Relationship between astrocyte reactivity, using novel 11C-BU99008 PET, and glucose metabolism, grey matter volume and amyloid load in cognitively impaired individuals

Post mortem neuropathology suggests that astrocyte reactivity may play a significant role in neurodegeneration in Alzheimer’s disease. We explored this in vivo using multimodal PET and MRI imaging. Twenty subjects (11 older, cognitively impaired patients and 9 age-matched healthy controls) underwent brain scanning using the novel reactive astrocyte PET tracer 11C-BU99008, 18F-FDG and 18F-florbetaben PET, and T1-weighted MRI. Differences between cognitively impaired patients and healthy controls in regional and voxel-wise levels of astrocyte reactivity, glucose metabolism, grey matter volume and amyloid load were explored, and their relationship to each other was assessed using Biological Parametric Mapping (BPM). Amyloid beta (Aβ)-positive patients showed greater 11C-BU99008 uptake compared to controls, except in the temporal lobe, whilst further increased 11C-BU99008 uptake was observed in Mild Cognitive Impairment subjects compared to those with Alzheimer’s disease in the frontal, temporal and cingulate cortices. BPM correlations revealed that regions which showed reduced 11C-BU99008 uptake in Aβ-positive patients compared to controls, such as the temporal lobe, also showed reduced 18F-FDG uptake and grey matter volume, although the correlations with 18F-FDG uptake were not replicated in the ROI analysis. BPM analysis also revealed a regionally-dynamic relationship between astrocyte reactivity and amyloid uptake: increased amyloid load in cortical association areas of the temporal lobe and cingulate cortices was associated with reduced 11C-BU99008 uptake, whilst increased amyloid uptake in primary motor and sensory areas (in which amyloid deposition occurs later) was associated with increased 11C-BU99008 uptake. These novel observations add to the hypothesis that while astrocyte reactivity may be triggered by early Aβ-deposition, sustained pro-inflammatory astrocyte reactivity with greater amyloid deposition may lead to astrocyte dystrophy and amyloid-associated neuropathology such as grey matter atrophy and glucose hypometabolism, although the evidence for glucose hypometabolism here is less strong.


INTRODUCTION
Astrocytes are integral to normal brain function, playing important roles in neurogenesis, synaptogenesis, control of blood-brain barrier permeability and maintaining extracellular homeostasis [1]. In Alzheimer's disease (AD), astrocytes can assume a reactive phenotype in response to disease by undergoing morphological, molecular and functional remodeling [2]. While astrocyte reactivity is associated with amyloid beta (Aβ) plaques [3], the precise role of this astrocyte reactivity in neurodegeneration is still unclear. It is suggested that astrocytes could have a beneficial and detrimental role, and this could also depend on the pathological insult and the susceptibility of the host [4]. It is proposed that with higher levels of Aβ, astrocyte reactivity can produce neurotoxic reactive oxygen species and inflammatory cytokines [5]. Astrocytes in AD also can lose normal neuroprotective capabilities as they become dystrophic with the progression of AD pathology [4,6].
Glucose hypometabolism, measured using 18 F-fluorodeoxyglucose ( 18 F-FDG) PET, and brain atrophy, measured using MRI, are two of the earliest neuroimaging markers of neurodegeneration developed for AD [7]. However, both measures are sensitive to changes in astrocyte reactivity [8,9], and the contribution of FDG signal from astrocyte reactivity is yet to be fully elucidated. By contributing to synaptic loss and neurodegeneration, pro-inflammatory and dystrophic astrocytes may be associated with accelerated grey matter (GM) atrophy [10]. Astrocytes are also necessary for metabolic support of neuronal activity [11], so AD-related changes in astrocytes might contribute directly to the brain glucose hypometabolism characteristic of AD [7].
