Search

Current lines of research into mood disorders indicate that immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain functions, even when these mediators are produced in peripheral tissues. Elevated levels of circulating immune molecules have been consistently associated with depressive symptoms in a number of clinical populations and experimental models, to the extent that major depressive disorder (MDD) is now seen, at least in part, as a disorder of immunity. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy with the hope to improve treatment efficacy, particularly in those cohorts that do not respond well to standard medication. Such new practice requires the availability of biomarkers to tailor these new therapies to those most likely to benefit but also clear mechanisms of action describing the interaction between peripheral immunity and brain function. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease through peripherally induced sickness behaviour as the model for immune-induced MDD. After an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we propose a modified model of periphery-brain interaction that goes beyond the currently established view of interaction between peripheral cytokines and microglia cells as the driver of depression. Instead, we suggest that brain barriers are primary actors in the communication between body and brain and, as a consequence, in the pathophysiology of the disease. This model suggests novel biomarkers, novel targets for therapies as well as a novel mechanism for resistance to standard treatments.

The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain’s function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research – spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses – to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.

Background Impaired brain metabolism may be central to schizophrenia pathophysiology, but the magnitude and consistency of metabolic dysfunction is unknown. Methods We searched MEDLINE, PsychINFO and EMBASE between 01/01/1980 and 13/05/2021 for studies comparing regional brain glucose metabolism using 18FDG-PET, in schizophrenia/first-episode psychosis v. controls. Effect sizes (Hedges g) were pooled using a random-effects model. Primary measures were regional absolute and relative CMRGlu in frontal, temporal, parietal and occipital lobes, basal ganglia and thalamus. Results Thirty-six studies (1335 subjects) were included. Frontal absolute glucose metabolism (Hedge's g = −0.74 ± 0.54, p = 0.01; I2 = 67%) and metabolism relative to whole brain (g = −0.44 ± 0.34, p = 0.01; I2 = 55%) were lower in schizophrenia v. controls with moderate heterogeneity. Absolute frontal metabolism was lower in chronic (g = −1.18 ± 0.73) v. first-episode patients (g = −0.09 ± 0.88) and controls. Medicated patients showed frontal hypometabolism relative to controls (−1.04 ± 0.26) while metabolism in drug-free patients did not differ significantly from controls. There were no differences in parietal, temporal or occipital lobe or thalamic metabolism in schizophrenia v. controls. Excluding outliers, absolute basal ganglia metabolism was lower in schizophrenia v. controls (−0.25 ± 0.24, p = 0.049; I2 = 5%). Studies identified reporting voxel-based morphometry measures of absolute 18FDG uptake (eight studies) were also analysed using signed differential mapping analysis, finding lower 18FDG uptake in the left anterior cingulate gyrus (Z = −4.143; p = 0.007) and the left inferior orbital frontal gyrus (Z = −4.239; p = 0.02) in schizophrenia. Conclusions We report evidence for hypometabolism with large effect sizes in the frontal cortex in schizophrenia without consistent evidence for alterations in other brain regions. Our findings support the hypothesis of hypofrontality in schizophrenia.

While COVID-19 research has seen an explosion in the literature, the impact of pandemic-related societal and lifestyle disruptions on brain health among the uninfected remains underexplored. However, a global increase in the prevalence of fatigue, brain fog, depression and other "sickness behavior"-like symptoms implicates a possible dysregulation in neuroimmune mechanisms even among those never infected by the virus. We compared fifty-seven 'Pre-Pandemic' and fifteen 'Pandemic' datasets from individuals originally enrolled as control subjects for various completed, or ongoing, research studies available in our records, with a confirmed negative test for SARS-CoV-2 antibodies. We used a combination of multimodal molecular brain imaging (simultaneous positron emission tomography / magnetic resonance spectroscopy), behavioral measurements, imaging transcriptomics and serum testing to uncover links between pandemic-related stressors and neuroinflammation. Healthy individuals examined after the enforcement of 2020 lockdown/stay-at-home measures demonstrated elevated brain levels of two independent neuroinflammatory markers (the 18 kDa translocator protein, TSPO, and myoinositol) compared to pre-lockdown subjects. The serum levels of two inflammatory markers (interleukin-16 and monocyte chemoattractant protein-1) were also elevated, although these effects did not reach statistical significance after correcting for multiple comparisons. Subjects endorsing higher symptom burden showed higher TSPO signal in the hippocampus (mood alteration, mental fatigue), intraparietal sulcus and precuneus (physical fatigue), compared to those reporting little/no symptoms. Post-lockdown TSPO signal changes were spatially aligned with the constitutive expression of several genes involved in immune/neuroimmune functions. This work implicates neuroimmune activation as a possible mechanism underlying the non-virally-mediated symptoms experienced by many during the COVID-19 pandemic. Future studies will be needed to corroborate and further interpret these preliminary findings.

