Clinical Drug Experience Knowledgebase

Background Information Diabetes mellitus (DM) affects 9% of the European population and the cost of caring for patients with DM accounts for 15% of the European health care budget expenditure. Al-most 90% of patients have type 2 DM, and absolute numbers are expected to rise in parallel to the current obesity and metabolic syndrome epidemic. Improved treatment has reduced mortality but the prolonged duration of DM increases the likelihood of development of late diabetic complications.

Diabetic nephropathy is one of the major late complications of diabetes and is associated with substantial cardiovascular morbidity and mortality and is a leading cause of end stage renal disease (ESRD) in the Western world. In clinical practice, renal impairment is diagnosed by albuminuria or proteinuria and/or changes in serum creatinine/creatinine clearance indicating alterations of the glomerular filtration rate (GFR). However, the inter-individual variability is high, and as a consequence, these standard tests have a moderate specificity and sensitivity at early stages of disease, with major limitations in the diagnosis of the early stages of diabetic nephropathy (DN).

Development of DN is generally characterized by an increase of urinary albumin excretion rate (>300 mg/24 h or 200 μg/min). Microalbuminuria (30-300 mg/24 h or 20-200 μg/min) is considered a risk factor and as an early indicator of future onset of DN. Microalbuminuria is regarded as the earliest clinical marker of renal damage. However, structural changes to the kidney have already occurred at the stage of microalbuminuria and patients with microalbuminuria have a high risk for development of renal disease, but also increased morbidity and mortality due to cardiovascular disease.

Blood pressure and glycemic control with pharmacotherapeutic intervention as well as life style interventions are the cornerstones of type 2 DM management aiming at prevention of microvascular complications. Specific therapy, particularly treatment with angiotensin converting enzyme inhibitors (ACE) and angiotensin receptor antagonists (ARB) to prevent progression to overt proteinuria and advanced stages of diabetic nephropathy is recommended if microalbuminuria is present. Studies aiming for earlier prevention of nephropathy by starting renin angiotensin aldosterone system (RAAS) blocking treatment in normoalbuminuric patients have given mixed and often disappointing results. This might reflect that a large fraction of normoalbuminuric patient may not be at risk for progression thereby reducing the event rate or power in previous studies. Early identification of normoalbuminuric patients at high risk for development of diabetic nephropathy could identify patients who might benefit of intervention with increased blockade of the RAAS. Furthermore, blockade of the RAAS with aldosterone blockade has been demonstrated to reduce urinary albumin excretion with 20-30% on top of standard antihypertensive treatment including ACE or ARB in proteinuric type 1 and 2 diabetic patients, and a 60% reduction was seen in microalbuminuric type 1 diabetic patients. Therefore, it may also hold the potential to reduce the risk of development of microalbuminuria in high risk normoalbuminuric patients.

CKD Biomarker panel Proteomics is the analysis of large number of proteins or polypeptides in tissue and body fluids. Capillary electrophoresis mass spectrometry (CE-MS) enables reproducible and robust high-resolution analysis of several thousand low-molecular-weight urinary proteins/peptides in about one hour. Urine holds several advantages over blood in clinical proteomics. It can be collected non-invasively and its proteome is relatively stable. Members of the consortium have successfully identified a urinary biomarker pattern including 273 peptides significantly associated with chronic kidney disease (CKD273).

Importantly, the biomarker panel has been validated in a multicentric approach involving >1000 blinded samples. The accuracy was high (96% sensitivity and 98% specificity), when evaluating only the diabetic patients in the test-set. To test the CKD273 pat-tern as a tool for early detection of DN, we recently performed an independent longitudinal study of normoalbuminuric diabetic patients at inclusion. The urinary CKD273 pattern distinguished progressing patients from non-progressing patients. The corresponding receiver operating characteristic (ROC) analysis resulted in an area under the curve (AUC) of 0.925 assuming a prevalence of 30% for DN. The positive predictive value was 97% and the negative predictive value was 88%. The specificity of the CKD273 pattern was further evaluated in patients without any evidence for renal impairment based on clinical history, creatinine, or urinary protein levels resulting in an overall specificity of 98%.

The used CKD273 pattern showed that these biomarkers can detect initiation and progression of DN earlier than the currently used indicators, well preceding increases in urinary albumin levels. While the CKD273 pattern detected DN with >90% accuracy four years before clinical diagnosis, serum creatinine and/or Urine albumin execration rate did not detect DN earlier than one and two years before clinical manifestation, respectively. In addition, diagnostic accuracy was significantly lower compared to the CKD273 pattern. In addition, two independent studies on type 1 and type 2 DM patients, on longitudinally collected samples over a period of 10 years demonstrate that CKD273 markers of kidney disease were altered 3 to 5 years prior to manifestation of albuminuria, and 1 to 2 years prior to development of microalbuminuria. Thus, the performance of the CKD273 pattern is better than prediction based on urinary albumin values and represents potentially a significant improvement over the current state of the art in assessing DN, enabling earlier detection with higher accuracy than urinary albumin.

Finally, the proteome analysis and application of the CKD273 pattern indicated a positive scoring for CKD in microalbuminuric type 2 diabetic patients, which showed persistent improvement during long-term renoprotective treatment with Irbesartan, while placebo treated patients showed a slight deterioration of kidney damage markers likely reflecting disease progression in the absence of preemptive intervention.

Collectively, our existing data strongly indicate that the urinary proteomics based test ap-pears ideal to identify patients who will develop microalbuminuria and ultimately DN and thereby facilitates targeting intensified preventative therapy to this group.

Rationale:

Urinary proteomics predicts development of microalbuminuria (as a surrogate marker for the development of overt nephropathy) in a cohort of type 2 diabetic patients with normal urinary albumin excretion at screening.
Early initiation of preventive therapy with spironolactone reduces risk of transition to microalbuminuria in those identified by urinary proteomics to be at high risk, and thereby delays progression to overt nephropathy. Treatment can be spared for those with low risk according to urinary proteomics, paving the way of personalised medicine

Primary Objective To confirm that urinary proteomics can predict development of microalbuminuria (as a surrogate marker for the development of overt nephropathy) in a cohort of type 2 diabetic patients with normal urinary albumin excretion.

Secondary Objectives To investigate if early initiation of preventive therapy with spironolactone 25 mg once daily reduces risk of transition to microalbuminuria in those patients identified by urinary proteomics to be at high risk.

Additional Scientific Objectives To compare the rate of change in urinary albumin excretion rate in high vs. low-risk population (based on the proteomic test), and to compare the effect of spironolactone on rate of change in urine albumin execration rate in the intervention group.

In addition, the objective is to study the rate of change in estimated GFR in relation to urinary marker pattern (CKD 273) and the intervention with spironolactone.

To study the ability of urinary proteomic patterns, to predict cardiovascular or renal events during the study as well as response to intervention, in relation to study endpoints.