Unravelling potential biomarkers for acute and chronic brucellosis through proteomic and bioinformatic approaches.
bioinformatics
biomarkers
brucellosis
differential expression analysis
enrichment analysis
proteomics
random forest model
weighted gene co-expression network analysis (WGCNA)
Journal
Frontiers in cellular and infection microbiology
ISSN: 2235-2988
Titre abrégé: Front Cell Infect Microbiol
Pays: Switzerland
ID NLM: 101585359
Informations de publication
Date de publication:
2023
2023
Historique:
received:
03
05
2023
accepted:
27
06
2023
medline:
1
8
2023
pubmed:
31
7
2023
entrez:
31
7
2023
Statut:
epublish
Résumé
This study aimed to identify biomarkers for acute and chronic brucellosis using advanced proteomic and bioinformatic methods. Blood samples from individuals with acute brucellosis, chronic brucellosis, and healthy controls were analyzed. Proteomic techniques and differential expression analysis were used to identify differentially expressed proteins. Co-expression modules associated with brucellosis traits were identified using weighted gene co-expression network analysis (WGCNA). 763 differentially expressed proteins were identified, and two co-expression modules were found to be significantly associated with brucellosis traits. 25 proteins were differentially expressed in all three comparisons, and 20 hub proteins were identified. Nine proteins were found to be both differentially expressed and hub proteins, indicating their potential significance. A random forest model based on these nine proteins showed good classification performance. The identified proteins are involved in processes such as inflammation, coagulation, extracellular matrix regulation, and immune response. They provide insights into potential therapeutic targets and diagnostic biomarkers for brucellosis. This study improves our understanding of brucellosis at the molecular level and paves the way for further research in targeted therapies and diagnostics.
Identifiants
pubmed: 37520434
doi: 10.3389/fcimb.2023.1216176
pmc: PMC10373591
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1216176Informations de copyright
Copyright © 2023 Yang, Qiao, Yu, Zong, Liu and Li.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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