Search

Transcriptomic, proteomic and immune repertoire profiling reveals distinct peripheral features of MIS-C and pediatric COVID-19, including elevated soluble spike protein levels, more pronounced type II IFN-dependent gene expression and a higher B cell mutation rate in patients with MIS-C.Pediatric Coronavirus Disease 2019 (pCOVID-19) is rarely severe; however, a minority of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might develop multisystem inflammatory syndrome in children (MIS-C), with substantial morbidity. In this longitudinal multi-institutional study, we applied multi-omics (analysis of soluble biomarkers, proteomics, single-cell gene expression and immune repertoire analysis) to profile children with COVID-19 (n = 110) and MIS-C (n = 76), along with pediatric healthy controls (pHCs; n = 76). pCOVID-19 was characterized by robust type I interferon (IFN) responses, whereas prominent type II IFN-dependent and NF-kappa B-dependent signatures, matrisome activation and increased levels of circulating spike protein were detected in MIS-C, with no correlation with SARS-CoV-2 PCR status around the time of admission. Transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation. The association of MIS-C with the combination of HLA A*02, B*35 and C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load than pCOVID-19 and pHC. These results identify distinct immunopathological signatures in pCOVID-19 and MIS-C that might help better define the pathophysiology of these disorders and guide therapy.

This article investigates the functional connectivity patterns of the nucleus accumbens (NAcc) in 18 healthy participants using a resting state functional connectivity (rsFC) protocol. Also, a meta-analytic connectivity modeling (MACM) was used to characterize patterns of functional coactivations involving NAcc: The results of a structure-basedmeta-analyses of 57 fMRI and PET studies were submitted to activation likelihood estimation analysis to estimate consistent activation patterns across the different imaging studies. The results of the combined rsFC and MACM analyses show that spontaneous activity in NAcc predicts activity in regions implicated in reward circuitries, including orbitomedial prefrontal cortex, globus pallidus, thalamus, midbrain, amygdala, and insula. This confirms the key role of NAcc in the mesocorticolimbic system, which integrates inputs from limbic and cortical regions. We also detected activity in brain regions having few or no direct anatomical connections with NAcc, such as sensorimotor cortex, cerebellum, medial and posterior parietal cortex, and medial/inferior temporal cortex, supporting the view that not all functional connections can be explained by anatomical connections but can also result from connections mediated by third areas. Our rsFC findings are in line with the results of the structure-based meta-analysis: MACM maps are superimposable with NAcc rsFC results, and the reward paradigm class is the one that most frequently generates activation in NAcc. Our results overlap considerably with recently proposed schemata of the main neuron systems in the limbic forebrain and in the anterior part of the limbic midbrain in rodents and nonhuman primates.

Background: Neuroimaging studies on brain correlates of rewarding experiences suggest a central role for the nucleus accumbens (NAcc). Methods: This study investigates the functional connectivity patterns of the NAcc in 18 healthy participants, using a resting-state functional connectivity (rsFC) protocol. Also, meta-analytic connectivity modeling (MACM) was used to characterize patterns of functional co-activations involving the NAcc: the results of a structure-based meta-analyses of 59 functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies were submitted to activation likelihood estimation (ALE) analysis in order to estimate consistent activation patterns across the different imaging studies. Results: The results of the combined rsFC and MACM analyses show that spontaneous activity in the NAcc predicts activity in regions implicated in reward circuitries, including orbito-medial prefrontal cortex, globus pallidus, thalamus, midbrain, amygdala, and insula. This confirms the key role of the NAcc in the mesocortico-limbic system, which integrates inputs from limbic and cortical regions. We also detected activity in brain regions having few or no direct anatomical connections with the NAcc, such as the sensori-motor cortex, cerebellum, medial and posterior parietal cortex, and medial/inferior temporal cortex, supporting the view that not all functional connections can be explained by anatomical connections, but can also result from connections mediated by third areas. Conclusions: Our rsFC findings are in line with the results of the structure-based meta-analysis: MACM maps are superimposable with the NAcc rsFC results, and the reward paradigm class is the one that most frequently generates activation in the NAcc.

As different areas within the PMC have different connectivity patterns with various cortical and subcortical regions, we hypothesized that distinct functional modules may be present within the PMC. Because the PMC appears to be the most active region during resting state, it has been postulated to play a fundamental role in the control of baseline brain functioning within the default mode network (DMN). Therefore one goal of this study was to explore which components of the PMC are specifically involved in the DMN. In a sample of seventeen healthy volunteers, we performed an unsupervised voxelwise ROI-based clustering based on resting state functional connectivity. Our results showed four clusters with different network connectivity. Each cluster showed positive and negative correlations with cortical regions involved in the DMN. Progressive shifts in PMC functional connectivity emerged from anterior to posterior and from dorsal to ventral ROIs. Ventral posterior portions of PMC were found to be part of a network implicated in the visuo-spatial guidance of movements, whereas dorsal anterior portions of PMC were interlinked with areas involved in attentional control. Ventral retrosplenial PMC selectively correlated with a network showing considerable overlap with the DMN, indicating that it makes essential contributions in self-referential processing, including autobiographical memory processing. Finally, ventral posterior PMC was shown to be functionally connected with a visual network. The paper represents the first attempt to provide a systematic, unsupervised, voxelwise clustering of the human posteromedial cortex (PMC), using resting-state functional connectivity data. Moreover, a ROI-based parcellation was used to confirm the results.

Aims Converging evidence supports the existence of a fronto-parietal association network which is most active during the baseline resting state and selectively deactivates during non-self directed cognitive tasks and neuropsychiatric conditions characterised by altered or abolished consciousness (Default Mode Network, DMN). Functional neuroimaging studies have suggested a central role for the precuneus and surrounding parietal areas (posteromedial cortex, PMC) in the control of baseline brain functioning within the DMN. Tracing studies in primates have shown that different areas within the PMC have different connectivity patterns, thus we set out to provide a systematic connectivity map of this key area using the resting-state functional connectivity approach. Methods Ten equispaced regions of interest were drawn within the PMC and submitted to seed-ROIs correlation analysis with fMRI in 17 subjects. Results We found a high level of local connectivity within the ten PMC components, with stronger functional intercorrelations among closely located areas. Moreover, anterior portions of PMC resulted to be part of a network implicated in the visuo-spatial guidance of movements, whereas posterior portions of PMC were interlinked with areas involved in processing self-relevant information and emotions. Conclusions The posterior PMC selectively correlates with a network showing considerable overlap with the DMN, thus suggesting that it makes essential contributions in self-referential processing and consciousness.