Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington, USA,
Kidney Research Institute, University of Washington, Seattle, Washington, USA,
Am J Nephrol. 2020;51(10):839-848. doi: 10.1159/000510830. Epub 2020 Oct 14.
Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict.
We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques.
At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was -5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68-0.79; p < 0.001).
Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.
1 型糖尿病（T1D）患者的估算肾小球滤过率（eGFR）下降轨迹存在差异。T1D 中导致 eGFR 快速下降的分子途径尚不清楚，个体发生 eGFR 快速下降的风险也难以预测。
我们设计了一项病例对照研究，其中包含嵌套在四个特征明确的 T1D 队列（芬兰糖尿病研究、斯滕诺、EDC 和 CACTI）中的多个暴露测量，以确定与快速 eGFR 下降相关的生物标志物。在此，我们报告了这些研究的原理和设计，以及在研究人群中测试临床特征与快速 eGFR 下降之间关联的模型结果，在此基础上构建“组学”研究。病例（n=535）和对照（n=895）的定义为每年 eGFR 下降幅度分别≥3 和 <1 mL/min/1.73 m2。使用逻辑回归测试人口统计学和临床变量与快速 eGFR 下降的关联，使用曲线下面积（AUC）统计评估预测。使用高分辨率质谱技术进行靶向代谢组学、脂质组学和蛋白质组学研究。
在基线时，平均年龄为 43 岁，糖尿病病程为 27 年，eGFR 为 94 mL/min/1.73 m2，62%的参与者为正常白蛋白尿。在中位随访 7.6 年期间，病例和对照组的平均年 eGFR 变化分别为-5.7 和 0.6 mL/min/1.73 m2。较年轻的年龄、较长的糖尿病病程、较高的基线 HbA1c、尿白蛋白/肌酐比和 eGFR 与快速 eGFR 下降显著相关。纳入这些变量以及性别和平均动脉压的预测模型的交叉验证 AUC 为 0.74（95%CI：0.68-0.79；p<0.001）。
已知的危险因素对快速 eGFR 下降有一定的鉴别能力。使用靶向组学策略确定与 T1D 中快速 eGFR 下降相关的血液和尿液生物标志物，可能有助于深入了解疾病机制，并改进使用传统危险因素的临床预测模型。
