Effects of oral vitamin C supplementation in hemodialysis patients: a proteomic assessment.

Evidence indicates that oxidative stress is present in dialysis patients, and is associated with vitamin C deficiency. Limited data are available regarding the effects of vitamin C supplementation on oxidative stress and inflammation markers in these patients. Moreover, there are no data available on plasma polypeptide fingerprints by proteome analysis before and after vitamin C supplementation. Therefore, we analyzed plasma samples from a prospective, randomized, open-labeled trial to assess the effects of oral vitamin C supplementation (250 mg three times per week), to define the plasma polypeptide pattern in hemodialysis patients. Our results reveal that more than 30 polypeptides show significant changes in the dialysis patients in comparison to controls with normal renal function, and that several polypeptides are affected/normalized by oral vitamin C supplementation. These results underline the remarkable potential for proteomics to recognize specific peptide profiles in different pathological situations, which might not be detected by classical methods.

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.