Background: Alterations in the serotonergic control of brain pathways responsible for facial emotion processing in people with autism spectrum disorder (ASD) may be a target for intervention. However, the molecular underpinnings of autistic-neurotypical serotonergic differences are challenging to access in vivo. Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) has helped define molecular-enriched functional magnetic resonance imaging (fMRI) brain networks based on a priori information about the spatial distribution of neurochemical systems from available PET templates. Methods: We used REACT to estimate the dominant fMRI signal related to the serotonin (5-HT) transporter (SERT) distribution during processing of aversive facial emotion in adults with and without ASD. We first predicted a group difference in baseline (placebo) functioning of this system. We next used a single 20 mg oral dose of citalopram, a serotonin reuptake inhibitor, to test the hypothesis that network activity in people with and without ASD would respond differently to inhibition of SERT. To confirm the specificity of our findings, we also repeated the analysis with 5-HT1A, 5-HT1B, 5-HT2A and 5-HT4 receptor maps. Results: Using REACT with the SERT map, we found a baseline group difference in the SERT-enriched response to faces in the ventromedial prefrontal cortex. A single oral dose of citalopram ‘shifted’ the response in the ASD group towards the neurotypical baseline but did not alter response in the control group. Similar differences in SERT-enriched response were observed after controlling for other 5-HT maps. Conclusions: Our findings suggest that the SERT-enriched functional network is dynamically different in ASD during processing of socially relevant stimuli. Whether this acute neurobiological response to citalopram in ASD translates to a clinical target will be an important next step.

Recent advances in high-throughput technologies enable a more comprehensive interpretation of the tumour evolution through the study of the intra-tumour heterogeneity. Several algorithms, however, often relies on the use of models that described the top of the iceberg regarding the stromal contamination of the samples, making diagnosis difficult to assess. Indeed, such as radio wave receivers, tools to analyse high-throughput technologies data, are used to enable the discrimination between multiple signals differing in frequencies. However, such tools often look at the average frequency more than distinct signals, leading to analyse a confused signal. This confusion could dramatically lead to a mis–interpretation of the real data, especially during the diagnosis as it relies on the choice of a unique scenario among many others. Here, we describe how this signal confusion occurs in the most classical DNA microarray analysis of tumours and we provide statistics to determine how many other possible scenario can lead the same signals, in order to improve the robustness of pigeon hole logic based analysis. Based on simulations, where a unique tumour population was diluted by an increasing gradient of normal cells, we underline the causes and consequences of such signal confusion for up to five allelic copies. Despite the removal of all technical biaises and background noise, we show how the signal confusion remains systematically present in the commonly used DNA microarray analysis, especially for the genotypes AAAAB, AAAB and AAB for copy numbers 5, 4 and 3 respectively, as well as their symmetric combinations for the B allele.

PDF file - 45K, SUV in tumors normalized to body weight.

PDF file - 61K, SUV in tumors, average and maximum.

