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BackgroundHydroxychloroquine has been shown to inhibit entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into epithelial cells in vitro, but clinical studies found no evidence of reduced mortality when treating patients with COVID-19. We aimed to evaluate the effectiveness of hydroxychloroquine for prevention of COVID-19 mortality, as opposed to treatment for the disease.MethodsWe did a prespecified observational, population-based cohort study using national primary care data and linked death registrations in the OpenSAFELY platform, which covers approximately 40% of the general population in England, UK. We included all adults aged 18 years and older registered with a general practice for 1 year or more on March 1, 2020. We used Cox regression to estimate the association between ongoing routine hydroxychloroquine use before the COVID-19 outbreak in England (considered as March 1, 2020) compared with non-users of hydroxychloroquine and risk of COVID-19 mortality among people with rheumatoid arthritis or systemic lupus erythematosus. Model adjustment was informed by a directed acyclic graph.FindingsBetween Sept 1, 2019, and March 1, 2020, of 194 637 people with rheumatoid arthritis or systemic lupus erythematosus, 30 569 (15·7%) received two or more prescriptions of hydroxychloroquine. Between March 1 and July 13, 2020, there were 547 COVID-19 deaths, 70 among hydroxychloroquine users. Estimated standardised cumulative COVID-19 mortality was 0·23% (95% CI 0·18 to 0·29) among users and 0·22% (0·20 to 0·25) among non-users; an absolute difference of 0·008% (−0·051 to 0·066). After accounting for age, sex, ethnicity, use of other immunosuppressive drugs, and geographical region, no association with COVID-19 mortality was observed (HR 1·03, 95% CI 0·80 to 1·33). We found no evidence of interactions with age or other immunosuppressive drugs. Quantitative bias analyses indicated that our observed associations were robust to missing information for additional biologic treatments for rheumatological disease. We observed similar associations with the negative control outcome of non-COVID-19 mortality.InterpretationWe found no evidence of a difference in COVID-19 mortality among people who received hydroxychloroquine for treatment of rheumatological disease before the COVID-19 outbreak in England. Therefore, completion of randomised trials investigating pre-exposure prophylactic use of hydroxychloroquine for prevention of severe outcomes from COVID-19 are warranted.FundingMedical Research Council.

BackgroundHydroxychloroquine has been shown to inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro, but early clinical studies found no benefit treating patients with coronavirus disease 2019 (COVID-19). We set out to evaluate the effectiveness of hydroxychloroquine for prevention, as opposed to treatment, of COVID-19 mortality.MethodsWe pre-specified and conducted an observational, population-based cohort study using national primary care data and linked death registrations in the OpenSAFELY platform, representing 40% of the general population in England. We used Cox regression to estimate the association between ongoing routine hydroxychloroquine use prior to the COVID-19 outbreak in England and risk of COVID-19 mortality among people with rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE). Model adjustment was informed by a directed acyclic graph.ResultsOf 194,637 patients with RA or SLE, 30,569 (15.7%) received ≥ 2 prescriptions of hydroxychloroquine in the six months prior to 1 March 2020. Between 1 March 2020 and 13 July 2020, there were 547 COVID-19 deaths, 70 among hydroxychloroquine users. Estimated standardised cumulative COVID-19 mortality was 0.23% (95% CI 0.18–0.29) among users and 0.22% (95% CI 0.20–0.25) among non-users; an absolute difference of 0.008% (95% CI –0.051-0.066). After accounting for age, sex, ethnicity, use of other immunuosuppressives, and geographic region, no association with COVID-19 mortality was observed (HR 1.03, 95% CI 0.80–1.33). We found no evidence of interactions with age or other immunosuppressives. Quantitative bias analyses indicated observed associations were robust to missing information regarding additional biologic treatments for rheumatological disease. We observed similar associations with the negative control outcome of non-COVID-19 mortality.ConclusionWe found no evidence of a difference in COVID-19 mortality among patients who received hydroxychloroquine for treatment of rheumatological disease prior to the COVID-19 outbreak in England.Research in contextEvidence before this studyPublished trials and observational studies to date have shown no evidence of benefit of hydroxychloroquine as a treatment for hospitalised patients who already have COVID-19. A separate question remains: whether routine ongoing use of hydroxychloroquine in people without COVID-19 protects against new infections or severe outcomes. We searched MEDLINE/PubMed for pharmacoepidemiological studies evaluating hydroxychloroquine for prevention of severe COVID-19 outcomes. The keywords “hydroxychloroquine AND (COVID OR coronavirus OR SARS-CoV-2) AND (prophyl* OR prevent*) AND (rate OR hazard OR odds OR risk)” were used and results were filtered to articles from the last year with abstracts available. 109 papers were identified for screening; none investigated pre-exposure prophylactic use of hydroxychloroquine for prevention of severe COVID-19 outcomes. Clinical trials of prophylactic use of hydroxychloroquine are ongoing; however, the largest trial does not expect to meet recruitment targets due to “…unjustified extrapolation and exaggerated safety concerns together with intense politicisation and negative publicity.” In the absence of reported clinical trials, evidence can be generated from real-world data to support the need for randomised clinical trials.Added value of this studyIn this cohort study representing 40% of the population of England, we investigated whether routine use of hydroxychloroquine prior to the COVID-19 outbreak prevented COVID-19 mortality. Using robust pharmacoepidemiological methods, we found no evidence to support a substantial benefit of hydroxychloroquine in preventing COVID-19 mortality. At the same time, we have shown no significant harm, and this generates the equipoise to justify continuing randomised trials. We have demonstrated in this study that it is feasible to address specific hypotheses about medicines in a rapid and transparent manner to inform interim clinical decision making and support the need for large-scale, randomised trial data.Implications of all the available evidenceThis is the first study to investigate the ongoing routine use of hydroxychloroquine and risk of COVID-19 mortality in a general population. While we found no evidence of any protective benefit, due to the observational nature of the study, residual confounding remains a possibility. Completion of trials for prevention of severe outcomes is warranted, but prior to the completion of these, we found no evidence to support the use of hydroxychloroquine for prevention of COVID-19 mortality.

Estimation of the direct genetic effect of an individuals’ own genotype on their phenotype, independent of any contaminating indirect parental genetic effects is becoming increasingly important. These conditional estimates are of interest in their own right, but are also useful for downstream analyses such as intergenerational Mendelian randomization. We compare several available multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate conditional direct and indirect genetic effects, while accounting for sample overlap. Using robustly associated birth weight variants and data from the UK Biobank, we contrasted the point estimates and their standard errors at each of the individual loci compared to those obtained using individual level genotype data, in addition to comparing the computational time, inflation of the test statistics and number of genome-wide significant SNPs identified by each of the methods. We show that Genomic SEM outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We subsequently applied Genomic SEM to fertility data in the UK Biobank and partitioned the genetic effect into female and male fertility in addition to a sibling specific effect. This analysis identified one novel locus for fertility and replicated seven previously identified loci. We also identified genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We therefore recommend Genomic SEM to be used to partition genetic effects across the genome into direct and indirect components.

