Characterisation of Bidor Kaolinite and Illite

Two types of commercial clay minerals from the Bidor region of Perak were studied. From the X-ray diffraction study, these clays were identified as disordered kaolinite and 2 M polymorph of illite. The morphologies, the surface properties, the pore structures and the infrared absorption properties were examined. The basis for the identification of these clays is discussed

Determinants of male reproductive health disorders: the Men in Australia Telephone Survey (MATeS)

Background: The relationship between reproductive health disorders and lifestyle factors in middle-aged and older men is not clear. The aim of this study is to describe lifestyle and biomedical associations as possible causes of erectile dysfunction (ED), prostate disease (PD), lower urinary tract symptoms (LUTS) and perceived symptoms of androgen deficiency (pAD) in a representative population of middle-aged and older men, using the Men in Australia Telephone Survey (MATeS). Methods: A representative sample (n = 5990) of men aged 40+ years, stratified by age and State, was contacted by random selection of households, with an individual response rate of 78%. All men participated in a 20-minute computer-assisted telephone interview exploring general and reproductive health. Associations between male reproductive health disorders and lifestyle and biomedical factors were analysed using multivariate logistic regression (odds ratio [95% confidence interval]). Variables studied included age, body mass index, waist circumference, smoking, alcohol consumption, physical activity, co-morbid disease and medication use for hypertension, high cholesterol and symptoms of depression. Results: Controlling for age and a range of lifestyle and co-morbid exposures, sedentary lifestyle and being underweight was associated with an increased likelihood of ED (1.4 [1.1-1.8]; 2.9 [1.5-5.8], respectively) and pAD (1.3 [1.1-1.7]; 2.7 [1.4-5.0], respectively. Diabetes and cardiovascular disease were both associated with ED, with hypertension strongly associated with LUTS and pAD. Current smoking (inverse association) and depressive symptomatology were the only variables independently associated with PD. All reproductive disorders showed consistent associations with depression (measured either by depressive symptomatology or medication use) in both age-adjusted and multivariate analyses. Conclusion: A range of lifestyle factors, more often associated with chronic disease, were significantly associated with male reproductive health disorders. Education strategies directed to improving general health may also confer benefits to male reproductive health.Carol A. Holden, Robert I. McLachlan, Marian Pitts, Robert Cumming, Gary Wittert, Johnathon P. Ehsani, David M. de Kretser, David J. Handelsma

Associations between weight change and biomarkers of cardiometabolic risk in South Asians:secondary analyses of the PODOSA trial

Background/Objectives: The association of weight changes with cardiometabolic biomarkers in South Asians has been sparsely studied. Subjects/Methods: We measured cardiometabolic biomarkers at baseline and after 3 years in the Prevention of Diabetes and Obesity in South Asians Trial. We investigated the effect of a lifestyle intervention on biomarkers in the randomized groups. In addition, treating the population as a single cohort, we estimated the association between change in weight and change in biomarkers. Results: Complete data were available at baseline and after 3 years in 151 participants. At 3 years, there was an adjusted mean reduction of 1·44 kg (95% confidence interval (95% CI): 0.18–2.71) in weight and 1.59 cm (95% CI: 0.08–3.09) in waist circumference in the intervention arm as compared with the control arm. There was no clear evidence of difference between the intervention and control arms in change of mean value of any biomarker. As a single cohort, every 1 kg weight reduction during follow-up was associated with a reduction in triglycerides (−1.3%, P=0.048), alanine aminotransferase (−2.5%, P=0.032), gamma-glutamyl transferase (−2.2%, P=0.040), leptin (−6.5%, P<0.0001), insulin (−3.7%, P=0.0005), fasting glucose (−0.8%, P=0.0071), 2-h glucose (−2.3%, P=0.0002) and Homeostatic Model Assessment of insulin resistance (HOMA-IR: −4.5%, P=0.0002). There was no evidence of associations with other lipid measures, tissue plasminogen activator, markers of inflammation or blood pressure. Conclusions: We demonstrate that modest weight decrease in SAs is associated with improvements in markers of total and ectopic fat as well as insulin resistance and glycaemia in South Asians at risk of diabetes. Future trials with more intensive weight change are needed to extend these findings

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

Combination of the W boson polarization measurements in top quark decays using ATLAS and CMS data at s = 8 TeV

Abstract: The combination of measurements of the W boson polarization in top quark decays performed by the ATLAS and CMS collaborations is presented. The measurements are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of about 20 fb−1 for each experiment. The measurements used events containing one lepton and having different jet multiplicities in the final state. The results are quoted as fractions of W bosons with longitudinal (F0), left-handed (FL), or right-handed (FR) polarizations. The resulting combined measurements of the polarization fractions are F0 = 0.693 ± 0.014 and FL = 0.315 ± 0.011. The fraction FR is calculated from the unitarity constraint to be FR = −0.008 ± 0.007. These results are in agreement with the standard model predictions at next-to-next-to-leading order in perturbative quantum chromodynamics and represent an improvement in precision of 25 (29)% for F0 (FL) with respect to the most precise single measurement. A limit on anomalous right-handed vector (VR), and left- and right-handed tensor (gL, gR) tWb couplings is set while fixing all others to their standard model values. The allowed regions are [−0.11, 0.16] for VR, [−0.08, 0.05] for gL, and [−0.04, 0.02] for gR, at 95% confidence level. Limits on the corresponding Wilson coefficients are also derived

Relationships between resistance to cross-linking agents and glutathione metabolism, aldehyde dehydrogenase isozymes and adenovirus replication in human tumour cell lines

In a panel of 10 human tumour cell lines with no prior exposure to drugs in vitro, resistance to cisplatin correlated with resistance to the nitrogen mustard derivatives Asta Z-7557 (mafosfamide, an activated form of cyclophosphamide), melphalan and chlorambucil. Simultaneous treatment with dl-buthionine-S,R-sulfoximine did not enhance the toxicity of cisplatin or Asta Z-7557, and no correlation was found between drug resistance and cellular levels of metallothioneins (as judged by sensitivity to cadmium chloride), glutathione (GSH), GSH reductase, GSH transferase, or γ-glutamyltranspeptidase. The two cell lines most resistant to Asta Z-7557 expressed aldehyde dehydrogenase cytosolic isozyme 1, found also in normal ovary, but not isozyme 3. Treatment of resistant cells with cisplatin or Asta Z-7557 inhibited cellular DNA synthesis and replication of adenovirus 5 to a lesser extent than in sensitive cells. The virus could be directly inactivated by both drugs prior to infection, subsequent replication being inhibited to the same extent in sensitive and resistant cells. In contrast to Asta Z-7557 and other DNA damaging agents, cisplatin was much more toxic to adenovirus (d 0.022-0.048 μM) than to cells (d 0.25-2.5 μM). The adenovirus 5 mutant Ad5ts125 having a G → A substitution was even more sensitive to cisplatin (d 7-8 nM) than wild type virus and another mutant. Cisplatin was detoxified less by sonicated resistant cells than sensitive cells, as judged by inactivation of Ad5ts125 added to the reaction mixture. It can be inferred that (i) the major differences in cellular resistance to cisplatin and Asta Z-7557 in the present material did not involve enhanced DNA repair or protection by metallothioneins or GSH, but were associated with the ability to continue cellular and viral DNA synthesis during treatment, (ii) resistance was not associated with less template damage, and (iii) the adenovirus genome may be a suitable probe for predicting tumour resistance to cisplatin and for elucidating the DNA sequence dependence of cisplatin toxicity

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

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