Translocator Protein-18 kDa (TSPO) Positron Emission Tomography (PET) Imaging and Its Clinical Impact in Neurodegenerative Diseases (original) (raw)

Abstract

In vivo exploration of activated microglia in neurodegenerative diseases is achievable by Positron Emission Tomography (PET) imaging, using dedicated radiopharmaceuticals targeting the translocator protein-18 kDa (TSPO). In this review, we emphasized the major advances made over the last 20 years, thanks to TSPO PET imaging, to define the pathophysiological implication of microglia activation and neuroinflammation in neurodegenerative diseases, including Parkinson’s disease, Huntington’s disease, dementia, amyotrophic lateral sclerosis, multiple sclerosis, and also in psychiatric disorders. The extent and upregulation of TSPO as a molecular biomarker of activated microglia in the human brain is now widely documented in these pathologies, but its significance, and especially its protective or deleterious action regarding the disease’s stage, remains under debate. Thus, we exposed new and plausible suggestions to enhance the contribution of TSPO PET imaging for biomedical research by exploring microglia’s role and interactions with other cells in brain parenchyma. Multiplex approaches, associating TSPO PET radiopharmaceuticals with other biomarkers (PET imaging of cellular metabolism, neurotransmission or abnormal protein aggregates, but also other imaging modalities, and peripheral cytokine levels measurement and/or metabolomics analysis) was considered. Finally, the actual clinical impact of TSPO PET imaging as a routine biomarker of neuroinflammation was put into perspective regarding the current development of diagnostic and therapeutic strategies for neurodegenerative diseases.

Keywords: microglial activation, neuroinflammation, PET, radiopharmaceutical, TSPO, neurodegenerative diseases, psychiatric disorders

1. Microglia

Microglial cells are the resident macrophages of the central nervous system (CNS) that play different roles in both physiological and pathological conditions, by maintaining brain parenchyma integrity and involving in a wide range of neurodegenerative diseases. Microglia represent approximately 5–15% of all cells in the human brain [1,2]. The brain homeostasis is achieved in part though the ability of microglia to regulate inflammation, such as cytotoxicity, repair and regeneration [3]. In parallel to their well-known immune-modulatory functions, microglia are highly dynamic cells which contribute to the synaptic remodelling/plasticity as well as synaptogenesis, synaptic transmission and pruning [4].

Several cellular actors including neurons, astrocytes, T-cells and the blood brain barrier (BBB) modulate microglial function and form a very dynamic network [5]. In particular, microglia have been proposed to act as sensors, effectors and injury recipients of the brain homeostasis breakdown [6]. In fact, upon injury, various afferents stimuli (e.g., soluble factors, cellular interactions [7,8]) induced morphological (i.e., amoeboid, rod, multi-nucleated, epithelioid or dystrophic state) and functional changes of microglia, known as microglial “activation” [6,9].

In front of homeostatic disturbances (e.g., vascular or tissue damage), microglial cells shift from sensing activity to a reactive state. Originally based on peripheral monocytes/macrophages, the reactive phenotype of microglial cells is dichotomized into “classical activation” or M1, pro-inflammatory and “alternative activation” or M2, anti-inflammatory reactions. According to this concept, microglia phenotypes are defined by triggering responses to cytokines and microbial agents. In fact, interferon-γ from T helper cell type 1 (Th1) causes M1 activation, a response usually associated with the struggle against intracellular pathogens. In M1 state, macrophages release pro-inflammatory cytokines such as IL-1β, IL-6, TNF-α or ROS/RNS. On the other hand, the secretion of IL-4 or IL-13 from Th2 promotes M2a polarization and supports tissue repair/regeneration. M2b cells are induced by the immune complex, secrete IL-10 and regulate the immune response [10]. When macrophages release TGF-β or IL-10 (M2c reaction), anti-inflammatory effects are observed [7,11]. Microglia polarization/action is a process highly context-dependent [12] (nature of activating stimulus; e.g., PAMPS and/or DAMPS) which is integrated in a time-dependent fashion (acute versus chronic injury) [6].

2. TSPO as a Target of Activated Microglia PET Imaging

2.1. TSPO

First described as a peripheral benzodiazepine receptor (PBR), the translocator protein-18 kDa (TSPO) has been fortuitously identified by Braestrup et al., using rat kidneys as a control tissue during central benzodiazepine receptor (CBR) binding studies using [3H]-diazepam. This secondary binding site for diazepam, which is distinct in its structure from the CBR, was shown to be abundantly distributed in peripheral tissues [13]. It has been renamed as 18-kDa translocator protein (TSPO) to better reflect the cellular functions and tissue distribution of this protein [14]. TSPO is a highly hydrophobic five transmembrane domain protein mainly situated in the outer mitochondrial membrane. TSPO is widely distributed in most peripheral organs including kidneys, nasal epithelium, adrenal glands, lungs and heart, whilst the highest concentrations are in the steroid producing tissues; is also minimally expressed in resting microglial cells in the healthy brain [15]. Although modestly expressed in healthy brain parenchyma, TSPO is substantially upregulated predominantly in microglia cells in a number of neurodegenerative and neuroinflammatory diseases during the microglia activation process [16]. In addition to activated microglia, Lavisse et al. showed that reactive astrocytes could also overexpress TSPO using a model of selective astrocyte activation in the rat striatum [17]. Likewise, after brain injury induced by focal cerebral ischemia, both microglia and astrocytes have been found to overexpress TSPO [18], with a dissimilar distribution within the infarcted lesion. Thus, astrocytes were mainly observed in the rim surrounding the lesion core, whereas microglia were abundant in the core of infarction [19]. Furthermore, cells of the mononuclear phagocyte lineage, such as peripheral macrophages, also express the TSPO and, in the case of a disrupted BBB, also infiltrate the damaged CNS due to the vascular permeability increased by neuroinflammation [20].

TSPO is thought to be involved in a wide array of vital cellular functions including porphyrin transport and heme synthesis, regulation of cell proliferation, steroid biosynthesis and programmed cell death [21]. TSPO’s functions in metabolic homeostasis remain unclear, especially in the supra-physiologic stimulation of microglia. Most studies point out that high TSPO expression attenuates ROS generation [22,23]. Gatliff and Campanella [24] recently specify to what extent TSPO drives the mitochondrial quality control. Indeed, more than TSPO (over)expression, it seems to be the expression ratio of TSPO to VDAC1 (voltage-dependent anion channel 1) that regulates ROS production. Subsequently, this ROS generation leads to an accumulation of defective mitochondria due to an ineffective mitophagy PARK2-dependent mitochondriopathy [24], which is involved in several neurodegenerative diseases such as Parkinson’s disease (PD) [25], Huntington’s disease (HD) [26] and Alzheimer‘s disease (AD) [27]. Others authors suggest a role of TSPO in oxidative stress by directly facilitating the breakdown of porphyrin [28]. The use of TSPO ligands in rodent models of neuroinflammation (e.g., kainic acid excitoxicity [29] or intracerebroventricular infusion of lipopolysaccharide (LPS) [30]) highlighted TSPO’s involvement in hippocampal gliosis and especially in microgliosis.

The colocalization of TSPO upregulation and activated glia has been observed in human degenerative disorders including AD, PD, multiple sclerosis (MS), (HD) [31] and amyotrophic lateral sclerosis (ALS) [32]. As a result, this increased density of TSPO in CNS diseases has been considered to be a relevant and an early biomarker to evaluate neuroinflammation over disease progression [33].

Positron Emission Tomography (PET) imaging of microglia has widely grown over the last 25 years, through the development of radiopharmaceuticals targeting several molecular biomarkers of microglial activation. In this context, many biological targets of neuroinflammation for both diagnosis and therapeutic purposes have been identified. Among them, TSPO has become the reference molecular biomarker for microglia PET imaging. Thus, TSPO PET imaging has been used for both improving the knowledge regarding the role of neuroinflammation in CNS diseases and to assess the efficacy of novel anti-inflammatory therapeutic strategies. Yet, the upregulation of TSPO PET radioligands’ binding is not discriminant between activated microglia, astrocytes and infiltrated macrophages. Indeed, in AD, Venneti et al. [34] observed that astrocytes are not a negligible factor in the increased TSPO PET radioligand binding. Moreover, TSPO overexpression in both astrocytes and microglia seems to be temporally distinct depending on the stage of disease and the disease itself [35]. Thus, TSPO PET imaging is not selective of microglia activation, but depicts a broader multicellular inflammatory reaction.

In this section, we summarize the progress being made in both the involvement of microglia in various neurologic conditions and the understanding of microglial activation in CNS disorders thanks to TSPO PET molecular imaging.

2.2. TSPO PET Tracers

A wide variety of endogenous compounds like diazepam, cholesterol or porphyrin interacts with TSPO at distinct binding sites. Because of the availability of high affinity and selective ligands, which can be labeled with various radioisotopes (11C, 18F), the distribution of TSPO can be visualized with PET technique. Historically, the benzodiazepine 11C-Ro5-4864 was the first ligand able to discriminate peripheral from central benzodiazepine receptors. Then, the most widely used TSPO PET radiopharmaceutical, namely 11C-(R)-PK11195, an isoquinoline carboxamide developed in the early 1980s, was the first non-benzodiazepine type compound identified to bind to TSPO with high affinity (human Kd = 2 nM) [36]. However, 11C-(R)-PK11195 clinical usefulness is narrowed by several major limitations, including the short half-life of carbon-11, a low brain bioavailability and a poor signal-to-noise ratio due to high nonspecific binding [37]. To counteract these drawbacks, there has been a great effort for the development of second generation TSPO PET radiotracers [38,39,40], including phenoxyarylacetamides derivatives labeled with carbon-11 (11C-PBR28, 11C-DAA1106) or fluorine-18 (18F-FEPPA, 18F-PBR06), imidazopyridines derivatives (11C-CLINME) and pyrazolopyrimidines derivatives (18F-DPA-714). Indeed, a single nucleotide polymorphism in the TSPO gene (rs6971) leading to an amino-acid substitution (A147T) has shown to be the cause of binding affinity properties variation with a huge heterogeneity in PET images and their associated quantitative data. The fact that the second-generation radiopharmaceuticals have been found to be sensitive to this polymorphism leads searchers to develop rs6971-insensitive radioligands. These rs6971-insensitive radioligands, called third generation TSPO tracers, include 11C-ER176 [41] and flutriciclamide (18F-GE180) [42]. Nonetheless, the clinical relevance of these compounds remains to be confirmed [41].

TSPO PET tracers have been investigated in various preclinical and clinical studies and we have now reported major advances provided by the development of new tracers (Table 1).

Table 1.

A summary of the different generation of TSPO radiotracers from Vivash and O’Brien [43].

Chemical Class	Radioligand	Advantage	Limitation	Generation
Isoquinoline carboxamide	11C-PK11195	rs6971-insensitive		First
Indole acetamides	11C-SSR180575		rs6971-sensitiveReproducibility in humansShort half-time 11C	Second (11C)
Vinca alkaloids	11C-vinpocetine
Phenoxyarylacetamides	11C-PBR28	Cerebellum validated as a reference region
11C-DAA1106
Imidazopyridine acetamides	11C-DPA713
Imidazopyridines	11C-CLINME
Dihydro-9_H_-purinacetamides	11C-DAC
11C-AC-5216
Phenoxyarylacetamides	18F-FEDAA1106	Longer half-time than 11CImproved signal-to-noise ratio	rs6971-sensitiveReproducibility in humans	Second (18F)
18F-PBR06
18F-FEPPA
Imidazopyridine acetamides	18F-PBR111
Pyrazolopyrimidines	18F-DPA-714
Isoquinoline carboxamide	11C-ER176	“rs6971—less sensitive in vivo than 2G”		Third
Tetrahydrocarbazole	18F-GE180	rs6971-insensitive

3. Clinical Input of TSPO PET Imaging in Neurodegenerative Diseases

3.1. Parkinson’s Disease and Related Syndromes

Parkinson’s disease (PD) is a common age-related neurodegenerative disorder that mainly affects the motor system. Symptoms include resting tremor, asymmetrical bradykinesia and muscular rigidity. PD results from the progressive degeneration of dopaminergic neurons, initially in the substantia nigra, which causes a clinical parkinsonism when the loss of the striatal dopamine reaches to 60% [44,45,46]. PD is neuropathologically characterized by a neuronal rarefaction in the substantia nigra pars compacta and the presence of neuronal Lewy bodies (LB) inclusions, which are abnormal aggregates of α-synuclein [47]. Since the discovery of activated microglia in a post mortem study of PD brains, objectified by a large amount of HLA-DR-positive microglial cells in the locus niger, “neuroinflammation” became one of the main culprits in the pathogenesis and in the progression of PD [48]. Correlation analysis between TSPO tracer binding potential values and clinical parameters show that microglial activation PET imaging should predict the symptom severity, but only in early-stage PD patients (Table 2) [49,50,51]. Indeed, the nigral 11C-PK11195 accumulation was significantly positively correlated with the motor severity of the UPDRS assessment (unified Parkinson’s disease rating scale) in drug-naïve PD patients [49]. In addition, PD patients presented significantly increased 11C-PK11195 uptake in the basal ganglia (striatum and pallidum), thalamus, brainstem and frontal, temporal and cortical regions [51,52]. This TSPO overexpression in different cerebral regions supports the notion that microglial activation is not confined to nigrostriatal dopaminergic neurons within PD pathophysiology. Moreover, identified by positive CD68 immunoreactivity, amoeboid activated microglial cells were identified in both the striatum and the hippocampus of PD patients, suggesting that an inflammatory response occurs to the active α-synuclein pathology in the hippocampus area [53]. Furthermore, TSPO PET imaging shows that the microglial shift, from a sensing to a reactive state, takes place at the early stage of PD [49,54] and can occur even without dementia [52,55]. This was corroborated by reported data from a rat model of PD, where the activation of microglia seems to precede dopaminergic neuronal cell loss [56]. Given the fact that a chronological spread of LB inclusions occurred in α-synucleinopathies [57], and these α-synuclein can directly provoke microglial activation [58], we could expect to find, in a time-dependent fashion, a widespread TSPO signal in PET imaging. Interestingly, Gerhard and colleagues [51] reported a lack of change in levels of cortical and subcortical TSPO tracer uptake for two years, despite the clinical deterioration of PD patients. Similarly, microglia TEP imaging followed-up with a second generation of TSPO radioligand (11C-DPA713) also failed (in ROI—Regions of interest—analysis) to show increased tracer binding at one year in earlier stage PD patients [55]. Therefore, microglial activation assessed by TSPO PET imaging seems to be relatively static over time in PD, and only microglia phenotypes may change with the disease progression.

Table 2.

PET imaging studies assessing TSPO tracers in parkinsonian disorders.

Multiple system atrophy (MSA) is another form of atypical parkinsonism in which overlapping symptoms as well as tremor, akinesia and rigidity are associated with autonomic failure and cerebellar dysfunction. In contrast to PD, the accumulation of α-synuclein fibrils leads to the generation of glial cytoplasmic inclusions (GCI) which affects mostly the oligodendroglia rather than neurons [59].

In MSA patients, significantly increased 11C-PK11195 uptake has been observed in the dorsolateral prefrontal cortex, putamen, pallidum, pons and substantia nigra, reflecting the known distribution of microglial and neuronal lesions in MSA [66]. Additionally, TSPO is overexpressed in the white matter of MSA and Progressive Supranuclear Palsy (PSP) patients [61]. In MSA, these results appear to echo the findings of neuropathological studies and could reflect the demyelination process which predominantly affects the MSA-C variant [67]. Unlike the PD scenario progression, microglial activation in a mouse model of MSA-like neurodegeneration occurred parallel to the dopaminergic neuronal loss in the locus niger [68]. Remarkably, the analysis of histopathological patterns of MSA brains revealed that the amount of GCIs and the level of microglial activity is reduced especially since the tissue injury becomes severe in white matter areas, unlike gray matter areas [69]. If we generalize this concept of microglial (down/up)-regulation according to lesion severity in MSA, that could explain that 11C-PK11195 binding increased in the thalamus or decreased in the substantia nigra after 24 weeks of active disease, compared to baseline [63].

Apart from α-synucleinopathies, tauopathies such as PSP and corticobasal degeneration (CBD) belong to parkinsonian disorders. In addition to parkinsonism, the clinical features of PSP include early falls and abnormal eye movements (vertical supranuclear gaze palsy) [70]. The hallmark of PSP comprises the deposition of 4-repeat (4R) tau protein in neurofibrillary tangles and neuropil threads that are found in the basal ganglia and brainstem [71].

In vivo microglia imaging showed increased 11C-PK11195 binding in basal ganglia, thalamus, midbrain, substantia nigra, pons, cerebellum and frontal lobe in PSP patients [51]. A post mortem study by Fernández-Botrán et al. [72] specified that the high degree of correlation between microglial activation, tau burden and the areas of degeneration (substantia nigra and subthalamic nucleus) previously described [73], involves a high expression level of IL-1β. Although the involvement of microglial activation as etiology or consequence remains unclear, these results suggest that there is an M1 reactive phenotype of microglial cells at a point of PSP progression. Similar to PD, while PSP patients clinically declined over 6 to 10 months, there were no significant changes in TSPO PET imaging [51].

CBD is a rare neurodegenerative tauopathy in which the hyperphosphorylated 4R tau deposits concern neurons and glia, in both the cerebral cortex and the basal ganglia. In CBD, a recent report supports that astrogliopathy precedes neuronal loss, which leads to clinical symptoms as well as asymmetrical akinetic-rigidity, apraxia, disequilibrium and limb dystonia [74]. Elevated 11C-PK11195 binding in the striatum, thalamus and substantia nigra [64,65] is in consonance with neurological injury patterns in CBD [73,75], especially tau load [74]. Besides the diagnostic interest of PET, molecular imaging has also been used as a tool to evaluate treatment efficacy in neurodegenerative disorders [60,62,63].