BackgroundClose contact with children may provide cross-reactive immunity to SARs-CoV-2 due to more frequent prior coryzal infections from seasonal coronaviruses. Alternatively, close contact with children may increase risk of SARs-CoV-2 infection. We investigated whether risk of infection with SARs-CoV-2 and severe outcomes differed between adults living with and without children.MethodsWorking on behalf of NHS England, we conducted a population-based cohort study using primary care data and pseudonymously-linked hospital and intensive care admissions, and death records, from patients registered in general practices representing 40% of England. Using multivariable Cox regression, we calculated fully-adjusted hazard ratios (HR) of outcomes from 1st February-3rd August 2020 comparing adults living with and without children in the household.FindingsAmong 9,157,814 adults ≤65 years, living with children 0-11 years was not associated with increased risks of recorded SARS-CoV-2 infection, COVID-19 related hospital or ICU admission but was associated with reduced risk of COVID-19 death (HR 0.75, 95%CI 0.62-0.92). Living with children aged 12-18 years was associated with a small increased risk of recorded SARS-CoV-2 infection (HR 1.08, 95%CI 1.03-1.13), but not associated with other COVID-19 outcomes. Living with children of any age was also associated with lower risk of dying from non-COVID-19 causes. Among 2,567,671 adults >65 years there was no association between living with children and outcomes related to SARS-CoV-2. We observed no consistent changes in risk following school closure.InterpretationFor adults living with children there is no evidence of an increased risk of severe COVID-19 outcomes. These findings have implications for determining the benefit-harm balance of children attending school in the COVID-19 pandemic.FundingThis work was supported by the Medical Research Council MR/V015737/1.Research in contextEvidence before this studyWe searched MEDLINE on 19th October 2020 for population-based epidemiological studies comparing the risk of SARS-CoV-2 infection and COVID-19 disease in people living with and without children. We searched for articles published in 2020, with abstracts available, and terms “(children or parents or dependants) AND (COVID or SARS-CoV-2 or coronavirus) AND (rate or hazard or odds or risk), in the title, abstract or keywords. 244 papers were identified for screening but none were relevant. One additional study in preprint was identified on medRxiv and found a reduced risk of hospitalisation for COVID-19 and a positive SARS-CoV-2 infection among adult healthcare workers living with children.Added value of this studyThis is the first population-based study to investigate whether the risk of recorded SARS-CoV-2 infection and severe outcomes from COVID-19 differ between adults living in households with and without school-aged children during the UK pandemic. Our findings show that for adults living with children there is no evidence of an increased risk of severe COVID-19 outcomes although there may be a slightly increased risk of recorded SARS-CoV-2 infection for working-age adults living with children aged 12 to 18 years. Working-age adults living with children 0 to 11 years have a lower risk of death from COVID-19 compared to adults living without children, with the effect size being comparable to their lower risk of death from any cause. We observed no consistent changes in risk of recorded SARS-CoV-2 infection and severe outcomes from COVID-19 comparing periods before and after school closure.Implications of all the available evidenceOur results demonstrate no evidence of serious harms from COVID-19 to adults in close contact with children, compared to those living in households without children. This has implications for determining the benefit-harm balance of children attending school in the COVID-19 pandemic.

In recent years, the environmental problems associated with plastics have become a matter of global concern. Current responses seek to replace plastics with other materials, however it is not yet clear that these alternatives will deliver improved environmental outcomes. There remains an urgent need for more nuanced understandings of plastics, their role in society, and their environmental impacts. Drawing on social science perspectives that emphasise the co-evolution of materials and society, this paper outlines a socio-technical approach to plastics and social change. In this view, plastics are understood in terms of the networks and relations of which they are part – highlighting the limitations of both technological solutions and the blanket condemnation of particular materials. The analysis focuses specifically on plastic packaging, exploring the interplay of technological innovation and consumer practices to better account for processes of change. Our arguments are advanced through reference to three case studies: the launch of a ‘roast in the bag’ chicken by a food retailer, the switch to compostable packaging by a potato crisps (chips) brand, and the refilling of plastic bottles by a cosmetics company. Particular attention is paid to the relationships between commercial, environmental and regulatory concerns. To conclude, we consider implications of the approach presented here for transdisciplinary and policy debates about the problems associated with single-use plastics.

BackgroundCOVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England.MethodsWe conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size.ResultsA total of 17,510,002 adults were included in the study; 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09; black HR 1.08; 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07; black HR 1.68, 95%CI 1.61-1.76; mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52; black HR 3.07, 95%CI 2.61-3.61; mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38; black HR 1.55, 95%CI 1.38-1.75; mixed HR 1.40, 95%CI 1.12-1.76; other HR 1.25, 95%CI 1.05-1.49).We observed heterogeneity of associations after disaggregation into detailed ethnic groupings; Indian and African groups were at higher risk of all outcomes; Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19.ConclusionsWe found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.

Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide1. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53-1.65)); greater age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29-1.69) and 1.45 (1.32-1.58), respectively). We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far. More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly.

The Classical Twin Method (CTM) compares the similarity of monozygotic (MZ) twins with that of dizygotic (DZ) twins to make inferences about the relative importance of genes and environment in the etiology of individual differences. The design has been applied to thousands of traits across the biomedical, behavioral and social sciences and is arguably the most widely used natural experiment known to science. The fundamental assumption of the CTM is that trait relevant environmental covariation within MZ pairs is the same as that found within DZ pairs, so that zygosity differences in within-pair variance must be due to genetic factors uncontaminated by the environment. This equal environments assumption (EEA) has been, and still is hotly contested, and has been mentioned as a possible contributing factor to the missing heritability conundrum. In this manuscript, we introduce a new model for testing the EEA, which we call the Augmented Classical Twin Design which uses identity by descent (IBD) sharing between DZ twin pairs to estimate separate environmental variance components for MZ and DZ twin pairs, and provides a test of whether these are equal. We show through simulation that given large samples of DZ twin pairs, the model provides unbiased estimates of variance components and valid tests of the EEA under strong assumptions (e.g. no epistatic variance, IBD sharing in DZ twins estimated accurately etc.) which may not hold in reality. Sample sizes in excess of 50,000 DZ twin pairs with genome-wide genetic data are likely to be required in order to detect substantial violations of the EEA with moderate power. Consequently, we recommend that the Augmented Classical Twin Design only be applied to datasets with very large numbers of DZ twin pairs ( 50,000 DZ twin pairs), and given the strong assumptions relating to the absence of epistatic variance, appropriate caution be exercised regarding interpretation of the results.

ImportanceThere has been speculation that non-steroidal anti-inflammatory drugs (NSAIDs) may negatively affect coronavirus disease 2019 (COVID-19) outcomes, yet clinical evidence is limited.ObjectiveTo assess the association between NSAID use and deaths from COVID-19 using OpenSAFELY, a secure analytical platform.DesignTwo cohort studies (1stMarch-14thJune 2020).SettingWorking on behalf of NHS England, we used routine clinical data from >17 million patients in England linked to death data from the Office for National Statistics.ParticipantsStudy 1: General population (people with an NSAID prescription in the last three years). Study 2: people with rheumatoid arthritis/osteoarthritis.ExposuresCurrent NSAID prescription within the 4 months before 1stMarch 2020.Main Outcome and MeasureWe used Cox regression to estimate hazard ratios (HRs) for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, adjusting for age, sex, comorbidities and other medications.ResultsIn Study 1, we included 535,519 current NSAID users and 1,924,095 non-users in the general population. The crude HR for current use was 1.25 (95% CI, 1.07–1.46), versus non-use. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR, 0.95, 95% CI, 0.80–1.13) in the fully adjusted model.In Study 2, we included 1,711,052 people with rheumatoid arthritis/osteoarthritis, of whom 175,631 (10%) were current NSAID users. The crude HR for current use was 0.43 (95% CI, 0.36–0.52), versus non-use. In the fully adjusted model, we observed a lower risk of COVID-19 related death (HR, 0.78, 95% CI, 0.65–0.94) associated with current use of NSAID versus non-use.Conclusion and RelevanceWe found no evidence of a harmful effect of NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about therapeutic use of NSAIDs.

