IRF9 and XAF1 as Diagnostic Markers of Primary Sjogren Syndrome.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36132546", "kind": "science-record", "revision": 4, "content_hash": "sha256:cfaa6b5adfed14dd221a7dac3fec440b6a6e9828002852de63f134eed35d7181", "created_at": "2026-11-01T18:15:24Z", "updated_at": "2026-11-01T22:07:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "IRF9 and XAF1 as Diagnostic Markers of Primary Sjogren Syndrome.", "doi": "10.1155/2022/1867321", "pmid": "36132546", "authors": ["Lu Xiao", "Zhou Yang", "Shudian Lin"], "journal": "Computational and mathematical methods in medicine", "year": 2022, "abstract": "Objective: Primary Sjogren syndrome (pSS) is characterized by lymphocytic infiltration of the salivary and lacrimal glands. It is a chronic systemic autoimmune disease. Genetic contributions and disturbed biological systems are the two major causes of pSS, but its etiology is unclear. This study is aimed at identifying potential pSS diagnostic markers and mechanisms at the transcriptome level.\nMethods: Whole blood datasets of patients with pSS were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the online tool, GEO2R. R software was used to perform enrichment analyses to understand the functions and enriched pathways of the DEGs. A protein-protein interaction network was constructed to identify hub genes and significant gene clusters. The least absolute shrinkage and selection operator logistic regression was used to screen pSS diagnostic markers. The expression level and diagnostic performance of the identified genes were tested using another GEO dataset.\nResults: A total of 221 DEGs were screened from the whole blood samples of 161 patients with pSS and 59 healthy controls. Functional enrichment analysis demonstrated that DEGs were mostly enriched in defense response to virus, response to virus, and type I interferon signaling pathway. Cytoscape identified 10 hub genes and two gene clusters. IRF9 (AUC = 0.799) and XAF1 (AUC = 0.792) were identified as pSS diagnostic markers. The expression levels of the two identified genes were validated by GSE51092.\nConclusion: IRF9 and XAF1 were identified as diagnostic markers. The potential underlying molecular mechanism of pSS was explored.", "claims": [{"id": "claim-method", "statement": "LASSO logistic regression was used to perform feature selection to identify diagnostic markers for pSS.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36132546", "locator": "sections[8] \"2.6. Screening and Verification of Diagnostic Markers\" paragraph 2", "quote": "LASSO logistic regression was used to perform feature selection to identify diagnostic markers for pSS."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during the current study are available in the GEO repository. GEO is a free, publicly available repository database that stores a large number of gene functions and expression. The working links are as follows: GSE84844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84844), GSE66795 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66795), and GSE51092 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51092).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36132546", "locator": "sections[17] \"Data Availability\" paragraph 2", "quote": "The datasets generated and/or analyzed during the current study are available in the GEO repository. GEO is a free, publicly available repository database that stores a large number of gene functions and expression. The working links are as follows: GSE84844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84844), GSE66795 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66795), and GSE51092 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51092)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "IRF9 and XAF1 were identified as pSS diagnostic markers, with individual AUCs of 0.799 and 0.792 and a combined AUC of 0.822 in GSE51092.", "kind": "quantitative", "target": {"value": 0.822, "unit": "auc", "tolerance": null, "source": "When IRF9 and XAF1 were fitted into one variable, the diagnostic efficiency reached a higher level in the validation set (AUC = 0.822, Figure 4(d))."}, "evidence": [{"asset": "source:pmid:36132546", "locator": "sections[14] \"3.4. Screening and Verification of Diagnostic Markers\" paragraph 2", "quote": "The AUCs of IRF9 and XAF1 were 0.799 and 0.792, respectively, which indicated that IRF9 and XAF1 had certain diagnostic values (Figure 4(d))."}, {"asset": "source:pmid:36132546", "locator": "sections[14] \"3.4. Screening and Verification of Diagnostic Markers\" paragraph 2", "quote": "When IRF9 and XAF1 were fitted into one variable, the diagnostic efficiency reached a higher level in the validation set (AUC = 0.822, Figure 4(d))."