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Microglial activation and tau burden predict cognitive decline in Alzheimer's disease.

ABSTRACT: Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer's disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer's disease pathology. Twenty-six patients (n?=?12 with clinically probable Alzheimer's dementia and n?=?14 with amyloid-positive mild cognitive impairment) and 29 healthy control subjects underwent baseline assessment with 18F-AV-1451 PET, 11C-PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke's Cognitive Examination. Regional grey matter volumes, and regional binding of 18F-AV-1451 and 11C-PK11195 were derived from 15 temporo-parietal regions characteristically affected by Alzheimer's disease pathology. A principal component analysis was used on each imaging modality separately, to identify the main spatial distributions of pathology. A latent growth curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals' estimated rate of cognitive decline on the neuroimaging components and examined univariable predictive models with single-modality predictors, and a multi-modality predictive model, to identify the independent and combined prognostic value of the different neuroimaging markers. Principal component analysis identified a single component for the grey matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the rate of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of 18F-AV-1451 and the first (i.e. anterior temporal) component for 11C-PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer's disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer's disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer's disease.

SUBMITTER: Malpetti M

PROVIDER: S-EPMC7241955 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Microglial activation and tau burden predict cognitive decline in Alzheimer's disease.

Malpetti Maura M Kievit Rogier A RA Passamonti Luca L Jones P Simon PS Tsvetanov Kamen A KA Rittman Timothy T Mak Elijah E Nicastro Nicolas N Bevan-Jones W Richard WR Su Li L Hong Young T YT Fryer Tim D TD Aigbirhio Franklin I FI O'Brien John T JT Rowe James B JB

Brain : a journal of neurology 20200501 5

Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer's disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cog ...[more]

PMID: 32380523

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Project description:PurposeBiomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.Patients and methodsA total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.ResultsBaseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.ConclusionOur study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.

Project description:For early detection of Alzheimer's disease, it is important to find biomarkers with predictive value for disease progression and clinical manifestations, such as cognitive decline. Individuals can now be profiled based on their biomarker status for Aβ42 (A) or tau (T) deposition and neurodegeneration (N). The aim of this study was to compare the cerebrospinal fluid (CSF) and imaging (PET/MR) biomarkers in each ATN category and to assess their ability to predict longitudinal cognitive decline. A subset of 282 patients, who had had at the same time PET investigations with amyloid-β and tau tracers, CSF sampling, and structural MRI (18% within 13 months), was selected from the ADNI dataset. The participants were grouped by clinical diagnosis at that time: cognitively normal, subjective memory concern, early or late mild cognitive impairment, or AD. Agreement between CSF (amyloid-β-1-42(A), phosphorylated-Tau181(T), total-Tau(N)), and imaging (amyloid-β PET (florbetaben and florbetapir)(A), tau PET (flortaucipir)(T), hippocampal volume (MRI)(N)) positivity in ATN was assessed with Cohen's Kappa. Linear mixed-effects models were used to predict decline in the episodic memory. There was moderate agreement between PET and CSF for A biomarkers (Kappa = 0.39-0.71), while only fair agreement for T biomarkers (Kappa ≤ 0.40, except AD) and discordance for N biomarkers across all groups (Kappa ≤ 0.14) was found. Baseline PET tau predicted longitudinal decline in episodic memory irrespective of CSF p-Tau181 positivity (p ≤ 0.02). Baseline PET tau and amyloid-β predicted decline in episodic memory (p ≤ 0.0001), but isolated PET amyloid-β did not. Isolated PET Tau positivity was only observed in 2 participants (0.71% of the sample). While results for amyloid-β were similar using CSF or imaging, CSF and imaging results for tau and neurodegeneration were not interchangeable. PET tau positivity was superior to CSF p-Tau181 and PET amyloid-β in predicting cognitive decline in the AD continuum within 3 years of follow-up.

Project description:BackgroundElevated cerebrospinal fluid (CSF) concentrations of total tau (T-tau) and phosphorylated tau at Thr181 (P-tau181) protein are typical of Alzheimer's disease (AD). However, the T-tau assay measures only the mid-region of the protein, while tau in CSF is instead composed of a series of fragments. One fragment species in particular, N-224, shows increased levels in AD compared to controls. In this multicentre study, we performed a clinical validation of the N-224 assay in cohorts including patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD, non-AD dementias and controls.MethodsCohorts consisted of 30 SCD and 30 probable AD from the Amsterdam Dementia Cohort (cohort 1) and 539 controls, 195 SCD, 232 MCI, 137 AD and 253 non-AD from the Swedish BioFINDER study (cohort 2). All samples had AD core biomarkers (Aβ42, T-tau, P-tau181) measurements. N-224 was measured with an in-house ultrasensitive Simoa assay.ResultsN-224 levels were significantly higher in AD compared to SCD (cohort 1: p = 0.003) and in AD compared to all other diagnostic groups in cohort 2 (control, SCD, MCI and non-AD, p < 0.0001). Within the non-AD group, N-224 showed significantly lower concentrations compared to AD in Parkinson's disease (PD, p < 0.0001), Parkinson's disease dementia (PDD, p = 0.004), progressive supranuclear palsy (PSP, < 0.0001), multiple system atrophy (MSA, p = 0.002) and parkinsonisms not otherwise specified (NOS, p = 0.007). In cohort 1, higher concentrations of N-224 were associated to lower Mini-Mental State Examination (MMSE) scores (R2 = 0.318, β = 0.564, p ≤ 0.0001) and could accurately identify a pathological (< 24) MMSE score (p < 0.0001, AUC = 0.824).ConclusionsN-224 tau can distinguish AD subjects from SCD and can discriminate subgroups of non-AD dementias from AD. Therefore, N-224 may be a useful addition to the tau biomarker toolbox for the study of tau species in CSF and for better understanding disease pathogenesis.

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Microglial activation and tau burden predict cognitive decline in Alzheimer's disease.

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Microglial activation and tau burden predict cognitive decline in Alzheimer's disease.

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