Causal associations between thyroid dysfunction and COVID-19 susceptibility and severity: A bidirectional Mendelian randomization study.

Background: Observational studies have reported an association between coronavirus disease 2019 (COVID-19) risk and thyroid dysfunction, but without a clear causal relationship. We attempted to evaluate the association between thyroid function and COVID-19 risk using a bidirectional two-sample Mendelian randomization (MR) analysis. Methods: Summary statistics on the characteristics of thyroid dysfunction (hypothyroidism and hyperthyroidism) were obtained from the ThyroidOmics Consortium. Genome-wide association study statistics for COVID-19 susceptibility and its severity were obtained from the COVID-19 Host Genetics Initiative, and severity phenotypes included hospitalization and very severe disease in COVID-19 participants. The inverse variance-weighted (IVW) method was used as the primary analysis method, supplemented by the weighted-median (WM), MR-Egger, and MR-PRESSO methods. Results were adjusted for Bonferroni correction thresholds. Results: The forward MR estimates show no effect of thyroid dysfunction on COVID-19 susceptibility and severity. The reverse MR found that COVID-19 susceptibility was the suggestive risk factor for hypothyroidism (IVW: OR = 1.577, 95% CI = 1.065-2.333, P = 0.022; WM: OR = 1.527, 95% CI = 1.042-2.240, P = 0.029), and there was lightly association between COVID-19 hospitalized and hypothyroidism (IVW: OR = 1.151, 95% CI = 1.004-1.319, P = 0.042; WM: OR = 1.197, 95% CI = 1.023-1.401, P = 0.023). There was no evidence supporting the association between any phenotype of COVID-19 and hyperthyroidism. Conclusion: Our results identified that COVID-19 might be the potential risk factor for hypothyroidism. Therefore, patients infected with SARS-CoV-2 should strengthen the monitoring of thyroid function.

Insomnia and sleep duration on COVID-19 susceptibility and hospitalization: A Mendelian randomization study.

Background: Sleep disturbance including insomnia and sleep duration is associated with an increased risk of infectious. With the ongoing coronavirus disease 2019 (COVID-19) pandemic, it is important to explore potential causal associations of sleep disturbance on COVID-19 susceptibility and hospitalization. Method: Insomnia and sleep duration were selected as exposure. Outcomes included susceptibility and hospitalization for COVID-19. Two sample mendelian randomization design was used to assess causality between sleep and COVID-19. Inverse variance weighted method was used as main analysis method to combine the ratio estimates for each instrumental variable to obtain the causal effect. Cochran's Q statistic was used to test for global heterogeneity. MR-Egger and weighting median estimator (WME) were used as sensitivity analysis to ensure the stability and reliability of the results. MR-Egger intercept term was used to test the mean pleiotropy. In addition, the direct effects of insomnia and sleep duration on COVID-19 susceptibility and hospitalization were estimated using multivariable mendelian randomization (MVMR). Results: Univariate MR provided no evidence of a causal associations of insomnia on COVID-19 susceptibility (OR = 1.10, 95% CI:0.95, 1.27; p = 0.21) and hospitalization (OR = 0.61, 95% CI:0.40, 0.92; p = 0.02); as does sleep duration (ORCOIVD - 19susceptibility = 0.93, 95% CI:0.86, 1.01; p = 0.07; ORCOIVD - 19 hospitalization = 1.21, 95% CI: 0.99, 1.47; p = 0.08). MVMR results showed that insomnia may be a risk factor for increased susceptibility to COVID-19 (OR = 1.65, 95% CI: 1.34, 2.05; p <0.001); and sleep duration was also associated with increased COVID-19 susceptibility (OR = 1.31, 95% CI: 1.18, 1.46; p < 0.001). Conclusion: Insomnia and extreme sleep duration may risk factors for increased COVID-19 susceptibility. Relieving insomnia and maintaining normal sleep duration may be powerful measures to reduce COVID-19 infections.

Thyroid Function and COVID-19 Susceptibility and Its Severity: A Two-Sample Mendelian Randomization Study.