BackgroundIt is unclear whether HIV infection is associated with risk of COVID-19 death. We aimed to investigate this in a large-scale population-based study in England.MethodsWorking on behalf of NHS England, we used the OpenSAFELY platform to analyse routinely collected electronic primary care data linked to national death registrations. People with a primary care record for HIV infection were compared to people without HIV. COVID-19 death was defined by ICD-10 codes U07.1 or U07.2 anywhere on the death certificate. Cox regression models were used to estimate the association between HIV infection and COVID-19 death, initially adjusted for age and sex, then adding adjustment for index of multiple deprivation and ethnicity, and finally for a broad range of comorbidities. Interaction terms were added to assess effect modification by age, sex, ethnicity, comorbidities and calendar time.Results17.3 million adults were included, of whom 27,480 (0.16%) had HIV recorded. People living with HIV were more likely to be male, of black ethnicity, and from a more deprived geographical area than the general population. There were 14,882 COVID-19 deaths during the study period, with 25 among people with HIV. People living with HIV had nearly three-fold higher risk of COVID-19 death than those without HIV after adjusting for age and sex (HR=2.90, 95% CI 1.96-4.30). The association was attenuated but risk remained substantially raised, after adjustment for deprivation and ethnicity (adjusted HR=2.52, 1.70-3.73) and further adjustment for comorbidities (HR=2.30, 1.55-3.41). There was some evidence that the association was larger among people of black ethnicity (HR = 3.80, 2.15-6.74, compared to 1.64, 0.92-2.90 in non-black individuals, p-interaction=0.045)InterpretationHIV infection was associated with a markedly raised risk of COVID-19 death in a country with high levels of antiretroviral therapy coverage and viral suppression; the association was larger in people of black ethnicity.

Disaggregation and estimation of genetic effects from offspring and parents has long been of interest to statistical geneticists. Recently, technical and methodological advances have made the genome-wide and loci-specific estimation of direct offspring and parental genetic nurture effects more possible. However, unbiased estimation using these methods requires datasets where both parents and at least one child have been genotyped, which are relatively scarce. Our group has recently developed a method and accompanying software (IMPISH; [Hwang et al., 2020][1]) which is able to impute missing parental genotypes from observed data on sibships and estimate their effects on an offspring phenotype conditional on the effects of genetic transmission. However, this method is unable to disentangle maternal and paternal effects, which may differ in magnitude and direction. Here, we introduce an extension to the original IMPISH routine which takes advantage of all available nuclear families to impute parent-specific missing genotypes and obtain asymptotically unbiased estimates of genetic effects on offspring phenotypes. We apply this this method to data from related individuals in the UK Biobank, showing concordance with previous estimates of maternal genetic effects on offspring birthweight. We also conduct the first GWAS jointly estimating offspring-, maternal-, and paternal-specific genetic effects on body mass index. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-9

Disaggregation and estimation of genetic effects from offspring and parents has long been of interest to statistical geneticists. Recently, technical and methodological advances have made the genome-wide and loci-specific estimation of direct offspring and parental genetic nurture effects more possible. However, unbiased estimation using these methods requires datasets where both parents and at least one child have been genotyped, which are relatively scarce. Our group has recently developed a method and accompanying software (IMPISH; Hwang et al. in PLoS Genet 16:e1009154, 2020) which is able to impute missing parental genotypes from observed data on sibships and estimate their effects on an offspring phenotype conditional on the effects of genetic transmission. However, this method is unable to disentangle maternal and paternal effects, which may differ in magnitude and direction. Here, we introduce an extension to the original IMPISH routine which takes advantage of all available nuclear families to impute parent-specific missing genotypes and obtain asymptotically unbiased estimates of genetic effects on offspring phenotypes. We apply this this method to data from related individuals in the UK Biobank, showing concordance with previous estimates of maternal genetic effects on offspring birthweight. We also conduct the first GWAS jointly estimating offspring-, maternal-, and paternal-specific genetic effects on body-mass index.

Indirect genetic effects from relatives may result in misleading quantifications of heritability, but can also be of interest in their own right. In this paper we propose Trio-GCTA, a model for separating direct and indirect genetic effects when genome-wide single nucleotide polymorphism data have been collected from parent-offspring trios. The model is applicable to phenotypes obtained from any of the family members. We discuss appropriate parameter interpretations and apply the method to three exemplar phenotypes: offspring birth weight, maternal relationship satisfaction, and paternal body-mass index, using real data from the Norwegian Mother, Father and Child Cohort Study (MoBa).

BackgroundEarly descriptions of the coronavirus outbreak showed a lower prevalence of asthma and COPD than was expected for people diagnosed with COVID-19, leading to speculation that inhaled corticosteroids (ICS) may protect against infection with SARS-CoV-2, and development of serious sequelae. We evaluated the association between ICS and COVID-19 related death using linked electronic health records in the UK.MethodsWe conducted cohort studies on two groups of people (COPD and asthma) using the OpenSAFELY platform to analyse data from primary care practices linked to national death registrations. People receiving an ICS were compared to those receiving alternative respiratory medications. Our primary outcome was COVID-19 related death.FindingsWe identified 148,588 people with COPD and 817,973 people with asthma receiving relevant respiratory medications in the four months prior to 01 March 2020. People with COPD receiving ICS were at a greater risk of COVID-19 related death compared to those receiving a long-acting beta agonist (LABA) and a long-acting muscarinic antagonist (LAMA) (adjusted HR = 1.38, 95% CI = 1.08 – 1.75). People with asthma receiving high dose ICS were at an increased risk of death compared to those receiving a short-acting beta agonist (SABA) only (adjusted HR = 1.52, 95%CI = 1.08 – 2.14); the adjusted HR for those receiving low-medium dose ICS was 1.10 (95% CI = 0.82 – 1.49). Quantitative bias analyses indicated that an unmeasured confounder of only moderate strength of association with exposure and outcome could explain the observed associations in both populations.InterpretationThese results do not support a major role of ICS in protecting against COVID-19 related deaths. Observed increased risks of COVID-19 related death among people with COPD and asthma receiving ICS can be plausibly explained by unmeasured confounding due to disease severity.FundingThis work was supported by the Medical Research Council MR/V015737/1.

