Evidence map›Paper›PMID 42630417›Full record

ArticleFrontiers in immunology2026

Identification of key genes related to arginine metabolism in immunoglobulin A nephropathy through the combination of scRNA-seq and bulk RNA-seq data.

Hong Xia, Wenze Jiang, Mengting Zhu, Yubing Li, Shengcheng Tai, Dandan Qiu, Zhenliang Fan, Zhejun Chen, Yan Liu, Peipei Zhang and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Hong Xia *Zhejiang Chinese Medical University, Hangzhou, China.
Wenze Jiang *Nephrology and Rheumatology Department, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Mengting Zhu *Zhejiang Chinese Medical University, Hangzhou, China.
Yubing LiNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Shengcheng TaiNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Dandan QiuNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Zhenliang FanNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Zhejun ChenNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Yan LiuNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Peipei ZhangNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Keda LuNephrology Department, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immunoglobulin A nephropathy (IgAN) is a major cause of chronic kidney disease and kidney failure. Currently, arginine metabolism (AM)-related genes (AMRGs) have been reported to play direct or indirect roles in various kidney-related diseases. This study aimed to identify AM-associated key genes in IgAN, potentially paving the way for targeted therapies. Methods: The data pertaining to IgAN and AMRGs were procured from public databases and literature, respectively. Candidate genes were obtained by integrating differentially expressed genes (DEGs) with AMRGs, and the genes were experimentally verified using qPCR. The identification of key genes was facilitated by machine learning algorithms and gene expression analyses. Of particular significance was the use of the nomogram to evaluate the diagnostic efficacy of these key genes. Functional enrichment, immune infiltration, drug prediction, and molecular docking analyses were performed. Single-cell analysis was employed to ascertain cell types, with the identification of key cells facilitated by key genes. Results: ARG1 and ARG2 were identified as key genes, and the expression of these 2 genes was found to be downregulated in IgAN samples. The nomogram developed utilizing these key genes demonstrated a satisfactory capacity for differentiating among various sample types. The key genes were found to be enriched in several signaling pathways, including PIP3 signaling in B lymphocytes and BCR signaling pathway. Furthermore, most of the differential immune cells showed significant negative correlations with key genes. Effector memory CD8+ T cells exhibited extremely significant negative correlations with both ARG1 and ARG2 (correlation coefficient (r) < -0.70, P < 0.001). Riluzole exhibited strong binding affinity for key genes and formed stable complexes. Finally, monocytes were considered key cells and played a critical role in IgAN. Conclusion: This study suggests that ARG1 and ARG2 may be key genes and potential mechanistic indicators of IgAN associated with AM, but it needs to be further verified in non-invasive samples and larger independent cohorts. Additionally, monocytes were recognized as key cells in the progression of IgAN, providing valuable insights to support the development of targeted therapies.

Indexed as

ArginaseArginineGlomerulonephritis, IGAGene Expression ProfilingHumansMolecular Docking SimulationNomogramsRNA-SeqSingle-Cell AnalysisTranscriptomeARG1 protein, humanArginaseArgininearginine metabolismbiomarkerimmunoglobulin A nephropathyRNA‑seqsingle-cell analysis

Identifiers

PMID42630417
PMCPMC13493611

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