Ten genes are considered as potential biomarkers for the diagnosis of dermatomyositis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34818375", "kind": "science-record", "revision": 4, "content_hash": "sha256:cb6d54980259f96a1b2f097cc87462c819504bb48496ba775d1564f0a53ac13f", "created_at": "2026-11-01T17:36:31Z", "updated_at": "2026-11-01T22:05:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Ten genes are considered as potential biomarkers for the diagnosis of dermatomyositis.", "doi": "10.1371/journal.pone.0260511", "pmid": "34818375", "authors": ["Lu Xiao", "Wei Xiao", "Shudian Lin"], "journal": "PloS one", "year": 2021, "abstract": "OBJECTIVE: This study aimed to identify the biomarkers and mechanisms for dermatomyositis (DM) progression at the transcriptome level through a combination of microarray and bioinformatic analyses.\nMETHOD: Microarray 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.\nRESULT: A 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.\nCONCLUSION: Our work identified 10 valuable genes as potential biomarkers for the diagnosis of DM and explored the potential underlying molecular mechanism of the disease.", "claims": [{"id": "claim-method", "statement": "Two gene expression datasets containing patients with DM and HCs were analyzed with two-group comparisons (P < 0.01), and then 2458 and 178 DEGs were identified from GSE48280 and GSE5370 respectively. The expression levels of 10 identified hub genes were validated by GSE1551 and GSE11971 using an independent sample t test. The ROC-AUC was performed by GraphPad PRISM 7.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34818375", "locator": "sections[9] \"Identification of DEGs\" paragraph 2", "quote": "Two gene expression datasets containing patients with DM and HCs were analyzed with two-group comparisons (P < 0.01), and then 2458 and 178 DEGs were identified from GSE48280 and GSE5370 respectively."}, {"asset": "source:pmid:34818375", "locator": "sections[7] \"Statistical analysis\" paragraph 2", "quote": "The expression levels of 10 identified hub genes were validated by GSE1551 and GSE11971 using an independent sample t test."}, {"asset": "source:pmid:34818375", "locator": "sections[7] \"Statistical analysis\" paragraph 2", "quote": "The ROC-AUC was performed by GraphPad PRISM 7."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GEO database is a public repository database, which stores a large number of gene functions and expressions [14]. We used ‘‘dermatomyositis” as the key word to search expression profiling of DM in the database. Finally, two datasets GSE48280 (GPL6244) and GSE5370(GPL96), including muscle biopsies from 10 patients with DM and 9 HCs, were selected as test sets [15].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34818375", "locator": "sections[3] \"Data collection\" paragraph 2", "quote": "The GEO database is a public repository database, which stores a large number of gene functions and expressions [14]. We used ‘‘dermatomyositis” as the key word to search expression profiling of DM in the database. Finally, two datasets GSE48280 (GPL6244) and GSE5370(GPL96), including muscle biopsies from 10 patients with DM and 9 HCs, were selected as test sets [15]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After integration of these DEGs by using bioinformatic analysis, a total of 63 common DEGs were identified in patients with DM (Fig 2C), including 61 upregulated genes and 2 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34818375", "locator": "sections[9] \"Identification of DEGs\" paragraph 2", "quote": "After integration of these DEGs by using bioinformatic analysis, a total of 63 common DEGs were identified in patients with DM (Fig 2C), including 61 upregulated genes and 2 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After integration of these DEGs by using bioinformatic analysis, a total of 63 common DEGs were identified in patients with DM (Fig 2C), including 61 upregulated genes and 2 downregulated genes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34818375"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE11971"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE11971"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34818375", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1371/journal.pone.0260511", "sha256": "sha256:8cb07aaceec7362e791431cab546acf7edc1c12a6ca8a2df04304ee88ceb17a5", "bytes": 19755, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1371/journal.pone.0260511", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8612544", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE11971", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11971", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE11971", "version": null, "note": "The GEO database is a public repository database, which stores a large number of gene functions and expressions [14]. 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