Urinary Peptidomic Signature for Noninvasive Diagnosis of Alport Syndrome in Children.
17 affiliations
- 1Department of Nephrology and Hypertension, Health Research Institute-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid, Madrid, Spain.
- 2Clinic of Nephrology and Rheumatology, University Medical Center Goettingen, Goettingen, Germany.
- 3Institut National de La Santé et De La Recherche Médicale (INSERM), UMR 1297, Institute of Metabolic and Cardiovascular Disease, Toulouse, France.
- 4University of Toulouse, Toulouse, France.
- 5Division of Pediatric Nephrology, Department of Pediatrics, Faculty of Medicine, Heidelberg University, Heidelberg, Germany.
- 6Kidney and Urinary Tract Center, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA.
- 7Division of Nephrology and Hypertension, Nationwide Children's Hospital, Columbus, Ohio, USA.
- 8Department of Pediatrics, Faculty of Medicine, University Hospital Cologne and University of Cologne, Cologne, Germany.
- 9Faculty of Applied Healthcare Science, Deggendorf Institute of Technology, Deggendorf, Germany.
- 10Department of Pediatrics, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.
- 11Mosaiques Diagnostics, Hannover, Germany.
- 12Institute for Molecular Cardiovascular Research (IMCAR), RWTH Aachen University Hospital, Aachen, Germany.
- 13Department of Pediatric Internal Medicine, Rheumatology and Nephrology, Toulouse University Hospital, Toulouse, France.
- 14Centre de Référence Des Maladies Rénales Rares du Sud-Ouest (SORARE), Toulouse University Hospital, Toulouse, France.
- 15RICORS2040-renal, Madrid, Spain.
- 16Departamento de Farmacología, Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain.
- 17Departamento de Medicina, Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain.
Abstract
Introduction
Early diagnosis of Alport syndrome (AS) in children remains challenging because early manifestations are nonspecific. Some clinically suspected cases remain genetically unresolved because no disease-causing variant has been identified or the variants identified are of uncertain significance. Urinary peptidomics is a promising noninvasive biomarker approach. We aimed to develop and validate a urinary peptidomic signature for pediatric AS.Methods
Urinary peptide profiles generated by capillary electrophoresis-mass spectrometry were analyzed in 282 urine samples from 57 children with AS (80.7% had X-linked disease, mean age was 10 ± 4 years, 4% were female, and mean estimated glomerular filtration rate [eGFR] was 128 ± 31 ml/min per 1.73 m²) enrolled in EARLY PRO-TECT trial, along with 651 samples from pediatric kidney disease cohorts and healthy controls. The data set was randomly divided into discovery (70%) and validation (30%) cohorts. Differential peptides identified by Wilcoxon testing with Benjamini-Hochberg adjustment were used to develop a support vector machine classifier. Performance was assessed by cross-validation and application to the validation cohort.Results
A total of 151 discriminatory peptides were identified. Sequence information was available for 87 peptides used for classifier generation; 60.9% were collagen-derived. In validation, the classifier achieved an area under the receiver operating characteristic curve (AUC) of 0.999 (95% confidence interval [CI], 0.997-1.000), with 100% sensitivity, 97.4% specificity, and 98.2% accuracy. After adjustment for age, sex, and eGFR, performance remained high (adjusted AUC, 0.918 [95% CI, 0.884-0.951]). Longitudinal analyses demonstrated stable classifier scores over up to 3 years.Conclusion
We developed and validated an accurate urinary peptidomic classifier for noninvasive diagnosis of pediatric AS. The signature may complement genetic testing and support earlier recognition of AS.
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BibTeX
@article{byrska2026urinary,
title = {{Urinary Peptidomic Signature for Noninvasive Diagnosis of Alport Syndrome in Children.}},
author = {Julia Byrska and Jan Boeckhaus and Kleanthi Voutsadaki and Benjamin Breuil and Eléonore Delecroix and Sheila Murunga and Bénédicte Buffin-Meyer and Brian Becknell and Daryl McLeod and Kathrin Burgmaier and Max C Liebau and Franz Schaefer and Justyna Siwy and Harald Mischak and Margarita Kondyli and Stéphane Decramer and Maria D Sanchez-Niño and Alberto Ortiz and Oliver Gross and Joost P Schanstra},
journal = {Kidney international reports},
year = {2026},
month = sep,
doi = {10.1016/j.ekir.2026.107093},
url = {https://europepmc.org/article/MED/42927079},
note = {CC BY},
}
RIS
TY - JOUR
TI - Urinary Peptidomic Signature for Noninvasive Diagnosis of Alport Syndrome in Children.
AU - Julia Byrska
AU - Jan Boeckhaus
AU - Kleanthi Voutsadaki
AU - Benjamin Breuil
AU - Eléonore Delecroix
AU - Sheila Murunga
AU - Bénédicte Buffin-Meyer
AU - Brian Becknell
AU - Daryl McLeod
AU - Kathrin Burgmaier
AU - Max C Liebau
AU - Franz Schaefer
AU - Justyna Siwy
AU - Harald Mischak
AU - Margarita Kondyli
AU - Stéphane Decramer
AU - Maria D Sanchez-Niño
AU - Alberto Ortiz
AU - Oliver Gross
AU - Joost P Schanstra
PY - 2026
DA - 2026/09/25
JO - Kidney international reports
DO - 10.1016/j.ekir.2026.107093
UR - https://europepmc.org/article/MED/42927079
AB - Introduction Early diagnosis of Alport syndrome (AS) in children remains challenging because early manifestations are nonspecific. Some clinically suspected cases remain genetically unresolved because no disease-causing variant has been identified or the variants identified are of uncertain significance. Urinary peptidomics is a promising noninvasive biomarker approach. We aimed to develop and validate a urinary peptidomic signature for pediatric AS.Methods Urinary peptide profiles generated by capillary electrophoresis-mass spectrometry were analyzed in 282 urine samples from 57 children with AS (80.7% had X-linked disease, mean age was 10 ± 4 years, 4% were female, and mean estimated glomerular filtration rate [eGFR] was 128 ± 31 ml/min per 1.73 m²) enrolled in EARLY PRO-TECT trial, along with 651 samples from pediatric kidney disease cohorts and healthy controls. The data set was randomly divided into discovery (70%) and validation (30%) cohorts. Differential peptides identified by Wilcoxon testing with Benjamini-Hochberg adjustment were used to develop a support vector machine classifier. Performance was assessed by cross-validation and application to the validation cohort.Results A total of 151 discriminatory peptides were identified. Sequence information was available for 87 peptides used for classifier generation; 60.9% were collagen-derived. In validation, the classifier achieved an area under the receiver operating characteristic curve (AUC) of 0.999 (95% confidence interval [CI], 0.997-1.000), with 100% sensitivity, 97.4% specificity, and 98.2% accuracy. After adjustment for age, sex, and eGFR, performance remained high (adjusted AUC, 0.918 [95% CI, 0.884-0.951]). Longitudinal analyses demonstrated stable classifier scores over up to 3 years.Conclusion We developed and validated an accurate urinary peptidomic classifier for noninvasive diagnosis of pediatric AS. The signature may complement genetic testing and support earlier recognition of AS.
SN - 2468-0249
ER -