Integration of metabolomics and transcriptomics provides insights into the molecular mechanism of temporomandibular joint osteoarthritis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38753666", "kind": "science-record", "revision": 5, "content_hash": "sha256:a5f1a0ee08bc12b7f123f58bca0e1324b98726038875e756c34166e4b784c5b8", "created_at": "2026-11-01T19:20:42Z", "updated_at": "2026-11-01T22:54:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integration of metabolomics and transcriptomics provides insights into the molecular mechanism of temporomandibular joint osteoarthritis.", "doi": "10.1371/journal.pone.0301341", "pmid": "38753666", "authors": ["Palati Tuerxun", "Takkun Ng", "Ke Zhao", "Ping Zhu"], "journal": "PloS one", "year": 2024, "abstract": "The deficiency of clinically specific biomarkers has made it difficult to achieve an accurate diagnosis of temporomandibular joint osteoarthritis (TMJ-OA) and the insufficient comprehension of the pathogenesis of the pathogenesis of TMJ-OA has posed challenges in advancing therapeutic measures. The combined use of metabolomics and transcriptomics technologies presents a highly effective method for identifying vital metabolic pathways and key genes in TMJ-OA patients. In this study, an analysis of synovial fluid untargeted metabolomics of 6 TMJ-OA groups and 6 temporomandibular joint reducible anterior disc displacement (TMJ-DD) groups was conducted using liquid and gas chromatography mass spectrometry (LC/GC-MS). The differential metabolites (DMs) between TMJ-OA and TMJ-DD groups were analyzed through multivariate analysis. Meanwhile, a transcriptomic dataset (GSE205389) was obtained from the GEO database to analyze the differential metabolism-related genes (DE-MTGs) between TMJ-OA and TMJ-DD groups. Finally, an integrated analysis of DMs and DE-MTGs was carried out to investigate the molecular mechanisms associated with TMJ-OA. The analysis revealed significant differences in the levels of 46 DMs between TMJ-OA and TMJ-DD groups, of which 3 metabolites (L-carnitine, taurine, and adenosine) were identified as potential biomarkers for TMJ-OA. Collectively, differential expression analysis identified 20 DE-MTGs. Furthermore, the integration of metabolomics and transcriptomics analysis revealed that the tricarboxylic acid (TCA) cycle, alanine, aspartate and glutamate metabolism, ferroptosis were significantly enriched. This study provides valuable insights into the metabolic abnormalities and associated pathogenic mechanisms, improving our understanding of TMJOA etiopathogenesis and facilitating potential target screening for therapeutic intervention.", "claims": [{"id": "claim-method", "statement": "The “limma” package [19] for RStudio was utilized to identify differentially expressed genes (DEGs) between TMJ-OA and TMJ-DD in the GSE205389 datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38753666", "locator": "sections[8] \"Differential metabolism-related genes between TMJ-OA and TMJ-DD\" paragraph 3", "quote": "The “limma” package [19] for RStudio was utilized to identify differentially expressed genes (DEGs) between TMJ-OA and TMJ-DD in the GSE205389 datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All transcriptomic files are available from the GEO database (accession number(s) GSE205389, GSE205684.).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38753666", "locator": "sections[21] \"Data Availability\" paragraph 2", "quote": "All transcriptomic files are available from the GEO database (accession number(s) GSE205389, GSE205684.)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 549 differentially expressed genes and 20 differentially expressed metabolism-related genes between TMJ-OA and TMJ-DD groups.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38753666", "locator": "sections[15] \"Identification of DEGs and DE-MTGs\" paragraph 2", "quote": "A total of 549 DEGs (291 upregulated genes and 258 downregulated genes) were identified (S2 Table)."}, {"asset": "source:pmid:38753666", "locator": "sections[15] \"Identification of DEGs and DE-MTGs\" paragraph 2", "quote": "The 20 DE-MTGs identified by overlapping were selected (Fig 4B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 549 differentially expressed genes and 20 differentially expressed metabolism-related genes between TMJ-OA and TMJ-DD groups.", "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:38753666"], "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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