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Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer’s disease
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2022 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 13, no 1, article id 4566Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Nature , 2022. Vol. 13, no 1, article id 4566
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Medical and Health Sciences
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URN: urn:nbn:se:kth:diva-316838DOI: 10.1038/s41467-022-32202-6ISI: 000836609800002PubMedID: 35931678Scopus ID: 2-s2.0-85135531088OAI: oai:DiVA.org:kth-316838DiVA, id: diva2:1692500
Note

Correction in DOI 10.1038/s41467-024-50044-2

QC 20221005

Available from: 2022-09-02 Created: 2022-09-02 Last updated: 2024-07-24Bibliographically approved

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Smedby, Örjan

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