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.
ADPKD is the most prevalent inherited renal disease accounting for 4% of the ESRD population, and the course of disease is highly variable due to a number of different gene mutations. At present, there is no means of prognosticating the rate by which individuals with ADPKD progress, an important need both for patients planning as well for decisions on who would benefit most from any new therapeutic. This project will lead to a simple, office-based urine and/or blood test for prognostication of ADPKD, which can be utilized in the primary care, nephrology, and urology clinics and which will lead to earlier treatment of this relatively common disease. In addition, work from this proposal will lead to new knowledge about the pathology of the disease and to new ?targets? for drug manufacturers.
| Hu, Susie L; Weiss, Robert H (2018) Management of the Incidental Kidney Mass in the Nephrology Clinic. Clin J Am Soc Nephrol 13:1407-1409 |
| Weiss, Robert H (2018) Metabolomics and Metabolic Reprogramming in Kidney Cancer. Semin Nephrol 38:175-182 |
| Hwang, Vicki J; Zhou, Xia; Chen, Xiaonan et al. (2017) Anticystogenic activity of a small molecule PAK4 inhibitor may be a novel treatment for autosomal dominant polycystic kidney disease. Kidney Int 92:922-933 |
| Chen, Ching-Hsien; Weiss, Robert H (2017) GHetting to know ADPKD proliferative signaling, STAT. Kidney Int 91:524-526 |