Purpose: To establish biomarkers indicating clinical response to taxanes, we determined whether early changes in [18F]-3′deoxy-3′-fluorothymidine positron emission tomography (FLT-PET) can predict benefit from docetaxel therapy in breast cancer.Experimental Design: This was a prospective unblinded study in 20 patients with American Joint Committee on Cancer (AJCC) stage II–IV breast cancer unresponsive to first-line chemotherapy or progressing on previous therapy. Individuals underwent a baseline dynamic FLT-PET scan followed by a scan 2 weeks after initiating the first or second cycle of docetaxel. PET variables were compared with anatomic response midtherapy (after 3 cycles).Results: Average and maximum tumor standardized uptake values at 60 minutes (SUV60,av and SUV60,max) normalized to body surface area ranged between 1.7 and 17.0 and 5.6 and 26.9 × 10−5 m2/mL, respectively. Docetaxel treatment resulted in a significant decrease in FLT uptake (P = 0.0003 for SUV60,av and P = 0.0002 for SUV60,max). Reduction in tumor SUV60,av was associated with target lesion size changes midtherapy (Pearson R for SUV60,av = 0.64; P = 0.004) and predicted midtherapy target lesion response (0.85 sensitivity and 0.80 specificity). Decreases in SUV60,av in responders were due, at least in part, to reduced net intracellular trapping of FLT (rate constant, Ki). Docetaxel significantly reduced Ki by 51.1% (±28.4%, P = 0.0009).Conclusion: Changes in tumor proliferation assessed by FLT-PET early after initiating docetaxel chemotherapy can predict lesion response midtherapy with good sensitivity warranting prospective trials to assess the ability to stop therapy in the event of non–FLT-PET response. Clin Cancer Res; 17(24); 7664–72. ©2011 AACR.

PDF file - 46K, Changes in FLT SUV after 1 and 2 cycles of docetaxel.

The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience, ranging from the level of wakefulness in anaesthesia, to the activity of individual neurons, to voltage in EEG, and to blood flow in fMRI. This lack of consensus presents a significant challenge to developing accurate models of neural dynamics and places neuroscience at odd with the physical sciences, in which a single definition of a system's state unites all of its subdisciplines — from classical physics, to general relativity, and quantum mechanics. This definition is that the state of a dynamical system is sufficiently well specified when it can determine what the system does next. By collecting every possible state, we can then construct a phase space representation. However, unlike systems modelled in physics, the rules governing brain dynamics are not (usually) described by known mathematical laws, and therefore precise features that constitute a brain state must be determined through empirical methods. We demonstrate that Dynamic Causal Modelling (DCM) can be used to identify these relevant features in low-dimensional embedding of resting fMRI data, allowing us to construct a tailored phase space in which all possible brain states are represented. We find that these data are well described by first-order differential equations, with sparse coupling between brain gradients. We show that our approach provides a new perspective on brain states that will aid in the development of accurate models of neural dynamics and can be adapted to different data modalities and neuroimaging scenarios.

The difference between brain age predicted from MRI and chronological age (the so-called BrainAGE) has been proposed as an ageing biomarker. We analyse its cross-species potential by testing it on rats undergoing an ageing modulation intervention. Our rat brain age prediction model combined Gaussian process regression with a classifier and achieved a mean absolute error (MAE) of 4.87 weeks using cross-validation on a longitudinal dataset of 31 normal ageing rats. It was then tested on two groups of 24 rats (MAE = 9.89 weeks, correlation coefficient = 0.86): controls vs. a group under long-term environmental enrichment and dietary restriction (EEDR). Using a linear mixed-effects model, BrainAGE was found to increase more slowly with chronological age in EEDR rats ( p = 0.015 for the interaction term). Cox regression showed that older BrainAGE at 5 months was associated with higher mortality risk ( p = 0.03 ). Our findings suggest that lifestyle-related prevention approaches may help to slow down brain ageing in rodents and the potential of BrainAGE as a predictor of age-related health outcomes.

Hippocampal hyperactivity driven by GABAergic interneuron deficits and NMDA receptor hypofunction is associated with the hyperdopaminergic state often observed in schizophrenia. Furthermore, previous research in the methylazoxymethanol acetate (MAM) rat model has demonstrated that repeated peripubertal diazepam administration can prevent the emergence of adult hippocampal hyperactivity, dopamine system hyperactivity, and associated psychosis-relevant behaviors. Here, we sought to characterize hippocampal GABAA and NMDA receptors in MAM-treated rats and to elucidate the receptor mechanisms underlying the promising effects of peripubertal diazepam exposure. Quantitative receptor autoradiography was used to measure receptor density in dorsal hippocampus CA1, ventral hippocampus CA1, and in ventral subiculum. Specifically, [3H]-Ro15-4513 was used to quantify the density of α5 GABAA receptors (α5GABAAR), [3H]-flumazenil to quantify α1-3;5GABAAR, and [3H]-MK801 to quantify NMDA receptors. MAM rats exhibited anxiety and schizophrenia-relevant behaviors as measured by elevated plus maze and amphetamine-induced hyperlocomotion (AIH), although diazepam only partially rescued these behaviors. α5GABAAR density was reduced in MAM-treated rats in all hippocampal sub-regions, and negatively correlated with AIH. Ventral hippocampus CA1 α5GABAAR density was positively correlated with anxiety-like behavior. Dorsal hippocampus CA1 NMDA receptor density was increased in MAM-treated rats, and positively correlated with AIH. [3H]-Flumazenil revealed no significant effects. Finally, we found no significant effect of diazepam treatment on receptor densities, potentially related to the only partial rescue of schizophrenia-relevant phenotypes. Overall, our findings provide first evidence of α5GABAAR and NMDA receptor abnormalities in the MAM model, suggesting that more selective pharmacological agents may become a novel therapeutic mechanism in schizophrenia.

The relationship between obesity and brain structure is incompletely understood. Using diffusion-weighted MRI from ∼30,000 UK Biobank participants we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal-temporal-striatal system associated with ISOVF and a medial temporal-occipital-striatal system associated with ICVF. The ISOVF∼WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF∼WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg= 0.026,P= 0.36) and ICVF (rg= 0.112,P <9 × 10−4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (p

Highlights • The neural bases of altered emotion processing in psychosis are still unclear. • Systematic review indicated widespread activation decreases to emotion in first-episode psychosis. • Evidence in people at clinical high-risk for psychosis lacked convergence. • These findings were corroborated by image-based meta-analyses., Aberrant emotion processing is a well-established component of psychotic disorders and is already present at the first episode of psychosis (FEP). However, the role of emotion processing abnormalities in the emergence of psychosis and the underlying neurobiology remain unclear. Here, we systematically reviewed functional magnetic resonance studies that used emotion processing task paradigms in FEP patients, and in people at clinical high-risk for psychosis (CHRp). Image-based meta-analyses with Seed-based d Mapping on available studies (n = 6) were also performed. Compared to controls, FEP patients showed decreased neural responses to emotion, particularly in the amygdala and anterior cingulate cortex. There were no significant differences between CHRp subjects and controls, but a high degree of heterogeneity was identified across studies. The role of altered emotion processing in the early phase of psychosis may be clarified through more homogenous experimental designs, particularly in the CHRp population.

Boltzmann entropy is a measure of the hidden information contained within a system. In the context of neuroimaging, information can be hidden within the multiple brain states that cannot be distinguished within a single image. Here, we show that information can also be hidden within multiple indistinguishable connections between neuronal regions, as quantified by a metric that we term ‘selection entropy’. We show the ways in which selection entropy behaves in comparison with the Kullback-Leibler (KL) divergence (relative entropy). Firstly, we use synthetic datasets to demonstrate that selection entropy is more sensitive to small changes in probability distributions as compared with the KL divergence. Secondly, we show that selection entropy identifies a principle gradient between sensorimotor and transmodal brain regions more definitively than the KL divergence within resting-state fMRI timeseries. As such, we introduce selection entropy as an additional asset in the analysis of neuronal functional selectivity.