Aims/HypothesisHigher maternal BMI during pregnancy results in higher offspring birth weight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity coupled with a favourable metabolic profile, in a Mendelian Randomisation (MR) study comparing the effect of maternal “metabolically favourable adiposity” on offspring birth weight with the effect of maternal general adiposity (as indexed by BMI).MethodsTo test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birth weight, we performed two sample MR. We used variants identified in large genetic association studies as associated with either higher adiposity and a favourable metabolic profile, or higher BMI (N = 442,278 and N = 322,154 for metabolically favourable adiposity and BMI, respectively). We then used data from the same variants in a large genetic study of maternal genotype and offspring birth weight independent of fetal genetic effects (N = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total N = 9,323 mother-child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birth weight and cord-blood biomarkers.ResultsHigher maternal adiposity with a favourable metabolic profile was associated with lower offspring birth weight (−94 (95% CI: −150 to −38) grams per 1 SD (6.5%) higher maternal metabolically favourable adiposity). By contrast, higher maternal BMI was associated with higher offspring birth weight (35 (95% CI: 16 to 53) grams per 1 SD (4 kg/m2) higher maternal BMI). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures and their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels whilst maternal BMI increases them.The effects on neonatal anthropometric traits were consistent with the overall effect on birth weight, but the smaller sample sizes for these analyses meant the effects were imprecisely estimated. We also found evidence to suggest that maternal metabolically favourable adiposity decreases cord-blood leptin whilst maternal BMI increases it.Conclusions/InterpretationOur results show that higher adiposity in mothers does not necessarily lead to higher offspring birth weight. Higher maternal adiposity can lead to lower offspring birth weight if accompanied by a favourable metabolic profile.Research in ContextWhat is already known about this subject?Studies in non-pregnant people with obesity suggest many people can have a “metabolically healthy” form of obesity, but effects in pregnancy and on offspring are not known.Multiple lines of evidence show that higher maternal BMI is causally associated with higher offspring birth weight, and that this may be mediated by the fetal insulin response to higher maternal gestational glucose.Recently, genetic variants have been identified, where one allele is associated with higher adiposity but lower risk of type II diabetes and favourable metabolic profile, including lower insulin and glucose levels, so called “metabolically favourable adiposity”; the mechanism is thought to be due to greater subcutaneous adipose storage capacity that leads to higher insulin sensitivity.What is the key question?What is the effect of maternal metabolically favourable adiposity on birth weight, and how does it compare with the effect of maternal BMI on birth weight?What are the new findings?Higher maternal adiposity can lead to lower, not higher birth weight, if it is also associated with a metabolically favourable profile; this contrasts with the effect of higher maternal general adiposity (BMI), on higher birth weight.Higher maternal metabolically favourable adiposity causes lower maternal fasting plasma glucose levels, most likely due to higher insulin sensitivity; in contrast higher maternal general adiposity leads to higher maternal fasting plasma glucose levels, most likely due to lower insulin sensitivity.How might this impact on clinical practice in the foreseeable future?Identifying ways of stratifying overweight and obese pregnant women into those with and without metabolically favourable adiposity could allow for targeted management to obtain healthy fetal growth and birth weight.

Background: Lung function is highly heritable and differs between the sexes throughout life. However, little is known about sex-differential genetic effects on lung function. We aimed to conduct the first genome-wide genotype-by-sex interaction study on lung function to identify genetic effects that differ between males and females. Methods: We tested for interactions between 7,745,864 variants and sex on spirometry-based measures of lung function in UK Biobank (N=303,612), and sought replication in 75,696 independent individuals from the SpiroMeta consortium. Results: Five independent single-nucleotide polymorphisms (SNPs) showed genome-wide significant (P

Indirect genetic effects from relatives may result in misleading quantifications of heritability, but can also be of interest in their own right. In this paper we propose Trio-GCTA, a model for separating direct and indirect genetic effects when genome-wide single nucleotide polymorphism data have been collected from parent-offspring trios. The model is applicable to phenotypes obtained from any of the family members. We discuss appropriate parameter interpretations and apply the method to four exemplar phenotypes; offspring birth weight, offspring temperament, maternal relationship satisfaction, and paternal body-mass index, using real data from the Norwegian Mother, Father and Child Cohort Study (MoBa).

Unlike other commonly studied complex traits, pregnancy phenotypes like gestational duration and fetal size measurements at birth are conjointly determined by maternal and fetal genomes. Current approaches of heritability estimation based upon an individual’s genotype information are limited in addressing confounding by shared alleles between mother and fetus. Here, we propose a novel approach of treating the mother-child pairs as a single analytical unit with three haplotypes - maternal transmitted (m1), maternal non-transmitted (m2) and paternal transmitted (p1). Using our haplotype-based approach, we estimate the SNP heritability (ĥ2) of gestational duration and gestational duration adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance in gestational duration is mainly attributable to m1 and m2 ( and ). In contrast, variance in fetal size measurements at birth are mainly attributable to m1 and p1. Variance in birth weight is attributable to both m1 and p1 ( and ). However, variance in birth length ( and ) and head circumference ( and ) are largely attributable to m1. Our results suggest that gestational duration is primarily determined by the maternal genome whereas fetal size measurements at birth are primarily determined by fetal genome. In addition, the difference between and suggests a greater contribution of the maternal transmitted haplotype than the paternal transmitted haplotype to birth length and head circumference. Our haplotype-based GCTA approach (H-GCTA) resolves explicit contributions of maternal and fetal genomes to SNP heritability of pregnancy phenotypes.

Fat distribution is an independent cardiometabolic risk factor. However, its molecular and cellular underpinnings remain obscure. Here we demonstrate that two independent GWAS signals at RSPO3, which are associated with increased body mass index-adjusted waist-to-hip ratio, act to specifically increase RSPO3 expression in subcutaneous adipocytes. These variants are also associated with reduced lower-body fat, enlarged gluteal adipocytes and insulin resistance. Based on human cellular studies RSPO3 may limit gluteofemoral adipose tissue (AT) expansion by suppressing adipogenesis and increasing gluteal adipocyte susceptibility to apoptosis. RSPO3 may also promote upper-body fat distribution by stimulating abdominal adipose progenitor (AP) proliferation. The distinct biological responses elicited by RSPO3 in abdominal versus gluteal APs in vitro are associated with differential changes in WNT signalling. Zebrafish carrying a nonsense rspo3 mutation display altered fat distribution. Our study identifies RSPO3 as an important determinant of peripheral AT storage capacity., Genetic variants at the RSPO3 locus are associated with waist-to-hip ratio (adjusted for BMI). Here, Loh et al. describe two independent RSPO3 signals that associate with body fat distribution, perform fine-mapping and explore the function of RSPO3 in human adipocyte biology and body fat distribution in zebrafish

BackgroundEstablishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary.Data sourcesPrimary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform.Population17,425,445 adults.Time period1st Feb 2020 to 25th April 2020.Primary outcomeDeath in hospital among people with confirmed COVID-19.MethodsCohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings.ResultsThere were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82).ConclusionsWe have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients’ records; we will update and extend these results regularly.