3.2. Huntington’s Disease

Huntington’s disease (HD) is an autosomal dominant inherited trinucleotide (CAG) repeat neurodegenerative disorder in which the age at onset is inversely correlated with the size of the polyglutamine repeat expansion [76]. This feature allows for the dichotomization of HD patients into premanifest HD, i.e., gene carriers are clinically asymptomatic, and manifest HD, that is to say, after motor onset of the disease [77]. This mutation in the exon 1 of the gene encoding the Huntingtin protein (HTT) leads to a mutant HTT (mHTT) which is expressed by peripheral monocytes of premanifest HD patients [78], and induces both a loss of function (e.g., regulating intracellular transport, controlling apoptosis pathway) and a gain of toxic functions (e.g., abnormal protein-protein interaction, promoting pro-inflammatory cytokines) [79,80]. HD is neuropathologically characterized by the formation of intranuclear inclusions of mHTT [81] resulting in striatal, cortical and hypothalamic atrophy [82,83] which are associated with an accumulation of reactive microglia in these same regions [31,84]. In line with these findings, in vivo microglia PET imaging showed an overexpression of TSPO in the striatum [84,85,86,87,88] ,cortical regions [85,87,88,89] and hypothalamus [87,88] (Table 3). According to lesion topology, which even depends on the stage of HD, symptoms include motor troubles (chorea, parkinsonism), cognitive decline (slowed mentation, impaired strategy) and psychiatric disorders (mood, irritability, apathy, depression) [77,90]. To such an extent, microglial activation seems to begin in cognitive regions, especially in associative striatum and correlated with cognitive dysfunction [88]. Moreover, striatal 11C-PK11195 binding is strongly correlated with the five-year probability of disease onset in asymptomatic HD gene carriers [86,88]. Furthermore, in manifest HD patients, the correlation between striatal TSPO tracer binding and the severity of motor symptoms (evaluated by the unified Huntington’s disease rating scale) [85,88] could echo the ex vivo relationship found between neuronal loss and density of reactive microglia [84]. Although HD is a monogenic disease, recent studies revealed that different genes, distinct from the HD locus itself, could change disease manifestation and progression [91]. We hypothesize that these genetics and thus clinical features could explain the difference in microglial activation, objectified by ventral striatum TSPO tracer binding variability in premanifest HD patients [88,89].

Table 3.

PET imaging studies assessing TSPO tracers in Huntington’s disease.

3.3. Dementia

Alzheimer’s disease (AD) is the most prevalent neurodegenerative cause of dementia and is characterized by amnesic memory impairment, language deteriorate and behavioral changes due to cognitive decline [92]. The neuropathological hallmarks of AD include extracellular peptide amyloid β (Aβ) forming neuritic plaques and neurofibrillary tangles (NFTs) of intraneuronal deposits of hyperphosphorylated/misfolded tau proteins. Each of these lesions has a characteristic distribution during the evolution of AD and has a more or less strong clinicopathological correlation. A transcellular propagation of abnormal tau proteins [93] and Aβ [94] occurred in AD. Regarding the neurofibrillary degeneration, it starts in the entorhinal cortex and then spreads to synaptically connected brain areas such as the hippocampus/limbic system, and finally affects the frontal and parietal lobes (i.e., associative isocortex) [95]. The amount and the topography of these NFTs match with the neuronal loss and correlate with the severity and the duration of dementia as well as lesions topology (e.g., neocortex, limbic system) is in consonance with the clinical features of AD (e.g., cognitive impairment) [96]. Moreover, tau hyperphosphorylation seems to be promoted by a pro-inflammatory environment (e.g., IL-6 release [97]) and may support microglial activation [98], highlighting the vicious circle of tauopathy’s process in AD (for review, see Calsolaro et al., 2016 [99]). Microglia PET imaging supported these experimental results. Indeed, microglia PET imaging revealed greater radioligand uptake in AD patients than in healthy controls in the same regions which are sequentially affected by neurofibrillary degeneration: entorhinal cortex [100,101,102], hippocampus [101,103,104], frontal [103,104,105,106] and parietal cortex [100,101,103,104,105,106,107,108,109,110] (Table 4). Longitudinal studies exhibited an increase in cortical-activated microglia during the course of AD [101,103,110]. Similarly, cross-sectional post mortem studies using the temporal neocortex of 40 AD subjects with a symptom duration ranging from 4 to 20 years showed a significant positive association between CDC68+ microglia and symptom duration [101]. Comparison in TSPO density between mild cognitive impairment due to AD (MCI) and AD dementia yielded ambiguous results: significant difference was found between the two groups [101,102,109] or was absent [110,111,112] according to different studies. MCI represents a diagnostic entity for the transition between normal aging and AD dementia [113]. Analogous to Aβ and tau that has already accumulated in the brain of MCI patients [114], PET imaging showed that microglial activation occurred before the onset of clinical symptoms of dementia [108,110,115]. These results are consistent with the presence of neuroinflammatory biomarkers in the cerebrospinal fluid of pre-symptomatic AD subjects [116]. Nevertheless, some studies provided contradictory results [109,111,112].

Table 4.

PET imaging studies assessing TSPO tracers in dementias.

Unlike NFTs, amyloid plaques deposition showed a lesser stereotypical spatiotemporal pattern of progression; they accumulate mainly in the isocortex, and the amyloid burden does not correlate with the severity or the duration of dementia [117,118]. Supported by various biomarker-autopsy correlation studies, Jack et al. [119] proposed that AD biomarker curves assume a sigmoidal shape as a function of time, involving a threshold effect and a late deceleration of tau and Aβ loads. With current data on microglial activation, it seems difficult to give a similar trend to the progression of neuroinflammation in AD dementia. However, microglial activation states obviously play a significant role in aging and age-related disease, especially in AD. Aβ (both, soluble [120] and fibrillary [121]) can bind to several Toll-like receptors (TLR) and co-receptors expressed on microglia, leading to its activation [122] and promoting the formation of clusters of activated microglia surrounding amyloid plaques in AD brains [123]. In line with these ex vivo findings, TSPO PET imaging showed higher microglial activation in various cortical regions known to be the seat of Aβ deposits [124] (e.g., prefrontal [104,107,108], temporal [100,101,102,104,105,106,107,108,109,125], occipital [101,104,105,107,108,125], precuneus [101,109,110], cingulum [100,104,110]) in AD dementia patients, compared to healthy subjects. This Aβ-induced inflammatory environment [126], combined with effect of immunosenescence on microglia [127,128], lead to a situation in which microglia that initially exhibited a neuroprotective M2 phenotype at the beginning of AD [129], become confined to a classical activated state (i.e., M1) with strongly reduced Aβ-clearing capabilities in the advanced stage of AD [7].

Correlation analysis between TSPO tracer binding and AD severity provided heterogeneous findings. In most studies, in parallel to cognitive deterioration, objectified by a decreased MMSE score [105,106,125] or increased CDR-SB [101,109], TSPO expression density in cortical regions was linearly raised. To the same extent, Kreisl et al. [101] exhibited that early onset AD (EOAD) patients presented significantly higher 11C-PBR28 than later onset AD (LOAD) patients, both at baseline and follow-up. This overexpression of activated microglia in more active AD (i.e., early onset) may confer on it the status of a deleterious process. Other studies found no link [105,108,109,113]. Conversely, one of the surprising results of the study of Hamelin et al. [110] is that MMSE scores correlate positively with TSPO tracer binding. Moreover, the radioligand (18F-DPA-714) GCI was greater in slow decliners than in fast decliners, suggesting an early neuroprotective effect of microglial activation in AD.

In light of such antipodic findings, we cannot exclude the fact that TSPO PET imaging has limited abilities to robustly reflect microglial activation in AD. In fact, Banati et al. [33] suggested that the overexpression of TSPO in activated microglia may be related to structural changes in mitochondria due to morphological changes in microglial cells. On the basis of that postulate, we hypothesize that the profound morphological deterioration of microglial cells which occurred in AD [128] could be a source of signal variability in TSPO PET imaging.

Frontotemporal lobar degeneration (FTLD) is a clinically, pathologically and genetically heterogeneous syndrome characterized by progressive clinical features such as behavioral and personality changes, cognitive decline and parkinsonism [137]. These symptoms result from progressive neurodegeneration and, ultimately, focal atrophy of the frontal and temporal cortex in which inclusions of hyperphosphorylated tau protein in neurons and glial cells (FTLD-tau) and inclusions of TDP-43 (FTLD-TDP) compose the two main histopathological hallmarks of this disease [138]. FTLD has a strong genetic component; mutations causing FTLD include MAPT (microtubule-associated protein tau) and progranulin [139]. Interestingly, proganulin is expressed by activated microglia [140] and polarizes microglial cells into M2 anti-inflammatory phenotypes [130], suggesting that microglia polarization deficiency could play a role in FTLD. Indeed, Cagnin et al. [133] demonstrated an enhanced uptake of tracer (11C-PK11195) in the typically affected frontotemporal regions. Two MAPT pre-symptomatic gene carriers exhibited microglial activation in either, posterior cingulate cortex, region which sends projection to the superior temporal sulcus, or in the medial frontal cortex [131]. Elevated putaminal uptake of TSPO tracer in frontotemporal dementia patients [130] is consistent with the neuropathological (involvement of the basal ganglia [141]) and clinical features (parkinsonism [142]) of FTLD.

3.4. Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a rare adult-onset neurodegenerative disorder in which upper and lower motor neurons degenerate leading to progressive muscle paralysis then respiratory failure with a fatal outcome, typically within 2–4 years from onset [143]. This motoneuropathy that occurred from 5% to 20% in a positive family history of ALS, fronto-temporal demence (FTD) or both, results in fasciculation, cramps, muscle atrophy associated with hyperreflexia and spasticity [144,145]. Central inflammation has been proposed to play a role in the motor neuron death process in ALS [146]. TSPO PET imaging supported this assumption. Indeed, ALS patients presented significantly greater TSPO tracer binding in motor cortex than healthy volunteers [32,147,148]. Moreover, “microgliopathy”, assessed by CD68- and Iba1-reactive microglial cells, correlated with the disease progression and is linked to the severity of upper motor neuron deficits in the corticospinal tract of ALS patient autopsies [149]. These ex vivo findings were clinically sustained by PET studies, where TSPO expression density was correlated with motor symptoms severity, assessed by the UMND (Upper Motor Neuron Disorders) score [32,147] (Table 5). Interestingly, the one study that described an elevated TSPO radioligand uptake (11C-PBR28) in the brainstem of bulbar-onset ALS patients was also the one in which a statistical correlation was found between SUVr values and ALSFRS-R (revised ALS functional rating scale) [147]. Given the fact that this functional scale is more accurate to evidence lower motor neuron involvement [32], this association is probably due to the fact that microglial activation in the brainstem could reflect inflammation around the lower motor neurons of the cranial nerves [147]. The murine model of ALS, in which microglial cells overexpressed mutant-superoxide dismutase (mSOD1), the main cause of non-sporadic ALS, point out the pathogenic role of microglia in ALS; mutant protein may be more involved in disease progression than in its initiation [150]. Inversely, activated microglia in the temporal region could be involved in the early stage of ALS [148], and then progressively decrease. Indeed, this cerebral area was not affected in ALS patients with a more advanced stage [32,147]. Like AD dementia, a switch from the classically activated M1 phenotype to the alternatively activated M2 microglial state takes place during the progression of ALS disease [151,152].

Table 5.

PET imaging studies assessing TSPO tracers in amyotrophic lateral sclerosis.

3.5. Psychiatric Disorders

Bipolar disorder (BD) is a chronic mood trouble in which episodes of elevated mood and manic state are typically alternated with major depressive access, interspersed by euthymic periods [153]. Although the pathophysiology of this severe mental illness remains to be elucidated, a large body of literature suggests that several pathophysiological processes may sequentially and/or concurrently occur in BD, as well as corticolimbic control circuits deterioration, monoaminergic neurotransmission imbalance or microglia homeostasis disruption (for review, see Sigitova et al., 2016 [154]). Among these, hippocampal neuroinflammation, assessed by enhanced 11C-PK11195 binding compared to healthy subjects [155], could echo the change in the cytokines pattern’s profile (TNF, IL-1, IL-2 and IL-6) of BD-I patients [156] (Table 6).

Table 6.

PET imaging studies assessing TSPO tracers in psychiatric disorders.

Major depressive disorder (MDD) is a highly prevalent condition, affecting nearly 4% of the adult population [157], which could complicate neurodegenerative disorders (e.g., MS [158], PD [159]) or be isolated, without comorbidities. Although this depressive disorder mainly concerns mood disturbance, clinical features include a large range of symptoms as cognitive deficits, vegetative impairment (e.g., loss of appetite, sleeping difficulties) or behavioral deterioration (e.g., anhedonia, suicidal ideation). Several data, such as the association between central inflammation and depression-like symptoms in rodents [160], abnormalities in peripheral cytokines of depressed patients [161], or association between interferon alpha in the context of hepatitis C and depressive symptoms [162], have led some investigators to propose a microglial dysregulation theory for MDD etiology [163]. Nevertheless, post mortem studies have questioned this assumption. Indeed, no evidence of microglial activation was found in the brain of MDD patients [164,165,166]. In line with these results, microglia PET imaging did not reveal any statistical difference in 11C-PBR28 binding between healthy volunteers and patients with mild to moderate depression [167]. However, Setiawan and colleagues [168] recently found increased microglial activity (18F-FEPPA, VT, total distribution volume) in the anterior cingulate cortex of MDD patients, the region known to be implicated in the modulation of emotional behavior [169]. Moreover, this PET imaging result was correlated with the MDE (major depressive episode) severity, objectified by a 17-item Hamilton depression rating scale (HDRS) score [168].

Apart from epidemiological [178] and genetic [179] evidences of overlap between BD and schizophrenia (SCZ), molecular imaging of microglia of these psychiatric disorders also share some similarities, especially hippocampal TSPO overexpression compared to normal controls [155,172]. SCZ is a chronic early adult-onset psychiatric disorder in which symptoms are typically divided into positive (e.g., hallucinations), negative (e.g., affective flattening, alogia) and cognitive (e.g., concentration and memory impairment) [180]. Multiple lines of evidence from immunohistochemical cell counting studies to clinical trials of a non-selective microglial inhibitor support the fact that microglia is involved in the pathophysiology of SCZ [181]. Nevertheless, as with post mortem studies [182], microglia PET studies provided conflicting results. Indeed, some studies revealed significantly higher TSPO radioligand binding in SCZ patients in total gray matter [171,175], especially in the frontal and temporal lobes [175] and the hippocampus [172] than in controls subjects. However, other studies found no clear difference between normal controls and SCZ patients in various brain regions [173,174].

Neuroinflammation imaging in psychiatry is in an early stage, and there is much more to investigate (for review, see Slifstein and Abi-Dargham, 2016 [183]), especially regarding TSPO imaging. Indeed, there is evidence that the dysregulation of steroidogenesis by TSPO is associated with psychiatric disorders. For instance, an association has been found between rs6971 polymorphism in the TSPO gene and the diagnosis of BD [184].

3.6. Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease of the CNS in which migration of myelin-reactive T-cells into the CNS is followed by astrocyte and microglial activation, recruitment of peripheral macrophages and oligodendrocyte destruction, resulting in focal and diffuse demyelination [185,186]. The clinical presentation of MS as well as symptoms produced by the episodes of neurologic dysfunction (i.e., “attacks” or “relapses”) are heterogeneous. Regarding the symptoms of MS, tingling, weakness, vision loss, incoordination or bladder dysfunction may occur and depend upon the site of neurologic involvement. As regards the clinical picture, the most typical form at the onset of the disease is relapsing-remitting MS (RRMS), which is characterized by attacks interspersing with neurologically stable periods. Over several years to decades, RRMS shifts into secondary progressive MS; the recovery between relapses becomes partial and gradually provokes persistent symptoms which lead to irreversible disability. Only a minority of patients (~10–20%) experience insidious worsening without acute attacks, a clinical course known as primary progressive MS (PPMS) [187,188]. The major substrates of the disease progression include demyelinated cortical lesions, diffuse cortical and deep gray matter degeneration [189], which are associated with the chronic activation of microglia [190,191,192]. Microglia play a central role in maintaining the central chronic inflammation in MS [193,194], to the extent that its presence and distribution in the plaques allow for the neuropathological classification of the nature of the white matter lesions (i.e., active versus inactive) in secondary progressive multiple sclerosis (SPMS) [195].

Although the clinical and/or MRI discovery of dissemination of the lesions in time and space remains the cornerstone of MS diagnostics, TSPO PET imaging could be a promising technique to diagnose MS or to detect the conversion of RRMS to SPMS. In light of the limits of clinical assessment (e.g., measuring EDSS, expanded disability status scale) [196] and MRI parameters [197] to predict the progression of MS, TSPO PET studies have shown hopeful findings (Table 7). Indeed, activated microglia in SPMS relative to RRMS are characterized by both specific and more diffuse distribution in cortical regions [198] as well as greater TSPO radiopharmaceutical uptake, especially in the thalamus [199,200] and deep gray matter [200]. Provided that these results will be replicated in larger cohorts, it paves the way to early intervention in MS, thanks to TSPO PET imaging, in order to prevent or efficiently treat SPMS. At the upstream level in the disease history, Giannetti and colleagues demonstrated in clinically isolated syndrome (CIS), the prodromal state of MS, that patients who developed MS at two years had higher 11C-PK11195 binding at baseline, especially in normal-appearing white matter (NAWM) [201]. Analogous to the relationship between MCI and AD, we hypothesize that NAWM TSPO tracer uptake of CIS subjects could allow for the establishment of an _x_-year probability of disease (i.e., MS) onset. This significant increase in NAWM TSPO density, compared to healthy volunteers, has also been found in RRMS [200] and SPMS patients [200,202]. In addition to detecting activated microglia in areas of the brain which appear normal in MRI, the NAWM, TSPO PET imaging could predict the development of some gadolinium-enhancing lesions. In fact, increased focal 11C-PBR28 binding in an area of NAWM at the time of the PET scan corresponded to a contrast-enhancing lesion at a follow-up MRI exam one month later, as was found in two MS patients, suggesting a role for early microglial activation in MS lesion formation [203]. Apart from the fact that microglial activation may precede MS lesions, and that there is a greater TSPO radioligand uptake in RRMS than in SPMS, a body of evidence gives a deleterious status of activating microglia in MS. Among these, RRMS patients who had the greatest number of relapses (i.e., more clinically active) also had the highest 11C-PK11195 binding potential [198,204]. Furthermore, association analysis revealed that TSPO tracer binding levels in various brain regions correlated positively with both MS score severity (e.g., EDSS) [198,200,205,206] and disease duration [199,203]. This set of results is in consonance with post mortem studies in which severe cortical microglia activation and demyelination are associated with a pejorative outcome [207,208,209]. Nevertheless, some microglia PET studies provide conflicting results in terms of the association analysis in either EDSS [210,211] or disease duration [204,210].

Table 7.

PET imaging studies assessing TSPO tracers in multiple sclerosis.

Ratchford and colleagues [204] provided proof of the concept that microglia PET imaging with 11C-PK11195 could also be a tool to assess disease-modifying drugs for RRMS efficacity. Indeed, radiopharmaceutical binding potential per unit volume was statistically decreased in the whole brain after one year of glatiramer acetate. This result supported the in vitro evidence of its mechanism of action in which an inhibition of transformation to an activated microglia form could be responsible for therapeutic effects [212].

4. Multiplex Approaches to Improve TSPO PET Imaging Significance

TSPO molecular imaging provides valuable information such as presence, intensity and localization of the microglia activation, but this uniparametric approach might be considered as one component of a multiplexed strategy. Indeed, TSPO imaging combined with further PET targets, imaging techniques (e.g., MRIf), or even biology, could allow for a deeper understanding of the role of activated microglia in neurodegenerative disorders. We organize this section into; first, unimodal approaches, that is to say, TSPO PET imaging coupled with other PET radiopharmaceuticals; and second, multimodal approaches associating microglia PET imaging with other modalities.

4.1. Unimodal Approaches

4.1.1. Neuroinflammation PET Imaging Targeting Molecular Biomarkers Other than TSPO

Neuroinflammation is a complex physiological response to CNS injuries involving a biochemical molecular cascade involved in both tissue degradation and remodeling. Activation of microglia cells that leads to cell death is often related to oxidative stress through cytokines and chemokines release, glutamate-induced excitotoxicity, mitochondrial dysfunction or by protein aggregation. As described above, PET studies exploring neuroinflammation in CNS disorders have mainly been focused on the evaluation of the sole TSPO. Therefore, identifying and imaging other molecular biomarkers involved in inflammatory cascade would be a promising approach combined with TSPO imaging.

PET imaging associating TSPO radioligands with tracers for other molecular targets involved in microglial activation has already allowed for the assessment of temporal progression of different biochemical mechanisms involved in neuroinflammation. Indeed, in the rodent model of cerebral ischemia, Martín et al. have assessed in parallel the in vivo expression of both α4β2 (nicotinic acetylcholine receptors) and TSPO in reactive glial cells using 2-18F-fluoro-A85380 and 11C-PK11195, respectively [219]. Results have shown a progressive binding increase during the first week after cerebral ischemia, followed by a progressive PET-binding decrease in the ischemic territory. Likewise, differential time-dependent activation of TSPO and matrix metalloproteinases (MMPs), protease involved in tissue degradation and remodeling has been observed by PET co-imaging with the 18F-DPA714 and the 18F-BR-351, suggesting that their expression after stroke are subsequent or independent phenomena [220]. While TSPO is known to be an early biomarker in the neuroinflammation cascade, another longitudinal investigation, using 18F-FSPG and 18F-DPA-714, in the cerebral ischemia model displayed an earlier expression of the cystine/glutamate antiporter (system xc-), involved in glutamatergic excitotoxicity, compared to TSPO imaging, evidencing its novel role on inflammation after cerebral ischemia [221]. 18F-FSPG, a system xc- PET tracer, combined with 11C-PK11195 has also been used during the course of experimental autoimmune encephalomyelitis (EAE) induction in rats. In this MS model, 18F-FSPG showed on the one hand a significant increase of system xc-function in the lumbar section of the spinal cord at 14 days but, on the other hand, showed a significant increase of microglial/macrophage activation in the spinal cord and cerebellum two weeks after EAE induction. These dissimilar binding profiles between both PET tracers might be due to the existence of different microglial/macrophage populations throughout the CNS following MS [222]. In the same way, to assess COX implication during the neurodegenerative process in AD, COX-1 and TSPO PET co-imaging provided details of the time course in the inflammatory process in a rodent model of neuroinflammation (induced by intrastriatal injection of lipopolysaccharide or quinolinic acid). High accumulation of COX-1 tracer (11C-ketoprofen methyl ester) was observed in the early phase, matching with the time course of microglial activation and macrophages, whereas the high accumulation of 11C-PK11195 started slowly and lasted until at least 14 days afterward, corresponding to changes in both the activation of microglia/macrophages and astrocytes [223].

Thus, upregulated biomarkers in reactive glial cells complementary to TSPO are expected in order to fulfill the current clinician’s expectancies regarding the microglial role in neurodegenerative diseases and associated potential novel therapeutic approaches.

4.1.2. Dopaminergic PET Imaging

Dopaminergic neurotransmission is a key player in various brain functions, including behavior and motor functions, and is involved in the pathogenesis of psychiatric (e.g., SCZ, depression) and neurological disorders (e.g., PD, parkinsonian syndromes) [224]. Movement disorders are strongly linked with dopaminergic impairment of the striato-pallido-thalamic-cortical axis in which the striatum receives afferent projections from cortical glutamatergic and nigral dopaminergic neurons [225]. Molecular imaging of dopaminergic presynaptic integrity (e.g., DAT with 11C-CFT or 18F-FE-PE2I), dopamine synthesis and turnover (e.g., 18F-DOPA) and postsynaptic dopamine receptors (18F-Fallypride) are used to evaluate this dopaminergic pathway in various CNS conditions [224]. Experimental models of PD suggest that microglial activation may lead to dopaminergic neuronal loss though iNOS-dependent oxidative stress [226]. Three clinical studies have been performed to assess this association between microglial activation and dopamine terminal loss in PD [49,51,62]. Concerning PD patients under antiparkinsonian medication, association analysis revealed that microglial activation did not correlate significantly with either putaminal 18F-DOPA signal [65] or nigrostriatal DAT levels, objectified by 18F-FE-PE2I binding [62]. Nevertheless, the mechanism of action of antiparkinsonian drugs is based on the enhancement of dopaminergic transmission in the brain, therefore in this situation PET imaging of the dopaminergic system is de facto biased, as previously demonstrated [227,228]. The one study conducted on ten drug-naive patients with PD (rated at stage 1 to 2 on the Hoehn and Yahr scale) brought out the fact that 11C-PK11195 binding in the midbrain significantly and negatively correlated with those for 11C-CFT in the dorsal putamen, a region known to engage in motor execution [49]. Moreover, this microglial activation correlated positively with the motor severity (UPDRS assessment) [49], suggesting a causal deleterious relationship between microglial activation and nigrostriatal pathway impairment, both clinically (UPDRS) and biochemically (central hypodopaminergism). However, this association does not elucidate the sequence of events. Indeed, dopaminergic neuronal loss is accompanied by the release of endogenous constituents known as damage-associated molecular patterns (DAMPs), which are able to activate microglial cells [229].

4.1.3. Abnormal Protein Aggregates PET Imaging

Amyloid deposition, tangle formation, activated microglia and neuronal dysfunction are pathological processes involved in AD. However, the relative role of these processes in driving disease progression is still unclear. As stated above, microglia PET imaging in AD provides heterogeneous findings, hence the association analysis between fibrillar β amyloid, objectified by 11C-PIB binding, and microglial activation could (i) investigate longitudinal changes of microglial activation and amyloid; and (ii) assess the temporospatial relationship between these processes in AD. Indeed, a positive correlation was found in most of the cortical regions between amyloid burden and microglial activation [103,110,217]. Longitudinal study revealed that this correlation was less pronounced at follow-up, and the location of the correlated regions presented a dynamic change [103], suggesting that microglial activation is not static and its progression during AD may fit with the model of Calsolaro et al. [99]. Furthermore, the positive correlation between amyloid load and microglial activation is stronger in AD patients than in MCI patients, suggesting that microglial activation could be driven by the presence of amyloid deposition [103] while other studies challenged these findings in MCI patients [111,115]. Likewise, a positive correlation was seen in the parietal lobe and the anterior cingulate cortex in PDD patients [125]. This combined approach of amyloid and microglial imaging is nevertheless submitted to debate by some studies pointing out no correlation [101,105,109,111] or negative association with amyloid deposits in the posterior cingulate cortex in AD patients [106].

On the same model as the amyloid/microglia imaging, with the emergence of new NFTs PET tracers, the combined use of tau and microglial imaging should also contribute to the pattern of distribution of the increased tau deposition and widespread microglial activation in AD subjects. Not only because post mortem and initial tau imaging studies indicate that the amount of tau deposition and their topographical distribution in the brain might be more relevant, and more tightly associated with neurodegeneration and cognitive decline than β amyloid deposition [114], but also because in studies of tau model mice using 18F-FEDAA1106 or 11C-Ac-5216, microglial TSPO expression was linked to neurotoxic tau pathology. Nevertheless, to our knowledge, no combined use of tau and microglial imaging study has been performed to date.

Furthermore, recent studies suggest that neuroinflammation and α-synuclein disorders are interconnected processes which promote each other and perpetuate neurotoxicity. This interaction leads to distinct microglial polarization states and drives the chronic progression of neurodegeneration [230,231]. Thus, it seems appropriate to combine neuroinflammation/α-synuclein imaging, for which efficient radiopharmaceutical are currently strongly expected.

4.1.4. PET Tracer in MS

Microglia PET imaging (11C-PK11195) has been used in combination with 11C-methionine for the differential diagnostics between tumefactive MS lesion and low-grade glioma in a case report [231]. Beside this diagnostic potential of TSPO PET imaging in MS as previously described, the hopeful results of myelin PET tracers in animal studies such as 11C-CIC or 11C-MeDAS (for review, see Faria et al. [185]) lead us to believe that a multiplexed approach with these radiotracers could allow us to understand the relationship between the demyelination/remyelination process and microglial activation in MS.

4.1.5. Cerebral Metabolic State Imaging: 18F-FDG

Cerebral glucose metabolic rate (rCMRGlc) measured by 18F-fluorodeoxyglucose (18F-FDG) PET is currently the most accurate in vivo method for the investigation of regional human brain metabolism, and is suggested to be to be an indirect measure of synaptic function [132]. Thus, changes in neuronal activity induced by neurodegenerative diseases are reflected in an alteration in glucose metabolism.

A significant negative correlation between microglial activation and glucose metabolism was present in the hippocampus [125,132], medial temporal cortex [125] in AD patients, in the temporoparietal and occipital cortex [125] and hippocampus [132] in PDD patients, and in the hippocampus in MCI patients [125] . This inverse correlation implies the direct damaging effect by the activated microglia on neuronal loss in AD and PDD, objectified by the glucose metabolism decrease. In addition, Fan and colleagues have used three combined molecular imaging radiopharmaceuticals (11C-PIB, 11C-PK11195 and 18F-FDG) to show a correlation between amyloid load, levels of microglial activation, and reduced glucose metabolism in AD and, to a lesser extent, in MCI and PDD subjects; furthermore, the correlation between amyloid load and glucose metabolism was more extensive at follow-up and was consistently associated with cognitive decline in AD patients, suggesting that, once synaptic dysfunction occurs, the disease is active and progressive [85].

4.2. Multimodal Approaches

4.2.1. Imaging Modalities Other Than PET

In order to investigate CNS disorders by a broader approach combining concomitantly complementary pathophysiological aspects, the use of TSPO PET in a multimodal neuroimaging strategy has increased significantly in recent years. In this framework, MRI and its different subtypes (i.e., structural, diffusion and functional MRI) are among the most democratized approaches, in combination with TSPO PET imaging.

Brain atrophy assessed in structural MRI has been found in various CNS disorders [232]. This is especially true in AD, where hippocampal atrophy correlates with clinical decline and assumes the status of both the diagnostic and imaging biomarker of AD progression [233]. This approach was used to assess the relationship between microglial activation and neurodegenerative process in AD [101,124], PDD [132], SCZ [177] and MS [200,205,213,218]. Indeed, the amount of activated microglia in the whole cortex, medial temporal lobe and hippocampus was inversely correlated with hippocampal volume and 18F-FDG hippocampal uptake in AD and PDD patients [132]. In front of this spatial agreement between microglial activation in the cortical projections from the hippocampus and hippocampal atrophy, the authors assumed that microglial cells in a reactive state might be one of the effectors of neurodegeneration [132]. The same association between TSPO density increase and cerebral volume decrease reached significance in various cortical regions such as the inferior parietal lobule, precuneus, superior temporal cortex and especially in the prefrontal cortex [101], in which interconnection with the thalamus and hippocampus [233] are strongly linked to episodic memory impairment in AD patients [234]. On the contrary in BD-I patients, association analysis between 11C-PK11195 binding potential and hippocampal volume failed to exhibit a significant relationship [170]. Quantitative magnetization transfer imaging (qMTI), an advanced structural MRI technique providing information about in vivo tissue integrity, is able to detect inflammation-related changes in brain microstructures [235]. Furthermore, qMTI in MS patients has shed light on the pattern of tissue structural abnormalities in NAWM being greatest near the ventricles [236]. In a way to characterize the temporal/sequential/spatial relationship between microglial activation and anatomically objective brain lesions, a coupling TSPO PET/qMTI could be a promising approach, especially in MS.

Diffusion-weighted imaging, reflecting (ab)normal tissue diffusivity (measured by apparent diffusion coefficient (ADC)), has been used in combination with 11C-PK11195 in PD, MSA and PSP patients [61]. Although the small sample size limits the scope of study’s conclusions about the impact of microglial activation on tissue damage, a positive correlation between microglial activation and ADC was found in the pons of atypical parkinsonism patients. Given the fact that ADC indirectly reflects cellularity, this association suggests a causal relationship between microglial activation/TSPO overexpression and gliosis.

fMRI is a technique that uses blood-oxygen-level-dependent (BOLD) contrast to detect changes in brain hemodynamics. Hippocampal functional connectivities to the subguenal and prefrontal and parietal regions correlated with the beck depression inventory scores and 18F-PBR111 DVR in MS patients. This correlation analysis between hippocampal 18F-PBR111 binding and functional connectivity, assessed by fRMI, lead authors to hypothesize that microglial activation is involved in MDE pathophysiology in MS patients [218]. Besides “conventional fMRI”, innovative techniques like GluCEST (Glutamate chemical exchange saturation transfer) appear to be hopeful tools to assess and understand neuroinflammation [237], and may be even more useful in a multiplexed approach with microglia PET imaging.

Beyond the interest of coupling MRI techniques with TSPO PET modality, recent advances in imaging of activated microglia have been shown promising results. Indeed, 2D optical imaging spectroscopy [238] or optical projection tomography applied to a 3D spatial assessment of the development of neuroinflammation [239] provided positive outcomes in rodent models.

4.2.2. Biology

The understanding of the microglial activation status in neurodegenerative disorders could be reached by coupling microglia PET imaging to several biological techniques including metabolomics, transcriptomics, magnetic resonance spectroscopy (MRS) and measurement of central and/or peripheral pro-inflammatory components. Among these, 1H MRS in BD-I patients provided surprising results. Whereas no relationship was found between phosphocholine + glycerophosphocholine concentrations, cellular turnover biomarkers and microglial activation; _N_-acetylaspartate + _N_-acetyl-aspartyl-glutamate concentrations, representing loss of neuronal integrity when levels decreased, were positively associated with 11C-PK11195 binding in the left hippocampus [170]. These findings challenged the neuroinflammation theory of psychiatric disorders in which activating microglia have a negative effect on neuronal survival [240].

In MS patients with a higher inflammatory load, the concentration of myoinositol, a metabolite which has been proposed as a glial and especially as an astrocyte marker [241], was correlated with 11C-PBR28 DVR in WM lesions, suggesting the joint activation of astrocytes and microglia in MS [211].

The association between inflammatory biomarkers (cytokine levels [89,168], or proteins carbonylation [54] and TSPO PET imaging in neurodegenerative disorders was also the subject of several studies. Early stage dementia with Lewy bodies (DLB) and PD patients exhibited significantly greater levels of total carbonylated proteins in cerebrospinal fluid (CSF) than healthy controls, suggesting that relative aspecific oxidative modifications occurred in both neurodegenerative disorders [54]. The lack of correlation between central inflammation measured by 18F-FEPPA VT and levels of several pro-inflammatory cytokines such as IL-1β , IL-6 and TNF-α supports the idea that microglial activation can occur in MDE even when peripheral inflammation is absent [168]. In patients with recent onset of SCZ, the absence of this association has also been found between 11C-DPA713 VT and both plasma and cerebrospinal fluid IL-6 levels [176].

5. TSPO PET Imaging Potential Added Value in the Clinical Practice

As discussed above, TSPO PET imaging has been used in a large number of studies concerning neurodegenerative diseases over the past 20 years. However, such a major investment has not yet resulted in an expected impact for clinical practice. In AD or SCZ, for instance, our present analysis came to conflicting results, which are moreover based on small numbers (<100) of patients. The overall trend that could be drawn from these studies would suggest that early microglial activation could represent a beneficial response, whereas chronic exposure would induce detrimental effects by promoting neuronal death, thus contributing to the progression of the disease.

