Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts.

ABSTRACT:

Introduction

Patients with Alzheimer's disease (AD) show heterogeneity in profile of cognitive impairment. We aimed to identify cognitive subtypes in four large AD cohorts using a data-driven clustering approach.

Methods

We included probable AD dementia patients from the Amsterdam Dementia Cohort (n = 496), Alzheimer's Disease Neuroimaging Initiative (n = 376), German Dementia Competence Network (n = 521), and University of California, San Francisco (n = 589). Neuropsychological data were clustered using nonnegative matrix factorization. We explored clinical and neurobiological characteristics of identified clusters.

Results

In each cohort, a two-clusters solution best fitted the data (cophenetic correlation >0.9): one cluster was memory-impaired and the other relativ

SUBMITTER: Scheltens NME 

PROVIDER: S-EPMC5857387 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature