Genome-wide Association Study of Long COVID (preprint)

Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections(1,2). Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction(3-5). The biological mechanisms that contribute to the development of Long COVID remain to be clarified. We leveraged the COVID-19 Host Genetics Initiative(6,7) to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity(6), lung function(8), and cancers(9), suggesting a broader role for lung function in the pathophysiology of Long COVID. While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.

Adiposity and Mortality among Patients Severely Ill with COVID-19 and non-COVID-19 Respiratory Conditions: A Cross-Context Comparison Study in the UK (preprint)

Objective: To assess the causality of adiposity for mortality among patients severely ill with COVID-19 and non-COVID-19 respiratory conditions by examining the consistency of associations across temporal and geographical contexts where biases vary Design: Prospective cohort study Setting: 297 intensive care units (ICUs) in England, Wales, and Northern Ireland monitored by the Intensive Care National Audit and Research Centre Case Mix Programme Participants: Patients aged [≥]16 years admitted to ICU with COVID-19 (N=33,352; Feb 2020-Aug 2021) and non-COVID-19 respiratory conditions (N=24,739; Feb 2018-Aug 2019) Main outcome measure: 30-day mortality post ICU admission Results: Compared with non-COVID-19 respiratory patients, COVID-19 patients were younger, less often of a white ethnic group, and more often with extreme obesity (body mass index (BMI) [≥] 40kg/m2). COVID-19 patients had fewer comorbidities but higher mortality (35% vs. 23% mortality in non-COVID-19). Socio-demographic and comorbidity factors and their associations with BMI and mortality varied more by date than geographical region of ICU admission, particularly among COVID-19 patients. Among COVID-19 patients, higher BMI was associated with a small excess mortality (hazard ratio (HR) per standard deviation (SD)=1.05; 95% CI=1.03, 1.08), driven by extreme obesity (HR per SD=1.21; 95% CI=1.13, 1.31 vs. normal-weight). Extreme obesity was strongly associated with higher mortality only during Feb-April 2020 (HR=1.49, 95% CI=1.27, 1.73 vs. normal-weight); this association weakened thereafter (BMI-date interaction P=0.03). Among non-COVID-19 respiratory patients, higher BMI was associated with lower mortality (HR per SD=0.84; 95% CI=0.82, 0.87), seen across all overweight/obesity groups. These negative obesity-mortality associations were similar across most admission dates and regions. Conclusions: Obesity is associated with higher mortality among COVID-19 patients, but lower mortality among non-COVID respiratory patients. These associations appear vulnerable to confounding/selection bias in both patient groups, questioning the existence or stability of causal effects. Among COVID-19 patients, unfavourable obesity-mortality associations differ by admission date. Among non-COVID-19 respiratory patients, favourable obesity-mortality associations may reflect comorbidity-induced weight loss.

Variation inERAP2has opposing effects on severe respiratory infection and autoimmune disease (preprint)

Introduction ERAP2 is an aminopeptidase involved in immunological antigen presentation. Genotype data in human samples from before and after the Black Death, an epidemic due to Yersinia pestis , have marked changes in population allele frequency of the common single nucleotide polymorphism (SNP) rs2549794. This SNP in strong linkage disequilibrium with a key splicing SNP in ERAP2 (rs2248374) and this suggests that variation at ERAP2 may be relevant for protection from infection. rs2549794 is also associated with Crohn’s disease and findings imply balancing selection between infection and autoimmune disease at this locus. There have been no large-scale prospective case-control studies of variation at ERAP2 and infection. Methods This study aimed to explore the association between variation at ERAP2 and a) infection, b) autoimmune disease, and c) parental longevity as a proxy for lifespan. Genome Wide Association Studies (GWAS) of these outcomes were identified in contemporary cohorts (UK Biobank, FinnGen, and GenOMICC). Effect estimates were extracted for rs2549794 and rs2248374. Additionally, cis expression and protein quantitative trait loci (QTLs) for ERAP2 were used in Mendelian randomisation analyses. Results Across all cohorts, the T allele (minor allele frequency of 0.4-0.5) of rs2549794 showed evidence of association with respiratory infection (odds ratio; OR for pneumonia 1.03; 95% CI 1.01-1.05; p = 0.014). Effect estimates were larger in bacterial rather than viral infection and larger for more severe phenotypes (OR for critical care admission with pneumonia 1.08; 95% CI 1.02-1.14, p = 0.008, OR for death from pneumonia 1.07; 95% CI 1.01-1.12; p = 0.014). In contrast, opposing effects were identified for Crohn’s disease (OR 0.86; 95% CI 0.82-0.90, p = 8.6 × 10 −9 ) and type 1 diabetes (OR 0.95; 95% CI 0.90-0.99, p = 0.02). No strong evidence for association was identified for sepsis. Carriage of the T allele was associated with increased age of parental death (beta in Z-scored years across both parents age at death 0.01, 95% CI 0.004-0.017, p = 0.002). Similar results were identified for rs2248374. In Mendelian randomisation analyses, increasing transcription or protein levels of ERAP2 were strongly associated with protection from respiratory infection, with opposing effects identified on Crohn’s disease and type 1 diabetes. Increased expression of ERAP2 was associated with reduced parental longevity. Conclusions Variation at ERAP2 is associated with severe respiratory infection in modern societies, with an opposing association with Crohn’s disease and type 1 diabetes. These data support the hypothesis that changes in allele frequencies in ERAP2 observed at the time of the Black Death reflect protection from infection, and suggest ongoing balancing selection at this locus driven by autoimmune and infectious disease

