Department of Nephrology, 1st Faculty of Medicine and General University Hospital, Charles University, 128 08 Prague, Czech Republic.
Nordic Bioscience, 2730 Herlev, Denmark.
Int J Mol Sci. 2023 Jan 20;24(3):2064. doi: 10.3390/ijms24032064.
We evaluated biomarkers related to kidney fibrosis for the outcome of patients with IgA nephropathy (IgAN). Clinical parameters (estimated glomerular filtration rate, hypertension, proteinuria) and histological findings were assessed in 134 patients with IgAN at the time of diagnosis and followed up prospectively (mean follow-up time, 56.5 months). We measured biomarkers of collagen and laminin turnover in serum and urine collected at the time of kidney biopsy using a novel enzyme-linked immunosorbent assay. Linear discriminant analysis and logistic regression models were used to predict the patient's kidney outcome. Five serum and urine biomarkers of laminin and collagen turnover (sLG1M, sPRO-C3, sPRO-C6, uPRO-C6/Cr, uC3M/Cr) could significantly differentiae IgAN patients with a worse prognosis. Clinical parameters (glomerular filtration rate (GFR), proteinuria) distinguished patients at risk of IgAN progression with a specificity of 87.3% and a sensitivity of 45.2% (area under the curve-AUC 0.751). The addition of the biomarkers significantly increased the prognostic ability with a specificity of 85.1% and a sensitivity of 73.3% (AUC 0.905). We have identified three serum (sLG1M, sPRO-C3, sPRO-C6) and two urinary markers (uPRO-C6/Cr, u-C3M /Cr) that significantly improve the prognostic ability of markers of kidney function to identify an IgAN patient's risk of progressing to ESKD.
我们评估了与 IgA 肾病(IgAN)患者结局相关的肾纤维化生物标志物。在诊断时,对 134 例 IgAN 患者进行了临床参数(估计肾小球滤过率、高血压、蛋白尿)和组织学检查,并前瞻性随访(平均随访时间为 56.5 个月)。我们使用新型酶联免疫吸附试验检测了在肾活检时收集的血清和尿液中胶原蛋白和层粘连蛋白代谢的生物标志物。使用线性判别分析和逻辑回归模型预测患者的肾脏结局。5 种血清和尿液层粘连蛋白和胶原蛋白代谢的生物标志物(sLG1M、sPRO-C3、sPRO-C6、uPRO-C6/Cr、uC3M/Cr)可以显著区分预后较差的 IgAN 患者。临床参数(肾小球滤过率(GFR)、蛋白尿)可以区分有 IgAN 进展风险的患者,特异性为 87.3%,敏感性为 45.2%(曲线下面积-AUC 0.751)。加入生物标志物后,特异性为 85.1%,敏感性为 73.3%(AUC 0.905),显著提高了预测能力。我们已经确定了三种血清(sLG1M、sPRO-C3、sPRO-C6)和两种尿液标志物(uPRO-C6/Cr、u-C3M/Cr),它们可以显著提高肾功能标志物的预后能力,从而识别 IgAN 患者进展为 ESKD 的风险。