Psychosocial predictors of COVID-19 infection in UK biobank (N = 104 201).

BACKGROUND: Since the outbreak of COVID-19, data on its psychosocial predictors are limited. We therefore aimed to explore psychosocial predictors of COVID-19 infection at the UK Biobank (UKB). METHODS: This was a prospective cohort study conducted among UKB participants. RESULTS: The sample size was N = 104 201, out of which 14 852 (14.3%) had a positive COVID-19 test. The whole sample analysis showed significant interactions between sex and several predictor variables. Among females, absence of college/university degree [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.45-1.66] and socioeconomic deprivation (OR 1.16 95% CI 1.11-1.21) were associated with higher odds of COVID-19 infection, while history of psychiatric consultation (OR 0.85 95% CI 0.77-0.94) with lower odds. Among males, absence of college/university degree (OR 1.56, 95% CI 1.45-1.68) and socioeconomic deprivation (OR 1.12, 95% CI 1.07-1.16) were associated with higher odds, while loneliness (OR 0.87, 95% CI 0.78-0.97), irritability (OR 0.91, 95% CI 0.83-0.99) and history of psychiatric consultation (OR 0.85, 95% CI 0.75-0.97) were associated with lower odds. CONCLUSION: Sociodemographic factors predicted the odds of COVID-19 infection equally among male and female participants, while psychological factors had differential impacts.

New Horizons: the value of UK Biobank to research on endocrine and metabolic disorders.

UK Biobank is an intensively characterized prospective study of 500 000 men and women, aged 40 to 69 years when recruited, between 2006 and 2010, from the general population of the United Kingdom. Established as an open-access resource for researchers worldwide to perform health research that is in the public interest, UK Biobank has collected (and continues to collect) a vast amount of data on genetic, physiological, lifestyle, and environmental factors, with prolonged follow-up of heath conditions through linkage to administrative electronic health records. The study has already demonstrated its unique value in enabling research into the determinants of common endocrine and metabolic diseases. The importance of UK Biobank, heralded as a flagship project for UK health research, will only increase over time as the number of incident disease events accrue, and the study is enhanced with additional data from blood assays (such as whole-genome sequencing, metabolomics, and proteomics), wearable technologies (including physical activity and cardiac monitors), and body imaging (magnetic resonance imaging and dual-energy X-ray absorptiometry). This unique research resource is likely to transform our understanding of the causes, diagnosis, and treatment of many endocrine and metabolic disorders.

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.

BACKGROUND: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis. METHODS: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. RESULTS: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios. CONCLUSIONS: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.

A phenome-wide investigation of risk factors for severe COVID-19.

With the continued spread of COVID-19 globally, it is crucial to identify the potential risk or protective factors associated with COVID-19. Here, we performed genetic correlation analysis and Mendelian randomization analysis to examine genetic relationships between COVID-19 hospitalization and 405 health conditions and lifestyle factors in 456 422 participants from the UK Biobank. The genetic correlation analysis revealed 134 positive and 65 negative correlations, including those with intakes of a variety of dietary components. The MR analysis indicates that a set of body fat-related traits, maternal smoking around birth, basal metabolic rate, lymphocyte count, peripheral enthesopathies and allied syndromes, blood clots in the leg, and arthropathy are causal risk factors for severe COVID-19, while higher education attainment, physical activity, asthma, and never smoking status protect against the illness. Our findings have implications for risk stratification in patients with COVID-19 and the prevention of its severe outcomes.

Association of Social Isolation and Loneliness With Incident Heart Failure in a Population-Based Cohort Study.