The novel PET tracer 11 C-BU99008 has high specificity and selectivity for binding sites of type-2 imidazoline receptors (I 2 -BS), which are expressed primarily within astrocytes and are upregulated with reactivity [12]. This tracer thus allows the study of astrocyte reactivity in vivo [13][14][15][16][17][18]. Pathologically increased 11 C-BU99008 PET signal recently has been demonstrated in neurodegenerative disorders including AD [19] and Parkinson's disease [20]. Currently, the only available PET tracer which can measure astrocyte reactivity in vivo is 11 C-deuterium-L -deprenyl ( 11 C-DED) [21,22]. However, this tracer binds to monoamine oxidase-B (MAO-B), which is reduced in the presence of late stage Aβ-deposition. Therefore, it remains unclear if the lower 11 C-DED binding observed in late-stage compared to early-stage AD subjects reflects a reduction in astrocyte reactivity or simply lower levels of MAO-B [23]. The higher specific binding of 11 C-BU99008 than 11 C-DED to detect astrocyte reactivity has recently been demonstrated in post mortem brain tissue from AD patients [24]likely due to the fact they will be detecting different astrocyte subtypes-and thus 11 C-BU99008 warrants further study in this clinical population. The aim of this study was to evaluate the relationship between astrocyte reactivity, using 11 C-BU99008 PET, and glucose metabolism, GM atrophy and Aβ-deposition in cognitively impaired patients with a clinical diagnosis of ADrelated dementia or Mild Cognitive Impairment (MCI).

MATERIALS AND METHODS
We recruited 20 subjects for this pilot study. Ethical approval was obtained from the local and regional Research Ethics Committee, whilst approval to administer radiotracers was obtained from the Administration of Radioactive Substances Advisory Committee UK. The human biological samples sourced from participants were obtained ethically and their research use was in accordance with the terms of the informed consent.

Subjects
Subjects were recruited from memory clinics, research registries and advertisements. We included 11 cognitively impaired patients with a clinical diagnosis of AD-related dementia or MCI (6 clinically diagnosed AD, 5 MCI; Mini-Mental Status Examination (MMSE) score [mean ± SD] = 22.6 ± 4.1) and 9 age-matched healthy controls (MMSE score [mean ± SD] = 29.1 ± 1.27) without a history of brain disease ( Table 1). The inclusion criteria for cognitively impaired patients included the ability to give informed consent, an MMSE score ≥17 and at least 8 years of education. Exclusion criteria for all participants included contradictions to MRI and any evidence of significant small vessel or vascular disease on MRI. AD patients were defined according to a clinical diagnosis based on previous MRI and/or FDG PET, and Aβ imaging from this study was not used as an inclusion/ exclusion criteria, nor were AD patients excluded who were Aβ-negative according to our analysis. All subjects underwent medical and detailed cognitive assessments using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), as well as 11 C-BU99008, 18 F-FDG and 18 F-florbetaben PET and T1-weighted structural MRI. Aβ-positivity was defined by using a whole brain uptake cut-off of 1.43 [25].

Image acquisition
All image acquisition was performed at the Invicro Centre for Imaging Sciences in London, UK. MRI images were acquired using either a 3 Tesla Magnetom Trio or Verio (Siemens Healthcare Sector, Erlangen, Germany) with a 32-receiver channel head matrix coil. All PET imaging was performed on a Siemens Truepoint PET/CT scanner. All three PET scans were completed on separate days, with no longer than 30 days between the first and last scan completed. The order of the PET scans was not fixed and varied between participants depending on the availability of the PET tracers.
