Renal Metabolite Handling: from Gene to Function to Disease

肾脏在维持全身内环境稳定方面起着核心作用。慢性肾病（CKD）影响超过10%的成年普通人群。即使在生理条件下，我们对肾脏的多种功能的理解也是不完整的，这阻碍了CKD特异性治疗的发展。获得对肾功能（病理）生理学的了解由于器官的复杂性而变得复杂：过滤和分泌溶质的处理差异很大。这些溶质中的许多是代谢物、小的中间体或代谢过程的产物。代谢物浓度的全基因组遗传筛选是一种无偏见的方式来深入了解这些过程，例如通过鉴定新的代谢物转运蛋白或酶。在KO 3598/4-1的第一个资助期内，我们成功地建立了通过将基因组学和代谢组学数据联系起来研究大型人群中人类肾脏代谢物处理的方法。我们对1,200例CKD患者的代谢物处理产生了新的见解。这包括特定于已知尿毒症毒素的发现，但也包括适用于人类肾脏生理学的更一般的发现，例如鉴定人体中肾酶和氨基酸交换剂的底物。对于第二个资助期，我们现在提出了几个重要的进展：首先，我们将把德国慢性肾脏病研究的人口规模从1,200人增加到5,217人。这将提高统计功效，特别是用于鉴定对代谢物浓度有较大影响的罕见遗传变异。其次，我们将代谢物的数量从188增加到> 1，400。尿代谢物浓度的非靶向、基于质谱的定量将允许对特定生化途径的深入评价和对未知身份的分子的研究。第三，我们将对我们的研究结果与健康个体的基于人群的研究结果进行系统性比较，以便系统地区分CKD特异性机制和对肾脏代谢的更普遍的见解。第四，我们将能够通过评估代谢物和风险变体与> 2，000例CKD进展事件，心血管终点和全因死亡率之间的关联，将确定的机制转化为临床见解。为了识别和表征肾脏代谢物处理的机制，我们将使用无偏的全基因组关联研究和全外显子组罕见变异关联研究（目标1），复合代谢物测量的全基因组遗传筛选，如高度相关代谢物的比率和簇（目标2），以及相关机制的流行病学和实验随访研究（目标3）。已经生成了遗传，代谢组学和终点数据，使拟议的研究可行，前沿和相关，以推进我们对肾脏在健康和疾病代谢物处理中的作用的见解。

The kidneys have a central role for whole body homeostasis. Chronic kidney disease (CKD) affects >10% of the adult general population. Our understanding of the manifold functions of the kidney is incomplete even under physiological conditions, impeding the development of specific therapies for CKD. Gaining insights into kidney function (patho-)physiology has been complicated by the organ’s complexity: the handling of filtered and secreted solutes varies widely. Many of these solutes are metabolites, small intermediates or products of metabolic processes. Genome-wide genetic screens of metabolite concentrations are an unbiased way to gain insights into such processes, for example by identifying novel metabolite transporters or enzymes. In the first funding period of KO 3598/4-1, we successfully established methods to study human renal metabolite handling in large human populations by linking genomics and metabolomics data. We generated novel insights into metabolite handling in 1,200 patients with CKD. This included findings specific to known uremic toxins, but also more general findings applicable to human renal physiology, such as the identification of substrates of renal enzymes and amino acid exchangers in humans. For a second funding period, we now propose several important advances: first, we will increase the population size from 1,200 to all 5,217 persons in the German Chronic Kidney Disease study. This will lead to improved statistical power especially for the identification of rare genetic variants with large effects on metabolite concentrations. Second, we will increase the number of metabolites from 188 to >1,400. The non-targeted, mass-spectrometry based quantification of urinary metabolite concentrations will allow both for the in-depth evaluation of specific biochemical pathways and for the study of molecules of yet unknown identity. Third, we will perform a systematic comparison of our findings to those from a population-based study of healthy individuals, in order to systematically distinguish CKD-specific mechanisms from more general insights into renal metabolism. And fourth, we will be able to translate the identified mechanisms into clinical insights by evaluating the associations between metabolites and risk variants with >2,000 events of CKD progression, cardiovascular endpoints and all-cause mortality. To identify and characterize mechanisms of renal metabolite handling, we will use unbiased genome-wide association studies and exome-wide rare variant association studies (Aim 1), genome-wide genetic screens of composite metabolite measures such as ratios and clusters of highly correlated metabolites (Aim 2), and epidemiological and experimental follow-up studies of implicated mechanisms (Aim 3). Genetic, metabolomics and endpoint data have already been generated, making the proposed research feasible, cutting-edge and relevant to advance our insights into the role of the kidney in metabolite handling in health and disease.