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.
Nephrol Dial Transplant. 2018 Jul 1;33(7):1189-1196. doi: 10.1093/ndt/gfx255.
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.
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.
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).
Plasma kidney injury biomarkers can help predict development of DKD in T1D.
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。
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。
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）。
血浆肾损伤生物标志物有助于预测 T1D 患者 DKD 的发生。