Concerns about the climate crisis and the escalating pace of global consumption are accelerating the pressure on governments to moderate public demand for resources like water, food and energy. Notwithstanding their increasing sophistication, standard behavioural change approaches continue to be criticised for a narrow understanding of what shapes behaviour. One alternative theoretical position comes from practice theories, which draw on interpretive and relational understandings to focus on practices rather than people's behaviour, and hence highlight the complex and distributed set of factors shaping resource use. While practice theories have gained considerable interest from policy institutions within and beyond the UK they so far have had limited impact upon policy. It has even been argued that there are insurmountable challenges in reconciling the ontological commitments of practice theories with the realities of policy processes. This article advances academic and policy debates about the practical implications of practice theories. It works with evidence from transdisciplinary research intended to establish whether and how key distinctive insights from social practice research can usefully be brought to bear on policy. We pursued this through co-productive research with four key UK national policy partners, focusing on effective communication of social practice research evidence on agreed issues. A key outcome of collaboratively negotiating challenging social theory to usefully influence policy processes is the ‘Change Points’ approach, which our partners identified as offering new thinking on initiatives promoting reductions in people's use and disposal of resources. The Change Points approach was developed to enable policy processes to confront the complexities of everyday action, transforming both how problems are framed and how practical initiatives for effecting change are developed. We discuss the case of food waste reduction in order to demonstrate the potential of Change Points to reframe behaviour change policy. We end the paper by addressing the potential and limitations of informing policy with insights from practice theories based upon the successes as well as the challenges we have met. This discussion has broader implications beyond practice theories to other fields of social theory, and to debates on the relations between academic research and policy more broadly. We argue that, through a co-productive approach with policy professionals, and so engagement with the practices of policy making, it is possible to provide a partial and pragmatic but nevertheless effective translation of key distinctive insights from practice theories and related research, to reframe policy problems and hence to identify spaces for effecting change for sustainability.

The Eocene-Oligocene transition (EOT) is one of the most dramatic climate shifts of the Cenozoic with severe consequences for reef ecosystems. The onset of continental Antarctic glaciation is associated with widespread environmental change, resulting in a global peak in biotic turnover. Whilst numerous studies of the biotic response to the changes at the EOT have been carried out, most high-resolution studies consist of open ocean records of marine plankton and predominantly single groups of organisms. However, this is not representative of the ocean system as a whole and does not provide a holistic view of mechanism of restructuring of the marine ecosystems. The shelf seas and reefs are some of the most diverse and fundamentally important ecosystems of the oceans. Long-term diversity loss across the EOT has been shown in several macrofossil studies, but mainly at low resolution, and recovery is not well understood. Many shelf species are ecosystem engineers whose loss and recovery have profound implications for the entire ecosystem. Understanding these interactions will provide insights into shallow marine ecosystems and their response to major climate perturbations.The Tanzanian Drilling Project EOT record (TDP 11, 12, 17) is recognised globally for its completeness and exceptionally preserved calcareous microfossils. It is most importantly, though, a rare record of both shallow water organisms and open ocean plankton. The latter are fundamentally important for reconstructions of the environment and a globally calibrated timescale. Here we draw together a unique dataset of high-resolution mollusc, Dasycladaceae, bryozoan, larger benthic foraminifers, coral, smaller benthic foraminifera, trace element and isotope records from the EOT. The response and recovery of these species is compared with known, modern physiology of each group to provide a complete picture of the shallow marine ecosystem response.Following rapid extinctions within the larger foraminifera during the transition, molluscs, Dasycladaceae and bryozoans all show increases in abundance, indicating a major shift in shelf ecosystem composition. These assemblage changes are coincident with a period of more positive values in d13C of both benthic and planktonic foraminifera and changes in trace element values. Comparison with the open ocean record of planktonic foraminiferal, pteropod, and nannofossils confirm these assemblage changes are a biological, rather than sedimentological response and additionally support a that a transition to more eutrophic conditions took place. an environmental framework of traditional and novel geochemistry, indicate that increased nutrient fluxes played a pivotal role in restructuring shelf ecosystem dynamics and therefore offers new insight into mechanisms of reorganisation under ecosystem loss and environmental change.

Na is incorporated into marine carbonate minerals and was recently proposed as a proxy for paleo-salinity. However we demonstrated that Na/Ca ratio in foraminiferal shells (Na/Cashell) is actually a novel proxy for past ocean Ca concentrations (Casw) in benthic foraminifera (Hauzer et al., 2018). In the present study, we determined the extent to which foraminiferal Na/Ca (and other elements) change with salinity for the high-Mg large benthic foraminifer Operculina ammonoides. This laboratory culture experiment was conducted under four different salinities 32.9, 36.1, 40.65 and 43.0 PSU, at a constant temperature of 25 °C and pH of ~8.17. O. ammonoides specimens were labeled with the fluorescent dye Calcein (40 µM) for five days prior to the experiment. Experimental seawater was prepared from filtered Gulf of Eilat seawater (40.65 PSU) and the salinity was modified by the addition of deionized water or by the evaporation to the desired value at room temperature. All experimental seawater were spiked with 135Ba in order to unambiguously determine newly grown CaCO3 during spatially-resolved analysis of the shell. Six specimens of each treatment were selected according to the presence of non-fluorescent chambers past the Calcein mark. The CaCO3 shells were analyzed using the LA-ICPMS. Water chemistry was analyzed using ICP-OES and ICP-MS. Experimental foraminifera added 90-160% of their original weight, based on alkalinity-depletion measurements during the experiment. The elemental ratios of Na, Mg and Li to Ca in O. ammonoides shells increased linearly with increasing seawater salinity. In contrast, Sr/Cashell showed no resolvable change with salinity. Since Na/Cashell does correlate with salinity, it appears that it could be used as a paleosalinity proxy. However, when variations of Na/Cashell due to salinity are compared to variations due to Casw, it is clear that salinity has a minor effect compared to the Ca concentrations. Thus, when reconstructing paleosalinity, Na/Cashell will produce accurate results only for samples that are within the residence time of Casw (~1My). Furthermore, regional and global changes in ocean salinity over geological time can only slightly affect the use of Na/Cashell as a proxy for past changes in Casw.Hauzer, H., Evans, D., Müller, W., Rosenthal, Y., & Erez, J. (2018). Calibration of Na partitioning in the calcitic foraminifer Operculina ammonoides under variable Ca concentration: Toward reconstructing past seawater composition. Earth and Planetary Science Letters, 497, 80-91.

Glaciers are important indicators of climate change and observations worldwide document increasing rates of mountain glacier recession. Here we present ~200 years of change in mountain glacier extent in northern Troms and western Finnmark. This was achieved through: (1) mapping recent (post-1980s) changes in ice extent from remotely sensed data and (2) lichenometric dating and mapping of major moraine systems within a sub-set of the main study area (the Rotsund Valley). Lichenometric dating reveals that the Little Ice Age (LIA) maximum occurred as early as AD 1814 (±41 years), which is before the early-20th century LIA maximum proposed on the nearby Lyngen Peninsula, but younger than the LIA maximum limits in southern and central Norway (ca. AD 1740-50). Between LIA maximum and AD 1989, the reconstructed glaciers (n = 15) shrank by 3.9 km2 (39%), with those that shrank by >50% fronted by proglacial lakes. Between AD 1989 and 2018, the total area of glaciers within the study area (n = 219 in AD 1989) shrank by ~35 km2. Very small glaciers (2 in AD 1989) show the highest relative rates of shrinkage, and 90% of mapped glaciers within the study area are 2 as of AD 2018.

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring., Author summary Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. Estimating indirect parental genetic effects on offspring outcomes at the genotype level has been challenging because it requires large-scale, individual level genotypes from both parents and their offspring, and there is a paucity of cohorts around the world with this information. Here we present a new approach to estimate indirect parental genetic effects without the requirement of physically genotyped parents. Our method creates virtual parental genotypes based on the genotypes of offspring pairs, and then uses these virtual genotypes in downstream genetic association analyses. We developed a software package “IMPISH” that allows users to impute virtual parental genotypes in their own genome-wide datasets and then use these in downstream genome-wide association analyses, as well a series of power calculators to estimate the power to detect indirect parental genetic effects on offspring phenotypes. We apply our method to educational attainment data from the UK Biobank and show that indirect parental genetic effects are related to offspring educational attainment even after correcting for offspring genotype at the same loci.

