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pmid:35993048

Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes.

Liang Mo · Zhangzheng Wang · Haoran Huang · Jianxiong Li · Chao Ma · Jiahao Zhang · Fayi Huang · Wei He · Yuhao Liu · Chi Zhou

BioMed research international · 2022 doi:10.1155/2022/3921570

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes.
doi
10.1155/2022/3921570
pmid
35993048
authors array · 10 items
[0]
Liang Mo
[1]
Zhangzheng Wang
[2]
Haoran Huang
[3]
Jianxiong Li
[4]
Chao Ma
[5]
Jiahao Zhang
[6]
Fayi Huang
[7]
Wei He
[8]
Yuhao Liu
[9]
Chi Zhou
journal
BioMed research international
year
2022
abstract
Purpose: The aim of this study is to explore pathological mechanisms of bone fragility in type 2 diabetes mellitus (T2DM) patients. Methods: Identifying common genes for T2DM and osteoporosis by taking the intersection is shared by the Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases. The differentially expressed genes (DEGs) and the differentially expressed miRNAs (DEMs) were identified by analyzing the Gene Expression Omnibus (GEO) datasets (GSE35958, GSE43950, and GSE70318). FunRich and miRNet were applied to predict potential upstream transcription factors and downstream target genes of candidate DEMs, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore potential mechanisms using Metascape. Eventually, a miRNA-gene network was constructed by Cytoscape software. Results: 271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318. SP1 was predicted to potentially regulate most of the DEMs. Enrichment analysis showed the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play an important role in diabetic skeletal fragility. Two genes (NAMPT and IGFBP5) were considered as key genes involving in the development of diabetic osteoporosis. Through the construction of the miRNA-gene network, most of the hub genes were found to be potentially modulated by miR-96-5p and miR-7-5p. Conclusion: The study uncovered several important genes, miRNAs, and pathological mechanisms involved in diabetic skeletal fragility, among which the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play important roles.
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GEO2R, an interactive web tool, was used to screen out differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between the experimental group and control group. |logFC| > 1 and the adjusted P value < 0.05 were considered to indicate statistical significance.
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271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318.
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271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318.
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Effects of Primary Osteoporosis on Human Mesenchymal Stem Cells
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Serum microRNA signatures are indicative of skeletal fractures in post-menopausal women with and without type 2 diabetes and influence osteo-genic differentiation of mesenchymal stem cells
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35993048", "kind": "science-record", "revision": 4, "content_hash": "sha256:7603a20f33998706e73452ea4c8c475dc892ba93afc1d3451ba20093795cbd3b", "created_at": "2026-11-01T18:15:09Z", "updated_at": "2026-11-01T22:07:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes.", "doi": "10.1155/2022/3921570", "pmid": "35993048", "authors": ["Liang Mo", "Zhangzheng Wang", "Haoran Huang", "Jianxiong Li", "Chao Ma", "Jiahao Zhang", "Fayi Huang", "Wei He", "Yuhao Liu", "Chi Zhou"], "journal": "BioMed research international", "year": 2022, "abstract": "Purpose: The aim of this study is to explore pathological mechanisms of bone fragility in type 2 diabetes mellitus (T2DM) patients.\nMethods: Identifying common genes for T2DM and osteoporosis by taking the intersection is shared by the Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases. The differentially expressed genes (DEGs) and the differentially expressed miRNAs (DEMs) were identified by analyzing the Gene Expression Omnibus (GEO) datasets (GSE35958, GSE43950, and GSE70318). FunRich and miRNet were applied to predict potential upstream transcription factors and downstream target genes of candidate DEMs, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore potential mechanisms using Metascape. Eventually, a miRNA-gene network was constructed by Cytoscape software.\nResults: 271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318. SP1 was predicted to potentially regulate most of the DEMs. Enrichment analysis showed the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play an important role in diabetic skeletal fragility. Two genes (NAMPT and IGFBP5) were considered as key genes involving in the development of diabetic osteoporosis. Through the construction of the miRNA-gene network, most of the hub genes were found to be potentially modulated by miR-96-5p and miR-7-5p.\nConclusion: The study uncovered several important genes, miRNAs, and pathological mechanisms involved in diabetic skeletal fragility, among which the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play important roles.", "claims": [{"id": "claim-method", "statement": "GEO2R, an interactive web tool, was used to screen out differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between the experimental group and control group. |logFC| > 1 and the adjusted P value < 0.05 were considered to indicate statistical significance.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35993048", "locator": "sections[6] \"2.4. Analysis of Datasets in GEO\" paragraph 3", "quote": "GEO2R, an interactive web tool, was used to screen out differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between the experimental group and control group. |logFC| > 1 and the adjusted P value < 0.05 were considered to indicate statistical significance."}], "state": "complete"}, {"id": "claim-data-access", "statement": "No data were used to support this study.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35993048", "locator": "sections[23] \"Data Availability\" paragraph 2", "quote": "No data were used to support this study."}], "state": "complete"}, {"id": "claim-target-result", "statement": "271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35993048", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318.", "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:35993048"], "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:GSE35958"], "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:GSE35958"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35993048", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/3921570", "sha256": 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"access_statement_verbatim": "No data were used to support this study.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM878100", "GSM878101", "GSM878102", "GSM878103", "GSM878104", "GSM878105", "GSM878106", "GSM878107", "GSM878108"], "sample_count": 9, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Effects of Primary Osteoporosis on Human Mesenchymal Stem Cells", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE43950", "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=GSE43950", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE43950", "version": null, "note": "No data were used to support this study.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "No data were used to support this study.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1074874", "GSM1074875", "GSM1074876", "GSM1074877", "GSM1074878", "GSM1074879", "GSM1074880", "GSM1074881", "GSM1074882", "GSM1074883", "GSM1074884", "GSM1074885", "GSM1074886", "GSM1074887"], "sample_count": 14, "group_sizes": null, "group_sizes_basis": null, "platform": "10379", "taxon": "Homo sapiens", "title": "Gene expression profiling in endothelial precursor cells of patients protected from microvascular complications", "resolution_checked_at": "2026-11-01T18:06:44Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE70318", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": 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"downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE35958 not downloaded", "asset:data:geo:GSE35958 licence not read", "asset:data:geo:GSE43950 not downloaded", "asset:data:geo:GSE43950 licence not read", "asset:data:geo:GSE70318 not downloaded", "asset:data:geo:GSE70318 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "PPI"}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": 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Eventually, the three microarray datasets (GSE35958 [23], GSE43950 [24], and"], "order_basis": "paper_text_order:2118", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["PPI"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}