The expression of RBPJ and its potential role in rheumatoid arthritis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39350019", "kind": "science-record", "revision": 4, "content_hash": "sha256:a1aa8bd225021e604dbe4b215efc659066f43ae3632883301cc5004a25e5a2e4", "created_at": "2026-11-01T20:29:33Z", "updated_at": "2026-11-01T22:55:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The expression of RBPJ and its potential role in rheumatoid arthritis.", "doi": "10.1186/s12864-024-10804-2", "pmid": "39350019", "authors": ["Shuaishuai Chen", "Weibo Zhao", "Juping Du", "Suyun Chen", "Jun Li", "Bo Shen", "Yuanlin Zhou", "Shiyong Chen"], "journal": "BMC genomics", "year": 2024, "abstract": "BACKGROUND: Recombination signal-binding protein for immunoglobulin kappa J region (RBPJ) is a transcriptional regulator that plays an important role in maintaining immune homeostasis. This study aimed to estimate the expression of RBPJ in rheumatoid arthritis (RA) patients and investigate its relationship with RA.\nMETHODS: A total of 83 newly diagnosed RA patients and 70 healthy controls were included. mRNA was extracted from peripheral blood mononuclear cells (PBMCs), and the expression of RBPJ was detected using quantitative real-time PCR (qRT‒PCR). An RA dataset (GSE89408) was obtained from the Gene Expression Omnibus (GEO) database, and RA synovial tissues were divided into two groups. The differentially expressed genes (DEGs) were selected with the \"DESeq2\" R package.\nRESULTS: RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR). RA synovial tissues from GSE89408 were classified into RBPJ-low (≤ 25%) and RBPJ-high (≥ 75%) groups according to RBPJ expression, and 562 DEGs were identified. Gene Ontology (GO) enrichment analyses revealed that the DEGs significantly affected the regulation of T cell activation and lymphocyte/mononuclear cell differentiation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the most enriched pathways of DEGs were the T cell receptor signaling pathway, Th1/2 and Th17 cell differentiation, the PI3K - Akt signaling pathway and cytokine‒cytokine receptor interaction. CytoHubba Plugin revealed that most of the top 10 genes were involved in osteoclast differentiation, the T cell receptor signaling pathway and cytokine‒cytokine receptor interaction.\nCONCLUSIONS: RBPJ expression was significantly lower in RA patients and negatively correlated with disease activity. GEO dataset analysis demonstrated that RBPJ may be involved in osteoclast differentiation, T cell activation and differentiation, and the T cell receptor signaling pathway. Our research may contribute to understanding the potential mechanisms by which RBPJ regulates T cell differentiation and cytokine‒cytokine receptor interaction in RA patients.", "claims": [{"id": "claim-method", "statement": "The relative RBPJ mRNA expression data were analyzed by SPSS 23.0 statistical software (IBM Corp., Armonk, N.Y., USA) and compared using Student’s t test. The correlations between RBPJ and laboratory indicators were determined using Spearman’s correlation analysis. The DEGs between the two groups were selected using the “DESeq2” R package (version 4.3.1) with the following thresholds: adjusted p value < 0.01 and |log2 fold change| > 1.2.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39350019", "locator": "sections[8] \"Statistical analysis\" paragraph 2", "quote": "The relative RBPJ mRNA expression data were analyzed by SPSS 23.0 statistical software (IBM Corp., Armonk, N.Y., USA) and compared using Student’s t test."}, {"asset": "source:pmid:39350019", "locator": "sections[8] \"Statistical analysis\" paragraph 2", "quote": "The correlations between RBPJ and laboratory indicators were determined using Spearman’s correlation analysis."}, {"asset": "source:pmid:39350019", "locator": "sections[5] \"GEO database analyses of RBPJ expression in RA synovial tissues\" paragraph 2", "quote": "The DEGs between the two groups were selected using the “DESeq2” R package (version 4.3.1) with the following thresholds: adjusted p value < 0.01 and |log2 fold change| > 1.2."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data were obtained from the GEO DataSets (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89408). The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39350019", "locator": "sections[24] \"notes\" paragraph 1", "quote": "The data were obtained from the GEO DataSets (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89408). The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39350019", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR).", "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:39350019"], "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:GSE89408"], "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:GSE89408"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39350019", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12864-024-10804-2", "sha256": "sha256:c396e1afb11a765c80b444591dab7c08197d1df03b7a3c44721a4efd75a3eaed", "bytes": 35029, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12864-024-10804-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11441141", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE89408", "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=GSE89408", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE89408", "version": null, "note": "The data were obtained from the GEO DataSets (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89408). The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data were obtained from the GEO DataSets (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE89408). 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The correlations between RBPJ and laboratory indicators were determined using Spearman’s correlation analysis. The DEGs between the two groups were selected using the “DESeq2” R package (version 4.3.1) with the following thresholds: adjusted p value < 0.01 and |log2 fold change| > 1.2."}}, {"id": "method-2", "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": 0.8, "band": "high", "quote": "PPI"}}], "targets": [], "gaps": []}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: deseq2."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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An RA dataset (GSE89408) was obta", "asured by qRT‒PCR using BeyoFast™ SYBR Green qPCR mix (high Rox) with a Step-One Plus Real-Tim", "Materials and methods Quantitative real-time PCR analysis of PBMCs We collected fresh periphe", "een qPCR mix (high Rox) with a Step-One Plus Real-Time PCR system (ABI). The procedure conditions were"], "order_basis": "paper_text_order:560", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The relative RBPJ mRNA expression data were analyzed by SPSS 23.0 statistical software (IBM Corp., Armonk, N.Y., USA) and compared using Student’s t test. The correlations between RBPJ and laboratory indicators were determined using Spearman’s correlation analysis. The DEGs between the two groups were selected using the “DESeq2” R package (version 4.3.1) with the following thresholds: adjusted p value < 0.01 and |log2 fold change| > 1.2."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}