Journal
NEUROBIOLOGY OF AGING
Volume 65, Issue -, Pages 98-108Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.neurobiolaging.2018.01.009
Keywords
Alzheimer's disease; Structural magnetic resonance imaging; Cortical volumes; Subcortical volumes; Cluster analyses; Random forest similarity
Categories
Funding
- Swedish Foundation for Strategic Research (SSF)
- The Swedish Research Council (VR)
- Strategic Research Programme in Neuroscience at Karolinska Institutet (StratNeuro)
- Swedish Brain Power
- Stockholm County Council
- Karolinska Institutet
- Hjarnfonden
- Alzheimerfonden
- Ake Wiberg Foundation
- Birgitta och Sten Westerberg
- InnoMed, (Innovative Medicines in Europe) an Integrated Project - the European Union of the Sixth Framework program [FP6-2004-LIFESCIHEALTH-5]
- Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
- DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- BioClinica, Inc.
- Biogen Idec Inc.
- Bristol-Myers Squibb Company
- Eisai Inc.
- Elan Pharmaceuticals, Inc.
- Eli Lilly and Company
- F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.
- GE Healthcare
- Innogenetics, N.V.
- IXICO Ltd.
- Janssen Alzheimer Immunotherapy Research & Development, LLC.
- Johnson & Johnson Pharmaceutical Research & Development LLC.
- Medpace, Inc.
- Merck Co., Inc.
- Meso Scale Diagnostics, LLC.
- NeuroRx Research
- Novartis Pharmaceuticals Corporation
- Pfizer Inc.
- Piramal Imaging
- Servier
- Synarc Inc.
- Takeda Pharmaceutical Company
- Canadian Institutes of Health Research
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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 nonlinear 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. (C) 2018 Elsevier Inc. All rights reserved.
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