Therapeutic potential of IL6R blockade for the treatment of sepsis and sepsis-related death: Findings from a Mendelian randomisation study (preprint)

Introduction Sepsis is characterised by dysregulated, life-threatening immune responses, which are thought to be driven by cytokines such as interleukin-6 (IL-6). Genetic variants in IL6R known to downregulate IL-6 signalling are associated with improved COVID-19 outcomes, a finding later confirmed in randomised trials of IL-6 receptor antagonists (IL6RA). We hypothesised that blockade of IL6R could also improve outcomes in sepsis. Methods We performed a Mendelian randomisation analysis using single nucleotide polymorphisms (SNPs) in and near IL6R to evaluate the likely causal effects of IL6R blockade on sepsis, sepsis severity, other infections, and COVID-19. We weighted SNPs by their effect on CRP and combined results across them in inverse variance weighted meta-analysis, proxying the effect of IL6RA. Our outcomes were measured in UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative (HGI), and the GenOSept and GainS consortium. We performed several sensitivity analyses to test assumptions of our methods, including utilising variants around CRP in a similar analysis. Results In the UK Biobank cohort (N=485,825, including 11,643 with sepsis), IL6R blockade was associated with a decreased risk of sepsis (OR=0.80; 95% CI 0.66-0.96, per unit of natural log transformed CRP decrease). The size of this effect increased with severity, with larger effects on 28-day sepsis mortality (OR=0.74; 95% CI 0.38-0.70); critical care admission with sepsis (OR=0.48, 95% CI 0.30-0.78) and critical care death with sepsis (OR=0.37, 95% CI 0.14 - 0.98) Similar associations were seen with severe respiratory infection: OR for pneumonia in critical care 0.69 (95% CI 0.49 - 0.97) and for sepsis survival in critical care (OR=0.22; 95% CI 0.04- 1.31) in the GainS and GenOSept consortium. We also confirm the previously reported protective effect of IL6R blockade on severe COVID-19 (OR=0.69, 95% 0.57 - 0.84) in the COVID-19 HGI, which was of similar magnitude to that seen in sepsis. Sensitivity analyses did not alter our primary results. Conclusions IL6R blockade is causally associated with reduced incidence of sepsis, sepsis related critical care admission, and sepsis related mortality. These effects are comparable in size to the effect seen in severe COVID-19, where IL-6 receptor antagonists were shown to improve survival. This data suggests a randomised trial of IL-6 receptor antagonists in sepsis should be considered.

Mental-health before and during the COVID-19 pandemic in adults with neurodevelopmental disorders. (preprint)