A comparison between PET radioligands’ development, targeting TSPO and β-amyloid (Aβ) plaques, respectively, illustrates this assessment: while the first clinical uses of these radiopharmaceuticals were approximately contemporaneous, those of 11C-PK1195 being even much earlier than those of 11C-PiB and 18F-FDDNP (two of the first developed Aβ tracers) [242,243], several Aβ-radiopharmaceuticals are nowadays routinely used to assess amyloid-β burden in a clinical setting. Aβ-PET represents a major advance in the evaluation of patients with cognitive impairment when AD is a possible cause, and affects the diagnosis and the resulting treatment recommendations [243]. TSPO radiopharmaceuticals (18F-DPA714, 18F-FEPPA, 18F-PBR06, or 18F-GE180 being among the most promising ones), remain at the same time dedicated to specialized PET centers and restricted to research applications.

The current state of knowledge, which clearly identifies the neuroinflammation process as a constitutive part of the pathophysiology of neurodegenerative diseases, might give a new impetus for TSPO PET imaging, especially for the noninvasive and longitudinal evaluation of anti-inflammatory therapies for these diseases. For instance, Ratchford et al. recently reported a longitudinal TSPO PET study evaluating microglial activation in MS. One year treatment with glatiramer acetate reduced TSPO binding significantly in both cortical gray matter and cerebral white matter, when compared with cerebellum [204]. This promising approach gives excellent comparative data for longitudinal TSPO PET studies evaluating therapeutics in progressive diseases. Nevertheless, several drawbacks limit the ability of TSPO as a PET imaging molecular target in routine clinical practice, such as the identified polymorphism affecting the binding affinity properties of most of TSPO ligands and the TSPO multicellular expression, among others. Thus, we mentioned above the interest of TSPO imaging combined with further PET targets, but the dissimilar binding profile observed and its correlation with neuroinflammation cellular dynamics remains a major issue for understanding the pathophysiological and clinical relevance of what we are imaging.

6. Conclusions

TSPO PET tracers were the most widely used and allowed us to better characterize microglia-related neuroinflammation in terms of intensity, localization and static/dynamic feature of microglial activation in various neurodegenerative troubles. Recent studies challenged the paradigm that activated microglia are detrimentally involved in neurodegenerative process. Indeed, microglia seem to play a role in CNS disorders with a relative dichromatic status that occurs in a time-dependent fashion. With the benefit of hindsight over 25 years, TSPO PET imaging showed several limitations in relation to the multicellular expression of the target or its similar expression, whatever the microglia polarization state. Thus, new PET biomarkers reflecting some specific functions of activated microglia (e.g., polarization, microglial oxidative stress-related) conjugated with a multiplex strategy combining several modalities (imaging, biology) may solve clinicians’ concerns about characterizing the role of activated microglia over the progression of CNS disorders.

Finally, the usefulness of TSPO PET imaging as a major research tool has appeared inescapable over years. Indeed, it has allowed for better understanding of the neuroinflammation process in CNS disorders, and the multiplex approach, either unimodal or multimodal, would certainly broaden the knowledge of this issue. Nowadays, however, the main challenge remains to identify the scope of TSPO PET imaging for a transfer in routine clinical use whether as a diagnostic, prognostic or therapeutic effects assessment tool.

Acknowledgments

This study was supported by the French National Agency for Research (“Investissements d’Avenir” n°ANR-11-LABX-0018-01), IRON; and the European Union’s Seventh Framework Programme (FP7/2004-2013) under grant agreement n°278850 (INMiND).

Conflicts of Interest

The authors declare no conflict of interest.

