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The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Background: Legionella pneumophila (L. pneumophila) is a causative agent of severe pneumonia. It is highly adapted to intracellular replication and manipulates host cell functions like vesicle trafficking and mRNA translation to its own advantage. However, it is still unknown to what extent microRNAs (miRNAs) are involved in the Legionella-host cell interaction.
Methods: WT and MyD88-/- murine bone marrow-derived macrophages (BMM) were infected with L. pneumophila, the transcriptome was analyzed by high throughput qPCR array (microRNAs) and conventional qPCR (mRNAs), and mRNA-miRNA interaction was validated by luciferase assays with 3´-UTR mutations and western blot.
Results: L. pneumophila infection caused a pro-inflammatory reaction and significant miRNA changes in murine macrophages. In MyD88-/- cells, induction of inflammatory markers, such as Ccxl1/Kc, Il6 and miR-146a-5p was reduced. Induction of miR-125a-3p was completely abrogated in MyD88-/- cells. Target prediction analyses revealed N-terminal asparagine amidase 1 (NTAN1), a factor from the n-end rule pathway, to be a putative target of miR-125a-3p. This interaction could be confirmed by luciferase assay and western blot.
Conclusion: Taken together, we characterized the miRNA regulation in L. pneumophila infection with regard to MyD88 signaling and identified NTAN1 as a target of miR-125a-3p. This finding unravels a yet unknown feature of Legionella-host cell interaction, potentially relevant for new treatment options.