A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging.

Introduction: Recent evidence suggests the blood-to-brain influx rate (K1 ) in TSPO PET imaging as a promising biomarker of blood-brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test-retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03-0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers' unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal.

Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging.

INTRODUCTION: We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation. METHODS: Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF's functional form and shape, enabling precise predictions of the concentrations of [11C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma. RESULTS: We found a robust linear correlation between our model's predicted AIF curves and those obtained through traditional, invasive measurements. We achieved an average cross-validated Pearson correlation of 0.86 for whole blood and 0.89 for parent plasma curves. Moreover, our method's ability to estimate the volumes of distribution across several key brain regions - without significant differences between the use of predicted versus actual AIFs in a two-tissue compartmental model - successfully captures the intrinsic variability related to sex, the binding affinity of the translocator protein (18 kDa), and age. CONCLUSIONS: These results not only validate our method's accuracy and reliability but also establish a foundation for a streamlined, non-invasive approach to dynamic PET data quantification. By offering a precise and less invasive alternative to traditional quantification methods, our technique holds significant promise for expanding the applicability of PET imaging across a wider range of tracers, thereby enhancing its utility in both clinical research and diagnostic settings.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients.

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

Mesostriatal Dopaminergic Circuit Dysfunction in Schizophrenia: A Multimodal Neuromelanin-Sensitive Magnetic Resonance Imaging and [18F]-DOPA Positron Emission Tomography Study.

BACKGROUND: Striatal hyperdopaminergia is implicated in the pathoetiology of schizophrenia, but how this relates to dopaminergic midbrain activity is unclear. Neuromelanin (NM)-sensitive magnetic resonance imaging provides a marker of long-term dopamine function. We examined whether midbrain NM-sensitive magnetic resonance imaging contrast-to-noise ratio (NM-CNR) was higher in people with schizophrenia than in healthy control (HC) participants and whether this correlated with dopamine synthesis capacity. METHODS: One hundred fifty-four participants (schizophrenia group: n = 74, HC group: n = 80) underwent NM-sensitive magnetic resonance imaging of the substantia nigra and ventral tegmental area (SN-VTA). A subset of the schizophrenia group (n = 38) also received [18F]-DOPA positron emission tomography to measure dopamine synthesis capacity (Kicer) in the SN-VTA and striatum. RESULTS: SN-VTA NM-CNR was significantly higher in patients with schizophrenia than in HC participants (effect size = 0.38, p = .019). This effect was greatest for voxels in the medial and ventral SN-VTA. In patients, SN-VTA Kicer positively correlated with SN-VTA NM-CNR (r = 0.44, p = .005) and striatal Kicer (r = 0.71, p < .001). Voxelwise analysis demonstrated that SN-VTA NM-CNR was positively associated with striatal Kicer (r = 0.53, p = .005) and that this relationship seemed strongest between the ventral SN-VTA and associative striatum in schizophrenia. CONCLUSIONS: Our results suggest that NM levels are higher in patients with schizophrenia than in HC individuals, particularly in midbrain regions that project to parts of the striatum that receive innervation from the limbic and association cortices. The direct relationship between measures of NM and dopamine synthesis suggests that these aspects of schizophrenia pathophysiology are linked. Our findings highlight specific mesostriatal circuits as the loci of dopamine dysfunction in schizophrenia and thus as potential therapeutic targets.

Simultaneous assessment of blood flow and myelin content in the brain white matter with dynamic [11 C]PiB PET: a test-retest study in healthy controls.

