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 hospitalization2–4 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

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

The South Pacific trough: a crucial component of low-frequency pressure variations that determine ENSO development and strength

Much ENSO research and modelling has recently focussed on air-sea interactions along the equator and high-frequency wind and pressure changes. At a larger scale, van Loon (1984) proposed that the weakening of the Pacific trades between April-July prior to El Niño occurred as an enhanced surface trough in the westerlies developed in the South Pacific. This enhancement of the annual cycle (with a stronger high pressure over Australia) was proposed to: 1) direct southerly wind anomalies up into the western equatorial Pacific to the east of Australia, thereby contributing to westerly anomalies, and 2) direct south-westerly winds against the South Pacific high, thus weakening the high and the southeast trades moving back towards the western Pacific, i.e. a combined effect on the trades. Here, we explore temporal and spatial aspects of El Niño development by comparing composite anomaly sequences of sea-level pressure (SLP), surface winds and SST leading into strong, weak and late developing events. We confirm the traditional view that the Southern Oscillation is, to first order, a standing oscillation with geographically fixed nodes and antinodes. This oscillation of low pressure between south-eastern Australia and the central South Pacific is more pronounced leading into stronger El Niño events, with a resultant stronger pressure gradient between the regions early in year (0). We therefore confirm the South Pacific troughs combined effect on the Pacific trades, and find that the maximum warming in Nino 3 occurs between April-July when the trough is most influential in the annual cycle. An El Niño will not develop, or continue into a second austral summer, without a high pressure over Indo-Australia and an enhanced South Pacific trough extending low pressure up to the eastern equatorial Pacific. Composites of stronger El Niño events suggest that there is a more self sustaining propagation of low pressure and associated westerly wind anomalies from the Australian region in year (-1) into the Pacific in year (0). This progression appears to be linked to an eastward progression of warm SST anomalies along the equator that bi-furcates into the South Pacific Convergence Zone and northern Pacific subtropics early in year (0). Significant low pressure anomalies in the North and South Pacific midlatitudes appear critical in MJJ (0) to provide the large scale forcing required for significant Pacific warming. The larger spatial extent of warm SST and negative MSLP anomalies in strong events suggest that the planetary waves in the northern subtropics also become involved and compliment the southern hemisphere. In contrast, weaker El Niño events had a weaker and less distinct eastward progression of low pressure and SST anomalies and much less support from the northern midlatitudes between May-October (0). The timing of ridge strengthening in the North and South Pacific was also found to determine whether an El Niño developed into a La Niño or neutral conditions. Reference: van Loon, H., 1984: The Southern Oscillation. Part III, Associations with the trades and with the trough in the westerlies of the South Pacific Ocean. Mon. Wea. Rev., 112, 947-954..Pages: 633-63

Mapping the human genetic architecture of COVID-19

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 diseases3–7. 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

