Hitachi Chemical Co. America, Ltd., R and D Center, Irvine, California, USA.
NanoSomiX, Inc., Aliso Viejo, California, USA.
Am J Nephrol. 2018;47(5):283-291. doi: 10.1159/000489129. Epub 2018 May 18.
Extracellular vesicles (EVs) enclose mRNA derived from their cell of origin and are considered a source of potential biomarkers. We examined urinary EV mRNA from individuals with diabetic kidney disease (DKD), chronic kidney disease, type 2 diabetes (T2DM), and obese and healthy controls to determine if such biomarkers had the potential to classify kidney disease and predict patients at higher risk of renal function decline.
A total of 242 participants enrolled in this study. Urinary EV mRNA from all subjects were isolated by a filter-based platform, and the expression of 8 target genes were determined by quantitative polymerase chain reaction (qPCR). Changes in estimated glomerular filtration rate (eGFR) in 161 T2DM patients were evaluated for 2 consecutive years and compared with EV RNA profiles at baseline.
We observe that mild and severe DKD groups show a significant 3.2- and -4.4-fold increase in UMOD compared to healthy controls and expression increases linearly from healthy, diabetic, and DKD subjects. UMOD expression is significantly correlated to albumin creatinine ratio (ACR), eGFR, and HbA1c. Using linear discriminant analyses with mRNA from severe DKD and T2DM as training data, a multi-gene signature classified DKD and -non-DKD with a sensitivity of 93% and specificity of 73% with area under the receiver operating characteristic (ROC) curve (AUC) = 0.90. Although 6% of T2DM were determined to have a > 80% posterior probability of developing DKD based on this mRNA profile, eGFR changes observed within the 2-year follow-up did not reveal a decline in kidney function.
Urinary EV UMOD mRNA levels are progressively elevated from T2DM to DKD groups and correlate with widely used eGFR and ACR diagnostic criteria. An EV mRNA signature could identify DKD with greater than 90% sensitivity and 70% specificity.
细胞外囊泡 (EV) 包裹着源自其起源细胞的 mRNA,并被认为是潜在生物标志物的来源。我们检测了来自糖尿病肾病 (DKD)、慢性肾脏病、2 型糖尿病 (T2DM) 以及肥胖和健康对照个体的尿液 EV mRNA,以确定这些生物标志物是否有可能对肾脏疾病进行分类,并预测肾功能下降风险较高的患者。
本研究共纳入 242 名参与者。通过基于滤器的平台分离所有受试者的尿液 EV mRNA,并通过定量聚合酶链反应 (qPCR) 确定 8 个靶基因的表达。对 161 名 T2DM 患者连续 2 年的估计肾小球滤过率 (eGFR) 变化进行评估,并与基线时的 EV RNA 谱进行比较。
我们观察到轻度和重度 DKD 组与健康对照组相比,UMOD 表达分别显著增加了 3.2 倍和 4.4 倍,且表达水平从健康、糖尿病和 DKD 受试者呈线性增加。UMOD 表达与白蛋白肌酐比 (ACR)、eGFR 和 HbA1c 显著相关。使用严重 DKD 和 T2DM 的 mRNA 进行线性判别分析作为训练数据,多基因特征可将 DKD 和非-DKD 分类,其灵敏度为 93%,特异性为 73%,ROC 曲线下面积 (AUC) = 0.90。尽管根据该 mRNA 谱,6%的 T2DM 被确定为发生 DKD 的可能性大于 80%,但在 2 年随访期间观察到的 eGFR 变化并未显示肾功能下降。
尿液 EV UMOD mRNA 水平从 T2DM 到 DKD 组逐渐升高,并与广泛使用的 eGFR 和 ACR 诊断标准相关。EV mRNA 特征可识别 DKD,灵敏度大于 90%,特异性大于 70%。