BACKGROUND: Exploring the relationship between oxygen supply and myelin damage would benefit from a simultaneous quantification of myelin and cerebral blood flow (CBF) in the brain's white matter (WM). To validate an analytical method for quantifying both CBF and myelin content in the WM using dynamic [11C]PiB positron emission tomography (PET). METHODS: A test-retest study was performed on eight healthy subjects who underwent two consecutive dynamic [11 C]PiB-PET scans. Three quantitative approaches were compared: simplified reference tissue model 2 (SRTM2), LOGAN graphical model, and standardized uptake value ratio (SUVR). The sensitivity of methods to the size of the region of interest was explored by simulating lesion masks obtained from 36 subjects with multiple sclerosis. Reproducibility was assessed using the relative difference and interclass correlation coefficient. Repeated measures correlations were used to test for cross-correlations between metrics. RESULTS: Among the CBF measures, the relative delivery (R1) of the simplified reference tissue model 2 (SRTM2) displayed the best reproducibility in the white matter, with a strong influence of the size of regions analyzed, the test-retest variability being below 10% for regions above 68 mm3 in the supratentorial white matter. [11C]PiB PET-derived proxies of CBF demonstrated lower perfusion of white matter compared to grey matter with an overall ratio equal to 1.71 ± 0.09 when the SRTM2-R1 was employed. Tissue binding in the white matter was well estimated by the Logan graphical model through estimation of the distribution volume ratio (LOGAN-DVR) and SRTM2 distribution volume ratio (SRTM2-DVR), with test-retest variability being below 10% for regions exceeding 106 mm3 for LOGAN-DVR and 300 mm3 for SRTM2-DVR. SRTM2-DVR provided a better contrast between white matter and grey matter. The interhemispheric variability was also dependent on the size of the region analyzed, being below 10% for regions above 103 mm3 for SRTM2-R1 and above 110 mm3 for LOGAN-DVR. Whereas the 1 to 8-minute standardized uptake value ratio (SUVR1-8) showed an intermediary reproducibility for CBF assessment, SUVR0-2 for perfusion or SUVR50-70 for tissue binding showed poor reproducibility and correlated only mildly with SRTM2-R1 and LOGAN-DVR estimations respectively. CONCLUSIONS: [11C]PiB PET imaging can simultaneously quantify perfusion and myelin content in WM diseases associated with focal lesions. For longitudinal studies, SRTM2-R1 and DVR should be preferred over SUVR for the assessment of regional CBF and myelin content, respectively. TRIAL REGISTRATION: European Union Clinical Trials Register EUDRACT; EudraCT Number: 2008-004174-40; Date: 2009-03-06; https//www.clinicaltrialsregister.eu ; number 2008-004174-40.

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Histamine-3 Receptor Availability and Glutamate Levels in the Brain: A PET-1H-MRS Study of Patients With Schizophrenia and Healthy Controls.

BACKGROUND: The histamine-3 receptor (H3R) may have a role in cognitive processes through its action as a presynaptic heteroreceptor inhibiting the release of glutamate in the brain. To explore this, we examined anterior cingulate cortex (ACC) and striatum H3R availability in patients with schizophrenia and characterized their relationships with glutamate levels in corresponding brain regions. METHODS: We employed a cross-sectional study, recruiting 12 patients with schizophrenia and 12 healthy volunteers. Participants underwent positron emission tomography using the H3R-specific radio ligand [11C]MK-8278, followed by proton magnetic resonance spectroscopy to measure glutamate levels, recorded as Glu and Glx. Based on existing literature, the ACC and striatum were selected as regions of interest. RESULTS: We found significant inverse relationships between tracer uptake and Glu (r = -0.66, P = .02) and Glx (r = -0.62, P = .04) levels in the ACC of patients, which were absent in healthy volunteers (Glu: r = -0.19, P = .56, Glx: r = 0.10, P = .75). We also found a significant difference in striatal (F1,20 = 6.00, P = .02) and ACC (F1,19 = 4.75, P = .04) Glx levels between groups. CONCLUSIONS: These results provide evidence of a regionally specific relationship between H3Rs and glutamate levels, which builds on existing preclinical literature. Our findings add to a growing literature indicating H3Rs may be a promising treatment target in schizophrenia, particularly for cognitive impairment, which has been associated with altered glutamate signaling.

Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. METHODS: We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis. RESULTS: The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. DISCUSSION: The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.

Microglial activation, tau and amyloid deposition in TREM2 p.R47H carriers and mild cognitive impairment patients: a multi-modal/multi-tracer PET/MRI imaging study with influenza vaccine immune challenge.

