An inflammatory cytokine signature predicts IgA nephropathy severity and progression

被引:0
|
作者
Chen, Lei [1 ]
Chen, Xizhao [2 ]
Cai, Guangyan [2 ]
Jiang, Hongli [1 ]
Chen, Xiangmei [2 ]
Zhang, Min [2 ]
机构
[1] Xi An Jiao Tong Univ, Dept Crit Care Nephrol & Blood Purificat, Affiliated Hosp 1, Xian 710061, Shaanxi, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Nephrol Inst Chinese Peoples Liberat Army, Natl Clin Res Ctr Kidney Dis, Dept Nephrol,Med Ctr 1,State Key Lab Kidney Dis,Be, Beijing 100853, Peoples R China
来源
MEDCOMM | 2024年 / 5卷 / 11期
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
IgA nephropathy; Olink Proteomics; prognosis biomarkers; single-cell sequencing; HOMEOSTATIC CHEMOKINE CXCL12; KIDNEY-DISEASE; DUAL BLOCKADE; RENAL-DISEASE; PATHOGENESIS; TWEAK/FN14; PROGNOSIS; INSIGHTS; PROVIDES; PATHWAY;
D O I
10.1002/mco2.783
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
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.
引用
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页数:15
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