Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

Sodium-glucose co-transporter-2 inhibitors for hospitalised patients with COVID-19: a prospective meta-analysis of randomised trials

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors have been proposed as a potential treatment for adults hospitalised with COVID-19, due to their potential anti-inflammatory and endothelial protective effects. Published evidence from randomised control trials (RCTs) does not provide evidence of benefit. We aimed to estimate the effect of oral administration of SGLT2 inhibitors compared with usual care or placebo in adults hospitalised with COVID-19.

METHODS

Eligible RCTs that estimated the effect of oral administration of SGLT2 inhibitors compared with usual care or placebo on 28-day all-cause mortality (primary outcome) were included in this prospective meta-analysis. The primary safety outcome was ketoacidosis by 28 days. Trials were identified through systematic searches of ClinicalTrials.gov, EudraCT, and the WHO ISRCTN registry between Nov 1, 2022 and Jan 31, 2023. The search terms were "random*" AND "COVID" AND each SGLT2i, not restricted by trial status or language. Individual searches were then combined. Prespecified summary outcome data, overall and within subgroups of interest, were provided by each trial. The primary analyses were inverse variance weighted meta-analysis of odds ratios (ORs). Risk of bias was assessed using the Cochrane Risk of Bias tool. This study was registered with PROSPERO, CRD42023406442.

FINDINGS

Three eligible trials randomly assigned 6096 participants (3025 to the SGLT2 inhibitor group and 3071 to the usual care or placebo group). 2381 (39%) patients were women and 1547 (25%) had type 2 diabetes at randomisation. By 28 days, there were 351 deaths in the SGLT2 inhibitor group and 382 deaths in the usual care or placebo group (summary OR 0·93 [95% CI 0·79-1·08]; p=0·33, I2 for inconsistency across trials 0%). The risk of bias was assessed as being low. Ketoacidosis was observed in seven participants in the SGLT2 inhibitor group and two patients in the usual care or placebo group.

INTERPRETATION

Although administration of SGLT2 inhibitor was safe, we found no clear evidence that adding SGLT2 inhibitor therapy improved outcomes in patients hospitalised with COVID-19 compared with usual care or placebo. These data do not support the use of SGLT2 inhibitors as standard treatment in adults hospitalised for COVID-19.

FUNDING

None.

Adiposity and mortality among intensive care patients with COVID-19 and non-COVID-19 respiratory conditions: a cross-context comparison study in the UK

BACKGROUND

Adiposity shows opposing associations with mortality within COVID-19 versus non-COVID-19 respiratory conditions. We assessed the likely causality of adiposity for mortality among intensive care patients with COVID-19 versus non-COVID-19 by examining the consistency of associations across temporal and geographical contexts where biases vary.

METHODS

We used data from 297 intensive care units (ICUs) in England, Wales, and Northern Ireland (Intensive Care National Audit and Research Centre Case Mix Programme). We examined associations of body mass index (BMI) with 30-day mortality, overall and by date and region of ICU admission, among patients admitted with COVID-19 (N = 34,701; February 2020-August 2021) and non-COVID-19 respiratory conditions (N = 25,205; February 2018-August 2019).

RESULTS

Compared with non-COVID-19 patients, COVID-19 patients were younger, less often of a white ethnic group, and more often with extreme obesity. COVID-19 patients had fewer comorbidities but higher mortality. Socio-demographic and comorbidity factors and their associations with BMI and mortality varied more by date than region of ICU admission. Among COVID-19 patients, higher BMI was associated with excess mortality (hazard ratio (HR) per standard deviation (SD) = 1.05; 95% CI = 1.03-1.07). This was evident only for extreme obesity and only during February-April 2020 (HR = 1.52, 95% CI = 1.30-1.77 vs. recommended weight); this weakened thereafter. Among non-COVID-19 patients, higher BMI was associated with lower mortality (HR per SD = 0.83; 95% CI = 0.81-0.86), seen across all overweight/obesity groups and across dates and regions, albeit with a magnitude that varied over time.

CONCLUSIONS

Obesity is associated with higher mortality among COVID-19 patients, but lower mortality among non-COVID-19 respiratory patients. These associations appear vulnerable to confounding/selection bias in both patient groups, questioning the existence or stability of causal effects.

Mendelian Randomization Studies in Atherosclerotic Cardiovascular Diseases

This review aimed to highlight the pivotal role of Mendelian randomization (MR) in advancing atherosclerotic cardiovascular disease (ASCVD) research-a field often hindered by the complexities and limitations of traditional studies. MR, which uses genetic variants as instrumental variables, provides a robust mechanism for inferring causality, offering insights untainted by the confounding factors and biases often prevalent in observational and randomized controlled trials. We explored the significant contributions of MR for elucidating the causal relationship between low-density lipoprotein cholesterol and ASCVD, and analyzed its assumptions and methodological nuances. We discussed issues surrounding instrumental variable selection, pleiotropy, and ethical considerations, in an effort to offer a balanced and insightful analysis. We highlighted the promising integration of MR with emerging technologies and global data sharing, as well as its potential to drive personalized medicine. This review provided a concise yet comprehensive journey into MR's transformative impact on ASCVD research, offering a blend of current insights and challenges, in addition to future prospects. We aimed to serve a valuable resource for those seeking to navigate the intricate pathways of causality and intervention in ASCVD, to aid the development of enhanced understanding and targeted treatment strategies in the future.

The possible causal relationship between COVID-19 and imaging markers of cerebral small vessel disease: a Mendelian randomization study

OBJECTIVES

Observational studies have suggested that SARS-CoV-2 infection may increase the burden of cerebral small vessel disease (CSVD). This study aims to explore the causal correlation between COVID-19 and the imaging markers of CSVD using Mendelian randomization (MR) methods.

METHODS

Summary-level genome-wide association study (GWAS) statistics for COVID-19 susceptibility, hospitalization, and severity were utilized as proxies for exposure. Large-scale meta-analysis GWAS data on three neuroimaging markers of white matter hyperintensity, lacunar stroke, and brain microbleeds, were employed as outcomes. Our primary MR analysis employed the inverse variance weighted (IVW) approach, supplemented by MR-Egger, weighted median, and MR-PRESSO methods. We also conducted multivariable MR analysis to address confounding bias and validate the robustness of the established causal estimates. Comprehensive sensitivity analyses included Cochran's Q test, Egger-intercept analysis, MR-PRESSO, and leave-one-out analysis.

RESULTS

The MR analysis revealed a significant causal correlation between the severity of COVID-19 and an increased risk of lacunar stroke, as demonstrated by the IVW method (ORivw = 1.08, 95% CI: 1.03-1.16, pivw = 0.005, FDR = 0.047). Nevertheless, no causal correlations were observed between COVID-19 susceptibility or hospitalization and any CSVD imaging markers. The robustness and stability of these findings were further confirmed by multivariable MR analysis and comprehensive sensitivity analyses.

DISCUSSION

This study provides compelling evidence of a potential causal effect of severe COVID-19 on the incidence of lacunar stroke, which may bring fresh insights into the understanding of the comorbidity between COVID-19 and CSVD.

Dietary habits, traveling and the living situation potentially influence the susceptibility to SARS-CoV-2 infection: results from healthcare workers participating in the RisCoin Study

PURPOSE

To explore occupational and non-occupational risk and protective factors for the coronavirus disease 2019 (COVID-19) in healthcare workers (HCWs).

METHODS

Serum specimens and questionnaire data were obtained between October 7 and December 16, 2021 from COVID-19-vaccinated HCWs at a quaternary care hospital in Munich, Germany, and were analyzed in the RisCoin Study.

RESULTS

Of 3,696 participants evaluated, 6.6% have had COVID-19 at least once. Multivariate logistic regression analysis identified working in patient care occupations (7.3% had COVID-19, 95% CI 6.4-8.3, Pr = 0.0002), especially as nurses, to be a potential occupation-related COVID-19 risk factor. Non-occupational factors significantly associated with high rates of the disease were contacts to COVID-19 cases in the community (12.8% had COVID-19, 95% CI 10.3-15.8, Pr < 0.0001), being obese (9.9% had COVID-19, 95% CI 7.1-13.5, Pr = 0.0014), and frequent traveling abroad (9.4% had COVID-19, 95% CI 7.1-12.3, Pr = 0.0088). On the contrary, receiving the basic COVID-19 immunization early during the pandemic (5.9% had COVID-19, 95% CI 5.1-6.8, Pr < 0.0001), regular smoking (3.6% had COVID-19, 95% CI 2.1-6.0, Pr = 0.0088), living with the elderly (3.0% had COVID-19, 95% CI 1.0-8.0, Pr = 0.0475), and frequent consumption of ready-to-eat meals (2.6% had COVID-19, 95% CI 1.1-5.4, Pr = 0.0045) were non-occupational factors potentially protecting study participants against COVID-19.

