Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).
‘Fake news’ has been a topic of controversy during and following the 2016 U.S. presidential election. Much of the scholarship on it to date has focused on the ‘fakeness’ of fake news, illuminating the kinds of deception involved and the motivations of those who deceive. This study looks at the ‘newsness’ of fake news by examining the extent to which it imitates the characteristics and conventions of traditional journalism. Through a content analysis of 886 fake news articles, we find that in terms of news values, topic, and formats, articles published by fake news sites look very much like traditional—and real—news. Most of their articles included the news values of timeliness, negativity, and prominence; were about government and politics; and were written in an inverted pyramid format. However, one point of departure is in terms of objectivity, operationalized as the absence of the author’s personal opinion. The analysis found that the majority of articles analyzed included the opinion of their author or authors.
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