Crop Updates 1999 - Cereals

This article covers sixty papers FOREWORD ACKNOWLEDGMENTS PLENARY PAPERS 1. Western Australia’s climate: trends and opportunities, Len W. Broadbridge, Director, Bureau of Meterorology 2. Managing seasonal variations in agriculture, Dr Doug Abrecht, Director, Dryland Research Institute, Merredin CROP ESTABLISHMENT 3. Soil management to prevent waterlogging on duplex soils in the Great Southern, D. Bakker, Greg Hamilton, Cliff Spann and Doug Rowe, Agriculture Western Australia 4. The influence of no-till and press wheels on crop production for heavy soils, Peter Fisher, Jennifer Bignell, Matthew Braimbridge, Greg Hamilton, Agriculture Western Australia NUTRITION 5. Fertiliser nitrogen, applied late, needs rain to increase grain nitrogen and protein levels in wheat, Bill Bowden1, Ross Brennan1, Reg Lunt1 and Senthold Asseng2 1 Agriculture Western Australia, 2 CSIRO 6. Canola upsets the nutrition of the next cereal crop? Bill Bowden1, Garren Knell1, Cherie Rowles 1, Simon Bedbrook\u27, Chris Gazey 1,Mike Bolland1, Ross Brennan 1, Lyn Abbott2, Zed Rengel2 and Wayne Pluske3, 1 Agriculture Western Australia, 2 UWA Soil Science, 3 CSBP 7. Comparisons between high analysis nitrogen sources, Erin Cahill, CSBP 8. Urea additives for reduced drilled urea toxicity for canola and wheat, Bill Crabtree, WANTFA 9. Fertiliser placement, Matthew Evans, CSBP 9. The profitability of variable rate nitrogen applications on wheat, Tim Nielsen, CSBP Technical Services DISEASE 10. Fungicide for wheat leaf disease: boon or bane? Jat Bhathal, Rob Loughman and D. Rasmussen, Plant Pathology, Agriculture Western Australia 11. Role of retained wheat stubbles in disease carryover in wheat/lupin rotations, Jat Bhathal and Rob Loughman, Plant Pathology, Agriculture Western Australia 12. Comparison of aerial and ground application of fungicide for lead disease control ion wheat, Jat Bhathal and Rob Loughman, Plant Pathology, Agriculture Western Australia 13. Bean yellow mosaic virus infection of alternative pasture legume species, Roger Jones, CRC for legumes in Mediterranean Agriculture and Agriculture Western Australia 14. Survey of cereal root nematodes in cropping soils in Western Australia, Sean Kelly1, Ian Riley2 and Robert Loughman1, 1 Agriculture Western Australia,2 University of Adelaide 15. Crop management options for root lesion nematode, Robert Loughman 1, Sharyn Taylor2, Vivien Vanstone 3, Ian Riley3 and Dominie Wright1, 1 Agriculture Western Australia, 2SARDI Plant Research Centre, Glen Osmond, South Australia 3 University of Adelaide, Glen Osmond, South Australia 16. Forecasting barley yellow dwarf risk in cereals, Debbie Thackray and Roger Jones, Agriculture Western Australia and CRC for Legumes in Mediterranean Agriculture 17. Managing barley yellow dwarf virus in cereal crops, Debbie Thackray, Roger Jones and Simon McKirdy, Agriculture Western Australia and CRC for Legumes in Mediterranean Agriculture 18. Broadacre diagnostic service, Dominie Wright, Agriculture Western Australia, AGWEST Plant Laboratories 19. Using twist fungus (Dilophospora alopecuri) to reduce the risk of annual ryegrass toxicity, Dr George Yan1 and Dr Ian Riley2, 1 Plant Research and Development Service, Agriculture Western Australia, 2 Applied and Molecular Ecology, Waite Campus, The University of Adelaide, South Australia NEW VARIETIES 20. New wheat and oat varieties for 1999, Robin Wilson, lain Barclay, Robyn Mclean, Dean Diepeveen, Robert Loughman, and Bill Lambe, Agriculture Western Australia 21. Performance in 1998 of recently released wheat varieties, Robin Wilson, lain Barclay, Robyn Mclean, Dean Diepeveen, Robert Loughman and Bill Lambe, Agriculture Western Australia WHEAT AGRONOMY 22. Increasing the noodle ‘strike rate’, Wal Anderson, Brenda Shackley and Mechelle Owen, Agriculture Western Australia, Quality Wheat CRC 23. Variety trials: wheat and barley, Peter Burgess, Lamond Burgess & Associates 24. South coast wheat variety farmer survey, Ben Curtis, Agriculture Western Australia 25. Residual effects of deep ripping, gypsum and nutrients on grain yields and soil properties, Mohammed A. Hamza and W.K. Anderson, Agriculture Western Australia 26. How to ensure durum wheat profitability! Jamie Henderson, Frank Boetel and Alfredo lmpiglia, Agriculture Western Australia 27. Agronomic evaluation of new wheat varieties for 1999 in the Northern Agricultural Region, Frances Hoyle, Agriculture Western Australia 28. The influence of on-farm management and variety of grain screening levels, Frances Hoyle, Agriculture Western Australia 29. Variety response of hard wheats to management, Darshan Sharma and Wal Anderson, Agriculture Western Australia BARLEY AND OATS 30. Studies into production of export oaten hay, Pierre Fievez, Pierre Fievez and Associates 31. Gairdner barley in the Central and Northern Regions, Blakely Paynter, Agriculture Western Australia 32. Improving milling oat quality, Glenn McDonald, Agriculture Western Australia 33. Gairdner barley in the Southern Region, Kevin Young, Agriculture Western Australia PASTURE 34. The herbicide tolerance of some annual pasture legumes, Andrew Blake, Agriculture Western Australia 35. Pasture