CONCLUSION

The newly discovered associations between the living situation, traveling as well as dietary habits and altered COVID-19 risk can potentially help refine containment measures and, furthermore, contribute to new mechanistic insights that may aid the protection of risk groups and vulnerable individuals.

COVID-19 susceptibility, hospitalization and severity and the risk of brain cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have reported structural changes in the brains of patients with coronavirus disease 2019 (COVID-19); it remains unclear whether these associations are causal.

AIM

We evaluated the causal effects of COVID-19 susceptibility, hospitalization and severity on cortical structures.

DESIGN

Mendelian randomization (MR) study.

METHODS

Data on the different COVID-19 phenotypes were obtained from the latest large-scale genome-wide association study (R7) of the COVID-19 Host Genetics Initiative. Brain structure data, including cortical thickness (TH) and surface area (SA), were obtained from the ENIGMA Consortium. Additionally, we employed the round 5 dataset released in January 2021 as the validation cohort. The inverse-variance weighted (IVW) method was used as the primary analysis in MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. We performed enrichment analysis on the MR analyses that passed the sensitivity analysis filtering.

RESULTS

After IVW and sensitivity analyses, we observed causal associations between COVID-19 susceptibility and rostral middle frontal SAw (P = 0.0308, β = -39.1236), cuneus THw (P = 0.0170, β = -0.0121), medial orbitofrontal THw (P = 0.0002, β = 0.0225), postcentral THw (P = 0.0217, β = -0.0106), temporal pole THw (P = 0.0077, β = 0.0359), medial orbitofrontal SAnw (P = 0.0106, β = -24.0397), medial orbitofrontal THnw (P = 0.0007, β = 0.0232), paracentral SAnw (P = 0.0483, β = -20.1442), rostral middle frontal SAnw (P = 0.0368, β = -81.9719) and temporal pole THnw (P = 0.0429, β = 0.0353). COVID-19 hospitalization had causal effects on medial orbitofrontal THw (P = 0.0053, β = 0.0063), postcentral THw (P = 0.0143, β = -0.0042), entorhinal THnw (P = 0.0142, β = 0.0142), medial orbitofrontal THnw (P = 0.0147, β = 0.0065) and paracentral SAnw (P = 0.0119, β = -7.9970). COVID-19 severity had causal effects on rostral middle frontal SAw (P = 0.0122, β = -11.8296), medial orbitofrontal THw (P = 0.0155, β = 0.0038), superior parietal THw (P = 0.0291, β = -0.0021), lingual SAnw (P = 0.0202, β = -11.5270), medial orbitofrontal THnw (P = 0.0290, β = 0.0039), paracentral SAnw (P = 0.0180, β = -5.7744) and pars triangularis SAnw (P = 0.0151, β = -5.4520).

CONCLUSION

Our MR results demonstrate a causal relationship between different COVID-19 phenotypes and cortical structures.

The association between COVID-19 and infertility: Mendelian randomization analysis

Since December 2019, COVID-19 has triggered a global pandemic. The association of COVID-19 with the long-term reproductive situation of women and males is not clear. Thus, our aim was to assess the causal association between COVID-19 and infertility using Mendelian randomization (MR) analysis based on the OpenGWAS database. Two-sample MR analysis was conducted using one genome-wide association study (GWAS) on COVID-19 and infertility in individuals of European ancestry. The summary data of genetic variation come from the GWAS in European populations. We applied several MR methods, including MR Egger, weighted median, inverse variance weighted, simple mode, weighted mode, to test causal relationships. After observing the statistical analysis results of MR, we conducted sensitivity analysis to test robustness. After gene prediction, it was found that there was no clear causal relationship between COVID-19 and male infertility in MR analysis [OR 0.4702 (95% CI, 0.1569-1.4093), P = .178]. Moreover, COVID-19 was not associated with female infertility [OR 0.9981 (95% CI, 0.763-1.544), P = .646]. Sensitivity analysis showed that the MR results were robust [level pleiotropy, male: (MR-Egger, intercept = 0.1967434; se = 0.1186876; P = .2392406); female: (MR-Egger, intercept = -0.05902506; se = 0.05362049; P = .3211367)]. To further validate the impact of COVID-19 on infertility, we added a covariate (sex hormone binding global levels, abortion) to the MR analysis, which is a multivariate MR analysis. According to univariate and multivariate MR analyses, the evidence does not support that COVID-19 is a causal risk factor for infertility in European population. This information can provide information for doctors in reproductive centers when managing infertility patients.

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

BACKGROUND

Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

RESULTS

Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

CONCLUSIONS

We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

Causal association of COVID-19 with brain structure changes: Findings from a non-overlapping 2-sample Mendelian randomization study

Recent cohort studies suggested that SARS-CoV-2 infection is associated with changes in brain structure. However, the potential causal relationship remains unclear. We performed a two-sample Mendelian randomization analysis to determine whether genetic susceptibility of COVID-19 is causally associated with changes in cortical and subcortical areas of the brain. This 2-sample MR (Mendelian Randomization) study is an instrumental variable analysis of data from the COVID-19 Host Genetics Initiative (HGI) meta-analyses round 5 excluding UK Biobank participants (COVID-19 infection, N = 1,348,701; COVID-19 severity, N = 1,557,411), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Global and regional cortical measures, N = 33,709; combined hemispheric subcortical volumes, N = 38,851), and UK Biobank (left/right subcortical volumes, N = 19,629). A replication analysis was performed on summary statistics from different COVID-19 GWAS study (COVID-19 infection, N = 80,932; COVID-19 severity, N = 72,733). We found that the genetic susceptibility of COVID-19 was not significantly associated with changes in brain structures, including cortical and subcortical brain structure. Similar results were observed for different (1) MR estimates, (2) COVID-19 GWAS summary statistics, and (3) definitions of COVID-19 infection and severity. This study suggests that the genetic susceptibility of COVID-19 is not causally associated with changes in cortical and subcortical brain structure.

An updated meta-analysis of Chinese herbal medicine for the prevention of COVID-19 based on Western-Eastern medicine

Background and aims: Chinese herbal medicine (CHM) was used to prevent and treat coronavirus disease 2019 (COVID-19) in clinical practices. Many studies have demonstrated that the combination of CHM and Western medicine can be more effective in treating COVID-19 compared to Western medicine alone. However, evidence-based studies on the prevention in undiagnosed or suspected cases remain scarce. This systematic review and meta-analysis aimed to investigate the effectiveness of CHM in preventing recurrent, new, or suspected COVID-19 diseases. Methods: We conducted a comprehensive search using ten databases including articles published between December 2019 and September 2023. This search aimed to identify studies investigating the use of CHM to prevent COVID-19. Heterogeneity was assessed by a random-effects model. The relative risk (RR) and mean differences were calculated using 95% confidence intervals (CI). The modified Jadad Scale and the Newcastle-Ottawa Scale (NOS) were employed to evaluate the quality of randomized controlled trials and cohort studies, respectively. Results: Seventeen studies with a total of 47,351 patients were included. Results revealed that CHM significantly reduced the incidence of COVID-19 (RR = 0.24, 95% CI = 0.11-0.53, p = 0.0004), influenza (RR = 0.37, 95% CI = 0.18-0.76, p = 0.007), and severe pneumonia exacerbation rate (RR = 0.17, 95% CI = 0.05-0.64, p = 0.009) compared to non-treatment or conventional control group. Evidence evaluation indicated moderate quality evidence for COVID-19 incidence and serum complement components C3 and C4 in randomized controlled trials. For the incidence of influenza and severe pneumonia in RCTs as well as the ratio of CD4+/CD8+ lymphocytes, the evidence quality was low. The remaining outcomes including the disappearance rate of symptoms and adverse reactions were deemed to be of very low quality. Conclusion: CHM presents a promising therapeutic option for the prevention of COVID-19. However, additional high-quality clinical trials are needed to further strengthen evidential integrity.

Association between COVID-19 and myasthenia gravis (MG): A genetic correlation and Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between coronavirus disease 2019 (COVID-19) and myasthenia gravis (MG). Here, we aimed to estimate the genetic correlation and causal relationship between COVID-19 susceptibility, hospitalization, severity, and MG phenotypes using linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) approach.

METHODS

Summary statistics of COVID-19 susceptibility, hospitalization, and severity were used as instrumental variables for exposure traits. Large-scale genome-wide association study (GWAS) data for MG were used as outcome traits. The inverse variance weighted approach was used for the main MR analysis, complemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analysis was implemented using Cochran's Q test, MR-PRESSO method, and MR-Egger intercept test.

RESULTS

LDSC analysis did not reveal any genetic correlation among COVID-19 susceptibility, hospitalization, severity, and MG phenotypes, including MG, early-onset MG, and late-onset MG (p > .05). Our MR analysis did not provide evidence supporting a causal effect of COVID-19 susceptibility, hospitalization, or severity on MG phenotypes (p > .05). Extensive sensitivity analysis strengthened the robustness and consistency of the MR estimates.