The COVID-19 pandemic negatively impacted mental health globally. Individuals with neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), are at elevated risk of mental health difficulties. Therefore, we investigated the impact of the pandemic on anxiety, depression and mental wellbeing in adults with NDDs using longitudinal data from the Avon Longitudinal Study of Parents and Children study (n=3,058). Mental health data were collected pre-pandemic (age 21-25) and at three timepoints during the pandemic (ages 27-28) using the Short Mood and Feelings Questionnaire, Generalised Anxiety Disorder Assessment-7, and Warwick Edinburgh Mental Wellbeing Scale. ADHD and ASD were defined using validated cut-points of the Strengths and Difficulties Questionnaire and Autism Spectrum Quotient, self-reported at age 25. We used multi-level mixed-effects models to investigate changes in mental health in those with ADHD and ASD compared to those without. Prevalences of depression, anxiety and poor mental wellbeing were higher at all timepoints (pre-pandemic and during pandemic) in those with ADHD and ASD compared to those without. Anxiety increased to a greater extent in those with ADHD ({beta}=0.8 [0.2,1.4], p=0.01) and ASD ({beta}=1.2 [-0.1,2.5], p=0.07), while depression symptoms decreased, particularly in females with ASD ({beta}=-3.1 [-4.6,-1.5], p=0.0001). On average, mental wellbeing decreased in all, but to a lesser extent in those with ADHD ({beta}=1.3 [0.2,2.5], p=0.03) and females with ASD ({beta}=3.0 [0.2,5.9], p=0.04). To conclude, anxiety disproportionately increased in adults with NDDs during the pandemic, however, the related lockdowns may have provided a protective environment for depressive symptoms in the same individuals.

Socioeconomic inequality in SARS-CoV-2 testing and COVID-19 outcomes in UK Biobank over the first year of the pandemic: can inequalities be explained byselection bias? (preprint)

Background Structural barriers to testing may introduce selection bias in COVID-19 research. We explore whether changes to testing and lockdown restrictions introduce time-specific selection bias into analyses of socioeconomic position (SEP) and SARS-CoV-2 infection. Methods Using UK Biobank (N = 420 231; 55 % female; mean age = 56.3 [SD=8.01]) we estimated the association between SEP and i) being tested for SARS-CoV-2 infection versus not being tested ii) testing positive for SARS-CoV-2 infection versus testing negative and iii) testing negative for SARS-CoV-2 infection versus not being tested, at four distinct time-periods between March 2020 and March 2021. We explored potential selection bias by examining the same associations with hypothesised positive (ABO blood type) and negative (hair colour) control exposures. Finally, we conducted a hypothesis-free phenome-wide association study to investigate how individual characteristics associated with testing changed over time. Findings The association between low SEP and SARS-CoV-2 testing attenuated across time-periods. Compared to individuals with a degree, individuals who left school with GCSEs or less had an OR of 1.05 (95% CI: 0.95 to 1.16) in March-May 2020 and 0.98 (95% CI: 0.94 to 1.02) in January-March 2021. The magnitude of the association between low SEP and testing positive for SARS-CoV-2 infection increased over the same time-periods. For the same comparisons, the OR for testing positive increased from 1.27 (95% CI: 1.08 to 1.50), to 1.73 (95% CI: 1.59 to 1.87). We found little evidence of an association between both control exposures and all outcomes considered. Our phenome-wide analysis highlighted a broad range of individual traits were associated with testing, which were distinct across time-periods. Interpretation The association between SEP (and indeed many individual traits) and SARS-CoV-2 testing changed over time, indicating time-specific selection pressures in COVID-19. However, positive, and negative control analyses suggest that changes in the magnitude of the association between SEP and SARS-CoV-2 infection over time were unlikely to be explained by selection bias and reflect true increases in socioeconomic inequalities.

The relationship between BMI and COVID-19: exploring misclassification and selection bias in a two-sample Mendelian randomisation study (preprint)

