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Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis

Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and ther...

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Detalles Bibliográficos
Autores principales: Yang, Fang, Wang, Yumei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5952067/
https://www.ncbi.nlm.nih.gov/pubmed/29805480
http://dx.doi.org/10.3892/etm.2018.6026
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author Yang, Fang
Wang, Yumei
author_facet Yang, Fang
Wang, Yumei
author_sort Yang, Fang
collection PubMed
description Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis.
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spelling pubmed-59520672018-05-27 Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis Yang, Fang Wang, Yumei Exp Ther Med Articles Sepsis is a type of systemic inflammatory response syndrome with high morbidity and mortality. Skeletal muscle dysfunction is one of the major complications of sepsis that may also influence the outcome of sepsis. The aim of the present study was to explore and identify potential mechanisms and therapeutic targets of sepsis. Systemic bioinformatics analysis of skeletal muscle gene expression profiles from the Gene Expression Omnibus was performed. Differentially expressed genes (DEGs) in samples from patients with sepsis and control samples were screened out using the limma package. Differential co-expression and coregulation (DCE and DCR, respectively) analysis was performed based on the Differential Co-expression Analysis package to identify differences in gene co-expression and coregulation patterns between the control and sepsis groups. Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways of DEGs were identified using the Database for Annotation, Visualization and Integrated Discovery, and inflammatory, cancer and skeletal muscle development-associated biological processes and pathways were identified. DCE and DCR analysis revealed several potential therapeutic targets for sepsis, including genes and transcription factors. The results of the present study may provide a basis for the development of novel therapeutic targets and treatment methods for sepsis. D.A. Spandidos 2018-06 2018-04-03 /pmc/articles/PMC5952067/ /pubmed/29805480 http://dx.doi.org/10.3892/etm.2018.6026 Text en Copyright: © Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Yang, Fang
Wang, Yumei
Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title_full Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title_fullStr Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title_full_unstemmed Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title_short Systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
title_sort systemic bioinformatics analysis of skeletal muscle gene expression profiles of sepsis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5952067/
https://www.ncbi.nlm.nih.gov/pubmed/29805480
http://dx.doi.org/10.3892/etm.2018.6026
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