PET 11 C-BU99008 PET: All subjects underwent 11 C-BU99008 PET scanning to assess astrocyte reactivity in the brain. 11 C-BU99008 was synthesised on site. An initial CT scan was acquired for attenuation correction of the PET images, before a mean activity of 330 (±30) MBq 11 C-BU99008 in 20 ml normal saline was injected into the antecubital vein. Dynamic emission 11 C-BU99008 PET images were acquired over 120 min and rebinned into 29 timeframes: 8 × 15 s, 3 × 60 s, 5 × 120 s, 5 × 300 s, and 8 × 600 s. All subjects had arterial blood sampled continuously for the first 15 min, with 12 additional samples taken at 5,10,15,20,25,30,40,50,60,70,80, and 100 min after injection. A gamma counter was used to measure radioactivity in the whole blood and plasma for each sample. Reverse-phase high-performance liquid chromatography was used to evaluate metabolism of 11 C-BU99008 by calculating the relative proportions of parent tracer and metabolites in the blood. Parametric images (Impulse Response Function at 120 min (IRF-120)) of 11 C-BU99008 were generated using spectral analysis. This was performed using Modelling, Input Functions and Compartmental Kinetics Parametric Map (MICK-PM) software (available on request from Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK). 18 F-FDG and 18 F-florbetaben PET: All subjects also underwent 18 F-FDG and 18 F-florbetaben PET scanning to assess glucose metabolism and Aβdeposition in the brain, respectively. Subjects received a target dose of 185 MBq 18 F-FDG and 236 MBq 18 F-florbetaben as single intravenous boluses in the respective scanning sessions. For 18 F-FDG scans, PET acquisition commenced 30 min after tracer injection, and the scans were acquired for 30 min. Using MICKPM, activity over the last 30 min was averaged, resulting in a 3D 30-60 min 18 F-FDG add-image. For 18 F-florbetaben scans, PET acquisition commenced 90 min after tracer administration and the subjects were scanned for 30 min. Activity over the 30 min acquisition period was averaged, resulting in a 3D 90-120 min 18 F-florbetaben add-image.

Image processing
MRI and PET images were pre-processed using SPM12 (Wellcome centre for human neuroimaging, UCL, London, UK) in MATLAB (v2014a). 3D PET data was co-registered to the structural MRI of each subject. The structural MRI was segmented into GM, white matter (WM) and cerebrospinal fluid, and the GM and WM maps were used to generate a study-specific template using Diffeomorphic Anatomical Registration Through Exponential Lie Algebra (DARTEL) [26]. The DARTEL flow fields were then used to normalise each of the co-registered PET images and GM maps to MNI space and an 8 mm FWHM Gaussian kernel was used to smooth the data. Tracer uptake for 11 C-BU99008 PET was calculated through spectral analysis (IRF-120 min). Tracer uptake for 18 F-FDG and 18 F-florbetaben PET was evaluated using the standardised uptake value ratio (SUVr) and the Hammers atlas [27], referenced to the pons GM/WM, and the cerebellar GM, respectively. This was done by dividing the cerebral cortical 18 F-FDG and 18 F-florbetaben mean images by the uptake value of the relevant reference region, which had been calculated in Analyse 11.0 (developed by the Biomedical Imaging Resource at the Mayo Clinic). This resulted in smoothed, normalised, 18 F-FDG, 18 F-florbetaben, 11 C-BU99008 and GM Voxel-Based Morphometry (VBM) images that were used to assess glucose metabolism, Aβ deposition, astrocyte reactivity and GM atrophy patterns, respectively. This was done through Regions of Interest (ROI) analysis, as well as voxel-wise Statistical Parametric Mapping (SPM) and Biological Parametric Mapping (BPM) analysis. Partial Volume Correction (PVC) was not performed as PVC can increase noise within the data [28], leading to further signal leakage between regions and tissue classes which cannot be corrected for [29]. In addition, when comparing in vivo Aβ PET within subject with post mortem slices in AD subjects, PVC has been shown to have either no effect [30] or reduce [31] the accuracy of quantification of Aβ. Furthermore, as we are looking at increases for both 11 C-BU99008 and 18 F-Florbetaben, the PVC would have augmented the effect.

