ADPKD is the most prevalent inherited renal disease, accounting for 4% of the ESRD population. Detection of renal cysts utilizing renal imaging has been the most common method of diagnosis of this disease however, cyst appearance is often delayed with affected individuals not demonstrating renal cystic disease until the 4th decade of life. At present, other than genotyping, there is no test to diagnose the disease in its earliest stages and is successful only 85% of the time. In this revised proposal, we will exploit the new science of metabolomics, in collaboration with internationally-renowned experts in this nascent field, to discover a pattern of urinary and plasma metabolites which serve as biomarkers for ADPKD. We will utilize patient materials from the ongoing HALT study;a HALT Principal Investigator is the co-Investigator for this study. Our collaborating biostatistician has calculated the desired sample size utilizing preliminary data derived from preliminary urinary metabolomic analysis of patients and controls from our two institutions. Our proposal is extraordinary in that we have assembled a unique cadre of investigators: a cell biologist who is also a clinician-scientist nephrologist (Dr. Weiss), a nephrologist and clinical trials expert (Dr. Chapman), a proteomics and genomics bioinformatics expert (Dr. Perroud), four metabolomics experts (Drs Hammock, Grant, Michelmore and Fiehn), and a biostatistician with expertise in """"""""omic"""""""" analyses (Dr. Kim) to utilize metabolomics to tackle the problem of diagnosis and treatment of a relatively common disease which is difficult to diagnose, and for which current treatment options are limited. The application has been markedly improved since the original submission by the addition of more preliminary data (including a human control trial and a mouse PKD metabolomic experiment), as well as narrative which addresses all of the concerns of the original reviewers including a new Specific Aim which addresses important concerns about control data interpretation. Several additional metabolomics experts at the PI's institution, with whom he has ongoing scientific relationships, have been recruited for this revision to assist in complicated metabolomic data interpretation, should this become necessary. Successful completion of these experiments will result in a major advance in diagnosis as well as, ultimately, the selection of optimal treatment regimens for this disease. Ours will be the first described use of metabolomics in cystic kidney disease, and one of the first to exploit this technology in any renal disease. Furthermore, our work can serve as a model for using metabolomics to glean pathway and network data from a variety of hereditary diseases.
NARRATIVE ADPKD is the most prevalent inherited renal disease accounting for 4% of the ESRD population. At present, other than genotyping, which is successful only 85% of the time, there is no test to diagnose the disease in its early, pre-cystic stages at which time novel therapies have the best chance of being effective. This project will lead to a simple, office-based urine and/or blood test for detection 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 selection of patients who will most benefit from any new drug.
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