Introduction
Along with features such as extracellular accumulation of amyloid-β plaques and neuroinflammation, the intracellular aggregation of misfolded tau protein as neurofibrillary tangles (NFT) constitutes one of the neuropathological hallmarks of Alzheimer disease (AD) [
1]. Under physiological circumstances, the microtubule-associated protein tau (MAPT) plays an important role in binding and stabilizing microtubules, regulating axonal transport, interacting with filaments of the cellular cytoskeleton, and probably also contributes to DNA/RNA protection in the nucleus [
2]. In AD and non-AD tauopathies, though, the natively soluble and unfolded tau protein undergoes a conformational change via mechanisms such as hyperphosphorylation and misfolding, leading to diminished physiological functions of tau and its accumulation as NFT [
3‐
5]. Deposition of hyperphosphorylated tau in brain is associated with neuroinflammation [
5], which may exacerbate the ongoing tauopathy and amyloid-β accumulation, while aggravating neuronal degeneration [
4,
5]. Indeed, the neuroinflammation in AD shows spatial overlap with deposition of amyloid-β and NFT accumulation [
6]. Furthermore, particular components of the neuroinflammatory cascade promote the development of NFT [
7]. Importantly, the onset of neuroinflammation occurs early in tauopathies, suggesting that biomarkers of neuroinflammation might serve as a tool to predict the individual disease course [
8].
The transgenic P301S mouse model accumulates tau in the brainstem [
9‐
11], hippocampus [
10,
12], and cerebral cortex [
10], and this accumulation is accompanied by a decline in spatial learning [
12]. Immunohistochemical (IHC) analysis revealed increased microglial activation in transgenic P301S mice at 5 months of age, compared to findings in wild-type mice [
13]. Other studies demonstrate the capacity of wild-type mouse microglia to phagocytize NFTs accumulating in the brain of P301S mice [
14] and likewise in cultured neurons from P301S mice [
15], consistent with a dual role of microglial activation in exerting neuroprotective [
14] and neurodegenerative effects [
15]. However, the time course of microglial neuroinflammation and its net effect on neurodegeneration is not yet established in this mouse model of tauopathy.
Because understanding the role of neuroinflammation in AD and non-AD tauopathies is of crucial importance, we undertook longitudinal monitoring of microglial activation in P301S mice by means of
18F-GE-180 μPET in vivo, extending a technique we have established in amyloid-β mouse models. The tracer
18F-GE-180 binds to the 18 kDa translocator protein (TSPO) expressed in activated microglial cells in living mouse brain, showing excellent correlation with ex vivo validation in several different amyloid-β mouse models [
16‐
19]. We now aimed to test the predictive value of early microglial activation in this tau mouse model by undertaking serial
18F-GE-180 μPET until 6.4 months of age, augmented by analyses of spatial learning with the Morris water maze test (MWM) and glucose metabolism with
18F-fluorodesoxyglucose (
18F-FDG) μPET. Finally, we made an IHC examination of tau and microglia by AT8, IBA1, and CD68 antisera. Moreover, we compared the temporal kinetics of microglial activation of the tau mouse model with corresponding findings retrieved from our historical amyloid-β mouse model studies.
Discussion
We report the first longitudinal in vivo μPET imaging study of microglial activation together with assessment of multiple outcome parameters in a tau mouse model. Our data clearly indicate that μPET with the TSPO tracer 18F-GE-180 gives reliable assessment of microglial activation in living P301S mice, as proven by the high correlation with specific IHC markers. Analysis of individual TSPO μPET time courses to 6.4 months of age revealed that microglial activation in the tau model mice exponentially increases with age. Importantly, longitudinal elevations of TSPO expression in P301S mice predicted aggravated tau accumulation and worse performance in spatial learning. Levels of glucose metabolism at the late stage were positively associated with longitudinal TSPO μPET increases, but early elevations of TSPO expression predicted stronger hypometabolism in P301S mice. These findings may be reconciled by consideration of the ambivalent role of microgliosis in neurodegeneration, in some circumstances imparting neuroprotection, and in other circumstances marking a more aggressive pathology. This dual role is seemingly decided by the type of pathology (i.e., tau or amyloid-β over-expression) and the time course.
We show that transfer of TSPO μPET technology from different amyloid-β mouse models [
19,
22,
24] to the present tau mouse model is feasible without major caveats. As in some former studies [
16,
20], we successfully validated a suitable pseudo reference region for TSPO μPET in P301S mice, and we were again able to show that this methodology reduces variance at the group level. This SUVR approach supported the detection of robust longitudinal increases of TSPO expression in different target regions of the P301S mouse model, which were matched with increases of microglial activation markers measured later by IHC. Furthermore, our μPET data were validated by direct correlation with IHC at the terminal time point. Interestingly, the phagocytosis marker CD68, which indicated the highest association with TSPO μPET in our earlier study of amyloid-β mice [
19], significantly correlated with TSPO μPET values in the cortex but not in the brainstem of tau mice. Yet, the present correlation of
18F-GE-180 TSPO μPET with the more general activation marker IBA1 in the brainstem of tau mice could hinge on different microglia phenotypes and their covariance with TSPO expression in different brain regions [
25]. However, we note that several specific and random factors like regional blood flow or slice selection could also cause these divergent observations. Our findings are in line with those of a study conducting longitudinal μPET with the TSPO tracer
11C-AC-5216 in another tau mouse model (PS19), likewise showing time dependent progression of TSPO expression in the entorhinal cortex and the hippocampus [
26]. Another study of PS19 mice found microglial activation especially in the hippocampus to occur ahead of discernible tau accumulation and brain atrophy [
27]. This implicates that microglial activation can already be present in very early phases of AD, when seeding of tau just begins and is not identifiable by tau IHC yet. This also suggests that neuroinflammation could be triggered by non fibrillar components of tau, ending up in a vicious circle in the pathogenesis of AD. However, we note that many of the complex underlying mechanisms and interrelations are not completely discovered yet [
3,
5,
28]. Understanding the role of neuroinflammation in neurodegenerative disorders is of high importance as it is associated with deposition of NFT, amyloid-β, and neuronal degeneration. Translational imaging in mouse models and patients will facilitate to close important research gaps in terms of reciprocal validation and therapy monitoring.