Statistical analysis
ROI analysis. Subject-specific object maps were created from the Hammers atlas [27,32] and were used to sample the ROI radioactivity concentration for the three normalised (not smoothed) PET images, as well as the ROI volume of the VBM images. The ROIs included the frontal lobe, temporal lobe, medial temporal lobe, parietal lobe, occipital lobe, posterior cingulate and the whole brain (made up of the four lobes and the cingulate). Tracer uptake and GM volume for each ROI in cognitively impaired patients was compared against that of the healthy controls using a two-sample Student's t test (two-tailed), with statistical difference set to p < 0.05. Due to the exploratory nature of this study, multiple comparison corrections were not performed. Correlation between each of the four imaging measures in each of the four lobes and whole brain for Aβpositive patients was calculated using Pearson's correlation coefficient in SPSS (v26, released 2019). SPM analysis. Voxel-level SPM analysis was performed in order to better characterise the spatial distribution of tracer uptake difference between the cognitively impaired patients and the healthy controls. The three smoothed, normalised PET and VBM images of all subjects were entered into four separate two-sample Student's t tests in SPM12 (twotailed). Significant clusters were identified using cluster-level family wise error (FWE) corrected p values. Single subject analysis was also performed on each of the four modalities by comparing each patients' images against a mean healthy control image in further separate two-sample Student's t tests in SPM12 (two-tailed).
BPM correlation analysis. In order to assess the neuroanatomical relationship between 11 C-BU99008 binding and glucose metabolism, Aβ deposition and GM atrophy, Z-score maps for each of the four imaging modalities were created. These represent tracer uptake and GM atrophy patterns relative to the healthy control's mean and standard deviation for each subject on a voxel-level basis, calculated with the following formulae: Zmap of 11 C À BU99008 ¼ Patient 11 C À BU99008 À mean of controls 11 C À BU99008 SD of controls 11 C À BU99008 Zmap of 18  Voxel-level correlations between 11 C-BU99008 and the remaining three modalities were estimated for Aβ-positive patients using BPM [33], an SPM toolbox that runs through MATLAB and SPM5. Due to the exploratory nature of this study, multiple comparison corrections were not performed.
SPM single subject analysis showed inter-subject and interregional heterogeneity in 11 C-BU99008 uptake, and consistently reduced 18 F-FDG uptake and GM atrophy in the temporal lobe and hippocampus of Aβ-positive patients (Fig. 2).
Please note, the ROI and single subject SPM results were not corrected for multiple comparisons due to the exploratory nature of the study.

Group-level SPM analysis
Two-sample Student's t test in SPM contrasting Aβ-positive patients and healthy controls showed distributions of differences in tracer uptake and GM volumes that were consistent with the ROI-analyses ( Fig. 3 and Supplementary Table 1). Following cluster-level FWEcorrection, Aβ-positive patients had increased 11 C-BU99008 uptake particularly in the frontal and occipital lobes (Fig. 3a), reduced 18 F-FDG uptake in the temporal, parietal and occipital lobes (Fig. 3b), reduced GM volume in temporal regions, particularly the hippocampi (Fig. 3c), and increased 18 F-florbetaben uptake in frontotemporal regions (Fig. 3d). An exploratory two-sample Student's t test comparing MCI and AD subjects showed increased 11 C-BU99008 uptake in MCI patients, particularly in the frontal and temporal regions (Supplementary Fig. 1 and Supplementary Table 1).
Associations of 11 C-BU99008 and 18 F-florbetaben. BPM analysis in Aβ-positive patients described an inverse correlation of increased 18 F-florbetaben uptake with reduced 11 C-BU99008 uptake in regions such as the temporal lobe and the cingulate (Fig. 4e), whilst increased 18 F-florbetaben uptake was positively correlated with increased 11 C-BU99008 uptake in primary motor and primary sensory areas (Fig. 4g). ROI analyses showed that  18 F-Florbetaben. Difference in tracer uptake and GM volume between Aβ-positive patients and healthy controls was analysed using two-sample Student's t tests (two-tailed), with statistical difference set to p < 0.05. Multiple comparison corrections were not performed on the ROI results due to the exploratory nature of this pilot study. "Whole Brain" refers to the composite cortex, combining all the four lobes and the cingulate. * denotes p < 0.05. reduced 11 C-BU99008 uptake was correlated with increased 18 F-florbetaben uptake, particularly in the frontal (r = −0.780, p = 0.039), temporal (r = −0.779, p = 0.039) and occipital (r = −0.911, p = 0.004) lobe, as well as the whole brain (r = −0.798, p = 0.032; Fig. 4f).