BACKGROUND: Social isolation and loneliness have emerged as important risk factors for cardiovascular diseases, particularly during the coronavirus disease pandemic. However, it is unclear whether social isolation and loneliness had independent and joint associations with incident heart failure (HF). OBJECTIVES: This study sought to examine the association of social isolation, loneliness, and their combination with incident HF. METHODS: The UK Biobank study is a population-based cohort study. Social isolation and loneliness were assessed using self-reported questionnaires. HF cases were identified by linking hospital records and death registries. The weighted polygenic risk score associated with HF was calculated. RESULTS: Among the 464,773 participants (mean age: 56.5 ± 8.1 years, 45.3% male), 12,898 incident HF cases were documented during a median follow-up of 12.3 years. Social isolation (most vs least: adjusted HR: 1.17; 95% CI:1.11-1.23) and loneliness (yes vs no: adjusted HR: 1.19; 95% CI: 1.11-1.27) were significantly associated with an increased risk of incident HF. The association between an elevated risk of HF and social isolation was modified by loneliness (Pinteraction = 0.034). A gradient of association between social isolation and the risk of incident HF was found only among individuals without loneliness (Ptrend < 0.001), but not among those with loneliness (Ptrend = 0.829). These associations were independent of the genetic risk of HF. CONCLUSIONS: Social isolation and loneliness were independently associated with a higher likelihood of incident HF regardless of genetic risk. The association between social isolation and incident HF was potentially modified by loneliness status.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

Accelerated ageing is associated with increased COVID-19 severity and differences across ethnic groups may exist.

Background: While increased age is an established risk factor for COVID-19, there is great heterogeneity in outcomes within age groups. This is because chronological age does not reflect health, unlike biological age. We intend to investigate the association between accelerated ageing and COVID-19 outcomes through the lens of three measures, namely phenotypic age acceleration (PhenoAgeAccel), telomere length (Adjusted T/S Ratio) and facial ageing, and to examine whether there are differences across ethnic groups. Methods: Taking participants from the UK Biobank, we associated accelerated ageing with severe COVID-19 outcomes, defined as COVID-related hospitalisation or death. Separate logistic regressions models were created for age and the three accelerated ageing-related variables, adjusting for a variety of covariates in each model. Multivariable logistic regression models were also created within White, Black, Asian and Other ethnic groups to assess for potential differing associations. Forward likelihood ratio logistic regression models were created to evaluate importance of the variables and to assess for patterns of association across the total population and ethnic groups. Results: After adjusting for all covariates, the odds ratio (OR) and 95% confidence interval (95% CI) of COVID-19 severe outcomes for age was 1.080 (1.074-1.086). After further adjusting age for the accelerated ageing variables, the ORs were 1.029 (1.020-1.039) for PhenoAgeAccel and 0.847 (0.772-0.929) for Facial Ageing's "Younger Than You Are" while Adjusted T/S ratio and "Older Than You Are" were statistically insignificant. The OR for age remained similar across ethnic groups. Both PhenoAgeAccel and younger facial ages in the White population and PhenoAgeAccel in the Black population had ORs of 1.031 (1.021-1.042), 0.853 (0.774-0.939), and 1.049 (1.001-1.100), respectively. Both Adjusted T/S Ratio and older facial ages showed statistical insignificance in all ethnicities. In forward logistic regression, age and PhenoAgeAccel were the age-related variables selected most frequently in all models. Interpretation: Accelerated ageing is associated with increased COVID-19 severity. The mechanisms at work here are likely immunosenescence and inflamaging. This association indicates that anti-ageing treatment may improve COVID-19 outcome. The results within ethnic groups and that of telomere length were inconclusive, but point to a need for future, more focused research on the topic.

Occupational characteristics associated with SARS-CoV-2 infection in the UK Biobank during August-November 2020: a cohort study.

