# A peripheral proteomic signature of Alzheimer’s disease is identified in the plasma extracellular vesicles of mild cognitive impairment patients from a memory clinic: the BIOPEXAL study

## TL;DR

This study identifies a proteomic signature in plasma extracellular vesicles that may help detect Alzheimer’s disease in early stages.

## Contribution

A novel peripheral proteomic signature in plasma extracellular vesicles is identified for early Alzheimer’s detection.

## Key findings

- pEVs proteome correlates with AD biomarkers like CSF Aβ42 and pTau181.
- Some pEVs proteins predict conversion from MCI to AD dementia.
- pEVs show strong correlations with brain atrophy measures in MRI.

## Abstract

Alzheimer’s disease (AD) is commonly diagnosed when neuronal damage is already established and irreversible. Achieving an accurate differential diagnosis in the preclinical and mild cognitive impairment (MCI) stage is one of the greatest challenges nowadays. Nanotechnological analysis of plasma extracellular vesicles (pEVs) are gaining attention as a promising tool for the early detection of AD pathology. This study aims to evaluate the proteomic profile of pEVs from patients with MCI and AD dementia to explore their potential as AD screening tools.

pEVs were isolated by ultracentrifugation from 144 patients with MCI A-T-, MCI A+T+, and AD dementia. Nanoparticle tracking analysis and cryo-TEM were used to characterize the pEVs. CSF, serum and pEVs proteomics were carried out by using the multiplex PEA technology of Olink® proteomics, Inflammation and Neurology Explore 384 panels (768 proteins).

Characterization results showed that isolated plasma fraction corresponded in shape, size and concentration to EVs. Many pEVs neurology proteins involved in AD pathology significantly correlated (r > ± 0.30, p < 0.05) with their CSF homonyms, but not with their serum’s. pEVs’ proteome correlated with common AD signatures (CSF Aβ42 and pTau181, plasma pTau181, MMSE, NBACE, and Qalb) showing similar patterns to those observed with CSF biomarkers. Several pEVs neurology proteins didn’t exhibit differences between the MCI A+T+ and AD dementia groups, whilst they did with MCI A-T-. Proteins in pEVs showed strong correlations with several measures of brain atrophy in MRI. Several neurology pEV proteins predicted conversion from MCI to AD dementia. Moreover, some of these showed a significant diagnostic accuracy of AD pathology.

Preliminary results suggest that EVs biomarker signature could reflect AD pathology in the prodromal stages of AD continuum. However, further experiments are still needed for a better understanding of EVs’ role in AD development and pathology dissemination.