ObjectiveTo use the example of the effect of body mass index (BMI) on COVID-19 susceptibility and severity to illustrate methods to explore potential selection and misclassification bias in Mendelian randomisation (MR) of COVID-19 determinants. DesignTwo-sample MR analysis. SettingSummary statistics from the Genetic Investigation of ANthropometric Traits (GIANT) and COVID-19 Host Genetics Initiative (HGI) consortia. Participants681,275 participants in GIANT and more than 2.5 million people from the COVID-19 HGI consortia. ExposureGenetically instrumented BMI. Main outcome measuresSeven case/control definitions for SARS-CoV-2 infection and COVID-19 severity: very severe respiratory confirmed COVID-19 vs not hospitalised COVID-19 (A1) and vs population (those who were never tested, tested negative or had unknown testing status (A2)); hospitalised COVID-19 vs not hospitalised COVID-19 (B1) and vs population (B2); COVID-19 vs lab/self-reported negative (C1) and vs population (C2); and predicted COVID-19 from self-reported symptoms vs predicted or self-reported non-COVID-19 (D1). ResultsWith the exception of A1 comparison, genetically higher BMI was associated with higher odds of COVID-19 in all comparison groups, with odds ratios (OR) ranging from 1.11 (95%CI: 0.94, 1.32) for D1 to 1.57 (95%CI: 1.57 (1.39, 1.78) for A2. As a method to assess selection bias, we found no strong evidence of an effect of COVID-19 on BMI in a no-relevance analysis, in which COVID-19 was considered the exposure, although measured after BMI. We found evidence of genetic correlation between COVID-19 outcomes and potential predictors of selection determined a priori (smoking, education, and income), which could either indicate selection bias or a causal pathway to infection. Results from multivariable MR adjusting for these predictors of selection yielded similar results to the main analysis, suggesting the latter. ConclusionsWe have proposed a set of analyses for exploring potential selection and misclassification bias in MR studies of risk factors for SARS-CoV-2 infection and COVID-19 and demonstrated this with an illustrative example. Although selection by socioeconomic position and arelated traits is present, MR results are not substantially affected by selection/misclassification bias in our example. We recommend the methods we demonstrate, and provide detailed analytic code for their use, are used in MR studies assessing risk factors for COVID-19, and other MR studies where such biases are likely in the available data. SummaryO_ST_ABSWhat is already known on this topicC_ST_ABS- Mendelian randomisation (MR) studies have been conducted to investigate the potential causal relationship between body mass index (BMI) and COVID-19 susceptibility and severity. - There are several sources of selection (e.g. when only subgroups with specific characteristics are tested or respond to study questionnaires) and misclassification (e.g. those not tested are assumed not to have COVID-19) that could bias MR studies of risk factors for COVID-19. - Previous MR studies have not explored how selection and misclassification bias in the underlying genome-wide association studies could bias MR results. What this study adds- Using the most recent release of the COVID-19 Host Genetics Initiative data (with data up to June 2021), we demonstrate a potential causal effect of BMI on susceptibility to detected SARS-CoV-2 infection and on severe COVID-19 disease, and that these results are unlikely to be substantially biased due to selection and misclassification. - This conclusion is based on no evidence of an effect of COVID-19 on BMI (a no-relevance control study, as BMI was measured before the COVID-19 pandemic) and finding genetic correlation between predictors of selection (e.g. socioeconomic position) and COVID-19 for which multivariable MR supported a role in causing susceptibility to infection. - We recommend studies use the set of analyses demonstrated here in future MR studies of COVID-19 risk factors, or other examples where selection bias is likely.

Continuing inequalities in COVID-19 mortality in England and Wales, and the changing importance of regional, over local, deprivation (preprint)

Abstract Background: Observational studies have highlighted that where individuals live is far more important for risk of dying with COVID-19, than for dying of other causes. Deprivation is commonly proposed as explaining such differences. During the period of localised restrictions in late 2020, areas with higher restrictions tended to be more deprived. We explore how this impacted the relationship between deprivation and mortality and see whether local or regional deprivation matters more for inequalities in COVID-19 mortality. Methods: We use publicly available population data on deaths due to COVID-19 and all-cause mortality between March 2020 and April 2021 to investigate the scale of spatial inequalities. We use a multiscale approach to simultaneously consider three spatial scales through which processes driving inequalities may act. We go on to explore whether deprivation explains such inequalities. Results Adjusting for population age structure and number of care homes, we find highest regional inequality in October 2020, with a COVID-19 mortality rate ratio of 5.86 (95% CI 3.31 to 19.00) for the median between-region comparison. We find spatial context is most important, and spatial inequalities higher, during periods of low mortality. Almost all unexplained spatial inequality in October 2020 is removed by adjusting for deprivation. During October 2020, one standard deviation increase in regional deprivation was associated with 2.45 times higher local mortality (95% CI, 1.75 to 3.48). Conclusions Spatial inequalities are greatest in periods of lowest overall mortality, implying that as mortality declines it does not do so equally. During the prolonged period of low restrictions and low mortality in summer 2020, spatial inequalities strongly increased. Contrary to previous months, we show that the strong spatial patterning during autumn 2020 is almost entirely explained by deprivation. As overall mortality declines, policymakers must be proactive in detecting areas where this is not happening, or risk worsening already strong health inequalities.