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "IRF9 and XAF1 were identified as pSS diagnostic markers, with individual AUCs of 0.799 and 0.792 and a combined AUC of 0.822 in GSE51092.", "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:36132546"], "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:GSE51092"], "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:GSE51092"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36132546", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/1867321", "sha256": "sha256:1d6b39df7e67f4f7cd0f154de454ed19b85c93523d2b16e3a366be475bc3d6da", "bytes": 20776, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/1867321", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9484944", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE51092", "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=GSE51092", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE51092", "version": null, "note": "The datasets generated and/or analyzed during the current study are available in the GEO repository. 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The working links are as follows: GSE84844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84844), GSE66795 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66795), and GSE51092 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51092).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2252121", "GSM2252122", "GSM2252123", "GSM2252124", "GSM2252125", "GSM2252126", "GSM2252127", "GSM2252128", "GSM2252129", "GSM2252130", "GSM2252131", "GSM2252132", "GSM2252133", "GSM2252134", "GSM2252135", "GSM2252136", "GSM2252137", "GSM2252138", "GSM2252139", "GSM2252140", "GSM2252141", "GSM2252142", "GSM2252143", "GSM2252144", "GSM2252145", "GSM2252146", "GSM2252147", "GSM2252148", "GSM2252149", "GSM2252150", "GSM2252151", "GSM2252152", "GSM2252153", "GSM2252154", "GSM2252155", "GSM2252156", "GSM2252157", "GSM2252158", "GSM2252159", "GSM2252160", "GSM2252161", "GSM2252162", "GSM2252163", "GSM2252164", "GSM2252165", "GSM2252166", "GSM2252167", "GSM2252168", "GSM2252169", "GSM2252170", "GSM2252171", "GSM2252172", "GSM2252173", "GSM2252174", "GSM2252175", "GSM2252176", "GSM2252177", "GSM2252178", "GSM2252179", "GSM2252180"], "sample_count": 60, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Multi-omics profiling of patients with primary Sjogren's syndrome", "resolution_checked_at": "2026-11-01T18:06:44Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE51092 not downloaded", "asset:data:geo:GSE51092 licence not read", "asset:data:geo:GSE66795 not downloaded", "asset:data:geo:GSE66795 licence not read", "asset:data:geo:GSE84844 not downloaded", "asset:data:geo:GSE84844 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "LASSO logistic regression was used to perform feature selection to identify diagnostic markers for pSS."}}, {"id": "method-2", "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": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.822, "unit": "auc", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["glm_logit_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: logistic."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE84844", "GSE66795", "GSE51092"], "resolved_accessions": ["GSE84844", "GSE66795", "GSE51092"], "statements": ["The datasets generated and/or analyzed during the current study are available in the GEO repository. GEO is a free, publicly available repository database that stores a large number of gene functions and expression. The working links are as follows: GSE84844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84844), GSE66795 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66795), and GSE51092 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51092)."], "basis": "The paper names GSE84844, GSE66795, GSE51092 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["glm_logit_fit"], "assets": ["source:pmid:36132546", "data:geo:GSE51092"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE51092"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:06:17Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 6773, "completion_tokens": 1368, "cached_tokens": 128}}, "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:36132546", "type": "paper", "label": "pmid:36132546"}, {"id": "source:pmid:36132546", "type": "manuscript", "label": "PMID 36132546 full text"}, {"id": "data:geo:GSE51092", "type": "dataset", "label": "GEO GSE51092"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36132546", "type": "paper", "label": "pmid:36132546"}, {"id": "source:pmid:36132546", "type": "manuscript", "label": "PMID 36132546 full text"}, {"id": "data:geo:GSE51092", "type": "dataset", "label": "GEO GSE51092"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36132546", "type": "extraction", "used": ["source:pmid:36132546"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE51092", "type": "accession_resolution", "used": ["data:geo:GSE51092"], "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:36132546", "parent_hash": "sha256:f0f281236d5ef8f39b0fe94dd8dd97a3c710e554d9e1090495b04a72459f2f34", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE51092 licence not read", "asset:data:geo:GSE51092 not downloaded", "asset:data:geo:GSE66795 licence not read", "asset:data:geo:GSE66795 not downloaded", "asset:data:geo:GSE84844 licence not read", "asset:data:geo:GSE84844 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["LASSO logistic regression was used to perform feature selection to identify diagnostic markers for pSS."], "order_basis": "analysis_only", "id": "assay:1"}]}