3 research outputs found
Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts
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
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Prominent Non-Memory Deficits in Alzheimer's Disease Are Associated with Faster Disease Progression.
BackgroundAlzheimer's disease (AD) is a heterogeneous disorder.ObjectiveTo investigate whether cognitive AD subtypes are associated with different rates of disease progression.MethodsWe included 1,066 probable AD patients from the Amsterdam Dementia Cohort (n = 290), Alzheimer's Disease Neuroimaging Initiative (n = 268), Dementia Competence Network (n = 226), and University of California, San Francisco (n = 282) with available follow-up data. Patients were previously clustered into two subtypes based on their neuropsychological test results: one with most prominent memory impairment (n = 663) and one with most prominent non-memory impairment (n = 403). We examined associations between cognitive subtype and disease progression, as measured with repeated Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale sum of boxes (CDR sob), using linear mixed models. Furthermore, we investigated mortality risk associated with subtypes using Cox proportional hazard analyses.ResultsPatients were 71±9 years old; 541 (51%) were female. At baseline, pooled non-memory patients had worse MMSE scores (23.1±0.1) and slightly worse CDR sob (4.4±0.1) than memory patients (MMSE 24.0±0.1; p < 0.001; CDR sob 4.1±0.1; p < 0.001). During follow-up, pooled non-memory patients showed steeper annual decline in MMSE (-2.8±0.1) and steeper annual increase in CDR sob (1.8±0.1) than memory patients (MMSE - 1.9±0.1; pinteraction<0.001; CDR sob 1.3±0.1; pinteraction<0.001). Furthermore, the non-memory subtype was associated with an increased risk of mortality compared with the memory subtype at trend level (HR = 1.36, CI = 1.00-1.85, p = 0.05).ConclusionsAD patients with most prominently non-memory impairment show faster disease progression and higher risk of mortality than patients with most prominently memory impairment
Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts
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