Candidate urinary biomarker discovery in ureteropelvic junction obstruction: a proteomic approach

Hrair-George O Mesrobian1, Michael E Mitchell, William A See

  • 1Department of Urology, Medical College and Children's Hospital of Wisconsin, Milwaukee, Wisconsin, USA. hmesrobi@mcw.edu

Insights

Urinary proteome analysis reveals distinct protein differences in infants with ureteropelvic junction obstruction. This finding may aid in classifying disease severity and selecting candidates for early surgery.

Area of Science:

  • Biochemistry
  • Pediatric Nephrology
  • Proteomics

Background:

  • Ureteropelvic junction obstruction (UPJO) progression is variable, with natural history unfolding over years.
  • Urinary proteome analysis shows promise in differentiating UPJO from normal infants.
  • Current diagnostic and prognostic methods for UPJO require refinement.

Purpose of the Study:

  • To confirm findings on urinary proteome differences in UPJO using liquid chromatography/nano-spray mass spectrometry.
  • To examine the urinary proteome in infants with unilateral grade IV UPJO compared to healthy controls.
  • To identify potential urinary protein biomarkers for UPJO classification.

Main Methods:

  • Urine specimens collected from 21 healthy infants and 25 infants with grade IV unilateral UPJO.
  • Liquid chromatography/tandem mass spectrometry (LC-MS/MS) used for proteomic analysis.
  • Data normalization and annotation performed using the IPA knowledge platform.

Main Results:

  • Significant differences in protein abundance observed between UPJO infants and controls at 1-6 months (31 proteins) and 7-12 months (18 proteins).
  • Identified proteins clustered into major functional networks.
  • Previously reported UPJO biomarkers were detected, except for transforming growth factor-beta1.

Conclusions:

  • Confirms significant urinary proteome differences in unilateral UPJO compared to healthy infants.
  • Provides new data on specific protein and peptide abundance in UPJO.
  • Suggests potential for improved disease subgroup classification and early surgical candidate selection based on urinary biomarkers.
Abstract