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ABSTRACT
Background and objectives
Chronic allograft nephropathy (CAN) is a major complication that occurs post-transplantation. At present, the diagnosis of CAN is based on renal biopsy. Therefore, there is an ultimate need to identify more specific and sensitive noninvasive methods for the early diagnosis of CAN. Recently, proteomic-based modalities have been developed to discover biomarkers of CAN.
Methods
Urine samples from 75 participants were collected. Participants were divided into three groups: Group I: 25 patients with CAN, Group II: 25 transplanted patients with stable renal functions, and Group III: 25 healthy control subjects matched for age and sex. Each group was divided into training set and test set. Specimens were purified with magnetic beads-based weak cation exchange chromatography and analyzed using MALDI-TOF MS.
Results
A Genetic Algorithm (GA) was used to set up the classification models. Five peaks represented the proteomic profile that differentiates between the CAN patients and the control group with sensitivity of 100%, specificity of 100%, recognition capability of 100%, and cross-validation of 91.7% and five peaks differentiate between the transplant patients with normal renal functions and the control groups with sensitivity of 96.8%, specificity of 95.5%, recognition capability of 98%, and cross-validation of 100%.
Interpretation and conclusions
We identified a pattern for CAN and transplant patients with normal renal functions by proteomic profiling using MALDI-TOF-MS and magnetic beads.
Disclosure statement
The authors declare that they have no conflicts of interest.