BACKGROUND: Occupational exposures may play a key role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection risk. We used a job-exposure matrix linked to the UK Biobank to measure occupational characteristics and estimate associations with a positive SARS-CoV-2 test. METHODS: People reporting job titles at their baseline interview in England who were < 65 years of age in 2020 were included. Healthcare workers were excluded because of differential access to testing. Jobs were linked to the US Occupational Information Network (O*NET) job exposure matrix. O*NET-based scores were examined for occupational physical proximity, exposure to diseases/infection, working outdoors exposed to weather, and working outdoors under cover (score range = 1-5). Jobs were classified as remote work using two algorithms. SARS-CoV-2 test results were evaluated between August 5th-November 10th, 2020, when the UK was released from lockdown. Cox regression was used to calculate adjusted hazard ratios (aHRs), accounting for age, sex, race, education, neighborhood deprivation, assessment center, household size, and income. RESULTS: We included 115,451 people with job titles, of whom 1746 tested positive for SARS-CoV-2. A one-point increase in physical proximity score was associated with 1.14 times higher risk of SARS-CoV-2 (95%CI = 1.05-1.24). A one-point increase in the exposure to diseases/infections score was associated with 1.09 times higher risk of SARS-CoV-2 (95%CI = 1.02-1.16). People reporting jobs that could not be done remotely had higher risk of SARS-CoV-2 regardless of the classification algorithm used (aHRs = 1.17 and 1.20). Outdoors work showed an association with SARS-CoV-2 (exposed to weather aHR = 1.06, 95%CI = 1.01-1.11; under cover aHR = 1.08, 95%CI = 1.00-1.17), but these associations were not significant after accounting for whether work could be done remotely. CONCLUSION: People in occupations that were not amenable to remote work, required closer physical proximity, and required more general exposure to diseases/infection had higher risk of a positive SARS-CoV-2 test. These findings provide additional evidence that coronavirus disease 2019 (COVID-19) is an occupational disease, even outside of the healthcare setting, and indicate that strategies for mitigating transmission in in-person work settings will remain important.

Impaired kidney function biomarkers and risk of severe COVID-19: Analysis of population-based cohort data.

BACKGROUND: Patients with impaired kidney function were found at a high risk of COVID-19 hospitalization and mortality in many observational, cross-sectional, and hospital-based studies, but evidence from large-scale prospective cohorts has been lacking. We aimed to examine the association of kidney function-related biomarkers and their genetic predisposition with the risk of developing severe COVID-19 in population-based data. METHODS: We analyzed data from UK Biobank to examine the prospective association of abnormal kidney function biomarkers with severe COVID-19, defined by laboratory-confirmed COVID-19 hospitalizations. Using genotype data, we constructed polygenic risk scores (PRS) to represent an individual's overall genetic risk for these biomarkers. We also identified tipping points where the risk of severe COVID-19 began to increase significantly for each biomarker. RESULTS: Of the 502,506 adults, 1650 (0.32%) were identified as severe COVID-19, before August 12, 2020. High levels of cystatin C (OR: 1.3; 95% CI: 1.2-1.5; FDR = 1.5 × 10-5 ), serum creatinine (OR: 1.7; 95% CI: 1.3-2.1; p = 3.5 × 10-4 ; FDR = 3.5 × 10-4 ), microalbuminuria (OR: 1.4; 95% CI: 1.2-1.6; FDR = 4 × 10-4 ), and UACR (urinary albumin creatinine ratio; OR: 1.4; 95% CI: 1.2-1.6; p = 3.5 × 10-4 ; FDR = 3.5 × 10-4 ) were found significantly associated with severe COVID-19. Individuals with top 10% of PRS for elevated cystatin C, urate, and microalbuminuria had 28% to 43% higher risks of severe COVID-19 than individuals with bottom 30% PRS (p < 0.05). Tipping-point analyses further supported that severe COVID-19 could occur even when the values of cystatin C, urate (male), and microalbuminuria were within their normal value ranges (OR >1.1, p < 0.05). CONCLUSIONS: Findings from this study might point to new directions for clinicians and policymakers in optimizing risk-stratification among patients based on polygenic risk estimation and tipping points of kidney function markers. Our results call for further investigation to develop a better strategy to prevent severe COVID-19 outcomes among patients with genetic predisposition to impaired kidney function. These findings could provide a new tool for clinicians and policymakers in the future especially if we need to live with COVID-19 for a long time.

The UK Biobank: A Shining Example of Genome-Wide Association Study Science with the Power to Detect the Murky Complications of Real-World Epidemiology.

