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应用尿蛋白质组学预测 2 型糖尿病合并高血压患者螺内酯治疗的蛋白尿反应。

Predicting albuminuria response to spironolactone treatment with urinary proteomics in patients with type 2 diabetes and hypertension.

机构信息

Steno Diabetes Center, Gentofte, Denmark.

University of Southern Denmark, Research Unit for Cardiovascular and renal protection, Odense, Denmark.

出版信息

Nephrol Dial Transplant. 2018 Feb 1;33(2):296-303. doi: 10.1093/ndt/gfw406.

Abstract

BACKGROUND

The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetes. Prior studies have shown large between-patient variability in albuminuria treatment response. We previously developed and validated a urinary proteomic classifier that predicts onset and progression of chronic kidney disease. Here, we tested whether the proteomic classifier based on 273 urinary peptides (CKD273) predicts albuminuria response to spironolactone treatment.

METHODS

We performed a post hoc analysis in a double-blind randomized clinical trial with allocation to either spironolactone 12.5-50 mg/day (n = 57) or placebo (n = 54) for 16 weeks. Patients were diagnosed with type 2 diabetes and resistant hypertension. Treatment was an adjunct to renin-angiotensin system inhibition. Primary endpoint was the percentage change in urine albumin to creatinine ratio (UACR). Capillary electrophoresis mass spectrometry was used to quantify urinary peptides at baseline. The previously validated combination of 273 known urinary peptides was used as proteomic classifier.

RESULTS

Spironolactone reduced UACR relative to placebo by 50%, although with a large between-patient variability in UACR response (5th to 95th percentile, 7 to 312%). An interaction was detected between CKD273 and treatment assignment (β = -1.09, P = 0.026). Higher values of CKD273 at baseline were associated with a larger reduction in UACR in the spironolactone group (β = -0.70, P = 0.049), but not in the placebo group (β = 0.39, P = 0.25). Stratified in tertiles of baseline CKD273, reduction in UACR was greater in the highest tertile, 63% (95% confidence interval: 35-79%), as compared with the two other tertiles combined, 16% (-17 to 40%) (P = 0.011).

CONCLUSIONS

A urinary proteomics classifier can be used to identify individuals with type 2 diabetes who are more likely to show an albuminuria-lowering response to spironolactone treatment. These results suggest that urinary proteomics may be a valuable tool to tailor therapy, but confirmation in a larger clinical trial is required.

摘要

背景

醛固酮受体拮抗剂螺内酯可显著减少糖尿病患者的白蛋白尿。先前的研究表明,白蛋白尿治疗反应存在很大的个体间差异。我们之前开发并验证了一种基于 273 种尿肽的尿蛋白质组学分类器,可预测慢性肾脏病的发病和进展。在此,我们检测了基于 273 种尿肽(CKD273)的蛋白质组学分类器是否可预测螺内酯治疗对白蛋白尿的反应。

方法

我们对一项双盲随机临床试验进行了事后分析,该试验将患者随机分配至螺内酯 12.5-50mg/天(n=57)或安慰剂(n=54)组,治疗 16 周。患者被诊断为 2 型糖尿病和耐药性高血压。治疗是肾素-血管紧张素系统抑制的辅助手段。主要终点是尿白蛋白与肌酐比值(UACR)的变化百分比。毛细管电泳质谱法用于在基线时定量尿液肽。先前验证的 273 种已知尿肽的组合被用作蛋白质组学分类器。

结果

与安慰剂相比,螺内酯使 UACR 降低了 50%,尽管 UACR 反应存在很大的个体间差异(第 5 百分位至第 95 百分位,7%至 312%)。检测到 CKD273 与治疗分配之间存在交互作用(β=-1.09,P=0.026)。基线时 CKD273 值较高与螺内酯组 UACR 的更大降低相关(β=-0.70,P=0.049),但与安慰剂组无关(β=0.39,P=0.25)。按基线 CKD273 的三分位分层,最高三分位的 UACR 降低幅度更大,为 63%(95%置信区间:35%至 79%),而另外两个三分位的总和为 16%(-17%至 40%)(P=0.011)。

结论

尿蛋白质组学分类器可用于识别 2 型糖尿病患者,这些患者更有可能对螺内酯治疗的白蛋白尿降低反应。这些结果表明,尿蛋白质组学可能是一种有价值的治疗方法,但需要在更大的临床试验中得到证实。

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