CONCLUSION

Our study did not find evidence of a genetic correlation or causal relationship among COVID-19 susceptibility, hospitalization, severity, and MG. Future studies with more GWAS data are needed to evaluate the association between COVID-19 phenotypes and MG and its subgroups.

A network meta-analysis of association between cardiometabolic risk factors and COVID-19 outcome severity

BACKGROUND

Cardiometabolic comorbidities have been associated with a higher risk of COVID-19 severity and mortality, but more investigations are needed to determine which comorbidity is more detrimental.

METHODS

Embase, Emcare, and MEDLINE were searched systematically for prospective and retrospective studies assessing the associations of cardiometabolic risk factors and COVID-19 outcomes of hospitalization, severity, and mortality among COVID-19-diagnosed patients. Literature search was performed from first publication to May 19, 2021. Study quality was assessed by the Newcastle-Ottawa Scale.

RESULTS

From the literature search, 301 studies suggested that all included cardiometabolic risk factors were associated with a higher risk of COVID-19 hospitalization, severity, and mortality, except that overweight was associated with a decreased risk of mortality (relative risk [RR] 0.88; 95% CI, 0.80-0.98). Patients with diabetes (RR 1.46; 95% CI, 1.45-1.47) were most likely to be hospitalized; patients with heart failure had the highest risk for severe COVID-19 outcomes (RR 1.89; 95% CI, 1.71-2.09); while patients with stroke were most susceptible to overall mortality (RR 1.99; 95% CI, 1.90-2.08). In the network meta-analysis, cerebrovascular disease had the highest impact (RR 1.69; 95% CI, 1.65-1.73) on COVID-19 outcomes compared to other cardiometabolic risk factors. For different combinations of risk factors, cardiovascular disease and diabetes combined (RR 6.98; 95% CI, 5.28-9.22) was more detrimental than others.

CONCLUSIONS

Considering the high prevalence of cardiometabolic comorbidities and risk of all severe outcomes, patients with cardiometabolic comorbidities should be prioritized in vaccination and treatment development of COVID-19.

Cardiometabolic risk management: insights from a European Society of Cardiology Cardiovascular Round Table

Metabolic comorbidities are common in patients with cardiorenal disease; they can cause atherosclerotic cardiovascular disease (ASCVD), speed progression, and adversely affect prognosis. Common comorbidities are Type 2 diabetes mellitus (T2DM), obesity/overweight, chronic kidney disease (CKD), and chronic liver disease. The cardiovascular system, kidneys, and liver are linked to many of the same risk factors (e.g. dyslipidaemia, hypertension, tobacco use, diabetes, and central/truncal obesity), and shared metabolic and functional abnormalities lead to damage throughout these organs via overlapping pathophysiological pathways. The COVID-19 pandemic has further complicated the management of cardiometabolic diseases. Obesity, T2DM, CKD, and liver disease are associated with increased risk of poor outcomes of COVID-19 infection, and conversely, COVID-19 can lead to worsening of pre-existing ASCVD. The high rates of these comorbidities highlight the need to improve recognition and treatment of ASCVD in patients with obesity, insulin resistance or T2DM, chronic liver diseases, and CKD and equally, to improve recognition and treatment of these diseases in patients with ASCVD. Strategies to prevent and manage cardiometabolic diseases include lifestyle modification, pharmacotherapy, and surgery. There is a need for more programmes at the societal level to encourage a healthy diet and physical activity. Many pharmacotherapies offer mechanism-based approaches that can target multiple pathophysiological pathways across diseases. These include sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists, selective mineralocorticoid receptor antagonists, and combined glucose-dependent insulinotropic peptide/glucagon-like peptide-1 receptor agonist. Non-surgical and surgical weight loss strategies can improve cardiometabolic disorders in individuals living with obesity. New biomarkers under investigation may help in the early identification of individuals at risk and reveal new treatment targets.

Effectiveness of behavioural change interventions on physical activity, diet and body mass index of public primary healthcare users in Kosovo: the KOSCO cohort

BACKGROUND

Prevalent physical inactivity and poor nutrition contribute to high non-communicable disease (NCD) morbidity and mortality in Kosovo. To improve health services for patients with NCD the Accessible Quality Healthcare project developed behaviour change interventions following the principles of the WHO Package of Essential NCD (PEN) protocol. They were implemented into the public primary healthcare (PHC) system of five early-stage implementation municipalities (ESIM, 2018) and seven late-stage implementation municipalities (2020).

OBJECTIVE

To assess the effect of the behaviour change interventions; motivational stages of behaviour change for physical activity and nutrition; and body mass index (BMI).

DESIGN

Prospective cohort study.

DATA COLLECTION AND ANALYSIS

We included 891 public PHC users aged 40 years and above, who were enrolled in the KOSCO (Kosovo Non-Communicable Disease Cohort) cohort in 2019 and followed-up biannually until February 2021. The PHC users who consulted for themselves any health service were approached and recruited for cohort participation. Each participant contributed up to four self-reports of nutrition and physical activity, and up to three reports of motivation to change for a better lifestyle. These outcomes were modelled prospectively with robust mixed-effects Poisson regressions. The association between behaviour change interventions and BMI was quantified using linear regression.

RESULTS

There was a high rate of smokers 20.5% and obesity 53.1%, and high rates of self-reported diagnoses of diabetes: 57.1%; hypertension 62.6%. We found no effect of residing in an ESIM, but adherence to both guidelines was higher in ESIM at the latest follow-up time point. ESIM residence was also associated with a twofold increase in the probability of reporting a high motivation for a better lifestyle and with a statistically non-significant decrease in BMI of -0.14 kg/m2 (95% CI: -0.46 to 0.19) at the latest follow-up.

CONCLUSION

The longitudinal results extend evidence on the effect of WHO PEN protocol in promoting physical activity and nutritional behaviour in the Kosovo context.

Biomarkers of glucose homeostasis as mediators of the relationship of body mass index and waist circumference with COVID-19 outcomes among postmenopausal women: The Women's Health Initiative

BACKGROUND & AIMS

Systematic reviews, meta-analyses and Mendelian randomization studies suggest that cardiometabolic diseases may be associated with COVID-19 risk and prognosis, with evidence implicating insulin resistance (IR) as a common biological mechanism. As driving factors for IR, we examined body mass index (BMI) and waist circumference (WC) among postmenopausal women in association with COVID-19 outcomes (positivity and hospitalization), and the role of glucose homeostasis as a mediator of this relationship.

METHODS

Associations of BMI and WC at baseline (1993-1998) with COVID-19 outcomes collected at Survey 1 (June-December, 2020) and/or Survey 2 (September-December, 2021) were evaluated among 42,770 Women's Health Initiative (WHI) participants (baseline age: 59.36 years) of whom 16,526 self-reported having taken ≥1 COVID-19 test, with 1242 reporting ≥1 positive COVID-19 test and 362 reporting ≥1 COVID-19 hospitalization. We applied logistic regression and causal mediation analyses to sub-samples with available fasting biomarkers of glucose homeostasis (glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, Homeostasis Model Assessment for β-cell function, Quantitative Insulin-sensitivity Check Index, Triglyceride-Glucose index (TyG)) at baseline, whereby 57 of 759 reported COVID-19 test positivity and 23 of 1896 reported COVID-19 hospitalization.

RESULTS

In fully adjusted models, higher BMI, WC and TyG were associated with COVID-19 test positivity and hospitalization. Glucose concentrations mediated associations of BMI and WC with COVID-19 positivity, whereas TyG mediated BMI and WC's associations with COVID-19 hospitalization.

CONCLUSIONS

Obesity and central obesity markers collected an average of 24 years prior were associated with COVID-19 outcomes among postmenopausal women. Glucose concentration and TyG partly mediated these associations.

A novel penalized inverse-variance weighted estimator for Mendelian randomization with applications to COVID-19 outcomes

Mendelian randomization utilizes genetic variants as instrumental variables (IVs) to estimate the causal effect of an exposure variable on an outcome of interest even in the presence of unmeasured confounders. However, the popular inverse-variance weighted (IVW) estimator could be biased in the presence of weak IVs, a common challenge in MR studies. In this article, we develop a novel penalized inverse-variance weighted (pIVW) estimator, which adjusts the original IVW estimator to account for the weak IV issue by using a penalization approach to prevent the denominator of the pIVW estimator from being close to zero. Moreover, we adjust the variance estimation of the pIVW estimator to account for the presence of balanced horizontal pleiotropy. We show that the recently proposed debiased IVW (dIVW) estimator is a special case of our proposed pIVW estimator. We further prove that the pIVW estimator has smaller bias and variance than the dIVW estimator under some regularity conditions. We also conduct extensive simulation studies to demonstrate the performance of the proposed pIVW estimator. Furthermore, we apply the pIVW estimator to estimate the causal effects of five obesity-related exposures on three coronavirus disease 2019 (COVID-19) outcomes. Notably, we find that hypertensive disease is associated with an increased risk of hospitalized COVID-19; and peripheral vascular disease and higher body mass index are associated with increased risks of COVID-19 infection, hospitalized COVID-19, and critically ill COVID-19.

