1. Modeling a biofluid-derived extracellular vesicle surface signature to differentiate pediatric idiopathic nephrotic syndrome clinical subgroups
- Author
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Giulia Cricri, Andrea Gobbini, Stefania Bruno, Linda Bellucci, Sarah Tassinari, Federico Caicci, Chiara Tamburello, Teresa Nittoli, Irene Paraboschi, Alfredo Berrettini, Renata Grifantini, Benedetta Bussolati, William Morello, Giovanni Montini, and Federica Collino
- Subjects
Idiopathic nephrotic syndrome ,Extracellular vesicles ,Protein biomarkers ,Steroid resistance ,Medicine ,Science - Abstract
Abstract Idiopathic Nephrotic Syndrome (INS) is a common childhood glomerular disease requiring intense immunosuppressive drug treatments. Prediction of treatment response and the occurrence of relapses remains challenging. Biofluid-derived extracellular vesicles (EVs) may serve as novel liquid biopsies for INS classification and monitoring. Our cohort was composed of 105 INS children at different clinical time points (onset, relapse, and persistent proteinuria, remission, respectively), and 19 healthy controls. The expression of 37 surface EV surface markers was evaluated by flow cytometry in serum (n = 83) and urine (n = 74) from INS children (mean age = 10.1, 58% males) at different time points. Urine EVs (n = 7) and serum EVs (n = 11) from age-matched healthy children (mean age = 7.8, 94% males) were also analyzed. Tetraspanin expression in urine EVs was enhanced during active disease phase in respect to the remission group and positively correlates with proteinuria levels. Unsupervised clustering analysis identified an INS signature of 8 markers related to immunity and angiogenesis/adhesion processes. The CD41b, CD29, and CD105 showed the best diagnostic scores separating the INS active phase from the healthy condition. Interestingly, combining urinary and serum EV markers from the same patient improved the precision of clinical staging separation. Three urinary biomarkers (CD19, CD44, and CD8) were able to classify INS based on steroid sensitivity. Biofluid EVs offer a non-invasive tool for INS clinical subclassification and “personalized” interventions.
- Published
- 2024
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