Flora H Duits1, Kirsten E J Wesenhagen2, Laura Ekblad1,3, Emma Wolters1,4, Eline A J Willemse5, Philip Scheltens1, Wiesje M van der Flier1,6, Charlotte E Teunissen5, Pieter Jelle Visser1,7,8, Betty M Tijms1. 1. Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. 2. Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands. k.wesenhagen@amsterdamumc.nl. 3. Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland. 4. Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam Neuroscience, Amsterdam, Netherlands. 5. Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam UMC, Amsterdam Neuroscience, Amsterdam, Netherlands. 6. Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands. 7. Alzheimer Center Limburg, Department of Psychiatry & Neuropsychology, School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands. 8. Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Abstract
BACKGROUND: As 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. METHODS: We 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). RESULTS: Individuals 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). LIMITATIONS: The number of subjects in some subgroups and subanalyses was small, especially in the highest tau subgroup and in tau PET analyses. CONCLUSIONS: In 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.
BACKGROUND: As 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. METHODS: We 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). RESULTS: Individuals with normal cognition (NC) (total n = 1111), mild cognitive impairment (MCI) (total n = 1213) and Alzheimer's diseasedementia (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). LIMITATIONS: The number of subjects in some subgroups and subanalyses was small, especially in the highest tau subgroup and in tauPET analyses. CONCLUSIONS: In 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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