COVID-19 and cognitive performance: a Mendelian randomization study

Background

A substantial proportion of individuals with COVID-19 experienced cognitive impairment after resolution of SARS-CoV-2 infection. We aimed to evaluate whether genetic liability to SARS-CoV-2 infection per se, or more severe COVID-19, is causally linked to cognitive deficit.

Methods

We firstly performed univariable Mendelian randomization (MR) analysis to examine whether genetic liability to SARS-CoV-2 infection, hospitalized and severe COVID-19 is causally associated with cognitive performance. To dissect the causal pathway, multivariable MR (MVMR) analysis was conducted by adjusting for five inflammatory markers [C-reactive protein, interleukin (IL)-1β, IL-6, IL-8, and tumour necrosis factor α, as proxies of systemic inflammation].

Results

In univariable MR analysis, host genetic liability to SARS-CoV-2 infection was associated with lower cognitive performance [inverse variance weighted (IVW) analysis, estimate: -0.023; 95% Confidence Interval (CI): -0.038 to -0.009]. Such causal association was attenuated in MVMR analysis when we adjusted for the five correlated inflammatory markers in one analysis (IVW analysis, estimate: -0.022; 95% CI: -0.049 to 0.004). There was insufficient evidence of association for genetic liability to hospitalized and severe COVID-19 with cognitive performance.

Conclusion

The causal effect of host genetic liability to SARS-CoV-2 infection on reduced cognitive performance may be mediated by systemic inflammation. Future studies examining whether anti-inflammatory agents could alleviate cognitive impairment in SARS-CoV-2-infected individuals are warranted.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity

BACKGROUND

Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity.

METHODS

Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship.

RESULTS

Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity.

CONCLUSIONS

This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.

The remote diet intervention to reduce Long COVID symptoms trial (ReDIRECT): protocol for a randomised controlled trial to determine the effectiveness and cost-effectiveness of a remotely delivered supported weight management programme for people with Long COVID and excess weight, with personalised improvement goals

Objectves

The Remote Diet Intervention to Reduce Long COVID Symptoms Trial (ReDIRECT) evaluates whether the digitally delivered, evidence-based, cost-effective Counterweight-Plus weight management programme improves symptoms of Long COVID in people with overweight/obesity.

Methods

Baseline randomised, non-blinded design with 240 participants allocated in a 1:1 ratio either to continue usual care or to add the remotely delivered Counterweight-Plus weight management programme, which includes a Counterweight dietitian supported delivery of 12 weeks total diet replacement, food reintroduction, and long-term weight loss maintenance. Randomisation is achieved by accessing a web-based randomisation system incorporated into the study web portal developed by a registered Clinical Trials Unit. We are using an innovative approach to outcome personalisation, with each participant selecting their most dominant Long COVID symptom as their primary outcome assessed at six months. Participants in the control arm enter the weight management programme after six months. We are recruiting participants from social media and existing networks (e.g., Long COVID Scotland groups), through newspaper advertisements and from primary care. Main inclusion criteria: people with Long COVID symptoms persisting > three months, aged 18 years or above, body mass index (BMI) above 27kg/m 2 (>25kg/m 2 for South Asians). The trial includes a process evaluation (involving qualitative interviews with participants and analysis of data on dose, fidelity and reach of the intervention) and economic evaluation (within-trial and long-term cost-utility analyses).

Anticipated results

The recruitment for this study started in December 2021 and ended in July 2022. Project results are not yet available and will be shared via peer-reviewed publication once the six-months outcomes have been analysed.

Trial registration

Current Controlled Trials ISRCTN12595520.

Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis

AIMS/HYPOTHESIS

To provide a systematic overview of the current body of evidence on high-risk phenotypes of diabetes associated with COVID-19 severity and death.

METHODS

This is the first update of our recently published living systematic review and meta-analysis. Observational studies investigating phenotypes in individuals with diabetes and confirmed SARS-CoV-2 infection with regard to COVID-19-related death and severity were included. The literature search was conducted from inception up to 14 February 2022 in PubMed, Epistemonikos, Web of Science and the COVID-19 Research Database and updated using PubMed alert to 1 December 2022. A random-effects meta-analysis was used to calculate summary relative risks (SRRs) with 95% CIs. The risk of bias was evaluated using the Quality in Prognosis Studies (QUIPS) tool and the certainty of evidence using the GRADE approach.

RESULTS

A total of 169 articles (147 new studies) based on approximately 900,000 individuals were included. We conducted 177 meta-analyses (83 on COVID-19-related death and 94 on COVID-19 severity). Certainty of evidence was strengthened for associations between male sex, older age, blood glucose level at admission, chronic insulin use, chronic metformin use (inversely) and pre-existing comorbidities (CVD, chronic kidney disease, chronic obstructive pulmonary disease) and COVID-19-related death. New evidence with moderate to high certainty emerged for the association between obesity (SRR [95% CI] 1.18 [1.04, 1.34], n=21 studies), HbA1c (53-75 mmol/mol [7-9%]: 1.18 [1.06, 1.32], n=8), chronic glucagon-like peptide-1 receptor agonist use (0.83 [0.71, 0.97], n=9), pre-existing heart failure (1.33 [1.21, 1.47], n=14), pre-existing liver disease (1.40 [1.17, 1.67], n=6), the Charlson index (per 1 unit increase: 1.33 [1.13, 1.57], n=2), high levels of C-reactive protein (per 5 mg/l increase: 1.07 [1.02, 1.12], n=10), aspartate aminotransferase level (per 5 U/l increase: 1.28 [1.06, 1.54], n=5), eGFR (per 10 ml/min per 1.73 m2 increase: 0.80 [0.71, 0.90], n=6), lactate dehydrogenase level (per 10 U/l increase: 1.03 [1.01, 1.04], n=7) and lymphocyte count (per 1×109/l increase: 0.59 [0.40, 0.86], n=6) and COVID-19-related death. Similar associations were observed between risk phenotypes of diabetes and severity of COVID-19, with some new evidence on existing COVID-19  vaccination status (0.32 [0.26, 0.38], n=3), pre-existing hypertension (1.23 [1.14, 1.33], n=49), neuropathy and cancer, and high IL-6 levels. A limitation of this study is that the included studies are observational in nature and residual or unmeasured confounding cannot be ruled out.

CONCLUSIONS/INTERPRETATION

Individuals with a more severe course of diabetes and pre-existing comorbidities had a poorer prognosis of COVID-19 than individuals with a milder course of the disease.

REGISTRATION

PROSPERO registration no. CRD42020193692.

PREVIOUS VERSION

This is a living systematic review and meta-analysis. The previous version can be found at https://link.springer.com/article/10.1007/s00125-021-05458-8 FUNDING: The German Diabetes Center (DDZ) is funded by the German Federal Ministry of Health and the Ministry of Culture and Science of the State North Rhine-Westphalia. This study was supported in part by a grant from the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD).

Causal association of COVID-19 with brain structure changes: Findings from a non-overlapping 2-sample Mendelian randomization study

Recent cohort studies suggested that SARS-CoV-2 infection is associated with changes in brain structure. However, the potential causal relationship remains unclear. We performed a two-sample Mendelian randomization analysis to determine whether genetic susceptibility of COVID-19 is causally associated with changes in cortical and subcortical areas of the brain. This 2-sample MR (Mendelian Randomization) study is an instrumental variable analysis of data from the COVID-19 Host Genetics Initiative (HGI) meta-analyses round 5 excluding UK Biobank participants (COVID-19 infection, N=1,348,701; COVID-19 severity, N=1,557,411), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Global and regional cortical measures, N=33,709; combined hemispheric subcortical volumes, N=38,851), and UK Biobank (left/right subcortical volumes, N=19,629). A replication analysis was performed on summary statistics from different COVID-19 GWAS study (COVID-19 infection, N=80,932; COVID-19 severity, N=72,733). We found that the genetic susceptibility of COVID-19 was not significantly associated with changes in brain structures, including cortical and subcortical brain structure. Similar results were observed for different (1) MR estimates, (2) COVID-19 GWAS summary statistics, and (3) definitions of COVID-19 infection and severity. This study suggests that the genetic susceptibility of COVID-19 is not causally associated with changes in cortical and subcortical brain structure.

Biomarkers Associated With Severe COVID-19 Among Populations With High Cardiometabolic Risk: A 2-Sample Mendelian Randomization Study

Importance

Cardiometabolic parameters are established risk factors for COVID-19 severity. The identification of causal or protective biomarkers for COVID-19 severity may facilitate the development of novel therapies.

