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pmid:33551990
Integrative Analyses of Genes Associated With Osteoporosis in CD16+ Monocyte.
Bin Hu · Xiangan Kong · Li Li · Fang Dai · Qiu Zhang · Ruifeng Shi
Frontiers in endocrinology · 2020 doi:10.3389/fendo.2020.581878
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Experiment
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Complete file
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However, the mechanism by which monocytes subpopulations lead to osteoporosis remains unclear. The aim of this study was to identify genes associated with osteoporosis in monocytes subsets.\nMethods: Three microarray datasets including GSE7158 (transcription of low/high-peak bone mass), GSE101489 (transcription of CD16+/CD16- monocyte) and GSE93883 (miRNA expression profile of primary osteoporosis) were derived from the Gene Expression Omnibus (GEO) database and analyzed with GEO2R tool to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using Metascape database and GSEA software. STRING was utilized for the Protein-Protein Interaction Network construct. The hub genes were screened out using the Cytoscape software. Related miRNAs were predicted in miRWalk, miRDB, and TargetScan databases.\nResults: Total 368 DEGs from GSE7158 were screened out, which were mostly enriched in signaling, positive regulation of biological process and immune system process. The hub genes were clustered into two modules by PPI network analysis. We identified 15 overlapping DGEs between GSE101489 and GSE7158 microarray datasets. Moreover, all of them were up-regulated genes in both datasets. Then, nine key genes were screened out from above 15 overlapping DEGs using Cytoscape software. It is a remarkable fact that the nine genes were all in one hub gene module of GSE7158. Additionally, 183 target miRNAs were predicted according to the above nine DEGs. After cross-verification with miRNA express profile dataset for osteoporosis (GSE93883), 12 DEmiRNAs were selected. Finally, a miRNA-mRNA network was constructed with the nine key genes and 12 miRNAs, which were involved in osteoporosis.\nConclusion: Our analysis results constructed a gene expression framework in monocyte subsets for osteoporosis. This approach could provide a novel insight into osteoporosis.", "claims": [{"id": "claim-method", "statement": "The online analysis tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect the DEGs between HPBM and LPBM samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33551990", "locator": "sections[4] \"Data Processing\" paragraph 2", "quote": "The online analysis tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to detect the DEGs between HPBM and LPBM samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33551990", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:33551990"], "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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norvegicus", "title": "Gene expression-based, individualized outcome prediction for osteoporosis with vertebral fracture", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33551990:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:960edd771350fa13b1103b3f2b92774d8f8bebbd33b76fee2e27b686d3025898", "bytes": 2319, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[9]/table-wrap[1]#T1", "version": null, "note": "Top 20 enriched terms for differentially expressed genes in monocytes of low peak bone mass (LPBM).", "structure": {"pmcid": "PMC7859337", "section_index": 9, "section_title": "Identification and Enrichment of Differentially Expressed Genes in Low-Peak Bone Mass Monocytes", "row_count": 21, 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"regulation of cell-substrate adhesion", "11", "3.11", "–3.48", "–0.5"], ["GO:0048762", "GO Biological Processes", "mesenchymal cell differentiation", "11", "3.11", "–3.43", "–0.5"], ["GO:0002068", "GO Biological Processes", "glandular epithelial cell development", "4", "1.13", "–3.29", "–0.47"], ["GO:0003678", "GO Molecular Functions", "DNA helicase activity", "6", "1.69", "–2.99", "–0.2"], ["GO:0051216", "GO Biological Processes", "cartilage development", "10", "2.82", "–2.95", "–0.18"], ["GO:1901611", "GO Molecular Functions", "phosphatidylglycerol binding", "3", "0.85", "–2.92", "–0.16"], ["GO:0042623", "GO Molecular Functions", "ATPase activity, coupled", "12", "3.39", "–2.9", "-0.16"], ["GO:0030011", "GO Biological Processes", "maintenance of cell polarity", "3", "0.85", "–2.75", "-0.04"], ["GO:0071634", "GO Biological Processes", "regulation of transforming growth factor beta production", "4", "1.13", "–2.75", "–0.04"], ["GO:0005938", "GO Cellular Components", "cell cortex", 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