Several observational studies have confirmed the relationship between thyroid hormones and coronavirus disease 2019 (COVID-19), but this correlation remains controversial. We performed a two-sample Mendelian randomization (MR) analysis based on the largest publicly available summary datasets. Summary statistics with 49 269 individuals for free thyroxine (FT4) and 54 288 for thyroid stimulating hormone (TSH) were used as exposure instruments. Genome-wide association studies of susceptibility (cases = 38 984; controls = 1 644 784), hospitalization (cases: 9986 = controls = 1 877 672), and very severe disease (cases = 5101; controls = 1 383 241) of COVID-19 were used as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis, and utilized MR-Egger regression, weighted median, and robust adjusted profile score (RAPS) for sensitivity analysis. Genetic predisposition to higher serum levels of FT4 within the normal range was negatively associated with the risk of COVID-19 hospitalization (odds ratio [OR] = 0.818; 95% CI, 0.718-0.932; P = 2.6 × 10-3) and very severe disease (OR = 0.758; 95% CI, 0.626-0.923; P = 5.8 × 10-3), but not susceptibility. There is no evidence that genetically predicted circulating TSH levels are associated with COVID-19 susceptibility and severity risk. Neither apparent pleiotropy nor heterogeneity were detected in the sensitivity analysis. In summary, we found that higher FT4 levels may reduce the risk of COVID-19 severity, suggesting that thyroid function testing may be required for patients with COVID-19.

COVID-19 and risk of neurodegenerative disorders: A Mendelian randomization study.

Emerging evidence has suggested a close correlation between COVID-19 and neurodegenerative disorders. However, whether there exists a causal association and the effect direction remains unknown. To examine the causative role of COVID-19 in the risk of neurodegenerative disorders, we estimated their genetic correlation, and then conducted a two-sample Mendelian randomization analysis using summary statistics from genome-wide association studies of susceptibility, hospitalization, and severity of COVID-19, as well as six major neurodegenerative disorders including Alzheimer's disease (AD), amyotrophic lateral sclerosis, frontotemporal dementia, Lewy body dementia, multiple sclerosis, and Parkinson's disease. We identified a significant and positive genetic correlation between hospitalization of COVID-19 and AD (genetic correlation: 0.23, P = 8.36E-07). Meanwhile, hospitalization of COVID-19 was significantly associated with a higher risk of AD (OR: 1.02, 95% CI: 1.01-1.03, P: 1.19E-03). Consistently, susceptibility (OR: 1.05, 95% CI: 1.01-1.09, P: 9.30E-03) and severity (OR: 1.01, 95% CI: 1.00-1.02, P: 0.012) of COVID-19 were nominally associated with higher risk of AD. The results were robust under all sensitivity analyses. These results demonstrated that COVID-19 could increase the risk of AD. Future development of preventive or therapeutic interventions could attach importance to this to alleviate the complications of COVID-19.

COVID-19 and Thyroid Function: A Bi-Directional Two-Sample Mendelian Randomization Study.

Background: Thyroid dysfunction has been observed among some patients with coronavirus disease (COVID-19). It is unclear whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (or its severity) leads to the development of thyroid dysfunction, or vice versa. In this study, we examined the bi-directional causal relationship between host genetic liability to three COVID-19 phenotypes (including SARS-CoV-2 infection, hospitalized and severe COVID-19) and three thyroid dysfunction traits (including hyperthyroidism, hypothyroidism, and autoimmune thyroid disease [AITD]) and three continuous traits of thyroid hormones (including thyrotropin [TSH] and free thyroxine [fT4] within reference range, and TSH in full range). Methods: Summary statistics from the largest available meta-analyses of human genome-wide association studies were retrieved for the following variables: SARS-CoV-2 infection (n = 1,348,701), COVID-19 hospitalization (n = 1,557,411), severe COVID-19 (n = 1,059,456), hyperthyroidism (n = 51,823), hypothyroidism (n = 53,423), AITD (n = 755,406), TSH within reference range (n = 54,288), fT4 within reference range (n = 49,269), and TSH in full range (n = 119,715). Using a two-sample Mendelian randomization (MR) approach, the inverse-variance weighted (IVW) method was adopted as the main MR analysis. Weighted median, contamination mixture, MR-Egger, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods were applied as sensitivity analyses. Results: Host genetic susceptibility to SARS-CoV-2 infection was causally associated with hypothyroidism in the main IVW analysis (per doubling in prevalence of SARS-CoV-2 infection, odds ratio [OR] = 1.335; 95% confidence interval [CI]: 1.167-1.526; p = 2.4 × 10-5, surpassing the Bonferroni multiple-testing threshold). Similar causal estimates were observed in the sensitivity analyses (weighted median: OR = 1.296; CI: 1.066-1.575; p = 9 × 10-3; contamination mixture: OR = 1.356; CI: 1.095-1.818; p = 0.013; MR-Egger: OR = 1.712; CI: 1.202-2.439; p = 2.92 × 10-3, and MR-PRESSO: OR = 1.335; CI: 1.156-1.542; p = 5.73 × 10-4). Host genetic liability to hospitalized or severe COVID-19 was not associated with thyroid dysfunction or thyroid hormone levels. In the reverse direction, there was no evidence to suggest that genetic predisposition to thyroid dysfunction or genetically determined thyroid hormone levels altered the risk of the COVID-19 outcomes. Conclusions: This bi-directional MR study supports that host response to SARS-CoV-2 viral infection plays a role in the causal association with increased risk of hypothyroidism. Long-term follow-up studies are needed to confirm the expected increased hypothyroidism risk.

