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.
Competing Interest Statement
L.H.P.P, C.F.C., K.T., and Y.C. are employees of WellSIM Biomedical Technologies, Inc., which may commercialize some of the technologies described in this work with pending patent applications.
Funding Statement
The authors acknowledge financial support from National Institutes of Health grants (1R41AG076098-01, 1R43AG080878-01, and 2R44GM144009-02). We also thank Knight ADRC of Washington University in St. Louis and their grants [Healthy Aging and Senile Dementia (P01 AG03991), Alzheimer Disease Research Center (P30 AG066444), Adult Children Study (P01 AG026276)]. We thank Indiana University for providing samples from the National Centralized Repository for Alzheimer Disease and Related Dementias (NCRAD), which receives government support under a cooperative agreement grant (U24 AG21886) awarded by the National Institute on Aging (NIA).
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
Ethics committee of WellSIM Biomedical Technologies, Inc. waived ethical approval for this work.
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Yes
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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
Yes
Data Availability
All data produced in the present study are available upon reasonable request to the authors