BACKGROUND: Microglia are increasingly understood to play an important role in the pathogenesis of Alzheimer's disease. The rs75932628 (p.R47H) TREM2 variant is a well-established risk factor for Alzheimer's disease. TREM2 is a microglial cell surface receptor. In this multi-modal/multi-tracer PET/MRI study we investigated the effect of TREM2 p.R47H carrier status on microglial activation, tau and amyloid deposition, brain structure and cognitive profile. METHODS: We compared TREM2 p.R47H carriers (n = 8; median age = 62.3) and participants with mild cognitive impairment (n = 8; median age = 70.7). Participants underwent two [18F]DPA-714 PET/MRI scans to assess TSPO signal, indicative of microglial activation, before and after receiving the seasonal influenza vaccination, which was used as an immune stimulant. Participants also underwent [18F]florbetapir and [18F]AV1451 PET scans to assess amyloid and tau burden, respectively. Regional tau and TSPO signal were calculated for regions of interest linked to Braak stage. An additional comparison imaging healthy control group (n = 8; median age = 45.5) had a single [18F]DPA-714 PET/MRI. An expanded group of participants underwent neuropsychological testing, to determine if TREM2 status influenced clinical phenotype. RESULTS: Compared to participants with mild cognitive impairment, TREM2 carriers had lower TSPO signal in Braak II (P = 0.04) and Braak III (P = 0.046) regions, despite having a similar burden of tau and amyloid. There were trends to suggest reduced microglial activation following influenza vaccine in TREM2 carriers. Tau deposition in the Braak VI region was higher in TREM2 carriers (P = 0.04). Furthermore, compared to healthy controls TREM2 carriers had smaller caudate (P = 0.02), total brain (P = 0.049) and white matter volumes (P = 0.02); and neuropsychological assessment revealed worse ADAS-Cog13 (P = 0.03) and Delayed Matching to Sample (P = 0.007) scores. CONCLUSIONS: TREM2 p.R47H carriers had reduced levels of microglial activation in brain regions affected early in the Alzheimer's disease course and differences in brain structure and cognition. Changes in microglial response may underlie the increased Alzheimer's disease risk in TREM2 p.R47H carriers. Future therapeutic agents in Alzheimer's disease should aim to enhance protective microglial actions.

An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?

BACKGROUND: The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. MAIN BODY: This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF. CONCLUSION: Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

Sub-Chronic Ketamine Administration Increases Dopamine Synthesis Capacity in the Mouse Midbrain: a Preclinical In Vivo PET Study.

PURPOSE: There is robust evidence that people with schizophrenia show elevated dopamine (DA) synthesis capacity in the striatum. This finding comes from positron emission tomography (PET) studies using radiolabelled l-3,4-dihydroxyphenylalanine (18F-DOPA). DA synthesis capacity also appears to be elevated in the midbrain of people with schizophrenia compared to healthy controls. We therefore aimed to optimise a method to quantify 18F-DOPA uptake in the midbrain of mice, and to utilise this method to quantify DA synthesis capacity in the midbrain of the sub-chronic ketamine model of schizophrenia-relevant hyperdopaminergia. PROCEDURES: Adult male C57Bl6 mice were treated daily with either ketamine (30 mg/kg, i.p.) or vehicle (saline) for 5 days. On day 7, animals were administered 18F-DOPA (i.p.) and scanned in an Inveon PET/CT scanner. Data from the saline-treated group were used to optimise an atlas-based template to position the midbrain region of interest and to determine the analysis parameters which resulted in the greatest intra-group consistency. These parameters were then used to compare midbrain DA synthesis capacity (KiMod) between ketamine- and saline-treated animals. RESULTS: Using an atlas-based template to position the 3.7 mm3 midbrain ROI with a T*-Tend window of 15-140 min to estimate KiMod resulted in the lowest intra-group variability and moderate test-retest agreement. Using these parameters, we found that KiMod was elevated in the midbrain of ketamine-treated animals in comparison to saline-treated animals (t(22) = 2.19, p = 0.048). A positive correlation between DA synthesis capacity in the striatum and the midbrain was also evident in the saline-treated animals (r2 = 0.59, p = 0.005) but was absent in ketamine-treated animals (r2 = 0.004, p = 0.83). CONCLUSIONS: Using this optimised method for quantifying 18F-DOPA uptake in the midbrain, we found that elevated striatal DA synthesis capacity in the sub-chronic ketamine model extends to the midbrain. Interestingly, the dysconnectivity between the midbrain and striatum seen in this model is also evident in the clinical population. This model may therefore be ideal for assessing novel compounds which are designed to modulate pre-synaptic DA synthesis capacity.

