Maurizio Bruschi1, Simona Granata2, Laura Santucci1, Giovanni Candiano1, Antonia Fabris2, Nadia Antonucci2, Andrea Petretto3, Martina Bartolucci3, Genny Del Zotto4, Francesca Antonini4, Gian Marco Ghiggeri5, Antonio Lupo2, Giovanni Gambaro6, Gianluigi Zaza7. 1. Division of Nephrology, Dialysis, and Transplantation, Laboratory of Molecular Nephrology. 2. Renal Unit, Department of Medicine, University Hospital of Verona, Verona, Italy; and. 3. Laboratory of Mass Spectrometry-Core Facilities. 4. Department of Research and Diagnostics, and. 5. Division of Nephrology, Dialysis and Transplantation, Istituto di Ricovero e Cura a Carattere Scientifico, Istituto Giannina Gaslini, Genoa, Italy. 6. Division of Nephrology and Dialysis, School of Medicine, Columbus-Gemelli University Hospital Catholic University, Rome, Italy. 7. Renal Unit, Department of Medicine, University Hospital of Verona, Verona, Italy; and gianluigi.zaza@univr.it.
Abstract
BACKGROUND AND OBJECTIVES: Microvesicles and exosomes are involved in the pathogenesis of autosomal dominant polycystic kidney disease. However, it is unclear whether they also contribute to medullary sponge kidney, a sporadic kidney malformation featuring cysts, nephrocalcinosis, and recurrent kidney stones. We addressed this knowledge gap by comparative proteomic analysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The protein content of microvesicles and exosomes isolated from the urine of 15 patients with medullary sponge kidney and 15 patients with autosomal dominant polycystic kidney disease was determined by mass spectrometry followed by weighted gene coexpression network analysis, support vector machine learning, and partial least squares discriminant analysis to compare the profiles and select the most discriminative proteins. The proteomic data were verified by ELISA. RESULTS: A total of 2950 proteins were isolated from microvesicles and exosomes, including 1579 (54%) identified in all samples but only 178 (6%) and 88 (3%) specific for medullary sponge kidney microvesicles and exosomes, and 183 (6%) and 98 (3%) specific for autosomal dominant polycystic kidney disease microvesicles and exosomes, respectively. The weighted gene coexpression network analysis revealed ten modules comprising proteins with similar expression profiles. Support vector machine learning and partial least squares discriminant analysis identified 34 proteins that were highly discriminative between the diseases. Among these, CD133 was upregulated in exosomes from autosomal dominant polycystic kidney disease and validated by ELISA. CONCLUSIONS: Our data indicate a different proteomic profile of urinary microvesicles and exosomes in patients with medullary sponge kidney compared with patients with autosomal dominant polycystic kidney disease. The urine proteomic profile of patients with autosomal dominant polycystic kidney disease was enriched of proteins involved in cell proliferation and matrix remodeling. Instead, proteins identified in patients with medullary sponge kidney were associated with parenchymal calcium deposition/nephrolithiasis and systemic metabolic derangements associated with stones formation and bone mineralization defects. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2019_04_24_CJASNPodcast_19_06_.mp3.
BACKGROUND AND OBJECTIVES: Microvesicles and exosomes are involved in the pathogenesis of autosomal dominant polycystic kidney disease. However, it is unclear whether they also contribute to medullary sponge kidney, a sporadic kidney malformation featuring cysts, nephrocalcinosis, and recurrent kidney stones. We addressed this knowledge gap by comparative proteomic analysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The protein content of microvesicles and exosomes isolated from the urine of 15 patients with medullary sponge kidney and 15 patients with autosomal dominant polycystic kidney disease was determined by mass spectrometry followed by weighted gene coexpression network analysis, support vector machine learning, and partial least squares discriminant analysis to compare the profiles and select the most discriminative proteins. The proteomic data were verified by ELISA. RESULTS: A total of 2950 proteins were isolated from microvesicles and exosomes, including 1579 (54%) identified in all samples but only 178 (6%) and 88 (3%) specific for medullary sponge kidney microvesicles and exosomes, and 183 (6%) and 98 (3%) specific for autosomal dominant polycystic kidney disease microvesicles and exosomes, respectively. The weighted gene coexpression network analysis revealed ten modules comprising proteins with similar expression profiles. Support vector machine learning and partial least squares discriminant analysis identified 34 proteins that were highly discriminative between the diseases. Among these, CD133 was upregulated in exosomes from autosomal dominant polycystic kidney disease and validated by ELISA. CONCLUSIONS: Our data indicate a different proteomic profile of urinary microvesicles and exosomes in patients with medullary sponge kidney compared with patients with autosomal dominant polycystic kidney disease. The urine proteomic profile of patients with autosomal dominant polycystic kidney disease was enriched of proteins involved in cell proliferation and matrix remodeling. Instead, proteins identified in patients with medullary sponge kidney were associated with parenchymal calcium deposition/nephrolithiasis and systemic metabolic derangements associated with stones formation and bone mineralization defects. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2019_04_24_CJASNPodcast_19_06_.mp3.
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