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants that are reliably associated with human traits. Although GWASs are restricted to certain variant frequencies, they have improved our understanding of the genetic architecture of complex traits and diseases. The UK Biobank (UKBB) has brought substantial analytical opportunity and performance to association studies. The dramatic expansion of many GWAS sample sizes afforded by the inclusion of UKBB data has improved the power of estimation of effect sizes but, critically, has done so in a context where phenotypic depth and precision enable outcome dissection and the application of epidemiological approaches. However, at the same time, the availability of such a large, well-curated, and deeply measured population-based collection has the capacity to increase our exposure to the many complications and inferential complexities associated with GWASs and other analyses. In this review, we discuss the impact that UKBB has had in the GWAS era, some of the opportunities that it brings, and exemplar challenges that illustrate the reality of using data from this world-leading resource.

COVID-19 Risk Appears to Vary Across Different Alcoholic Beverages.

Objectives: To evaluate the associations of status, amount, and frequency of alcohol consumption across different alcoholic beverages with coronavirus disease 2019 (COVID-19) risk and associated mortality. Methods: This study included 473,957 subjects, 16,559 of whom tested positive for COVID-19. Multivariate logistic regression analyses were used to evaluate the associations of alcohol consumption with COVID-19 risk and associated mortality. The non-linearity association between the amount of alcohol consumption and COVID-19 risk was evaluated by a generalized additive model. Results: Subjects who consumed alcohol double above the guidelines had a higher risk of COVID-19 (1.12 [1.00, 1.25]). Consumption of red wine above or double above the guidelines played protective effects against the COVID-19. Consumption of beer and cider increased the COVID-19 risk, regardless of the frequency and amount of alcohol intake. Low-frequency of consumption of fortified wine (1-2 glasses/week) within guidelines had a protective effect against the COVID-19. High frequency of consumption of spirits (≥5 glasses/week) within guidelines increased the COVID-19 risk, whereas the high frequency of consumption of white wine and champagne above the guidelines decreased the COVID-19 risk. The generalized additive model showed an increased risk of COVID-19 with a greater number of alcohol consumption. Alcohol drinker status, frequency, amount, and subtypes of alcoholic beverages were not associated with COVID-19 associated mortality. Conclusions: The COVID-19 risk appears to vary across different alcoholic beverage subtypes, frequency, and amount. Red wine, white wine, and champagne have chances to reduce the risk of COVID-19. Consumption of beer and cider and spirits and heavy drinking are not recommended during the epidemics. Public health guidance should focus on reducing the risk of COVID-19 by advocating healthy lifestyle habits and preferential policies among consumers of beer and cider and spirits.

COVID-19 related outcomes among individuals with neurodegenerative diseases: a cohort analysis in the UK biobank.

BACKGROUND: An increased susceptibility to COVID-19 has been suggested for individuals with neurodegenerative diseases, but data are scarce from longitudinal studies. METHODS: In this community-based cohort study, we included 96,275 participants of the UK Biobank who had available SARS-CoV-2 test results in Public Health England. Of these, 2617 had a clinical diagnosis of neurodegenerative diseases in the UK Biobank inpatient hospital data before the outbreak of COVID-19 (defined as January 31st, 2020), while the remaining participants constituted the reference group. We then followed both groups from January 31st, 2020 to June 14th, 2021 for ascertainment of COVID-19 outcomes, including any COVID-19, inpatient care for COVID-19, and COVID-19 related death. Logistic regression was applied to estimate the association between neurogenerative disease and risks of COVID-19 outcomes, adjusted for multiple confounders and somatic comorbidities. RESULTS: We observed an elevated risk of COVID-19 outcomes among individuals with a neurodegenerative disease compared with the reference group, corresponding to a fully adjusted odds ratio of 2.47 (95%CI 2.25-2.71) for any COVID-19, 2.18 (95%CI 1.94-2.45) for inpatient COVID-19, and 3.67 (95%CI 3.11-4.34) for COVID-19 related death. Among individuals with a positive test result for SARS-CoV-2, individuals with neurodegenerative diseases had also a higher risk of COVID-19 related death than others (fully adjusted odds ratio 2.08; 95%CI 1.71-2.53). CONCLUSION: Among UK Biobank participants who received at least one test for SARS-CoV-2, a pre-existing diagnosis of neurodegenerative disease was associated with a subsequently increased risk of COVID-19, especially COVID-19 related death.

