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Lookup NU author(s): Professor John-Paul TaylorORCiD, Professor John O'Brien, Dr Michael FirbankORCiD, Emeritus Professor Alan Thomas, Dr Paul DonaghyORCiD, Shady Rahayel
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2026. Background: Dementia with Lewy bodies shares clinical and pathological features with both Parkinson’s disease and Alzheimer’s disease, but the local biological factors that render specific cortical regions vulnerable to atrophy remain poorly defined. In particular, it is unclear whether cortical thinning in dementia with Lewy bodies reflects generic neurodegenerative mechanisms, processes shared with Parkinson’s disease and Alzheimer’s disease, or dementia with Lewy bodies-specific molecular and network susceptibilities. Methods: A total of 89 patients with dementia with Lewy bodies and 89 matched controls underwent T1-weighted brain MRI. Scans were processed to generate surface-based cortical thickness maps. Regional cortical thickness estimates, after slice-by-slice manual correction, were mapped to gene expression data from healthy postmortem human brains to identify transcriptomic signatures associated with decreased thickness in dementia with Lewy bodies. We assessed whether genes whose expression was increased with regional thinning converged onto established Parkinson’s disease- and Alzheimer’s disease-related pathways and identified genes uniquely implicated in dementia with Lewy bodies. Spatial annotation mapping was then used to test whether patterns of cortical thinning overlapped with in vivo neurotransmitter system distributions and whether the observed thickness pattern was constrained by large-scale structural connectivity, consistent with a network-based propagation process. Results: Cortical thinning predominated in regions that, in the healthy brain, show higher expression of genes involved in mitochondrial function and synaptic transmission. The transcriptomic profile associated with thinning significantly overlapped with genes belonging to Parkinson’s disease and Alzheimer’s disease pathways, supporting shared pathogenic mechanisms across Lewy body- and Alzheimer-type neurodegeneration. However, 90 genes associated with cortical thinning did not overlap with Parkinson’s disease or Alzheimer’s disease pathways and were enriched for GABAergic signalling. Spatial mapping analyses showed that regions with greatest thickness reductions colocalized with GABAA, serotoninergic 5-HT1A, 5-HT1B, 5-HT4, and dopaminergic D2 receptor distributions, and that the thickness pattern followed structural connectivity. Conclusions: MRI-derived cortical thickness changes in dementia with Lewy bodies reflect selective molecular and network vulnerabilities rather than a non-specific degenerative process. Mitochondrial and synaptic genes, together with a distinct GABAergic association and connectivity constraints, delineate mechanisms explaining why some cortical territories are more affected in dementia with Lewy bodies.
Author(s): Delva A, Joza S, Tremblay C, Vo A, Filiatrault M, Carrier M, Taylor J-P, O'Brien JT, Firbank M, Thomas A, Donaghy PC, Camicioli R, Chertkow H, Dagher A, Postuma RB, Rahayel S
Publication type: Article
Publication status: Published
Journal: Journal of Biomedical Science
Year: 2026
Volume: 33
Online publication date: 10/06/2026
Acceptance date: 02/06/2026
Date deposited: 23/06/2026
ISSN (print): 1021-7770
ISSN (electronic): 1423-0127
Publisher: BioMed Central Ltd
URL: https://doi.org/10.1186/s12929-026-01267-6
DOI: 10.1186/s12929-026-01267-6
Data Access Statement: The dataset supporting the conclusions of this article were obtained from multiple sources. Access to the Newcastle cohort is governed by institutional policies and requires approval from the study investigators. For the CCNA dataset, qualified researchers may request access to COMPASS-ND data through the CCNA. Group-average parcellated maps for DLB and control participants can be shared upon reasonable request. All software tools used in the analyses are publicly available and referenced in the Methods section.
PubMed id: 42265698
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