Agrawal Shipra, Merchant Michael L, Kino Jiro, Li Ming, Wilkey Daniel W, Gaweda Adam E, Brier Michael E, Chanley Melinda A, Gooding Jessica R, Sumner Susan J, Klein Jon B, Smoyer William E
The Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
The Ohio State University, Columbus, Ohio, USA.
Kidney Int Rep. 2019 Sep 19;5(1):66-80. doi: 10.1016/j.ekir.2019.09.009. eCollection 2020 Jan.
Nephrotic syndrome (NS) is a characterized by massive proteinuria, edema, hypoalbuminemia, and dyslipidemia. Glucocorticoids (GCs), the primary therapy for >60 years, are ineffective in approximately 50% of adults and approximately 20% of children. Unfortunately, there are no validated biomarkers able to predict steroid-resistant NS (SRNS) or to define the pathways regulating SRNS.
We performed proteomic analyses on paired pediatric NS patient plasma samples obtained both at disease presentation before glucocorticoid initiation and after approximately 7 weeks of GC therapy to identify candidate biomarkers able to either predict steroid resistance before treatment or define critical molecular pathways/targets regulating steroid resistance.
Proteomic analyses of 15 paired NS patient samples identified 215 prevalent proteins, including 13 candidate biomarkers that predicted SRNS before GC treatment, and 66 candidate biomarkers that mechanistically differentiated steroid-sensitive NS (SSNS) from SRNS. Ingenuity Pathway Analyses and protein networking pathways approaches further identified proteins and pathways associated with SRNS. Validation using 37 NS patient samples (24 SSNS/13 SRNS) confirmed vitamin D binding protein (VDB) and APOL1 as strong predictive candidate biomarkers for SRNS, and VDB, hemopexin (HPX), adiponectin (ADIPOQ), sex hormone-binding globulin (SHBG), and APOL1 as strong candidate biomarkers to mechanistically distinguish SRNS from SSNS. Logistic regression analysis identified a candidate biomarker panel (VDB, ADIPOQ, and matrix metalloproteinase 2 [MMP-2]) with significant ability to predict SRNS at disease presentation ( = 0.003; area under the receiver operating characteristic curve = 0.78).
Plasma proteomic analyses and immunoblotting of serial samples in childhood NS identified a candidate biomarker panel able to predict SRNS at disease presentation, as well as candidate molecular targets/pathways associated with clinical steroid resistance.
肾病综合征(NS)的特征是大量蛋白尿、水肿、低白蛋白血症和血脂异常。糖皮质激素(GCs)作为主要治疗方法已有60多年,但在约50%的成人和约20%的儿童中无效。不幸的是,目前尚无经过验证的生物标志物能够预测激素抵抗性肾病综合征(SRNS)或确定调节SRNS的途径。
我们对成对的儿科NS患者血浆样本进行了蛋白质组学分析,这些样本在糖皮质激素治疗开始前的疾病初发时以及GC治疗约7周后采集,以确定能够在治疗前预测激素抵抗或确定调节激素抵抗的关键分子途径/靶点的候选生物标志物。
对15对NS患者样本的蛋白质组学分析鉴定出215种常见蛋白质,其中包括13种在GC治疗前预测SRNS的候选生物标志物,以及66种从机制上区分激素敏感性肾病综合征(SSNS)和SRNS的候选生物标志物。通路分析和蛋白质网络通路方法进一步确定了与SRNS相关的蛋白质和通路。使用37例NS患者样本(24例SSNS/13例SRNS)进行验证,证实维生素D结合蛋白(VDB)和载脂蛋白L1(APOL1)是SRNS的强预测候选生物标志物,而VDB、血红素结合蛋白(HPX)、脂联素(ADIPOQ)、性激素结合球蛋白(SHBG)和APOL1是从机制上区分SRNS和SSNS的强候选生物标志物。逻辑回归分析确定了一个候选生物标志物组合(VDB、ADIPOQ和基质金属蛋白酶2 [MMP-2]),其在疾病初发时预测SRNS的能力显著(P = 0.003;受试者工作特征曲线下面积 = 0.78)。
儿童NS患者系列样本的血浆蛋白质组学分析和免疫印迹确定了一个能够在疾病初发时预测SRNS的候选生物标志物组合,以及与临床激素抵抗相关的候选分子靶点/途径。