ABSTRACT
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.
Subject(s)
COVID-19 , Critical Illness , Genome, Human , Host-Pathogen Interactions , Whole Genome Sequencing , ATP-Binding Cassette Transporters , COVID-19/genetics , COVID-19/mortality , COVID-19/pathology , COVID-19/virology , Cell Adhesion Molecules , Critical Care , Critical Illness/mortality , E-Selectin , Factor VIII , Fucosyltransferases , Genome, Human/genetics , Genome-Wide Association Study , Host-Pathogen Interactions/genetics , Humans , Interleukin-10 Receptor beta Subunit , Lectins, C-Type , Mucin-1 , Nerve Tissue Proteins , Phospholipid Transfer Proteins , Receptors, Cell Surface , Repressor Proteins , SARS-CoV-2/pathogenicity , Galactoside 2-alpha-L-fucosyltransferaseABSTRACT
A central research question in natural vision is how to allocate fixation to extract informative cues for scene perception. With high quality images, psychological and computational studies have made significant progress to understand and predict human gaze allocation in scene exploration. However, it is unclear whether these findings can be generalised to degraded naturalistic visual inputs. In this eye-tracking and computational study, we methodically distorted both man-made and natural scenes with Gaussian low-pass filter, circular averaging filter and Additive Gaussian white noise, and monitored participants' gaze behaviour in assessing perceived image qualities. Compared with original high quality images, distorted images attracted fewer numbers of fixations but longer fixation durations, shorter saccade distance and stronger central fixation bias. This impact of image noise manipulation on gaze distribution was mainly determined by noise intensity rather than noise type, and was more pronounced for natural scenes than for man-made scenes. We furthered compared four high performing visual attention models in predicting human gaze allocation in degraded scenes, and found that model performance lacked human-like sensitivity to noise type and intensity, and was considerably worse than human performance measured as inter-observer variance. Furthermore, the central fixation bias is a major predictor for human gaze allocation, which becomes more prominent with increased noise intensity. Our results indicate a crucial role of external noise intensity in determining scene-viewing gaze behaviour, which should be considered in the development of realistic human-vision-inspired attention models.
Subject(s)
Attention/physiology , Visual Perception/physiology , Adolescent , Adult , Analysis of Variance , Cues , Female , Fixation, Ocular/physiology , Humans , Male , Photic Stimulation/methods , Saccades/physiology , Time Factors , Young AdultABSTRACT
The plant shoot body plan is highly variable, depending on the degree of branching. Characterization of the max1-max4 mutants of Arabidopsis demonstrates that branching is regulated by at least one carotenoid-derived hormone. Here we show that all four MAX genes act in a single pathway, with MAX1, MAX3, and MAX4 acting in hormone synthesis, and MAX2 acting in perception. We propose that MAX1 acts on a mobile substrate, downstream of MAX3 and MAX4, which have immobile substrates. These roles for MAX3, MAX4, and MAX2 are consistent with their known molecular identities. We identify MAX1 as a member of the cytochrome P450 family with high similarity to mammalian Thromboxane A2 synthase. This, with its expression pattern, supports its suggested role in the MAX pathway. Moreover, the proposed enzymatic series for MAX hormone synthesis resembles that of two already characterized signal biosynthetic pathways: prostaglandins in animals and oxilipins in plants.