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

Autonomy: Risk Assessment

Oceanography and ocean observation in general is ever trending toward both automated in situ observation and working in extreme environments. These goals can only be met by de?risking the technology and deployment practices to acceptable levels of risks. A number of industries have standardised risk management processes to support the design and development of their systems. The lack of formal risk assessment of autonomous ocean vehicles has hindered the potential for true autonomy, which is required for exploring unstructured and unexplored environments. When discussing risks different stakeholders may have different consequences foremost in mind. For example the vehicle owner may be interested in risk of loss, whereas the user is interested in risk of vehicle unavailability. Other risks, such as legal risks and risk of collision, affect all stakeholders. This chapter presents a risk management process using several methods tailored to autonomous oceanvehicles in which risk assessment is a key component