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

Do Curved Reaching Movements Emerge From Competing Perceptions? A Reply to van der Wel et al. (2009)

Contains fulltext : 90173.pdf (publisher's version ) (Closed access)Spivey, Grosjean, and Knoblich (2005) reported smoothly curved reaching movements, via computer-mouse tracking, which suggested a continuously evolving flow of distributed lexical activation patterns into motor movement during a phonological competitor task. For example, when instructed to click the "candy," participants' mouse-cursor trajectories curved conspicuously toward a picture of a candle before landing on the picture of the candy. In their commentary on this work, van der Wel, Eder, Mitchel, Walsh, and Rosenbaum (2009) describe a quantitative simulation of reaching movements that stands as an existence proof that a discrete-processing speech perception system can feed into a continuous-processing motor movement system to produce reach trajectories similar to that observed by Spivey et al. In this reply, we describe eye-tracking evidence, new mouse-tracking evidence, and a dynamic version of van der Wel et al's simulation, all of which suggest that competing perceptual representations may instigate the preparation of multiple movement plans that are merged in a dynamically weighted average, thus producing a single smoothly curved movement. Like van der Wel et al., we are optimistic that an emphasis on the computational linking hypothesis between hypothesized perceptual representations and recorded motor movements will elucidate the discrete versus continuous aspects of perceptual, cognitive, and motor processing

Language production: computational models

Dell GS, Cholin J. Language production: computational models. In: Spivey MJ, McRae K, Jonnaise M, eds. Cambridge Handbook of Psycholinguistics. Cambridge: Cambridge University Press; 2012: 426-442