Objective-To determine whether microglial activity, measured using translocator-protein positron emission tomographic imaging (PET), is increased in unmedicated subjects presenting with sub-clinical symptoms indicating they are at ultra high risk of psychosis, and to determine if it is elevated in schizophrenia after controlling for a translocator specific genetic polymorphism.Method-Here we use the second generation radioligand [ 11 C]PBR28 and PET to image microglial activity in the brains of subjects at ultra high risk for psychosis. Subjects were recruited from early intervention centres. We also imaged a cohort of patients with schizophrenia and healthy controls for comparison, in total 56 subjects completed the study. At screening, subjects were genotyped to account for the rs6971 polymorphism in the gene encoding the 18Kd Translocator Protein. The main outcome measure was total grey matter [ 11 C]PBR28 binding ratio, representing microglial activity. Conclusion-Microglial activity is elevated in schizophrenia and in subjects with sub-clinical symptoms who are at ultra high risk of psychosis, and is related to at risk symptom severity. This indicates that neuroinflammation is linked to the risk of psychosis and related disorders, and the expression of sub-clinical symptoms. Follow up of ultra high risk subjects will determine whether this is specific to the later development of schizophrenia or risk factors in general. Results-[

A common pattern of intrathecal (meninges and CSF) inflammatory profile strongly correlates with increased cortical pathology, both at the time of diagnosis and at death. These results suggest a role for detailed CSF analysis combined with MRI as a prognostic marker for more aggressive MS. Ann Neurol 2018 Ann Neurol 2018;83:739-755.

The 18-kDA translocator protein (TSPO) is consistently elevated in activated microglia of the central nervous system (CNS) in response to a variety of insults as well as neurodegenerative and psychiatric conditions. It is therefore a target of interest for molecular strategies aimed at imaging neuroinflammation in vivo. For more than 20 years, positron emission tomography (PET) has allowed the imaging of TSPO density in brain using [11C]-(R)-PK11195, a radiolabelled-specific antagonist of the TSPO that has demonstrated microglial activation in a large number pathological cohorts. The significant clinical interest in brain immunity as a primary or comorbid factor in illness has sparked great interest in the TSPO as a biomarker and a surprising number of second generation TSPO radiotracers have been developed aimed at improving the quality of TSPO imaging through novel radioligands with higher affinity. However, such major investment has not yet resulted in the expected improvement in image quality. We here review the main methodological aspects of TSPO PET imaging with particular attention to TSPO genetics, cellular heterogeneity of TSPO in brain tissue and TSPO distribution in blood and plasma that need to be considered in the quantification of PET data to avoid spurious results as well as ineffective development and use of these radiotracers.

The positron emission tomography radioligand [ 11 C]PBR28 targets translocator protein (18 kDa) (TSPO) and is a potential marker of neuroinflammation. [ 11 C]PBR28 binding is commonly quantified using a two-tissue compartment model and an arterial input function. Previous studies with [ 11 C]-(R)-PK11195 demonstrated a slow irreversible binding component to the TSPO proteins localized in the endothelium of brain vessels, such as venous sinuses and arteries. However, the impact of this component on the quantification of [ 11 C]PBR28 data has never been investigated. In this work we propose a novel kinetic model for [ 11 C]PBR28. This model hypothesizes the existence of an additional irreversible component from the blood to the endothelium. The model was tested on a data set of 19 healthy subjects. A simulation was also performed to quantify the error generated by the standard twotissue compartmental model when the presence of the irreversible component is not taken into account. Our results show that when the vascular component is included in the model the estimates that include the vascular component (2TCM-1K) are more than three-fold smaller, have a higher time stability and are better correlated to brain mRNA TSPO expression than those that do not include the model (2TCM).