Immunology of multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) leading to demyelination, axonal damage, and progressive neurologic disability. The development of MS is influenced by environmental factors, particularly the Epstein-Barr virus (EBV), and genetic factors, which include specific HLA types, particularly DRB1*1501-DQA1*0102-DQB1*0602, and a predisposition to autoimmunity in general. MS patients have increased circulating T-cell and antibody reactivity to myelin proteins and gangliosides. It is proposed that the role of EBV is to infect autoreactive B cells that then seed the CNS and promote the survival of autoreactive T cells there. It is also proposed that the clinical attacks of relapsing-remitting MS are orchestrated by myelin-reactive T cells entering the white matter of the CNS from the blood, and that the progressive disability in primary and secondary progressive MS is caused by the action of autoantibodies produced in the CNS by ­meningeal lymphoid follicles with germinal centers

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Deficits in social behavioral tests in a mouse model of alternating hemiplegia of childhood

Social behavioral deficits have been observed in patients diagnosed with alternating hemiplegia of childhood (AHC), rapid-onset dystonia-parkinsonism and CAPOS syndrome, in which specific missense mutations in ATP1A3, encoding the Na+, K+-ATPase α3 subunit, have been identified. To test the hypothesis that social behavioral deficits represent part of the phenotype of Na+, K+-ATPase α3 mutations, we assessed the social behavior of the Myshkin mouse model of AHC, which has an I810N mutation identical to that found in an AHC patient with co-morbid autism. Myshkin mice displayed deficits in three tests of social behavior: nest building, pup retrieval and the three-chamber social approach test. Chronic treatment with the mood stabilizer lithium enhanced nest building in wild-type but not Myshkin mice. In light of previous studies revealing a broad profile of neurobehavioral deficits in the Myshkin model – consistent with the complex clinical profile of AHC – our results suggest that Na+, K+-ATPase α3 dysfunction has a deleterious, but nonspecific, effect on social behavior. By better defining the behavioral profile of Myshkin mice, we identify additional ATP1A3-related symptoms for which the Myshkin model could be used as a tool to advance understanding of the underlying neural mechanisms and develop novel therapeutic strategies