Autosomal Dominant Polycystic Kidney Disease (ADPKD) is one of the most common monogenic diseases, affecting >1:1000 individuals worldwide. It is characterized by large fluid-filled renal cysts that remodel, compress and destroy surrounding normal tissue, and that progressively reduce kidney function, leading to end stage renal disease in about 50% of patients by the sixth decade of life. Most ADPKD results from mutations in two genes, PKD1, which encodes the polycystin-1 protein (PC1), and PKD2, which encodes the polycystin-2 protein (PC2). PC1 and PC2 interact with one another and are thought to play a role in cilia signaling. It is generally accepted that the cilium is a central component in the pathways that drive ADPKD pathogenesis. Although their mechanistic connection to the functional PC complex in cilia is unclear, numerous signaling pathways are perturbed in cysts. In the past few years the list of disease-related pathways has grown through new evidence that implicates metabolism as a novel pathway that is profoundly affected in ADPKD and that may both participate in disease pathogenesis and serve as a target for therapeutic development. While it remains to be established whether the newly-identified metabolic derangements that characterize ADPKD are direct drivers of cyst formation, it is clear that the nature and activities of a cell's many and varied intertwined metabolic circuits plays a central role in determining its capacity to invest the energy required in order to participate in the proliferation and active solute and fluid transport that are required for cyst growth. The main goal of this proposal is to provide the research community with novel tools and data sets that will substantially enhance efforts to explore and exploit the metabolic changes that characterize ADPKD. We will produce a uniquely designed and rigorously curated resource based upon novel in vivo models of the cell specific transcriptomic, mitochondrial proteomic and mitochondrial metabolic effects that result from the earliest stages after loss of the PC proteins and that are further informed by the effects of concomitant cilia loss and PC protein reactivation. This program will make use of adult inducible conditional PC knockout mouse models and will employ strategies that will permit conditional isolation of ribosomes (TRAP) and conditional isolation of mitochondria, thus enabling cell-type- specific transcriptomic and mitochondrial proteomic and metabolomic studies. State of the art in vivo metabolic flux studies will be applied to the kidney cortices of these novel genetic mouse models. The results of these analyses will be combined to produce robust biological data sets that will be assembled through application of the requisite informatics mechanisms in order to disseminate these data to the broader research community in near real time. Critically, our in vivo studies are designed to discover the earliest changes that occur after kidney tubules lose polycystin protein expression?at time points well before cysts form. The research team brings together extensive and complementary expertise in ADPKD animal models, PC signaling and biology and in vivo metabolic studies coupled with strong biostatistical and bioinformatics support to produce the proposed resource.

Public Health Relevance

Autosomal dominant polycystic kidney disease (ADPKD) is the most common cause of inherited kidney disease; it causes the kidneys to enlarge and stop working and many times patients need either dialysis or transplantation to replace the kidneys' function. This research program is designed to use innovative mouse models based on inactivation of the same genes as cause the human disease in combination with other recent technological advances to create large, comprehensive data sets of the specific changes in gene expression and metabolic function in the subset of cells in the kidney that will give rise to the cysts that ultimately destroy kidney function. These data sets will be made publicly available so that the maximum number of investigators can make use of them in their efforts to understand how this disease occurs and, more importantly, to develop the therapies that will slow this disease without causing unnecessary side effects to patients.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
High Impact Research and Research Infrastructure Programs (RC2)
Project #
1RC2DK120534-01
Application #
9710264
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Maric-Bilkan, Christine
Project Start
2019-09-09
Project End
2024-06-30
Budget Start
2019-09-09
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Yale University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520