Article: Assess Alzheimer's Disease via Plasma Extracellular Vesicle-derived mRNA.
medRxiv : the preprint server for health sciences
2023
Abstract: Alzheimer's disease (AD), the most prevalent neurodegenerative disorder globally, has emerged as a significant health concern, particularly due to the increasing aging population. Recently, it has been revealed that extracellular vesicles (EVs) ... ...
Abstract | Alzheimer's disease (AD), the most prevalent neurodegenerative disorder globally, has emerged as a significant health concern, particularly due to the increasing aging population. Recently, it has been revealed that extracellular vesicles (EVs) originating from neurons play a critical role in AD pathogenesis and progression. These neuronal EVs can cross the blood-brain barrier and enter peripheral circulation, offering a less invasive means for assessing blood-based AD biomarkers. In this study, we analyzed plasma EV-derived messenger RNA (mRNA) from 82 subjects, including individuals with AD, mild cognitive impairment (MCI), and healthy controls, using next-generation sequencing (NGS) to profile their gene expression for functional enrichment and pathway analysis. Based on the differentially expressed genes identified in both MCI and AD groups, we established a diagnostic model by implementing a machine learning classifier. The refined model demonstrated an average diagnostic accuracy over 98% and showed a strong correlation with different AD stages, suggesting the potential of plasma EV-derived mRNA as a promising non-invasive biomarker for early detection and ongoing monitoring of AD. |
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Language | English |
Publishing date | 2023-12-26 |
Publishing country | United States |
Document type | Preprint |
DOI | 10.1101/2023.12.26.23299985 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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