Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer’s disease
(2022) In Nature Communications 13(1).- Abstract
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... (More)
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.
(Less)
- author
- author collaboration
- organization
- publishing date
- 2022-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Communications
- volume
- 13
- issue
- 1
- article number
- 4566
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85135531088
- pmid:35931678
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-022-32202-6
- language
- English
- LU publication?
- yes
- id
- 9edb5923-9374-4b5d-9364-78916bd1c790
- date added to LUP
- 2022-11-29 14:41:58
- date last changed
- 2024-09-16 08:10:59
@article{9edb5923-9374-4b5d-9364-78916bd1c790, abstract = {{<p>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.</p>}}, author = {{Poulakis, Konstantinos and Pereira, Joana B. and Muehlboeck, J. Sebastian and Wahlund, Lars Olof and Smedby, Örjan and Volpe, Giovanni and Masters, Colin L. and Ames, David and Niimi, Yoshiki and Iwatsubo, Takeshi and Ferreira, Daniel and Westman, Eric}}, issn = {{2041-1723}}, language = {{eng}}, number = {{1}}, publisher = {{Nature Publishing Group}}, series = {{Nature Communications}}, title = {{Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer’s disease}}, url = {{http://dx.doi.org/10.1038/s41467-022-32202-6}}, doi = {{10.1038/s41467-022-32202-6}}, volume = {{13}}, year = {{2022}}, }