Evidence map›Paper›PMID 33608059›Full record

ArticleAlzheimer's research & therapy2021

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

Fedor Levin, Daniel Ferreira, Catharina Lange, Martin Dyrba, Eric Westman, Ralph Buchert, Stefan J Teipel, Michel J Grothe, Alzheimer’s Disease Neuroimaging Initiative

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
8.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 1 synthesis or guideline pooled it, 105 citations in OpenAlex.

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4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 4 countries.

Fedor LevinGerman Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany.
Daniel FerreiraDivision of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden.
Catharina LangeDepartment of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.
Martin DyrbaGerman Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany.
Eric WestmanDivision of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden.
Ralph BuchertDepartment of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Stefan J TeipelGerman Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany.
Michel J GrotheGerman Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Rostock, Germany. michel.grothe@dzne.de.ORCID http://orcid.org/0000-0003-2600-9022
Alzheimer’s Disease Neuroimaging Initiative
German Center for Neurodegenerative Diseases · DEKarolinska Institutet · SEUniversität Hamburg · DEWellcome Centre for Human Neuroimaging · GB

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

backgroundPrevious 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.

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.

Indexed as

Alzheimer DiseaseCognitive DysfunctionBrainFluorodeoxyglucose F18HumansMagnetic Resonance ImagingPositron-Emission TomographyFluorodeoxyglucose F18Alzheimer’s diseaseFDG-PETHypometabolismMild cognitive impairmentProdromalSubtypes

Identifiers

PMID33608059
PMCPMC7896407
OpenAlexW3129955977

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.