systems for cropping rotations in the northern wheatbelt, Keith Devenish, Agriculture Western Australia 36. Perennial pastures reduce recharge and acidification, Perry Dolling, Agriculture Western Australia 37. It’s time to include Lucerne in the pasture-crop system, Roy Latta 1, Lisa-Jane Blacklow2 and Chris Matthews 1,1 Agriculture Western Australia, 2 University of Western Australia, 38. New alternative pasture legume for fine textured soils, Angelo Loi, Brad Nutt and Rochelle McRobb, National Australian Pasture Legumes Improvement Program (NAPLIP) and Centre for Legumes in Mediterranean Agriculture (CLIMA) 39. Increasing pasture productivity on acid wodjil soils, Brad Nutt, David Webb and Andrew McRobb, Centre for Legumes in Mediterranean Agriculture (CLIMA) 40. Annual legume pasture species now available for use in cropping systems. Clinton Revell, Agriculture Western Australia 41. Herbicide and cultural management of Cadiz serradella in ‘phase’ pastures, Clinton Revell, Agriculture Western Australia 42. Spring spraying for redlegged earth mite, James Ridsdill-Smith and Celia Pavri, CSIRO Entomology and CLIMA 43. Water use and water extraction by recently developed pasture legume species and cultivars, David Tennant1, Darryl McClements2, Ross Thompson 1 and Mike Ewing2, 1 Natural Resource Management Services, Soil Management, 2 Plant Research and Development, Pasture Sciences 44. Death knell to doublegees? Tim Woodburn· and Paul Yeoh, CSIRO Entomology/CRC Weed Management Systems, Floreat LIMING 45. Calculated lime requirements for rotations, James Fisher1, Art Diggle 1•2 and Bill Bowden 1•2, 1 Centre for Legumes in Mediterranean Agriculture 2 Agriculture Western Australia 46. The RH lime reactivity test and RH of typical WA limes, Mark Whitten and Andrew Rate, Soil Science and Plant Nutrition, University of Western Australia YIELD MAPPING 47. Benchmarking target yields for wheat, Senthold Asseng 1, Bill Bowden2 and Paul Carlile3, 1 CSIRO Plant Industry, 2 Agriculture Western Australia, 3 UWA 48. Getting the most information from farm scale trial, Ed Blanchard, Agricultural Engineering and Precision Farming Consultant, Merredin, WA 49. Measuring nutrient changes using yield maps, Ed Blanchard, Agricultural engineering and precision farming consultant; Precision Farming Demonstration Project Coordinator for the Kondinin Group, Merredin WA BREEDING 50. Crop improvement royalties – investing in the future, Bevan Buirchell and Dean Diepeveen, Agriculture Western Australia 51. Screening cereals for genotypic variation in phosphorus efficiency, Lorraine Osborne and Zed Rengel, Soil Science and Plant Nutrition, University of Western Australia ON FARM TESTING 52. Test as you grow pays dividends, John Blake, Tress Walmsley, Terry Piper, Wal Anderson, Dean Diepeveen, Cameron Weeks, Michael Dodd, Amanda Falconer, Caroline Peek, Glenn Adam, Agriculture Western Australia 53. How useful is on-farm testing, Camray Gethin 1, Richard Guinness2, Simon Bedbrook1, Dean Diepeveen4, 1 TopCrop Development Officer, Agriculture Western Australia, 2 Farmer, Kunjin TopCrop Group, Corrigin, 3 Agricultural Consultant, Farmanco, York, 4 CVT service, Crop Industries, Agriculture Western Australia, ECONOMICS 54. The impact of farm practices on sustainability costs of rotations, Pierre Fievez, Pierre Fievez and Associates 55. Right rotations for TopCrop, Daniel Fels, Agriculture Western Australia 56. Dollars of water use efficiency, Andrew Rintoul, FAST National, GRDC funded project, Planfarm 57. Farm business structures, Andrew Rintoul, FAST National, GRDC funded project, Planfarm CLIMATE 58. Broadscale weather aspects affecting Western Australia during 1998 and prospects for 1999, Mal Lamond, Lamond Weather Services 59. An updated look at aspects of rainfall trends and variability in the south-west of Western Australia, Roger Tapp, Climate and Consultancy Section, Bureau of Meteorology, Perth WA 60. Frost research in the eastern wheatbelt, Craig White, Research Officer, Agriculture Western Australia, Presented by D.G. Abrech

Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (<60 years) cases with no reported clinical risk factors (n = 378), compared to 0.24% of controls (odds ratio [OR] = 12.3, p = 1.27 × 10−10). Incorporation of the results of either functional assays or protein modeling led to a pronounced increase in effect size (ORmax = 46.5, p = 1.74 × 10−15). Association signals for the X-chromosomal gene TLR7 were also detected in the female-only subgroup, suggesting the existence of additional mechanisms beyond X-linked recessive inheritance in males. Additionally, supporting evidence was generated for a contribution to severe COVID-19 of the previously implicated genes IFNAR2, IFIH1, and TBK1. Our results refine the genetic contribution of rare TLR7 variants to severe COVID-19 and strengthen evidence for the etiological relevance of genes in the interferon signaling pathway

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, 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).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)

Mapping the human genetic architecture of COVID-19

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