BACKGROUND: Synucleinopathies include a spectrum of disorders varying in features and severity, including idiopathic/isolated REM sleep behaviour disorder (iRBD), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Distinct brain atrophy patterns may already be seen in iRBD; however, how brain atrophy begins and progresses remains unclear. METHODS: A multicentric cohort of 1276 participants (451 polysomnography-confirmed iRBD, 142 PD with probable RBD, 87 DLB, and 596 controls) underwent T1-weighted MRI and longitudinal clinical assessments. Brain atrophy was quantified using vertex-based cortical surface reconstruction and volumetric segmentation. The unsupervised machine learning algorithm, Subtype and Stage Inference (SuStaIn), was used to reconstruct spatiotemporal patterns of brain atrophy progression. FINDINGS: SuStaIn identified two distinct subtypes of brain atrophy progression: 1) a "cortical-first" subtype, with atrophy beginning in the frontal lobes and involving the subcortical structures at later stages; and 2) a "subcortical-first" subtype, with atrophy beginning in the limbic areas and involving cortical structures at later stages. Both cortical- and subcortical-first subtypes were associated with a higher rate of increase in MDS-UPDRS-III scores over time, but cognitive decline was subtype-specific, being associated with advancing stages in patients classified as cortical-first but not subcortical-first. Classified patients were more likely to phenoconvert over time compared to stage 0/non-classified patients. Among the 88 patients with iRBD who phenoconverted during follow-up, those classified within the cortical-first subtype had a significantly increased likelihood of developing DLB compared to PD, unlike those classified within the subcortical-first subtype. INTERPRETATION: There are two distinct atrophy progression subtypes in iRBD, with the cortical-first subtype linked to an increased likelihood of developing DLB, while both subtypes were associated with worsening parkinsonian motor features. This underscores the potential utility of subtype identification and staging for monitoring disease progression and patient selection for trials. FUNDING: This study was supported by grants to S.R. from Alzheimer Society Canada (0000000082) and by Parkinson Canada (PPG-2023-0000000122). The work performed in Montreal was supported by the Canadian Institutes of Health Research (CIHR), the Fonds de recherche du Québec - Santé (FRQS), and the W. Garfield Weston Foundation. The work performed in Oxford was funded by Parkinson's UK (J-2101) and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). The work performed in Prague was funded by the Czech Health Research Council (grant NU21-04-00535) and by The National Institute for Neurological Research (project number LX22NPO5107), financed by the European Union - Next Generation EU. The work performed in Newcastle was funded by the NIHR Newcastle BRC based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. The work performed in Paris was funded by grants from the Programme d'investissements d'avenir (ANR-10-IAIHU-06), the Paris Institute of Neurosciences - IHU (IAIHU-06), the Agence Nationale de la Recherche (ANR-11-INBS-0006), Électricité de France (Fondation d'Entreprise EDF), the EU Joint Programme-Neurodegenerative Disease Research (JPND) for the Control-PD Project (Cognitive Propagation in Prodromal Parkinson's disease), the Fondation Thérèse et René Planiol, the Fonds Saint-Michel; by unrestricted support for research on Parkinson's disease from Energipole (M. Mallart) and the Société Française de Médecine Esthétique (M. Legrand); and by a grant from the Institut de France to Isabelle Arnulf (for the ALICE Study). The work performed in Sydney was supported by a Dementia Team Grant from the National Health and Medical Research Council (#1095127). The work performed in Cologne was funded by the Else Kröner-Fresenius-Stiftung (grant number 2019_EKES.02), the Köln Fortune Program, Faculty of Medicine, University of Cologne, and the "Netzwerke 2021 Program (Ministry of Culture and Science of Northrhine Westphalia State). The work performed in Aarhus was supported by funding from the Lundbeck Foundation, Parkinsonforeningen (The Danish Parkinson Association), and the Jascha Foundation.

