Constructing a competing endogenous RNA network for osteoarthritis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35284549", "kind": "science-record", "revision": 5, "content_hash": "sha256:6119a6220b05e52d4b9650fabb7b19fc6168166c1a738e5b6b8df53a65458c4c", "created_at": "2026-11-01T18:14:04Z", "updated_at": "2026-11-01T22:48:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Constructing a competing endogenous RNA network for osteoarthritis.", "doi": "10.21037/atm-21-6711", "pmid": "35284549", "authors": ["Shu-Liang Hua", "Jun-Qing Liang", "Guo-Fang Hu", "Xi-Ren Yang", "Da-Lang Fang", "Ji-Li Lu"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Osteoarthritis (OA) is one of the most common diseases in elderly people; however, the correlation between molecular alterations and the occurrence and progression of OA are still not well understood. We conducted this study to investigate the molecular changes in OA via the competing endogenous ribonucleic acid (ceRNA) network.\nMethods: We downloaded the messenger RNA (mRNA) data set, GSE48556, the microRNA (miRNA) data set, GSE105027, and the long non-coding (lncRNA) data set, GSE126963 from the Gene Expression Omnibus (GEO) database, and examined the differentially expressed genes (DEGs) in these data sets. Further, we constructed a ceRNA network of the differentially expressed miRNAs, mRNAs, and lncRNAs. To determine the biological functions of the ceRNA network, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Finally, we conducted an immune cell infiltration analysisusing single-sample gene set enrichment analysis to examine the abundance of immune cells in healthy and OA patients, and compared the infiltration of 28 immune cells between the healthy and OA samples. We also analyzed the relationship between the abundance of immune cells and mRNA expression levels in the ceRNA network.\nResults: Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network. The functional enrichment analyses showed that these lncRNAs, miRNAs, and mRNAs are involved in various significant biological process, such as the regulation of leukocyte migration, Mitogen-Activated Protein (MAP) kinase tyrosine/serine/threonine phosphatase activity, the interleukin-17 signaling pathway, the tumor necrosis factor signaling pathway, and osteoclast differentiation, and can also have a strong effect on immune cell infiltration.\nConclusions: The dual-specificity phosphatase 1-specific ceRNA network can be used as a diagnostic tool to assess the progression of OA patients.", "claims": [{"id": "claim-method", "statement": "The LIMMA package was used for the differential gene analysis, and the thresholds were set to |logFC|>0.3 and a P value <0.05. 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The Wilcoxon non-parameter test was used for comparisons between 2 groups, and the Spearman method was used for the correlation analysis."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35284549", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network.", "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:35284549"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon", "step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35284549", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/atm-21-6711", "sha256": "sha256:c69e9d28ef8b20b5a3a46f75edf1d36db5821806cefe4d0e7f0662dcf63b3cce", "bytes": 21881, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/atm-21-6711", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8904995", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The LIMMA package was used for the differential gene analysis, and the thresholds were set to |logFC|>0.3 and a P value <0.05. 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