Implementation of U.K. Earth system models for CMIP6

We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere-land-ocean-sea ice model HadGEM3-GC3.1 and the Earth system model UKESM1 which adds a carbon-nitrogen cycle and atmospheric chemistry to HadGEM3-GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions.We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3-GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation.We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility

Operationalizing marketable blue carbon

The global carbon sequestration and avoided emissions potentially achieved via blue carbon is high (∼3% of annual global greenhouse gas emissions); however, it is limited by multidisciplinary and interacting uncertainties spanning the social, governance, financial, and technological dimensions. We compiled a transdisciplinary team of experts to elucidate these challenges and identify a way forward. Key actions to enhance blue carbon as a natural climate solution include improving policy and legal arrangements to ensure equitable sharing of benefits; improving stewardship by incorporating indigenous knowledge and values; clarifying property rights; improving financial approaches and accounting tools to incorporate co-benefits; developing technological solutions for measuring blue carbon sequestration at low cost; and resolving knowledge gaps regarding blue carbon cycles. Implementing these actions and operationalizing blue carbon will achieve measurable changes to atmospheric greenhouse gas concentrations, provide multiple co-benefits, and address national obligations associated with international agreements

The Hubble Space Telescope Wide Field Camera 3 Early Release Science data: Panchromatic Faint Object Counts for 0.2-2 microns wavelength

We describe the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) Early Release Science (ERS) observations in the Great Observatories Origins Deep Survey (GOODS) South field. The new WFC3 ERS data provide calibrated, drizzled mosaics in the UV filters F225W, F275W, and F336W, as well as in the near-IR filters F098M (Ys), F125W (J), and F160W (H) with 1-2 HST orbits per filter. Together with the existing HST Advanced Camera for Surveys (ACS) GOODS-South mosaics in the BViz filters, these panchromatic 10-band ERS data cover 40-50 square arcmin at 0.2-1.7 {\mu}m in wavelength at 0.07-0.15" FWHM resolution and 0.090" Multidrizzled pixels to depths of AB\simeq 26.0-27.0 mag (5-{\sigma}) for point sources, and AB\simeq 25.5-26.5 mag for compact galaxies. In this paper, we describe: a) the scientific rationale, and the data taking plus reduction procedures of the panchromatic 10-band ERS mosaics; b) the procedure of generating object catalogs across the 10 different ERS filters, and the specific star-galaxy separation techniques used; and c) the reliability and completeness of the object catalogs from the WFC3 ERS mosaics. The excellent 0.07-0.15" FWHM resolution of HST/WFC3 and ACS makes star- galaxy separation straightforward over a factor of 10 in wavelength to AB\simeq 25-26 mag from the UV to the near-IR, respectively.Comment: 51 pages, 71 figures Accepted to ApJS 2011.01.2

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Known and unknown requirements in healthcare

We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).Supported by a career development award from the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH) (K08HL114642 to Dr. Stitziel) and by the Foundation for Barnes–Jewish Hospital. Dr. Peloso is supported by the National Heart, Lung, and Blood Institute of the NIH (award number K01HL125751). Dr. Kathiresan is supported by a Research Scholar award from the Massachusetts General Hospital, the Donovan Family Foundation, grants from the NIH (R01HL107816 and R01HL127564), a grant from Fondation Leducq, and an investigator-initiated grant from Merck. Dr. Merlini was supported by a grant from the Italian Ministry of Health (RFPS-2007-3-644382). Drs. Ardissino and Marziliano were supported by Regione Emilia Romagna Area 1 Grants. Drs. Farrall and Watkins acknowledge the support of the Wellcome Trust core award (090532/Z/09/Z), the British Heart Foundation (BHF) Centre of Research Excellence. Dr. Schick is supported in part by a grant from the National Cancer Institute (R25CA094880). Dr. Goel acknowledges EU FP7 & Wellcome Trust Institutional strategic support fund. Dr. Deloukas’s work forms part of the research themes contributing to the translational research portfolio of Barts Cardiovascular Biomedical Research Unit, which is supported and funded by the National Institute for Health Research (NIHR). Drs. Webb and Samani are funded by the British Heart Foundation, and Dr. Samani is an NIHR Senior Investigator. Dr. Masca was supported by the NIHR Leicester Cardiovascular Biomedical Research Unit (BRU), and this work forms part of the portfolio of research supported by the BRU. Dr. Won was supported by a postdoctoral award from the American Heart Association (15POST23280019). Dr. McCarthy is a Wellcome Trust Senior Investigator (098381) and an NIHR Senior Investigator. Dr. Danesh is a British Heart Foundation Professor, European Research Council Senior Investigator, and NIHR Senior Investigator. Drs. Erdmann, Webb, Samani, and Schunkert are supported by the FP7 European Union project CVgenes@ target (261123) and the Fondation Leducq (CADgenomics, 12CVD02). Drs. Erdmann and Schunkert are also supported by the German Federal Ministry of Education and Research e:Med program (e:AtheroSysMed and sysINFLAME), and Deutsche Forschungsgemeinschaft cluster of excellence “Inflammation at Interfaces” and SFB 1123. Dr. Kessler received a DZHK Rotation Grant. The analysis was funded, in part, by a Programme Grant from the BHF (RG/14/5/30893 to Dr. Deloukas). Additional funding is listed in the Supplementary Appendix.This is the author accepted manuscript. The final version is available from the Massachusetts Medical Society via http://dx.doi.org/10.1056/NEJMoa150765

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

Effectiveness of rapid SARS-CoV-2 genome sequencing in supporting infection control for hospital-onset COVID-19 infection : multicenter, prospective study

Background: Viral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. Methods: We conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data-collection period, followed by intervention periods comprising 8 weeks of 'rapid' (<48h) and 4 weeks of 'longer-turnaround' (5-10 day) sequencing using a sequence reporting tool (SRT). Data were collected on all hospital onset COVID-19 infections (HOCIs; detected ≥48h from admission). The impact of the sequencing intervention on IPC knowledge and actions, and on incidence of probable/definite hospital-acquired infections (HAIs) was evaluated. Results: A total of 2170 HOCI cases were recorded from October 2020-April 2021, corresponding to a period of extreme strain on the health service, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (incidence rate ratio 1.60, 95%CI 0.85-3.01; P=0.14) or rapid (0.85, 0.48-1.50; P=0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8% and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2% and 11.6% of cases where the report was returned. In a 'per-protocol' sensitivity analysis there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. Capacity to respond effectively to insights from sequencing was breached in most sites by the volume of cases and limited resources. Conclusion: While we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days. Funding: COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) [grant code: MC_PC_19027], and Genome Research Limited, operating as the Wellcome Sanger Institute. Clinical trial number: ClinicalTrials.gov Identifier: NCT04405934

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant