An early and late peak in microglial activation in Alzheimer's disease trajectory - PubMed (original) (raw)

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

Zhen Fan et al. Brain. 2017.

Abstract

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 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.

Keywords: Alzheimer’s disease; amyloid imaging; microglial activation; mild cognitive impairment; neuropathology.

© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Figures

Figure 1

Figure 1

SPM analysis between baseline and follow-up microglial activation in MCI subjects. (A) Paired _t_-test SPM analysis between baseline and follow-up microglial activation in all subjects with MCI. (B) Paired _t_-test SPM analysis between baseline and follow-up microglial activation in amyloid positive subjects. (C) Paired _t_-test SPM analysis between baseline and follow up microglial activation in amyloid negative subjects. Supplementary Table 2 details the coordinates with their statistical results.

Figure 2

Figure 2

Longitudinal changes in 11C-(R)PK11195 BP and 11C-PIB in subjects with MCI compared to controls at baseline and follow-up. (A and B) Clusters of significantly increased 11C-(R)PK11195 BP in subjects with MCI compared to healthy controls at baseline and follow-up, respectively, with the same voxel threshold of P < 0.01 and extent threshold of 50 voxels. (C and D) Clusters of significantly increased 11C-PIB in subjects with MCI compared to healthy controls at baseline and follow-up (P < 0.0001 and extent of 200 voxels). Supplementary Table 3 details the coordinates with their statistical results. (E and F) 3D intensity T-map of 11C-(R)PK11195 BP and 11C-PIB RATIO for two individual subjects with MCI at baseline and follow-up. The surface plot represents significant increase in the microglial activation (left) and amyloid deposition (right) against the control group at baseline superimposed on a 3D matrix at baseline and follow-up.

Figure 3

Figure 3

Voxel-based correlation between 11C-(R)PK11195 BP and 11C-PIB uptake. BPM-positive correlation between microglial activation and amyloid deposition superimposed on a SPM render brain image, along with 3D intensity T-map of BPM correlation in sagittal view in MCI and Alzheimer’s disease cohort. (A and B) Positive correlations between 11C-PIB RATIO and 11C-(R)PK11195 BP in subjects with MCI at baseline and follow-up, respectively, at a cluster threshold of P < 0.05 with an extent threshold of 50-voxel. (C and D) Positive correlations between 11C-PIB RATIO and 11C-(R)PK11195 BP in subjects with Alzheimer’s disease at baseline and follow-up, respectively, at a cluster threshold of P < 0.05 with an extent threshold of 50-voxel. Supplementary Table 4 details the significant clusters.

Figure 4

Figure 4

Hypothetical model of dual peak of microglial activation in the Alzheimer’s trajectory.Top: The hypothetical model of morphological changes in microglia in Alzheimer’s disease trajectory, where ramified microglia transform to anti-inflammatory (protective) microglial phenotype and pro-inflammatory (toxic) microglial phenotypes. Bottom: The microglial activation in relation to other biomarkers detectable using positron emission tomography where two peaks of microglial activation are present in Alzheimer’s trajectory. Modified from Jack et al. (2010).

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References

    1. Amor S, Puentes F, Baker D, van der Valk P. Inflammation in neurodegenerative diseases. Immunology 2010; 129: 154–69. - PMC - PubMed
    1. Anderson AN, Pavese N, Edison P, Tai YF, Hammers A, Gerhard A. et al. A systematic comparison of kinetic modelling methods generating parametric maps for [(11)C]-(R)-PK11195. Neuroimage 2007; 36: 28–37. - PubMed
    1. Cai Z, Hussain MD, Yan LJ. Microglia, neuroinflammation, and beta-amyloid protein in Alzheimer’s disease. Int J Neurosci 2013; 124: 307–21. - PubMed
    1. Casanova R, Srikanth R, Baer A, Laurienti PJ, Burdette JH, Hayasaka S. et al. Biological parametric mapping: a statistical toolbox for multimodality brain image analysis. Neuroimage 2007; 34: 137–43. - PMC - PubMed
    1. Craig-Schapiro R, Perrin RJ, Roe CM, Xiong C, Carter D, Cairns NJ. et al. YKL-40: a novel prognostic fluid biomarker for preclinical Alzheimer’s disease. Biol Psychiatry 2010; 68: 903–12. - PMC - PubMed

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