Exploring selection bias in COVID-19 research: Simulations and prospective analyses of two UK cohort studies (preprint)

Background Non-random selection into analytic subsamples could introduce selection bias in observational studies of SARS-CoV-2 infection and COVID-19 severity (e.g. including only those have had a COVID-19 PCR test). We explored the potential presence and impact of selection in such studies using data from self-report questionnaires and national registries. Methods Using pre-pandemic data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (mean age=27.6 (standard deviation [SD]=0.5); 49% female) and UK Biobank (UKB) (mean age=56 (SD=8.1); 55% female) with data on SARS-CoV-2 infection and death-with-COVID-19 (UKB only), we investigated predictors of selection into COVID-19 analytic subsamples. We then conducted empirical analyses and simulations to explore the potential presence, direction, and magnitude of bias due to selection when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. Results In both ALSPAC and UKB a broad range of characteristics related to selection, sometimes in opposite directions. For example, more educated participants were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB. We found bias in many simulated scenarios. For example, in one scenario based on UKB, we observed an expected odds ratio of 2.56 compared to a simulated true odds ratio of 3, per standard deviation higher BMI. Conclusion Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depends on the outcome definition, the true effect of the risk factor, and the assumed selection mechanism.

Association of COVID-19 with arterial and venous vascular diseases: a population-wide cohort study of 48 million adults in England and Wales (preprint)

Importance: The long-term effects of COVID-19 on the incidence of vascular diseases are unclear. Objective: To quantify the association between time since diagnosis of COVID-19 and vascular disease, overall and by age, sex, ethnicity, and pre-existing disease. Design: Cohort study based on population-wide linked electronic health records, with follow up from January 1st to December 7th 2020. Setting and participants: Adults registered with an NHS general practice in England or Wales and alive on January 1st 2020. Exposures: Time since diagnosis of COVID-19 (categorised as 0-6 days, 1-2 weeks, 3-4, 5-8, 9-12, 13-26 and 27-49 weeks since diagnosis), with and without hospitalisation within 28 days of diagnosis. Main outcomes and measures: Primary outcomes were arterial thromboses (mainly acute myocardial infarction and ischaemic stroke) and venous thromboembolic events (VTE, mainly pulmonary embolism and lower limb deep vein thrombosis). We also studied other vascular events (transient ischaemic attack, haemorrhagic stroke, heart failure and angina). Hazard ratios were adjusted for demographic characteristics, previous disease diagnoses, comorbidities and medications. Results: Among 48 million adults, 130,930 were and 1,315,471 were not hospitalised within 28 days of COVID-19. In England, there were 259,742 first arterial thromboses and 60,066 first VTE during 41.6 million person-years follow-up. Adjusted hazard ratios (aHRs) for first arterial thrombosis compared with no COVID-19 declined rapidly from 21.7 (95% CI 21.0-22.4) to 3.87 (3.58-4.19) in weeks 1 and 2 after COVID-19, 2.80 (2.61-3.01) during weeks 3-4 then to 1.34 (1.21-1.48) during weeks 27-49. aHRs for first VTE declined from 33.2 (31.3-35.2) and 8.52 (7.59-9.58) in weeks 1 and 2 to 7.95 (7.28-8.68) and 4.26 (3.86-4.69) during weeks 3-4 and 5-8, then 2.20 (1.99-2.44) and 1.80 (1.50-2.17) during weeks 13-26 and 27-49 respectively. aHRs were higher, for longer after diagnosis, after hospitalised than non-hospitalised COVID-19. aHRs were also higher among people of Black and Asian than White ethnicity and among people without than with a previous event. Across the whole population estimated increases in risk of arterial thromboses and VTEs were 2.5% and 0.6% respectively 49 weeks after COVID-19, corresponding to 7,197 and 3,517 additional events respectively after 1.4 million COVID-19 diagnoses. Conclusions and Relevance: High rates of vascular disease early after COVID-19 diagnosis decline more rapidly for arterial thromboses than VTEs but rates remain elevated up to 49 weeks after COVID-19. These results support continued policies to avoid COVID-19 infection with effective COVID-19 vaccines and use of secondary preventive agents in high-risk patients.