Please note, the BPM and ROI results were not corrected for multiple comparisons due to the exploratory nature of this pilot study.

DISCUSSION
In this study, we used the novel imidazoline receptor PET tracer 11 C-BU99008 to test for evidence of a dynamic relationship between astrocyte reactivity and amyloid-associated neurodegeneration based on tissue hypometabolism and atrophy measured using 18 F-FDG PET and structural MRI, respectively. We found evidence for increased astrocyte reactivity in Aβ-positive patients, as increased 11 C-BU99008 uptake was observed primarily in frontal, parietal and occipital regions. Furthermore, these increases were greater in MCI than AD patients. Voxel-wise correlational analyses showed that lower 11 C-BU99008 uptake in Aβ-positive patients was associated with hypometabolism in the parietal, temporal and frontal lobes, even though there was no correlation at ROI level. In addition, lower 11 C-BU99008 uptake in Aβ-positive patients was associated with GM atrophy in frontal and temporal lobes both on a regional and voxel-wise basis. Finally, analyses of regional differences in the relationships between PET markers of Aβ-deposition and astrocyte reactivity displayed a striking heterogeneity. Previously, in the same cohort of patients, we evaluated positive correlations between amyloid and 11 C-BU99008, and we observed that greater Aβ-deposition was associated with increased 11 C-BU99008 uptake in primary motor and primary sensory cortical areas in the parietal cortex [19]. However, as astrocytes can have beneficial and detrimental effects, we performed further evaluation to explore positive and negative associations between amyloid and astrocyte reactivity. We observed greater Aβ-deposition was also associated with decreased 11 C-BU99008 uptake in different localised regions in the rest of the cortices; particularly temporal and cingulate regions. These observations are consistent with a hypothetical model (illustrated in Fig. 5) in which astrocyte reactivity is maximal in earlier stages of pathological progression (when it may contribute to the clearance of Aβ plaques [34]), but, with greater Aβ deposition, astrocytes may progressively become dystrophic or transition to assume a neurotoxic phenotype [4], both of which are likely to accelerate neurodegeneration leading to brain atrophy and hypometabolism. Whilst there is regional, temporal and morphological variation with astrocyte reactivity across the   N = 7). a BPM: Reduced 11 C-BU99008 uptake correlated with reduced 18 F-FDG uptake, rendered at cluster threshold of p < 0.01. b ROI: 11 C-BU99008 uptake positively correlated with 18 F-FDG uptake in the temporal (r = 0.567) and parietal (r = 0.623) lobes, although these did not reach significance (p = 0.184 and p = 0.135, respectively). c BPM: Reduced 11 C-BU99008 uptake correlated with reduced GM volume, shown through sections at cluster threshold of p < 0.01. d ROI: 11 C-BU99008 uptake positively correlated with GM volume in the temporal (r = 0.935, p = 0.002) and parietal (r = 0.833, p = 0.02) lobes. e BPM: Increased 18 F-florbetaben uptake correlated with reduced 11 C-BU99008 uptake, rendered at cluster threshold of p < 0.05. f ROI: 11 C-BU99008 uptake positively correlated with 18 F-florbetaben uptake in the temporal (r = 0.779) and parietal (r = 0.471) lobes, although only the temporal lobe reached significance (p = 0.039 and p = 0.287, respectively). g BPM: Increased 18 F-florbetaben uptake correlated with increased 11 C-BU99008 uptake, rendered at cluster threshold of p < 0.05. Colourbar units in (a), (c), (e), and (g) are contrast estimates representative of Z-scores. All BPM correlations are displayed with an extent threshold of 50 voxels. Multiple comparison corrections were not performed on the BPM results due to the exploratory nature of this pilot study.
