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pmid:40109657

Identification of RSAD2 as a Key Biomarker Linking Iron Metabolism and Dendritic Cell Activation in Systemic Lupus Erythematosus Through Bioinformatics and Experimental Validation.

Hengrong Qian · Sheng Gao · Ting Zhang · Yuanyuan Xie · Siyan Chen · Yanggang Hong · Xinlei Wu · Zhouhang Xing · Lingjie Kong · Jintao Mo · Yiming Lin · Anzhe Zheng · Wenqian Wang · Liangxing Wang · Chunyan Hua

Journal of inflammation research · 2025 doi:10.2147/JIR.S500115

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Experiment

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Data

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title
Identification of RSAD2 as a Key Biomarker Linking Iron Metabolism and Dendritic Cell Activation in Systemic Lupus Erythematosus Through Bioinformatics and Experimental Validation.
doi
10.2147/JIR.S500115
pmid
40109657
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[0]
Hengrong Qian
[1]
Sheng Gao
[2]
Ting Zhang
[3]
Yuanyuan Xie
[4]
Siyan Chen
[5]
Yanggang Hong
[6]
Xinlei Wu
[7]
Zhouhang Xing
[8]
Lingjie Kong
[9]
Jintao Mo
[10]
Yiming Lin
[11]
Anzhe Zheng
[12]
Wenqian Wang
[13]
Liangxing Wang
[14]
Chunyan Hua
journal
Journal of inflammation research
year
2025
abstract
Background: Systemic lupus erythematosus (SLE) is characterized by aberrant immune activation and disrupted iron metabolism, yet the molecular mediators that govern both processes remain unclear. This study aims to identify pivotal genes that modulate immune responses and iron metabolism, and to delineate their contributions to SLE pathogenesis. Methods: Differentially expressed genes related to iron metabolism (IM-DEGs) were identified using datasets (GSE72326, GSE110169, GSE126307, and GSE50772) from the GEO database and the MSigDB. Functional enrichment analyses were performed on the iron metabolism related genes (IM-Genes). A weighted gene co-expression network analysis was constructed to identify hub genes, which were further refined as potential biomarkers using the least absolute shrinkage and selection operator method. The predictive value of these biomarkers was validated using receiver operating characteristic (ROC) curves and the nomogram. CIBERSORT was employed to evaluate immune cell infiltration in SLE. Additionally, the expression and function of RSAD2 were confirmed using RNA interference, quantitative real-time PCR, and Western blotting techniques. Results: Bioinformatics analyses identified 4 potential biomarkers: RSAD2, MT2A, LCN2, and LTF. RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators. Its diagnostic potential was confirmed through ROC curve and nomogram, highlighting its role in SLE pathogenesis. Elevated RSAD2 expression was observed in peripheral blood mononuclear cells of SLE patients, positively correlating with activated dendritic cells (DCs). Notably, Rsad2 knockdown markedly impaired the function of activated DCs, as evidenced by suppressed expression of inflammatory mediators and iron metabolism-related genes. Conclusion: Our findings suggest that RSAD2 is a potential diagnostic biomarker and therapeutic target for SLE, elucidating the intricate relationship between immune dysregulation and aberrant iron metabolism in activated DCs, which exacerbates SLE.
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The 124 IM-Genes were subsequently subjected to LASSO regression algorithm to pinpoint high-value diagnostic biomarkers.
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sections[24] "Identification of RSAD2 as a Key Biomarker in SLE-Associated Iron Metabolism" paragraph 2
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The 124 IM-Genes were subsequently subjected to LASSO regression algorithm to pinpoint high-value diagnostic biomarkers.
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The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.
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The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.
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RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators.
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RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators.
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RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators.
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GSM1228940
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null
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570
taxon
Homo sapiens
title
Expression data in PBMCs from SLE patients and controls
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[4] object · 15 fields
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data:geo:GSE72326
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sha256
null
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null
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null
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The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.
structure object · 15 fields
repository
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GEO accession URL
access_statement_verbatim
The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.
access_statement_kind
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10558
taxon
Homo sapiens
title
Modular transcriptional repertoire analyses identify neutrophil signature as candidate biomarker for lupus nephritis
resolution_checked_at
2026-11-01T20:16:08Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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[7]
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The 124 IM-Genes were subsequently subjected to LASSO regression algorithm to pinpoint high-value diagnostic biomarkers.
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The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none.