Time-varying selection bias in analyses of COVID-19 in UK Biobank

RationaleAssociations between COVID-19 risk factors and COVID-19 outcomes change over time, likely due to selection into who receives a COVID-19 test. When studies do not account for the changes in testing criteria, the association between a risk factor and outcome is a joint estimate across time. The transportability of a joint estimate aggregated over multiple testing periods may be limited. To improve generalisability, it is desirable to estimate effects net of time-varying selection.Aim1) Demonstrate variation in the association between covariates expected to associate with testing, and those which would not, on COVID-19 at different timepoints. 2) Apply methods to mitigate biases in empirical estimates.MethodsAnalyses will be carried out on up to 421,037 UK Biobank participants residing in England at baseline (mean age at baseline = 56;55% female). Risk factors will be determined at baseline (from 2006 to 2010), and COVID-19 outcomes will be ascertained from linked Public Health England COVID-19 test data and mortality statistics.Univariate cox proportional hazard models will be used to explore how associations between time-varying and time-stable variables change over time with;i) having a test for COVID-19, ii) testing positive for COVID-19 and iii) dying with COVID-19.Time-varying risk factors will be based on measures of socioeconomic position (SEP) including education, Townsend deprivation index and income. ABO blood group will be considered as a time-stable risk factor. Distinct time periods will be defined based on changes in testing definitions and changes in lockdown restrictions.Inverse probability weights will then be calculated for each time period. These weights will then be applied to models estimating risk across all time periods.Expected ResultsPreliminary analyses show that the size of the association between SEP and i) COVID-19 testing and ii) testing positive for COVID-19, changes across the course of the pandemic. These differences may be due to differential testing and not time-varying causal effects of the risk factor. We expect inverse probability weights will provide estimates closer to the true value for the association between each risk factor and outcome, independent of selection pressures on receiving a COVID-19 test. Population Health Relevance. Where studies do not account for time-varying selection pressures, the causal interpretations and the validity of results may be distorted. Where these findings are to be translated into developing population level or pharmaceutical interventions to mitigate against COVID-19 outcomes, efforts may be diverted away from more important risk factors.

Interrogating structural inequalities in COVID-19 mortality in England and Wales

BackgroundNumerous observational studies have highlighted structural inequalities in COVID-19 mortality in the UK. Such studies often fail to consider the complex spatial nature of such inequalities in their analysis, leading to the potential for bias and an inability to reach conclusions about the most appropriate structural levels for policy intervention.MethodsWe use publicly available population data on COVID-19 related- and all-cause mortality between March and July 2020 in England and Wales to investigate the spatial scale of such inequalities. We propose a multiscale approach to simultaneously consider four spatial scales at which processes driving inequality may act and apportion inequality between these.ResultsAdjusting for population age structure, number of care homes and residing in the North we find highest regional inequality in March and June/July. We find finer-grained within-region increased steadily from March until July. The importance of spatial context increases over the study period. No analogous pattern is visible for non-COVID mortality. Higher relative deprivation is associated with increased COVID-19 mortality at all stages of the pandemic but does not explain structural inequalities.ConclusionResults support initial stochastic viral introduction in the South, with initially high inequality decreasing before the establishment of regional trends by June and July, prior to reported regionality of the ‘second-wave’. We outline how this framework can help identify structural factors driving such processes, and offer suggestions for a long-term, locally-targeted model of pandemic relief in tandem with regional support to buffer the social context of the area.

Mendelian Randomization Analyses Show That Higher Acetyl-Carnitine and Carnitine Levels in Blood Protect Against Severe COVID19 (preprint)

Background: Severe Covid19 is characterised by a hyperactive immune response. Carnitine, an essential nutrient, and it’s derivative acetyl-carnitine can downregulate proinflammatory cytokines and has been suggested as a potential treatment for the disease.Methods: We carried out Mendelian randomization analyses using publicly available data from a large genome wide association study (GWAS) of metabolites and a collaborative genome wide study of Covid19 to investigate the nature of the relationship between carnitine and acetyl-carnitine and Covid19 infection, hospitalisation with Covid19 and very severe Covid19. We used the same methodology to determine whether carnitine was associated with co-morbidities commonly found among those with severe Covid19.Findings: We found evidence of a protective effect against very severe Covid19 for both carnitine and acetyl-carnitine, with around a 40% reduction in risk associated with a doubling of carnitine or acetyl-carnitine (carnitine odds ratio (OR) = 0.56, 95% confidence intervals (CI) 0.33 to 0.95, p=0.03 and acetyl-carnitine OR=0.60, 95% CI 0.35 to 1.02, p=0.06), and evidence of protective effects on hopitalisation with Covid19. For acetyl-carnitine the largest protective effect was seen in the comparison between those hospitalised with Covid19 and those infected but not hospitalised (OR=0.34, 95%CI 0.18 to 0.62, p=0.0005).Interpretation: Carnitine and acetyl-carnitine merit further investigation in respect to the prevention of severe Covid19.Funding Information: NK is supported by World Cancer Research Fund (2020/019). SJL and GDS are supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and GDS is Director of the Medical Research Council Integrative Epidemiology Unit at the University of Bristol supported by the Medical Research Council (MC_UU_00011/1). SJL and NK are affiliated with this unit. SJL and GDS are also supported by the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre which is funded by the National Institute for Health Research (NIHR).Declaration of Interests: The authors do not have any conflicts of interest in relation to the work in this manuscript.