Objective

To identify protein biomarkers that promote or reduce COVID-19 severity and that mediate the association of cardiometabolic risk factors with COVID-19 severity.

Design, Setting, and Participants

This genetic association study using 2-sample mendelian randomization (MR) was conducted in 2022 to investigate associations among cardiometabolic risk factors, circulating biomarkers, and COVID-19 hospitalization. Inputs for MR included genetic and proteomic data from 4147 participants with dysglycemia and cardiovascular risk factors collected through the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Genome-wide association study summary statistics were obtained from (1) 3 additional independent plasma proteome studies, (2) genetic consortia for selected cardiometabolic risk factors (including body mass index [BMI], type 2 diabetes, type 1 diabetes, and systolic blood pressure; all n >10 000), and (3) the COVID-19 Host Genetics Initiative (n = 5773 hospitalized and 15 497 nonhospitalized case participants with COVID-19). Data analysis was performed in July 2022.

Exposures

Genetically determined concentrations of 235 circulating proteins assayed with a multiplex biomarker panel from the ORIGIN trial for the initial analysis.

Main Outcomes and Measures

Hospitalization status of individuals from the COVID-19 Host Genetics Initiative with a positive COVID-19 test result.

Results

Among 235 biomarkers tested in samples totaling 22 101 individuals, MR analysis showed that higher kidney injury molecule-1 (KIM-1) levels reduced the likelihood of COVID-19 hospitalization (odds ratio [OR] per SD increase in KIM-1 levels, 0.86 [95% CI, 0.79-0.93]). A meta-analysis validated the protective association with no observed directional pleiotropy (OR per SD increase in KIM-1 levels, 0.91 [95% CI, 0.88-0.95]). Of the cardiometabolic risk factors studied, only BMI was associated with KIM-1 levels (0.17 SD increase in biomarker level per 1 kg/m2 [95% CI, 0.08-0.26]) and COVID-19 hospitalization (OR per 1-SD biomarker level, 1.33 [95% CI, 1.18-1.50]). Multivariable MR analysis also revealed that KIM-1 partially mitigated the association of BMI with COVID-19 hospitalization, reducing it by 10 percentage points (OR adjusted for KIM-1 level per 1 kg/m2, 1.23 [95% CI, 1.06-1.43]).

Conclusions and Relevance

In this genetic association study, KIM-1 was identified as a potential mitigator of COVID-19 severity, possibly attenuating the increased risk of COVID-19 hospitalization among individuals with high BMI. Further studies are required to better understand the underlying biological mechanisms.

The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

BACKGROUND

Poor sleep is associated with an increased risk of infections and all-cause mortality but the causal direction between poor sleep and respiratory infections has remained unclear. We examined if poor sleep contributes as a causal risk factor to respiratory infections.

METHODS

We used data on insomnia, influenza and upper respiratory infections (URIs) from primary care and hospital records in the UK Biobank (N ≈ 231,000) and FinnGen (N ≈ 392,000). We computed logistic regression to assess association between poor sleep and infections, disease free survival hazard ratios, and performed Mendelian randomization analyses to assess causality.

FINDINGS

Utilizing 23 years of registry data and follow-up, we discovered that insomnia diagnosis associated with increased risk for infections (FinnGen influenza Cox's proportional hazard (CPH) HR = 4.34 [3.90, 4.83], P = 4.16 × 10-159, UK Biobank influenza CPH HR = 1.54 [1.37, 1.73], P = 2.49 × 10-13). Mendelian randomization indicated that insomnia causally predisposed to influenza (inverse-variance weighted (IVW) OR = 1.65, P = 5.86 × 10-7), URI (IVW OR = 1.94, P = 8.14 × 10-31), COVID-19 infection (IVW OR = 1.08, P = 0.037) and risk of hospitalization from COVID-19 (IVW OR = 1.47, P = 4.96 × 10-5).

INTERPRETATION

Our findings indicate that chronic poor sleep is a causal risk factor for contracting respiratory infections, and in addition contributes to the severity of respiratory infections. These findings highlight the role of sleep in maintaining sufficient immune response against pathogens.

FUNDING

Instrumentarium Science Foundation, Academy of Finland, Signe and Ane Gyllenberg Foundation, National Institutes of Health.

The bidirectional interaction of COVID-19 infections and lipoproteins

COVID-19 infections decrease total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I, A-II, and B levels while triglyceride levels may be increased or inappropriately normal for the poor nutritional status. The degree of reduction in total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I are predictive of mortality. With recovery lipid/lipoprotein levels return towards pre-infection levels and studies have even suggested an increased risk of dyslipidemia post-COVID-19 infection. The potential mechanisms for these changes in lipid and lipoprotein levels are discussed. Decreased HDL-C and apolipoprotein A-I levels measured many years prior to COVID-19 infections are associated with an increased risk of severe COVID-19 infections while LDL-C, apolipoprotein B, Lp (a), and triglyceride levels were not consistently associated with an increased risk. Finally, data suggest that omega-3-fatty acids and PCSK9 inhibitors may reduce the severity of COVID-19 infections. Thus, COVID-19 infections alter lipid/lipoprotein levels and HDL-C levels may affect the risk of developing COVID-19 infections.

Effects of social confinement during the first wave of COVID-19 in Mexico City

Background

The COVID-19 pandemic led to global social confinement that had a significant impact on people's lives. This includes changes such as increased loneliness and isolation, changes in sleep patterns and social habits, increased substance use and domestic violence, and decreased physical activities. In some cases, it has increased mental health problems, such as anxiety, depression, and post-traumatic stress disorder.

Objective

The objective of this study is to analyze the living conditions that arose during social confinement in the first wave of COVID-19 within a group of volunteers in Mexico City.

Methods

This is a descriptive and cross-sectional analysis of the experiences of volunteers during social confinement from 20 March 2020 to 20 December 2020. The study analyzes the impact of confinement on family life, work, mental health, physical activity, social life, and domestic violence. A maximum likelihood generalized linear model is used to determine the association between domestic violence and demographic and health-related factors.

Results

The findings indicate that social confinement had a significant impact on the participants, resulting in difficulties within families and vulnerable conditions for individuals. Gender and social level differences were observed in work and mental health. Physical activity and social life were also modified. We found that suffering from domestic violence was significantly associated with being unmarried (OR = 1.4454, p-value = 0.0479), lack of self-care in feeding habits (OR = 2.3159, p-value = 0.0084), and most notably, having suffered from a symptomatic COVID-19 infection (OR = 4.0099, p-value = 0.0009). Despite public policy to support vulnerable populations during confinement, only a small proportion of the studied population reported benefiting from it, suggesting areas for improvement in policy.

Conclusion

The findings of this study suggest that social confinement during the COVID-19 pandemic had a significant impact on the living conditions of people in Mexico City. Modified circumstances on families and individuals, included increased domestic violence. The results can inform policy decisions to improve the living conditions of vulnerable populations during times of social confinement.

Associations of Combustible Cigarette, Electronic Cigarette, and Dual Use With COVID Infection and Severity in the U.S.: A Cross-sectional Analysis of the 2021 National Health Information Survey

Given the potential respiratory health risks, the association of COVID infection and the use of combustible cigarettes, electronic nicotine delivery systems (ENDS), and concurrent dual use is a priority for public health. Many published reports have not accounted for known covarying factors. This study sought to calculate adjusted odds ratios for self-reported COVID infection and disease severity as a function of smoking and ENDS use, while accounting for factors known to influence COVID infection and disease severity (i.e., age, sex, race and ethnicity, socioeconomic status and educational attainment, rural or urban environment, self-reported diabetes, COPD, coronary heart disease, and obesity status). Data from the 2021 U.S. National Health Interview Survey, a cross-sectional questionnaire design, were used to calculate both unadjusted and adjusted odds ratios for self-reported COVID infection and severity of symptoms. Results indicate that combustible cigarette use is associated with a lower likelihood of self-reported COVID infection relative to non-use of tobacco products (AOR = .64; 95% CI [.55, .74]), whereas ENDS use is associated with a higher likelihood of self-reported COVID infection (AOR = 1.30; 95% CI [1.04, 1.63]). There was no significant difference in COVID infection among dual users (ENDS and combustible use) when compared with non-users. Adjusting for covarying factors did not substantially change the results. There were no significant differences in COVID disease severity between those of varying smoking status. Future research should examine the relationship between smoking status and COVID infection and disease severity utilizing longitudinal study designs and non-self-report measures of smoking status (e.g., the biomarker cotinine), COVID infection (e.g., positive tests), and disease severity (e.g., hospitalizations, ventilator assistance, mortality, and ongoing symptoms of long COVID).