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI.

Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test-retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL 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.

The histamine system and cognitive function: An in vivo H3 receptor PET imaging study in healthy volunteers and patients with schizophrenia.

BACKGROUND: The histamine-3 receptor (H3R) is an auto- and heteroreceptor that inhibits the release of histamine and other neurotransmitters. Post-mortem evidence has found altered H3R expression in patients with psychotic disorders, which may underlie cognitive impairment associated with schizophrenia (CIAS). AIMS: We used positron emission tomography (PET) imaging to compare brain uptake of an H3R selective tracer between patients with schizophrenia and matched controls (healthy individuals). Regions of interest included the dorsolateral prefrontal cortex (DLPFC) and striatum. We explored correlations between tracer uptake and symptoms, including cognitive domains. METHODS: A total of 12 patients and 12 matched controls were recruited to the study and were assessed with psychiatric and cognitive rating scales. They received a PET scan using the H3R-specific radioligand [11C]MK-8278 to determine H3R availability. RESULTS: There was no statistically significant difference in tracer uptake between patients and controls in the DLPFC (t19 = 0.79, p = 0.44) or striatum (t21 = 1.18, p = 0.25). An exploratory analysis found evidence for lower volume of distribution in the left cuneus (pFWE-corrected = 0.01). DLPFC tracer uptake was strongly correlated with cognition in controls (trail making test (TMT) A: r = 0.77, p = 0.006; TMT B: rho = 0.74, p = 0.01), but not in patients (TMT A: r = -0.18, p = 0.62; TMT B: rho = -0.06, p = 0.81). CONCLUSIONS: These findings indicate H3R in the DLPFC might play a role in executive function and this is disrupted in schizophrenia in the absence of major alterations in H3R availability as assessed using a selective radiotracer for H3R. This provides further evidence for the role of H3R in CIAS.

The relationship between striatal dopamine and anterior cingulate glutamate in first episode psychosis changes with antipsychotic treatment.

The neuromodulator dopamine and excitatory neurotransmitter glutamate have both been implicated in the pathogenesis of psychosis, and dopamine antagonists remain the predominant treatment for psychotic disorders. To date no study has measured the effect of antipsychotics on both of these indices together, in the same population of people with psychosis. Striatal dopamine synthesis capacity (Kicer) and anterior cingulate glutamate were measured using 18F-DOPA positron emission tomography and proton magnetic resonance spectroscopy respectively, before and after at least 5 weeks' naturalistic antipsychotic treatment in people with first episode psychosis (n = 18) and matched healthy controls (n = 20). The relationship between both measures at baseline and follow-up, and the change in this relationship was analyzed using a mixed linear model. Neither anterior cingulate glutamate concentrations (p = 0.75) nor striatal Kicer (p = 0.79) showed significant change following antipsychotic treatment. The change in relationship between whole striatal Kicer and anterior cingulate glutamate, however, was statistically significant (p = 0.017). This was reflected in a significant difference in relationship between both measures for patients and controls at baseline (t = 2.1, p = 0.04), that was not present at follow-up (t = 0.06, p = 0.96). Although we did not find any effect of antipsychotic treatment on absolute measures of dopamine synthesis capacity and anterior cingulate glutamate, the relationship between anterior cingluate glutamate and striatal dopamine synthesis capacity did change, suggesting that antipsychotic treatment affects the relationship between glutamate and dopamine.

Sickness behaviour and depression: An updated model of peripheral-central immunity interactions.

Current research into mood disorders indicates that circulating immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain function. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy to improve treatment efficacy, particularly in subjects that do not respond to standard medication. Such new practice requires biomarkers to tailor these new therapies to those most likely to benefit but also validated mechanisms of action describing the interaction between peripheral immunity and brain function to optimize target intervention. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease, MDD, through peripherally induced sickness behaviour. In this proposal paper, after an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we put forward a modified model of periphery-brain interactions that goes beyond the currently established view of microglia cells as the drivers of depression. Instead, we suggest that, for most patients with mild levels of peripheral inflammation, brain barriers are the primary actors in the pathophysiology of the disease and in treatment resistance. We then highlight data gaps in this proposal and suggest novel lines of research.

An automatic analysis framework for FDOPA PET neuroimaging.

In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Kicer: for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.