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capability object · 3 fields
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
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The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.
basis
The paper names GSE72326, GSE110169, GSE126307, GSE50772 in NCBI GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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minimax
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2026-11-01T19:48:52Z
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40109657", "kind": "science-record", "revision": 3, "content_hash": "sha256:4410b0b07190c1c809e3b3ba26536976e8d2df2d5b89ce524f9a99c48da7a082", "created_at": "2026-11-01T20:30:18Z", "updated_at": "2026-11-01T22:13:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of RSAD2 as a Key Biomarker Linking Iron Metabolism and Dendritic Cell Activation in Systemic Lupus Erythematosus Through Bioinformatics and Experimental Validation.", "doi": "10.2147/JIR.S500115", "pmid": "40109657", "authors": ["Hengrong Qian", "Sheng Gao", "Ting Zhang", "Yuanyuan Xie", "Siyan Chen", "Yanggang Hong", "Xinlei Wu", "Zhouhang Xing", "Lingjie Kong", "Jintao Mo", "Yiming Lin", "Anzhe Zheng", "Wenqian Wang", "Liangxing Wang", "Chunyan Hua"], "journal": "Journal of inflammation research", "year": 2025, "abstract": "Background: Systemic lupus erythematosus (SLE) is characterized by aberrant immune activation and disrupted iron metabolism, yet the molecular mediators that govern both processes remain unclear. This study aims to identify pivotal genes that modulate immune responses and iron metabolism, and to delineate their contributions to SLE pathogenesis.\nMethods: Differentially expressed genes related to iron metabolism (IM-DEGs) were identified using datasets (GSE72326, GSE110169, GSE126307, and GSE50772) from the GEO database and the MSigDB. Functional enrichment analyses were performed on the iron metabolism related genes (IM-Genes). A weighted gene co-expression network analysis was constructed to identify hub genes, which were further refined as potential biomarkers using the least absolute shrinkage and selection operator method. The predictive value of these biomarkers was validated using receiver operating characteristic (ROC) curves and the nomogram. CIBERSORT was employed to evaluate immune cell infiltration in SLE. Additionally, the expression and function of RSAD2 were confirmed using RNA interference, quantitative real-time PCR, and Western blotting techniques.\nResults: Bioinformatics analyses identified 4 potential biomarkers: RSAD2, MT2A, LCN2, and LTF. RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators. Its diagnostic potential was confirmed through ROC curve and nomogram, highlighting its role in SLE pathogenesis. Elevated RSAD2 expression was observed in peripheral blood mononuclear cells of SLE patients, positively correlating with activated dendritic cells (DCs). Notably, Rsad2 knockdown markedly impaired the function of activated DCs, as evidenced by suppressed expression of inflammatory mediators and iron metabolism-related genes.\nConclusion: Our findings suggest that RSAD2 is a potential diagnostic biomarker and therapeutic target for SLE, elucidating the intricate relationship between immune dysregulation and aberrant iron metabolism in activated DCs, which exacerbates SLE.", "claims": [{"id": "claim-method", "statement": "The 124 IM-Genes were subsequently subjected to LASSO regression algorithm to pinpoint high-value diagnostic biomarkers.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40109657", "locator": "sections[24] \"Identification of RSAD2 as a Key Biomarker in SLE-Associated Iron Metabolism\" paragraph 2", "quote": "The 124 IM-Genes were subsequently subjected to LASSO regression algorithm to pinpoint high-value diagnostic biomarkers."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40109657", "locator": "sections[33] \"Data Sharing Statement\" paragraph 2", "quote": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators.", "kind": "quantitative", "target": {"value": 0.927, "unit": "auc", "tolerance": null, "source": "RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators."