Autosomal dominant polycystic kidney disease (ADPKD) is a major cause of disabling morbidity and is the fourth leading cause of end-stage renal failure in the world, affecting more than 500,000 U.S. citizens and millions more worldwide. Researchers at the University of Alabama, Emory University, University of Kansas, Mayo Clinic and Washington University St. Louis joined together in 2000 to create the Consortium for Radiologic Studies of Polycystic Kidney Disease (CRISPI). The primary objectives of this investigation were to: (1) to develop and test the accuracy and reproducibility of imaging techniques to monitor changes in renal cyst size and parenchymal involvement, (2) to establish and maintain a database of uniformly and accurately collected information, and (3) to maintain and make available such data to facilitate the planning and implementation of clinically appropriate interventions in the near future. The goals of CRISPII are to extend the observations of CRISPI in order to: 1) draw unequivocal linkage between the rate of kidney/cyst enlargement and qualitative and quantitative end-points;2) to provide a marker of disease progression (kidney volume) sensitive and accurate enough to be used as a primary outcome marker in clinical trials aiming to forestall disease progression;3) to develop and test other biomarkers of disease progression.
The specific aims are:
Aim 1 : Extend the preliminary observations of CRISPI to ascertain the extent to which quantitative (kidney volume and hepatic and kidney cyst volume) or qualitative (cyst distribution and character) structural parameters predict renal insufficiency.
Aim 2 : Extend the preliminary observations of CRISPI to ascertain the extent to which age and sex-adjusted measurements of renal blood flow by MR technology predict the rate of renal growth;and, renal blood flow and kidney volume predict the rate of renal function decline in ADPKD.
Aim 3 : Exhaustively analyze the living database and stored biologic samples derived from CRISPI and the CRISPII extension to develop and test new metrics to quantify and monitor disease progression. Extend the analysis of monocyte chemotactic protein-1 (MCP-1) excretion to determine if absolute levels of urinary MCP-1 excretion and changes in the rates of excretion bear relation to specific morbid events (e.g. gross hematuria, new onset hypertension urinary tract infection, renal stone, nonspecific renal pain, and worsening renal function (declining GFR or increased albuminuria).

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK056943-10
Application #
7769514
Study Section
Special Emphasis Panel (ZDK1-GRB-G (O1))
Program Officer
Flessner, Michael Francis
Project Start
2000-02-01
Project End
2011-07-14
Budget Start
2010-01-01
Budget End
2011-07-14
Support Year
10
Fiscal Year
2010
Total Cost
$289,974
Indirect Cost
Name
University of Kansas
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
016060860
City
Kansas City
State
KS
Country
United States
Zip Code
66160
Kline, Timothy L; Korfiatis, Panagiotis; Edwards, Marie E et al. (2017) Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease. Kidney Int 92:1206-1216
Shen, Chengli; Landsittel, Douglas; Irazabal, María V et al. (2017) Performance of the CKD-EPI Equation to Estimate GFR in a Longitudinal Study of Autosomal Dominant Polycystic Kidney Disease. Am J Kidney Dis 69:482-484
Yu, Alan S L; Shen, Chengli; Landsittel, Douglas P et al. (2017) Baseline total kidney volume and the rate of kidney growth are associated with chronic kidney disease progression in Autosomal Dominant Polycystic Kidney Disease. Kidney Int :
Kim, Youngwoo; Bae, Sonu K; Cheng, Tianming et al. (2016) Automated segmentation of liver and liver cysts from bounded abdominal MR images in patients with autosomal dominant polycystic kidney disease. Phys Med Biol 61:7864-7880
Heyer, Christina M; Sundsbak, Jamie L; Abebe, Kaleab Z et al. (2016) Predicted Mutation Strength of Nontruncating PKD1 Mutations Aids Genotype-Phenotype Correlations in Autosomal Dominant Polycystic Kidney Disease. J Am Soc Nephrol 27:2872-84
Kim, Youngwoo; Ge, Yinghui; Tao, Cheng et al. (2016) Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease. Clin J Am Soc Nephrol 11:576-84
Porath, Binu; Gainullin, Vladimir G; Cornec-Le Gall, Emilie et al. (2016) Mutations in GANAB, Encoding the Glucosidase II? Subunit, Cause Autosomal-Dominant Polycystic Kidney and Liver Disease. Am J Hum Genet 98:1193-1207
Irazabal, María V; Rangel, Laureano J; Bergstralh, Eric J et al. (2015) Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials. J Am Soc Nephrol 26:160-72
Bae, Kyongtae T; Sun, Hongliang; Lee, June Goo et al. (2014) Novel methodology to evaluate renal cysts in polycystic kidney disease. Am J Nephrol 39:210-7
Boertien, Wendy E; Meijer, Esther; Li, Jie et al. (2013) Relationship of copeptin, a surrogate marker for arginine vasopressin, with change in total kidney volume and GFR decline in autosomal dominant polycystic kidney disease: results from the CRISP cohort. Am J Kidney Dis 61:420-9

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