• Keywords
• Dementia with Lewy bodies, MRI, Machine learning, Parkinson's disease, REM sleep behaviour disorder, Subtyping,
• MeSH
• Atrophy MeSH
• Lewy Body Disease pathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Brain * pathology   diagnostic imaging   MeSH
• Parkinson Disease pathology   MeSH
• REM Sleep Behavior Disorder * pathology   etiology   diagnosis   diagnostic imaging   MeSH
• Disease Progression MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH

Co-pathologies are common in dementia with Lewy bodies and other dementia disorders. We investigated cerebrovascular and Alzheimer's disease co-pathologies in patients with dementia with Lewy bodies in comparison with patients with mild cognitive impairment, Alzheimer's disease, mixed dementia, vascular dementia or Parkinson's disease with dementia and cognitively unimpaired participants. We assessed the association of biomarkers of cerebrovascular and Alzheimer's disease co-pathologies with medial temporal atrophy and global cognitive performance. Additionally, we evaluated whether the findings were specific to dementia with Lewy bodies. We gathered a multi-cohort dataset of 4549 participants (dementia with Lewy bodies = 331, cognitively unimpaired = 1505, mild cognitive impairment = 1489, Alzheimer's disease = 708, mixed dementia = 268, vascular dementia = 148, Parkinson's disease with dementia = 120) from the MemClin Study, Karolinska Imaging in Dementia Study, Gothenburg H70 Birth Cohort Studies and the European DLB Consortium. Cerebrovascular co-pathology was assessed with visual ratings of white matter hyperintensities using the Fazekas scale through structural imaging. Alzheimer's disease biomarkers of β-amyloid and phosphorylated tau were assessed in the cerebrospinal fluid for a subsample (N = 2191). Medial temporal atrophy was assessed with visual ratings and global cognition with the mini-mental state examination. Differences and associations were assessed through regression models, including interaction terms. In dementia with Lewy bodies, 43% had a high white matter hyperintensity load, which was significantly higher than that in cognitively unimpaired (14%), mild cognitive impairment (26%) and Alzheimer's disease (27%), but lower than that in vascular dementia (62%). In dementia with Lewy bodies, white matter hyperintensities were associated with medial temporal atrophy, and the interaction term showed that this association was stronger than that in cognitively unimpaired and mixed dementia. However, the association between white matter hyperintensities and medial temporal atrophy was non-significant when β-amyloid was included in the model. Instead, β-amyloid predicted medial temporal atrophy in dementia with Lewy bodies, in contrast to the findings in mild cognitive impairment where medial temporal atrophy scores were independent of β-amyloid. Dementia with Lewy bodies had the lowest performance on global cognition, but this was not associated with white matter hyperintensities. In Alzheimer's disease, global cognitive performance was lower in patients with more white matter hyperintensities. We conclude that white matter hyperintensities are common in dementia with Lewy bodies and are associated with more atrophy in medial temporal lobes, but this association depended on β-amyloid-related pathology in our cohort. The associations between biomarkers were overall stronger in dementia with Lewy bodies than in some of the other diagnostic groups.

• Keywords
• atrophy, imaging, multi-cohort, naturalistic cohort,
• Publication type
• Journal Article MeSH

Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) data to investigate DLB subtypes. We included 165 DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid, tau, and cerebrovascular biomarkers at baseline, and cognitive decline over three years. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n = 49, 30%); a subtype with low GM volumes in fronto-occipital regions (n = 76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n = 40, 24%). This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.

• Publication type
• Journal Article MeSH

Mild cognitive impairment with the core clinical features of dementia with Lewy bodies is recognized as a prodromal stage of dementia with Lewy bodies. Although grey matter atrophy has been demonstrated in prodromal dementia with Lewy bodies, longitudinal rates of atrophy during progression to probable dementia with Lewy bodies are unknown. We investigated the regional patterns of cross-sectional and longitudinal rates of grey matter atrophy in prodromal dementia with Lewy bodies, including those who progressed to probable dementia with Lewy bodies. Patients with mild cognitive impairment with at least one core clinical feature of dementia with Lewy bodies (mean age = 70.5; 95% male), who were enrolled in the Mayo Clinic Alzheimer's Disease Research Center and followed for at least two clinical evaluations and MRI examinations, were included (n = 56). A cognitively unimpaired control group (n = 112) was matched 2:1 to the patients with mild cognitive impairment by age and sex. Patients either remained stable (n = 28) or progressed to probable dementia with Lewy bodies (n = 28) during a similar follow-up period and pathologic confirmation was available in a subset of cases (n = 18). Cross-sectional and longitudinal rates of grey matter atrophy were assessed using voxel-based and atlas-based region of interest analyses. At baseline, prodromal dementia with Lewy bodies was characterized by atrophy in the nucleus basalis of Meynert both in those who remained stable and those who progressed to probable dementia with Lewy bodies (P < 0.05 false discovery rate corrected). Increase in longitudinal grey matter atrophy rates were widespread, with greatest rates of atrophy observed in the enthorhinal and parahippocampal cortices, temporoparietal association cortices, thalamus and the basal ganglia, in mild cognitive impairment patients who progressed to probable dementia with Lewy bodies at follow-up (P < 0.05 false discovery rate corrected). Rates of inferior temporal atrophy were associated with greater rates of worsening on the clinical dementia rating-sum of boxes. Seventeen of the 18 (94%) autopsied cases had Lewy body disease. Results show that atrophy in the nucleus basalis of Meynert is a feature of prodromal dementia with Lewy bodies regardless of proximity to progression to probable dementia with Lewy bodies. Longitudinally, grey matter atrophy progresses in regions with significant cholinergic innervation, in alignment with clinical disease progression, with widespread and accelerated rates of atrophy in patients who progress to probable dementia with Lewy bodies. Given the prominent neurodegeneration in the cholinergic system, patients with prodromal dementia with Lewy bodies may be candidates for cholinesterase inhibitor treatment.