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset diseases, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half-Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.

Lower maternal serum vitamin B12 (B12) and folate levels have been associated with lower offspring birthweight in observational studies. The aim of this study was to investigate whether this relationship is causal.We performed two-sample Mendelian Randomization (MR) using summary data on associations between genotype-B12 (10 genetic variants) or genotype-folate (4 genetic variants) levels from a genome-wide association study of 45,576 individuals (sample 1) and maternal-specific genetic effects on offspring birthweight from the latest EGG consortium meta-analysis with 297,356 individuals reporting their own birthweight and 210,248 women reporting their offspring’s birthweight (sample 2). To investigate the effect of offspring’s own B12 or folate levels on their own birthweight, we performed two-sample MR using the fetal-specific genetic effects from the latest EGG consortium meta-analysis. We used the inverse variance weighted method, and sensitivity analyses to account for pleiotropy, in addition to sensitivity analyses excluding a potentially pleiotropic variant in theFUT2gene for B12.We did not find evidence for a causal effect of maternal B12 on offspring birthweight, nor evidence for an effect of offspring B12 on their own birthweight using the fetal-specific genetic effect. The results were consistent across the different methods and in sensitivity analyses excluding theFUT2variant. We found a positive effect of maternal folate on offspring birthweight (0.146 [0.065, 0.227], which corresponds to an increase in birthweight of 71g per 1SD higher folate). We found some evidence for a small inverse effect of fetal folate on their own birthweight (−0.051 [−0.100, −0.003]).In conclusion, our results are consistent with evidence from randomized controlled trials that increased maternal folate levels increase offspring birthweight. We did not find evidence for a causal effect of B12 on offspring birthweight, suggesting previous observational studies may have been due to confounding.

There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.

Introduction Hearing loss has been identified as the potentially largest modifiable risk factor for Alzheimer's disease (AD), estimated to account for a similar increase in AD risk as the apolipoprotein E (APOE) gene. Methods We investigated the genetic relationship between hearing loss and AD, and sought evidence for a causal relationship. Results We found a significant genetic overlap between hearing impairment and AD and a polygenic risk score for AD was able to significantly predict hearing loss in an independent cohort. Additionally, regions of the genome involved in inflammation were identified to be shared between hearing difficulty and AD. However, causality tests found no significant evidence of a causal relationship between these traits in either direction. Discussion Overall, these results show that the relationship between hearing difficulty and AD may, in part, be due to shared genes and immune response pathways between the traits. However, currently available data do not support a causal relationship.

It is unclear to what extent parental influences on the development of internalizing problems in offspring are explained by indirect genetic effects, reflected in the environment provided by the parent, in addition to the genes transmitted from parent to child. In this study, these effects were investigated using two innovative methods in a large birth cohort. Using maternal‐effects genome complex trait analysis (M‐GCTA), the effects of offspring genotype, maternal or paternal genotypes, and their covariance on offspring internalizing problems were estimated in 3,801 mother–father–child genotyped trios. Next, estimated genetic correlations within pedigree data, including 10,688 children, were used to estimate additive genetic effects, maternal and paternal genetic effects, and a shared family effect using linear mixed effects modeling. There were no significant maternal or paternal genetic effects on offspring anxiety or depressive symptoms at age 8, beyond the effects transmitted via the genetic pathway between parents and children. However, indirect maternal genetic effects explained a small, but nonsignificant, proportion of variance in childhood depressive symptoms in both the M‐GCTA (~4%) and pedigree (~8%) analyses. Our results suggest that parental effects on offspring internalizing problems are predominantly due to transmitted genetic variants, rather than the indirect effect of parental genes via the environment.

There is a robust observational relationship between lower birthweight and higher risk of cardiometabolic disease in later life. The Developmental Origins of Health and Disease (DOHaD) hypothesis posits that adverse environmental factors in utero increase future risk of cardiometabolic disease. Here, we explore if a genetic risk score (GRS) of maternal SNPs associated with offspring birthweight is also associated with offspring cardiometabolic risk factors, after controlling for offspring GRS, in up to 26,057 mother–offspring pairs (and 19,792 father–offspring pairs) from the Nord-Trøndelag Health (HUNT) Study. We find little evidence for a maternal (or paternal) genetic effect of birthweight associated variants on offspring cardiometabolic risk factors after adjusting for offspring GRS. In contrast, offspring GRS is strongly related to many cardiometabolic risk factors, even after conditioning on maternal GRS. Our results suggest that the maternal intrauterine environment, as proxied by maternal SNPs that influence offspring birthweight, is unlikely to be a major determinant of adverse cardiometabolic outcomes in population based samples of individuals., Observationally, lower birthweight is a risk factor for cardiometabolic disease. Using Mendelian Randomization, the authors investigate whether maternal genetic factors that lower offspring birthweight also increase offspring cardiometabolic risk and show that the observational correlation is unlikely to be due to the intrauterine environment.

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention., Vincenzo Forgetta and colleagues investigate possible utility of genetic information in assessing fracture risk., Author summary Why was this study done? Osteoporosis screening identifies only a small proportion of the screened population to be eligible for intervention. The prediction of heritable risk factors using polygenic risk scores could decrease the number of screened individuals by reassuring those with low genetic risk. We investigated whether the genetic prediction of heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—could be incorporated into an established screening guideline to identify individuals at low risk for osteoporosis. What did the researchers do and find? Using UK Biobank, we developed a polygenic risk score (gSOS) consisting of 21,717 genetic variants that was strongly correlated with SOS (r2 = 23.2%). Using the National Osteoporosis Guideline Group clinical assessment guidelines in 5 validation cohorts, we estimate that reassuring individuals with a high gSOS, rather than doing further assessments, could reduce the number of clinical-risk-factor-based Fracture Risk Assessment Tool (FRAX) tests and bone-density-measurement-based FRAX tests by 37% and 41%, respectively, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention. What do these findings mean? We show that genetic pre-screening could reduce the number of screening tests needed to identify individuals at risk of osteoporotic fractures. Therefore, the potential exists to improve the efficiency of osteoporosis screening programs without large losses in sensitivity or specificity to identify individuals who should receive an intervention. Further translational studies are needed to test the clinical applications of this polygenic risk score; however, our work shows how such scores could be tested in the clinic.

The nexus of water-energy-food (WEF) is as apparent at the household scale as it is anywhere else. We introduce the ‘Nexus at Home’ as a starting point for exploring the dynamics of WEF resource use and household sustainability. Drawing on two research projects we focus specifically on domestic kitchens as a site where practices of cooking, eating, cleaning, and disposing of waste come together. Whilst these practices have long been targets for policy intervention, existing approaches draw on a limited range of perspectives from the social sciences. Reflecting on our work with four non-academic partners (Defra, BEIS, FSA, Waterwise), we consider how social practice and geographies of household sustainability research might be combined with the dictum of ‘nexus thinking’ to re-imagine the framing of policy and intervention to reduce the resource intensity of everyday life. Synthesising existing ‘home practices’ literature in the context of the ‘live’ policy problems raised by our partners, we seek to provide clear guidance for intervening in kitchen practices. We draw on one topic which has not yet been the subject of social practices research: fats, oils and grease (FOG) going down the kitchen plughole and contributing to widespread sewer blockages. In doing so we document the sequence of interrelated food provisioning activities through which WEF is put to use in domestic kitchens and contributes to FOG blockages in sewers. We reflect upon the multiple ways these practices are shaped by the rhythms of daily life, dynamics within the home, wider cultural conventions, and infrastructures. This paper contributes to the nascent transdisciplinary research agenda of translating home practices research into wider conceptualisations of ‘intervention’, with a specific orientation towards academic and non-academic stakeholders who are interested in influencing systems of sustainable consumption and production within, and across, the water-energy-food sectors.

