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Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria (PRIORITY)
Start date: Jan 1, 2012, End date: Dec 31, 2017 PROJECT  FINISHED 

Patients with diabetes are at risk of developing diabetic nephropathy, which will ultimately result in the requirement for renal replacement therapy and is also associated with high cardiovascular morbidity and mortality. Detection of low concentrations of albuminuria in urine (microalbuminuria) is the current clinical standard for detecting those at significant risk and targeting preventive treatment. However, albuminuria is of low specificity at early stages of disease, and of considerable biological variability, hence a poor predictor at early stages of disease. In two independent studies we have demonstrated that urinary proteomics offers the prospect of detecting nephropathy earlier in the preclinical phase, enabling targeted treatment at an earlier stage. We propose to assess the potential of this technology to identify normoalbuminuric patients at risk and to target therapy with an aldosterone receptor antagonist (spironolactone) as add-on to recommended therapy including angiotensin converting enzyme (ACE) inhibition or angiotensin II receptor blockers (ARBs) according to national guidelines. We will test the following hypotheses: (1) urinary proteomics predicts progression of albuminuria (as a surrogate marker for the development of overt nephropathy) in a cohort of 3280 type 2 diabetic patients with normal urinary albumin excretion, and (2) early initiation of intensive preventive therapy directed by urinary proteomics reduces progression of albuminuria in those 20 % at high risk and thereby delay progression to overt nephropathy and spare treatment for those with low risk, paving the way of personalised medicine. This will be the first biomarker-directed therapy trial for primary prevention of diabetic kidney disease. Additional clinical and circulating biomarkers will be assessed and models to predict progression of albuminuria including clinical factors, biomarkers and proteomics will be developed.

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