Association Between Diabetes Severity and Risks of COVID-19 Infection and Outcomes

BACKGROUND

Little is known about whether diabetes increases the risk of COVID-19 infection and whether measures of diabetes severity are related to COVID-19 outcomes.

OBJECTIVE

Investigate diabetes severity measures as potential risk factors for COVID-19 infection and COVID-19 outcomes.

DESIGN, PARTICIPANTS, MEASURES

In integrated healthcare systems in Colorado, Oregon, and Washington, we identified a cohort of adults on February 29, 2020 (n = 1,086,918) and conducted follow-up through February 28, 2021. Electronic health data and death certificates were used to identify markers of diabetes severity, covariates, and outcomes. Outcomes were COVID-19 infection (positive nucleic acid antigen test, COVID-19 hospitalization, or COVID-19 death) and severe COVID-19 (invasive mechanical ventilation or COVID-19 death). Individuals with diabetes (n = 142,340) and categories of diabetes severity measures were compared with a referent group with no diabetes (n = 944,578), adjusting for demographic variables, neighborhood deprivation index, body mass index, and comorbidities.

RESULTS

Of 30,935 patients with COVID-19 infection, 996 met the criteria for severe COVID-19. Type 1 (odds ratio [OR] 1.41, 95% CI 1.27-1.57) and type 2 diabetes (OR 1.27, 95% CI 1.23-1.31) were associated with increased risk of COVID-19 infection. Insulin treatment was associated with greater COVID-19 infection risk (OR 1.43, 95% CI 1.34-1.52) than treatment with non-insulin drugs (OR 1.26, 95% 1.20-1.33) or no treatment (OR 1.24; 1.18-1.29). The relationship between glycemic control and COVID-19 infection risk was dose-dependent: from an OR of 1.21 (95% CI 1.15-1.26) for hemoglobin A1c (HbA1c) < 7% to an OR of 1.62 (95% CI 1.51-1.75) for HbA1c ≥ 9%. Risk factors for severe COVID-19 were type 1 diabetes (OR 2.87; 95% CI 1.99-4.15), type 2 diabetes (OR 1.80; 95% CI 1.55-2.09), insulin treatment (OR 2.65; 95% CI 2.13-3.28), and HbA1c ≥ 9% (OR 2.61; 95% CI 1.94-3.52).

CONCLUSIONS

Diabetes and greater diabetes severity were associated with increased risks of COVID-19 infection and worse COVID-19 outcomes.

Invasive Mechanical Ventilation and Death Was More Likely in Patients with Lower LDL Cholesterol Levels during COVID-19 Hospitalization: A Retrospective Propensity-Matched Cohort Study

Hyperlipidemia has been associated with worse outcomes in patients with Coronavirus disease 2019 (COVID-19). However, lower LDL-C (low-density lipoprotein cholesterol) levels have been associated with increased COVID-19 severity and mortality. We conducted a retrospective observational study of patients with COVID-19 admitted to New York City Health and Hospitals from 1 March 2020 to 31 October 2020, comparing pre-COVID-19 LDL-C levels or LDL-C levels obtained during COVID-19 hospitalization, with the need for invasive mechanical ventilation and death. Propensity score matching was performed using logistic regression models, and standardized mean differences were calculated. A total of 3020 patients (median age 61 years; 36% women) were included. In the matched cohort, on multivariate logistic regression analysis, LDL was inversely associated with in-hospital death (OR: 0.99, 95% CI: 0.986–0.999, p = 0.036). As a categorical variable, LDL > 70 mg/dL was associated with 47% lower likelihood of invasive mechanical ventilation (OR: 0.53, 95% CI: 0.29–0.95, p = 0.034). No significant association between pre-COVID-19 LDL and death or invasive mechanical ventilation was found (OR: 1.00, 95% CI 0.99–1.01, p = 0.833). Low LDL-C level measured during COVID-19 was associated with a higher likelihood of invasive mechanical ventilation and in-hospital death. A similar association was not found between pre-COVID-19 LDL-C and these outcomes. LDL-C levels obtained during COVID-19 are likely not reflective of the baseline lipid profile.

Estimating Burden of Mortality due to Excess Body Mass Index in the US Adult Population by Combining Evidence from a Mendelian Randomization Study and National Health Surveys

Importance

Assessment of the burden of mortality due to excess body weight in a population and its subgroups is important for designing health policies for interventions. Mendelian randomization (MR) studies can provide an opportunity to correct for unmeasured confounding bias present in observational studies, but such evidence has not been used to assess population burden of mortality due to excess BMI.

Objective

Combine results from a recent Mendelian randomization (MR) study and data from the National Health Surveys to estimate preventable fraction (PF) of 10-year all-cause and cause-specific mortality by different degrees of BMI reduction in the US adult population and underlying risk strata.

Designs

We use cross-sectional data on the distribution of BMI and other risk factors of mortality from the National Health and Nutritional Examination Surveys (NHANES) across two-time spans (1999-2006 and 2017-2018). We use linked data from National Death Index to characterize the observed risk of 10-year mortality associated with BMI and other risk factors based on the NHANES 1999-2006 cohort. We further import results from an external MR study on linear and non-linear effects of BMI and use novel methods to estimate preventable fraction (PF) for deaths under different counterfactual scenarios of BMI reduction in the NHANES population.

Settings

Primary analysis is restricted to the NHANES non-Hispanic white population (age range 40-69 years) due to the unavailability of MR studies in other groups, but projections are provided for the African American population under the assumption of homogeneity of causal effects.

Outcome

Preventable fraction for 10-year all-cause mortality and cause-specific mortality due to 50% and 100% reduction of excess BMI (BMI>25.6 kg/m2) for the US adult population in the age range of 40-69 years.

Results

Nearly 33% and 43% of the NHANES 2017-2018 target population are overweight (25.6 kg/m2≤BMI<30.7 kg/m2) and obese (BMI>30.7 kg/m2), respectively, according to WHO definitions. Estimates of relative risks for different BMI categories (relative to normal BMI) from the external MR study range from 1.05 (25.6 kg/m2 ≤ BMI < 27.8 kg/m2) to 5.95 (BMI> 42.4 kg/m2). We estimate PF for 10-year all-cause mortality due to 50% and 100% reduction of excess BMI for the population to be 24% (95% CI: 14 - 34) and 35% (95% CI: 22-48), respectively. The estimate of PF of death due to heart disease and cancer for this population reaches up to 48% (95% CI: 25-71) and 18% (95% CI: -2-38), respectively. Partitioning of PF shows that 60% of all BMI-attributable deaths arise from only 12% of the population who are at the highest risk due to obesity and a combination of other risk factors.

Conclusions

Nearly one in three deaths in a contemporary US adult population can be attributed to overweight and obesity. A substantial fraction of these deaths are likely to be preventable through pragmatic and targeted BMI interventions.

Association of educational attainment with esophageal cancer, Barrett's esophagus, and gastroesophageal reflux disease, and the mediating role of modifiable risk factors: A Mendelian randomization study

Background

Observational studies have reported that educational attainment has been related to the risk of esophageal cancer (EC) and its precancerous lesions. However, the causal relationship remains controversial. We aimed to apply the Mendelian randomization (MR) design to determine the causal associations between genetically predicted educational attainment and EC, Barrett's esophagus (BE), and gastroesophageal reflux disease (GERD), and to explore whether modifiable risk factors play a mediating role.

Methods

Using summary statistics from genome-wide association studies (GWASs) based on European ancestry individuals of several years in education (EduYears, primary analysis, n = 293,723), college completion (College, secondary analysis, n = 95,427), EC (n = 420,531), BE (n = 361,194), and GERD (n = 420,531), genetic associations between two education phenotypes and EC, BE, and GERD were tested by two-sample MR analyses. Then, two-step MR mediation analyses were used to assess the proportion of the aforementioned association that might be mediated by body mass index (BMI), major depressive disorder (MDD), smoking, drinking, carbohydrates, fat, and protein intake.

Results

Genetically predicted EduYears was negatively associated with the risk of EC, BE, and GERD {odds ratio (OR), 0.64 [95% confidence interval (CI) 0.44–0.94], 0.86 (95% CI, 0.75–0.99), and 0.62 (95%CI, 0.58–0.67)}. EduYears was negatively associated with BMI, MDD, and smoking (range of OR: 0.76–0.84). There were positive associations between BMI, smoking with EC, BE, and GERD, as well as between MDD with GERD (range of OR: 1.08–1.50). For individual mediating effect, BMI and smoking mediated 15.75 and 14.15% of the EduYears-EC association and 15.46 and 16.85% of the EduYears-BE association. BMI, MDD, and smoking mediated 5.23, 4.98, and 4.49% of the EduYears-GERD association. For combined mediation, the aforementioned mediators explained 26.62, 28.38, and 11.48% of the effect of EduYears on EC, BE, and GERD. The mediating effects of drinking and dietary composition were not significant in the effect of education on EC, BE, and GERD.