Adapting the UK Biobank Brain Imaging Protocol and Analysis Pipeline for the C-MORE Multi-Organ Study of COVID-19 Survivors.

SARS-CoV-2 infection has been shown to damage multiple organs, including the brain. Multiorgan MRI can provide further insight on the repercussions of COVID-19 on organ health but requires a balance between richness and quality of data acquisition and total scan duration. We adapted the UK Biobank brain MRI protocol to produce high-quality images while being suitable as part of a post-COVID-19 multiorgan MRI exam. The analysis pipeline, also adapted from UK Biobank, includes new imaging-derived phenotypes (IDPs) designed to assess the possible effects of COVID-19. A first application of the protocol and pipeline was performed in 51 COVID-19 patients post-hospital discharge and 25 controls participating in the Oxford C-MORE study. The protocol acquires high resolution T1, T2-FLAIR, diffusion weighted images, susceptibility weighted images, and arterial spin labelling data in 17 min. The automated imaging pipeline derives 1,575 IDPs, assessing brain anatomy (including olfactory bulb volume and intensity) and tissue perfusion, hyperintensities, diffusivity, and susceptibility. In the C-MORE data, IDPs related to atrophy, small vessel disease and olfactory bulbs were consistent with clinical radiology reports. Our exploratory analysis tentatively revealed some group differences between recovered COVID-19 patients and controls, across severity groups, but not across anosmia groups. Follow-up imaging in the C-MORE study is currently ongoing, and this protocol is now being used in other large-scale studies. The protocol, pipeline code and data are openly available and will further contribute to the understanding of the medium to long-term effects of COVID-19.

Explaining Ethnic Differentials in COVID-19 Mortality: A Cohort Study.

Ethnic inequalities in coronavirus disease 2019 (COVID-19) hospitalizations and mortality have been widely reported, but there is scant understanding of how they are embodied. The UK Biobank prospective cohort study comprises approximately half a million people who were aged 40-69 years at study induction, between 2006 and 2010, when information on ethnic background and potential explanatory factors was captured. Study members were prospectively linked to a national mortality registry. In an analytical sample of 448,664 individuals (248,820 women), 705 deaths were ascribed to COVID-19 between March 5, 2020, and January 24, 2021. In age- and sex-adjusted analyses, relative to White participants, Black study members experienced approximately 5 times the risk of COVID-19 mortality (odds ratio (OR) = 4.81, 95% confidence interval (CI): 3.28, 7.05), while there was a doubling in the South Asian group (OR = 2.05, 95% CI: 1.30, 3.25). Controlling for baseline comorbidities, social factors (including socioeconomic circumstances), and lifestyle indices attenuated this risk differential by 34% in Black study members (OR = 2.84, 95% CI: 1.91, 4.23) and 37% in South Asian individuals (OR = 1.57, 95% CI: 0.97, 2.55). The residual risk of COVID-19 deaths in ethnic minority groups may be ascribed to a range of unmeasured characteristics and requires further exploration.

Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities.

Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation.

Association of pre-pandemic high-density lipoprotein cholesterol with risk of COVID-19 hospitalisation and death: The UK Biobank cohort study.

There is growing evidence of, and biological plausibility for, elevated levels of high-density lipoprotein cholesterol (HDL-C) being related to lower rates of respiratory disease. We tested whether pre-pandemic HDL-C within the normal range is associated with subsequent COVID-19 hospitalisations and death. We analysed data on participants from UK Biobank, a prospective cohort study, baseline data for which were collected between 2006 and 2010. Follow-up for COVID-19 was via hospitalisation records (1845 events in 317,306 individuals) and a national mortality registry (458 deaths in 317,833 individuals). After controlling for a series of confounding factors which included health behaviours, inflammatory markers, and socio-economic status, higher levels of HDL-C were related to a lower risk of later hospitalisation. The effect was linear (p-value for trend 0.001), whereby a 0.2 mmol/L increase in HDL-C was associated with a 7% lower risk (odds ratio; 95% confidence interval: 0.93; 0.90, 0.96). Corresponding relationships for mortality were markedly weaker, such that statistical significance at conventional levels were not apparent for both the linear trend (p-value 0.25) and the odds ratio per 0.2 mmol/L increase (0.98; 0.91, 1.05). While our finding for HDL-C and hospitalisations for COVID-19 raise the possibility that favourable modification of this cholesterol fraction via lifestyle changes or drug intervention may impact upon the risk of the disease, it warrants testing in other studies.

