A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis

TY - JOUR

T1 - A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis

AU - Coles, Nathan P.

AU - Elsheikh, Suzan

AU - Gouda, Alaa

AU - Quesnel, Agathe

AU - Butler, Lucy

AU - Achadu, Ojodomo J.

AU - Islam, Meez

AU - Kalesh, Karunakaran

AU - Occhipinti, Annalisa

AU - Angione, Claudio

AU - Marles-Wright, Jon

AU - Koss, David J.

AU - Thomas, Alan J.

AU - Outeiro, Tiago F.

AU - Filippou, Panagiota S.

AU - Khundakar, Ahmad A.

N1 - Publisher Copyright: © 2025 .

PY - 2026/1

Y1 - 2026/1

N2 - Background Lewy body dementias (LBD), comprising dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD), are defined by misfolded α-synuclein aggregation. Seed amplification assays (SAAs), such as RT-QuIC, enable sensitive detection of α-synuclein aggregates but typically provide binary readouts and require fluorescence labeling. Raman spectroscopy offers a label-free approach to detect subtle biochemical changes, and its diagnostic potential can be enhanced with machine learning. Objectives This proof-of-concept study aimed to evaluate whether Raman spectroscopy combined with machine learning can improve SAA-based discrimination of LBD from controls in cerebrospinal fluid (CSF). Methods We analyzed a small number of post-mortem CSF samples from pathologically confirmed DLB (n = 2), PDD (n = 2), and controls (n = 2) using a 7-day SAA. Raman spectra were collected on Days 1, 4, and 7 and analyzed using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP). Results Following SAA, both PCA and UMAP distinguished combined LBD samples from controls within 24 h (Day 1), reflecting biochemical changes consistent with α-synuclein fibrillation. Spectral shifts indicated decreased α-helical content with increased β-sheet structures. No consistent separation between DLB and PDD was observed. Conclusion This preliminary study demonstrates that combining Raman spectroscopy with machine learning can enable rapid, label-free detection of disease-specific changes. Despite the very limited sample size, these findings highlight the potential of this novel workflow and strongly warrant its validation in larger cohorts.

AB - Background Lewy body dementias (LBD), comprising dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD), are defined by misfolded α-synuclein aggregation. Seed amplification assays (SAAs), such as RT-QuIC, enable sensitive detection of α-synuclein aggregates but typically provide binary readouts and require fluorescence labeling. Raman spectroscopy offers a label-free approach to detect subtle biochemical changes, and its diagnostic potential can be enhanced with machine learning. Objectives This proof-of-concept study aimed to evaluate whether Raman spectroscopy combined with machine learning can improve SAA-based discrimination of LBD from controls in cerebrospinal fluid (CSF). Methods We analyzed a small number of post-mortem CSF samples from pathologically confirmed DLB (n = 2), PDD (n = 2), and controls (n = 2) using a 7-day SAA. Raman spectra were collected on Days 1, 4, and 7 and analyzed using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP). Results Following SAA, both PCA and UMAP distinguished combined LBD samples from controls within 24 h (Day 1), reflecting biochemical changes consistent with α-synuclein fibrillation. Spectral shifts indicated decreased α-helical content with increased β-sheet structures. No consistent separation between DLB and PDD was observed. Conclusion This preliminary study demonstrates that combining Raman spectroscopy with machine learning can enable rapid, label-free detection of disease-specific changes. Despite the very limited sample size, these findings highlight the potential of this novel workflow and strongly warrant its validation in larger cohorts.

KW - Diagnostics

KW - Lewy body dementia

KW - Machine learning analysis

KW - Raman spectroscopy

KW - α-synuclein aggregation

UR - https://www.scopus.com/pages/publications/105021931386

U2 - 10.1016/j.jneumeth.2025.110617

DO - 10.1016/j.jneumeth.2025.110617

M3 - Article

C2 - 41238048

AN - SCOPUS:105021931386

SN - 0165-0270

VL - 425

JO - Journal of Neuroscience Methods

JF - Journal of Neuroscience Methods

M1 - 110617

ER -