AD spectrum [2], our results support previous research and a model which illustrates the rise and fall trajectory of gross levels of astrocyte reactivity through disease progression. This model is also supported by the results from previous studies using other astrocyte markers [21,22,35]. 11 C-BU99008 is a novel PET tracer that binds to I 2 -BS, expression of which is associated with astrocyte reactivity [36,37]. Brain I 2 -BS is upregulated with healthy aging [38], and is further increased in AD [39]. The sensitivity and specificity of 11 C-BU99008 to bind to I 2 -BS expressing reactive astrocytes has been further evidenced in a recent autoradiography study of AD brains where tracer uptake was more significant compared to cognitively normal brains [24]. In line with this, we have previously reported increased 11 C-BU99008 uptake in the same cohort of cognitively impaired patients compared to healthy controls [19]. This corroborates with earlier studies using another PET marker of astrocyte reactivity, 11 C-DED [35]. Interestingly, another 11 C-DED study found increased binding in the frontal lobe in Aβ-positive MCI, but not AD, subjects compared to healthy controls [21], in line with findings in this present study as we observed increased 11 C-BU99008 uptake in MCI subjects compared to AD subjects, particularly in the frontal, temporal and cingulate cortices. Both these findings agree with the hypothesis that astrocyte reactivity is predominantly an early event in the progression of AD pathology.
Astrocytes play an essential role in synapse formation along with the maturation of the synapses and synaptic pruning [40]. Astrocytes undergo morphological, molecular and functional remodelling in the presence of injury and disease states to become reactive astrocytes [2]. In the early stages, reactive astrocytes may have a neuroprotective role, aiding in the clearance of Aβ [3]. The spectrum of Aβ species mediating pathogenic changes in astrocytes is broad and complex, but it is hypothesised that Aβ oligomers can be involved in the primary pathogenesis of astrocyte reactivity [41,42]. In support of this hypothesis, we found increased 11 C-BU99008 uptake was associated with high levels of 18 F-florbetaben uptake in primary motor areas, regions where amyloid deposition is to happen at a later stage of the disease and therefore would have recently developed. Increased 11 C-DED binding has also been found in autosomal dominant AD patients early in their disease progression [43] with recent Aβ deposition [44]. In addition, a recent study demonstrated that plasma levels of glial fibrillary acid protein (GFAP), a marker of astrocyte reactivity, is an early marker of Aβ load, and was associated longitudinally with Aβ accumulation and cognitive decline [45]. In healthy conditions, astrocytes have several roles in providing neuronal support that contributes to normal neuronal function. Accumulation of Aβ induces astrocyte reactivity, causing the astrocytes to become hypertrophic. Then, the neuroprotective reactive astrocytes release proteases that aid in the cleavage and removal of Aβ plaques. MCI/Early AD: Despite the efforts of the reactive astrocytes, Aβ continues to accumulate and eventually the high levels cause the reactive astrocytes to become neurotoxic, as they release cytokines, chemokines and reactive oxygen species. The switch from neuroprotective to neurotoxic contributes to the early stages of astrocyte and GM atrophy. Advanced AD: Astrocyte reactivity in cortical regions with early amyloid deposition, and therefore early astrocyte reactivity, will experience advanced astrocyte atrophy. This results in the loss of normal function (such as blood flow maintenance) and further new neurotoxic functions (such as excessive glutamate release), both contributing to glucose hypometabolism and advanced GM atrophy which further contribute to cognitive impairment.
