Screening and validation of differentially expressed genes in polymyositis.

Bioinformatics DEGs HLA IFN-I Polymyositis

Journal

Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560

Informations de publication

Date de publication:
15 Feb 2024
Historique:
received: 09 05 2023
revised: 10 01 2024
accepted: 10 01 2024
medline: 6 2 2024
pubmed: 6 2 2024
entrez: 6 2 2024
Statut: epublish

Résumé

Polymyositis (PM), a prevalent inflammatory myopathy, currently lacks defined pathogenic mechanism. To illuminate its pathogenesis, we integrated bioinformatics and clinical specimens to examine potential aberrant gene expression patterns and their localization. We obtained GSE128470 and GSE3112 dataset from the Gene Expression Omnibus, performed Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis using CiberSort, identified differentially expressed genes with Limma, conducted functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, constructed a Protein-Protein Interaction network, and identified hub genes using Cytoscape. ROC analysis evaluated hub gene diagnostic accuracy for PM, validated their expression levels with clinical specimens. DEG analysis revealed 51 upregulated and 779 downregulated genes. Gene Ontology (GO) analysis implicated Type I interferon (IFN-Ⅰ) signaling, while KEGG pointed to cell adhesion molecule activation and oxidative phosphorylation inhibition. Protein-Protein Interaction (PPI) analysis identified 8 diagnosffftic hub genes. Clinical samples confirmed their upregulation in PM, especially IRF1 and IRF9 between muscle fibers. Different immune cell infiltrations were observed in PM patients versus controls. Our study explores potential pathogenic factors, diagnostic markers, and immune cells in PM, with a focus on verifying IRF1 and IRF9 upregulation in the IFN-I signaling pathway. These findings bear significance for PM diagnosis and treatment.

Sections du résumé

Background UNASSIGNED
Polymyositis (PM), a prevalent inflammatory myopathy, currently lacks defined pathogenic mechanism. To illuminate its pathogenesis, we integrated bioinformatics and clinical specimens to examine potential aberrant gene expression patterns and their localization.
Methods UNASSIGNED
We obtained GSE128470 and GSE3112 dataset from the Gene Expression Omnibus, performed Gene Set Enrichment Analysis (GSEA) and immune infiltration analysis using CiberSort, identified differentially expressed genes with Limma, conducted functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, constructed a Protein-Protein Interaction network, and identified hub genes using Cytoscape. ROC analysis evaluated hub gene diagnostic accuracy for PM, validated their expression levels with clinical specimens.
Results UNASSIGNED
DEG analysis revealed 51 upregulated and 779 downregulated genes. Gene Ontology (GO) analysis implicated Type I interferon (IFN-Ⅰ) signaling, while KEGG pointed to cell adhesion molecule activation and oxidative phosphorylation inhibition. Protein-Protein Interaction (PPI) analysis identified 8 diagnosffftic hub genes. Clinical samples confirmed their upregulation in PM, especially IRF1 and IRF9 between muscle fibers. Different immune cell infiltrations were observed in PM patients versus controls.
Conclusions UNASSIGNED
Our study explores potential pathogenic factors, diagnostic markers, and immune cells in PM, with a focus on verifying IRF1 and IRF9 upregulation in the IFN-I signaling pathway. These findings bear significance for PM diagnosis and treatment.

Identifiants

pubmed: 38317877
doi: 10.1016/j.heliyon.2024.e24537
pii: S2405-8440(24)00568-1
pmc: PMC10839795
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e24537

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Linmang Qin (L)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Haobo Lin (H)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Guangfeng Zhang (G)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Jieying Wang (J)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Tianxiao Feng (T)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Yunxia Lei (Y)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Yuesheng Xie (Y)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Ting Xu (T)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Xiao Zhang (X)

Department of Rheumatology and Immunology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.

Classifications MeSH