As there have been no direct comparisons of the time courses of microglial activation between amyloid-β and tau mouse models, we put a special focus on contrasting longitudinal in vivo TSPO expression of P301S mice against existing data in two common amyloid-β mouse models. To account for natural progression of microglial activation in the aging brain of rodents [
17], we compared standardized differences (
z-scores) in relation to age among the different mouse models. By this approach, we are able to show for the first time that temporal kinetics of microglial activation differ depending on whether it is driven by tau or amyloid-β pathology. In particular, TSPO expression in response to tau pathology showed attenuated and delayed development when compared to TSPO expression in response to Aβ overexpression. Importantly, there were similar increases of the amounts of AT8 positive tau in P301S mice or fibrillar Aβ in APP/PS1 and
AppNL-G-F mice with age, indicating that the observed differences were not driven by variant time courses of protein accumulation. In the translational aspect, the onset of Aβ and tau aggregation may precede the start of clinical symptoms in human AD [
29], and associations of both proteins with microglial activation have already been shown in human PET studies [
6]. Thus, the presence of amyloid-β and tau should be considered (i.e., by PET or CSF) when interpreting time courses of microglial activation in human neurodegenerative disease, to avoid bias arising from differences in their temporal associations. Furthermore, more detailed studies comparing tau and amyloid-β mouse models employing next generation sequencing or proteomics should resolve possible differences of microglia phenotypes in relation to the two abnormal protein aggregates.
Details of the role and time dependence of neuroinflammation in AD remain a matter of controversy and debate, given the ambivalence of protective and detrimental aspects [
3,
28,
30]. This also accounts for some earlier findings on microglial function in the P301S mouse model. Luo et al. [
14] showed in vitro and ex vivo the capability of isolated wild-type microglia to phagocytize tau in brain tissue of P301S mice, implicating a possible protective effect of fully functional microglia. On the other hand, a recent study of Brelstaff et al. [
15] indicated that activated microglia can phagocytize neurons of P301S mice and therefore seemingly mediate deleterious effects. This matches with the setting that microglial cells can generally be separated into two classes, proinflammatory (mainly detrimental) and anti-inflammatory (mainly protective) phenotypes, and can presumably change from one state to another depending on the required function [
28].
The strength of our data lies in its longitudinal in vivo design, covering approximately three quarters of the 9-month lifespan of P301S model mice. The compilation of data indicates that higher longitudinal TSPO expression in P301S mice predict higher tau accumulation and worse spatial learning at 6.4 months of age. Interestingly, the corresponding associations with glucose metabolism to
18F-FDG μPET gave different predictions for baseline and longitudinal measures. While early elevation in TSPO expression was associated with hypometabolism at 6.4 months, we observed higher terminal glucose metabolism in tau mice with TSPO increasing over time. While the first result suggests an overall deleterious effect of high early TSPO expression on the outcome of P301S mice, the second observation is more consistent with a coupling of microglial activation and glucose metabolism, as observed previously in PS2APP mice [
16]. With regard to spatial learning deficits, our earlier study with congruent methodology and design in PS2APP amyloid-β mice showed that early microglial activation in the forebrain strongly correlated with better cognitive performance in MWM [
31]. Speculatively, this could indicate different predictive capability of TSPO μPET depending on whether tau or amyloid-β accumulation is the primary driver of microgliosis. Regarding tau mouse models, our observation of higher tau accumulation in mice with early microglial activation is in line with findings of associated tau and neuroinflammation in the forebrain of rTg4510 tau mice [
32]. Our data also fit with the observations of attenuated NFT accumulation, reduced neuronal degeneration, and averted cognitive deterioration after pharmacological ablation of senescent microglial and astroglial cells in PS19 mice [
33], as well as fitting with the increased tau pathology occurring along with NLRP3 inflammasome activation [
7]. In summary, tau-associated microglial activation seems more detrimental than amyloid-β-associated effects. Importantly, our compilation of findings of amyloid-β and tau mouse models may help support a model wherein the net effect of neuroinflammation changes from being initially protective (A+/T−) to deleterious in late phases (A+/T+) of AD [
34]. Among the limitations of our study, we note that we did not perform longitudinal TSPO-PET imaging in male mice. Thus, we cannot evaluate effects of sex on the current results. We acknowledge a gap of 1 week in average between the final PET scan and IHC which might has a limited impact on correlation analyses between both modalities since microglial activation in P301S mice raises with aging.
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