}, "evidence": [{"asset": "source:pmid:40109657", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RSAD2 exhibited the highest clinical validity (AUC = 0.927) and was closely associated with classic diagnostic indicators.", "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:40109657"], "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:GSE110169"], "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:GSE110169"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40109657", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/JIR.S500115", "sha256": "sha256:1c6e213e8a2da24269da7864cb44d7a1ad16a4dc64ebe677ad5d8912346d0c4c", "bytes": 53030, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/JIR.S500115", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11920641", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE110169", "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=GSE110169", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE110169", "version": null, "note": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2981057", "GSM2981058", "GSM2981059", "GSM2981060", "GSM2981061", "GSM2981062", "GSM2981063", "GSM2981064", "GSM2981065", "GSM2981066", "GSM2981067", "GSM2981068", "GSM2981069", "GSM2981070", "GSM2981071", "GSM2981072", "GSM2981073", "GSM2981074", "GSM2981075", "GSM2981076", "GSM2981077", "GSM2981078", "GSM2981079", "GSM2981080", "GSM2981081", "GSM2981082", "GSM2981083", "GSM2981084", "GSM2981085", "GSM2981086", "GSM2981087", "GSM2981088", "GSM2981089", "GSM2981090", "GSM2981091", "GSM2981092", "GSM2981093", "GSM2981094", "GSM2981095", "GSM2981096", "GSM2981097", "GSM2981098", "GSM2981099", "GSM2981100", "GSM2981101", "GSM2981102", "GSM2981103", "GSM2981104", "GSM2981105", "GSM2981106", "GSM2981107", "GSM2981108", "GSM2981109", "GSM2981110", "GSM2981111", "GSM2981112", "GSM2981113", "GSM2981114", "GSM2981115", "GSM2981116", "GSM2981117", "GSM2981118", "GSM2981119", "GSM2981120", "GSM2981121", "GSM2981122", "GSM2981123", "GSM2981124", "GSM2981125", "GSM2981126", "GSM2981127", "GSM2981128", "GSM2981129", "GSM2981130", "GSM2981131", "GSM2981132", "GSM2981133", "GSM2981134", "GSM2981135", "GSM2981136", "GSM2981137", "GSM2981138", "GSM2981139", "GSM2981140", "GSM2981141", "GSM2981142", "GSM2981143", "GSM2981144", "GSM2981145", "GSM2981146", "GSM2981147", "GSM2981148", "GSM2981149", "GSM2981150", "GSM2981151", "GSM2981152", "GSM2981153", "GSM2981154", "GSM2981155", "GSM2981156", "GSM2981157", "GSM2981158", "GSM2981159", "GSM2981160", "GSM2981161", "GSM2981162", "GSM2981163", "GSM2981164", "GSM2981165", "GSM2981166", "GSM2981167", "GSM2981168", "GSM2981169", "GSM2981170", "GSM2981171", "GSM2981172", "GSM2981173", "GSM2981174", "GSM2981175", "GSM2981176", "GSM2981177", "GSM2981178", "GSM2981179", "GSM2981180", "GSM2981181", "GSM2981182", "GSM2981183", "GSM2981184", "GSM2981185", "GSM2981186", "GSM2981187", "GSM2981188", "GSM2981189", "GSM2981190", "GSM2981191", "GSM2981192", "GSM2981193", "GSM2981194", "GSM2981195", "GSM2981196", "GSM2981197", "GSM2981198", "GSM2981199", "GSM2981200", "GSM2981201", "GSM2981202", "GSM2981203", "GSM2981204", "GSM2981205", "GSM2981206", "GSM2981207", "GSM2981208", "GSM2981209", "GSM2981210", "GSM2981211", "GSM2981212", "GSM2981213", "GSM2981214", "GSM2981215", "GSM2981216", "GSM2981217", "GSM2981218", "GSM2981219", "GSM2981220", "GSM2981221", "GSM2981222", "GSM2981223", "GSM2981224", "GSM2981225", "GSM2981226", "GSM2981227", "GSM2981228", "GSM2981229", "GSM2981230", "GSM2981231", "GSM2981232", "GSM2981233", "GSM2981234", "GSM2981235", "GSM2981236", "GSM2981237", "GSM2981238", "GSM2981239", "GSM2981240", "GSM2981241", "GSM2981242", "GSM2981243", "GSM2981244", "GSM2981245", "GSM2981246", "GSM2981247", "GSM2981248", "GSM2981249", "GSM2981250", "GSM2981251", "GSM2981252", "GSM2981253", "GSM2981254", "GSM2981255", "GSM2981256", "GSM2981257", "GSM2981258", "GSM2981259", "GSM2981260", "GSM2981261", "GSM2981262", "GSM2981263", "GSM2981264", "GSM2981265", "GSM2981266", "GSM2981267", "GSM2981268", "GSM2981269", "GSM2981270", "GSM2981271", "GSM2981272", "GSM2981273", "GSM2981274", "GSM2981275", "GSM2981276", "GSM2981277", "GSM2981278", "GSM2981279", "GSM2981280", "GSM2981281", "GSM2981282", "GSM2981283", "GSM2981284", "GSM2981285", "GSM2981286", "GSM2981287", "GSM2981288", "GSM2981289", "GSM2981290", "GSM2981291", "GSM2981292", "GSM2981293", "GSM2981294", "GSM2981295", "GSM2981296", "GSM2981297", "GSM2981298", "GSM2981299"], "sample_count": 