Interaction of Aβ with reactive astrocytes has been proposed as a trigger for astrocytes to switch from a neuroprotective to a neurotoxic role. As astrocyte reactivity increases Aβ production [46], a positive feedback loop favouring the formation of neurotoxic, pro-inflammatory astrocytes is initiated. Reactive astrocytes exhibit beneficial and detrimental effects based on their reactivity profile. In mouse models of infection and stroke induced by lipopolysaccharide induction and middle artery occlusion, respectively, resting astrocytes polarise to become reactive astrocytes [47]. Neurotoxic astroglial phenotype is induced by cytokines secreted by activated microglia, which include complement factors (C1q), TNF-α and IL-1α [48]. This leads to astrocytes losing their ability to promote neuronal survival and outgrowth, synaptogenesis, and phagocytosis, and inducing the demise of neurons, oligodendrocytes and even astrocytes themselves. We found evidence of low astrocyte reactivity, perhaps due to astrocyte dystrophy in the presence of high Aβ load in this current study, as decreased 11 C-BU99008 uptake was associated with high levels of 18 F-florbetaben uptake in the temporal lobe, one of the earliest regions where Aβ deposition occurs [44]. This decreased 11 C-BU99008 uptake in the temporal lobe was also associated with greater relative progression of amyloid-associated neuropathology, that is glucose hypometabolism and GM atrophy. However, it is important to note the evidence of an association between reduced 11 C-BU99008 and 18 F-FDG uptake is less strong as it was observed at a voxel-wise basis, but not on a regional basis. We propose this reduced 11 C-BU99008 uptake in the temporal lobe region reflects astrocyte dystrophy [49], that eventually leads to astrocytic and neuronal atrophy [50,51] and glucose hypometabolism [6] (Fig. 5). Our results are corroborated from previous findings of correlations between regional reductions in 11 C-DED and 18 F-FDG PET signals, which were associated with regionally more advanced 11 C-PIB PET pathology in a longitudinal study of people with autosomal dominant AD or MCI [52].
There are obvious limitations to our study. First, only a small number of subjects were able to be imaged, requiring statistical analysis to be applied in a more liberal exploratory nature. However, while this is a pilot study, the explanatory power was enhanced by the design in which uptake of the three PET tracers and brain volume all were assessed in the same people. A second limitation was the cross-sectional design, which we acknowledge; however, post mortem pathology has the same limitation. Our results thus are better interpreted descriptively and as suggestive of a hypothetical model, rather than a strong, independent test. Nonetheless, the consistency of directions of effect observed in this study and the earlier 11 C-DED PET studies [21,52] provides compelling support for the hypothetical model presented (Fig. 5). That is, astrocyte reactivity occurs in response to early Aβdeposition, aiding in the clearance of Aβ, but following interactions with high levels of Aβ the astrocytes become neurotoxic, contributing to reduced tissue activity and cell death that is associated with cognitive impairment. It also strengthens confidence in the earlier work, which otherwise suffers from uncertainties regarding the specificity of binding of 11 C-DED in the brain [21]. Nonetheless, 11 C-BU99008 can detect astrocyte reactivity with a greater sensitivity than 11 C-DED [24], especially amongst higher levels of amyloid load [19,53], and thus should be prioritised to take it forward.
In conclusion, this study supports neuropathological observations arguing that astrocyte reactivity with amyloid-related neuropathology is dynamic [54]. We have demonstrated in vivo with the novel PET tracer 11 C-BU99008 that astrocyte reactivity is increased in regions presumed to represent earlier stages of pathological progression with low Aβ-deposition loads, and conversely relatively reduced in regions that show signs of more advanced disease progression with greater Aβ-deposition and atrophy. In the absence of molecular imaging markers intrinsically discriminating different reactive astrocyte phenotypes, our multimodal imaging approach may allow relevant inferences to be made from the relative 11 C-BU99008, 18 F-FDG and 18 F-florbetaben PET signals and brain volume sensitive MRI measures. Future, larger, longitudinal studies are needed to further test this dynamic model and, if supported, interventions developed to arrest progression of the neurotoxic phenotypic transformation of astrocytes in AD.