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

• Published in: Nature communications Vol. 13; no. 1; pp. 4566 - 15
• Main Authors: Poulakis, Konstantinos, Pereira, Joana B., Muehlboeck, J.-Sebastian, Wahlund, Lars-Olof, Smedby, Örjan, Volpe, Giovanni, Masters, Colin L., Ames, David, Niimi, Yoshiki, Iwatsubo, Takeshi, Ferreira, Daniel, Westman, Eric
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.08.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 692/53/2423; 692/617/375/132/1283; 692/699/375/132/1283; Alzheimer Disease - pathology; Alzheimer's disease; Atrophy; Atrophy - pathology; Bayes Theorem; Bayesian analysis; Brain - pathology; Clinical Medicine; Cluster Analysis; Clustering; Cognitive ability; Cognitive Dysfunction - pathology; Cross-Sectional Studies; Dementia disorders; Heterogeneity; Humanities and Social Sciences; Humans; Klinisk medicin; Longitudinal Studies; Magnetic Resonance Imaging; Medical and Health Sciences; Medical imaging; Medicin och hälsovetenskap; multidisciplinary; Neurodegenerative diseases; Neuroimaging; Neurologi; Neurology; Neurosciences; Neurovetenskaper; Risk analysis; Risk factors; Science; Science (multidisciplinary); Trajectory analysis; β-Amyloid
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-32202-6

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. Different types of atrophy in Alzheimer’s disease may reflect different disease stages or biologically distinct subtypes. Here the authors use longitudinal neuroimaging data to demonstrate five distinct patterns of atrophy with different demographical and cognitive characteristics.