Dataset Information

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy.

ABSTRACT:

Background

Diabetic nephropathy (DN) is one of the major late complications of diabetes. Treatment aimed at slowing down the progression of DN is available but methods for early and definitive detection of DN progression are currently lacking. The 'Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial' (PRIORITY) aims to evaluate the early detection of DN in patients with type 2 diabetes (T2D) using a urinary proteome-based classifier (CKD273).

Methods

In this ancillary study of the recently initiated PRIORITY trial we aimed to validate for the first time the CKD273 classifier in a multicentre (9 different institutions providing samples from 165 T2D patients) prospective setting. In addition we also investigated the influence of sample containers, age and gender on the CKD273 classifier.

Results

We observed a high consistency of the CKD273 classification scores across the different centres with areas under the curves ranging from 0.95 to 1.00. The classifier was independent of age (range tested 16-89 years) and gender. Furthermore, the use of different urine storage containers did not affect the classification scores. Analysis of the distribution of the individual peptides of the classifier over the nine different centres showed that fragments of blood-derived and extracellular matrix proteins were the most consistently found.

Conclusion

We provide for the first time validation of this urinary proteome-based classifier in a multicentre prospective setting and show the suitability of the CKD273 classifier to be used in the PRIORITY trial.

SUBMITTER: Siwy J

PROVIDER: S-EPMC4118140 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Publications

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy.

Siwy Justyna J Schanstra Joost P JP Argiles Angel A Bakker Stephan J L SJ Beige Joachim J Boucek Petr P Brand Korbinian K Delles Christian C Duranton Flore F Fernandez-Fernandez Beatriz B Jankowski Marie-Luise ML Al Khatib Mohammad M Kunt Thomas T Lajer Maria M Lichtinghagen Ralf R Lindhardt Morten M Maahs David M DM Mischak Harald H Mullen William W Navis Gerjan G Noutsou Marina M Ortiz Alberto A Persson Frederik F Petrie John R JR Roob Johannes M JM Rossing Peter P Ruggenenti Piero P Rychlik Ivan I Serra Andreas L AL Snell-Bergeon Janet J Spasovski Goce G Stojceva-Taneva Olivera O Trillini Matias M von der Leyen Heiko H Winklhofer-Roob Brigitte M BM Zürbig Petra P Jankowski Joachim J

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association 20140302 8

<h4>Background</h4>Diabetic nephropathy (DN) is one of the major late complications of diabetes. Treatment aimed at slowing down the progression of DN is available but methods for early and definitive detection of DN progression are currently lacking. The 'Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial' (PRIORITY) aims to evaluate the early detection of DN in patients with t ...[more]

PMID: 24589724

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Project description:BACKGROUND:Liver fibrosis is a consequence of chronic inflammation and is associated with protein changes within the hepatocytes structure. In this study, we aimed to investigate if this is reflected by the urinary proteome and can be explored to diagnose liver fibrosis in patients with chronic liver disease. METHODS:In a multicentre combined cross-sectional and prospective diagnostic test validation study, 129 patients with varying degrees of liver fibrosis and 223 controls without liver fibrosis were recruited. Additionally, 41 patients with no liver, but kidney fibrosis were included to evaluate interference with expressions of kidney fibrosis. Urinary low molecular weight proteome was analysed by capillary electrophoresis coupled to mass spectrometry (CE-MS) and a support vector machine marker model was established by integration of peptide markers for liver fibrosis. FINDINGS:CE-MS enabled identification of 50 urinary peptides associated with liver fibrosis. When combined into a classifier, LivFib-50, it separated patients with liver fibrosis (N = 31) from non-liver disease controls (N = 123) in cross-sectional diagnostic phase II evaluation with an area under the curve (AUC) of 0.94 (95% confidence intervals (CI): 0.89-0.97, p<0.0001). When adjusted for age, LivFib-50 demonstrated an AUC of 0.94 (95% CI: 0.89-0.97, p<0.0001) in chronic liver disease patients with (N = 19) or without (N = 17) liver fibrosis progression. In this prospective diagnostic phase III validation set, age-adjusted LivFib-50 showed 84.2% sensitivity (95% CI: 60.4-96.6) and 82.4% specificity (95% CI: 56.6-96.2) for detection of liver fibrosis. The sequence-identified peptides are mainly fragments of collagen chains, uromodulin and Na/K-transporting ATPase subunit ?. We also identified ten putative proteolytic cleavage sites, eight were specific for matrix metallopeptidases and two for cathepsins. INTERPRETATION:In liver fibrosis, urinary peptides profiling offers potential diagnostic markers and leads to discovery of proteolytic sites that could be targets for developing anti-fibrotic therapy.

Dataset Information

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy.

Background

Methods

Results

Conclusion

Publications

Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy.

Similar Datasets

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