Mining Potential Drug Targets for Osteoporosis Based on CeRNA Network.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36513616", "kind": "science-record", "revision": 4, "content_hash": "sha256:a80a32c2995003d80f73943dcd044fc161154912d9bee217d77bdb45134f8b94", "created_at": "2026-11-01T19:01:01Z", "updated_at": "2026-11-01T22:50:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Mining Potential Drug Targets for Osteoporosis Based on CeRNA Network.", "doi": "10.1111/os.13617", "pmid": "36513616", "authors": ["Zheng Wang", "Xiao-Fei Zhang", "Mao-Peng Wang", "Shuo Yan", "Zheng-Xu Dai", "Qing-Hang Qian", "Jie Zhao", "Xin-Long Ma", "Bing Li", "Jun Liu"], "journal": "Orthopaedic surgery", "year": 2023, "abstract": "OBJECTIVE: To identify key pathological hub genes, micro RNAs (miRNAs), and circular RNAs (circRNAs) of osteoporosis (OP) and construct their ceRNA network in an effort to explore the potential biomarkers and drug targets for OP therapy.\nMETHODS: GSE7158, GSE201543, and GSE161361 microarray datasets were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by comparing OP patients with healthy controls and hub genes were screened by machine learning algorithms. Target miRNAs and circRNAs were predicted by FunRich and circbank, then ceRNA network were constructed by Cytoscape. Pathways affecting OP were identified by functional enrichment analysis. The hub genes were verified by receiver operating characteristic (ROC) curve and real time quantitative PCR (RT-qPCR). Potential drug molecules related to OP were predicted by DSigDB database and molecular docking was analyzed by autodock vina software.\nRESULTS: A total of 179 DEGs were identified. By combining three machine learning algorithms, BAG2, MME, SLC14A1, and TRIM44 were identified as hub genes. Three OP-associated target miRNAs and 362 target circRNAs were predicted to establish ceRNA network. The ROC curves showed that these four hub genes had good diagnostic performance and their differential expression was statistically significant in OP animal model. Benzo[a]pyrene was predicted which could successfully bind to protein receptors related to the hub genes and it was served as the potential drug molecules.\nCONCLUSION: An mRNA-miRNA-circRNA network is reported, which provides new ideas for exploring the pathogenesis of OP. Benzo[a]pyrene, as potential drug molecules for OP, may provide guidance for the clinical treatment.", "claims": [{"id": "claim-method", "statement": "Differential expressions of genes between the OP and control datasets were screened using the “LIMMA” package in R (http://www.bioconductor.org/packages/release/bioc/html/limma.html).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36513616", "locator": "sections[5] \"Screening of DEGs\" paragraph 2", "quote": "Differential expressions of genes between the OP and control datasets were screened using the “LIMMA” package in R (http://www.bioconductor.org/packages/release/bioc/html/limma.html)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. GSE161361 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161361.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36513616", "locator": "sections[37] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. GSE161361 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161361."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 179 DEGs were identified, and BAG2, MME, SLC14A1, and TRIM44 were identified as hub genes using three machine-learning algorithms.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36513616", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 179 DEGs were identified. By combining three machine learning algorithms, BAG2, MME, SLC14A1, and TRIM44 were identified as hub genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 179 DEGs were identified, and BAG2, MME, SLC14A1, and TRIM44 were identified as hub genes using three machine-learning algorithms.", "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:36513616"], "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:GSE161361"], "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:GSE161361"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36513616", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1111/os.13617", "sha256": "sha256:3b4413d3b620d5739796b51b27be185b21f2bf916e4f0ba708b0e1bf08e00885", "bytes": 42003, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1111/os.13617", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10157711", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE161361", "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=GSE161361", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE161361", "version": null, "note": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. 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All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. GSE161361 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161361.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. GSE161361 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161361.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM6067330", "GSM6067331", "GSM6067332", "GSM6067333", "GSM6067334", "GSM6067335", "GSM6067336", "GSM6067337", "GSM6067338", "GSM6067339"], "sample_count": 10, "group_sizes": null, "group_sizes_basis": null, "platform": "20712", "taxon": "Homo sapiens", "title": "Bone metabolism-related serum miRNAs to diagnose postmenopausal osteoporosis in middle-aged and elderly women", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE7158", "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=GSE7158", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE7158", "version": null, "note": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. GSE161361 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161361.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets (GSE7158, GSE201543, and GSE161361) were analyzed in this study. All datasets were obtained from the GEO database. GSE7158 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE7158. GSE201543 can be downloaded from: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE201543. 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Potential drug molecules related to OP wer", "OC) curve and real time quantitative PCR (RT-qPCR). Potential drug molecules related to OP wer", "FunRich software. Animal Model of OP and RT‐qPCR Assays According to the method in previous l"], "order_basis": "paper_text_order:849", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ng to the method in previous literature, the mouse model of OP was established. 18 , 19 This study wa", "onitored every day after injection until the mice were killed. Twenty‐one days after injection, the", "killed. Twenty‐one days after injection, the mice were killed by cervical dislocation. The right fe", "ervical dislocation. The right femurs of the mice were taken, and the muscle and soft tissue were r"], "order_basis": "paper_text_order:2535", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Differential expressions of genes between the OP and control datasets were screened using the “LIMMA” package in R (http://www.bioconductor.org/packages/release/bioc/html/limma.html)."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}