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pmid:32110496

Co-expression network analysis reveals the pivotal role of mitochondrial dysfunction and interferon signature in juvenile dermatomyositis.

Danli Zhong · Chanyuan Wu · Jingjing Bai · Dong Xu · Xiaofeng Zeng · Qian Wang

PeerJ · 2020 doi:10.7717/peerj.8611

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Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:32110496
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science-record
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sha256:1d9d4bc7c6bd83be6587564efd90eeee287bf54f1be2a1008595263eb8bf6678
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:40:57Z
updated_at
2026-11-01T22:01:20Z
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paper object · 10 fields
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title
Co-expression network analysis reveals the pivotal role of mitochondrial dysfunction and interferon signature in juvenile dermatomyositis.
doi
10.7717/peerj.8611
pmid
32110496
authors array · 6 items
[0]
Danli Zhong
[1]
Chanyuan Wu
[2]
Jingjing Bai
[3]
Dong Xu
[4]
Xiaofeng Zeng
[5]
Qian Wang
journal
PeerJ
year
2020
abstract
BACKGROUND: Juvenile dermatomyositis (JDM) is an immune-mediated disease characterized by chronic organ inflammation. The pathogenic mechanisms remain ill-defined. METHODS: Raw microarray data of JDM were obtained from the gene expression omnibus (GEO) database. Based on the GSE3307 dataset with 39 samples, weighted correlation network analysis (WGCNA) was performed to identify key modules associated with pathological state. Functional enrichment analyses were conducted to identify potential mechanisms. Based on the criteria of high connectivity and module membership, candidate hub genes were selected. A protein-protein interaction network was constructed to identify hub genes. Another dataset (GSE11971) was used for the validation of real hub genes. Finally, the real hub genes were used to screen out small-molecule compounds via the Connectivity map database. RESULTS: Three modules were considered as key modules for the pathological state of JDM. Functional enrichment analysis indicated that responses to interferon and metabolism were dysregulated. A total of 45 candidate hub genes were selected according to the pre-established criteria, and 20 genes could differentiate JDM from normal controls by validation of another external dataset (GSE11971). These real hub genes suggested the pivotal role of mitochondrial dysfunction and interferon signature in JDM. Furthermore, drug repositioning highlighted the importance of acacetin, helveticoside, lanatoside C, deferoxamine, LY-294002, tanespimycin and L01AD from downregulated genes with the potential to perturb the development of JDM, while betonicine, felodipine, valproic acid, trichostatin A and sirolimus from upregulated genes provided potentially therapeutic goals for JDM. CONCLUSIONS: There are 20 real hub genes associated with the pathological state of JDM, suggesting the pivotal role of mitochondrial dysfunction and interferon signature in JDM. This analysis predicted several kinds of small-molecule compounds to treat JDM.
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Two-tailed Student’s t-test was applied to the significance of differences between groups, and P-value less than 0.05 was considered as statistically significant.
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sections[8] "Statistical analysis" paragraph 2
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Two-tailed Student’s t-test was applied to the significance of differences between groups, and P-value less than 0.05 was considered as statistically significant.
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The following information was supplied regarding data availability: The data is available at NCBI GEO: GSE3307 and GSE11971.
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sections[29] "Data Availability Statement" paragraphs 1-3
quote
The following information was supplied regarding data availability: The data is available at NCBI GEO: GSE3307 and GSE11971.
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Small molecule drugs screening based on CMap database.
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Small molecule drugs screening based on CMap database.
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Hub genes identified by co-expression and MCODE methods.
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Small molecule drugs screening based on CMap database.
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The following information was supplied regarding data availability: The data is available at NCBI GEO: GSE3307 and GSE11971.
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mechanisms remain ill-defined. METHODS: Raw microarray data of JDM were obtained from the gene expr
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32110496", "kind": "science-record", "revision": 7, "content_hash": "sha256:1d9d4bc7c6bd83be6587564efd90eeee287bf54f1be2a1008595263eb8bf6678", "created_at": "2026-11-01T15:40:57Z", "updated_at": "2026-11-01T22:01:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Co-expression network analysis reveals the pivotal role of mitochondrial dysfunction and interferon signature in juvenile dermatomyositis.", "doi": "10.7717/peerj.8611", "pmid": "32110496", "authors": ["Danli Zhong", "Chanyuan Wu", "Jingjing Bai", "Dong Xu", "Xiaofeng Zeng", "Qian Wang"], "journal": "PeerJ", "year": 2020, "abstract": "BACKGROUND: Juvenile dermatomyositis (JDM) is an immune-mediated disease characterized by chronic organ inflammation. The pathogenic mechanisms remain ill-defined.\nMETHODS: Raw microarray data of JDM were obtained from the gene expression omnibus (GEO) database. Based on the GSE3307 dataset with 39 samples, weighted correlation network analysis (WGCNA) was performed to identify key modules associated with pathological state. Functional enrichment analyses were conducted to identify potential mechanisms. Based on the criteria of high connectivity and module membership, candidate hub genes were selected. A protein-protein interaction network was constructed to identify hub genes. Another dataset (GSE11971) was used for the validation of real hub genes. Finally, the real hub genes were used to screen out small-molecule compounds via the Connectivity map database.\nRESULTS: Three modules were considered as key modules for the pathological state of JDM. Functional enrichment analysis indicated that responses to interferon and metabolism were dysregulated. A total of 45 candidate hub genes were selected according to the pre-established criteria, and 20 genes could differentiate JDM from normal controls by validation of another external dataset (GSE11971). These real hub genes suggested the pivotal role of mitochondrial dysfunction and interferon signature in JDM. Furthermore, drug repositioning highlighted the importance of acacetin, helveticoside, lanatoside C, deferoxamine, LY-294002, tanespimycin and L01AD from downregulated genes with the potential to perturb the development of JDM, while betonicine, felodipine, valproic acid, trichostatin A and sirolimus from upregulated genes provided potentially therapeutic goals for JDM.\nCONCLUSIONS: There are 20 real hub genes associated with the pathological state of JDM, suggesting the pivotal role of mitochondrial dysfunction and interferon signature in JDM. 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