Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration
Background
Previous 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.
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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Posted 26 Jan, 2021
On 19 Feb, 2021
On 02 Feb, 2021
Received 02 Feb, 2021
On 02 Feb, 2021
Invitations sent on 19 Jan, 2021
On 19 Jan, 2021
Received 19 Jan, 2021
On 18 Jan, 2021
On 18 Jan, 2021
On 18 Jan, 2021
Received 22 Nov, 2020
On 22 Nov, 2020
Received 06 Nov, 2020
On 04 Nov, 2020
On 02 Nov, 2020
Invitations sent on 01 Nov, 2020
On 31 Oct, 2020
On 31 Oct, 2020
On 30 Oct, 2020
On 29 Oct, 2020
Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration
Posted 26 Jan, 2021
On 19 Feb, 2021
On 02 Feb, 2021
Received 02 Feb, 2021
On 02 Feb, 2021
Invitations sent on 19 Jan, 2021
On 19 Jan, 2021
Received 19 Jan, 2021
On 18 Jan, 2021
On 18 Jan, 2021
On 18 Jan, 2021
Received 22 Nov, 2020
On 22 Nov, 2020
Received 06 Nov, 2020
On 04 Nov, 2020
On 02 Nov, 2020
Invitations sent on 01 Nov, 2020
On 31 Oct, 2020
On 31 Oct, 2020
On 30 Oct, 2020
On 29 Oct, 2020
Background
Previous 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.
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.
Figure 1
Figure 2
Figure 3
Figure 4