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比较血清和尿生物标志物与白蛋白/肌酐比值在 1 型糖尿病肾功能下降预测中的作用。

Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes.

机构信息

Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.

MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh, EH4 2XU, UK.

出版信息

Diabetologia. 2020 Apr;63(4):788-798. doi: 10.1007/s00125-019-05081-8. Epub 2020 Jan 8.

Abstract

AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR).

METHODS

From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min [1.73 m], respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others' prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min [1.73] m, both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data.

RESULTS

Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min [1.73 m], adjusting for baseline eGFR and other covariates (all at p<2.3 × 10). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min [1.73 m] were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, α-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min [1.73 m] increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR.

CONCLUSIONS/INTERPRETATION: A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing.

摘要

目的/假设:我们研究了候选生物标志物在血清或尿液中是否可以改善 1 型糖尿病患者的肾脏疾病进展预测,将其与尿白蛋白/肌酐比值(ACR)进行比较。

方法

我们从具有代表性的苏格兰糖尿病研究网络 1 型生物资源(SDRNT1BIO)中抽取了 50%和 25%的基线 eGFR 低于和高于 75ml/min[1.73m]的患者(N=1629),中位随访时间为 5.1 年。基于我们之前的大型发现和候选研究,使用多重 ELISA 和单分子阵列技术测量了 9 种血清生物标志物和 13 种尿液生物标志物。使用线性和逻辑回归模型测试了与最终 eGFR 和进展至<30ml/min[1.73m]的相关性,均调整了基线 eGFR。使用惩罚贝叶斯方法识别了简洁的生物标志物组合,并通过十折交叉验证评估了它们的性能,并与使用尿液 ACR 和其他临床记录数据进行了比较。

结果

七种血清和七种尿液生物标志物与最终 eGFR 或进展至<30ml/min[1.73m]有强烈关联,调整了基线 eGFR 和其他协变量(均在 p<2.3×10 处)。其中,四项血清生物标志物与这两种结局的 ACR 无关。与最终 eGFR 和进展至<30ml/min[1.73m]相关性最强的是血清 TNF 受体 1、肾损伤分子 1、CD27 抗原、α-1-微球蛋白和 syndecan-1。对于这两种结局,这些血清相关性在正常白蛋白尿患者中也是显著的。在基线协变量的基础上,用于预测最终 eGFR 的 r 值从血清生物标志物的 0.702 增加到 0.743,从 ACR 单独的 0.702 增加到 0.721。用于进展至<30ml/min[1.73m]的接收器工作特征曲线下面积从血清生物标志物的 0.876 增加到 0.953,从 ACR 单独的 0.911 增加到 0.953。其他尿液生物标志物的表现并不优于 ACR。

结论/解释:一组简单的血清生物标志物,与血清肌酐一起可以很好地测量,可能比 ACR 更能预测 1 型糖尿病患者的肾脏疾病进展,可能无需进行尿液检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cf4/7054370/e1167a6804d7/125_2019_5081_Fig1_HTML.jpg

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