This project responds to RFA DK-08-015 and seeks to participate in a Consortium to identify and validate biomarkers in CKD. We have assembled a team of experts in biomarker discovery that will examine CKD in the context of microvascular glomerular injury due to autoimmune disease (lupus nephritis, SLE), thrombotic disease (thrombotic thrombocytopenic purpura, TTP), and metabolic disease (diabetes mellitus, DM). These glomerular diseases including diabetes account for over half the patients currently on renal replacement therapy in the United States and over half the patients who come to ESRD annually. Therefore glomerular diseases leading to CKD have an enormous impact on the health care system and patient survival. We specifically propose to identify biomarkers that forecast the future development of CKD in patients at risk of glomerular injury from these diseases, and biomarkers that forecast future progressive CKD in patients with these diseases who already have early CKD. The rationale for developing these CKD forecasters will be to use them to identify patients with glomerular disease destined to develop CKD or progressive renal failure, and aggressively treat these patients to prevent the CKD outcomes. While current therapies to prevent CKD or progression are non-specific, it is anticipated that at least some of the biomarkers discovered here will provide insights into the pathogenesis of CKD that can be used to develop novel targeted therapies for prevention. To accomplish these goals, biomarker discovery will be done using proteomic techniques to interrogate the urine and serum proteomes of well-characterized patients with SLE, TTP, and DM in whom renal function has been followed longitudinally over prolonged time intervals. Once identified by mass spectrometry, these biomarkers will be validated using high-throughput methods in an FDA-compliant fashion in a larger, independent population of patients with glomerular disease and known long-term outcomes. Ultimately we will seek to validate CKD biomarkers that can be used in the clinical setting.

Public Health Relevance

This work will find markers in the urine and blood of patients with diseases like lupus and diabetes that can predict whether the patient will develop chronic kidney disease (CKD) in the future. Using these markers, we will identify patients at risk for CKD early, and treat them aggressively to prevent the CKD from occurring.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DK085673-05
Application #
8537430
Study Section
Special Emphasis Panel (ZDK1-GRB-S (O1))
Program Officer
Kimmel, Paul
Project Start
2009-09-30
Project End
2014-04-30
Budget Start
2013-05-01
Budget End
2014-04-30
Support Year
5
Fiscal Year
2013
Total Cost
$190,212
Indirect Cost
$96,503
Name
Ohio State University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
832127323
City
Columbus
State
OH
Country
United States
Zip Code
43210
Parikh, Samir V; Nagaraja, Haikady N; Hebert, Lee et al. (2014) Renal flare as a predictor of incident and progressive CKD in patients with lupus nephritis. Clin J Am Soc Nephrol 9:279-84
Hao, Wenrui; Rovin, Brad H; Friedman, Avner (2014) Mathematical model of renal interstitial fibrosis. Proc Natl Acad Sci U S A 111:14193-8
McLeish, Kenneth R; Merchant, Michael L; Klein, Jon B et al. (2013) Technical note: proteomic approaches to fundamental questions about neutrophil biology. J Leukoc Biol 94:683-92
Hebert, Lee A; Parikh, Samir; Prosek, Jason et al. (2013) Differential diagnosis of glomerular disease: a systematic and inclusive approach. Am J Nephrol 38:253-66
Merchant, Michael L; Gaweda, Adam E; Dailey, Andrew J et al. (2011) Oncostatin M receptor ýý and cysteine/histidine-rich 1 are biomarkers of the response to erythropoietin in hemodialysis patients. Kidney Int 79:546-54
Rood, Ilse M; Deegens, Jeroen K J; Merchant, Michael L et al. (2010) Comparison of three methods for isolation of urinary microvesicles to identify biomarkers of nephrotic syndrome. Kidney Int 78:810-6