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 [1.73 m]-2, 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 [1.73] m-2, 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 [1.73 m]-2, adjusting for baseline eGFR and other covariates (all at p<2.3 × 10-3). 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 [1.73 m]-2 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 r2 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 [1.73 m]-2 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.

中文翻译：

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血清和尿液生物标志物组与白蛋白/肌酐比值在预测1型糖尿病肾功能下降中的比较。

目的/假设我们将血清或尿液中的候选生物标志物的性能与尿白蛋白/肌酐比值（ACR）进行了比较，以检查其是否可改善1型糖尿病患者对肾脏疾病进展的预测。方法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，我们分别采样了50％和25％的起始eGFR分别低于和高于75 ml min-1 [1.73 m] -2（N = 1629）的人，并进行了5.1年的中位数随访。基于我们和其他人先前的大量发现和候选研究，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。与最终eGFR和进展至<30 ml min-1 [1.73] m-2的关联，均已针对基线eGFR进行了调整，使用线性和逻辑回归模型进行了测试。使用惩罚性贝叶斯方法鉴定了简约的生物标志物组，并通过十倍交叉验证评估了其性能，并与尿液ACR和其他临床记录数据进行了比较。结果7种血清和7种尿液生物标志物与最终eGFR或进展至<30 ml min-1 [1.73 m] -2密切相关，并调整了基线eGFR和其他协变量（均在p <2.3×10-3）。其中，两种结果的四种血清生物标志物的关联均独立于ACR。与最终eGFR和进展至<30 ml min-1 [1.73 m] -2的最强关联是血清TNF受体1，肾损伤分子1，CD27抗原，α-1-微球蛋白和syndecan-1。这些血清联想在正常白蛋白尿参与者中对于这两种结果也很重要。除基线协变量外，血清生物标志物的最终eGFR预测r2从0.702增至0.743，单独ACR的r2从0.702增至0.721。对于血清生物标志物而言，进展到<30 ml min-1 [1.73 m] -2的接收器工作特征曲线下的面积从0.876增加到0.953，单独使用ACR则增加到0.911。其他尿液生物标志物未优于ACR。结论/解释一组易于预测的血清生物标志物和血清肌酐一起可简化，在预测1型糖尿病肾病进展方面可能胜过ACR，从而可能不需要进行尿液检测。血清生物标志物为743，单独ACR为0.702至0.721。对于血清生物标志物而言，进展到<30 ml min-1 [1.73 m] -2的接收器工作特征曲线下的面积从0.876增加到0.953，单独使用ACR则增加到0.911。其他尿液生物标志物未优于ACR。结论/解释一组易于预测的血清生物标志物和血清肌酐一起可简化，在预测1型糖尿病肾病进展方面可能胜过ACR，从而可能不需要进行尿液检测。血清生物标志物为743，单独ACR为0.702至0.721。对于血清生物标志物而言，进展到<30 ml min-1 [1.73 m] -2的接收器工作特征曲线下的面积从0.876增加到0.953，单独使用ACR则增加到0.911。其他尿液生物标志物未优于ACR。结论/解释血清生物标志物与血清肌酐一起可轻松测量的简约组合可能在预测1型糖尿病肾病进展方面优于ACR，从而可能无需进行尿液检测。