Longitudinal landscape of urinary EV proteome reveals stable protein expression patterns within and between individuals

Urinary extracellular vesicles (EVs) are an attractive source for the detection of disease biomarkers. Mass spectrometry (MS) based proteomics is increasingly used for urinary EV proteome profiling and protein biomarker discovery. However, little is known about the consistency and stability of urinary EV proteins within individuals over time and between different individuals. In this study we profiled the urinary EV proteome of 8 healthy individuals over 6 months at 9 timepoints (total 72 samples) using DIA-MS. We identified a total of 1802 proteins with high correlation amongst all samples. While a minor fraction (10%) of the total urinary EV proteome was shown to play a role in determining personal expression patterns, most of the urinary EV proteins was found to be stable with >90% of the proteins detected in more than 1 person at all timepoints. The variability of urinary EV proteome between different individuals was shown to be significantly higher than personal variation as a result of a small subset (<20%) of proteins. The core interaction network of proteins identified in all individuals revealed EV proteins involved in signaling and localization and sub-clusters enriched for glycolytic activity, protein synthesis, and immune function. Gender-specific expression patterns were detected in the urinary EV proteome, mostly related to hormonal and reproduction pathways. In summary, our findings indicate that the urinary EV proteome is stable in longitudinal samples of healthy subjects, underscoring its potential as a reliable source for protein biomarkers.