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pmid:39319258

VCAM1: an effective diagnostic marker related to immune cell infiltration in diabetic nephropathy.

Yuanyuan Deng · Sai Zhang · Zheng Luo · Pengfei He · Xinyu Ma · Yu Ma · Jing Wang · Liyang Zheng · Ni Tian · Shaoning Dong · Xingkun Zhang · Mianzhi Zhang

Frontiers in endocrinology · 2024 doi:10.3389/fendo.2024.1426913

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:39319258
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science-record
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2026-11-01T20:29:30Z
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2026-11-01T22:12:45Z
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paper object · 10 fields
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title
VCAM1: an effective diagnostic marker related to immune cell infiltration in diabetic nephropathy.
doi
10.3389/fendo.2024.1426913
pmid
39319258
authors array · 12 items
[0]
Yuanyuan Deng
[1]
Sai Zhang
[2]
Zheng Luo
[3]
Pengfei He
[4]
Xinyu Ma
[5]
Yu Ma
[6]
Jing Wang
[7]
Liyang Zheng
[8]
Ni Tian
[9]
Shaoning Dong
[10]
Xingkun Zhang
[11]
Mianzhi Zhang
journal
Frontiers in endocrinology
year
2024
abstract
Introduction: The role of immune cells in the pathogenesis and advancement of diabetic nephropathy (DN) is crucial. The objective of this study was to identify immune-cell-related biomarkers that could potentially aid in the diagnosis and management of DN. Methods: The GSE96804 dataset was obtained from the Gene Expression Omnibus (GEO) database. Then, screen for intersections between differentially expressed genes (DEGs) and immune-related genes (IRGs). Identify core genes through protein-protein interaction (PPI) networks and the Cytoscape plugin. Subsequently, functional enrichment analysis was conducted. In addition, ROC analysis is performed to accurately identify diagnostic biomarkers. Apply the CIBERSORT algorithm to evaluate the proportion of immune cell infiltration. Finally, the mRNA, protein, and immunofluorescence expression of the biomarker was validated in the DN rat model. Results: The study yielded 74 shared genes associated with DN. Enrichment analysis indicated significant enrichment of these genes in focal adhesion, the humoral immune response, activation of the immune response, Cytokine-cytokine receptor interaction, and IL-17 signaling pathway. The optimal candidate gene VCAM1 was identified. The presence of VCAM1 in DN was further validated using the ROC curve. Analysis of immune cell infiltration matrices revealed a high abundance of monocytes, naïve B cells, memory B cells, and Macrophages M1/M2 in DN tissues. Correlation analysis identified one hub biomarker associated with immune-infiltrated cells in DN. Furthermore, our findings were validated through in vivo RT qPCR, WB, and IF techniques. Conclusions: Our research indicates that VCAM1 is a signature gene associated with DN and is linked to the progression, treatment, and prognosis of DN. A comprehensive examination of immune infiltration signature genes may offer new perspectives on the clinical diagnosis and management of DN.
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A ROC curve was created to evaluate how well the biomarkers could differentiate between the NC and DN samples using the “pROC” package in the R software.
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sections[7] "Diagnostic value of biomarkers in DN" paragraph 2
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A ROC curve was created to evaluate how well the biomarkers could differentiate between the NC and DN samples using the “pROC” package in the R software.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary material .
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VCAM1 was elevated in DN tissues and had diagnostic utility for distinguishing DN from control samples, with ROC AUC values exceeding 0.5.
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sections[23] "Diagnostic value of biomarkers" paragraph 2
quote
Additionally, the levels of VCAM1 expression were notably elevated in DN tissues compared to control tissues. The AUC values derived from the ROC curves all exceeded 0.5, suggesting a high level of confidence in the use of VCAM1 as a diagnostic biomarker for DN.
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VCAM1 was elevated in DN tissues and had diagnostic utility for distinguishing DN from control samples, with ROC AUC values exceeding 0.5.
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Exon Level Expression Profiling of Diabetic Nephropathy
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nfiltration. Finally, the mRNA, protein, and immunofluorescence expression of the biomarker was validated in
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hermore, our findings were validated through in vivo RT qPCR, WB, and IF techniques. Conclusions:
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ion of the biomarker was validated in the DN rat model. Results: The study yielded 74 shared
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analysis
definition_id
principal_component_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
pca_fit
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Principal component analysis
order_basis
consumes_earlier_output
id
assay:4