Mendelian randomization analyses show that higher acetyl-carnitine and carnitine levels in blood protect against severe Covid19 (preprint)

Background: Severe Covid19 is characterised by a hyperactive immune response. Carnitine, an essential nutrient, and its derivative acetyl-carnitine can downregulate proinflammatory cytokines and has been suggested as a potential treatment for the disease. Methods: We carried out Mendelian randomization analyses using publicly available data from a large genome wide association study (GWAS) of metabolites and a collaborative genome wide study of Covid19 to investigate the nature of the relationship between carnitine and acetyl-carnitine and Covid19 infection, hospitalisation with Covid19 and very severe Covid19. We used the same methodology to determine whether carnitine was associated with co-morbidities commonly found among those with severe Covid19. Results: We found evidence of a protective effect against very severe Covid19 for both carnitine and acetyl-carnitine, with around a 40% reduction in risk associated with a doubling of carnitine or acetyl-carnitine (carnitine odds ratio (OR) = 0.56, 95% confidence intervals (CI) 0.33 to 0.95, p=0.03 and acetyl-carnitine OR=0.60, 95% CI 0.35 to 1.02, p=0.06), and evidence of protective effects on hopitalisation with Covid19. For acetyl-carnitine the largest protective effect was seen in the comparison between those hospitalised with Covid19 and those infected but not hospitalised (OR=0.34, 95%CI 0.18 to 0.62, p=0.0005). Conclusion: Carnitine and acetyl-carnitine merit further investigation in respect to the prevention of severe Covid19.

Risk of death among teachers in England and Wales during the Covid19 pandemic (preprint)

ObjectivesTo use publicly available data on mortality in England and Wales to estimate the extent of occupation risk from Covid19 among teachers and others working in schools. DesignAnalysis of national death registration data from the Office for National Statistics. SettingEngland and Wales from March 20th - 28th December 2020, during the Covid-19 pandemic. ParticipantsWe compared mortality rates among teachers and other school workers to all working aged people and all professional occupations. Primary and Secondary outcomesDeaths with Covid19 was our primary outcome and death from all causes was our secondary outcome. ResultsWe found that the absolute mortality rates for deaths with Covid19 were generally low amongst teachers ([≤]39 per 100,000); they were also low relative to many other occupations. However, both male and female secondary school teachers had slightly higher risks of dying with Covid19 relative to all working aged people and greater risk compared to all professionals, primary school teachers did not have an elevated risk. The mortality risk for all causes was also higher in teachers compared to the working aged population. Excess deaths from all causes were higher among those aged over 65 who were working in schools compared to all over 65s who were currently working and compared to all professionals in this age group. ConclusionThere is weak evidence that secondary school teachers (in particular females) may have a slightly higher risk of Covid19 mortality, but compared to many other occupations their risk is low. Further research is needed to determine why there is a high proportion of excess of deaths which were apparently not due to Covid19 among over 65 year-olds working in schools.

Interrogating structural inequalities in COVID-19 Mortality in England and Wales (preprint)

