Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
05 08 2022
Historique:
received: 30 04 2021
accepted: 18 07 2022
entrez: 5 8 2022
pubmed: 6 8 2022
medline: 10 8 2022
Statut: epublish

Résumé

Understanding Alzheimer's disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity.

Identifiants

pubmed: 35931678
doi: 10.1038/s41467-022-32202-6
pii: 10.1038/s41467-022-32202-6
pmc: PMC9355993
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

4566

Subventions

Organisme : NIA NIH HHS
ID : U01 AG024904
Pays : United States
Organisme : CIHR
Pays : Canada

Informations de copyright

© 2022. The Author(s).

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Auteurs

Konstantinos Poulakis (K)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. konstantinos.poulakis@ki.se.

Joana B Pereira (JB)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmo, Sweden.

J-Sebastian Muehlboeck (JS)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.

Lars-Olof Wahlund (LO)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.

Örjan Smedby (Ö)

Department of Biomedical Engineering and Health Systems (MTH), KTH Royal Institute of Technology, Stockholm, Sweden.

Giovanni Volpe (G)

Department of Physics, University of Gothenburg, Gothenburg, Sweden.

Colin L Masters (CL)

The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Victoria, Australia.

David Ames (D)

Academic Unit for Psychiatry of Old Age, St George's Hospital, University of Melbourne, Melbourne, Victoria, Australia.
National Ageing Research Institute, Parkville, Victoria, Australia.

Yoshiki Niimi (Y)

Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan.

Takeshi Iwatsubo (T)

Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan.

Daniel Ferreira (D)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Department of Radiology, Mayo Clinic, Rochester, MN, USA.

Eric Westman (E)

Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

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Classifications MeSH