炎症细胞因子特征可预测 IgA 肾病的严重程度和病情发展

IF 10.7 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
MedComm Pub Date : 2024-11-03 DOI:10.1002/mco2.783
Lei Chen, Xizhao Chen, Guangyan Cai, Hongli Jiang, Xiangmei Chen, Min Zhang
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引用次数: 0

摘要

IgA 肾病(IgAN)是发病率最高的原发性肾小球肾炎,可导致终末期肾病和更高的死亡率。目前亟需反映分子机制的预后生物标志物来有效管理 IgAN。对肾脏单细胞转录组测序数据的分析表明,与健康对照组(HCs)相比,IgAN 的炎症细胞因子 TNFSF10、TNFSF12、CCL2、CXCL1 和 CXCL12 表达水平较高。我们还使用邻近延伸测定法(PEA)测定了 120 例 IgAN(57 例稳定型和 63 例进展型)和 32 例 HC 的尿蛋白,多变量和最小绝对缩小和选择算子(LASSO)逻辑回归分析均显示,CXCL12 和 MCP1 是预测 IgAN 进展严重程度的重要预后变量。这两种蛋白与估计肾小球滤过率(eGFR)呈负相关,这两种蛋白表达水平越高的患者,其肾脏预后越差。我们进一步利用 CXCL12、MCP1 和基线临床指标建立了一个风险指数模型,该模型在预测 IgAN 进展严重程度方面的曲线下面积(AUC)达到了惊人的 0.896。我们的研究强调了炎症蛋白生物标志物在无创预测 IgAN 严重程度和进展方面的重要性,为临床管理提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An inflammatory cytokine signature predicts IgA nephropathy severity and progression

An inflammatory cytokine signature predicts IgA nephropathy severity and progression

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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CiteScore
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