References

• 1.Pelvig D.P., Pakkenberg H., Stark A.K., Pakkenberg B. Neocortical glial cell numbers in human brains. Neurobiol. Aging. 2008;29:1754–1762. doi: 10.1016/j.neurobiolaging.2007.04.013. [DOI] [PubMed] [Google Scholar]
• 2.Lyck L., Santamaria I.D., Pakkenberg B., Chemnitz J., Schrøder H.D., Finsen B., Gundersen H.J.G. An empirical analysis of the precision of estimating the numbers of neurons and glia in human neocortex using a fractionator-design with sub-sampling. J. Neurosci. Methods. 2009;182:143–156. doi: 10.1016/j.jneumeth.2009.06.003. [DOI] [PubMed] [Google Scholar]
• 3.Ransohoff R.M., Perry V.H. Microglial physiology: Unique stimuli, specialized responses. Annu. Rev. Immunol. 2009;27:119–145. doi: 10.1146/annurev.immunol.021908.132528. [DOI] [PubMed] [Google Scholar]
• 4.Reemst K., Noctor S.C., Lucassen P.J., Hol E.M. The Indispensable Roles of Microglia and Astrocytes during Brain Development. Front. Hum. Neurosci. 2016;10:566. doi: 10.3389/fnhum.2016.00566. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 5.Nimmerjahn A., Kirchhoff F., Helmchen F. Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science. 2005;308:1314–1318. doi: 10.1126/science.1110647. [DOI] [PubMed] [Google Scholar]
• 6.Hanisch U.-K., Kettenmann H. Microglia: Active sensor and versatile effector cells in the normal and pathologic brain. Nat. Neurosci. 2007;10:1387–1394. doi: 10.1038/nn1997. [DOI] [PubMed] [Google Scholar]
• 7.Varnum M.M., Ikezu T. The classification of microglial activation phenotypes on neurodegeneration and regeneration in Alzheimer’s disease brain. Arch. Immunol. Ther. Exp. 2012;60:251–266. doi: 10.1007/s00005-012-0181-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 8.Chew L.-J., Fusar-Poli P., Schmitz T. Oligodendroglial alterations and the role of microglia in white matter injury: Relevance to schizophrenia. Dev. Neurosci. 2013;35:102–129. doi: 10.1159/000346157. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 9.Block M.L., Zecca L., Hong J.S. Microglia-mediated neurotoxicity: Uncovering the molecular mechanisms. Nat. Rev. Neurosci. 2007;8:57–69. doi: 10.1038/nrn2038. [DOI] [PubMed] [Google Scholar]
• 10.Lisi L., Stigliano E., Lauriola L., Navarra P., dello Russo C. Proinflammatory-activated glioma cells induce a switch in microglial polarization and activation status, from a predominant M2b phenotype to a mixture of M1 and M2a/B polarized cells. ASN Neuro. 2014;6:171–183. doi: 10.1042/AN20130045. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 11.Boche D., Perry V.H., Nicoll J.A.R. Review: Activation patterns of microglia and their identification in the human brain. Neuropathol. Appl. Neurobiol. 2013;39:3–18. doi: 10.1111/nan.12011. [DOI] [PubMed] [Google Scholar]
• 12.Smith J.A., Das A., Ray S.K., Banik N.L. Role of pro-inflammatory cytokines released from microglia in neurodegenerative diseases. Brain Res. Bull. 2012;87:10–20. doi: 10.1016/j.brainresbull.2011.10.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 13.Braestrup C., Squires R.F. Specific benzodiazepine receptors in rat brain characterized by high-affinity (3H)diazepam binding. Proc. Natl. Acad. Sci. USA. 1977;74:3805–3809. doi: 10.1073/pnas.74.9.3805. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 14.Papadopoulos V., Baraldi M., Guilarte T.R., Knudsen T.B., Lacapère J.J., Lindemann P., Norenberg M.D., Nutt D., Weizman A., Zhang M.R., et al. Translocator protein (18 kDa): New nomenclature for the peripheral-type benzodiazepine receptor based on its structure and molecular function. Trends Pharmacol. Sci. 2006;27:402–409. doi: 10.1016/j.tips.2006.06.005. [DOI] [PubMed] [Google Scholar]
• 15.Banati R.B. Visualising microglial activation in vivo. Glia. 2002;40:206–217. doi: 10.1002/glia.10144. [DOI] [PubMed] [Google Scholar]
• 16.Wilms H., Claasen J., Röhl C., Sievers J., Deuschl G., Lucius R. Involvement of benzodiazepine receptors in neuroinflammatory and neurodegenerative diseases: Evidence from activated microglial cells in vitro. Neurobiol. Dis. 2003;14:417–424. doi: 10.1016/j.nbd.2003.07.002. [DOI] [PubMed] [Google Scholar]
• 17.Lavisse S., Guillermier M., Hérard A.S., Petit F., Delahaye M., van Camp N., Ben Haim L., Lebon V., Remy P., Dollé F., Delzescaux T., Bonvento G., Hantraye P., Escartin C. Reactive astrocytes overexpress TSPO and are detected by TSPO positron emission tomography imaging. J. Neurosci. 2012;32:10809–10818. doi: 10.1523/JNEUROSCI.1487-12.2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 18.Martín A., Boisgard R., Thézé B., van Camp N., Kuhnast B., Damont A., Kassiou M., Dollé F., Tavitian B. Evaluation of the PBR/TSPO radioligand [18F]DPA-714 in a rat model of focal cerebral ischemia. J. Cereb. Blood Flow Metab. 2010;30:230–241. doi: 10.1038/jcbfm.2009.205. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 19.Rojas S., Martín A., Arranz M.J., Pareto D., Purroy J., Verdaguer E., Llop J., Gómez V., Gispert J.D., Millán O., et al. Imaging brain inflammation with [11C]PK11195 by PET and induction of the peripheral-type benzodiazepine receptor after transient focal ischemia in rats. J. Cereb. Blood Flow Metab. 2007;27:1975–1986. doi: 10.1038/sj.jcbfm.9600500. [DOI] [PubMed] [Google Scholar]
• 20.Winkeler A., Boisgard R., Martin A., Tavitian B. Radioisotopic imaging of neuroinflammation. J. Nucl. Med. 2010;51:1–4. doi: 10.2967/jnumed.109.065680. [DOI] [PubMed] [Google Scholar]
• 21.Mukhin A.G., Papadopoulos V., Costa E., Krueger K.E. Mitochondrial benzodiazepine receptors regulate steroid biosynthesis. Proc. Natl. Acad. Sci. USA. 1989;86:9813–9816. doi: 10.1073/pnas.86.24.9813. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 22.De Tassigny A., Assaly R., Schaller S., Pruss R.M., Berdeaux A., Morin D. Mitochondrial translocator protein (TSPO) ligands prevent doxorubicin-induced mechanical dysfunction and cell death in isolated cardiomyocytes. Mitochondrion. 2013;13:688–697. doi: 10.1016/j.mito.2013.10.001. [DOI] [PubMed] [Google Scholar]
• 23.Veenman L., Shandalov Y., Gavish M. VDAC activation by the 18 kDa translocator protein (TSPO), implications for apoptosis. J. Bioenerg. Biomembr. 2008;40:199–205. doi: 10.1007/s10863-008-9142-1. [DOI] [PubMed] [Google Scholar]
• 24.Gatliff J., Campanella M. TSPO is a REDOX regulator of cell mitophagy. Biochem. Soc. Trans. 2015;43:543–552. doi: 10.1042/BST20150037. [DOI] [PubMed] [Google Scholar]
• 25.Ryan B.J., Hoek S., Fon E.A., Wade-Martins R. Mitochondrial dysfunction and mitophagy in Parkinson’s: From familial to sporadic disease. Trends Biochem. Sci. 2015;40:200–210. doi: 10.1016/j.tibs.2015.02.003. [DOI] [PubMed] [Google Scholar]
• 26.Khalil B., El Fissi N., Aouane A., Cabirol-Pol M.J., Rival T., Liévens J.C. PINK1-induced mitophagy promotes neuroprotection in Huntington’s disease. Cell Death Dis. 2015;6:e1617. doi: 10.1038/cddis.2014.581. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 27.Ye X., Sun X., Starovoytov V., Cai Q. Parkin-mediated mitophagy in mutant hAPP neurons and Alzheimer’s disease patient brains. Hum. Mol. Genet. 2015;24:2938–2951. doi: 10.1093/hmg/ddv056. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 28.Li F., Liu J., Liu N., Kuhn L.A., Garavito R.M., Ferguson-Miller S. Translocator Protein 18 kDa (TSPO): An Old Protein with New Functions? Biochemistry. 2016;55:2821–2831. doi: 10.1021/acs.biochem.6b00142. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 29.Veiga S., Azcoitia I., Garcia-Segura L. M. Ro5-4864, a peripheral benzodiazepine receptor ligand, reduces reactive gliosis and protects hippocampal hilar neurons from kainic acid excitotoxicity. J. Neurosci. Res. 2005;80:129–137. doi: 10.1002/jnr.20430. [DOI] [PubMed] [Google Scholar]
• 30.Veiga S., Carrero P., Pernia O., Azcoitia I., Garcia-Segura L.M. Translocator protein 18 kDa is involved in the regulation of reactive gliosis. Glia. 2007;55:1426–1436. doi: 10.1002/glia.20558. [DOI] [PubMed] [Google Scholar]
• 31.Messmer K., Reynolds G.P. Increased peripheral benzodiazepine binding sites in the brain of patients with Huntington’s disease. Neurosci. Lett. 1998;241:53–56. doi: 10.1016/S0304-3940(97)00967-1. [DOI] [PubMed] [Google Scholar]
• 32.Turner M.R., Cagnin A., Turkheimer F.E., Miller C.C.J., Shaw C.E., Brooks D.J., Leigh P.N., Banati R.B. Evidence of widespread cerebral microglial activation in amyotrophic lateral sclerosis: An [11C](R)-PK11195 positron emission tomography study. Neurobiol. Dis. 2004;15:601–609. doi: 10.1016/j.nbd.2003.12.012. [DOI] [PubMed] [Google Scholar]
• 33.Banati R.B., Egensperger R., Maassen A., Hager G., Kreutzberg G.W., Graeber M.B. Mitochondria in activated microglia in vitro. J. Neurocytol. 2004;33:535–541. doi: 10.1007/s11068-004-0515-7. [DOI] [PubMed] [Google Scholar]
• 34.Venneti S., Lopresti B.J., Wang G., Hamilton R.L., Mathis C.A., Klunk W.E., Apte U.M., Wiley C.A. PK11195 labels activated microglia in Alzheimer’s disease and in vivo in a mouse model using PET. Neurobiol. Aging. 2009;30:1217–1226. doi: 10.1016/j.neurobiolaging.2007.11.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 35.Maeda J., Higuchi M., Inaji M., Ji B., Haneda E., Okauchi T., Zhang M.R., Suzuki K., Suhara T. Phase-dependent roles of reactive microglia and astrocytes in nervous system injury as delineated by imaging of peripheral benzodiazepine receptor. Brain Res. 2007;1157:100–111. doi: 10.1016/j.brainres.2007.04.054. [DOI] [PubMed] [Google Scholar]
• 36.Le Fur G., Perrier M.L., Vaucher N., Imbault F., Flamier A., Benavides J., Uzan A., Renault C., Dubroeucq M.C., Guérémy C. Peripheral benzodiazepine binding sites: Effect of PK 11195, 1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinolinecarboxamide. I. In vitro studies. Life Sci. 1983;32:1839–1847. doi: 10.1016/0024-3205(83)90062-0. [DOI] [PubMed] [Google Scholar]
• 37.Chauveau F., Boutin H., Van Camp N., Dollé F., Tavitian B. Nuclear imaging of neuroinflammation: A comprehensive review of [11C]PK11195 challengers. Eur. J. Nucl. Med. Mol. Imaging. 2008;35:2304–2319. doi: 10.1007/s00259-008-0908-9. [DOI] [PubMed] [Google Scholar]
• 38.Dollé F., Luus C., Reynolds A., Kassiou M. Radiolabelled molecules for imaging the translocator protein (18 kDa) using positron emission tomography. Curr. Med. Chem. 2009;16:2899–2923. doi: 10.2174/092986709788803150. [DOI] [PubMed] [Google Scholar]
• 39.Tang D., McKinley E.T., Hight M.R., Uddin M.I., Harp J.M., Fu A., Nickels M.L., Buck J.R., Manning H.C. Synthesis and structure-activity relationships of 5,6,7-substituted pyrazolopyrimidines: Discovery of a novel TSPO PET ligand for cancer imaging. J. Med. Chem. 2013;56:3429–3433. doi: 10.1021/jm4001874. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 40.Scarf A.M., Ittner L.M., Kassiou M. The translocator protein (18 kDa): Central nervous system disease and drug design. J. Med. Chem. 2009;52:581–592. doi: 10.1021/jm8011678. [DOI] [PubMed] [Google Scholar]
• 41.Ikawa M., Lohith T.G., Shrestha S., Telu S., Zoghbi S.S., Castellano S., Taliani S., Da Settimo F., Fujita M., Pike V.W., et al. 11C-ER176, a radioligand for 18-kDa translocator protein (TSPO), has adequate sensitivity to robustly image all three affinity genotypes in human brain. J. Nucl. Med. 2017;58:320–325. doi: 10.2967/jnumed.116.178996. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 42.Fan Z., Calsolaro V., Atkinson R.A., Femminella G.D., Waldman A., Buckley C., Trigg W., Brooks D.J., Hinz R., Edison P. Flutriciclamide (18F-GE180) PET: First-in-Human PET Study of Novel Third-Generation In Vivo Marker of Human Translocator Protein. J. Nucl. Med. 2016;57:1753–1759. doi: 10.2967/jnumed.115.169078. [DOI] [PubMed] [Google Scholar]
• 43.Vivash L., O’Brien T.J. Imaging Microglial Activation with TSPO PET: Lighting up Neurologic Diseases? J. Nucl. Med. 2016;57:165–168. doi: 10.2967/jnumed.114.141713. [DOI] [PubMed] [Google Scholar]
• 44.Brooks D. J., Ibanez V., Sawle G.V., Quinn N., Lees A.J., Mathias C.J., Bannister R., Marsden C.D., Frackowiak R.S. Differing patterns of striatal 18F-dopa uptake in Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy. Ann. Neurol. 1990;28:547–555. doi: 10.1002/ana.410280412. [DOI] [PubMed] [Google Scholar]
• 45.Fearnley J.M., Lees A.J. Ageing and Parkinson’s disease: Substantia nigra regional selectivity. Brain. 1991;114(Pt 5):2283–2301. doi: 10.1093/brain/114.5.2283. [DOI] [PubMed] [Google Scholar]
• 46.Morrish P.K., Sawle G.V., Brooks D.J. An [18F]dopa-PET and clinical study of the rate of progression in Parkinson’s disease. Brain. 1996;119(Pt 2):585–591. doi: 10.1093/brain/119.2.585. [DOI] [PubMed] [Google Scholar]
• 47.Gibb W.R. Neuropathology of Parkinson’s disease and related syndromes. Neurol. Clin. 1992;10:361–376. [PubMed] [Google Scholar]
• 48.McGeer P.L., Itagaki S., Boyes B.E., McGeer E.G. Reactive microglia are positive for HLA-DR in the substantia nigra of Parkinson’s and Alzheimer’s disease brains. Neurology. 1988;38:1285–1291. doi: 10.1212/WNL.38.8.1285. [DOI] [PubMed] [Google Scholar]
• 49.Ouchi Y., Yoshikawa E., Sekine Y., Futatsubashi M., Kanno T., Ogusu T., Torizuka T. Microglial activation and dopamine terminal loss in early Parkinson’s disease. Ann. Neurol. 2005;57:168–175. doi: 10.1002/ana.20338. [DOI] [PubMed] [Google Scholar]
• 50.Koshimori Y., Ko J.-H., Mizrahi R., Rusjan P., Mabrouk R., Jacobs M.F., Christopher L., Hamani C., Lang A.E., Wilson A.A., et al. Imaging striatal microglial activation in patients with Parkinson’s disease. PLoS ONE. 2015;10:e0138721. doi: 10.1371/journal.pone.0138721. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 51.Gerhard A., Pavese N., Hotton G., Turkheimer F., Es M., Hammers A., Eggert K., Oertel W., Banati R.B., Brooks D.J. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in idiopathic Parkinson’s disease. Neurobiol. Dis. 2006;21:404–412. doi: 10.1016/j.nbd.2005.08.002. [DOI] [PubMed] [Google Scholar]
• 52.Edison P., Ahmed I., Fan Z., Hinz R., Gelosa G., Ray Chaudhuri K., Walker Z., Turkheimer F.E., Brooks D.J. Microglia, amyloid, and glucose metabolism in Parkinson’s disease with and without dementia. Neuropsychopharmacology. 2013;38:938–949. doi: 10.1038/npp.2012.255. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 53.Doorn K.J., Moors T., Drukarch B., van de Berg W.D., Lucassen P.J., van Dam A.M. Microglial phenotypes and toll-like receptor 2 in the substantia nigra and hippocampus of incidental Lewy body disease cases and Parkinson’s disease patients. Acta Neuropathol. Commun. 2014;2:90. doi: 10.1186/s40478-014-0090-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 54.Iannaccone S., Cerami C., Alessio M., Garibotto V., Panzacchi A., Olivieri S., Gelsomino G., Moresco R.M., Perani D. In vivo microglia activation in very early dementia with Lewy bodies, comparison with Parkinson’s disease. Park. Relat. Disord. 2013;19:47–52. doi: 10.1016/j.parkreldis.2012.07.002. [DOI] [PubMed] [Google Scholar]
• 55.Terada T., Yokokura M., Yoshikawa E., Futatsubashi M., Kono S., Konishi T., Miyajima H., Hashizume T., Ouchi Y. Extrastriatal spreading of microglial activation in Parkinson’s disease: A positron emission tomography study. Ann. Nucl. Med. 2016;30:579–587. doi: 10.1007/s12149-016-1099-2. [DOI] [PubMed] [Google Scholar]
• 56.Marinova-Mutafchieva L., Sadeghian M., Broom L., Davis J.B., Medhurst A.D., Dexter D.T. Relationship between microglial activation and dopaminergic neuronal loss in the substantia nigra: A time course study in a 6-hydroxydopamine model of Parkinson’s disease. J. Neurochem. 2009;110:966–975. doi: 10.1111/j.1471-4159.2009.06189.x. [DOI] [PubMed] [Google Scholar]
• 57.Jellinger K.A. Neuropathology of sporadic Parkinson’s disease: Evaluation and changes of concepts. Mov. Disord. 2012;27:8–30. doi: 10.1002/mds.23795. [DOI] [PubMed] [Google Scholar]
• 58.Zhang Q.-S., Heng Y., Yuan Y.-H., Chen N.-H. Pathological α-synuclein exacerbates the progression of Parkinson’s disease through microglial activation. Toxicol. Lett. 2016;265:30–37. doi: 10.1016/j.toxlet.2016.11.002. [DOI] [PubMed] [Google Scholar]
• 59.Jellinger K.A., Wenning G.K. Multiple system atrophy: Pathogenic mechanisms and biomarkers. J. Neural Transm. Vienna Austria 1996. 2016;123:555–572. doi: 10.1007/s00702-016-1545-2. [DOI] [PubMed] [Google Scholar]
• 60.Bartels A.L., Willemsen A.T. M., Doorduin J., de Vries E.F.J., Dierckx R.A., Leenders K.L. [11C]-PK11195 PET: Quantification of neuroinflammation and a monitor of anti-inflammatory treatment in Parkinson’s disease? Park. Relat. Disord. 2010;16:57–59. doi: 10.1016/j.parkreldis.2009.05.005. [DOI] [PubMed] [Google Scholar]
• 61.Kobylecki C., Counsell S.J., Cabanel N., Wächter T., Turkheimer F.E., Eggert K., Oertel W., Brooks D.J., Gerhard A. Diffusion-weighted imaging and its relationship to microglial activation in parkinsonian syndromes. Park. Relat. Disord. 2013;19:527–532. doi: 10.1016/j.parkreldis.2013.01.017. [DOI] [PubMed] [Google Scholar]
• 62.Jucaite A., Svenningsson P., Rinne J.O., Cselényi Z., Varnäs K., Johnström P., Amini N., Kirjavainen A., Helin S., Minkwitz M., et al. Effect of the myeloperoxidase inhibitor AZD3241 on microglia: A PET study in Parkinson’s disease. Brain J. Neurol. 2015;138:2687–2700. doi: 10.1093/brain/awv184. [DOI] [PubMed] [Google Scholar]
• 63.Dodel R., Spottke A., Gerhard A., Reuss A., Reinecker S., Schimke N., Trenkwalder C., Sixel-Döring F., Herting B., Kamm C., et al. Minocycline 1-year therapy in multiple-system-atrophy: Effect on clinical symptoms and [11C] (R)-PK11195 PET (MEMSA-trial) Mov. Disord. 2010;25:97–107. doi: 10.1002/mds.22732. [DOI] [PubMed] [Google Scholar]
• 64.Gerhard A., Watts J., Trender-Gerhard I., Turkheimer F., Banati R.B., Bhatia K., Brooks D.J. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in corticobasal degeneration. Mov. Disord. 2004;19:1221–1226. doi: 10.1002/mds.20162. [DOI] [PubMed] [Google Scholar]
• 65.Henkel K., Karitzky J., Schmid M., Mader I., Glatting G., Unger J.W., Neumaier B., Ludolph A.C., Reske S.N., Landwehrmeyer G.B. Imaging of activated microglia with PET and [11C]PK 11195 in corticobasal degeneration. Mov. Disord. 2004;19:817–821. doi: 10.1002/mds.20040. [DOI] [PubMed] [Google Scholar]
