKN, KIT, FGFR2, GATA3, ERBB3, CDK1, PPARG, H2BC5, H4C4 and CDC20 might be associated with sepsis and its associated complications. Predicted miRNAs (e.g., hsa-mir-548ad-5p and hsa-mir-2113) and TFs (e.g., YAP1 and TBX5) were found to be significantly correlated with sepsis and its associated complications. In conclusion, the DEGs, relative pathways, hub genes, miRNA and TFs identified in the current investigation might help in understanding of the molecular mechanisms underlying sepsis and its associated complications progression and provide potential molecular targets and biomarkers for sepsis and its associated complications.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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