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pmid:35280393

Autophagy-related genes are potential diagnostic biomarkers for dermatomyositis.

Le Wang · Dalang Fang · Yuan Liu

Annals of translational medicine · 2022 doi:10.21037/atm-22-70

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

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2026-11-01T18:14:03Z
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title
Autophagy-related genes are potential diagnostic biomarkers for dermatomyositis.
doi
10.21037/atm-22-70
pmid
35280393
authors array · 3 items
[0]
Le Wang
[1]
Dalang Fang
[2]
Yuan Liu
journal
Annals of translational medicine
year
2022
abstract
Background: Dermatomyositis (DM) is an autoimmune disease mainly diagnosed by its symptoms and a physical examination, with only some subtypes of DM showing clear molecular changes. To date, few biomarkers have been identified to assess DM progression. Autophagy-related genes have been significantly correlated with inflammation, several types of autoimmune diseases, and the immune response, but few studies have explored the role of autophagy-related genes in DM. Therefore, this study aimed to investigate the roles of autophagy-related genes in DM. Methods: We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database: GSE1551, GSE46239, and GSE143323 and analyzed the differentially expressed genes (DEGs). We also conducted functional enrichment analyses with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To explore whether the autophagy-related genes were differentially expressed in DM compared with normal samples, we performed an intersection between the DEGs and autophagy-related genes obtained from the Human Autophagy Database (HADb, http://www.autophagy.lu/). Finally, we used selected autophagy-related genes as biomarkers for diagnosing and analyzing the correlation with immune cell infiltration. Results: Our results showed that 143 genes were upregulated, and 14 were downregulated in the DM samples compared with healthy samples. The functional enrichment analysis revealed that these DEGs played a significant role in the type I interferon signaling pathway, cytokine activity, chemokine activity, double-stranded RNA binding, and blood microparticles. The intersection results identified CCL2, CDKN1A, FOS, MYC, and TNFSF10 as the primary autophagy-related genes in DM. All showed significantly increased expressions in DM samples compared with healthy samples. We were also curious to investigate immune cell infiltration in DM. Our results showed that the selected autophagy-related genes significantly influenced the infiltration of multiple immune cells, such as B cells, macrophages, and natural killer cells. Finally, we assessed the diagnostic sensitivity of CCL2, CDKN1A, FOS, MYC, and TNFSF10 for DM. The results showed the area under the curve (AUC) values of the ROC were 0.855, 0.889, 0.744, 0.826, and 0.816, respectively. The combined genes' diagnostic AUC value was 0.951. Conclusions: CCL2, CDKN1A, FOS, MYC, and TNFSF10 are potential diagnostic biomarkers for DM.
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The healthy and DM samples were grouped and analyzed using R software’s “limma” package.
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sections[4] "Analysis of differentially expressed genes (DEGs)" paragraph 2
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The healthy and DM samples were grouped and analyzed using R software’s “limma” package.
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We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.
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We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.
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The combined genes’ diagnostic AUC value was 0.951.
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The combined genes’ diagnostic AUC value was 0.951.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35280393", "kind": "science-record", "revision": 5, "content_hash": "sha256:b2f1ed653bf392b16dc7075ffabecd38a6cc035545c1f51c68989b80cc9823a3", "created_at": "2026-11-01T18:14:03Z", "updated_at": "2026-11-01T22:48:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Autophagy-related genes are potential diagnostic biomarkers for dermatomyositis.", "doi": "10.21037/atm-22-70", "pmid": "35280393", "authors": ["Le Wang", "Dalang Fang", "Yuan Liu"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Dermatomyositis (DM) is an autoimmune disease mainly diagnosed by its symptoms and a physical examination, with only some subtypes of DM showing clear molecular changes. To date, few biomarkers have been identified to assess DM progression. Autophagy-related genes have been significantly correlated with inflammation, several types of autoimmune diseases, and the immune response, but few studies have explored the role of autophagy-related genes in DM. Therefore, this study aimed to investigate the roles of autophagy-related genes in DM.\nMethods: We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database: GSE1551, GSE46239, and GSE143323 and analyzed the differentially expressed genes (DEGs). We also conducted functional enrichment analyses with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To explore whether the autophagy-related genes were differentially expressed in DM compared with normal samples, we performed an intersection between the DEGs and autophagy-related genes obtained from the Human Autophagy Database (HADb, http://www.autophagy.lu/). Finally, we used selected autophagy-related genes as biomarkers for diagnosing and analyzing the correlation with immune cell infiltration.