Roles of Pyroptosis-Related Genes in the Diagnosis and Subtype Classification of Periodontitis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37090158", "kind": "science-record", "revision": 4, "content_hash": "sha256:f02d0fb8ac84007f930b3a31352daa743ae79edf5345e3fb3f1d053f0607ec1e", "created_at": "2026-11-01T19:01:45Z", "updated_at": "2026-11-01T22:51:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Roles of Pyroptosis-Related Genes in the Diagnosis and Subtype Classification of Periodontitis.", "doi": "10.1155/2023/8757233", "pmid": "37090158", "authors": ["Xiaofan Cheng", "Yifang Hu", "Guan Gui", "Xiaoya Hu", "Jie Zhu", "Bowei Shi", "Shoushan Bu"], "journal": "Journal of immunology research", "year": 2023, "abstract": "Pyroptosis is widely involved in many diseases, including periodontitis. Nonetheless, the functions of pyroptosis-related genes (PRGs) in periodontitis are still not fully elucidated. Therefore, we aimed to investigate the role of PRGs in periodontitis. Three datasets (GSE10334, GSE16134, and GSE173078) from the Gene Expression Omnibus (GEO) were selected to analyze the differences in expression values of the PRGs between nonperiodontitis and periodontitis tissue samples using difference analysis. Following this, five hub PRGs (charged multivesicular body protein 2B, granzyme B, Z-DNA-binding protein 1, interleukin-1β, and interferon regulatory factor 1) predicting periodontitis susceptibility were screened by establishing a random forest model, and a predictive nomogram model was constructed on the basis of these genes. Decision curve analysis suggested that the PRG-based predictive nomogram model could provide clinical benefits to patients. Three distinct PRG patterns (cluster A, cluster B, and cluster C) in the periodontitis samples were revealed according to the 48 significant PRGs, and the difference in the immune cell infiltration among the three patterns was explored. We observed that all infiltrating immune cells, except type 2 T helper cells, differ significantly among the three patterns. To quantify the PRG patterns, the PRG score was calculated by principal component analysis. According to the results, cluster B had the highest PRG score, followed by cluster A and cluster C. In conclusion, PRGs significantly contribute to the development of periodontitis. Our study of PRG patterns might open up a new avenue to guide individualized treatment plans for patients with periodontitis.", "claims": [{"id": "claim-method", "statement": "The differences in PRGs expression values between the healthy and periodontitis samples were analyzed utilizing the “limma” package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37090158", "locator": "sections[4] \"2.2. Landscape of the PRGs\" paragraph 2", "quote": "The differences in PRGs expression values between the healthy and periodontitis samples were analyzed utilizing the “limma” package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in this study are available in GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37090158", "locator": "sections[22] \"Data Availability\" paragraph 2", "quote": "The datasets analyzed in this study are available in GEO database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Across three GEO datasets, difference analysis identified 48 significant PRGs and supported three periodontitis PRG patterns with distinct immune-cell infiltration profiles.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37090158", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Three datasets (GSE10334, GSE16134, and GSE173078) from the Gene Expression Omnibus (GEO) were selected to analyze the differences in expression values of the PRGs between nonperiodontitis and periodontitis tissue samples using difference analysis."}, {"asset": "source:pmid:37090158", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Three distinct PRG patterns (cluster A, cluster B, and cluster C) in the periodontitis samples were revealed according to the 48 significant PRGs, and the difference in the immune cell infiltration among the three patterns was explored."}, {"asset": "source:pmid:37090158", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We observed that all infiltrating immune cells, except type 2 T helper cells, differ significantly among the three patterns."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Across three GEO datasets, difference analysis identified 48 significant PRGs and supported three periodontitis PRG patterns with distinct immune-cell infiltration profiles.", "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:37090158"], "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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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["pca_fit"], "assets": ["source:pmid:37090158", "data:geo:GSE10334"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE10334"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:37:18Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12930, "completion_tokens": 2041, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:37090158", "type": "paper", "label": "pmid:37090158"}, {"id": "source:pmid:37090158", "type": "manuscript", "label": "PMID 37090158 full text"}, {"id": "data:geo:GSE10334", "type": "dataset", "label": "GEO GSE10334"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37090158", "type": "paper", "label": "pmid:37090158"}, {"id": "source:pmid:37090158", "type": "manuscript", "label": "PMID 37090158 full text"}, {"id": "data:geo:GSE10334", "type": "dataset", "label": "GEO GSE10334"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37090158", "type": "extraction", "used": ["source:pmid:37090158"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE10334", "type": "accession_resolution", "used": ["data:geo:GSE10334"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:37090158", "parent_hash": "sha256:4e69098bc39d0cab3d26b8b913c971ffba2c93ac48bede19e2e1e0b710906c25", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE10334 licence not read", "asset:data:geo:GSE10334 not downloaded", "asset:data:geo:GSE16134 licence not read", "asset:data:geo:GSE16134 not downloaded", "asset:data:geo:GSE173078 licence not read", "asset:data:geo:GSE173078 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "principal_component_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pca_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The differences in PRGs expression values between the healthy and periodontitis samples were analyzed utilizing the “limma” package in R."], "order_basis": "analysis_only", "id": "assay:1"}]}