血浆生物标志物可改善 12 年随访期间 1 型糖尿病成人糖尿病肾病的预测：CACTI 研究。
Plasma biomarkers improve prediction of diabetic kidney disease in adults with type 1 diabetes over a 12-year follow-up: CACTI study.
机构信息
Department of Pediatric Endocrinology, University of Colorado School of Medicine, Aurora, CO, USA.
Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO, USA.
出版信息
Nephrol Dial Transplant. 2018 Jul 1;33(7):1189-1196. doi: 10.1093/ndt/gfx255.
BACKGROUND
The objective of the study was to determine whether plasma biomarkers of kidney injury improve the prediction of diabetic kidney disease (DKD) in adults with type 1 diabetes (T1D) over a period of 12 years.
METHODS
Participants (n = 527, 53% females) in the Coronary Artery Calcification in T1D (CACTI) Study were examined during 2002-04, at a mean (± standard deviation) age of 39.6 ± 9.0 years with 24.8 years as the median duration of diabetes. Urine albumin-to-creatinine (ACR) and estimated glomerular filtration rate (eGFR) by CKD-EPI (chronic kidney disease epidemiology collaboration) creatinine were measured at the baseline and after mean follow-up of 12.1 ± 1.5 years. Albuminuria was defined as ACR ≥30 mg/g and impaired GFR as eGFR <60 mL/min/1.73 m2. Kidney injury biomarkers (Meso Scale Diagnostics) were measured on stored baseline plasma samples. A principal component analysis (PCA) identified two components: (i) kidney injury molecule-1, calbindin, osteoactivin, trefoil factor 3 and vascular endothelial growth factor; and (ii) β-2 microglobulin, cystatin C, neutrophil gelatinase-associated lipocalin and osteopontin that were used in the multivariable regression analyses.
RESULTS
Component 2 of the PCA was associated with increase in log modulus ACR [β ± standard error (SE): 0.16 ± 0.07, P = 0.02] and eGFR (β ± SE: -2.56 ± 0.97, P = 0.009) over a period of 12 years after adjusting for traditional risk factors (age, sex, HbA1c, low-density lipoprotein cholesterol and systolic blood pressure and baseline eGFR/baseline ACR). Only Component 2 of the PCA was associated with incident-impaired GFR (odds ratio 2.08, 95% confidence interval 1.18-3.67, P = 0.01), adjusting for traditional risk factors. The addition of Component 2 to traditional risk factors significantly improved C-statistics and net-reclassification improvement for incident-impaired GFR (ΔAUC: 0.02 ± 0.01, P = 0.049, and 29% non-events correctly reclassified, P < 0.0001).
CONCLUSIONS
Plasma kidney injury biomarkers can help predict development of DKD in T1D.
背景
本研究旨在确定血浆肾损伤生物标志物是否能提高对 1 型糖尿病（T1D）成人在 12 年期间糖尿病肾病（DKD）的预测能力。
方法
CACTI 研究的参与者（n=527，53%为女性）于 2002-04 年接受检查，平均（±标准差）年龄为 39.6±9.0 岁，中位糖尿病病程为 24.8 年。基线时测量尿白蛋白与肌酐（ACR）比值和慢性肾脏病流行病学合作组（CKD-EPI）估算的肾小球滤过率（eGFR），平均随访 12.1±1.5 年后再次测量。白蛋白尿定义为 ACR≥30mg/g，GFR 受损定义为 eGFR＜60mL/min/1.73m2。使用存储的基线血浆样本测量肾损伤生物标志物（Meso Scale Diagnostics）。主成分分析（PCA）确定了两个组成部分：（i）肾损伤分子-1、钙结合蛋白、骨激活素、三叶因子 3 和血管内皮生长因子；（ii）β-2 微球蛋白、胱抑素 C、中性粒细胞明胶酶相关脂质运载蛋白和骨桥蛋白，它们被用于多变量回归分析。
结果
PCA 的第二组成分与 log 模数 ACR 的增加相关[β±标准误（SE）：0.16±0.07，P=0.02]，eGFR 降低[β±SE：-2.56±0.97，P=0.009]，在调整传统危险因素（年龄、性别、HbA1c、低密度脂蛋白胆固醇和收缩压以及基线 eGFR/基线 ACR）后 12 年内。只有 PCA 的第二组成分与新发 GFR 受损相关（比值比 2.08，95%置信区间 1.18-3.67，P=0.01），调整了传统危险因素。将第二组成分添加到传统危险因素中，可显著提高新发 GFR 受损的 C 统计量和净重新分类改善（ΔAUC：0.02±0.01，P=0.049，非事件正确重新分类率增加 29%，P＜0.0001）。
结论
血浆肾损伤生物标志物有助于预测 T1D 患者 DKD 的发生。
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