Relative Deprivation, Income Inequality, and Cardiovascular Health: Observational and Mendelian Randomization Studies in Hong Kong Chinese.

The associations between absolute vs. relative income at the household or neighborhood level and cardiovascular disease (CVD) risk remain understudied in the Chinese context. Further, it is unclear whether stress biomarkers, such as cortisol, are on the pathway from income to CVD risk. We examined the associations of absolute and relative income with CVD risk observationally, as well as the mediating role of cortisol, and validated the role of cortisol using Mendelian Randomization (MR) in Hong Kong Chinese. Within Hong Kong's FAMILY Cohort, associations of absolute and relative income at both the individual and neighborhood levels with CVD risk [body mass index (BMI), body fat percentage, systolic blood pressure, diastolic blood pressure, self-reported CVD and self-reported diabetes] were examined using multilevel logistic or linear models (n = 17,607), the mediating role of cortisol using the mediation analysis (n = 1,562), and associations of genetically predicted cortisol with CVD risk using the multiplicative generalized method of moments (MGMMs) or two-stage least squares regression (n = 1,562). In our cross-sectional observational analysis, relative household income deprivation (per 1 SD, equivalent to USD 128 difference in Yitzhaki index) was associated with higher systolic blood pressure (0.47 mmHg, 95% CI 0.30-0.64), but lower BMI (-0.07 kg/m2, 95% CI -0.11 to -0.04), independent of absolute income. Neighborhood income inequality was generally unrelated to CVD and its risk factors, nor was absolute income at the household or neighborhood level. Cortisol did not clearly mediate the association of relative household income deprivation with systolic blood pressure. Using MR, cortisol was unrelated to CVD risk. Based on our findings, relative household income deprivation was not consistently associated with cardiovascular health in Hong Kong Chinese, nor were neighborhood income inequality and absolute income, highlighting the context-specific ways in which relative and absolute income are linked to CVD risk.

The causal relationship between circulating cytokines and critically ill COVID-19: A bidirectional Mendelian randomization analysis.

Background: In this study, we performed a bidirectional mendelian randomization analysis on circulating cytokines and critically ill COVID-19. Methods: Both the exposure and outcome data were obtained from public genome wide association study (GWAS) database. We extracted independent instrumental variables from exposure at genome level significance (P < 5 × 10-8). Wald ratio or inverse variance weighted (IVW) method were used for estimating the causal relationships between circulating cytokines and critically ill COVID-19. Results: Only IL5 (cytokines to critically ill COVID-19 direction) and bNGF, IL8 (critically ill COVID-19 to cytokines direction) showed suggestive causal relations. However, these associations lost significance after FDR correction. Another validation data set of critically ill COVID-19 did not confirm these associations, either. Conclusions: Our Mendelian randomization did not find causal relationships between analyzable circulating cytokines and critically ill COVID-19.

A two-sample robust Bayesian Mendelian Randomization method accounting for linkage disequilibrium and idiosyncratic pleiotropy with applications to the COVID-19 outcomes.

Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of interest. Despite wide uses of various popular two-sample MR methods based on genome-wide association study summary level data, however, those methods could suffer from potential power loss or/and biased inference when the chosen genetic variants are in linkage disequilibrium (LD), and also have relatively large direct effects on the outcome whose distribution might be heavy-tailed which is commonly referred to as the idiosyncratic pleiotropy phenomenon. To resolve those two issues, we propose a novel Robust Bayesian Mendelian Randomization (RBMR) model that uses the more robust multivariate generalized t$t$ -distribution to model such direct effects in a probabilistic model framework which can also incorporate the LD structure explicitly. The generalized t$t$ -distribution can be represented as a Gaussian scaled mixture so that our model parameters can be estimated by the expectation maximization (EM)-type algorithms. We compute the standard errors by calibrating the evidence lower bound using the likelihood ratio test. Through extensive simulation studies, we show that our RBMR has robust performance compared with other competing methods. We further apply our RBMR method to two benchmark data sets and find that RBMR has smaller bias and standard errors. Using our proposed RBMR method, we find that coronary artery disease is associated with increased risk of critically ill coronavirus disease 2019. We also develop a user-friendly R package RBMR (https://github.com/AnqiWang2021/RBMR) for public use.

