Mechanism of lysine oxidase-like 1 promoting synovial inflammation mediating rheumatoid arthritis development.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38217541", "kind": "science-record", "revision": 4, "content_hash": "sha256:913a8cd9de380412e099eba4c5601359a93b26638b62dda81847fbbd19b069bf", "created_at": "2026-11-01T19:20:08Z", "updated_at": "2026-11-01T22:53:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Mechanism of lysine oxidase-like 1 promoting synovial inflammation mediating rheumatoid arthritis development.", "doi": "10.18632/aging.205429", "pmid": "38217541", "authors": ["Jiawei Hu", "Xuqiang Liu", "Qiang Xu", "Meisong Zhu", "Song Wang", "Kun Quan", "Min Dai", "Fengbo Mo", "Haibo Zhan"], "journal": "Aging", "year": 2024, "abstract": "Rheumatoid arthritis (RA) is a chronic inflammatory joint disease that causes great distress to patients and society. Early diagnosis is the key to the successful treatment of RA. The basement membrane, one of the oldest tissue structures, is localized under the epithelium. Its complex composition and rich biological functions have made it a focus of research in recent years, while basement membrane-associated genetic variants are involved in most human disease processes. The aim of this study is to find new diagnostic biomarkers for RA and explore their role and possible mechanism in rheumatoid arthritis. The GSE12021, GSE55235 and GSE55457 datasets were downloaded from the GEO database. Their fraction associated with basement membrane genes was analyzed and differentially expressed genes between the disease and normal groups were explored. We identified two basement membrane-associated genes, lysine oxidase-like 1 (LOXL1) and discoid peptide receptor 2 (DDR2). Focusing on the more interesting LOXL1, we found that LOXL1 expression was significantly elevated in the synovium of patients with rheumatoid arthritis, and LOXL1 mRNA and protein levels were elevated in tumor necrosis factor α-stimulated human synovial sarcoma cells (SW982). And LOXL1 knockdown inhibited tumor necrosis factor α-induced inhibition in SW982 cells expression of inducible nitric oxide synthase (INOS), cyclooxygenase-2 (COX2), and interleukin-6 (IL-6). Interestingly, knockdown of LOXL1 inhibited the phosphorylation of PI3K and AKT. In summary, LOXL1 may become a novel diagnostic gene for RA, and knockdown of LoxL1 may inhibit synovial inflammation by affecting PI3K/AKT pathway.", "claims": [{"id": "claim-method", "statement": "Basement membrane-associated differential genes between rheumatoid arthritis and healthy samples were identified using the Limma package in R. LASSO is a regression analysis algorithm that uses regularization to improve prediction accuracy by identifying genes with significant differences between basement membrane-associated RA and normal subjects through the “glmnet” package in R. Support Vector Machines (SVMs) are widely used for classification and regression analysis. We used recursive feature elimination (RFE) to circumvent overfitting. To obtain the most significant gene sets, SVM Recursive Feature Elimination (SVM-RFE) was used to screen appropriate features.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38217541", "locator": "sections[11] \"Analysis of basement membrane-associated differential genes and integrated microarray datasets\" paragraph 2", "quote": "Basement membrane-associated differential genes between rheumatoid arthritis and healthy samples were identified using the Limma package in R."}, {"asset": "source:pmid:38217541", "locator": "sections[13] \"Diagnostic gene selection\" paragraph 2", "quote": "LASSO is a regression analysis algorithm that uses regularization to improve prediction accuracy by identifying genes with significant differences between basement membrane-associated RA and normal subjects through the “glmnet” package in R."}, {"asset": "source:pmid:38217541", "locator": "sections[13] \"Diagnostic gene selection\" paragraph 2", "quote": "Support Vector Machines (SVMs) are widely used for classification and regression analysis."}, {"asset": "source:pmid:38217541", "locator": "sections[13] \"Diagnostic gene selection\" paragraph 2", "quote": "We used recursive feature elimination (RFE) to circumvent overfitting."}, {"asset": "source:pmid:38217541", "locator": "sections[13] \"Diagnostic gene selection\" paragraph 2", "quote": "To obtain the most significant gene sets, SVM Recursive Feature Elimination (SVM-RFE) was used to screen appropriate features."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38217541", "locator": "sections[16] \"Data availability statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The AUC value for DDR2 was 0.885, and the ROC value for LOXL1 was 0.836.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38217541", "locator": "sections[20] \"Identification of diagnostic markers and analysis of their diagnostic value\" paragraph 2", "quote": "The AUC value for DDR2 was 0.885, and the ROC value for LOXL1 was 0.836."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The AUC value for DDR2 was 0.885, and the ROC value for LOXL1 was 0.836.", "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:38217541"], "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:GSE12021"], "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:GSE12021"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38217541", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.205429", "sha256": 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LASSO is a regression analysis algorithm that uses regularization to improve prediction accuracy by identifying genes with significant differences between basement membrane-associated RA and normal subjects through the “glmnet” package in R. Support Vector Machines (SVMs) are widely used for classification and regression analysis. We used recursive feature elimination (RFE) to circumvent overfitting. 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And LOXL1 knockdown inhibited tumor necrosis factor α-induced in", "2), and interleukin-6 (IL-6). Interestingly, knockdown of LOXL1 inhibited the phosphorylation of PI", "y become a novel diagnostic gene for RA, and knockdown of LoxL1 may inhibit synovial inflammation b"], "order_basis": "paper_text_order:1330", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["from Pricella (Wuhan, China). The cells were cultured in DMEM containing 10% extra fetal bovine serum", "nged once every 2–3 days, and the cells were passaged when the cell fusion reached 90% or more. 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