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pmid:39205658

Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis.

Yong Jin · Yutong Wang · Xu Ma · Hongbin Li · Manling Zhang

American journal of physiology. Renal physiology · 2024 doi:10.1152/ajprenal.00122.2024

Paper

complete

Experiment

complete

Data

partial

Analysis

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Execution

absent

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title
Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis.
doi
10.1152/ajprenal.00122.2024
pmid
39205658
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Yong Jin
[1]
Yutong Wang
[2]
Xu Ma
[3]
Hongbin Li
[4]
Manling Zhang
journal
American journal of physiology. Renal physiology
year
2024
abstract
To explore molecular biomarkers associated with the pathophysiology and therapy of lupus nephritis (LN), we conducted a joint analysis of transcriptomic data from 40 peripheral blood mononuclear cells (PBMCs) (GSE81622) and 21 kidney samples (GSE112943) from the Gene Expression Omnibus database using bioinformatics. A total of 976 and 2,427 differentially expressed genes (DEGs) were identified in PBMCs and renal tissues. Seven and two functional modules closely related to LN were identified. Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney. Subsequently, 16 core genes closely associated with LN were verified by protein-protein interaction screening and quantitative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expression of these core genes was closely linked to neutrophil extracellular traps (NETs) generated by neutrophil activation, while degradation of NETs led to downregulation of core gene expression, thereby improving pathological symptoms of LN. Therefore, identification of patients with systemic lupus erythematosus exhibiting abnormal expression patterns for these core genes may serve as a useful indicator for kidney involvement. In addition, targeting neutrophils to modulate their activation levels and inhibit aberrant expression of these genes represents a potential therapeutic strategy for treating LN. NEW & NOTEWORTHY The mechanisms by which immune cells cause kidney injury in lupus nephritis are poorly understood. We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the GEO database to identify key molecular markers associated with neutrophil activation. We confirmed that neutrophil extracellular traps (NETs) formed by neutrophil activation promoted the upregulation of key genes in cell and animal models. Targeted degradation of NETs significantly ameliorated kidney injury in MRL/lpr mice.
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Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney.
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Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney.
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Genome-wide analysis of gene expression of cutaneous lupus skin samples and lupus nephritis kidney samples
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Whole genome transcription and DNA methylation analysis of peripheral blood mononuclear cells identified aberrant gene regulation pathways in systemic lupus erythematosus [expression]
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ritis (LN), we conducted a joint analysis of transcriptomic data from 40 peripheral blood mononuclear ce
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y understood. We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the
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tative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expressio
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ical (Beijing, China). A total of 20 MRL/lpr mice were used for this study. In addition, 15 C57BL/6
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entification of DEGs in Patients With LN All microarray datasets were subjected to standardization a
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, as shown in Fig. 4C. Subsequently, we used qPCR to validate the expression of these core gen
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39205658", "kind": "science-record", "revision": 4, "content_hash": "sha256:e68cdc93aa7e5f5a8ae116727302984e721d1fcdcfebf36547f09fb3033c4f1c", "created_at": "2026-11-01T20:29:19Z", "updated_at": "2026-11-01T22:55:02Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis.", "doi": "10.1152/ajprenal.00122.2024", "pmid": "39205658", "authors": ["Yong Jin", "Yutong Wang", "Xu Ma", "Hongbin Li", "Manling Zhang"], "journal": "American journal of physiology. Renal physiology", "year": 2024, "abstract": "To explore molecular biomarkers associated with the pathophysiology and therapy of lupus nephritis (LN), we conducted a joint analysis of transcriptomic data from 40 peripheral blood mononuclear cells (PBMCs) (GSE81622) and 21 kidney samples (GSE112943) from the Gene Expression Omnibus database using bioinformatics. A total of 976 and 2,427 differentially expressed genes (DEGs) were identified in PBMCs and renal tissues. Seven and two functional modules closely related to LN were identified. Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney. Subsequently, 16 core genes closely associated with LN were verified by protein-protein interaction screening and quantitative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expression of these core genes was closely linked to neutrophil extracellular traps (NETs) generated by neutrophil activation, while degradation of NETs led to downregulation of core gene expression, thereby improving pathological symptoms of LN. Therefore, identification of patients with systemic lupus erythematosus exhibiting abnormal expression patterns for these core genes may serve as a useful indicator for kidney involvement. In addition, targeting neutrophils to modulate their activation levels and inhibit aberrant expression of these genes represents a potential therapeutic strategy for treating LN. NEW & NOTEWORTHY The mechanisms by which immune cells cause kidney injury in lupus nephritis are poorly understood. We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the GEO database to identify key molecular markers associated with neutrophil activation. We confirmed that neutrophil extracellular traps (NETs) formed by neutrophil activation promoted the upregulation of key genes in cell and animal models. Targeted degradation of NETs significantly ameliorated kidney injury in MRL/lpr mice.", "claims": [{"id": "claim-method", "statement": "The limma R software package was used to screen DEGs in each dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39205658", "locator": "sections[3] \"Dataset Selection, Preprocessing, and Identification of DEGs\" paragraph 3", "quote": "The limma R software package was used to screen DEGs in each dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39205658", "locator": "sections[27] \"DATA AVAILABILITY\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39205658", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney.", "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:39205658"], "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:GSE112943"], "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:GSE112943"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39205658", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1152/ajprenal.00122.2024", "sha256": "sha256:0f72eeef9d523549766e01e61028226090b5adf0f47b6299aed643d8b42cc411", "bytes": 76813, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1152/ajprenal.00122.2024", "version": null, "note": "Full article fetched from PMC; 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We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the"], "order_basis": "paper_text_order:192", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["tative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expressio", "ical (Beijing, China). A total of 20 MRL/lpr mice were used for this study. In addition, 15 C57BL/6", "sed for this study. In addition, 15 C57BL/6J mice were included as a control group. MRL/lpr mice we", "ce were included as a control group. MRL/lpr mice were randomly divided into model groups at 13 wk,"], "order_basis": "paper_text_order:840", "id": "assay:2"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["entification of DEGs in Patients With LN All microarray datasets were subjected to standardization a"], "order_basis": "paper_text_order:4829", "id": "assay:3"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": [", as shown in Fig. 4C. 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