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

Roma crash map: An open data visualization tool for the municipalities of Rome

The open data availability, promoted by the open government approach, does not correspond to an effective and organized use of them with the detriment of both citizens and PAs. We assume that a data visualization tool could help the spread of information in an easy and accessible way, even for what concerns open data. In this paper we will focus on the map, as one of the most suitable tools for the interactive representation of spatial related data. So, we will present the Roma Crash Map platform, a web application that allows to visualize the road crashes open data related to the 19 Municipalities of the city of Rome. In details, we will report the considerations about the selection and design of the visualization tools, according to the purpose to familiarize the users with participating tools integrating maps or more complex geographical systems. © 2014 Springer International Publishing