Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35749386", "kind": "science-record", "revision": 4, "content_hash": "sha256:5ec55d06cf7bc7616243a8932c080b2b825fe7cb5a179bdbf4d62fb236d9b21a", "created_at": "2026-11-01T18:14:46Z", "updated_at": "2026-11-01T22:06:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of critical genes and molecular pathways in COVID-19 myocarditis and constructing gene regulatory networks by bioinformatic analysis.", "doi": "10.1371/journal.pone.0269386", "pmid": "35749386", "authors": ["Fengjun Zhang", "Cheng Yu", "Wenchang Xu", "Xiao Li", "Junchen Feng", "Hongshuo Shi", "Jingrong Yang", "Qinhua Sun", "Xianyi Cao", "Lin Zhang", "Min Peng"], "journal": "PloS one", "year": 2022, "abstract": "BACKGROUND: There is growing evidence of a strong relationship between COVID-19 and myocarditis. However, there are few bioinformatics-based analyses of critical genes and the mechanisms related to COVID-19 Myocarditis. This study aimed to identify critical genes related to COVID-19 Myocarditis by bioinformatic methods, explore the biological mechanisms and gene regulatory networks, and probe related drugs.\nMETHODS: The gene expression data of GSE150392 and GSE167028 were obtained from the Gene Expression Omnibus (GEO), including cardiomyocytes derived from human induced pluripotent stem cells infected with SARS-CoV-2 in vitro and GSE150392 from patients with myocarditis infected with SARS-CoV-2 and the GSE167028 gene expression dataset. Differentially expressed genes (DEGs) (adjusted P-Value <0.01 and |Log2 Fold Change| ≥2) in GSE150392 were assessed by NetworkAnalyst 3.0. Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes. Functional enrichment analyses were performed by using the \"clusterProfiler\" package in the R software, and protein-protein interaction (PPI) networks were constructed on the STRING website (https://cn.string-db.org/). Critical genes were identified by the CytoHubba plugin of Cytoscape by 5 algorithms. Transcription factor-gene (TF-gene) and Transcription factor-microRibonucleic acid (TF-miRNA) coregulatory networks construction were performed by NetworkAnalyst 3.0 and displayed in Cytoscape. Finally, Drug Signatures Database (DSigDB) was used to probe drugs associated with COVID-19 Myocarditis.\nRESULTS: Totally 850 DEGs (including 449 up-regulated and 401 down-regulated genes) and 159 significant genes in turquoise modules were identified from GSE150392 and GSE167028, respectively. Functional enrichment analysis indicated that common genes were mainly enriched in biological processes such as cell cycle and ubiquitin-protein hydrolysis. 6 genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) were identified as critical genes. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Etoposide, Methotrexate, Troglitazone, etc) were considered as target drugs for COVID-19 Myocarditis.\nCONCLUSIONS: Through bioinformatics method analysis, this study provides a new perspective to explore the pathogenesis, gene regulatory networks and provide drug compounds as a reference for COVID-19 Myocarditis. It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.", "claims": [{"id": "claim-method", "statement": "Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35749386", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Meanwhile, significant modular genes in GSE167028 were identified by weighted gene correlation network analysis (WGCNA) and overlapped with DEGs to obtain common genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Dataset related to SARS-CoV-2 infected cardiomyocytes was obtained from the Gene Expression Omnibus (GEO) datasets (https://www.ncbi.nlm.nih.gov/gds/) with accession number GSE150392(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150392) [21, 22] which from GPL18573 Illumina NextSeq 500 (Homo sapiens).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35749386", "locator": "sections[3] \"RNA-sequencing data collection\" paragraph 2", "quote": "Dataset related to SARS-CoV-2 infected cardiomyocytes was obtained from the Gene Expression Omnibus (GEO) datasets (https://www.ncbi.nlm.nih.gov/gds/) with accession number GSE150392(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150392) [21, 22] which from GPL18573 Illumina NextSeq 500 (Homo sapiens)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35749386", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "It is worth highlighting that critical genes (CDK1, KIF20A, PBK, KIF2C, CDC20, UBE2C) may be potential biomarkers and treatment targets of COVID-19 Myocarditis for future study.", "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:35749386"], "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. 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