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Despite its significant genetic component, the study of hypertension by genome-wide association presents more challenges than other common complex diseases. Its high prevalence, heterogeneity, and somewhat unclear definition are the challenges that need to be overcome on one hand. On the other hand, there are issues of small effect sizes and pleiotropism that are not specific to hypertension alone but nonetheless magnify the problems of genetic dissection when coupled with phenotypic misclassification. We discuss issues of study design and summarise published genome-wide association studies (GWASs) of hypertension and blood pressure. With careful study design and analysis success is possible, as demonstrated by the recent large-scale studies. Following these, there is still further scope to advance the field through high fidelity phenotyping and deep sequencing

Long Covid stigma: estimating burden and validating scale in a UK-based sample

Background Stigma can be experienced as perceived or actual disqualification from social and institutional acceptance on the basis of one or more physical, behavioural or other attributes deemed to be undesirable. Long Covid is a predominantly multisystem condition that occurs in people with a history of SARSCoV2 infection, often resulting in functional disability. This study aimed to develop and validate a Long Covid Stigma Scale (LCSS); and to quantify the burden of Long Covid stigma. Methods Data from the follow-up of a co-produced community-based Long Covid online survey using convenience non-probability sampling was used. Thirteen questions on stigma were designed to develop the LCSS capturing three domains-enacted (overt experiences of discrimination), internalised (internalising negative associations with Long Covid and accepting them as self-applicable) and anticipated (expectation of bias/poor treatment by others) stigma. Confirmatory factor analysis tested whether LCSS consisted of the three hypothesised domains. Model fit was assessed and prevalence was calculated. Results 966 UK-based participants responded (888 for stigma questions), with mean age 48 years (SD: 10.7) and 85% female. Factor loadings for enacted stigma were 0.70-0.86, internalised 0.75-0.84, anticipated 0.58-0.87, and model fit was good. The prevalence of experiencing stigma at least 'sometimes' and 'often/always' was 95% and 76% respectively. Anticipated and internalised stigma were more frequently experienced than enacted stigma. Those who reported having a clinical diagnosis of Long Covid had higher stigma prevalence than those without. Conclusion This study establishes a scale to measure Long Covid stigma and highlights common experiences of stigma in people living with Long Covid

UVA and Seasonal Patterning of 56 370 Myocardial Infarctions Across Scotland, 2000–2011

Background: Myocardial infarction exhibits seasonal patterning, with higher amplitude at increased latitude. Epidemiological evidence suggests that sunlight is protective against cardiovascular disease, independent of ambient temperature, but ultraviolet B–mediated vitamin D production has been discounted as causal. We aimed to determine whether ultraviolet A is associated with the seasonal patterning of myocardial infarction. Methods and Results: Routine hospitalization data were used to determine monthly incidence of myocardial infarction in Scotland between 2000 and 2011. Small‐area–level aggregated data were obtained on ambient temperature from the Meteorological Office and ultraviolet A and ultraviolet B irradiance from NASA satellites. Autoregressive distributed lag models were run for ultraviolet A and myocardial infarction, including adjustment for ambient temperature and ultraviolet B. Monthly incidence of myocardial infarction displayed winter peaks and summer troughs superimposed on the underlying trend, with a mean amplitude of 0.31 (95% CI: 0.21, 0.41) myocardial infarctions per 100 000 population per month. Ultraviolet A exposure was inversely associated with myocardial infarction independent of ambient temperature (coefficient, −0.05; 95% CI, −0.09, −0.01; P=0.015) and ultraviolet B UVB (coefficient, −0.05; 95% CI, −0.09, −0.02; P=0.004). Conclusions: Further research is required to explore whether an ultraviolet‐mediated mechanism different to vitamin D, such as nitric oxide–mediated vasodilatation, may play a causal role in the seasonal and geographical patterning of myocardial infarction

Antenatal exposure to solar radiation and learning disabilities: Population cohort study of 422,512 children

Learning disability varies by month of conception. The underlying mechanism is unknown but vitamin D, necessary for normal brain development, is commonly deficient over winter in high latitude countries due to insufficient ultraviolet radiation. We linked the 2007–2016 Scottish School Pupil Censuses to Scottish maternity records and to sunshine hours and antenatal ultraviolet A/B radiation exposure derived from weather stations and satellites respectively. Logistic regression analyses were used to explore the associations between solar radiation, then ultraviolet B, and learning disabilities, adjusting for the potential confounding effects of month of conception and sex. Of the 422,512 eligible, singleton schoolchildren born at term in Scotland, 79,616 (18.8%) had a learning disability. Total antenatal sunshine hours (highest quintile; adjusted OR 0.89; 95% CI: 0.86, 0.93; p < 0.001) and ultraviolet B exposure (highest quintile; adjusted OR 0.55; 95% CI: 0.51, 0.60; p < 0.001) were inversely associated with learning disabilities with evidence of a dose-relationship. The latter association was independent of ultraviolet A exposure. Significant associations were demonstrated for exposure in all three trimesters. Low maternal exposure to ultraviolet B radiation may play a role in the seasonal patterning of learning disabilities. Further studies are required to corroborate findings and determine the effectiveness of supplements