BackgroundNumerous observational studies have highlighted structural inequalities in COVID-19 mortality in the UK. Such studies often fail to consider the complex spatial nature of such inequalities in their analysis, leading to the potential for bias and an inability to reach conclusions about the most appropriate structural levels for policy intervention. MethodsWe use publicly available population data on COVID-19 related- and all-cause mortality between March and July 2020 in England and Wales to investigate the spatial scale of such inequalities. We propose a multiscale approach to simultaneously consider four spatial scales at which processes driving inequality may act and apportion inequality between these. ResultsAdjusting for population age structure, number of care homes and residing in the North we find highest regional inequality in March and June/July. We find finer-grained within-region increased steadily from March until July. The importance of spatial context increases over the study period. No analogous pattern is visible for non-COVID mortality. Higher relative deprivation is associated with increased COVID-19 mortality at all stages of the pandemic but does not explain structural inequalities. ConclusionsResults support initial stochastic viral introduction in the South, with initially high inequality decreasing before the establishment of regional trends by June and July, prior to reported regionality of the "second-wave". We outline how this framework can help identify structural factors driving such processes, and offer suggestions for a long-term, locally-targeted model of pandemic relief in tandem with regional support to buffer the social context of the area. Key MessagesO_LIRegional inequality in COVID-19 mortality declined from an initial peak in April, before increasing again in June/July. C_LIO_LIWithin-region inequality increased steadily from March until July. C_LIO_LIStrong regional trends are evident in COVID-19 mortality in June/July, prior to wider reporting of regional differences in "second wave". C_LIO_LIAnalogous spatial inequalities are not present in non-COVID related mortality over the study period. C_LIO_LIThese inequalities are not explained by age structure, care homes, or deprivation. C_LI

Evaluating the effects of cardiometabolic exposures on circulating proteins which may contribute to SARS-CoV-2 severity (preprint)

Background: Developing insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of critical importance to overcome the global pandemic caused by coronavirus disease 2019 (covid-19). In this study, we have applied Mendelian randomization (MR) to systematically evaluate the effect of 10 cardiometabolic risk factors and genetic liability to lifetime smoking on 97 circulating host proteins postulated to either interact or contribute to the maladaptive host response of SARS-CoV-2. Methods: We applied the inverse variance weighted (IVW) approach and several robust MR methods in a two-sample setting to systemically estimate the genetically predicted effect of each risk factor in turn on levels of each circulating protein. Multivariable MR was conducted to simultaneously evaluate the effects of multiple risk factors on the same protein. We also applied MR using cis-regulatory variants at the genomic location responsible for encoding these proteins to estimate whether their circulating levels may influence SARS-CoV-2 severity. Findings: In total, we identified evidence supporting 105 effects between risk factors and circulating proteins which were robust to multiple testing corrections and sensitivity analyses. For example, body mass index provided evidence of an effect on 23 circulating proteins with a variety of functions, such as inflammatory markers c-reactive protein (IVW Beta=0.34 per standard deviation change, 95% CI=0.26 to 0.41, P=2.19x10-16) and interleukin-1 receptor antagonist (IVW Beta=0.23, 95% CI=0.17 to 0.30, P=9.04x10-12). Further analyses using multivariable MR provided evidence that the effect of BMI on lowering immunoglobulin G, an antibody class involved in protecting the body from infection, is substantially mediated by raised triglycerides levels (IVW Beta=-0.18, 95% CI=-0.25 to -0.12, P=2.32x10-08, proportion mediated=44.1%). The strongest evidence that any of the circulating proteins highlighted by our initial analysis influence SARS-CoV-2 severity was identified for soluble glycoprotein 130 (odds ratio=1.81, 95% CI=1.25 to 2.62, P=0.002), a signal transductor for interleukin-6 type cytokines which are involved in the bodys inflammatory response. However, based on current case samples for severe SARS-CoV-2 we were unable to replicate findings in independent samples. Interpretation: Our findings highlight several key proteins which are influenced by established exposures for disease. Future research to determine whether these circulating proteins mediate environmental effects onto risk of SARS-CoV-2 are warranted to help elucidate therapeutic strategies for covid-19 disease severity.

Multi-omics study revealing tissue-dependent putative mechanisms of SARS-CoV-2 drug targets on viral infections and complex diseases (preprint)

Drug target prioritisation for new targets and drug repurposing of existing drugs for COVID-19 treatment are urgently needed for the current pandemic. Here we pooled 353 candidate drug targets of COVID-19 from clinical trial registries and the literature and estimated their putative causal effects in 11 SARS-CoV-2 related tissues on 622 complex human diseases. By constructing a disease atlas of drug targets for COVID-19, we prioritise 726 target-disease associations as evidence of causality using robust Mendelian randomization (MR) and colocalization evidence (http://epigraphdb.org/covid-19/ctda/). Triangulating these MR findings with historic drug trial information and the druggable genome, we ranked and prioritised three genes DHODH, ITGB5 and JAK2 targeted by three marketed drugs (Leflunomide, Cilengitide and Baricitinib) which may have repurposing potential with careful risk assessment. This study evidences the value of our integrative approach in prioritising and repurposing drug targets, which will be particularly applicable when genetic association studies of COVID-19 are available in the near future.