Objective Bone turnover, which regulates bone mass, may exert metabolic consequences, particularly on markers of glucose metabolism and adiposity. To better understand these relationships, we examined cross-sectional associations between bone turnover markers (BTMs) and metabolic traits in a population with high bone mass (HBM, BMD Z-score >=+3.2). Design beta-C-terminal telopeptide of type-I collagen (beta-CTX), procollagen type-1 amino-terminal propeptide (P1NP) and osteocalcin were assessed by electrochemiluminescence immunoassays. Metabolic traits, including lipids and glycolysis-related metabolites, were measured using nuclear magnetic resonance spectroscopy. Associations of BTMs with metabolic traits were assessed using generalized estimating equation linear regression, accounting for within-family correlation, adjusting for potential confounders (age, sex, height, weight, menopause, bisphosphonate and oral glucocorticoid use). Results A total of 198 adults with HBM had complete data, mean [SD] age 61.6 [13.7] years; 77% were female. Of 23 summary metabolic traits, citrate was positively related to all BTMs: adjusted beta(beta-CTX) = 0.050 (95% CI 0.024, 0.076), P = 1.71 x 10(-4), beta(osteocalcin) = 6.54 x 10(-4) (1.87 x 10(-4), 0.001), P = .006 and beta(P1NP) = 2.40 x 10(-4) (6.49 x 10(-5), 4.14 x 10(-4)), P = .007 (beta = increase in citrate (mmol/L) per 1 mu g/L BTM increase). Inverse relationships of beta-CTX (beta = -0.276 [-0.434, -0.118], P = 6.03 x 10(-4)) and osteocalcin (-0.004 [-0.007, -0.001], P = .020) with triglycerides were also identified. We explored the generalizability of these associations in 3664 perimenopausal women (age 47.9 [4.4] years) from a UK family cohort. We confirmed a positive, albeit lower magnitude, association between beta-CTX and citrate (adjusted beta(women) = 0.020 [0.013, 0.026], P = 1.95 x 10(-9)) and an inverse association of similar magnitude between beta-CTX and triglycerides (beta = -0.354 [-0.471, -0.237], P = 3.03 x 10(-9)). Conclusions Bone resorption is positively related to circulating citrate and inversely related to triglycerides. Further studies are justified to determine whether plasma citrate or triglyceride concentrations are altered by factors known to modulate bone resorption, such as bisphosphonates.

Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the world’s largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5×10−8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% – 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% – 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 – 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

Compositional zoning is observed rarely in chrome-spinel grains from slowly-cooled layered intrusions because diffusion of cations continues within the spinel to low temperatures. However, in certain circumstances, such gradational zoning of both divalent and trivalent cations is observed and may be useful in deciphering the thermal history of the host intrusions. The accessory chrome-spinels of the Kabanga mafic-ultramafic chonolith intrusions of the Kibaran igneous event in north western Tanzania are notable because they have preserved gradational compositional zoning. This zoning is demonstrated to predate and be independent of later hydrous alteration of the silicate assemblage. At Kabanga, most chrome-spinel grains within olivine-rich cumulate rocks are gradationally and cryptically zoned from Fe2+-Cr3+ rich cores to more Mg2+-Al3+ rich rims (normal zoning). A few grains are zoned from Mg2+-Al3+ rich cores to more Fe2+-Cr3+ rich rims (reverse zoned). The zoning of divalent cations is proportional to that of trivalent cations with Mg2+ following Al3+ and Fe2+ following Cr3+ from core to rim. The zoning of trivalent and tetravalent cations is interpreted to be caused by either new growth from an evolving melt or peritectic reactions between evolved or contaminated melt and adjacent Al-Cr-bearing ferromagnesian minerals, which is preserved by relatively rapid initial cooling in the small chonolith intrusions. Divalent cation zoning is controlled by sub-solidus exchange of Fe2+ and Mg with adjacent ferromagnesian minerals and continues to lower temperatures, indicated to be 580 to 630°C by the spinel-olivine geothermometer. Preservation of such zoning is more likely in the smaller chonolith intrusions that typically host magmatic nickel-copper sulfide deposits and can be used as an exploration indicator when interpreting chromite compositions in regional heavy indicator mineral surveys.

Hair color is one of the most recognizable visual traits in European populations and is under strong genetic control. Here we report the results of a genome-wide association study meta-analysis of almost 300,000 participants of European descent. We identified 123 autosomal and one X-chromosome loci significantly associated with hair color; all but 13 are novel. Collectively, single-nucleotide polymorphisms associated with hair color within these loci explain 34.6% of red hair, 24.8% of blond hair, and 26.1% of black hair heritability in the study populations. These results confirm the polygenic nature of complex phenotypes and improve our understanding of melanin pigment metabolism in humans.

© 2018, Hebrew University of Jerusalem. We present an example of two countable ω-categorical structures, one of which has a finite relational language, whose endomorphism monoids are isomorphic as abstract monoids, but not as topological monoids—in other words, no isomorphism between these monoids is a homeomorphism. For the same two structures, the automorphism groups and polymorphism clones are isomorphic, but not topologically isomorphic. In particular, there exists a countable ω-categorical structure in a finite relational language which can neither be reconstructed up to first-order biinterpretations from its automorphism group, nor up to existential positive bi-interpretations from its endomorphism monoid, nor up to primitive positive bi-interpretations from its polymorphism clone.

This article considers the relationships between consumption, the environment, and wider sociological endeavour. The current vogue for applying theories of practice to the policy domain of ‘sustainable consumption’ has been generative of conceptual renewal, however the field now sits closer to the applied environmental social sciences than to the sociology of consumption. The analysis proceeds via a close reading of the intellectual currents that have given rise to this situation, and it identifies a number of interrelated issues concerning conceptual slippage and the exclusion of core disciplinary concerns. Accordingly a more suitable definition of consumption is offered, an agenda for re-engaging with foundational approaches to consumer culture is established, and a renewal and reorientation of critique is proposed. Working through and building on the contributions of practice theoretical repertoires, this article suggests that consumption scholarship offers a distinctive set of resources to discussions of current ecological crises and uncertain social futures. These are briefly described and the conclusion argues that consumption still matters.