Evidence from post-mortem studies and in vivo imaging studies suggests there may be reducedIn this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = -0.74,This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Background: Evidence from post-mortem studies and in vivo imaging studies suggests there may be reduced N-methyl-d-aspartate receptor (NMDAR) levels in the hippocampus in patients with schizophrenia. Other studies have reported increased glutamate in striatum in schizophrenia patients. It has been hypothesised that NMDAR hypofunction leads to the disinhibition of glutamatergic signalling; however, this has not been tested in vivo. Methods: In this study, we investigated the relationship between hippocampal NMDAR and striatal glutamate using simultaneous positron emission tomography-magnetic resonance (PET-MR) imaging. We recruited 40 volunteers to this cross-sectional study; 21 patients with schizophrenia, all in their first episode of illness, and 19 healthy controls. We measured hippocampal NMDAR availability using the PET ligand [18F]GE179. This was indexed relative to whole brain as the distribution volume ratio (DVR). Striatal glutamatergic indices (glutamate and Glx) were acquired simultaneously, using combined PET-MR proton magnetic resonance spectroscopy (1H-MRS). Results: A total of 33 individuals (15 healthy controls, 18 patients) were included in the analyses (mean (SD) age of controls, 27.31 (4.68) years; mean (SD) age of patients, 24.75 (4.33), 27 male and 6 female). We found an inverse relationship between hippocampal DVR and striatal glutamate levels in people with first-episode psychosis (rho = −0.74, p Conclusion: This study show that lower relative NMDAR availability in the hippocampus may drive increased striatal glutamate levels in patients with schizophrenia. Further work is required to determine whether these findings may yield new targets for drug development in schizophrenia.

Entropy is a term that is frequently used in neuroscience to characterise time series and to make inferences about brain states. The purpose of this primer is to support these characterisations by providing an overview of entropy in the context of neural systems and to address some common misconceptions, the most popular of which is that entropy is equivalent to disorder. It is more accurate to say that entropy quantifies the information that is hidden from an observer — a point that we expand upon using toy models. We discuss the limitations of calculating entropy via neural time series and also suggest ways in which entropy could be used in future studies to infer the information capacity of neural systems.

Cell nuclear architecture has been explored in cancer and laminopathies but not in neurodegenerative disorders. Huntington’s disease (HD) is a neurodegenerative disorder that leads to neuronal death. Chromosome-wide changes in gene expression have been reported in HD, not only in the brain but also in peripheral blood cells, but whether this translates into nuclear and chromosome architecture alterations has not yet been studied. We investigate nuclear structure and chromosome organization in HD blood cells using fluorescence in situ hybridization in ultrathin cryosections (cryoFISH), coupled with machine learning image analysis to evaluate size, distribution, and morphology of nuclei and chromosomes. Four chromosomes were analyzed based on up- or downregulation of gene expression in HD. We show that blood cells from HD patients display increased nuclear size and filamentary shape, increased size of gene-rich chromosome 19, decreased filamentary shape of gene-rich chromosome 22, and a more radially centralized position for chromosome 19, whereas chromosomes 4 and 5 do not show detectable differences. We identify gross changes in nuclear architecture and chromosome organization associated with HD in blood. This adds a new layer of information onto disrupting mechanisms in HD and increases the potential of using blood to survey HD.

With the modernization and digitisation of the healthcare system, the need for exchanging medical data has become increasingly compelling. Biomedical imaging has been no exception, where the gathering of medical imaging acquisitions from multi-site collaborations have enabled to reach data sizes never imaginable until few years ago. Usually, medical imaging data have very large volume and diverse complexity, requiring bespoken transfer systems that protect personal information as well as data integrity. Despite many digital innovations, there are still technical and regulatory bottlenecks that make biomedical imaging data exchange challenging. Here we present Bitbox, a web-based application which provides a reliable yet straightforward service to securely exchange medical imaging data. With Bitbox, both imaging and non-imaging data of any type can be transferred from any external and independent site into a centralized server. A showcase of the system will be illustrated for the COVID-19 Clinical Neuroscience Study (COVID-CNS) project, a UK-wide experimental medicine study to investigate the neurological and neuropsychiatric effects of COVID-19 infections in hundreds of patients.

Scientific theories on the functioning and dysfunction of the human brain require a good understanding of both its development — before and after birth, and through maturation to adulthood — and its evolution from the ancestral primate brain. Adopting a complex-systems approach, here we propose that the apparent uniqueness of humans’ cognitive capacities might best be understood as emerging from multiple nested “virtuous cycles.” In particular, we propose that the intimate link that exists between oxygen metabolic loops, cortical expansion, and ultimately cognitive and social demands is a key driver of genetic developmental programs for the human brain. Overall, our proposed evolutionary model makes explicit mechanistic links between metabolism, molecular and cellular brain heterogeneity, and behaviour that may in time provide a clearer understanding of brain developmental trajectories and their disorders.

