MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies
Anna Inguanzo, Konstantinos Poulakis, Rosaleena Mohanty, Christopher G. Schwarz, Scott A. Przybelski, Patricia Diaz‐Galvan, Val J. Lowe, Bradley F. Boeve, Afina W. Lemstra, Marleen van de Beek, Wiesje M. van der Flier, Frederik Barkhof, Frederic Blanc, Paulo Loureiro de Sousa, Nathalie Philippi, Benjamin Cretin, Catherine Demuynck, Zuzana Nedelská, Jakub Hort, Bàrbara Segura, Carme Junqué, Ketil Oppedal, Dag Aarsland, Eric Westman, Kejal Kantarci, Daniel Ferreira
Abstract
Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) data to investigate DLB subtypes. We included 165 DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid, tau, and cerebrovascular biomarkers at baseline, and cognitive decline over three years. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n = 49, 30%); a subtype with low GM volumes in fronto-occipital regions (n = 76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n = 40, 24%). This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.