Metabolomic Signatures and Machine Learning Models for Distinguishing Alzheimer's Disease and Dementia with Lewy Bodies
This study demonstrates the potential of metabolomic biomarkers in differentiating AD from DLB, with APOE improving classification accuracy for AD. Future efforts will focus on validating findings in larger cohorts and translating these findings into non-invasive, cost-effective tool set to reduce AD and DLB misdiagnosis.
Authors
- Guillaume Sacco (ORCID: https://orcid.org/0000-0002-6881-1649)
- Seval Kul (ORCID: https://orcid.org/0000-0002-4716-9554)
- Stéphanie Boutillier (ORCID: https://orcid.org/0009-0007-2325-6403)
- Dany Mukesha (ORCID: https://orcid.org/0009-0001-9514-751X)
- Hüseyin Firat
- Mélitine Dubray
- Maité Sarter
- Floris Durand
- Lucas Pham‐Van
Institutions
- Centre Hospitalier Universitaire de Nice (FR)
- Firalis (France) (FR)
- Cognition Behaviour Technology (FR)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_098539
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00