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort

Background: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. Methods and findings: We studied data from UK Biobank (428,199 participants; aged 37–73; recruited 2006–2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96–1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28–1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12–1.46) and 1.77 (1.46–2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09–3.78); 2.79 (2.00–3.90); 2.66 (1.88–3.76); 2.13 (1.46–3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. Conclusions: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19

Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants

Introduction: Older people have been reported to be at higher risk of COVID-19 mortality. This study explored the factors mediating this association and whether older age was associated with increased mortality risk in the absence of other risk factors. Methods: In UK Biobank, a population cohort study, baseline data were linked to COVID-19 deaths. Poisson regression was used to study the association between current age and COVID-19 mortality. Results: Among eligible participants, 438 (0.09%) died of COVID-19. Current age was associated exponentially with COVID-19 mortality. Overall, participants aged ≥75 years were at 13-fold (95% CI 9.13–17.85) mortality risk compared with those <65 years. Low forced expiratory volume in 1 second, high systolic blood pressure, low handgrip strength, and multiple long-term conditions were significant mediators, and collectively explained 39.3% of their excess risk. The associations between these risk factors and COVID-19 mortality were stronger among older participants. Participants aged ≥75 without additional risk factors were at 4-fold risk (95% CI 1.57–9.96, P = 0.004) compared with all participants aged <65 years. Conclusions: Higher COVID-19 mortality among older adults was partially explained by other risk factors. ‘Healthy’ older adults were at much lower risk. Nonetheless, older age was an independent risk factor for COVID-19 mortality

Vitamin D concentrations and COVID-19 infection in UK Biobank

Background and aims: COVID-19 and low levels of vitamin D appear to disproportionately affect black and minority ethnic individuals. We aimed to establish whether blood 25-hydroxyvitamin D (25(OH)D) concentration was associated with COVID-19 risk, and whether it explained the higher incidence of COVID-19 in black and South Asian people. Methods: UK Biobank recruited 502,624 participants aged 37–73 years between 2006 and 2010. Baseline exposure data, including 25(OH)D concentration and ethnicity, were linked to COVID-19 test results. Univariable and multivariable logistic regression analyses were performed for the association between 25(OH)D and confirmed COVID-19, and the association between ethnicity and both 25(OH)D and COVID-19. Results: Complete data were available for 348,598 UK Biobank participants. Of these, 449 had confirmed COVID-19 infection. Vitamin D was associated with COVID-19 infection univariably (OR = 0.99; 95% CI 0.99–0.999; p = 0.013), but not after adjustment for confounders (OR = 1.00; 95% CI = 0.998–1.01; p = 0.208). Ethnicity was associated with COVID-19 infection univariably (blacks versus whites OR = 5.32, 95% CI = 3.68–7.70, p-value<0.001; South Asians versus whites OR = 2.65, 95% CI = 1.65–4.25, p-value<0.001). Adjustment for 25(OH)D concentration made little difference to the magnitude of the association. Conclusions: Our findings do not support a potential link between vitamin D concentrations and risk of COVID-19 infection, nor that vitamin D concentration may explain ethnic differences in COVID-19 infection

The association between a lifestyle score, socioeconomic status, and COVID-19 outcomes within the UK Biobank cohort

Background: Infection with SARS-CoV-2 virus (COVID-19) impacts disadvantaged groups most. Lifestyle factors are also associated with adverse COVID-19 outcomes. To inform COVID-19 policy and interventions, we explored effect modification of socioeconomic-status (SES) on associations between lifestyle and COVID-19 outcomes. Methods: Using data from UK-Biobank, a large prospective cohort of 502,536 participants aged 37–73 years recruited between 2006 and 2010, we assigned participants a lifestyle score comprising nine factors. Poisson regression models with penalised splines were used to analyse associations between lifestyle score, deprivation (Townsend), and COVID-19 mortality and severe COVID-19. Associations between each exposure and outcome were examined independently before participants were dichotomised by deprivation to examine exposures jointly. Models were adjusted for sociodemographic/health factors. Results: Of 343,850 participants (mean age > 60 years) with complete data, 707 (0.21%) died from COVID-19 and 2506 (0.76%) had severe COVID-19. There was evidence of a nonlinear association between lifestyle score and COVID-19 mortality but limited evidence for nonlinearity between lifestyle score and severe COVID-19 and between deprivation and COVID-19 outcomes. Compared with low deprivation, participants in the high deprivation group had higher risk of COVID-19 outcomes across the lifestyle score. There was evidence for an additive interaction between lifestyle score and deprivation. Compared with participants with the healthiest lifestyle score in the low deprivation group, COVID-19 mortality risk ratios (95% CIs) for those with less healthy scores in low versus high deprivation groups were 5.09 (1.39–25.20) and 9.60 (4.70–21.44), respectively. Equivalent figures for severe COVID-19 were 5.17 (2.46–12.01) and 6.02 (4.72–7.71). Alternative SES measures produced similar results. Conclusions: Unhealthy lifestyles are associated with higher risk of adverse COVID-19, but risks are highest in the most disadvantaged, suggesting an additive influence between SES and lifestyle. COVID-19 policy and interventions should consider both lifestyle and SES. The greatest public health benefit from lifestyle focussed COVID-19 policy and interventions is likely to be seen when greatest support for healthy living is provided to the most disadvantaged groups