Background: Atopic dermatitis (AD) is a prevalent disease with variable natural history. Longitudinal birth cohort studies provide an opportunity to define subgroups on the basis of disease trajectories, which may represent different genetic and environmental pathomechanisms.Objectives: We sought to investigate the existence of distinct longitudinal phenotypes of AD and test whether these findings are reproducible in 2 independent cohorts.Methods: The presence of AD was examined in 2 birth cohort studies including 9894 children from the United Kingdom (ALSPAC) and 3652 from the Netherlands (PIAMA). AD was defined by parental report of a typical itchy and/or flexural rash. Longitudinal latent class analysis was used to investigate patterns of AD from birth to the age of 11 to 16 years. We investigated associations with known AD risk factors, including FLG null mutations, 23 other established AD-genetic risk variants, and atopic comorbidity.Results: Six latent classes were identified, representing subphenotypes of AD, with remarkable consistency between the 2 cohorts. The most prevalent class was early-onset-early-resolving AD, which was associated with male sex. Two classes of persistent disease were identified (early-onset-persistent and early-onset-late-resolving); these were most strongly associated with the AD-genetic risk score as well as personal and parental history of atopic disease. A yet unrecognized class of mid-onset-resolving AD, not associated with FLG mutations, but strongly associated with asthma, was identified.Conclusions: Six classes based on temporal trajectories of rash were consistently identified in 2 population-based cohorts. The differing risk factor profiles and diverse prognoses demonstrate the potential importance of a stratified medicine approach for AD.

Background To date, 60 genetic variants have been robustly associated with birthweight. It is unclear whether these associations represent the effect of an individual’s own genotype on their birthweight, their mother’s genotype, or both. Methods We demonstrate how structural equation modelling (SEM) can be used to estimate both maternal and fetal effects when phenotype information is present for individuals in two generations and genotype information is available on the older individual. We conduct an extensive simulation study to assess the bias, power and type 1 error rates of the SEM and also apply the SEM to birthweight data in the UK Biobank study. Results Unlike simple regression models, our approach is unbiased when there is both a maternal and a fetal effect. The method can be used when either the individual’s own phenotype or the phenotype of their offspring is not available, and allows the inclusion of summary statistics from additional cohorts where raw data cannot be shared. We show that the type 1 error rate of the method is appropriate, and that there is substantial statistical power to detect a genetic variant that has a moderate effect on the phenotype and reasonable power to detect whether it is a fetal and/or a maternal effect. We also identify a subset of birthweight-associated single nucleotide polymorphisms (SNPs) that have opposing maternal and fetal effects in the UK Biobank. Conclusions Our results show that SEM can be used to estimate parameters that would be difficult to quantify using simple statistical methods alone.

BackgroundRecent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert their maximum influence during different periods of development. This includes analyses of social-communciation difficulties that share, depending on their developmental stage, stronger genetic links with either Autism Spectrum Disorder or schizophrenia. Here we developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social-communication difficulties, during a ∼10-year period spanning childhood and adolescence.MethodsLongitudinally assessed quantitative social-communication problems (N≤ 5,551) were studied in participants from a UK birth cohort (ALSPAC, 8 to 17 years). Using standardised measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models (GSEM) incorporating whole-genome genotyping information. Analogous to twin research, GSEM included Cholesky decomposition, common pathway and independent pathway models.ResultsA 2-factor Cholesky decomposition model described the data best. One genetic factor was common to SCDC measures across development, the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only ∼50% of the genetic variation at 17 years.ConclusionUsing latent factor models, we identified developmental changes in the genetic architecture of social-communication difficulties that enhance the understanding of ASD and schizophrenia-related dimensions. More generally, GSEM present a framework for modelling shared genetic aetiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.

We propose a new method, G-REMLadp, to estimate the phenotypic variance explained by parent-of-origin effects (POEs) across the genome. Our method uses restricted maximum likelihood analysis of genome-wide genetic relatedness matrices based on individuals’ phased genotypes. Genome-wide SNP data from parent child duos or trios is required to obtain relatedness matrices indexing the parental origin of offspring alleles, as well as offspring phenotype data to partition the trait variation into variance components. To calibrate the power of G-REMLadp to detect non-null POEs when they are present, we provide an analytic approximation derived from Haseman-Elston regression. We also used simulated data to quantify the power and Type I Error rates of G-REMLadp, as well as the sensitivity of its variance component estimates to violations of underlying assumptions. We subsequently applied G-REMLadp to 36 phenotypes in a sample of individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We found that the method does not seem to be inherently biased in estimating variance due to POEs, and that substantial correlation between parental genotypes is necessary to generate biased estimates. Our empirical results, power calculations and simulations indicate that sample sizes over 10000 unrelated parent-offspring duos will be necessary to detect POEs explaining 15%) for the 36 traits that we have examined. Electronic supplementary material The online version of this article (doi:10.1007/s10519-017-9880-0) contains supplementary material, which is available to authorized users.

The Munali Intrusive Complex (MIC) is a flattened tube-shaped, mafic-ultramafic intrusion located close to the southern Congo Craton margin in the Zambezi belt of southern Zambia. It is made up of a Central Gabbro Unit (CGU) core, surrounded by a Marginal Ultramafic-mafic Breccia Unit (MUBU), which contains magmatic Ni sulfide mineralisation. The MIC was emplaced into a sequence of metamorphosed Neoproterozoic rift sediments and is entirely hosted within a unit of marble. Munali has many of the characteristics of craton-margin, conduit-style, dyke-sill complex-hosted magmatic sulfide deposits. Three-dimensional modelling of the MUBU on the southern side of the MIC, where the Munali Nickel Mine is located, reveals a laterally discontinuous body located at the boundary between footwall CGU and hangingwall metasediments. Mapping of underground faces demonstrates the MUBU to have intruded after the CGU and be a highly complex, multi stage megabreccia made up of atypical ultramafic rocks (olivinites, olivine-magnetite rocks, and phoscorites), poikilitic gabbro and olivine basalt/dolerite dykes, brecciated on a millimetre to metre scale by magmatic sulfide. The breccia matrix is largely made up of a sulfide assemblage of pyrrhotite-pentlandite-chalcopyrite-pyrite with varying amounts of magnetite, apatite and carbonate. The sulfides become more massive towards the footwall contact. Late stage, high temperature sulfide-carbonate-magnetite veins cut the rest of the MUBU. The strong carbonate signature is likely due, in part, to contamination from the surrounding marbles, but may also be linked to a carbonatite melt related to the phoscorites. Ductile deformation and shear fabrics are displayed by talc-carbonate altered ultramafic clasts that may represent gas streaming textures by CO2-rich fluids. High precision U-Pb geochronology on zircons give ages of 862.39 ± 0.84 Ma for the poikilitic gabbro and 857.9 ± 1.9 Ma for the ultramafics, highlighting the multi-stage emplacement but placing both mafic and later ultramafic magma emplacement within the Neoproterozoic rifting of the Zambezi Ocean, most likely as sills or sheet-like bodies. Sulfide mineralisation is associated with brecciation of the ultramafics and so is constrained to a maximum age of 858 Ma. The Ni- and Fe-rich nature of the sulfides reflect either early stage sulfide saturation by contamination, or the presence of a fractionated sulfide body with Cu-rich sulfide elsewhere in the system. Munali is an example of a complex conduit-style Ni sulfide deposit affected by multiple stages and sources of magmatism during rifting at a craton margin, subsequent deformation; and where mafic and carbonatitic melts have interacted along deep seated crustal fault systems to produce a mineralogically unusual deposit.

Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratio per 1 s.d. of the risk score (similar to 6 alleles) (95% confidence interval) = 1.24 (1.20-1.27), P = 5.05 x 10(-49)), and we observed a 3.7-fold difference in COPD risk between individuals in the highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in genes for development, elastic fibers and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.