Smoking and COVID-19 Infection and Related Mortality: A Prospective Cohort Analysis of UK Biobank Data.

BACKGROUND: Several papers have shown contradictory evidence about the relationship between smoking and COVID-19-related deaths. There is little evidence about smoking and risk of infection. We aim to examine association between smoking and COVID-19 infection and subsequent mortality. METHODS: This was a prospective study with participants from the UK Biobank cohort. Participants who lived in England were followed up from 01/02/2020 to 28/06/2020 with data linked to hospital episode statistics, Office for National Statistics and Public Health England PCR tests. We compared current-smokers, previous-smokers with never-smokers and estimated risk ratio (RR) of COVID-19 infection and subsequent mortality using Poisson regression adjusting for age, sex, ethnicity, body mass index and socio-economic status. Interactions between smoking status and age and sex were tested for using multiplicative interactions, and analyses were stratified by median age (49-68 years, 69-86 years) and sex. RESULTS: In total, 402,978 participants were included in the analyses. The majority were never smokers, 226,294 (56.2%), 140,090 (34.8%) were previous smokers, and 39,974 (9.9%) current smokers. COVID-19 infection was identified in 1591 (0.39%) people, and 372/1591 (23.4%) died. Amongst the younger participants, smokers were nearly twice as likely to become infected with COVID-19 than never smokers (RR 1.88 [1.49-2.38]) whereas there was no difference for those aged 69+ (RR 1.05 [0.82-1.34]). In contrast, amongst the older participants, smokers were twice as likely to die from COVID-19 compared to non-smokers (RR 2.15 [1.11-4.16]) whereas there was no difference for those under the age of 69 (RR 1.22[0.83-1.79]). Similar patterns were observed for previous smokers. The impact of smoking was similar in men and women. CONCLUSION: The association between smoking and COVID-19 infection and subsequent death is modified by age. Smokers and previous smokers aged under 69 were at higher risk of COVID-19 infection, suggesting the risk is associated with increased exposure to SARS-COV-2 virus. Once infected, older smokers were twice as likely to die from COVID-19 than never smokers, possibly mediated by increased risk of chronic conditions/illnesses.

Alcohol Consumption Is Associated with Poor Prognosis in Obese Patients with COVID-19: A Mendelian Randomization Study Using UK Biobank.

BACKGROUND: Acute and chronic alcohol abuse has adverse impacts on both the innate and adaptive immune response, which may result in reduced resistance to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and promote the progression of coronavirus disease 2019 (COVID-19). However, there are no large population-based data evaluating potential causal associations between alcohol consumption and COVID-19. METHODS: We conducted a Mendelian randomization study using data from UK Biobank to explore the association between alcohol consumption and risk of SARS-CoV-2 infection and serious clinical outcomes in patients with COVID-19. A total of 12,937 participants aged 50-83 who tested for SARS-CoV-2 between 16 March to 27 July 2020 (12.1% tested positive) were included in the analysis. The exposure factor was alcohol consumption. Main outcomes were SARS-CoV-2 positivity and death in COVID-19 patients. We generated allele scores using three genetic variants (rs1229984 (Alcohol Dehydrogenase 1B, ADH1B), rs1260326 (Glucokinase Regulator, GCKR), and rs13107325 (Solute Carrier Family 39 Member 8, SLC39A8)) and applied the allele scores as the instrumental variables to assess the effect of alcohol consumption on outcomes. Analyses were conducted separately for white participants with and without obesity. RESULTS: Of the 12,937 participants, 4496 were never or infrequent drinkers and 8441 were frequent drinkers. Both logistic regression and Mendelian randomization analyses found no evidence that alcohol consumption was associated with risk of SARS-CoV-2 infection in participants either with or without obesity (All q > 0.10). However, frequent drinking, especially heavy drinking (HR = 2.07, 95%CI 1.24-3.47; q = 0.054), was associated with higher risk of death in patients with obesity and COVID-19, but not in patients without obesity. Notably, the risk of death in frequent drinkers with obesity increased slightly with the average amount of alcohol consumed weekly (All q < 0.10). CONCLUSIONS: Our findings suggest that alcohol consumption has adverse effects on the progression of COVID-19 in white participants with obesity, but was not associated with susceptibility to SARS-CoV-2 infection.