Conclusion

Our study supports that genetically predicted higher educational attainment has a protective effect on EC, BE, and GERD, and is partly mediated by reducing adiposity, smoking, and depression.

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.

Impact of ultra-processed food intake on the risk of COVID-19: a prospective cohort study

PURPOSE

Nutrition plays a key role in supporting the human immune system and reducing the risk of infections. However, there is limited evidence exploring the relationship between diet and the risk of COVID-19. This study aimed to assess the associations between consumption of ultra-processed foods (UPF) and COVID-19 risk.

METHODS

In total, 41,012 participants from the UK Biobank study with at least 2 of up to 5 times 24-h dietary assessments were included in this study. Dietary intakes were collected using an online 24-h dietary recall questionnaire and food items were categorized according to their degree of processing by the NOVA classification. COVID-19 infection was defined as individuals tested COVID-19 positive or dead of COVID-19. Association between average UPF consumption (% daily gram intake) and COVID-19 infection was assessed by multivariable logistic regression adjusted for potential confounders.

RESULTS

Compared to participants in the lowest quartile of UPF proportion (% daily gram intake) in the diet, participants in the 2nd, 3rd, and highest quartiles were associated with a higher risk of COVID-19 with the odds ratio (OR) value of 1.03 (95% CI: 0.94-1.13), 1.24 (95% CI: 1.13-1.36), and 1.22 (95% CI: 1.12-1.34), respectively (P for trend < 0.001), after adjusting for potential confounders. The results were robust in a series of sensitivity analyses. No interaction effect was identified between the UPF proportions and age groups, education level, body mass index, and comorbidity status. BMI mediated 13.2% of this association.

CONCLUSION

Higher consumption of UPF was associated with an increased risk of COVID-19 infection. Further studies are needed to better understand the underlying mechanisms in such association.

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.

Are inflammatory bowel diseases associated with an increased risk of COVID-19 susceptibility and severity? A two-sample Mendelian randomization study

Background: Due to inconsistent findings in observational studies regarding the relationship between inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn's disease (CD), and COVID-19, our objective is to explore a potential causative correlation between IBD and COVID-19 susceptibility and its severity using a two-sample Mendelian randomization (MR) analysis. Methods: Using summary data from genome-wide association studies, IBD, including UC and CD, were used as exposure instruments, while COVID-19 susceptibility, hospitalization, and very severe illness were employed as the outcome. The five analysis methods were adopted to evaluate the causal relationship between two diseases, with the inverse variance weighted (IVW) method being the most important. Also, sensitivity analyses were done to make sure that the main results of the MR analyses were reliable. Results: In the analysis using five methods, all p-values were higher than 0.05. There was no association between IBD and COVID-19 susceptibility, hospitalization, and severity in our MR study. The random-effect model was applied due to the existence of heterogeneity. MR-Egger regression revealed no indication of directional pleiotropy, and sensitivity analysis revealed similar relationships. Conclusion: This MR study found no evidence to support that IBD (which includes UC and CD) increases the risk of COVID-19 susceptibility or severity. Our result needs further confirmation through larger epidemiological studies.

The causal effect of physical activity intensity on COVID-19 susceptibility, hospitalization, and severity: Evidence from a mendelian randomization study

The protection of physical activity (PA) against COVID-19 is a rising research interest. However, the role of physical activity intensity on this topic is yet unclear. To bridge the gap, we performed a Mendelian randomization (MR) study to verify the causal influence of light and moderate-to-vigorous PA on COVID-19 susceptibility, hospitalization, and severity. The Genome-Wide Association Study (GWAS) dataset of PA (n = 88,411) was obtained from the UK biobank and the datasets of COVID-19 susceptibility (n = 1,683,768), hospitalization (n = 1,887,658), and severity (n = 1,161,073) were extracted from the COVID-19 Host Genetics Initiative. A random-effect inverse variance weighted (IVW) model was carried out to estimate the potential causal effects. A Bonferroni correction was used for counteracting. The problem of multiple comparisons. MR-Egger test, MR-PRESSO test, Cochran's Q statistic, and Leave-One-Out (LOO) were used as sensitive analysis tools. Eventually, we found that light PA significantly reduced the risk of COVID-19 infection (OR = 0.644, 95% CI: 0.480-0.864, p = 0.003). Suggestive evidence indicated that light PA reduced the risks of COVID-19 hospitalization (OR = 0.446, 95% CI: 0.227 to 0.879, p = 0.020) and severe complications (OR = 0.406, 95% CI: 0.167-0.446, p = 0.046). By comparison, the effects of moderate-to-vigorous PA on the three COVID-19 outcomes were all non-significant. Generally, our findings may offer evidence for prescribing personalized prevention and treatment programs. Limited by the available datasets and the quality of evidence, further research is warranted to re-examine the effects of light PA on COVID-19 when new GWAS datasets emerge.

A proteome-scale map of the SARS-CoV-2-human contactome

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

SARS-CoV-2 fires up inflammation in adipose tissue

Obesity is an important risk factor for severe COVID-19 and, possibly, for breakthrough SARS-CoV-2 infections in fully vaccinated people. Novel findings highlight how SARS-CoV-2 infects adipose tissue and promotes subclinical inflammation. Thus, also based on knowledge about endocrine dysfunction facilitating SARS-CoV-2 infection, a vicious cycle involving obesity, impaired metabolic health and COVID-19 might exist.

Genomics and phenomics of body mass index reveals a complex disease network

Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.

Body Mass Index and Clinical Outcomes in Adult COVID-19 Patients of Diverse Ethnicities

(1) Background: Body mass index (BMI) was observed to affect COVID-19 outcomes; however, the complete spectrum of clinical outcomes concerning BMI remains unexplored. The current study aimed to investigate the correlation between BMI and the severity and mortality of COVID-19, as well as ICU admission, radiological findings, clinical presentation, and time to viral clearance. (2) Methods: This retrospective study included 1796 multiethnic patients with COVID-19 treated at NMC Royal Hospital, Abu Dhabi, UAE. (3) Results: COVID-19’s adjusted odds of severity increased by 3.7- and 21.5-fold in classes I and III, respectively (p = 0.001). The odds of mortality were not significantly different after adjustment for age, sex, and race. The adjusted odds of ICU admission increased significantly by 3-fold and non-significantly by 4-fold in obesity classes I and II, respectively. Pneumonia was significantly higher in patients who were overweight and class I, II, and III obese. Furthermore, class III obese patients had a greater risk of presenting with combined respiratory and gastrointestinal manifestations (p < 0.001). The median time to viral clearance with a BMI > 40 kg/m2 was moderately higher than that with a BMI < 40 kg/m2. (4) Conclusions: High BMI was associated with pneumonia, ICU admission, severity, and mortality due to COVID-19.

Mendelian Randomization Shows a Causal Effect of Low Vitamin D on Non-infectious Uveitis and Scleritis Risk

PURPOSE

To investigate a causal relationship between Vitamin D levels and non-infectious uveitis and scleritis using Mendelian randomization (MR) techniques.

DESIGN

Two-sample Mendelian randomization case-control study.

METHODS

The study setting was a biobank of an academic, integrated health care system. The patient population comprised 375 case patients with a non-infectious uveitis and/or scleritis diagnosis and no diagnosis of infectious, trauma-related, or drug-induced uveitis/scleritis. In addition, there were 4167 controls with no uveitis or scleritis diagnosis. Causal effect estimates of low 25-hydroxy Vitamin D (25OHD) on uveitis/scleritis risk were calculated.

RESULTS

We found an association of genetically decreased 25OHD with uveitis/scleritis risk (odds ratio [OR] = 2.16, 95% CI = 1.01-4.64, P = .049, per SD decrease in log25OHD). In a first sensitivity MR analysis excluding the genetic variants that are unlikely to have a role in biologically active 25OHD, effect estimates were consistent with those from the primary analysis (OR = 2.38, 95% CI =1.06-5.36, P = 0.035, per SD of log25OHD). Furthermore, in a second sensitivity analysis using only the 6 variants within the CYP2R1 locus (which encodes 25OHD hydroxylase, the liver enzyme responsible for converting Vitamin D to 25OHD), genetically decreased 25OHD was strongly associated with increased uveitis/scleritis risk (OR = 6.42, 95% CI = 3.19-12.89, P = 1.7 × 10^-7, per SD of log25OHD).

CONCLUSIONS

Our findings suggest a causal relationship between low Vitamin D levels and higher risk of non-infectious uveitis and scleritis. Vitamin D supplementation may be a low-cost, low-risk intervention to mitigate non-infectious uveitis and scleritis risk, and should be explored in a prospective trial.

