Evidence map›Paper›PMID 37831661›Full record

ArticleBrain : a journal of neurology2024

Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases.

Nick Corriveau-Lecavalier, Leland R Barnard, Hugo Botha, Jonathan Graff-Radford, Vijay K Ramanan, Jeyeon Lee, Ellen Dicks, Rosa Rademakers, Bradley F Boeve, Mary M Machulda and 8 more

Open access · hybridAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Atypical Presentations of Alzheimer Disease.Continuum (Minneapolis, Minn.) · 2024
    Review
  6. Article
  7. Article
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

18 authors at 3 institutions in 2 countries.

Nick Corriveau-LecavalierDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-6561-9870
Leland R BarnardDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
Hugo BothaDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0003-4390-685X
Jonathan Graff-RadfordDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0003-2770-0691
Vijay K RamananDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0001-6591-8734
Jeyeon LeeDepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-6168-8385
Ellen DicksDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
Rosa RademakersDepartment of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA.
Bradley F BoeveDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-4153-8187
Mary M MachuldaDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA.
Julie A FieldsDepartment of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA.
Dennis W DicksonDepartment of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA.ORCID 0000-0001-7189-7917
Neill Graff-RadfordDepartment of Neurology, Mayo Clinic, Jacksonville, FL 32224, USA.
David S KnopmanDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-6544-066X
Val J LoweDepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
Ronald C PetersenDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
Clifford R JackDepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0001-7916-622X
David T JonesDepartment of Neurology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-4807-9833
Mayo Clinic · USMayo Clinic in Florida · USVIB-UAntwerp Center for Molecular Neurology · BE

Funding

SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
THE PGRN/TDP-43 AXIS IN ALZHEIMER?S DISEASE AND NEURODEGENERATIONP50AG016574 · NIA · MAYO CLINIC ROCHESTER · PI PETERSEN, RONALD C · 1999 to 2018
$36.9M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI KEJAL KANTARCI · 2019 to 2026
$33.5M
Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkersR37AG011378 · NIA · MAYO CLINIC ROCHESTER · PI CLIFFORD R. JACK · 2018 to 2026
$6.8M
Validating the New Criteria for Preclinical Alzheimer's diseaseR01AG041851 · NIA · MAYO CLINIC ROCHESTER · PI JACK, CLIFFORD R., KNOPMAN, DAVID S · 2012 to 2021
$6.3M
NIA NIH HHS P30 AG062677NIA NIH HHS P50 AG016574NIA NIH HHS R01 AG041851NIA NIH HHS R37 AG011378NIA NIH HHS U01 AG006786NIH HHS P30 AG062677
6 · The paper itself

Abstract

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.

Indexed as

Alzheimer DiseaseFrontotemporal DementiaCerebral CortexExecutive FunctionFluorodeoxyglucose F18HumansNeuropsychological TestsFluorodeoxyglucose F18behavioural Alzheimer’s diseasebehavioural variant frontotemporal dementiadysexecutive Alzheimer’s diseaseFDG-PETmachine learning

Identifiers

PMID37831661
PMCPMC10994526
OpenAlexW4387612989

What Socratic 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 Socratic graph.