Neurological diseases and COVID-19: prospective analyses using the UK Biobank.

COVID-19 (Coronavirus disease-19) may present with neurological signs, but whether people already affected by neurological conditions are at a higher risk of contracting COVID-19 is still not known. We, therefore, aimed to investigate the association of previously diagnosed neurological conditions with COVID-19. 502,536 community-dwelling UK Biobank participants (54.4% male, mean age 56.6 ± 10.3 years) were included. Among these, 57,463 participants had a diagnosis of neurological conditions (11.43%) and a total of 1326 COVID-19-positive cases were identified (0.26%). Neurological conditions were identified through medical history and linkage to data on hospital admissions (ICD-10 code G00-G99). COVID-19 presence was diagnosed using the data provided by Public Health England. The association of previous diagnosis of neurological conditions with COVID-19 was evaluated through logistic regressions, adjusted for potential confounders, reported as odds ratios (ORs) with their 95% confidence intervals (CIs). Nerve, nerve root and plexus disorders (G50-G59) were the most common conditions identified. The presence of COVID-19 was almost doubled in neurological conditions compared to the general population (0.45 vs. 0.24%, p < 0.0001). Previously diagnosed neurological conditions were associated with 60% higher odds of COVID-19 positive in the multivariable-adjusted model (OR = 1.6, 95% CI 1.4-1.8). Other degenerative diseases of the nervous system, extrapyramidal and movement disorders, polyneuropathies and other disorders of the peripheral nervous system, cerebral palsy and other paralytic syndromes were significantly associated with a higher odds of COVID-19. The presence of neurological conditions was associated with a significantly higher likelihood of COVID-19 compared to the general population.

Association of working shifts, inside and outside of healthcare, with severe COVID-19: an observational study.

BACKGROUND: Health and key workers have elevated odds of developing severe COVID-19; it is not known, however, if this is exacerbated in those with irregular work patterns. We aimed to investigate the odds of developing severe COVID-19 in health and shift workers. METHODS: We included UK Biobank participants in employment or self-employed at baseline (2006-2010) and with linked COVID-19 data to 31st August 2020. Participants were grouped as neither a health worker nor shift worker (reference category) at baseline, health worker only, shift worker only, or both, and associations with severe COVID-19 investigated in logistic regressions. RESULTS: Of 235,685 participants (81·5% neither health nor shift worker, 1·4% health worker only, 16·9% shift worker only, and 0·3% both), there were 580 (0·25%) cases of severe COVID-19. The odds of severe COVID-19 was higher in health workers (adjusted odds ratio: 2·32 [95% CI: 1·33, 4·05]; shift workers (2·06 [1·72, 2·47]); and in health workers who worked shifts (7·56 [3·86, 14·79]). Being both a health worker and a shift worker had a possible greater impact on the odds of severe COVID-19 in South Asian and Black and African Caribbean ethnicities compared to White individuals. CONCLUSIONS: Both health and shift work (measured at baseline, 2006-2010) were independently associated with over twice the odds of severe COVID-19 in 2020; the odds were over seven times higher in health workers who work shifts. Vaccinations, therapeutic and preventative options should take into consideration not only health and key worker status but also shift worker status.