• 66.Gerhard A., Banati R.B., Goerres G.B., Cagnin A., Myers R., Gunn R.N., Turkheimer F., Good C.D., Mathias C.J., Quinn N., et al. [11C](R)-PK11195 PET imaging of microglial activation in multiple system atrophy. Neurology. 2003;61:686–689. doi: 10.1212/01.WNL.0000078192.95645.E6. [DOI] [PubMed] [Google Scholar]
• 67.Stefanova N., Wenning G.K. Review: Multiple system atrophy: Emerging targets for interventional therapies. Neuropathol. Appl. Neurobiol. 2016;42:20–32. doi: 10.1111/nan.12304. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 68.Stefanova N., Reindl M., Neumann M., Kahle P.J., Poewe W., Wenning G.K. Microglial activation mediates neurodegeneration related to oligodendroglial alpha-synucleinopathy: Implications for multiple system atrophy. Mov. Disord. 2007;22:2196–2203. doi: 10.1002/mds.21671. [DOI] [PubMed] [Google Scholar]
• 69.Ishizawa K., Komori T., Arai N., Mizutani T., Hirose T. Glial cytoplasmic inclusions and tissue injury in multiple system atrophy: A quantitative study in white matter (olivopontocerebellar system) and gray matter (nigrostriatal system) Neuropathology. 2008;28:249–257. doi: 10.1111/j.1440-1789.2007.00855.x. [DOI] [PubMed] [Google Scholar]
• 70.Litvan I., Agid Y., Calne D., Campbell G., Dubois B., Duvoisin R.C., Goetz C.G., Golbe L.I., Grafman J., Growdon J.H., et al. Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): Report of the NINDS-SPSP international workshop. Neurology. 1996;47:1–9. doi: 10.1212/WNL.47.1.1. [DOI] [PubMed] [Google Scholar]
• 71.Hauw J.J., Daniel S.E., Dickson D., Horoupian D.S., Jellinger K., Lantos P.L., McKee A., Tabaton M., Litvan I. Preliminary NINDS neuropathologic criteria for Steele-Richardson-Olszewski syndrome (progressive supranuclear palsy) Neurology. 1994;44:2015–2019. doi: 10.1212/WNL.44.11.2015. [DOI] [PubMed] [Google Scholar]
• 72.Fernández-Botrán R., Ahmed Z., Crespo F.A., Gatenbee C., Gonzalez J., Dickson D.W., Litvan I. Cytokine expression and microglial activation in progressive supranuclear palsy. Park. Relat. Disord. 2011;17:683–688. doi: 10.1016/j.parkreldis.2011.06.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 73.Ishizawa K., Dickson D.W. Microglial activation parallels system degeneration in progressive supranuclear palsy and corticobasal degeneration. J. Neuropathol. Exp. Neurol. 2001;60:647–657. doi: 10.1093/jnen/60.6.647. [DOI] [PubMed] [Google Scholar]
• 74.Ling H., Kovacs G.G., Vonsattel J.P.G., Davey K., Mok K.Y., Hardy J., Morris H.R., Warner T.T., Holton J.L., Revesz T. Astrogliopathy predominates the earliest stage of corticobasal degeneration pathology. Brain J. Neurol. 2016;139:3237–3252. doi: 10.1093/brain/aww256. [DOI] [PubMed] [Google Scholar]
• 75.Dickson D.W., Bergeron C., Chin S.S., Duyckaerts C., Horoupian D., Ikeda K., Jellinger K., Lantos P.L., Lippa C.F., Mirra S.S., et al. Office of Rare Diseases neuropathologic criteria for corticobasal degeneration. J. Neuropathol. Exp. Neurol. 2002;61:935–946. doi: 10.1093/jnen/61.11.935. [DOI] [PubMed] [Google Scholar]
• 76.Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium Identification of genetic factors that modify clinical onset of Huntington’s disease. Cell. 2015;162:516–526. doi: 10.1016/j.cell.2015.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 77.Ross C.A., Aylward E.H., Wild E.J., Langbehn D.R., Long J.D., Warner J.H., Scahill R.I., Leavitt B.R., Stout J.C., Paulsen J.S., et al. Huntington disease: Natural history, biomarkers and prospects for therapeutics. Nat. Rev. Neurol. 2014;10:204–216. doi: 10.1038/nrneurol.2014.24. [DOI] [PubMed] [Google Scholar]
• 78.Björkqvist M., Wild E.J., Thiele J., Silvestroni A., Andre R., Lahiri N., Raibon E., Lee R.V., Benn C.L., Soulet D., et al. A novel pathogenic pathway of immune activation detectable before clinical onset in Huntington’s disease. J. Exp. Med. 2008;205:1869–1877. doi: 10.1084/jem.20080178. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 79.Liot G., Valette J., Pépin J., Flament J., Brouillet E. Energy defects in Huntington’s disease: Why “in vivo” evidence matters. Biochem. Biophys. Res. Commun. 2016;483:1084–1095. doi: 10.1016/j.bbrc.2016.09.065. [DOI] [PubMed] [Google Scholar]
• 80.Crotti A., Benner C., Kerman B.E., Gosselin D., Lagier-Tourenne C., Zuccato C., Cattaneo E., Gage F.H., Cleveland D.W., Glass C.K. Mutant Huntingtin promotes autonomous microglia activation via myeloid lineage-determining factors. Nat. Neurosci. 2014;17:513–521. doi: 10.1038/nn.3668. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 81.MacDonald M.E., Ambrose C.M., Duyao M.P., Myers R.H., Lin C., Srinidhi L., Barnes G., Taylor S.A., James M., Groot N., et al. A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. The Huntington’s Disease Collaborative Research Group. Cell. 1993;72:971–983. doi: 10.1016/0092-8674(93)90585-E. [DOI] [PubMed] [Google Scholar]
• 82.Ferrante R.J., Kowall N.W., Beal M.F., Martin J.B., Bird E.D., Richardson E.P. Morphologic and histochemical characteristics of a spared subset of striatal neurons in Huntington’s disease. J. Neuropathol. Exp. Neurol. 1987;46:12–27. doi: 10.1097/00005072-198701000-00002. [DOI] [PubMed] [Google Scholar]
• 83.Petersén A., Björkqvist M. Hypothalamic-endocrine aspects in Huntington’s disease. Eur. J. Neurosci. 2006;24:961–967. doi: 10.1111/j.1460-9568.2006.04985.x. [DOI] [PubMed] [Google Scholar]
• 84.Sapp E., Kegel K.B., Aronin N., Hashikawa T., Uchiyama Y., Tohyama K., Bhide P.G., Vonsattel J.P., DiFiglia M. Early and progressive accumulation of reactive microglia in the Huntington disease brain. J. Neuropathol. Exp. Neurol. 2001;60:161–172. doi: 10.1093/jnen/60.2.161. [DOI] [PubMed] [Google Scholar]
• 85.Pavese N., Gerhard A., Tai Y.F., Ho A.K., Turkheimer F., Barker R.A., Brooks D.J., Piccini P. Microglial activation correlates with severity in Huntington disease: A clinical and PET study. Neurology. 2006;66:1638–1643. doi: 10.1212/01.wnl.0000222734.56412.17. [DOI] [PubMed] [Google Scholar]
• 86.Tai Y.F., Pavese N., Gerhard A., Tabrizi S.J., Barker R.A., Brooks D.J., Piccini P. Microglial activation in presymptomatic Huntington’s disease gene carriers. Brain J. Neurol. 2007;130:1759–1766. doi: 10.1093/brain/awm044. [DOI] [PubMed] [Google Scholar]
• 87.Politis M., Pavese N., Tai Y.F., Tabrizi S.J., Barker R.A., Piccini P. Hypothalamic involvement in Huntington’s disease: An in vivo PET study. Brain J. Neurol. 2008;131:2860–2869. doi: 10.1093/brain/awn244. [DOI] [PubMed] [Google Scholar]
• 88.Politis M., Pavese N., Tai Y.F., Kiferle L., Mason S.L., Brooks D.J., Tabrizi S.J., Barker R.A., Piccini P. Microglial activation in regions related to cognitive function predicts disease onset in Huntington’s disease: A multimodal imaging study. Hum. Brain Mapp. 2011;32:258–270. doi: 10.1002/hbm.21008. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 89.Politis M., Lahiri N., Niccolini F., Su P., Wu K., Giannetti P., Scahill R.I., Turkheimer F.E., Tabrizi S.J., Piccini P. Increased central microglial activation associated with peripheral cytokine levels in premanifest Huntington’s disease gene carriers. Neurobiol. Dis. 2015;83:115–121. doi: 10.1016/j.nbd.2015.08.011. [DOI] [PubMed] [Google Scholar]
• 90.Mehrabi N.F., Waldvogel H.J., Tippett L.J., Hogg V.M., Synek B.J., Faull R.L.M. Symptom heterogeneity in Huntington’s disease correlates with neuronal degeneration in the cerebral cortex. Neurobiol. Dis. 2016;96:67–74. doi: 10.1016/j.nbd.2016.08.015. [DOI] [PubMed] [Google Scholar]
• 91.Vuono R., Winder-Rhodes S., de Silva R., Cisbani G., Drouin-Ouellet J., REGISTRY Investigators of the European Huntington’s Disease Network. Spillantini M.G., Cicchetti F., Barker R.A. The role of tau in the pathological process and clinical expression of Huntington’s disease. Brain J. Neurol. 2015;138:1907–1918. doi: 10.1093/brain/awv107. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 92.Dos Santos Picanço L.C., Ozela P.F., de Fátima de Brito Brito M., Pinheiro A.A., Padilha E.C., Braga F.S., de Paula da Silva C.H.T., Dos Santos C.B.R., Rosa J.M.C., da Silva Hage-Melim L.I. Alzheimer’s disease: A review from the pathophysiology to diagnosis, new perspectives for pharmacological treatment. Curr. Med. Chem. 2016 doi: 10.2174/0929867323666161213101126. [DOI] [PubMed] [Google Scholar]
• 93.Furman J.L., Vaquer-Alicea J., White C.L., Cairns N.J., Nelson P.T., Diamond M.I. Widespread tau seeding activity at early Braak stages. Acta Neuropathol. 2017;133:91–100. doi: 10.1007/s00401-016-1644-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 94.Harris J.A., Devidze N., Verret L., Ho K., Halabisky B., Thwin M.T., Kim D., Hamto P., Lo I., Yu G.-Q., et al. Transsynaptic progression of amyloid-β-induced neuronal dysfunction within the entorhinal-hippocampal network. Neuron. 2010;68:428–441. doi: 10.1016/j.neuron.2010.10.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 95.Braak H., Alafuzoff I., Arzberger T., Kretzschmar H., Del Tredici K. Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 2006;112:389–404. doi: 10.1007/s00401-006-0127-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 96.Ingelsson M., Fukumoto H., Newell K.L., Growdon J.H., Hedley-Whyte E.T., Frosch M.P., Albert M.S., Hyman B.T., Irizarry M.C. Early Abeta accumulation and progressive synaptic loss, gliosis, and tangle formation in AD brain. Neurology. 2004;62:925–931. doi: 10.1212/01.WNL.0000115115.98960.37. [DOI] [PubMed] [Google Scholar]
• 97.Lyman M., Lloyd D.G., Ji X., Vizcaychipi M.P., Ma D. Neuroinflammation: The role and consequences. Neurosci. Res. 2014;79:1–12. doi: 10.1016/j.neures.2013.10.004. [DOI] [PubMed] [Google Scholar]
• 98.Morales I., Guzmán-Martínez L., Cerda-Troncoso C., Farías G.A., Maccioni R.B. Neuroinflammation in the pathogenesis of Alzheimer’s disease. A rational framework for the search of novel therapeutic approaches. Front. Cell. Neurosci. 2014;8:112. doi: 10.3389/fncel.2014.00112. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 99.Calsolaro V., Edison P. Neuroinflammation in Alzheimer’s disease: Current evidence and future directions. Alzheimers Dement. 2016;12:719–732. doi: 10.1016/j.jalz.2016.02.010. [DOI] [PubMed] [Google Scholar]
• 100.Cagnin A., Brooks D.J., Kennedy A.M., Gunn R.N., Myers R., Turkheimer F.E., Jones T., Banati R.B. In Vivo measurement of activated microglia in dementia. Lancet. 2001;358:461–467. doi: 10.1016/S0140-6736(01)05625-2. [DOI] [PubMed] [Google Scholar]
• 101.Kreisl W.C., Lyoo C.H., Liow J.-S., Wei M., Snow J., Page E., Jenko K.J., Morse C.L., Zoghbi S.S., Pike V.W., et al. (11)C-PBR28 binding to translocator protein increases with progression of Alzheimer’s disease. Neurobiol. Aging. 2016;44:53–61. doi: 10.1016/j.neurobiolaging.2016.04.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 102.Lyoo C.H., Ikawa M., Liow J.-S., Zoghbi S.S., Morse C.L., Pike V.W., Fujita M., Innis R.B., Kreisl W.C. Cerebellum can serve as a pseudo-reference region in Alzheimer disease to detect neuroinflammation measured with pet radioligand binding to translocator protein. J. Nucl. Med. 2015;56:701–706. doi: 10.2967/jnumed.114.146027. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 103.Fan Z., Okello A.A., Brooks D.J., Edison P. Longitudinal influence of microglial activation and amyloid on neuronal function in Alzheimer’s disease. Brain J. Neurol. 2015;138:3685–3698. doi: 10.1093/brain/awv288. [DOI] [PubMed] [Google Scholar]
• 104.Suridjan I., Pollock B.G., Verhoeff N.P.L.G., Voineskos A.N., Chow T., Rusjan P.M., Lobaugh N.J., Houle S., Mulsant B.H., Mizrahi R. In Vivo imaging of grey and white matter neuroinflammation in Alzheimer’s disease: A positron emission tomography study with a novel radioligand, [18F]-FEPPA. Mol. Psychiatry. 2015;20:1579–1587. doi: 10.1038/mp.2015.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 105.Edison P., Archer H.A., Gerhard A., Hinz R., Pavese N., Turkheimer F.E., Hammers A., Tai Y.F., Fox N., Kennedy A., et al. Microglia, amyloid, and cognition in Alzheimer’s disease: An [11C](R)PK11195-PET and [11C]PIB-PET study. Neurobiol. Dis. 2008;32:412–419. doi: 10.1016/j.nbd.2008.08.001. [DOI] [PubMed] [Google Scholar]
• 106.Yokokura M., Mori N., Yagi S., Yoshikawa E., Kikuchi M., Yoshihara Y., Wakuda T., Sugihara G., Takebayashi K., Suda S., et al. In vivo changes in microglial activation and amyloid deposits in brain regions with hypometabolism in Alzheimer’s disease. Eur. J. Nucl. Med. Mol. Imaging. 2011;38:343–351. doi: 10.1007/s00259-010-1612-0. [DOI] [PubMed] [Google Scholar]
• 107.Yasuno F., Ota M., Kosaka J., Ito H., Higuchi M., Doronbekov T.K., Nozaki S., Fujimura Y., Koeda M., Asada T., Suhara T. Increased binding of peripheral benzodiazepine receptor in Alzheimer’s disease measured by positron emission tomography with [11C]DAA. Biol. Psychiatry. 2008;64:835–841. doi: 10.1016/j.biopsych.2008.04.021. [DOI] [PubMed] [Google Scholar]
• 108.Yasuno F., Kosaka J., Ota M., Higuchi M., Ito H., Fujimura Y., Nozaki S., Takahashi S., Mizukami K., Asada T., et al. Increased binding of peripheral benzodiazepine receptor in mild cognitive impairment-dementia converters measured by positron emission tomography with [11C]DAA1106. Psychiatry Res. 2012;203:67–74. doi: 10.1016/j.pscychresns.2011.08.013. [DOI] [PubMed] [Google Scholar]
• 109.Kreisl W.C., Lyoo C.H., McGwier M., Snow J., Jenko K.J., Kimura N., Corona W., Morse C.L., Zoghbi S.S., Pike V.W., et al. In vivo radioligand binding to translocator protein correlates with severity of Alzheimer’s disease. Brain J. Neurol. 2013;136:2228–2238. doi: 10.1093/brain/awt145. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 110.Hamelin L., Lagarde J., Dorothée G., Leroy C., Labit M., Comley R.A., de Souza L.C., Corne H., Dauphinot L., Bertoux M., et al. Early and protective microglial activation in Alzheimer’s disease: A prospective study using 18F-DPA-714 PET imaging. Brain J. Neurol. 2016;139:1252–1264. doi: 10.1093/brain/aww017. [DOI] [PubMed] [Google Scholar]
• 111.Wiley C.A., Lopresti B.J., Venneti S., Price J., Klunk W.E., DeKosky S.T., Mathis C.A. Carbon 11-labeled Pittsburgh Compound B and carbon 11-labeled (R)-PK11195 positron emission tomographic imaging in Alzheimer disease. Arch. Neurol. 2009;66:60–67. doi: 10.1001/archneurol.2008.511. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 112.Schuitemaker A., Kropholler M.A., Boellaard R., van der Flier W.M., Kloet R.W., van der Doef T.F., Knol D.L., Windhorst A.D., Luurtsema G., Barkhof F., et al. Microglial activation in Alzheimer’s disease: An (R)-[11C]PK11195 positron emission tomography study. Neurobiol. Aging. 2013;34:128–136. doi: 10.1016/j.neurobiolaging.2012.04.021. [DOI] [PubMed] [Google Scholar]
• 113.Albert M.S., DeKosky S.T., Dickson D., Dubois B., Feldman H.H., Fox N.C., Gamst A., Holtzman D.M., Jagust W.J., Petersen R.C., et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. J. Alzheimers Assoc. 2011;7:270–279. doi: 10.1016/j.jalz.2011.03.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 114.Villemagne V.L., Doré V., Bourgeat P., Burnham S.C., Laws S., Salvado O., Masters C.L., Rowe C.C. Aβ-amyloid and Tau Imaging in Dementia. Semin. Nucl. Med. 2017;47:75–88. doi: 10.1053/j.semnuclmed.2016.09.006. [DOI] [PubMed] [Google Scholar]
• 115.Okello A., Edison P., Archer H.A., Turkheimer F.E., Kennedy J., Bullock R., Walker Z., Kennedy A., Fox N., Rossor M., et al. Microglial activation and amyloid deposition in mild cognitive impairment: A PET study. Neurology. 2009;72:56–62. doi: 10.1212/01.wnl.0000338622.27876.0d. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 116.Melah K.E., Lu S.Y.-F., Hoscheidt S.M., Alexander A.L., Adluru N., Destiche D.J., Carlsson C.M., Zetterberg H., Blennow K., Okonkwo O.C., et al. Cerebrospinal Fluid Markers of Alzheimer’s Disease Pathology and Microglial Activation are Associated with Altered White Matter Microstructure in Asymptomatic Adults at Risk for Alzheimer’s Disease. J. Alzheimers Dis. JAD. 2016;50:873–886. doi: 10.3233/JAD-150897. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 117.Serrano-Pozo A., Frosch M.P., Masliah E., Hyman B.T. Neuropathological alterations in Alzheimer disease. Cold Spring Harb. Perspect. Med. 2011;1:a006189. doi: 10.1101/cshperspect.a006189. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 118.Nelson P.T., Alafuzoff I., Bigio E.H., Bouras C., Braak H., Cairns N.J., Castellani R.J., Crain B.J., Davies P., Del Tredici K., et al. Correlation of Alzheimer Disease Neuropathologic Changes With Cognitive Status: A Review of the Literature. J. Neuropathol. Exp. Neurol. 2012;71:362–381. doi: 10.1097/NEN.0b013e31825018f7. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 119.Jack C.R., Knopman D.S., Jagust W.J., Petersen R.C., Weiner M.W., Aisen P.S., Shaw L.M., Vemuri P., Wiste H.J., Weigand S.D., et al. Tracking pathophysiological processes in Alzheimer’s disease: An updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207–216. doi: 10.1016/S1474-4422(12)70291-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 120.Maezawa I., Zimin P.I., Wulff H., Jin L.-W. Amyloid-beta protein oligomer at low nanomolar concentrations activates microglia and induces microglial neurotoxicity. J. Biol. Chem. 2011;286:3693–3706. doi: 10.1074/jbc.M110.135244. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 121.Marlatt M.W., Bauer J., Aronica E., van Haastert E.S., Hoozemans J.J.M., Joels M., Lucassen P.J. Proliferation in the Alzheimer hippocampus is due to microglia, not astroglia, and occurs at sites of amyloid deposition. Neural Plast. 2014;2014:693851. doi: 10.1155/2014/693851. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 122.Cherry J.D., Olschowka J.A., O’Banion M.K. Neuroinflammation and M2 microglia: The good, the bad, and the inflamed. J. Neuroinflamm. 2014;11:98. doi: 10.1186/1742-2094-11-98. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 123.Prokop S., Miller K.R., Heppner F.L. Microglia actions in Alzheimer’s disease. Acta Neuropathol. 2013;126:461–477. doi: 10.1007/s00401-013-1182-x. [DOI] [PubMed] [Google Scholar]
• 124.Thal D.R., Rüb U., Orantes M., Braak H. Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology. 2002;58:1791–1800. doi: 10.1212/WNL.58.12.1791. [DOI] [PubMed] [Google Scholar]
