Heterogeneous patterns of brain atrophy in Alzheimer's disease

TY - JOUR

T1 - Heterogeneous patterns of brain atrophy in Alzheimer's disease

AU - Poulakis, Konstantinos

AU - Pereira, Joana B.

AU - Mecocci, Patricia

AU - Vellas, Bruno

AU - Tsolaki, Magda

AU - Kłoszewska, Iwona

AU - Soininen, Hilkka

AU - Lovestone, Simon

AU - Simmons, Andrew

AU - Wahlund, Lars-Olof

AU - Westman, Eric

PY - 2018/1/31

Y1 - 2018/1/31

N2 - There is increasing evidence showing that brain atrophy varies between patients with Alzheimer's disease (AD), suggesting that different anatomical patterns might exist within the same disorder. We investigated AD heterogeneity based on cortical and subcortical atrophy patterns in 299 AD subjects from 2 multicenter cohorts. Clusters of patients and important discriminative features were determined using random forest pairwise similarity, multidimensional scaling and distance-based hierarchical clustering. We discovered 2 typical (72.2%) and 3 atypical (28.8%) subtypes with significantly different demographic, clinical and cognitive characteristics, and different rates of cognitive decline. In contrast to previous studies, our unsupervised random forest approach based on cortical and subcortical volume measures and their linear and non-linear interactions, revealed more typical AD subtypes with important anatomically discriminative features, while the prevalence of atypical cases was lower. The hippocampal-sparing and typical AD subtypes, exhibited worse clinical progression in visuospatial, memory and executive cognitive functions. Our findings suggest there is substantial heterogeneity in AD that has an impact on how patients function and progress over time.

AB - There is increasing evidence showing that brain atrophy varies between patients with Alzheimer's disease (AD), suggesting that different anatomical patterns might exist within the same disorder. We investigated AD heterogeneity based on cortical and subcortical atrophy patterns in 299 AD subjects from 2 multicenter cohorts. Clusters of patients and important discriminative features were determined using random forest pairwise similarity, multidimensional scaling and distance-based hierarchical clustering. We discovered 2 typical (72.2%) and 3 atypical (28.8%) subtypes with significantly different demographic, clinical and cognitive characteristics, and different rates of cognitive decline. In contrast to previous studies, our unsupervised random forest approach based on cortical and subcortical volume measures and their linear and non-linear interactions, revealed more typical AD subtypes with important anatomically discriminative features, while the prevalence of atypical cases was lower. The hippocampal-sparing and typical AD subtypes, exhibited worse clinical progression in visuospatial, memory and executive cognitive functions. Our findings suggest there is substantial heterogeneity in AD that has an impact on how patients function and progress over time.

KW - Alzheimer's disease

KW - Structural magnetic resonance imaging

KW - Cortical volumes

KW - Subcortical volumes

KW - Cluster analyses

KW - Random forest similarity

U2 - 10.1016/j.neurobiolaging.2018.01.009

DO - 10.1016/j.neurobiolaging.2018.01.009

M3 - Article

SN - 0197-4580

JO - Neurobiology of Aging

JF - Neurobiology of Aging

ER -