Identification of urinary protein pattern in type 1 diabetic adolescents with early diabetic nephropathy by a novel combined proteome analysis.

Diabetic nephropathy is the main cause of morbidity and mortality in patients with Type 1 diabetes mellitus. Microalbuminuria has been established as a risk factor for the development and the progression of diabetic renal disease. A strong demand exists for better technologies to provide accurate diabetic nephropathy risk estimates before renal functional or structural disturbances already become established. Here, we present the application of a novel proteomics technology identifying urinary polypeptides and proteins. In this pilot study, we investigated 44 Type 1 diabetic patients with more than 5 years of diabetes duration compared with an age-matched control group. Random spot urine samples were examined utilizing high-resolution capillary electrophoresis (CE), coupled to mass spectrometry (MS). More than 1000 different polypeptides, characterized by their separation time and mass, were found between 800 Da and 66.5 kDa. Mathematical analysis revealed specific clusters of 54 polypeptides only found in Type 1 diabetic patients and an additional 88 polypeptides present or absent in patients with beginning nephropathy defined by the albumin-to-creatinine ratio (ACR; >35 mg/mmol). We observed polypeptide patterns characteristic for healthy controls and diabetic patients and subdivision of patients according to the excretion of polypeptides typical for diabetic nephropathy. Our study revealed that the urinary proteome contains a much greater variety of polypeptides than previously recognized and demonstrated the successful application of a novel high-throughput technology towards the human urinary proteome. Future prospective studies with the application of this technique may enable the earlier and more accurate detection of individuals at high risk to develop diabetic nephropathy.

Proteomic analysis for the assessment of diabetic renal damage in humans.

Renal disease in patients with Type II diabetes is the leading cause of terminal renal failure and a major healthcare problem. Hence early identification of patients prone to develop this complication is important. Diabetic renal damage should be reflected by a change in urinary polypeptide excretion at a very early stage. To analyse these changes, we used an online combination of CE/MS (capillary electrophoresis coupled with MS), allowing fast and accurate evaluation of up to 2000 polypeptides in urine. Employing this technology, we have examined urine samples from 39 healthy individuals and from 112 patients with Type II diabetes mellitus and different degrees of albumin excretion rate. We established a 'normal' polypeptide pattern in the urine of healthy subjects. In patients with Type II diabetes and normal albumin excretion rate, the polypeptide pattern in urine differed significantly from normal, indicating a specific 'diabetic' pattern of polypeptide excretion. In patients with higher grade albuminuria, we were able to detect a polypeptide pattern indicative of 'diabetic renal damage'. We also found this pattern in 35% of those patients who had low-grade albuminuria and in 4% of patients with normal albumin excretion. Moreover, we could identify several of the indicative polypeptides using MS/MS sequencing. We conclude that proteomic analysis with CE/MS permits fast and accurate identification and differentiation of polypeptide patterns in urine. Longitudinal studies should explore the potential of this powerful diagnostic tool for early detection of diabetic renal damage.