Type 2 diabetes is a major public health problem worldwide. Progressive chronic kidney disease (CKD) in type 2 diabetes is associated with significant morbidity and mortality. There are few approaches available for the early detection of CKD in diabetes. Our primary goal of this proposal is to develop novel urine biomarkers to better predict progressive CKD in diabetics. We propose that there are better markers to predict CKD in diabetics than albuminuria. These include biomarkers that reflect tubulointerstitial injury, inflammation and fibrosis, and oxidative stress. We have identified 11 promising serum and urinary biomarkers that reflect these different pathways of injury in diabetic kidney disease. The ACCORD study demonstrated that intensive glycemic control vs. standard glycemic control over a period of 3.5 years reduced the incidence of albuminuria but did not reduce the incidence of incident CKD nor end-stage renal disease (2.1% vs. 2.2%) between the two glycemia-treatment arms. These findings require explanations and only underscore the necessity to predict incident and progressive CKD in type 2 diabetes. The ultimate goal is to identify better surrogates or therapeutic targets for kidney disease in diabetics. Thus, our specific aims for this proposal are the following:
Specific Aim 1 : To identify novel biomarkers predictive of incident and progressive diabetic kidney disease. Hypothesis 1a: Novel biomarkers of tubulointerstitial kidney injury and other pathways of kidney disease progression measured on baseline samples will predict incident diabetic kidney disease in ACCORD. Hypothesis 1b: Changes in biomarkers from baseline to will predict those with fast progression of diabetic kidney disease (ESRD) Hypothesis 1c: A comprehensive model incorporating novel biomarkers of tubulointerstitial kidney damage will predict incident and progressive DKD better than demographic, clinical and laboratory variables alone Specific Aim 2: Using the panel of the top 5 biomarkers developed under Specific Aim #1, to understand the pathways by which intensive glycemic control reduced microvascular outcomes (albuminuria and retinopathy) but did not reduce the definitive events of incident CKD or ESRD in the ACCORD trial. Hypothesis 2a: Intensive glycemic control will have a beneficial effect on the serum and urine biomarkers that are most predictive of progressive diabetic kidney disease at 24 months, potentially indicating that the duration of therapy was not sufficiently long to witness differences in CKD and ESRD between the two groups.

Public Health Relevance

Diabetic kidney disease is a growing public health problem with enormous impact on morbidity and mortality. The potential impact of this project is to better understand the pathophysiology of initiation of diabetic kidney disease; improve prediction of diabetic kidney disease onset and progression; and development of novel targets for therapies to reduce the burden of diabetic kidney disease. Finally, this study will help explain the reasons that intensive glycemic control did not improve definitive kidney outcomes in the ACCORD trial.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK096549-05
Application #
9148172
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Kimmel, Paul
Project Start
2012-09-01
Project End
2017-06-30
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
5
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
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Chauhan, Kinsuk; Verghese, Divya Anna; Rao, Veena et al. (2018) Plasma endostatin predicts kidney outcomes in patients with type 2 diabetes. Kidney Int :
Nadkarni, Girish N; Chauhan, Kinsuk; Verghese, Divya A et al. (2018) Plasma biomarkers are associated with renal outcomes in individuals with APOL1 risk variants. Kidney Int 93:1409-1416
Meisner, Allison; Kerr, Kathleen F; Thiessen-Philbrook, Heather et al. (2018) Development of biomarker combinations for postoperative acute kidney injury via Bayesian model selection in a multicenter cohort study. Biomark Res 6:3
Nadkarni, Girish N; Ferrandino, Rocco; Chang, Alexander et al. (2017) Acute Kidney Injury in Patients on SGLT2 Inhibitors: A Propensity-Matched Analysis. Diabetes Care 40:1479-1485
Coca, Steven G; Nadkarni, Girish N; Huang, Yuan et al. (2017) Plasma Biomarkers and Kidney Function Decline in Early and Established Diabetic Kidney Disease. J Am Soc Nephrol 28:2786-2793
Meisner, Allison; Kerr, Kathleen F; Thiessen-Philbrook, Heather et al. (2016) Methodological issues in current practice may lead to bias in the development of biomarker combinations for predicting acute kidney injury. Kidney Int 89:429-38
Tummalapalli, Lekha; Nadkarni, Girish N; Coca, Steven G (2016) Biomarkers for predicting outcomes in chronic kidney disease. Curr Opin Nephrol Hypertens 25:480-486
Nadkarni, Girish N; Coca, Steven G (2016) Temporal Trends in AKI: Insights from Big Data. Clin J Am Soc Nephrol 11:1-3
Coca, Steven G; Zabetian, Azadeh; Ferket, Bart S et al. (2016) Evaluation of Short-Term Changes in Serum Creatinine Level as a Meaningful End Point in Randomized Clinical Trials. J Am Soc Nephrol 27:2529-42

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