See the published version of this article at Alzheimer's Research and Therapy.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration
Michel Grothe
German Center for Neurodegenerative Diseases (DZNE)
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2600-9022
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Alzheimer's Research and Therapy.
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.
Keywords
Alzheimer’s disease, subtypes, mild cognitive impairment, prodromal, FDG-PET, hypometabolism
Figure 1
Figure 2
Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 2
Posted 26 Jan, 2021
Published
On 19 Feb, 2021
No community comments so far
Reviewer #2 agreed
On 02 Feb, 2021
Review #2 received
Received 02 Feb, 2021
Editorial decision: Accept
On 02 Feb, 2021
Reviewers invited
Invitations sent on 19 Jan, 2021
Reviewer #1 agreed
On 19 Jan, 2021
Review #1 received
Received 19 Jan, 2021
Editor assigned
On 18 Jan, 2021
Submission checks complete
On 18 Jan, 2021
Editor invited
On 18 Jan, 2021
No comments provided
Review #2 received
Received 22 Nov, 2020
Editorial decision: Major Revision
On 22 Nov, 2020
Review #1 received
Received 06 Nov, 2020
Reviewer #2 agreed
On 04 Nov, 2020
Reviewer #1 agreed
On 02 Nov, 2020
Reviewers invited
Invitations sent on 01 Nov, 2020
Editor assigned
On 31 Oct, 2020
Editor invited
On 31 Oct, 2020
Submission checks complete
On 30 Oct, 2020
First submitted
On 29 Oct, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
Learn more about our company.
This preprint is under consideration at Alzheimer's Research and Therapy. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Data-driven FDG-PET subtypes of Alzheimer’s disease-related neurodegeneration
Michel Grothe
German Center for Neurodegenerative Diseases (DZNE)
Corresponding Author
ORCiD: https://orcid.org/0000-0003-2600-9022
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 2
Posted 26 Jan, 2021
Published
On 19 Feb, 2021
No community comments so far
Reviewer #2 agreed
On 02 Feb, 2021
Review #2 received
Received 02 Feb, 2021
Editorial decision: Accept
On 02 Feb, 2021
Reviewers invited
Invitations sent on 19 Jan, 2021
Reviewer #1 agreed
On 19 Jan, 2021
Review #1 received
Received 19 Jan, 2021
Editor assigned
On 18 Jan, 2021
Submission checks complete
On 18 Jan, 2021
Editor invited
On 18 Jan, 2021
No comments provided
Review #2 received
Received 22 Nov, 2020
Editorial decision: Major Revision
On 22 Nov, 2020
Review #1 received
Received 06 Nov, 2020
Reviewer #2 agreed
On 04 Nov, 2020
Reviewer #1 agreed
On 02 Nov, 2020
Reviewers invited
Invitations sent on 01 Nov, 2020
Editor assigned
On 31 Oct, 2020
Editor invited
On 31 Oct, 2020
Submission checks complete
On 30 Oct, 2020
First submitted
On 29 Oct, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cognitive Neuroscience
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Alzheimer's Research and Therapy.
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