• 125.Fan Z., Aman Y., Ahmed I., Chetelat G., Landeau B., Ray Chaudhuri K., Brooks D.J., Edison P. Influence of microglial activation on neuronal function in Alzheimer’s and Parkinson’s disease dementia. Alzheimers Dement. 2015;11:608.e7–621.e7. doi: 10.1016/j.jalz.2014.06.016. [DOI] [PubMed] [Google Scholar]
• 126.Wang W.-Y., Tan M.-S., Yu J.-T., Tan L. Role of pro-inflammatory cytokines released from microglia in Alzheimer’s disease. Ann. Transl. Med. 2015;3:136. doi: 10.3978/j.issn.2305-5839.2015.03.49. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 127.Zhao W., Zhang J., Davis E.G., Rebeck G.W. Aging reduces glial uptake and promotes extracellular accumulation of Aβ from a lentiviral vector. Front. Aging Neurosci. 2014;6:210. doi: 10.3389/fnagi.2014.00210. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 128.Davies D.S., Ma J., Jegathees T., Goldsbury A.C. Microglia show altered morphology and reduced arborisation in human brain during aging and Alzheimer’s disease. Brain Pathol. 2016 doi: 10.1111/bpa.12456. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 129.Jimenez S., Baglietto-Vargas D., Caballero C., Moreno-Gonzalez I., Torres M., Sanchez-Varo R., Ruano D., Vizuete M., Gutierrez A., Vitorica J. Inflammatory response in the hippocampus of PS1M146L/APP751SL mouse model of Alzheimer’s disease: Age-dependent switch in the microglial phenotype from alternative to classic. J. Neurosci. 2008;28:11650–11661. doi: 10.1523/JNEUROSCI.3024-08.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 130.Cagnin A., Rossor M., Sampson E.L., Mackinnon T., Banati R.B. In vivo detection of microglial activation in frontotemporal dementia. Ann. Neurol. 2004;56:894–897. doi: 10.1002/ana.20332. [DOI] [PubMed] [Google Scholar]
• 131.Miyoshi M., Shinotoh H., Wszolek Z.K., Strongosky A.J., Shimada H., Arakawa R., Higuchi M., Ikoma Y., Yasuno F., Fukushi K., et al. In vivo detection of neuropathologic changes in presymptomatic MAPT mutation carriers: A PET and MRI study. Parkinsonism Relat. Disord. 2010;16:404–408. doi: 10.1016/j.parkreldis.2010.04.004. [DOI] [PubMed] [Google Scholar]
• 132.Femminella G.D., Ninan S., Atkinson R., Fan Z., Brooks D.J., Edison P. Does Microglial Activation Influence Hippocampal Volume and Neuronal Function in Alzheimer’s Disease and Parkinson’s Disease Dementia? J. Alzheimers Dis. 2016;51:1275–1289. doi: 10.3233/JAD-150827. [DOI] [PubMed] [Google Scholar]
• 133.Schou M., Varnäs K., Sandell J., Johnström P., Cselenyi Z., Svensson S., Nakao R., Amini N., Bergman L., Sumic A., et al. Synthesis, radiolabeling, and in vivo pharmacokinetic evaluation of the amyloid β radioligand [11C]AZD4694 in nonhuman primates. Mol. Imaging Biol. 2014;16:173–179. doi: 10.1007/s11307-013-0666-3. [DOI] [PubMed] [Google Scholar]
• 134.Varrone A., Mattsson P., Forsberg A., Takano A., Nag S., Gulyás B., Borg J., Boellaard R., Al-Tawil N., Eriksdotter M., et al. In vivo imaging of the 18-kDa translocator protein (TSPO) with [18F]FEDAA1106 and PET does not show increased binding in Alzheimer’s disease patients. Eur. J. Nucl. Med. Mol. Imaging. 2013;40:921–931. doi: 10.1007/s00259-013-2359-1. [DOI] [PubMed] [Google Scholar]
• 135.Varrone A., Oikonen V., Forsberg A., Joutsa J., Takano A., Solin O., Haaparanta-Solin M., Nag S., Nakao R., Al-Tawil N., et al. Positron emission tomography imaging of the 18-kDa translocator protein (TSPO) with [18F]FEMPA in Alzheimer’s disease patients and control subjects. Eur. J. Nucl. Med. Mol. Imaging. 2015;42:438–446. doi: 10.1007/s00259-014-2955-8. [DOI] [PubMed] [Google Scholar]
• 136.Golla S.S.V., Boellaard R., Oikonen V., Hoffmann A., van Berckel B.N.M., Windhorst A.D., Virta J., Haaparanta-Solin M., Luoto P., Savisto N., et al. Quantification of [18F]DPA-714 binding in the human brain: Initial studies in healthy controls and Alzheimer’s disease patients. J. Cereb. Blood Flow Metab. 2015;35:766–772. doi: 10.1038/jcbfm.2014.261. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 137.Ghetti B., Oblak A.L., Boeve B.F., Johnson K.A., Dickerson B.C., Goedert M. Invited review: Frontotemporal dementia caused by microtubule-associated protein tau gene (MAPT) mutations: A chameleon for neuropathology and neuroimaging. Neuropathol. Appl. Neurobiol. 2015;41:24–46. doi: 10.1111/nan.12213. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 138.Irwin D.J., Cairns N.J., Grossman M., McMillan C.T., Lee E.B., Van Deerlin V.M., Lee V.M.-Y., Trojanowski J.Q. Frontotemporal Lobar Degeneration: Defining Phenotypic Diversity Through Personalized Medicine. Acta Neuropathol. 2015;129:469–491. doi: 10.1007/s00401-014-1380-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 139.Seltman R.E., Matthews B.R. Frontotemporal lobar degeneration: Epidemiology, pathology, diagnosis and management. CNS Drugs. 2012;26:841–870. doi: 10.2165/11640070-000000000-00000. [DOI] [PubMed] [Google Scholar]
• 140.Byrnes K.R., Washington P.M., Knoblach S.M., Hoffman E., Faden A.I. Delayed inflammatory mRNA and protein expression after spinal cord injury. J. Neuroinflamm. 2011;8:130. doi: 10.1186/1742-2094-8-130. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 141.Mackenzie I.R.A., Neumann M. Molecular neuropathology of frontotemporal dementia: Insights into disease mechanisms from postmortem studies. J. Neurochem. 2016;138(Suppl. S1):54–70. doi: 10.1111/jnc.13588. [DOI] [PubMed] [Google Scholar]
• 142.Park H.K., Chung S.J. New perspective on Parkinsonism in frontotemporal lobar degeneration. J. Mov. Disord. 2013;6:1–8. doi: 10.14802/jmd.13001. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 143.Kiernan M.C., Vucic S., Cheah B.C., Turner M.R., Eisen A., Hardiman O., Burrell J.R., Zoing M.C. Amyotrophic lateral sclerosis. Lancet. 2011;377:942–955. doi: 10.1016/S0140-6736(10)61156-7. [DOI] [PubMed] [Google Scholar]
• 144.Gordon P.H. Amyotrophic Lateral Sclerosis: An update for 2013 Clinical Features, Pathophysiology, Management and Therapeutic Trials. Aging Dis. 2013;4:295–310. doi: 10.14336/AD.2013.0400295. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 145.Byrne S., Heverin M., Elamin M., Bede P., Lynch C., Kenna K., MacLaughlin R., Walsh C., Al Chalabi A., Hardiman O. Aggregation of neurologic and neuropsychiatric disease in amyotrophic lateral sclerosis kindreds: A population-based case-control cohort study of familial and sporadic amyotrophic lateral sclerosis. Ann. Neurol. 2013;74:699–708. doi: 10.1002/ana.23969. [DOI] [PubMed] [Google Scholar]
• 146.Appel S.H., Zhao W., Beers D.R., Henkel J.S. The microglial-motoneuron dialogue in ALS. Acta Myol. Myopathies Cardiomyopathies Off. J. Mediterr. Soc. Myol. 2011;30:4–8. [PMC free article] [PubMed] [Google Scholar]
• 147.Zürcher N.R., Loggia M.L., Lawson R., Chonde D.B., Izquierdo-Garcia D., Yasek J.E., Akeju O., Catana C., Rosen B.R., Cudkowicz M.E., et al. Increased in vivo glial activation in patients with amyotrophic lateral sclerosis: Assessed with [11C]-PBR28. NeuroImage Clin. 2015;7:409–414. doi: 10.1016/j.nicl.2015.01.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 148.Corcia P., Tauber C., Vercoullie J., Arlicot N., Prunier C., Praline J., Nicolas G., Venel Y., Hommet C., Baulieu J.L., et al. Molecular imaging of microglial activation in amyotrophic lateral sclerosis. PLoS ONE. 2012;7:e52941. doi: 10.1371/journal.pone.0052941. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 149.Brettschneider J., Toledo J.B., Van Deerlin V.M., Elman L., McCluskey L., Lee V.M.-Y., Trojanowski J.Q. Microglial activation correlates with disease progression and upper motor neuron clinical symptoms in amyotrophic lateral sclerosis. PLoS ONE. 2012;7:e39216. doi: 10.1371/journal.pone.0039216. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 150.Lee J.C., Seong J., Kim S.H., Lee S.J., Cho Y.J., An J., Nam D.-H., Joo K.M., Cha C.I. Replacement of microglial cells using Clodronate liposome and bone marrow transplantation in the central nervous system of SOD1(G93A) transgenic mice as an in vivo model of amyotrophic lateral sclerosis. Biochem. Biophys. Res. Commun. 2012;418:359–365. doi: 10.1016/j.bbrc.2012.01.026. [DOI] [PubMed] [Google Scholar]
• 151.Henkel J.S., Beers D.R., Siklós L., Appel S.H. The chemokine MCP-1 and the dendritic and myeloid cells it attracts are increased in the mSOD1 mouse model of ALS. Mol. Cell. Neurosci. 2006;31:427–437. doi: 10.1016/j.mcn.2005.10.016. [DOI] [PubMed] [Google Scholar]
• 152.Liao B., Zhao W., Beers D.R., Henkel J.S., Appel S.H. Transformation from a neuroprotective to a neurotoxic microglial phenotype in a mouse model of ALS. Exp. Neurol. 2012;237:147–152. doi: 10.1016/j.expneurol.2012.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 153.AP Association . Diagnostic and Statistical Manual of Mental Disorders (DSM-5®) American Psychiatric Pub; Arlington, VA, USA: 2013. [Google Scholar]
• 154.Sigitova E., Fišar Z., Hroudová J., Cikánková T., Raboch J. Biological hypotheses and biomarkers of bipolar disorder. Psychiatry Clin. Neurosci. 2016 doi: 10.1111/pcn.12476. [DOI] [PubMed] [Google Scholar]
• 155.Haarman B.C.M.B., Riemersma-Van der Lek R.F., de Groot J.C., Ruhé H.G.E., Klein H.C., Zandstra T.E., Burger H., Schoevers R.A., de Vries E.F.J., Drexhage H.A., et al. Neuroinflammation in bipolar disorder—A [11C]-(R)-PK11195 positron emission tomography study. Brain. Behav. Immun. 2014;40:219–225. doi: 10.1016/j.bbi.2014.03.016. [DOI] [PubMed] [Google Scholar]
• 156.Dong X.-H., Zhen X.-C. Glial pathology in bipolar disorder: Potential therapeutic implications. CNS Neurosci. Ther. 2015;21:393–397. doi: 10.1111/cns.12390. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 157.Ustün T.B., Ayuso-Mateos J.L., Chatterji S., Mathers C., Murray C.J.L. Global burden of depressive disorders in the year 2000. Br. J. Psychiatry J. Ment. Sci. 2004;184:386–392. doi: 10.1192/bjp.184.5.386. [DOI] [PubMed] [Google Scholar]
• 158.Boeschoten R.E., Braamse A.M.J., Beekman A.T.F., Cuijpers P., van Oppen P., Dekker J., Uitdehaag B.M.J. Prevalence of depression and anxiety in Multiple Sclerosis: A systematic review and meta-analysis. J. Neurol. Sci. 2017;372:331–341. doi: 10.1016/j.jns.2016.11.067. [DOI] [PubMed] [Google Scholar]
• 159.Borgonovo J., Allende-Castro C., Laliena A., Guerrero N., Silva H., Concha M.L. Changes in neural circuitry associated with depression at pre-clinical, pre-motor and early motor phases of Parkinson’s disease. Park. Relat. Disord. 2017;35:17–24. doi: 10.1016/j.parkreldis.2016.11.009. [DOI] [PubMed] [Google Scholar]
• 160.Fu X., Zunich S.M., O’Connor J.C., Kavelaars A., Dantzer R., Kelley K.W. Central administration of lipopolysaccharide induces depressive-like behavior in vivo and activates brain indoleamine 2,3 dioxygenase in murine organotypic hippocampal slice cultures. J. Neuroinflamm. 2010;7:43. doi: 10.1186/1742-2094-7-43. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 161.Eyre H., Baune B.T. Neuroplastic changes in depression: A role for the immune system. Psychoneuroendocrinology. 2012;37:1397–1416. doi: 10.1016/j.psyneuen.2012.03.019. [DOI] [PubMed] [Google Scholar]
• 162.Udina M., Castellví P., Moreno-España J., Navinés R., Valdés M., Forns X., Langohr K., Solà R., Vieta E., Martín-Santos R. Interferon-induced depression in chronic hepatitis C: A systematic review and meta-analysis. J. Clin. Psychiatry. 2012;73:1128–1138. doi: 10.4088/JCP.12r07694. [DOI] [PubMed] [Google Scholar]
• 163.Frick L.R., Williams K., Pittenger C. Microglial dysregulation in psychiatric disease. Clin. Dev. Immunol. 2013;2013:608654. doi: 10.1155/2013/608654. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 164.Bayer T.A., Buslei R., Havas L., Falkai P. Evidence for activation of microglia in patients with psychiatric illnesses. Neurosci. Lett. 1999;271:126–128. doi: 10.1016/S0304-3940(99)00545-5. [DOI] [PubMed] [Google Scholar]
• 165.Steiner J., Bielau H., Brisch R., Danos P., Ullrich O., Mawrin C., Bernstein H.-G., Bogerts B. Immunological aspects in the neurobiology of suicide: Elevated microglial density in schizophrenia and depression is associated with suicide. J. Psychiatr. Res. 2008;42:151–157. doi: 10.1016/j.jpsychires.2006.10.013. [DOI] [PubMed] [Google Scholar]
• 166.Dean B., Gibbons A.S., Tawadros N., Brooks L., Everall I.P., Scarr E. Different changes in cortical tumor necrosis factor-α-related pathways in schizophrenia and mood disorders. Mol. Psychiatry. 2013;18:767–773. doi: 10.1038/mp.2012.95. [DOI] [PubMed] [Google Scholar]
• 167.Hannestad J., DellaGioia N., Gallezot J.-D., Lim K., Nabulsi N., Esterlis I., Pittman B., Lee J.-Y., O’Connor K.C., Pelletier D., et al. The neuroinflammation marker translocator protein is not elevated in individuals with mild-to-moderate depression: A [11C]PBR28 PET study. Brain. Behav. Immun. 2013;33:131–138. doi: 10.1016/j.bbi.2013.06.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 168.Setiawan E., Wilson A.A., Mizrahi R., Rusjan P.M., Miler L., Rajkowska G., Suridjan I., Kennedy J.L., Rekkas P.V., Houle S., et al. Role of translocator protein density, a marker of neuroinflammation, in the brain during major depressive episodes. JAMA Psychiatry. 2015;72:268–275. doi: 10.1001/jamapsychiatry.2014.2427. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 169.Drevets W.C., Savitz J., Trimble M. The subgenual anterior cingulate cortex in mood disorders. CNS Spectr. 2008;13:663–681. doi: 10.1017/S1092852900013754. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 170.Burger H., Doorduin J., Renken R.J., Sibeijn-Kuiper A.J., Marsman J.-B.C., de Vries E.F.J., de Groot J.C., Drexhage H.A., Mendes R., Nolen W.A., et al. Volume, metabolites and neuroinflammation of the hippocampus in bipolar disorder—A combined magnetic resonance imaging and positron emission tomography study. Brain. Behav. Immun. 2016;56:21–33. doi: 10.1016/j.bbi.2015.09.004. [DOI] [PubMed] [Google Scholar]
• 171.Van Berckel B.N., Bossong M.G., Boellaard R., Kloet R., Schuitemaker A., Caspers E., Luurtsema G., Windhorst A.D., Cahn W., Lammertsma A.A., et al. Microglia activation in recent-onset schizophrenia: A quantitative (R)-[11C]PK11195 positron emission tomography study. Biol. Psychiatry. 2008;64:820–822. doi: 10.1016/j.biopsych.2008.04.025. [DOI] [PubMed] [Google Scholar]
• 172.Doorduin J., de Vries E.F.J., Willemsen A.T.M., de Groot J.C., Dierckx R.A., Klein H.C. Neuroinflammation in schizophrenia-related psychosis: A PET study. J. Nucl. Med. 2009;50:1801–1807. doi: 10.2967/jnumed.109.066647. [DOI] [PubMed] [Google Scholar]
• 173.Takano A., Arakawa R., Ito H., Tateno A., Takahashi H., Matsumoto R., Okubo Y., Suhara T. Peripheral benzodiazepine receptors in patients with chronic schizophrenia: A PET study with [11C]DAA1106. Int. J. Neuropsychopharmacol. 2010;13:943–950. doi: 10.1017/S1461145710000313. [DOI] [PubMed] [Google Scholar]
• 174.Kenk M., Selvanathan T., Rao N., Suridjan I., Rusjan P., Remington G., Meyer J.H., Wilson A.A., Houle S., Mizrahi R. Imaging neuroinflammation in gray and white matter in schizophrenia: An in vivo PET study with [18F]-FEPPA. Schizophr. Bull. 2015;41:85–93. doi: 10.1093/schbul/sbu157. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 175.Bloomfield P.S., Selvaraj S., Veronese M., Rizzo G., Bertoldo A., Owen D.R., Bloomfield M.A.P., Bonoldi I., Kalk N., Turkheimer F., et al. Microglial activity in people at ultra high risk of psychosis and in schizophrenia: An [11C]PBR28 PET brain imaging study. Am. J. Psychiatry. 2016;173:44–52. doi: 10.1176/appi.ajp.2015.14101358. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 176.Coughlin J.M., Wang Y., Ambinder E.B., Ward R.E., Minn I., Vranesic M., Kim P.K., Ford C.N., Higgs C., Hayes L.N., et al. In vivo markers of inflammatory response in recent-onset schizophrenia: A combined study using [11C]DPA-713 PET and analysis of CSF and plasma. Transl. Psychiatry. 2016;6:e777. doi: 10.1038/tp.2016.40. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 177.Notter T., Coughlin J.M., Gschwind T., Weber-Stadlbauer U., Wang Y., Kassiou M., Vernon A.C., Benke D., Pomper M.G., Sawa A., et al. Translational evaluation of translocator protein as a marker of neuroinflammation in schizophrenia. Mol. Psychiatry. 2017 doi: 10.1038/mp.2016.248. [DOI] [PubMed] [Google Scholar]
• 178.Lichtenstein P., Yip B.H., Björk C., Pawitan Y., Cannon T.D., Sullivan P.F., Hultman C.M. Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: A population-based study. Lancet. 2009;373:234–239. doi: 10.1016/S0140-6736(09)60072-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 179.Cross-Disorder Group of the Psychiatric Genomics Consortium Identification of risk loci with shared effects on five major psychiatric disorders: A genome-wide analysis. Lancet. 2013;381:1371–1379. doi: 10.1016/S0140-6736(12)62129-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 180.Gejman P.V., Sanders A.R., Duan J. The role of genetics in the etiology of schizophrenia. Psychiatr. Clin. 2010;33:35–66. doi: 10.1016/j.psc.2009.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 181.Volk D.W. Role of microglia disturbances and immune-related marker abnormalities in cortical circuitry dysfunction in schizophrenia. Neurobiol. Dis. 2016;99:58–65. doi: 10.1016/j.nbd.2016.12.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 182.Trépanier M.O., Hopperton K.E., Mizrahi R., Mechawar N., Bazinet R.P. Postmortem evidence of cerebral inflammation in schizophrenia: A systematic review. Mol. Psychiatry. 2016;21:1009–1026. doi: 10.1038/mp.2016.90. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 183.Slifstein M., Abi-Dargham A. Recent developments in molecular brain imaging of neuropsychiatric disorders. Semin. Nucl. Med. 2017;47:54–63. doi: 10.1053/j.semnuclmed.2016.09.002. [DOI] [PubMed] [Google Scholar]
• 184.Arbo B.D., Benetti F., Garcia-Segura L.M., Ribeiro M.F. Therapeutic actions of translocator protein (18 kDa) ligands in experimental models of psychiatric disorders and neurodegenerative diseases. J. Steroid Biochem. Mol. Biol. 2015;154:68–74. doi: 10.1016/j.jsbmb.2015.07.007. [DOI] [PubMed] [Google Scholar]