Genome-wide Mendelian randomization and single-cell RNA sequencing analyses identify the causal effects of COVID-19 on 41 cytokines

The elevated levels of inflammatory cytokines have attracted much attention during the treatment of COVID-19 patients. The conclusions of current observational studies are often controversial in terms of the causal effects of COVID-19 on various cytokines because of the confounding factors involving underlying diseases. To resolve this problem, we conducted a Mendelian randomization analysis by integrating the GWAS data of COVID-19 and 41 cytokines. As a result, the levels of 2 cytokines were identified to be promoted by COVID-19 and had unsignificant pleiotropy. In comparison, the levels of 10 cytokines were found to be inhibited and had unsignificant pleiotropy. Among down-regulated cytokines, CCL2, CCL3 and CCL7 were members of CC chemokine family. We then explored the potential molecular mechanism for a significant causal association at a single cell resolution based on single-cell RNA data, and discovered the suppression of CCL3 and the inhibition of CCL3-CCR1 interaction in classical monocytes (CMs) of COVID-19 patients. Our findings may indicate that the capability of COVID-19 in decreasing the chemotaxis of lymphocytes by inhibiting the CCL3-CCR1 interaction in CMs.

Vascular endothelial growth factor and the risk of venous thromboembolism: a genetic correlation and two-sample Mendelian randomization study

Background

The relationship between vascular endothelial growth factor (VEGF) and the risk of venous thromboembolism (VTE) has always been one of the concerns in the medical field. However, the causal inferences from published observational studies on this issue may be affected by confounders or reverse causality. We performed a two-sample bidirectional Mendelian randomization (MR) to infer the associations between VEGF and VTE.

Methods

Summary statistics from genome-wide association studies (GWAS) for VEGF and VTE were obtained from published meta-analysis studies and the FinnGen consortium, respectively. Independent genetic variables significantly associated with exposure were selected as instrumental variables. Linkage disequilibrium score regression (LDSC) and five robust MR analytical approaches were conducted to estimate the genetic correlations and causal inference. The MR-Egger intercept, Cochran’s Q, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on outcomes. Notably, replication analyses were performed using different subgroups of VTE.

Results

LDSC failed to identify genetic correlations between VEGF and VTE. Based on 9 SNPs, the circulating VEGF level was positively related to the risk of VTE using inverse variance weighting (IVW) method (odds ratio (OR) = 1.064, 95% confidence interval (CI), 1.009–1.122). Reverse MR analyses showed that genetic liability for VTE was not associated with increased VEGF level (β = -0.021, 95% CI, -0.087-0.045). Pleiotropy-robust methods indicated no bias in any estimates.

Conclusions

Our findings failed to detect coheritability between VEGF and VTE. The suggestive positive effect of the higher VEGF level on the VTE risk may have clinical implications, suggesting that VEGF as a possible predictor and therapeutic target for VTE prevention need to be further warranted.

Blood Pressure Mediated the Effects of Urinary Uromodulin Levels on Myocardial Infarction: a Mendelian Randomization Study

Background:

The causal links between urinary uromodulin (uUMOD) and cardiovascular disease (CVD) are still not clarified.

Methods:

We first assessed the relationship between uUMOD and CVD using bidirectional 2-sample Mendelian randomization. Then, multivariable Mendelian randomization and product of the coefficients methods were used to investigate the role of blood pressure in mediating the effect of uUMOD on CVD.

Results:

1-unit higher uUMOD level was associated with a higher risk of myocardial infarction (MI), with an odds ratio of 1.08 ([95% CI, 1.02–1.14]; P =0.009), while MI was not associated with uUMOD levels in reverse. Our study did not support the causal effects of uUMOD on other CVD outcomes, including coronary artery disease, atrial fibrillation, heart failure, and ischemic stroke. In multivariable Mendelian Randomization, the direct effects of uUMOD on MI were attenuated to null after introducing systolic blood pressure or diastolic blood pressure. Mediation analysis showed that the indirect effect of uUMOD on MI mediated by systolic blood pressure or diastolic blood pressure was 1.05 ([95% CI, 1.04–1.06]; mediation proportion=69%) and 1.07 ([95% CI, 1.05–1.08]; mediation proportion=87%), respectively. Similar results were found in sensitivity analysis based on different sets of genetic instruments.

Conclusions:

Our findings provide evidence for the effect of higher uUMOD on increasing blood pressure, which mediates a consequent effect on MI risk in the general population. Further studies are necessary to verify the associations between uUMOD and other CVD outcomes.

A Mendelian randomization study of genetic predisposition to autoimmune diseases and COVID-19

Autoimmune diseases and coronavirus disease 2019 (COVID-19) share many similarities. Concerns have arisen that autoimmune diseases may increase the susceptibility and severity of COVID-19. We used Mendelian randomization to investigate whether liability to autoimmune diseases is related to COVID-19 susceptibility and severity. Genetic instruments for 8 autoimmune diseases, including type 1 diabetes mellitus, rheumatoid arthritis, systemic lupus erythematosus, psoriasis, multiple sclerosis, primary sclerosing cholangitis, primary biliary cirrhosis and juvenile idiopathic arthritis, were obtained from published genome-wide association studies. Two-sample Mendelian randomization analyses of the associations of liability to each autoimmune disease with COVID-19 infection, hospitalized COVID-19, and very severe COVID-19 were performed using the latest publicly available genome-wide association study for COVID-19. Genetic liability to each of the autoimmune diseases was largely not associated with COVID-19 infection, hospitalized COVID-19, or very severe COVID-19 after accounting for multiple comparison. Sensitivity analysis excluding genetic variants in the human leukocyte antigen gene, which has an important role in the immune response, showed similar results. The autoimmune diseases examined were largely not genetically associated with the susceptibility or severity of COVID-19. Further investigations are warranted.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

Effects of Hyperthyroidism on Venous Thromboembolism: A Mendelian Randomization Study

Objective

Observational studies show the correlation between thyroid dysfunction and risk of venous thromboembolism. However, the causal effects remain uncertain. Our study was conducted to evaluate whether thyroid function and dysfunction were causally linked to the risk of venous thromboembolism.

Methods

Publicly available summary data of thyrotropin (TSH) and free thyroxine (FT4), hypothyroidism, and hyperthyroidism were obtained from the ThyroidOmics Consortium and the UK Biobank. With single nucleotide polymorphisms (SNPs) as instrumental variables, the casual effects of genetically predicted TSH and FT4 and hypo- and hyperthyroidism on venous thromboembolism outcome were estimated through Mendelian randomization analysis methods (inverse variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode). Cochran's Q test was performed to evaluate the heterogeneity and horizontal pleiotropy.

Results

Our study selected 15 FT4-, 36 TSH-, 3 hyperthyroidism-, and 79 hypothyroidism-associated SNPs as instrumental variables. The IVW analysis results showed that the odds ratio of venous thromboembolism for hyperthyroidism was 1.124 (95% confidence interval: 1.019-1.240; p = 0.019), demonstrating the casual effect of hyperthyroidism not FT4, TSH, and hypothyroidism on venous thromboembolism. No heterogeneity or horizontal pleiotropy was observed according to Cochran's Q test.

Conclusion

Our Mendelian randomization analysis supports the causal effect of hypothyroidism on risk of venous thromboembolism. There is no evidence that genetically predicted TSH, FT4, and hypothyroidism have casual effects on venous thromboembolism. Future studies should be conducted to elucidate the underlying pathophysiological mechanisms.

Obesity, Hypovitaminosis D, and COVID-19: the Bermuda Triangle in Public Health

PURPOSE OF REVIEW

The COVID-19 pandemic has challenged public health to a significant extent by markedly increasing morbidity and mortality. Evidence suggests that obesity and hypovitaminosis D constitute important risk factors for SARS-CoV-2 infection, severity of disease, and poor outcomes. Due to their high prevalence globally, obesity and hypovitaminosis D are considered pandemics. This review presents current epidemiologic and genetic data linking obesity, hypovitaminosis D, and COVID-19, highlighting the importance of the convergence of three pandemics and their impact on public health. We also briefly summarize potential mechanisms that could explain these links.

RECENT FINDINGS

Epidemiologic data have shown that obesity is an independent risk factor for COVID-19, severe disease and death, and genetic evidence has suggested a causal association between obesity-related traits and COVID-19 susceptibility and severity. Additionally, obesity is independently associated with hypovitaminosis D, which is highly prevalent in subjects with obesity. Hypovitaminosis D is independently associated with a higher risk for COVID-19, severity, hospitalization, infectious complications, acute respiratory distress syndrome, and poor outcomes. However, genome-wide association studies have not revealed any causal association between vitamin D levels and the risk for COVID-19, while there is no robust evidence for a beneficial role of vitamin D supplementation in the prevention and treatment of COVID-19. In the context of the ongoing COVID-19 pandemic, the epidemiologic impact of obesity and hypovitaminosis D is emphasized. Efforts to increase public awareness and reinforce preventive and therapeutic measures against obesity and hypovitaminosis D are strongly required.

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.