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

Homogeneity testing: how homogeneous do heterogeneous cross-correlated regions seem?

The homogeneity of the flood frequency regime for a given pooling-group of sites is a fundamental assumption for many regional flood frequency analysis techniques. Assessing regional homogeneity is a critical step, which may be complicated by the presence of cross-correlation among flood sequences. The scientific literature proposes a number of statistical homogeneity tests and documents that inter-site correlation of floods is normally not negligible, but does not specifically address the impact of cross-correlation on such statistical tests. This paper analyzes the effectiveness of a well-known homogeneity test proposed in the scientific literature in the presence of inter-site cross-correlation through a series of Monte Carlo experiments. The numerical experiments enable us to comment on a possible theoretical correction for the test and to identify an empirical tool that accounts for the impact of inter-site cross-correlation of floods

Eureka : Artists from Australia

This catalogue of a double-exhibition of widely diverse work by 15 artists and two collectives, centres around themes of labour, human rights and politics. Statements by the artists, followed by a brief history of contemporary Australian art by Underhill, a staged "interview" of ideas by four Australian critics outlining current issues of debate, and an analysis of the pluralism in Australian art by Taylor. 81 bibl. ref