Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017
Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Scheltens Nienke M E, Tijms Betty M, Koene Teddy, Barkhof Frederik, Teunissen Charlotte E, Wolfsgruber Steffen, Wagner Michael, Kornhuber Johannes, Peters Oliver, Cohn-Sheehy Brendan I, Rabinovici Gil D, Miller Bruce L, Kramer Joel H, Scheltens Philip, van der Flier Wiesje M, German Dementia Competence Network, University of California San Francisco Memory and Aging Center, Amsterdam Dementia Cohort
Аннотация
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 relatively memory spared. Pooled analyses showed that the memory-spared clusters (29%-52% of patients) were younger, more often apolipoprotein E (APOE) ɛ4 negative, and had more severe posterior atrophy compared with the memory-impaired clusters (all P < .05).
CONCLUSIONS: We could identify two robust cognitive clusters in four independent large cohorts with distinct clinical characteristics.
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 relatively memory spared. Pooled analyses showed that the memory-spared clusters (29%-52% of patients) were younger, more often apolipoprotein E (APOE) ɛ4 negative, and had more severe posterior atrophy compared with the memory-impaired clusters (all P < .05).
CONCLUSIONS: We could identify two robust cognitive clusters in four independent large cohorts with distinct clinical characteristics.