Development of quantitative metabolomics analyses to understand cystic kidney diseases

慢性肾脏疾病（CKD）是心血管事件最重要的危险因素之一，需要透析或肾移植。CKD的一个常见病因是常染色体显性多囊肾病。常染色体显性多囊肾病的特点是代谢改变，导致成百上千个充满液体的小囊肿增殖，最终破坏肾脏。然而，导致这种表型的代谢途径尚不完全清楚。为了回答这个问题，我将使用非靶向的，基于质谱分析的代谢物实体，代谢物组。尽管代谢组学分析在生物标志物研究中被广泛使用，但该方法在理解（肾脏）疾病机制方面的潜力在很大程度上尚未被探索，生理扰动的影响也没有很好地表征。在这里提出的项目中，我将应用靶向和非靶向代谢组学来了解远端肾元的生理和病理。首先，我打算使用纳米结构成像质谱法来发现哪些代谢物特异性地发生在肾脏的哪个区域，以及它们如何通过生理刺激（尿浓度）发生变化。其次，我的目标是使用全球代谢组学策略来了解正在发展囊肿的肾脏的代谢变化。第三，我想利用目标代谢组学分析来表征一种酶的底物，我发现这种酶在老年肾脏和囊性肾脏中表达上调。总之，该项目产生的数据将对肾脏代谢产生新的见解，并以“多组学”方法补充先前产生的蛋白质组学数据。这项研究表明，这将是代谢组学在远端肾细胞病理生理学中的第一个应用。

Chronic kidney disease (CKD) is one of the most important risk factor for cardiovascular events and requires dialysis or renal transplantation. One frequent cause of CKD is autosomal dominant polycystic kidney disease. Autosomal dominant polycystic kidney disease is characterized by an altered metabolism which drives the proliferation of hundreds and thousands of small fluid-filled cysts, which ultimately destroy the kidney. The metabolic pathways which lead to this phenotype, however, are not completely understood. To answer this question, I will use untargeted, mass-spectrometry based analyses of the entitity of metabolites, the metabolome. Although metabolomic analysis are largely utilized in biomarker studies, the potential of the method to understand (renal) diseases mechanisms is largely unexplored, and the effect of phyisological perturbation is not well characterized. In the project proposed here, I will apply targeted and untargeted metabolomics to understand physiology and pathology of the distal nephron. First, I intend to use nanostructure imaging mass spectrometry to discover which metabolites specifically occur in which region of the kidney and how they change by physiological stimuli (urine concentration). Second, I aim to use a global metabolomics strategy to learn how metabolism changes in the kidneys which are developing cysts. Third, I want to utilize targeted metabolomics analysis to characterize a substrates of an enzyme I found to be upregulated in aged and cystic kidneys. Alltogether, the data generated in this project will generate new insights into renal metabolism and complement previously generated proteomic data in a "multi-omics" approach. The study suggested here will be among the first applications of metabolomics to distal nephron pathophysiology.