ArticleInternational journal of molecular sciences2019
Proteomic Analysis of Urinary Extracellular Vesicles Reveals a Role for the Complement System in Medullary Sponge Kidney Disease.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Porous perspectives: a comprehensive review of medullary sponge kidney.International urology and nephrology · 2025Review
- Detection and Isolation of Tissue-Specific Extracellular Vesicles From the Blood.Journal of extracellular biology · 2025Review
- Article
- Urinary extracellular vesicles in childhood kidney diseases.Pediatric nephrology (Berlin, Germany) · 2024Review
- Effect of urine alkalization on urinary inflammatory markers in cystinuric patients.Clinical kidney journal · 2024Article
- Extracellular Vesicles as Source of Biomarkers in Glomerulonephritis.International journal of molecular sciences · 2023Review
- Proteomic Approaches and Potential Applications in Autosomal Dominant Polycystic Kidney Disease and Fabry Disease.Diagnostics (Basel, Switzerland) · 2023Review
- Exosomal proteomics in kidney disease: From technical approaches to clinical applications.Journal of food and drug analysis · 2022Review
- A Comprehensive Proteomics Analysis of Urinary Extracellular Vesicles Identifies a Specific Kinase Protein Profile as a Novel Hallmark of Medullary Sponge Kidney Disease.Kidney international reports · 2022Article
- Sphingomyelin and Medullary Sponge Kidney Disease: A Biological Link Identified by Omics Approach.Frontiers in medicine · 2021Article
- Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment.Medicina (Kaunas, Lithuania) · 2020Review
- Editorial of Special Issue "Rare Kidney Diseases: New Translational Research Approach to Improve Diagnosis and Therapy".International journal of molecular sciences · 2020Article
- Exosomes in Nephropathies: A Rich Source of Novel Biomarkers.Disease markers · 2020Review
- Computational advances of tumor marker selection and sample classification in cancer proteomics.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medullary sponge kidney (MSK) disease is a rare and neglected kidney condition often associated with nephrocalcinosis/nephrolithiasis and cystic anomalies in the precalyceal ducts. Little is known about the pathogenesis of this disease, so we addressed the knowledge gap using a proteomics approach. The protein content of microvesicles/exosomes isolated from urine of 15 MSK and 15 idiopathic calcium nephrolithiasis (ICN) patients was investigated by mass spectrometry, followed by weighted gene coexpression network analysis, support vector machine (SVM) learning, and partial least squares discriminant analysis (PLS-DA) to select the most discriminative proteins. Proteomic data were verified by ELISA. We identified 2998 proteins in total, 1764 (58.9%) of which were present in both vesicle types in both diseases. Among the MSK samples, only 65 (2.2%) and 137 (4.6%) proteins were exclusively found in the microvesicles and exosomes, respectively. Similarly, among the ICN samples, only 75 (2.5%) and 94 (3.1%) proteins were exclusively found in the microvesicles and exosomes, respectively. SVM learning and PLS-DA revealed a core panel of 20 proteins that distinguished extracellular vesicles representing each clinical condition with an accuracy of 100%. Among them, three exosome proteins involved in the lectin complement pathway maximized the discrimination between MSK and ICN: Ficolin 1, Mannan-binding lectin serine protease 2, and Complement component 4-binding protein β. ELISA confirmed the proteomic results. Our data show that the complement pathway is involved in the MSK, revealing a new range of potential therapeutic targets and early diagnostic biomarkers.
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