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39319258", "kind": "science-record", "revision": 3, "content_hash": "sha256:5de49561840175197f8c828d0cff29718d1004c3f4b062a04e36dcbf6d1e8ea7", "created_at": "2026-11-01T20:29:30Z", "updated_at": "2026-11-01T22:12:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "VCAM1: an effective diagnostic marker related to immune cell infiltration in diabetic nephropathy.", "doi": "10.3389/fendo.2024.1426913", "pmid": "39319258", "authors": ["Yuanyuan Deng", "Sai Zhang", "Zheng Luo", "Pengfei He", "Xinyu Ma", "Yu Ma", "Jing Wang", "Liyang Zheng", "Ni Tian", "Shaoning Dong", "Xingkun Zhang", "Mianzhi Zhang"], "journal": "Frontiers in endocrinology", "year": 2024, "abstract": "Introduction: The role of immune cells in the pathogenesis and advancement of diabetic nephropathy (DN) is crucial. The objective of this study was to identify immune-cell-related biomarkers that could potentially aid in the diagnosis and management of DN.\nMethods: The GSE96804 dataset was obtained from the Gene Expression Omnibus (GEO) database. Then, screen for intersections between differentially expressed genes (DEGs) and immune-related genes (IRGs). Identify core genes through protein-protein interaction (PPI) networks and the Cytoscape plugin. Subsequently, functional enrichment analysis was conducted. In addition, ROC analysis is performed to accurately identify diagnostic biomarkers. Apply the CIBERSORT algorithm to evaluate the proportion of immune cell infiltration. Finally, the mRNA, protein, and immunofluorescence expression of the biomarker was validated in the DN rat model.\nResults: The study yielded 74 shared genes associated with DN. Enrichment analysis indicated significant enrichment of these genes in focal adhesion, the humoral immune response, activation of the immune response, Cytokine-cytokine receptor interaction, and IL-17 signaling pathway. The optimal candidate gene VCAM1 was identified. The presence of VCAM1 in DN was further validated using the ROC curve. Analysis of immune cell infiltration matrices revealed a high abundance of monocytes, naïve B cells, memory B cells, and Macrophages M1/M2 in DN tissues. Correlation analysis identified one hub biomarker associated with immune-infiltrated cells in DN. Furthermore, our findings were validated through in vivo RT qPCR, WB, and IF techniques.\nConclusions: Our research indicates that VCAM1 is a signature gene associated with DN and is linked to the progression, treatment, and prognosis of DN. A comprehensive examination of immune infiltration signature genes may offer new perspectives on the clinical diagnosis and management of DN.", "claims": [{"id": "claim-method", "statement": "A ROC curve was created to evaluate how well the biomarkers could differentiate between the NC and DN samples using the “pROC” package in the R software.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39319258", "locator": "sections[7] \"Diagnostic value of biomarkers in DN\" paragraph 2", "quote": "A ROC curve was created to evaluate how well the biomarkers could differentiate between the NC and DN samples using the “pROC” package in the R software."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39319258", "locator": "sections[33] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "VCAM1 was elevated in DN tissues and had diagnostic utility for distinguishing DN from control samples, with ROC AUC values exceeding 0.5.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39319258", "locator": "sections[23] \"Diagnostic value of biomarkers\" paragraph 2", "quote": "Additionally, the levels of VCAM1 expression were notably elevated in DN tissues compared to control tissues. The AUC values derived from the ROC curves all exceeded 0.5, suggesting a high level of confidence in the use of VCAM1 as a diagnostic biomarker for DN."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "VCAM1 was elevated in DN tissues and had diagnostic utility for distinguishing DN from control samples, with ROC AUC values exceeding 0.5.", "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:39319258"], "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:GSE30528"], "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:GSE30528"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39319258", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2024.1426913", "sha256": "sha256:99edd54db24c9ce93f80e69f8b12a039bbfaec822071b3e596f71dc3fe20eb26", "bytes": 55136, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2024.1426913", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11420029", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE30528", "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=GSE30528", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE30528", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary material .", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. 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Finally, the mRNA, protein, and immunofluorescence expression of the biomarker was validated in"], "order_basis": "paper_text_order:873", "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": ["hermore, our findings were validated through in vivo RT qPCR, WB, and IF techniques. Conclusions:", "ion of the biomarker was validated in the DN rat model. Results: The study yielded 74 shared", "under license SYXK (Beijing) 2019-0013. The rats were specific pathogen-free (SPF). The animals we", "ater. 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