• 185.De Faria D.P., Copray S., Buchpiguel C., Dierckx R., de Vries E. PET imaging in multiple sclerosis. J. Neuroimmune Pharmacol. 2014;9:468–482. doi: 10.1007/s11481-014-9544-2. [DOI] [PubMed] [Google Scholar]
• 186.Dulamea A.O. Role of oligodendrocyte dysfunction in demyelination, remyelination and neurodegeneration in multiple sclerosis. Adv. Exp. Med. Biol. 2017;958:91–127. doi: 10.1007/978-3-319-47861-6_7. [DOI] [PubMed] [Google Scholar]
• 187.Gelfand J.M. Multiple sclerosis: Diagnosis, differential diagnosis, and clinical presentation. Handb. Clin. Neurol. 2014;122:269–290. doi: 10.1016/B978-0-444-52001-2.00011-X. [DOI] [PubMed] [Google Scholar]
• 188.Compston A., Coles A. Multiple sclerosis. Lancet. 2008;372:1502–1517. doi: 10.1016/S0140-6736(08)61620-7. [DOI] [PubMed] [Google Scholar]
• 189.Zivadinov R., Pirko I. Advances in understanding gray matter pathology in multiple sclerosis: Are we ready to redefine disease pathogenesis? BMC Neurol. 2012;12:9. doi: 10.1186/1471-2377-12-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 190.Magliozzi R., Howell O.W., Reeves C., Roncaroli F., Nicholas R., Serafini B., Aloisi F., Reynolds R. A Gradient of neuronal loss and meningeal inflammation in multiple sclerosis. Ann. Neurol. 2010;68:477–493. doi: 10.1002/ana.22230. [DOI] [PubMed] [Google Scholar]
• 191.Haider L., Simeonidou C., Steinberger G., Hametner S., Grigoriadis N., Deretzi G., Kovacs G.G., Kutzelnigg A., Lassmann H., Frischer J.M. Multiple sclerosis deep grey matter: The relation between demyelination, neurodegeneration, inflammation and iron. J. Neurol. Neurosurg. Psychiatry. 2014;85:1386–1395. doi: 10.1136/jnnp-2014-307712. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 192.Howell O.W., Rundle J.L., Garg A., Komada M., Brophy P.J., Reynolds R. Activated microglia mediate axoglial disruption that contributes to axonal injury in multiple sclerosis. J. Neuropathol. Exp. Neurol. 2010;69:1017–1033. doi: 10.1097/NEN.0b013e3181f3a5b1. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 193.Gao Z., Tsirka S.E. Animal models of MS reveal multiple roles of microglia in disease pathogenesis. Neurol. Res. Int. 2011;2011:383087. doi: 10.1155/2011/383087. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 194.McMahon E.J., Bailey S.L., Castenada C.V., Waldner H., Miller S.D. Epitope spreading initiates in the CNS in two mouse models of multiple sclerosis. Nat. Med. 2005;11:335–339. doi: 10.1038/nm1202. [DOI] [PubMed] [Google Scholar]
• 195.Frischer J.M., Bramow S., Dal-Bianco A., Lucchinetti C.F., Rauschka H., Schmidbauer M., Laursen H., Sorensen P.S., Lassmann H. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain J. Neurol. 2009;132:1175–1189. doi: 10.1093/brain/awp070. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 196.Skoog B., Tedeholm H., Runmarker B., Odén A., Andersen O. Continuous prediction of secondary progression in the individual course of multiple sclerosis. Mult. Scler. Relat. Disord. 2014;3:584–592. doi: 10.1016/j.msard.2014.04.004. [DOI] [PubMed] [Google Scholar]
• 197.Gajofatto A., Calabrese M., Benedetti M.D., Monaco S. Clinical, MRI, and CSF markers of disability progression in multiple sclerosis. Dis. Markers. 2013;35:687–699. doi: 10.1155/2013/484959. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 198.Politis M., Giannetti P., Su P., Turkheimer F., Keihaninejad S., Wu K., Waldman A., Malik O., Matthews P.M., Reynolds R., et al. Increased PK11195 PET binding in the cortex of patients with MS correlates with disability. Neurology. 2012;79:523–530. doi: 10.1212/WNL.0b013e3182635645. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 199.Debruyne J.C., Versijpt J., van Laere K.J., de Vos F., Keppens J., Strijckmans K., Achten E., Slegers G., Dierckx R.A., Korf J., et al. PET visualization of microglia in multiple sclerosis patients using [11C]PK11195. Eur. J. Neurol. 2003;10:257–264. doi: 10.1046/j.1468-1331.2003.00571.x. [DOI] [PubMed] [Google Scholar]
• 200.Herranz E., Giannì C., Louapre C., Treaba C.A., Govindarajan S.T., Ouellette R., Loggia M.L., Sloane J.A., Madigan N., Izquierdo-Garcia D., et al. Neuroinflammatory component of gray matter pathology in multiple sclerosis. Ann. Neurol. 2016;80:776–790. doi: 10.1002/ana.24791. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 201.Giannetti P., Politis M., Su P., Turkheimer F.E., Malik O., Keihaninejad S., Wu K., Waldman A., Reynolds R., Nicholas R., et al. Increased PK11195-PET binding in normal-appearing white matter in clinically isolated syndrome. Brain J. Neurol. 2015;138:110–119. doi: 10.1093/brain/awu331. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 202.Rissanen E., Tuisku J., Rokka J., Paavilainen T., Parkkola R., Rinne J.O., Airas L. In Vivo Detection of Diffuse Inflammation in Secondary Progressive Multiple Sclerosis Using PET Imaging and the Radioligand 11C-PK11195. J. Nucl. Med. 2014;55:939–944. doi: 10.2967/jnumed.113.131698. [DOI] [PubMed] [Google Scholar]
• 203.Oh U., Fujita M., Ikonomidou V.N., Evangelou I.E., Matsuura E., Harberts E., Fujimura Y., Richert N.D., Ohayon J., Pike V.W., et al. Translocator protein PET imaging for glial activation in multiple sclerosis. J. Neuroimmune Pharmacol. 2011;6:354–361. doi: 10.1007/s11481-010-9243-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 204.Ratchford J.N., Endres C.J., Hammoud D.A., Pomper M.G., Shiee N., McGready J., Pham D.L., Calabresi P.A. Decreased microglial activation in MS patients treated with glatiramer acetate. J. Neurol. 2012;259:1199–1205. doi: 10.1007/s00415-011-6337-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 205.Colasanti A., Guo Q., Muhlert N., Giannetti P., Onega M., Newbould R.D., Ciccarelli O., Rison S., Thomas C., Nicholas R., et al. In Vivo Assessment of Brain White Matter Inflammation in Multiple Sclerosis with 18F-PBR111 PET. J. Nucl. Med. 2014;55:1112–1118. doi: 10.2967/jnumed.113.135129. [DOI] [PubMed] [Google Scholar]
• 206.Giannetti P., Politis M., Su P., Turkheimer F., Malik O., Keihaninejad S., Wu K., Reynolds R., Nicholas R., Piccini P. Microglia activation in multiple sclerosis black holes predicts outcome in progressive patients: An in vivo [11C](R)-PK11195-PET pilot study. Neurobiol. Dis. 2014;65:203–210. doi: 10.1016/j.nbd.2014.01.018. [DOI] [PubMed] [Google Scholar]
• 207.Magliozzi R., Howell O., Vora A., Serafini B., Nicholas R., Puopolo M., Reynolds R., Aloisi F. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain J. Neurol. 2007;130:1089–1104. doi: 10.1093/brain/awm038. [DOI] [PubMed] [Google Scholar]
• 208.Howell O.W., Reeves C.A., Nicholas R., Carassiti D., Radotra B., Gentleman S.M., Serafini B., Aloisi F., Roncaroli F., Magliozzi R., et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain J. Neurol. 2011;134:2755–2771. doi: 10.1093/brain/awr182. [DOI] [PubMed] [Google Scholar]
• 209.Kooi E.-J., Strijbis E.M.M., van der Valk P., Geurts J.J.G. Heterogeneity of cortical lesions in multiple sclerosis: Clinical and pathologic implications. Neurology. 2012;79:1369–1376. doi: 10.1212/WNL.0b013e31826c1b1c. [DOI] [PubMed] [Google Scholar]
• 210.Banati R.B., Newcombe J., Gunn R.N., Cagnin A., Turkheimer F., Heppner F., Price G., Wegner F., Giovannoni G., Miller D.H., et al. The peripheral benzodiazepine binding site in the brain in multiple sclerosis: Quantitative in vivo imaging of microglia as a measure of disease activity. Brain J. Neurol. 2000;123(Pt 11):2321–2337. doi: 10.1093/brain/123.11.2321. [DOI] [PubMed] [Google Scholar]
• 211.Datta G., Violante I.R., Scott G., Zimmerman K., Santos-Ribeiro A., Rabiner E.A., Gunn R.N., Malik O., Ciccarelli O., Nicholas R., et al. Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis. Mult. Scler. 2016;11:127–134. doi: 10.1177/1352458516681504. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 212.Schrempf W., Ziemssen T. Glatiramer acetate: Mechanisms of action in multiple sclerosis. Autoimmun. Rev. 2007;6:469–475. doi: 10.1016/j.autrev.2007.02.003. [DOI] [PubMed] [Google Scholar]
• 213.Vowinckel E., Reutens D., Becher B., Verge G., Evans A., Owens T., Antel J.P. PK11195 binding to the peripheral benzodiazepine receptor as a marker of microglia activation in multiple sclerosis and experimental autoimmune encephalomyelitis. J. Neurosci. Res. 1997;50:345–353. doi: 10.1002/(SICI)1097-4547(19971015)50:2<345::AID-JNR22>3.0.CO;2-5. [DOI] [PubMed] [Google Scholar]
• 214.Versijpt J., Debruyne J.C., Van Laere K.J., De Vos F., Keppens J., Strijckmans K., Achten E., Slegers G., Dierckx R.A., Korf J., et al. Microglial imaging with positron emission tomography and atrophy measurements with magnetic resonance imaging in multiple sclerosis: A correlative study. Mult. Scler. 2005;11:127–134. doi: 10.1191/1352458505ms1140oa. [DOI] [PubMed] [Google Scholar]
• 215.Takano A., Piehl F., Hillert J., Varrone A., Nag S., Gulyás B., Stenkrona P., Villemagne V.L., Rowe C.C., Macdonell R., et al. In vivo TSPO imaging in patients with multiple sclerosis: A brain PET study with [18F]FEDAA1106. EJNMMI Res. 2013;3:30. doi: 10.1186/2191-219X-3-30. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 216.Park E., Gallezot J.-D., Delgadillo A., Liu S., Planeta B., Lin S.-F., O’Connor K.C., Lim K., Lee J.-Y., Chastre A., et al. (11)C-PBR28 imaging in multiple sclerosis patients and healthy controls: Test-retest reproducibility and focal visualization of active white matter areas. Eur. J. Nucl. Med. Mol. Imaging. 2015;42:1081–1092. doi: 10.1007/s00259-015-3043-4. [DOI] [PubMed] [Google Scholar]
• 217.Trigg W., Buckley C., Heurling K., Sherwin P., Brooks D., Sridharan S., Hinz R., Crouch J., Lawlor M., Amodeo S., et al. Evaluation of [18F]GE-180 PET Imaging in Relapsing-Remitting Multiple Sclerosis Patients: A First-In-Human Study [Abstract] [(accessed on 20 January 2017)]; Available online: http://onlinelibrary.ectrims-congress.eu/ectrims/2015/31st/115715/william.trigg.evaluation.of.%5B%3Csup%3E18%3C.sup%3Ef%5Dge-180.pet.imaging.in.html.
• 218.Colasanti A., Guo Q., Giannetti P., Wall M.B., Newbould R.D., Bishop C., Onega M., Nicholas R., Ciccarelli O., Muraro P.A., et al. Hippocampal Neuroinflammation, functional connectivity, and depressive symptoms in multiple sclerosis. Biol. Psychiatry. 2016;80:62–72. doi: 10.1016/j.biopsych.2015.11.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 219.Martin A., Szczupak B., Gomez-Vallejo V., Domercq M., Cano A., Padro D., Munoz C., Higuchi M., Matute C., Llop J. In Vivo PET Imaging of the 4 2 Nicotinic Acetylcholine Receptor as a Marker for Brain Inflammation after Cerebral Ischemia. J. Neurosci. 2015;35:5998–6009. doi: 10.1523/JNEUROSCI.3670-14.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 220.Zinnhardt B., Viel T., Wachsmuth L., Vrachimis A., Wagner S., Breyholz H.J., Faust A., Hermann S., Kopka K., Faber C., et al. Multimodal imaging reveals temporal and spatial microglia and matrix metalloproteinase activity after experimental stroke. J. Cereb. Blood Flow Metab. Off. J. Int. Soc. Cereb. Blood Flow Metab. 2015;35:1711–1721. doi: 10.1038/jcbfm.2015.149. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 221.Domercq M., Szczupak B., Gejo J., Gómez-Vallejo V., Padro D., Gona K.B., Dollé F., Higuchi M., Matute C., Llop J., et al. PET imaging with [18F]FSPG evidences the role of system xc− on brain inflammation following cerebral ischemia in rats. Theranostics. 2016;6:1753–1767. doi: 10.7150/thno.15616. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 222.Martín A., Vázquez-Villoldo N., Gómez-Vallejo V., Padro D., Soria F.N., Szczupak B., Plaza-García S., Arrieta A., Reese T., Llop J., et al. In vivo imaging of system xc- as a novel approach to monitor multiple sclerosis. Eur. J. Nucl. Med. Mol. Imaging. 2016;43:1124–1138. doi: 10.1007/s00259-015-3275-3. [DOI] [PubMed] [Google Scholar]
• 223.Shukuri M., Takashima-Hirano M., Tokuda K., Takashima T., Matsumura K., Inoue O., Doi H., Suzuki M., Watanabe Y., Onoe H. In vivo expression of cyclooxygenase-1 in activated microglia and macrophages during neuroinflammation visualized by PET with 11C-ketoprofen methyl ester. J. Nucl. Med. 2011;52:1094–1101. doi: 10.2967/jnumed.110.084046. [DOI] [PubMed] [Google Scholar]
• 224.Shen L.-H., Liao M.-H., Tseng Y.-C. Recent advances in imaging of dopaminergic neurons for evaluation of neuropsychiatric disorders. J. Biomed. Biotechnol. 2012;2012:259349. doi: 10.1155/2012/259349. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 225.Karimi M., Perlmutter J.S. The role of dopamine and dopaminergic pathways in dystonia: Insights from neuroimaging. Tremor Hyperkinetic Mov. 2015;5:280. doi: 10.7916/D8J101XV. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 226.Dehmer T., Lindenau J., Haid S., Dichgans J., Schulz J.B. Deficiency of inducible nitric oxide synthase protects against MPTP toxicity in vivo. J. Neurochem. 2000;74:2213–2216. doi: 10.1046/j.1471-4159.2000.0742213.x. [DOI] [PubMed] [Google Scholar]
• 227.Guttman M., Stewart D., Hussey D., Wilson A., Houle S., Kish S. Influence of L-dopa and pramipexole on striatal dopamine transporter in early PD. Neurology. 2001;56:1559–1564. doi: 10.1212/WNL.56.11.1559. [DOI] [PubMed] [Google Scholar]
• 228.Kumakura Y., Danielsen E.H., Reilhac A., Gjedde A., Cumming P. Levodopa effect on [18F]fluorodopa influx to brain: Normal volunteers and patients with Parkinson’s disease. Acta Neurol. Scand. 2004;110:188–195. doi: 10.1111/j.1600-0404.2004.00299.x. [DOI] [PubMed] [Google Scholar]
• 229.Hu X., Liou A.K.F., Leak R.K., Xu M., An C., Suenaga J., Shi Y., Gao Y., Zheng P., Chen J. Neurobiology of microglial action in CNS injuries: Receptor-mediated signaling mechanisms and functional roles. Prog. Neurobiol. 2014;119:60–84. doi: 10.1016/j.pneurobio.2014.06.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 230.Schapansky J., Nardozzi J.D., LaVoie M.J. The complex relationships between microglia, alpha-synuclein, and LRRK2 in Parkinson’s disease. Neuroscience. 2015;302:74–88. doi: 10.1016/j.neuroscience.2014.09.049. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 231.Tarkkonen A., Rissanen E., Tuokkola T., Airas L. Utilization of PET imaging in differential diagnostics between a tumefactive multiple sclerosis lesion and low-grade glioma. Mult. Scler. Relat. Disord. 2016;9:147–149. doi: 10.1016/j.msard.2016.07.016. [DOI] [PubMed] [Google Scholar]
• 232.Van Schependom J., Jain S., Cambron M., Vanbinst A.-M., De Mey J., Smeets D., Nagels G. Reliability of measuring regional callosal atrophy in neurodegenerative diseases. NeuroImage Clin. 2016;12:825–831. doi: 10.1016/j.nicl.2016.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 233.Pini L., Pievani M., Bocchetta M., Altomare D., Bosco P., Cavedo E., Galluzzi S., Marizzoni M., Frisoni G.B. Brain atrophy in Alzheimer’s Disease and aging. Ageing Res. Rev. 2016;30:25–48. doi: 10.1016/j.arr.2016.01.002. [DOI] [PubMed] [Google Scholar]
• 234.Di Paola M., Macaluso E., Carlesimo G.A., Tomaiuolo F., Worsley K.J., Fadda L., Caltagirone C. Episodic memory impairment in patients with Alzheimer’s disease is correlated with entorhinal cortex atrophy. A voxel-based morphometry study. J. Neurol. 2007;254:774–781. doi: 10.1007/s00415-006-0435-1. [DOI] [PubMed] [Google Scholar]
• 235.Harrison N.A., Cooper E., Dowell N.G., Keramida G., Voon V., Critchley H.D., Cercignani M. Quantitative Magnetization Transfer Imaging as a Biomarker for Effects of Systemic Inflammation on the Brain. Biol. Psychiatry. 2015;78:49–57. doi: 10.1016/j.biopsych.2014.09.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 236.Liu Z., Pardini M., Yaldizli Ö., Sethi V., Muhlert N., Wheeler-Kingshott C.A.M., Samson R.S., Miller D.H., Chard D.T. Magnetization transfer ratio measures in normal-appearing white matter show periventricular gradient abnormalities in multiple sclerosis. Brain J. Neurol. 2015;138:1239–1246. doi: 10.1093/brain/awv065. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 237.Chen Y.Z., Dai Z.Z., Shen Z.W., Lin G.S., Zhuang C.Y., Li H.J., Wu R.H. Magnetic resonance imaging of glutamate in neuroinflammation. Radiol. Infect. Dis. 2016;3:92–97. doi: 10.1016/j.jrid.2016.03.006. [DOI] [Google Scholar]
• 238.Bray N., Burrows F.E., Jones M., Berwick J., Allan S.M., Schiessl I. Decreased haemodynamic response and decoupling of cortical gamma-band activity and tissue oxygen perfusion after striatal interleukin-1 injection. J. Neuroinflamm. 2016;13:195. doi: 10.1186/s12974-016-0664-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 239.Gupta S., Utoft R., Hasseldam H., Schmidt-Christensen A., Hannibal T.D., Hansen L., Fransén-Pettersson N., Agarwal-Gupta N., Rozell B., Andersson A., et al. Global and 3D laterial assessment of neuroinflammation in rodent models of Multiple Sclerosis. PLoS ONE. 2013;8:e76330. doi: 10.1371/journal.pone.0076330. [DOI] [PMC free article] [PubMed] [Google Scholar]
• 240.Beumer W., Gibney S.M., Drexhage R.C., Pont-Lezica L., Doorduin J., Klein H.C., Steiner J., Connor T.J., Harkin A., Versnel M.A., et al. The immune theory of psychiatric diseases: A key role for activated microglia and circulating monocytes. J. Leukoc. Biol. 2012;92:959–975. doi: 10.1189/jlb.0212100. [DOI] [PubMed] [Google Scholar]
• 241.Bitsch A., Bruhn H., Vougioukas V., Stringaris A., Lassmann H., Frahm J., Brück W. Inflammatory CNS demyelination: Histopathologic correlation with in vivo quantitative proton MR spectroscopy. AJNR Am. J. Neuroradiol. 1999;20:1619–1627. [PMC free article] [PubMed] [Google Scholar]
• 242.Ossenkoppele R., Tolboom N., Foster-Dingley J.C., Adriaanse S.F., Boellaard R., Yaqub M., Windhorst A.D., Barkhof F., Lammertsma A.A., Scheltens P., et al. Longitudinal imaging of Alzheimer pathology using [11C]PIB, [18F]FDDNP and [18F]FDG PET. Eur. J. Nucl. Med. Mol. Imaging. 2012;39:990–1000. doi: 10.1007/s00259-012-2102-3. [DOI] [PubMed] [Google Scholar]
• 243.Grundman M., Pontecorvo M.J., Salloway S.P., Doraiswamy P.M., Fleisher A.S., Sadowsky C.H., Nair A.K., Siderowf A., Lu M., Arora A.K., et al. Potential impact of amyloid imaging on diagnosis and intended management in patients with progressive cognitive decline. Alzheimer Dis. Assoc. Disord. 2013;27:4–15. doi: 10.1097/WAD.0b013e318279d02a. [DOI] [PubMed] [Google Scholar]