ArticlePloS one2021
Ten genes are considered as potential biomarkers for the diagnosis of dermatomyositis.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Review
- Construction and validation of a diagnostic model for dermatomyositis based on the LASSO algorithm.Central-European journal of immunology · 2025Article
- Altered Iron Regulation and the Role of Ferritin Heavy Chain in Dermatomyositis Patients.Journal of inflammation research · 2025Article
- Long non‑coding RNAs MALAT1, NEAT1 and DSCR4 can be serum biomarkers in predicting urosepsis occurrence and reflect disease severity.Experimental and therapeutic medicine · 2024Article
- Transcriptome analysis of skeletal muscle in dermatomyositis, polymyositis, and dysferlinopathy, using a bioinformatics approach.Frontiers in neurology · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to identify the biomarkers and mechanisms for dermatomyositis (DM) progression at the transcriptome level through a combination of microarray and bioinformatic analyses.
methodMicroarray datasets for skeletal muscle of DM and healthy control (HC) were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified by using GEO2R. Enrichment analyses were performed to understand the functions and enriched pathways of DEGs. A protein-protein interaction network was constructed to identify hub genes. The top 10 hub genes were validated by other GEO datasets. The diagnostic accuracy of the top 10 hub genes for DM was evaluated using the area under the curve of the receiver operating characteristic curve.
resultA total of 63 DEGs were identified between 10 DM samples and 9 HC samples. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that DEGs are mostly enriched in response to virus, defense response to virus, and type I interferon signaling pathway. 10 hub genes and 3 gene cluster modules were identified by Cytoscape. The identified hub genes were verified by GSE1551 and GSE11971 datasets and proven to be potential biomarkers for the diagnosis of DM.
conclusionOur work identified 10 valuable genes as potential biomarkers for the diagnosis of DM and explored the potential underlying molecular mechanism of the disease.
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