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An early and late peak in microglial activation in Alzheimer's disease trajectory.

ABSTRACT: Amyloid-? deposition, neuroinflammation and tau tangle formation all play a significant role in Alzheimer's disease. We hypothesized that there is microglial activation early on in Alzheimer's disease trajectory, where in the initial phase, microglia may be trying to repair the damage, while later on in the disease these microglia could be ineffective and produce proinflammatory cytokines leading to progressive neuronal damage. In this longitudinal study, we have evaluated the temporal profile of microglial activation and its relationship between fibrillar amyloid load at baseline and follow-up in subjects with mild cognitive impairment, and this was compared with subjects with Alzheimer's disease. Thirty subjects (eight mild cognitive impairment, eight Alzheimer's disease and 14 controls) aged between 54 and 77 years underwent 11C-(R)PK11195, 11C-PIB positron emission tomography and magnetic resonance imaging scans. Patients were followed-up after 14 ± 4 months. Region of interest and Statistical Parametric Mapping analysis were used to determine longitudinal alterations. Single subject analysis was performed to evaluate the individualized pathological changes over time. Correlations between levels of microglial activation and amyloid deposition at a voxel level were assessed using Biological Parametric Mapping. We demonstrated that both baseline and follow-up microglial activation in the mild cognitive impairment cohort compared to controls were increased by 41% and 21%, respectively. There was a longitudinal reduction of 18% in microglial activation in mild cognitive impairment cohort over 14 months, which was associated with a mild elevation in fibrillar amyloid load. Cortical clusters of microglial activation and amyloid deposition spatially overlapped in the subjects with mild cognitive impairment. Baseline microglial activation was increased by 36% in Alzheimer's disease subjects compared with controls. Longitudinally, Alzheimer's disease subjects showed an increase in microglial activation. In conclusion, this is one of the first longitudinal positron emission tomography studies evaluating longitudinal changes in microglial activation in mild cognitive impairment and Alzheimer's disease subjects. We found there is an initial longitudinal reduction in microglial activation in subjects with mild cognitive impairment, while subjects with Alzheimer's disease showed an increase in microglial activation. This could reflect that activated microglia in mild cognitive impairment initially may adopt a protective activation phenotype, which later change to a cidal pro-inflammatory phenotype as disease progresses and amyloid clearance fails. Thus, we speculate that there might be two peaks of microglial activation in the Alzheimer's disease trajectory; an early protective peak and a later pro-inflammatory peak. If so, anti-microglial agents targeting the pro-inflammatory phenotype would be most beneficial in the later stages of the disease.

SUBMITTER: Fan Z

PROVIDER: S-EPMC5837520 | biostudies-other | 2017 Mar

REPOSITORIES: biostudies-other

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An early and late peak in microglial activation in Alzheimer's disease trajectory.

Fan Zhen Z Brooks David J DJ Okello Aren A Edison Paul P

Brain : a journal of neurology 20170301 3

Amyloid-β deposition, neuroinflammation and tau tangle formation all play a significant role in Alzheimer's disease. We hypothesized that there is microglial activation early on in Alzheimer's disease trajectory, where in the initial phase, microglia may be trying to repair the damage, while later on in the disease these microglia could be ineffective and produce proinflammatory cytokines leading to progressive neuronal damage. In this longitudinal study, we have evaluated the temporal profile o ...[more]

PMID: 28122877

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Project description: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.

Dataset Information

An early and late peak in microglial activation in Alzheimer's disease trajectory.

Publications

An early and late peak in microglial activation in Alzheimer's disease trajectory.

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