• Keywords
• MRI, atrophy, dementia with Lewy bodies, mild cognitive impairment, prodromal DLB,
• Publication type
• Journal Article MeSH

We investigated whether cerebrovascular disease contributes to neurodegeneration and clinical phenotype in dementia with Lewy bodies (DLB). Regional cortical thickness and subcortical gray matter volumes were estimated from structural magnetic resonance imaging (MRI) in 165 DLB patients. Cortical and subcortical infarcts were recorded and white matter hyperintensities (WMHs) were assessed. Subcortical only infarcts were more frequent (13.3%) than cortical only infarcts (3.1%) or both subcortical and cortical infarcts (2.4%). Infarcts, irrespective of type, were associated with WMHs. A higher WMH volume was associated with thinner orbitofrontal, retrosplenial, and posterior cingulate cortices, smaller thalamus and pallidum, and larger caudate volume. A higher WMH volume was associated with the presence of visual hallucinations and lower global cognitive performance, and tended to be associated with the absence of probable rapid eye movement sleep behavior disorder. Presence of infarcts was associated with the absence of parkinsonism. We conclude that cerebrovascular disease is associated with gray matter neurodegeneration in patients with probable DLB, which may have implications for the multifactorial treatment of probable DLB.

• Keywords
• Cerebrovascular disease, Dementia with Lewy bodies (DLB), Magnetic resonance imaging, Neurodegeneration, White matter hyperintensities, infarcts,
• MeSH
• White Matter diagnostic imaging   pathology   MeSH
• Cerebrovascular Disorders complications   MeSH
• Nerve Degeneration etiology   MeSH
• Lewy Body Disease diagnostic imaging   etiology   pathology   psychology   MeSH
• Hallucinations MeSH
• Cognition MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Cerebral Cortex blood supply   diagnostic imaging   pathology   MeSH
• Brain Infarction diagnostic imaging   pathology   MeSH
• REM Sleep Behavior Disorder etiology   MeSH
• Gray Matter diagnostic imaging   pathology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

BACKGROUND: Alzheimer's disease (AD)-related pathology is frequently found in patients with dementia with Lewy bodies (DLB). However, it is unknown how amyloid-β and tau-related pathologies influence neurodegeneration in DLB. Understanding the mechanisms underlying brain atrophy in DLB can improve our knowledge about disease progression, differential diagnosis, drug development and testing of anti-amyloid and anti-tau therapies in DLB. OBJECTIVES: We aimed at investigating the combined effect of CSF amyloid-β42, phosphorylated tau and total tau on regional brain atrophy in DLB in the European DLB (E-DLB) cohort. METHODS: 86 probable DLB patients from the E-DLB cohort with CSF and MRI data were included. Random forest was used to analyze the association of CSF biomarkers (predictors) with visual rating scales for medial temporal lobe atrophy (MTA), posterior atrophy (PA) and global cortical atrophy scale-frontal subscale (GCA-F) (outcomes), including age, sex, education and disease duration as extra predictors. RESULTS: DLB patients with abnormal MTA scores had abnormal CSF Aβ42, shorter disease duration and older age. DLB patients with abnormal PA scores had abnormal levels of CSF Aβ42 and p-tau, older age, lower education and shorter disease duration. Abnormal GCA-F scores were associated with lower education, male sex, and older age, but not with any AD-related CSF biomarker. CONCLUSIONS: This study shows preliminary data on the potential combined effect of amyloid-β and tau-related pathologies on the integrity of posterior brain cortices in DLB patients, whereas only amyloid-β seems to be related to MTA. Future availability of α-synuclein biomarkers will help us to understand the effect of α-synuclein and AD-related pathologies on brain integrity in DLB.