\nResults: Our results showed that 143 genes were upregulated, and 14 were downregulated in the DM samples compared with healthy samples. The functional enrichment analysis revealed that these DEGs played a significant role in the type I interferon signaling pathway, cytokine activity, chemokine activity, double-stranded RNA binding, and blood microparticles. The intersection results identified CCL2, CDKN1A, FOS, MYC, and TNFSF10 as the primary autophagy-related genes in DM. All showed significantly increased expressions in DM samples compared with healthy samples. We were also curious to investigate immune cell infiltration in DM. Our results showed that the selected autophagy-related genes significantly influenced the infiltration of multiple immune cells, such as B cells, macrophages, and natural killer cells. Finally, we assessed the diagnostic sensitivity of CCL2, CDKN1A, FOS, MYC, and TNFSF10 for DM. The results showed the area under the curve (AUC) values of the ROC were 0.855, 0.889, 0.744, 0.826, and 0.816, respectively. The combined genes' diagnostic AUC value was 0.951.\nConclusions: CCL2, CDKN1A, FOS, MYC, and TNFSF10 are potential diagnostic biomarkers for DM.", "claims": [{"id": "claim-method", "statement": "The healthy and DM samples were grouped and analyzed using R software’s “limma” package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35280393", "locator": "sections[4] \"Analysis of differentially expressed genes (DEGs)\" paragraph 2", "quote": "The healthy and DM samples were grouped and analyzed using R software’s “limma” package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35280393", "locator": "sections[3] \"Raw data\" paragraph 2", "quote": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined genes’ diagnostic AUC value was 0.951.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35280393", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The combined genes’ diagnostic AUC value was 0.951."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The combined genes’ diagnostic AUC value was 0.951.", "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:35280393"], "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:GSE143323"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE143323"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35280393", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/atm-22-70", "sha256": "sha256:f8a1843b3b5e8153dd772dcfe8221c5aa4e0df305703887a7882c16832871219", "bytes": 30605, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/atm-22-70", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8908178", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE143323", "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=GSE143323", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE143323", "version": null, "note": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; 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GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM26512", "GSM26513", "GSM26514", "GSM26515", "GSM26516", "GSM26517", "GSM26518", "GSM26519", "GSM26520", "GSM26521", "GSM26522", "GSM26523", "GSM26524", "GSM26525", "GSM26526", "GSM26527", "GSM26528", "GSM26529", "GSM26530", "GSM26531", "GSM26532", "GSM26533", "GSM26534"], "sample_count": 23, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "dermatomyositis", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE46239", "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=GSE46239", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE46239", "version": null, "note": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We collected three datasets of dermatomyositis-related transcriptome from the Gene Expression Omnibus (GEO) database; GSE1551 contained 10 healthy samples and 13 DM samples, GSE46239 contained 4 healthy samples and 48 DM samples, and GSE143323 contained 20 healthy samples and 39 DM samples.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1126893", "GSM1126894", "GSM1126895", "GSM1126896", "GSM1126897", "GSM1126898", "GSM1126899", "GSM1126900", "GSM1126901", "GSM1126902", "GSM1126903", "GSM1126904", "GSM1126905", "GSM1126906", "GSM1126907", "GSM1126908", "GSM1126909", "GSM1126910", "GSM1126911", "GSM1126912", "GSM1126913", "GSM1126914", "GSM1126915", "GSM1126916", "GSM1126917", "GSM1126918", "GSM1126919", "GSM1126920", "GSM1126921", "GSM1126922", "GSM1126923", "GSM1126924", "GSM1126925", "GSM1126926", "GSM1126927", "GSM1126928", "GSM1126929", "GSM1126930", "GSM1126931", "GSM1126932", "GSM1126933", "GSM1126934", "GSM1126935", "GSM1126936", "GSM1126937", "GSM1126938", "GSM1126939", "GSM1126940", "GSM1126941", "GSM1126942", "GSM1126943", "GSM1126944"], "sample_count": 52, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene Expression Analysis of Dermatomyositis Skin", "resolution_checked_at": "2026-11-01T18:06:44Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE143323 not downloaded", "asset:data:geo:GSE143323 licence not read", "asset:data:geo:GSE1551 not downloaded", "asset:data:geo:GSE1551 licence not read", "asset:data:geo:GSE46239 not downloaded", "asset:data:geo:GSE46239 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The healthy and DM samples were grouped and analyzed using R software’s “limma” package."}}, {"id": "method-2", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.8, "band": "high", "quote": "limma"}}], "targets": [], "gaps": ["method.group_comparison_wilcoxon"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": false, "required_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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