Comprehensive strategy for identifying extracellular vesicle surface proteins as biomarkers for chronic kidney disease

Front Physiol. 2024 Feb 6:15:1328362. doi: 10.3389/fphys.2024.1328362. eCollection 2024.

Abstract

Chronic kidney disease (CKD) poses a significant health burden worldwide. Especially, obesity-induced chronic kidney disease (OCKD) is associated with a lack of accuracy in disease diagnostic methods. The identification of reliable biomarkers for the early diagnosis and monitoring of CKD and OCKD is crucial for improving patient outcomes. Extracellular vesicles (EVs) have emerged as potential biomarkers in the context of CKD. In this review, we focused on the role of EVs as potential biomarkers in CKD and OCKD and developed a comprehensive list of EV membrane proteins that could aid in the diagnosis and monitoring of the disease. To assemble our list, we employed a multi-step strategy. Initially, we conducted a thorough review of the literature on EV protein biomarkers in kidney diseases. Additionally, we explored papers investigating circulating proteins as biomarkers in kidney diseases. To further refine our list, we utilized the EV database Vesiclepedia.org to evaluate the qualifications of each identified protein. Furthermore, we consulted the Human Protein Atlas to assess the localization of these candidates, with a particular focus on membrane proteins. By integrating the information from the reviewed literature, Vesiclepedia.org, and the Human Protein Atlas, we compiled a comprehensive list of potential EV membrane protein biomarkers for CKD and OCKD. Overall, our review underscores the potential of EVs as biomarkers in the field of CKD research, providing a foundation for future studies aimed at improving CKD and OCKD diagnosis and treatment.

Keywords: biomarkers; chronic kidney disease; extracellular vesicles; obesity; surface proteins.

Publication types

  • Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the ResearchCube program 2022 for “NGDx—Next Generation Diagnostics” from Aalborg University Hospital. AH is supported by Project Grants in Clinical and Translational Medicine 2022 from the Novo Nordisk Foundation (NNF22OC0080036). CS is supported by the National Health and Medical Research Council, Australia, NHMRC 1195451.