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 hospitalization2–4 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

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

CPG-based locomotion control of a quadruped robot with an active spine

Central pattern generators (CPGs) are neural networks re- sponsible for producing rhythmic behaviours and are commonly found in both vertebrate and invertebrate animals. This paper proposes a novel internal feedback mechanism for a CPG model designed to generate leg- spine coordinated locomotion in a quadruped robot with an active spine. This mechanism enables the CPG to independently control the frequency and amplitude of the stance and swing durations while also modifying the definition of stance and swing phases to generate more gaits. The CPG model’s results are demonstrated on a simulated ”tensegrity quadruped robot” called TQbot, which features a flexible spine with 3 degrees of freedom (DOF). By adjusting the parameters, the CPG model can gen- erate gaits with leg-spine coordination and uses the spine for turning

Sea ice growth rates from tide-driven visible banding

In this paper, periodic tide-current-driven banding in a sea-ice core is demonstrated as a measure of the growth rate of first-year sea ice at congelation-ice depths. The study was performed on a core from the eastern McMurdo Sound, exploiting the well-characterized tidal pattern at the site. It points the way to a technique for determining early-season ice growth rates from late-season cores, in areas where under ice currents are known to be tidally dominated and the ice is landfast, thus providing data for a time of year when thin ice prevents direct thickness (and therefore growth rate) measurements. The measured results were compared to the growth-versus-depth predicted by a thermodynamic model.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

AMP-activated Protein Kinase Stimulates Warburg-like Glycolysis and Activation of Satellite Cells during Muscle Regeneration

Satellite cells are the major myogenic stem cells residing inside skeletal muscle and are indispensable for muscle regeneration. Satellite cells remain largely quiescent but are rapidly activated in response to muscle injury, and the derived myogenic cells then fuse to repair damaged muscle fibers or form new muscle fibers. However, mechanisms eliciting metabolic activation, an inseparable step for satellite cell activation following muscle injury, have not been defined. We found that a noncanonical Sonic Hedgehog (Shh) pathway is rapidly activated in response to muscle injury, which activates AMPK and induces a Warburg-like glycolysis in satellite cells. AMPKα1 is the dominant AMPKα isoform expressed in satellite cells, and AMPKα1 deficiency in satellite cells impairs their activation and myogenic differentiation during muscle regeneration. Drugs activating noncanonical Shh promote proliferation of satellite cells, which is abolished because of satellite cell-specific AMPKα1 knock-out. Taken together, AMPKα1 is a critical mediator linking noncanonical Shh pathway to Warburg-like glycolysis in satellite cells, which is required for satellite activation and muscle regeneration