Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40328806", "kind": "science-record", "revision": 3, "content_hash": "sha256:5e3e7fd07e22c206b6593785ed463d8aec768d1e65b9ae63abe9cfe0b4f4a4de", "created_at": "2026-11-01T20:30:29Z", "updated_at": "2026-11-01T22:14:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated bioinformatics, machine learning, and molecular docking reveal crosstalk genes and potential drugs between periodontitis and systemic lupus erythematosus.", "doi": "10.1038/s41598-025-00620-3", "pmid": "40328806", "authors": ["Junjie Wang", "Qingao Deng", "Lu Qi"], "journal": "Scientific reports", "year": 2025, "abstract": "Evidence indicates a connection between periodontitis (PD) and systemic lupus erythematosus (SLE), though the underlying co-morbid mechanisms remain unclear. This study sought to identify the genetic factors and potential therapeutic agents involved in the interaction between PD and SLE. We employed multi-omics methodologies, encompassing differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment (GO/KEGG), LASSO regression, diagnostic model construction, protein-protein interaction (PPI) networks, immune infiltration profiling, computational drug prediction, molecular docking, and disease subtyping, to analyze PD and SLE expression datasets from the Gene Expression Omnibus (GEO) database (GSE10334, GSE16134, GSE50772, and GSE81622). Cross-analysis identified 32 crosstalk genes (CGs) common to both PD and SLE. LASSO analysis pinpointed three key diagnostic genes (TAGLN, MMP9, TNFAIP6) for both conditions. The resulting diagnostic models demonstrated robust efficacy in both training and validation datasets. Four topological algorithms in Cytoscape highlighted four central crosstalk genes (TAGLN, MMP9, TNFAIP6, IL1B). Additionally, hesperidin, doxycycline, and cytochalasin D emerged as potential therapeutic agents. Two subtypes (C1 and C2) of PD and SLE were delineated based on CG expression profiles. The development of diagnostic models, potential drug identification, and disease subtype classification are poised to enhance diagnosis and treatment. These findings aim to deepen the understanding of PD and SLE complexities.", "claims": [{"id": "claim-method", "statement": "To identify shared diagnostic genes for PD and SLE, we analyzed the CG matrices from GSE10334 and GSE50772 using the LASSO regression algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40328806", "locator": "sections[17] \"Selection of shared diagnostic genes by LASSO analysis\" paragraph 2", "quote": "To identify shared diagnostic genes for PD and SLE, we analyzed the CG matrices from GSE10334 and GSE50772 using the LASSO regression algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analysed during the current study are available in the GEO repository, https://www.ncbi.nlm.nih.gov/geo/repository. The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40328806", "locator": "sections[31] \"notes\" paragraph 1", "quote": "The datasets generated and/or analysed during the current study are available in the GEO repository, https://www.ncbi.nlm.nih.gov/geo/repository. The datasets used and analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Cross-analysis identified 32 crosstalk genes (CGs) common to both PD and SLE.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40328806", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Cross-analysis identified 32 crosstalk genes (CGs) common to both PD and SLE."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Cross-analysis identified 32 crosstalk genes (CGs) common to both PD and SLE.", "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:40328806"], "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:GSE10334"], "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:GSE10334"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40328806", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-00620-3", "sha256": "sha256:584cc4476cc2219fd8a3a21a279dcf43b3eb6af28aa15e430b993e205ac1e4fb", "bytes": 36970, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-00620-3", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12055969", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10334", "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=GSE10334", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10334", "version": null, "note": "The datasets generated and/or analysed during the current study are available in the GEO repository, https://www.ncbi.nlm.nih.gov/geo/repository. 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