243, "group_sizes": null, "group_sizes_basis": null, "platform": "13667", "taxon": "Homo sapiens", "title": "BMS_TRD_SLE_RA_WB_study", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE126307", "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=GSE126307", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE126307", "version": null, "note": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3595978", "GSM3595979", "GSM3595980", "GSM3595981", "GSM3595982", "GSM3595983", "GSM3595984", "GSM3595985", "GSM3595986", "GSM3595987", "GSM3595988", "GSM3595989", "GSM3595990", "GSM3595991", "GSM3595992", "GSM3595993", "GSM3595994", "GSM3595995", "GSM3595996", "GSM3595997", "GSM3595998", "GSM3595999", "GSM3596000", "GSM3596001", "GSM3596002", "GSM3596003", "GSM3596004", "GSM3596005", "GSM3596006", "GSM3596007", "GSM3596008", "GSM3596009", "GSM3596010", "GSM3596011", "GSM3596012", "GSM3596013", "GSM3596014", "GSM3596015", "GSM3596016", "GSM3596017"], "sample_count": 40, "group_sizes": null, "group_sizes_basis": null, "platform": "13369", "taxon": "Homo sapiens", "title": "Functional rare and low frequency variants in BLK and BANK contribute to human lupus pathogenesis", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE50772", "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=GSE50772", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE50772", "version": null, "note": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1228860", "GSM1228861", "GSM1228862", "GSM1228863", "GSM1228864", "GSM1228865", "GSM1228866", "GSM1228867", "GSM1228868", "GSM1228869", "GSM1228870", "GSM1228871", "GSM1228872", "GSM1228873", "GSM1228874", "GSM1228875", "GSM1228876", "GSM1228877", "GSM1228878", "GSM1228879", "GSM1228880", "GSM1228881", "GSM1228882", "GSM1228883", "GSM1228884", "GSM1228885", "GSM1228886", "GSM1228887", "GSM1228888", "GSM1228889", "GSM1228890", "GSM1228891", "GSM1228892", "GSM1228893", "GSM1228894", "GSM1228895", "GSM1228896", "GSM1228897", "GSM1228898", "GSM1228899", "GSM1228900", "GSM1228901", "GSM1228902", "GSM1228903", "GSM1228904", "GSM1228905", "GSM1228906", "GSM1228907", "GSM1228908", "GSM1228909", "GSM1228910", "GSM1228911", "GSM1228912", "GSM1228913", "GSM1228914", "GSM1228915", "GSM1228916", "GSM1228917", "GSM1228918", "GSM1228919", "GSM1228920", "GSM1228921", "GSM1228922", "GSM1228923", "GSM1228924", "GSM1228925", "GSM1228926", "GSM1228927", "GSM1228928", "GSM1228929", "GSM1228930", "GSM1228931", "GSM1228932", "GSM1228933", "GSM1228934", "GSM1228935", "GSM1228936", "GSM1228937", "GSM1228938", "GSM1228939", "GSM1228940"], "sample_count": 81, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data in PBMCs from SLE patients and controls", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE72326", "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=GSE72326", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE72326", "version": null, "note": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data supporting the conclusions of this article are available in the article, Supplementary material, and the GEO repository (https://www.ncbi.nlm.nih.gov/geo/), MSigDB (http://software.broadinstitute.org/gsea/index.jsp), DAVID database (https://david.ncifcrf.gov). Further inquiries can be directed to the corresponding authors. The “Key resources table” section indicated all analyses methods, software packages, and online tools. Code requirements can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1860007", "GSM1860008", "GSM1860009", "GSM1860010", "GSM1860011", "GSM1860012", "GSM1860013", "GSM1860014", "GSM1860015", "GSM1860016", "GSM1860017", "GSM1860018", "GSM1860019", "GSM1860020", "GSM1860021", "GSM1860022", "GSM1860023", "GSM1860024", "GSM1860025", "GSM1860026", "GSM1860027", "GSM1860028", "GSM1860029", "GSM1860030", "GSM1860031", "GSM1860032", "GSM1860033", "GSM1860034", "GSM1860035", "GSM1860036", "GSM1860037", "GSM1860038", "GSM1860039", "GSM1860040", "GSM1860041", "GSM1860042", "GSM1860043", "GSM1860044", "GSM1860045", "GSM1860046", "GSM1860047", "GSM1860048", "GSM1860049", "GSM1860050", "GSM1860051", "GSM1860052", "GSM1860053", "GSM1860054", "GSM1860055", "GSM1860056", "GSM1860057", "GSM1860058", "GSM1860059", "GSM1860060", "GSM1860061", "GSM1860062", "GSM1860063", "GSM1860064", "GSM1860065", "GSM1860066", "GSM1860067", 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