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.

Keywords: biomarkers; chronic kidney disease; diabetic nephropathy; diagnosis; urine proteomics.

FIGURE 1:

Compiled urinary protein profiles. (A) All peptides detected in the combined T2D cohort with DN and (B) without DN. (C) The 273 CKD biomarkers in the combined T2D cohort with and (D) without DN. Normalized molecular weight (800–20 000 Da) in logarithmic scale is plotted against normalized migration time (18–45 min). The mean signal intensity of polypeptides is given as peak height.

FIGURE 2:

Classification results of the T2D patient cohort. (A) Classification of all T2D patients based on the CKD273 score divided per centre. The scores of patients with macroalbuminuria or/and eGFR < 45 mL/min/1.73 m² (cases) are marked in gray and the scores of patients with normalbuminuria and eGFR > 60 mL/min/1.73 m² (controls) are marked in black. The diagnosis cut-off of 0.343 is also shown. The centre number is given on the x-axis (Table 1). (B) Combined ROC curve for the CKD273-based prediction of all T2D patients (n = 165, AUC = 0.95).

FIGURE 3:

Validation of the individual 273 CKD biomarkers in the T2D cohort. Verification of the CKD biomarkers using all data of T2D patients (n = 165). Number and names of 67 validated (P < 0.05) protein fragments of the 100 most significant CKD biomarkers are shown.