Purpose Translocator protein 18-kDa (TSPO) imaging with positron emission tomography (PET) is widely used in research studies of brain diseases that have a neuro-immune component. Quantification of TSPO PET images, however, is associated with several challenges, such as the lack of a reference region, a genetic polymorphism affecting the affinity of the ligand for TSPO, and a strong TSPO signal in the endothelium of the brain vessels. These challenges have created an ongoing debate in the field about which type of quantification is most useful and whether there is an appropriate simplified model. Methods This review focuses on the quantification of TSPO radioligands in the human brain. The various methods of quantification are summarized, including the gold standard of compartmental modeling with metabolite-corrected input function as well as various alternative models and non-invasive approaches. Their advantages and drawbacks are critically assessed. Results and conclusions Researchers employing quantification methods for TSPO should understand the advantages and limitations associated with each method. Suggestions are given to help researchers choose between these viable alternative methods.

Dysfunctional mitochondria characterise Parkinson’s Disease (PD). Uncovering etiological molecules, which harm the homeostasis of mitochondria in response to pathological cues, is therefore pivotal to inform early diagnosis and therapy in the condition, especially in its idiopathic forms. This study proposes the 18 kDa Translocator Protein (TSPO) to be one of those. Both in vitro and in vivo data show that neurotoxins, which phenotypically mimic PD, increase TSPO to enhance cellular redox-stress, susceptibility to dopamine-induced cell death, and repression of ubiquitin-dependent mitophagy. TSPO amplifies the extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) signalling, forming positive feedback, which represses the transcription factor EB (TFEB) and the controlled production of lysosomes. Finally, genetic variances in the transcriptome confirm that TSPO is required to alter the autophagy–lysosomal pathway during neurotoxicity.

Purpose The aim of this study was to investigate the use of spectral analysis (SA) for voxel-wise analysis of TSPO PET imaging studies. TSPO PET quantification is methodologically complicated by the heterogeneity of TSPO expression and its cell-dependent modulation during neuroinflammatory response. Compartmental models to account for this complexity exist, but they are unreliable at the high noise typical of voxel data. On the contrary, SA is noise-robust for parametric mapping and provides useful information about tracer kinetics with a free compartmental structure. Procedures SA impulse response function (IRF) calculated at 90 min after tracer injection was used as main parameter of interest in 3 independent PET imaging studies to investigate its sensitivity to (1) a TSPO genetic polymorphism (rs6971) known to affect tracer binding in a cross-sectional analysis of healthy controls scanned with [11C]PBR28 PET; (2) TSPO density with [11C]PBR28 in a competitive blocking study with a TSPO blocker, XBD173; and (3) the higher affinity of a second radiotracer for TSPO, by using data from a head-to-head comparison between [11C]PBR28 and [11C]ER176 scans. Results SA-IRF produced parametric maps of visually good quality. These were sensitive to TSPO genotype (mean relative difference between high- and mixed-affinity binders = 25 %) and TSPO availability (mean signal displacement after 90 mg oral administration of XBD173 = 39 %). Regional averages of voxel-wise IRF estimates were strongly associated with regional total distribution volume (VT) estimated with a 2-tissue compartmental model with vascular compartment (Pearson’s r = 0.86 ± 0.11) but less strongly with standard 2TCM-VT (Pearson’s r = 0.76 ± 0.32). Finally, SA-IRF estimates for [11C]ER176 were significantly higher than [11C]PBR28 ones, consistent with the higher amount of specific binding of the former tracer. Conclusions SA-IRF can be used for voxel-wise quantification of TSPO PET data because it generates high-quality parametric maps, it is sensitive to TSPO availability and genotype, and it accounts for the complexity of TSPO tracer kinetics with no additional assumptions.

