9 research outputs found

    The early decline in renal function in patients with type 1 diabetes and proteinuria predicts the risk of end stage renal disease

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    The risk of end-stage renal disease (ESRD) remains high in patients with type 1diabetes and proteinuria; however, little is known about the rate of decline in their renal function. To help determine this we enrolled patients with 1 diabetes and proteinuria whose estimated glomerular filtration rate (eGFR) was normal (equal to or above 60 ml/min/1.73m2m^2). Using a minimum of 5 serial measurements of serum creatinine for 161 patients, we determined individual trajectories of eGFR change and the occurrence of ESRD during 5–18 years of follow-up. The rates were linear for 110 patients, for 24 the non-linear rate was mild enough to satisfy a linear model, and the rates were clearly non-linear for only 27 patients. Overall, in more than one third of patients, the eGFR decline was less than 3.5 ml/min/1.73m2m^2 per year and the lifetime risk of ESRD could be considered negligible. In the remainder of patients, eGFR declined with widely different slopes and ESRD developed within 2 to 18 years. Based on up to five years observation when renal function was within the normal range, the estimates of early eGFR slope predicted the risk of ESRD during subsequent follow-up better than the baseline clinical characteristics of glycated hemoglobin, blood pressure, or the albumin to creatinine ratio. Thus, the early slope of eGFR decline in patients with type 1diabetes and proteinuria can be used to predict the risk of ESRD

    A database of naturally occurring human urinary peptides and proteins for use in clinical applications

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    Owing to its availability, ease of collection and correlation with (patho-) physiology, urine is an attractive source for clinical proteomics. However, the lack of comparable datasets from large cohorts has greatly hindered development in this field. Here we report the establishment of a high resolution proteome database of naturally occurring human urinary peptides and proteins - ranging from 800-17,000 Da - from over 3,600 individual samples using capillary electrophoresis coupled to mass spectrometry, yielding an average of 1,500 peptides per sample. All processed data were deposited in an SQL database, currently containing 5,010 relevant unique urinary peptides that serve as classifiers for diagnosis and monitoring of diseases, including kidney and vascular diseases. Of these, 352 have been sequenced to date. To demonstrate the applicability of this database, two examples of disease diagnosis were provided: For renal damage diagnosis, patients with a specific renal disease were identified with high specificity and sensitivity in a blinded cohort of 131 individuals. We further show definition of biomarkers specific for immunosuppression and complications after transplantation (Kaposi's sarcoma). Due to its high information content, this database will be a powerful tool for the validation of biomarkers for both renal and non-renal diseases
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