期刊
ALZHEIMERS RESEARCH & THERAPY
卷 13, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s13195-020-00713-3
关键词
Alzheimer's disease; CSF tau; Gaussian mixture modelling; Prognosis
资金
- ZonMW Memorabel grant programme [733050824]
- Alzheimer Nederland grant [NL18003P]
- Sigrid Juselius Foundation
- Stichting Alzheimer Nederland
- Stichting VUmc fonds
Using Gaussian mixture modeling, four subgroups were identified based on CSF t-tau and p-tau levels in two independent cohorts, with increasingly high tau subgroups associated with faster clinical decline and higher risk of progression to Alzheimer's disease.
BackgroundAs Alzheimer's disease (AD) pathology presents decades before dementia manifests, unbiased biomarker cut-points may more closely reflect presence of pathology than clinically defined cut-points. Currently, unbiased cerebrospinal fluid (CSF) tau cut-points are lacking.MethodsWe investigated CSF t-tau and p-tau cut-points across the clinical spectrum using Gaussian mixture modelling, in two independent cohorts (Amsterdam Dementia Cohort and ADNI).ResultsIndividuals with normal cognition (NC) (total n =1111), mild cognitive impairment (MCI) (total n =1213) and Alzheimer's disease dementia (AD) (total n =1524) were included. In both cohorts, four CSF t- and p-tau distributions and three corresponding cut-points were identified. Increasingly high tau subgroups were characterized by steeper MMSE decline and higher progression risk to AD (cohort/platform-dependent HR, t-tau 1.9-21.3; p-tau 2.2-9.5).LimitationsThe number of subjects in some subgroups and subanalyses was small, especially in the highest tau subgroup and in tau PET analyses.ConclusionsIn two independent cohorts, t-tau and p-tau levels showed four subgroups. Increasingly high tau subgroups were associated with faster clinical decline, suggesting our approach may aid in more precise prognoses.
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