A Metabolomic Approach to Discovering Markers for ADPKD Progression

摘要 ADPKD是最常见的遗传性肾病，占ESRD人群的4%。检测 利用肾成像的囊肿是诊断这种疾病的最常用方法。更重要的是， 目前还没有明确的方法来预测哪些患者将进展最快，独立于 对症治疗和血压控制，谁将有一个更良性的过程。这一点 最重要的是，由于与疾病相关的无数突变， 路线是高度可变的。此外，在当今时代，我们正处于发现和 验证新的治疗方法，如加压素抑制剂，将有必要将患者分为 那些可能需要这种潜在毒性治疗的人与那些不需要干预就能做得很好的人。较早 来自这个小组的NIH拨款被用来制定最佳样本收集的后勤工作;我们表明， 明确地说，每天的变化是最小的，空腹样本是最佳的。使用材料 在HALT试验中，系统地收集了空腹血和尿并储存起来， 将对血浆进行非靶向代谢组学分析，以确定哪些代谢物可以区分 从缓慢ADPKD进展者迅速。我们将执行发现（目标1）和验证（目标3）实验 因此，在研究结束时，我们可以非常有信心地进行敏感和特异性的测试， ADPKD快速进展者。此外，我们将使用途径和网络分析（目标2）来发现新的 在第一次分析中未鉴定的代谢物，表明新的病理生理途径 和前景，这将导致迄今未被认识的治疗目标。成功完成 这些实验将导致一个重大的进展，在acquisition，病理生理学，以及，最终， 选择ADPKD的最佳治疗方案。我们的研究将是代谢组学在 人类囊性肾病，并且是第一个成功利用该技术治疗任何肾脏疾病的人。 此外，我们的工作将作为一个模型，使用代谢组学收集途径和网络数据，从一个 各种遗传性疾病。

ABSTRACT ADPKD is the most prevalent inherited renal disease, accounting for 4% of the ESRD population. Detection of cysts utilizing renal imaging has been the most common method of diagnosis of this disease. More importantly, there is at present no definitive way to predict which patients will progress most rapidly, independent of symptomatic therapy and blood pressure control, and who will have a more benign course. This is of paramount importance due to the fact that, due to the myriad mutations associated with the disease, the course is highly variable. Additionally, in the current era in which we are at the cusp of discovering and validating new therapeutics, such as the vasopressin inhibitors, it will be essential to segregate patients into those likely to need such potentially toxic therapy from those who will do well without intervention. An earlier NIH grant from this group was utilized to work out the logistics of optimal collection of samples; we showed unequivocally that day-to-day variability was minimal, and that fasting samples were optimal. Using materials from the HALT trial, in which fasting blood and urine were collected systematically and have been banked, we will perform non-targeted metabolomics analysis on plasma to determine which metabolites can differentiate rapid from slow ADPKD progressors. We will perform discovery (Aim 1) and validation (Aim 3) experiments using HALT samples so, by the end of the study, we can be quite confident of a sensitive and specific test for rapid ADPKD progressors. In addition, we will use pathway and network analysis (Aim 2) to discover novel metabolites which were not identified in the first analysis and which indicate new pathophysiological pathways and perspectives and which will lead to heretofore unrecognized targets for therapy. Successful completion of these experiments will result in a major advance in prognostication, pathophysiology, as well as, ultimately, the selection of optimal treatment regimens for ADPKD. Ours will be the first described use of metabolomics in human cystic kidney disease and one of the first to successfully exploit this technology in any renal disease. Furthermore, our work will serve as a model for using metabolomics to glean pathway and network data from a variety of hereditary diseases.