Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Measuring the Environmental Sustainability Performance of Global Supply Chains: a Multi-Regional Input-Output analysis for Carbon, Sulphur Oxide and Water Footprints

Measuring the performance of what an environmentally sustainable supply chain has become a challenge despite the convergence of the underlining principles of sustainable supply chain management. This challenge is exacerbated by the fact that supply chains are inherently dynamic and complex and also because multiple measures can be used to characterize performances. By identifying some of the critical issues in the literature regarding performance measurements, this paper contributes to the existing body of literature by adopting an environmental performance measurement approach for economic sectors (primary, secondary and tertiary sectors). It uses economic sectors and evaluates them on a sectoral level in specific countries as well as part of the Global Value Chain based on the established multi-regional input-output (MRIO) modelling framework. The MRIO model has been used to calculate direct and indirect (that is supply chain or upstream) environmental effects such as CO2, SO2, biodiversity, water consumption and pollution to name just a few of the applications. In this paper we use MRIO to calculate emissions and resource consumption intensities and footprints, direct and indirect impacts, and net emission flows between countries. These are exemplified by using carbon emissions, sulphur oxide emissions and water use in two highly polluting industries; Electricity production and Chemical industry in 33 countries, including the EU-27, Brazil, India and China, the USA, Canada and Japan from 1995 to 2009. Some of the results highlights include: On average, direct carbon emissions in the electricity sector across all 27 member states of the EU was estimated to be 1368 million tonnes and indirect carbon emissions to be 470.7 million tonnes per year representing 25.6% of the EU-27 total carbon emissions related to this sector. It was also observed that from 2004, sulphur oxide emissions intensities in electricity production in India and China have remained relatively constant at about 62.8 gSOx/$and 84.4 gSOx/$ although being higher than in other countries. In terms of water use, the high water use intensity in China (1040.27 litres/$) and India (961.63 litres/$), which are among the highest in the sector in the electricity sector is exacerbated by both countries being ranked as High Water Stress Risk countries. The paper also highlights many merits of the MRIO including: a 15-year time series study (which provides a measurement of environmental performance of key industries and an opportunity to assess technical and technological change during the investigated time period), a supply chain approach that provides a consistent methodological framework and accounts for all upstream supply chain environmental impacts throughout entire global supply chains. The paper also discusses the implications of the study to environmental sustainability performance measurement in terms of the level of analysis from a value chain hierarchy perspective, methodological issues, performance indicators, environmental exchanges and policy relevance

The epistemology of ethical intuitions

Intuitions are widely assumed to play an important evidential role in ethical inquiry. In this paper I critically discuss a recently influential claim that the epistemological credentials of ethical intuitions are undermined by their causal pedigree and functional role. I argue that this claim is exaggerated. In the course of doing so I argue that the challenge to ethical intuitions embodied in this claim should be understood not only as a narrowly epistemological challenge, but also as a substantially ethical one. I argue that this fact illuminates the epistemology of ethical intuitions