Characterization of a temporoparietal junction subtype of Alzheimer's disease

Meyer, François; Wehenkel, Marie; Phillips, Christophe; Geurts, Pierre; Hustinx, Roland; Bernard, Claire; Bastin, Christine; Salmon, Eric; Initiative, Alzheimer’s Disease Neuroimaging

doi:10.1002/hbm.24701

Cited by 6 publications

(4 citation statements)

References 40 publications

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“…FDG-PET may indicate a decrease in cerebral glucose metabolism that occurs prior to the macroscopic atrophy detectable with MRI, rendering the technique potentially more sensitive to early neurodegenerative processes [ 8 – 10 ]. While previous hypothesis-driven studies have also reported differential hypometabolic FDG-PET patterns amongst AD dementia patients [ 11 – 13 ], to our knowledge, FDG-PET has not yet been used for identifying neurodegeneration subtypes of AD in a data-driven manner. Given that detection of an “AD-typical” hypometabolism pattern by visual inspection of individual patients’ FDG-PET scans is commonly used for differential dementia diagnosis in research and clinical settings [ 7 , 12 , 14 – 16 ], a systematic evaluation of whether and how specific AD neurodegeneration subtypes are reflected in FDG-PET data can have important diagnostic implications.…”

Section: Introductionmentioning

confidence: 97%

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

et al. 2021

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Background Previous research has described distinct subtypes of Alzheimer’s disease (AD) based on the differences in regional patterns of brain atrophy on MRI. We conducted a data-driven exploration of distinct AD neurodegeneration subtypes using FDG-PET as a sensitive molecular imaging marker of neurodegenerative processes. Methods Hierarchical clustering of voxel-wise FDG-PET data from 177 amyloid-positive patients with AD dementia enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used to identify distinct hypometabolic subtypes of AD, which were then further characterized with respect to clinical and biomarker characteristics. We then classified FDG-PET scans of 217 amyloid-positive patients with mild cognitive impairment (“prodromal AD”) according to the identified subtypes and studied their domain-specific cognitive trajectories and progression to dementia over a follow-up interval of up to 72 months. Results Three main hypometabolic subtypes were identified: (i) “typical” (48.6%), showing a classic posterior temporo-parietal hypometabolic pattern; (ii) “limbic-predominant” (44.6%), characterized by old age and a memory-predominant cognitive profile; and (iii) a relatively rare “cortical-predominant” subtype (6.8%) characterized by younger age and more severe executive dysfunction. Subtypes classified in the prodromal AD sample demonstrated similar subtype characteristics as in the AD dementia sample and further showed differential courses of cognitive decline. Conclusions These findings complement recent research efforts on MRI-based identification of distinct AD atrophy subtypes and may provide a potentially more sensitive molecular imaging tool for early detection and characterization of AD-related neurodegeneration variants at prodromal disease stages.

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Section: Introductionmentioning

confidence: 97%

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

et al. 2021

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“…Interestingly, these cortical regions have an extended multi-decade duration of brain development, thus potentially being more vulnerable to negative effects, e.g., cocaine consumption, which begins in the first three decades (61). Another implication of these structural alterations, particularly in the temporoparietal junction, is their importance in neurodegenerative diseases (62,63). Further studies are needed to investigate the effects of CUD on aging and potential accelerated neurodegeneration.…”

Section: Discussionmentioning

confidence: 99%

Lower cortical thickness and increased brain aging in adults with cocaine use disorder

Schinz,

Schmitz-Koep,

Tahedl

et al. 2023

Front. Psychiatry

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BackgroundCocaine use disorder (CUD) is a global health issue with severe behavioral and cognitive sequelae. While previous evidence suggests a variety of structural and age-related brain changes in CUD, the impact on both, cortical thickness and brain age measures remains unclear.MethodsDerived from a publicly available data set (SUDMEX_CONN), 74 CUD patients and 62 matched healthy controls underwent brain MRI and behavioral-clinical assessment. We determined cortical thickness by surface-based morphometry using CAT12 and Brain Age Gap Estimate (BrainAGE) via relevance vector regression. Associations between structural brain changes and behavioral-clinical variables of patients with CUD were investigated by correlation analyses.ResultsWe found significantly lower cortical thickness in bilateral prefrontal cortices, posterior cingulate cortices, and the temporoparietal junction and significantly increased BrainAGE in patients with CUD [mean (SD) = 1.97 (±3.53)] compared to healthy controls (p < 0.001, Cohen’s d = 0.58). Increased BrainAGE was associated with longer cocaine abuse duration.ConclusionResults demonstrate structural brain abnormalities in CUD, particularly lower cortical thickness in association cortices and dose-dependent, increased brain age.

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“…While previous hypothesis-driven studies have also reported differential hypometabolic FDG-PET patterns among AD dementia patients (10,14,15), to our knowledge, FDG-PET has not yet been used for identifying neurodegeneration subtypes of AD in a data-driven manner.…”

Section: Introductionmentioning

confidence: 88%

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

Levin

Ferreira

Lange

et al. 2020

Preprint

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BackgroundPrevious research has described distinct subtypes of Alzheimer’s disease (AD) based on differences in regional patterns of brain atrophy on MRI. We conducted a data-driven exploration of distinct AD neurodegeneration subtypes using FDG-PET as a sensitive molecular imaging marker of neurodegenerative processes.MethodsHierarchical clustering of voxel-wise FDG-PET data from 177 amyloid-positive patients with AD dementia enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was used to identify distinct hypometabolic subtypes of AD, which were then further characterized with respect to clinical and biomarker characteristics. We then classified FDG-PET scans of 217 amyloid-positive patients with mild cognitive impairment (‘prodromal AD’) according to the identified subtypes and studied their domain-specific cognitive trajectories and progression to dementia over a follow-up interval of up to 72 months. ResultsThree main hypometabolic subtypes were identified: (i) “typical” (48.6%), showing a classic posterior temporo-parietal hypometabolic pattern, (ii) “limbic-predominant” (44.6%), characterized by old age and a memory-predominant cognitive profile, and (iii) a relatively rare “cortical-predominant” subtype (6.8%) characterized by younger age and more severe executive dysfunction. Subtypes classified in the prodromal AD sample demonstrated similar subtype characteristics as in the AD dementia sample and further showed differential courses of cognitive decline. ConclusionsThese findings complement recent research efforts on MRI-based identification of distinct AD atrophy subtypes and may provide a potentially more sensitive molecular imaging tool for early detection and characterization of AD-related neurodegeneration variants at prodromal disease stages.

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Characterization of a temporoparietal junction subtype of Alzheimer's disease

Cited by 6 publications

References 40 publications

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

Lower cortical thickness and increased brain aging in adults with cocaine use disorder

Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration

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