TY - JOUR
T1 - Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer’s disease
AU - Poulakis, Konstantinos
AU - Pereira, Joana B.
AU - Muehlboeck, J. Sebastian
AU - Wahlund, Lars Olof
AU - Smedby, Örjan
AU - Volpe, Giovanni
AU - Masters, Colin L.
AU - Ames, David
AU - Niimi, Yoshiki
AU - Iwatsubo, Takeshi
AU - Ferreira, Daniel
AU - Westman, Eric
AU - Japanese Alzheimer’s Disease Neuroimaging Initiative
AU - Australian Imaging, Biomarkers and Lifestyle study
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
U2 - 10.1038/s41467-022-32202-6
DO - 10.1038/s41467-022-32202-6
M3 - Article
C2 - 35931678
AN - SCOPUS:85135531088
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 4566
ER -