ArticleMedComm2024
An inflammatory cytokine signature predicts IgA nephropathy severity and progression.
Article in MedComm, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A nine-gene diagnostic model for IgA nephropathy based on multi-cohort machine learning: integrating gene expression and immunohistochemical validation.Renal failure · 2026Article
- Shared genetics of IgA nephropathy and cardiometabolic diseases revealed by integrative genomic analysis.Renal failure · 2026Article
- Risk prediction in IgA nephropathy: from conventional models to machine learning, deep learning, and precision nephrology.Renal failure · 2026Review
- Sarsasapogenin Preserves Podocyte Integrity and Attenuates Renal Injury in Experimental IgA Nephropathy.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Research progress in single‑cell omics technologies for kidney disease (Review).International journal of molecular medicine · 2026Review
- IgA Nephropathy: Mechanisms, Risk Stratification, and Precision Therapy.Diagnostics (Basel, Switzerland) · 2026Review
- Biomarkers predicting good prognosis among patients receiving immunosuppressive treatment in IgA nephropathy: the promising role of serum TGF-β1 and MCP-1.Frontiers in immunology · 2026Article
- Identification of Biomarker in Kidney Stone Disease by Integrating Transcriptomics and Olink Proteomics: A Case-Control Study.Journal of inflammation research · 2026Article
- Review
- Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis, resulting in end-stage renal disease and increased mortality rates. Prognostic biomarkers reflecting molecular mechanisms for effective IgAN management are urgently needed. Analysis of kidney single-cell transcriptomic sequencing data demonstrated that IgAN expressed high-expression levels of inflammatory cytokines TNFSF10, TNFSF12, CCL2, CXCL1, and CXCL12 than healthy controls (HCs). We also measured the urine proteins in 120 IgAN (57 stable and 63 progressive) and 32 HCs using the proximity extension assay (PEA), and the multivariable and least absolute shrinkage and selection operator (LASSO) logistic regression analysis both revealed that CXCL12, MCP1 were the prognostic significant variables to predict IgAN progression severity. These two proteins exhibited negative correlation with the estimated glomerular filtration rate (eGFR) and patients with higher expression levels of these two proteins had a higher probability to have poorer renal outcome. We further developed a risk index model utilizing CXCL12, MCP1, and baseline clinical indicators, which achieved an impressive area under the curve (AUC) of 0.896 for prediction of IgAN progression severity. Our study highlights the significance of the inflammatory protein biomarkers for noninvasive prediction of IgAN severity and progression, offering valuable insights for clinical management.
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