Proteomic Predictors of Chronic Kidney Disease in Liver Transplant Recipients

描述（由申请人提供）：肝移植（LT）受者是所有非肾脏实体器官移植受者中慢性肾脏疾病（CKD）发生率最高的人群。CKD在该人群中的影响是巨大的，导致早期和晚期发病率和死亡率以及肾器官资源利用。LT提供者目前采用的策略是等到肾功能不全在临床上明显时才制定治疗策略，这通常为时已晚且无效-这是CKD在这些患者中发展和进展的主要原因。如果肾损伤的机制得到更好的阐明，如果在临床建立肾损伤之前可以采用更成功、更积极的策略来检测肾损伤，这些方法可能会立即得到改进。该提案旨在确定是否可以在预测性生物标志物检测亚临床肾损伤的帮助下完成，以便设计新的生物标志物指导的干预性研究，以最大限度地减少该人群中的CKD。因此，我们的长期目标是利用预测性蛋白质组学生物标志物来识别有CKD风险的LT接受者 和合适的候选人进行干预，旨在减少这种风险。作为朝这个方向迈出的一步， 这项R21应用的目的是确定早期蛋白质组特征是否存在于肾功能保留的LT接受者中，这些接受者最终在LT后1-5年内发展为CKD。我们假设这样的血清蛋白质阵列可以预测CKD的未来发展，并识别需要早期干预策略的患者（例如，下一个提议）。这项研究计划有以下两个具体目标：目标1。确定LT后早期是否存在亚临床肾损伤的蛋白质组特征，以预测慢性肾脏疾病的发展。目标二。分析肝移植受者慢性肾病进展过程中蛋白质组特征系列变化的意义。我们在开展这项研究方面处于独特的地位，因为：1）生物样本[Baylor; NIAID CTOT 14试验（U 01 AI 084146）]将容易地用于分析预测特征; 2）西北大学，贝勒大学，斯克里普斯和一家蛋白质组学公司基于规则的医学（RBM）谁拥有许可的多分析物蛋白质组学面板-所有不同的角色，以实现我们的目标。该方法将在独立队列（Baylor & CTOT 14生物储存库）中初步测试和验证早期LT后蛋白质组学发现面板作为即将发生的CKD的预测。然后，我们将测试系列CTOT 14样本，以评估GFR测量的蛋白质特征的演变，从而深入了解肾损伤并改进预测。 由于RBM失去了作为原始资助机制的SBIR，CTOT 14中的蛋白质组学研究不再可用。完成后，我们将验证预测签名，可以通过促进积极主动的，生物标志物驱动的研究方法来改变该领域，以保护该人群的肾功能。1

DESCRIPTION (provided by applicant): Liver transplant (LT) recipients have amongst the highest rates of chronic kidney disease (CKD) of all non- renal solid organ transplant recipients. The impact of CKD in this population is substantial, leading to early and late morbidity and mortality and kidney organ resource utilization. The strategy that LT providers currently employ, which is to wait until renal dysfunction is clinically apparent to institute a treatment strategy, s often too late and ineffective - a major reason why CKD develops and progresses in these patients. These approaches might be imminently improved if mechanisms of renal injury were better clarified and if more successful, proactive strategies to detect renal injury before it is clinically established were available. This proposal aims to determine whether this can be done with the aid of predictive biomarkers detecting subclinical renal injury so as to design novel biomarker-guided interventional studies to minimize CKD in this population. Our long-term goal is thus to utilize predictive proteomic biomarkers that will identify LT recipients at risk for CKD and suitable candidates for interventions aimed at reducing this risk. As a step in that direction, the objective of this R21 application is to determine if early proteomic signatures are present in LT recipients with preserved renal function who eventually develop CKD within 1-5 years of LT. We hypothesize that such an array of serum proteins can predict the future development of CKD and identify patients in need of early interventional strategies (e.g. the next proposal). The study is planned with the following two specific aims: Aim 1. To determine if a proteomic signature of subclinical renal injury is present early after LT that predicts the development of chronic kidney disease. Aim 2. To analyze the significance of serial changes in proteomic signatures during the course of chronic kidney disease progression in liver transplant recipients. We are uniquely positioned to conduct this research because: 1) biosamples [Baylor; NIAID CTOT14 trial (U01 AI084146)] collected from LT recipients with early preserved renal function who subsequently did or did not develop CKD will be readily available to analyze for predictive signatures; 2) an established collaboration exists between the Northwestern, Baylor, Scripps and a proteomics company Rules Based Medicine (RBM) who have the licensed multi-analyte proteomic panels - all with distinct roles to accomplish our goals. The approach will be to initialy test and validate early post-LT proteomic discovery panels as predictive of impending CKD in independent cohorts (Baylor & CTOT14 biorepositories). We will then test serial CTOT14 samples to evaluate the evolution of protein signatures with GFR measures, providing insights into renal injury and refining prediction.This R21 will specifically provide funding for the CKD LT proteomics research in CTOT14 that is no longer available, as RBM lost the SBIR that was the original funding mechanism. Upon completion, we will have validated predictive signatures that could transform the field by promoting proactive, biomarker-driven investigations of approaches to preserve renal function in this population. 1