• Keywords
• Alzheimer disease, Atrophy, Biomarkers, Lewy body disease, Neuroimaging,
• MeSH
• Alzheimer Disease * diagnostic imaging   MeSH
• Amyloid beta-Peptides MeSH
• Atrophy MeSH
• Biomarkers MeSH
• Lewy Body Disease * diagnostic imaging   MeSH
• Humans MeSH
• Brain diagnostic imaging   MeSH
• Peptide Fragments MeSH
• tau Proteins MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Amyloid beta-Peptides MeSH
• Biomarkers MeSH
• Peptide Fragments MeSH
• tau Proteins MeSH

PURPOSE OF REVIEW: We summarize structural (s)MRI findings of gray matter (GM) atrophy related to cognitive impairment in Alzheimer's disease (AD) and Parkinson's disease (PD) in light of new analytical approaches and recent longitudinal studies results. RECENT FINDINGS: The hippocampus-to-cortex ratio seems to be the best sMRI biomarker to discriminate between various AD subtypes, following the spatial distribution of tau pathology, and predict rate of cognitive decline. PD is clinically far more variable than AD, with heterogeneous underlying brain pathology. Novel multivariate approaches have been used to describe patterns of early subcortical and cortical changes that relate to more malignant courses of PD. New emerging analytical approaches that combine structural MRI data with clinical and other biomarker outcomes hold promise for detecting specific GM changes in the early stages of PD and preclinical AD that may predict mild cognitive impairment and dementia conversion.

• Keywords
• Alzheimer’s disease, Cognition, Gray matter atrophy, Parkinson’s disease, Structural magnetic resonance imaging,
• MeSH
• Alzheimer Disease pathology   psychology   MeSH
• Biomarkers MeSH
• Cognition * MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Brain pathology   MeSH
• Parkinson Disease pathology   psychology   MeSH
• Gray Matter pathology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• Biomarkers MeSH

Many patients with dementia with Lewy bodies (DLB) have overlapping Alzheimer's disease (AD)-related pathology, which may contribute to white matter (WM) diffusivity alterations on diffusion tensor imaging (DTI). Consecutive patients with DLB (n = 30), age- and sex-matched AD patients (n = 30), and cognitively normal controls (n = 60) were recruited. All subjects underwent DTI, 18F 2-fluoro-deoxy-d-glucose, and (11)C Pittsburgh compound B positron emission tomography scans. DLB patients had reduced fractional anisotropy (FA) in the parietooccipital WM but not elsewhere compared with cognitively normal controls, and elevated FA in parahippocampal WM compared with AD patients, which persisted after controlling for β-amyloid load in DLB. The pattern of WM FA alterations on DTI was consistent with the more diffuse posterior parietal and occipital glucose hypometabolism of 2-fluoro-deoxy-d-glucose positron emission tomography in the cortex. DLB is characterized by a loss of parietooccipital WM integrity, independent of concomitant AD-related β-amyloid load. Cortical glucose hypometabolism accompanies WM FA alterations with a concordant pattern of gray and WM involvement in the parietooccipital lobes in DLB.

• Keywords
• Amyloid-beta load, Cortical hypometabolism, Dementia with Lewy bodies, Diffusion tensor imaging, Voxel-based analysis, White matter integrity,
• MeSH
• Amyloid beta-Peptides metabolism   MeSH
• Anisotropy MeSH
• White Matter pathology   MeSH
• Lewy Body Disease diagnostic imaging   metabolism   pathology   MeSH
• Glucose metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Positron-Emission Tomography MeSH
• Aged MeSH
• Occipital Lobe metabolism   MeSH
• Diffusion Tensor Imaging methods   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Amyloid beta-Peptides MeSH
• Glucose MeSH