The relationship between peripheral and central immunity and how these ultimately may cause depressed behaviour has been the focus of a number of imaging studies conducted with Positron Emission Tomography (PET). These studies aimed at testing the immune-mediated model of depression that proposes a direct effect of peripheral cytokines and immune cells on the brain to elicit a neuroinflammatory response via a leaky blood–brain barrier and ultimately depressive behaviour. However, studies conducted so far using PET radioligands targeting the neuroinflammatory marker 18 kDa translocator protein (TSPO) in patient cohorts with depression have demonstrated mild inflammatory brain status but no correlation between central and peripheral immunity. To gain a better insight into the relationship between heightened peripheral immunity and neuroinflammation, we estimated blood-to-brain and blood-to-CSF perfusion rates for two TSPO radiotracers collected in two separate studies, one large cross-sectional study of neuroinflammation in normal and depressed cohorts (N = 51 patients and N = 25 controls) and a second study where peripheral inflammation in N = 7 healthy controls was induced via subcutaneous injection of interferon (IFN)-α. In both studies we observed a consistent negative association between peripheral inflammation, measured with c-reactive protein P (CRP), and radiotracer perfusion into and from the brain parenchyma and CSF. Importantly, there was no association of this effect with the marker of BBB leakage S100β, that was unchanged. These results suggest a different model of peripheral-to-central immunity interaction whereas peripheral inflammation may cause a reduction in BBB permeability. This effect, on the long term, is likely to disrupt brain homeostasis and induce depressive behavioural symptoms.

PurposeThe conversion of synaptic glutamate to glutamine in astrocytes by glutamine synthetase (GS) is critical to maintaining healthy brain activity and may be disrupted in several brain disorders. As the GS catalysed conversion of glutamate to glutamine requires ammonia, we evaluated whether [13N]ammonia positron emission tomography (PET) could reliability quantify GS activity in humans.MethodsIn this test–retest study, eight healthy volunteers each received two dynamic [13N]ammonia PET scans on the morning and afternoon of the same day. Each [13N]ammonia scan was preceded by a [15O]water PET scan to account for effects of cerebral blood flow (CBF).ResultsConcentrations of radioactive metabolites in arterial blood were available for both sessions in five of the eight subjects. Our results demonstrated that kinetic modelling was unable to reliably distinguish estimates of the kinetic rate constantk3(related to GS activity) fromK1(related to [13N]ammonia brain uptake), and indicated a non-negligible back-flux of [13N] to blood (k2). Model selection favoured a reversible one-tissue compartmental model, and [13N]ammoniaK1correlated reliably (r2 = 0.72–0.92) with [15O]water CBF.ConclusionThe [13N]ammonia PET method was unable to reliably estimate GS activity in the human brain but may provide an alternative index of CBF.

Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) is a novel analytical strategy that enriches functional connectivity (FC) information from functional MRI (fMRI) with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the FC analysis. So far, this integrative approach has been used in blood oxygen level-dependent (BOLD) fMRI studies only, providing new insights into the brain mechanisms underlying specific disorders and its response to pharmacological challenges. In this study, we demonstrate that the application of REACT can be further extended to arterial spin labelling (ASL) fMRI. Some of the advantages of this extension include the combination of neurotransmitter specific information provided by molecular imaging with a quantitative marker of neuronal activity, the suitability of ASL for pharmacological MRI (phMRI) studies assessing drug effects on baseline brain function, and the possibility to acquire images that are not affected by susceptibility artifacts in the regions linked to major neurotransmitter systems.In this work, we tested the feasibility of applying REACT to resting state ASL fMRI and compared the molecular-enriched FC maps derived from ASL data with those derived from BOLD data. We applied REACT to high-resolution, whole-brain simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL- and BOLD-based FC maps related to six molecular systems, including the transporters of dopamine, noradrenaline, serotonin and vesicular acetylcholine, and the GABA-A and mGlu5 receptors. We then compared the ASL and BOLD FC maps in terms of spatial similarity, using the Dice Similarity Index and the voxel-wise spatial correlation. On a data subsample (N=19) we also evaluated the test-retest reproducibility of each modality using the regional intraclass correlation coefficient, and compared the two modalities.Our results showed robust spatial patterns of molecular-enriched functional connectivity for both modalities, moderate to high similarity between BOLD- and ASL-derived FC maps and mixed results in terms of reproducibility (i.e., none of the modalities outperformed the other). Overall, our findings show that the ASL signal is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits.Considering the more direct link of ASL imaging with neuronal acrivity compared to BOLD and its suitability for phMRI studies, this new integrative approach could become a valuable asset in clinical studies investigating functional alterations in patients with brain disorders, or in pharmacological studies investigating the effects of new or existing compounds on the brain.