Neurogenic bladder poses a major morbidity in children with spina bifida (SB), and videourodynamic studies (VUDS) are used to stratify this risk. This small-scale pilot study utilized current mass-spectrometry-based proteomic approaches to identify peptides or proteins in urine that may differentiate children at high risk of developing renal complications from a neurogenic bladder. Twenty-two urine samples of which nine had high bladder pressure storage that put the upper urinary tract at risk, while 13 with a lower risk for renal compromise were analyzed. More than 1,900 peptides across all 22 samples were quantified, and 115 peptides differed significantly (P < 0.05) between the two groups. Using machine learning approaches five peptides that showed the greatest differences between these two clinical categories were used to build a classifier. We tested this classifier by blind analysis of an additional six urine samples and showed that it correctly assigned the unknown samples in their proper risk category. These promising results indicate that a urinary screening test based on peptides could be performed on a regular basis to stratify the neurogenic bladder into low or high-risk categories. Expanding this work to larger cohorts as well as across a broad spectrum of urodynamics outcomes may provide a useful diagnostic test for neurogenic bladder.NEW & NOTEWORTHY This approach could help risk stratify the neurogenic bladder in patients with spina bifida and could allow us to safely defer on up to 1/3 of urodynamic studies. These pilot data justify a larger trial before this approach becomes a clinical tool.
Keywords: peptidomics; risk; spina bifida; stratification; urodynamics.