Brain and circulating EV proteome signatures in schizophrenia as prognostic markers for age-related dementia

Abstract

Schizophrenia (SZ) is epidemiologically linked to an increased risk of developing age-related dementias (ARD) predominantly characterized by Alzheimer's disease and vascular dementia. However, the molecular mechanisms underlying this association remain insufficiently elucidated. Extracellular vesicles (EVs) play a critical role in neuropathological processes and offer a promising avenue for identifying shared disease mechanisms and potential circulating markers for patient stratification. Here we used a two-phase systems biology approach integrating discovery-driven proteomics with a targeted validation strategy using data-independent acquisition mass spectrometry (DIA-MS) in a large, independent SZ cohort. First, we analyzed brain-derived EVs (bEVs) from post-mortem SZ and ARD subjects to identify shared molecular signatures. Next, we validated the presence and circulation of these bEV markers in circulating plasma EVs (pEVs) using DIA-MS data. Remarkably, SZ and ARD bEV proteome and peptidome showed overlapping alterations in neuronal connectivity, synaptic integrity, neuroinflammation, and metabolism. Unsupervised clustering analysis of correlated bEV/pEV markers stratified SZ patients into two clusters: high dementia risk and control-like profiles. Collectively, these data emphasize the significance of bEVs as crucial mediators of shared neuropathogenic mechanisms in SZ, and ARD. Furthermore, we identified a set of pEVs markers, including proteins and specific peptides, with a robust and promising bench-to-bedside trajectory that may facilitate the stratification of SZ patients at risk for ARD.

The authors are pleased to acknowledge to Spanish Ministry of Science and Innovation, research project QUALISAFEJUICE PID-2019-106645RB-I00, for its financial support. I. Neggazi thanks the University of Lleida for its predoctoral grant (BOU204-220/2020 UdL) and the Serra Húnter contract awarded to Pilar Colás-Medà for supporting this work. This work also received support from the PT national funds (FCT/MECI, Fundação para a Ciência e Tecnologia and Ministério da Educação, Ciência e Inovação) through the project UID/50006 – Laboratório Associado para a Química Verde - Tecnologias e Processos Limpos. This study was also funded by the PRR – Plano de Recuperação e Resiliência and by the NextGenerationEU funds at Universidade de Aveiro, through the scope of the Agenda for Business Innovation “Plataforma de Valorização, Industrialização e Inovação comercial para o AgroAlimentar (VIIAFOOD)” (Project no. 37 AAC n.° 02/C05-i01/2022 with the application C644929456-00000040).