To date, available treatment strategies for multiple sclerosis (MS) are ineffective in preventing or reversing progressive neurologic deterioration, creating a high, and unmet medical need. One potential way to fight MS may be by limiting the detrimental effects of reactive astrocytes, a key pathological hallmark for disease progression. One class of compounds that may exert beneficial effects via astrocytes are melanocortin receptor (MCR) agonists. Among the MCR, MC4R is most abundantly expressed in the CNS and several rodent studies have described that MC4R is—besides neurons—expressed by astrocytes. Activation of MC4R in astrocytes has shown to have potent anti-inflammatory as well as neuroprotective effects in vitro, suggesting that this could be a potential target to ameliorate ongoing inflammation, and neurodegeneration in MS. In this study, we set out to investigate human MC4R expression and analyze its downstream effects. We identified MC4R mRNA and protein to be expressed on astrocytes and observed increased astrocytic MC4R expression in active MS lesions. Furthermore, we show that the novel, highly selective MC4R agonist setmelanotide ameliorates the reactive phenotype in astrocytes in vitro and markedly induced interleukin−6 and −11 production, possibly through enhanced cAMP response element-binding protein (CREB) phosphorylation. Notably, stimulation of human macrophages with medium from astrocytes that were exposed to setmelanotide, skewed macrophages toward an anti-inflammatory phenotype. Taken together, these findings suggest that targeting MC4R on astrocytes might be a novel therapeutic strategy to halt inflammation-associated neurodegeneration in MS.
Background Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance.
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