Genetic predisposition to COVID-19 may increase the risk of hypertension disorders in pregnancy: A two-sample Mendelian randomization study.

AIMS: The aim of this study was to apply the Mendelian randomization (MR) design to explore the potential causal association between COVID-19 and the risk of hypertension disorders in pregnancy. METHODS: Our primary genetic instrument comprised 8 single-nucleotide polymorphisms (SNPs) associated with COVID-19 at genome-wide significance. Data on the associations between the SNPs and the risk of hypertension disorders in pregnancy were obtained from study based on a very large cohort of European population. The random-effects inverse-variance weighted method was conducted for the main analyses, with a complementary analysis of the weighted median and MR-Egger approaches. RESULTS: Using IVW, we found that genetically predicted COVID-19 was significantly positively associated with hypertension disorders in pregnancy, with an odds ratio (OR) of 1.111 [95% confidence interval (CI) 1.042-1.184; P = 0.001]. Weighted median regression also showed directionally similar estimates [OR 1.098 (95% CI, 1.013-1.190), P = 0.023]. Both funnel plots and MR-Egger intercepts suggest no directional pleiotropic effects observed. CONCLUSIONS: Our findings provide direct evidence that there is a shared genetic predisposition so that patients infected with COVID-19 may be causally associated with increased risk of hypertension disorders in pregnancy.

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19.

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Impact of body composition on COVID-19 susceptibility and severity: A two-sample multivariable Mendelian randomization study.

OBJECTIVES: Recent studies suggested obesity to be a possible risk factor for COVID-19 disease in the wake of the coronavirus (SARS-CoV-2) infection. However, the causality and especially the role of body fat distribution in this context is still unclear. Thus, using a univariable as well as multivariable two-sample Mendelian randomization (MR) approach, we investigated for the first time the causal impact of body composition on the susceptibility and severity of COVID-19. METHODS: As indicators of overall and abdominal obesity we considered the measures body mass index (BMI), waist circumference (WC), and trunk fat ratio (TFR). Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used. For the COVID-19 cohort neither age nor gender was available. Total and direct causal effect estimates were calculated using Single Nucleotide Polymorphisms (SNPs), sensitivity analyses were done applying several robust MR techniques and mediation effects of type 2 diabetes (T2D) and cardiovascular diseases (CVD) were investigated within multivariable MR analyses. RESULTS: Genetically predicted BMI was strongly associated with both, susceptibility (OR = 1.31 per 1 SD increase; 95% CI: 1.15-1.50; P-value = 7.3·10-5) and hospitalization (OR = 1.62 per 1 SD increase; 95% CI: 1.33-1.99; P-value = 2.8·10-6) even after adjustment for genetically predicted visceral obesity traits. These associations were neither mediated substantially by T2D nor by CVD. Finally, total but not direct effects of visceral body fat on outcomes could be detected. CONCLUSIONS: This study provides strong evidence for a causal impact of overall obesity on the susceptibility and severity of COVID-19 disease. The impact of abdominal obesity was weaker and disappeared after adjustment for BMI. Therefore, obese people should be regarded as a high-risk group. Future research is necessary to investigate the underlying mechanisms linking obesity with COVID-19.

Modifiable lifestyle factors and severe COVID-19 risk: a Mendelian randomisation study.

BACKGROUND: Lifestyle factors including obesity and smoking are suggested to be correlated with increased risk of COVID-19 severe illness or related death. However, whether these relationships are causal is not well known; neither for the relationships between COVID-19 severe illness and other common lifestyle factors, such as physical activity and alcohol consumption. METHODS: Genome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, physical activity and alcohol consumption identified by large-scale genome-wide association studies (GWAS) of up to 941,280 individuals were selected as instrumental variables. Summary statistics of the genetic variants on severe illness of COVID-19 were obtained from GWAS analyses of up to 6492 cases and 1,012,809 controls. Two-sample Mendelian randomisation analyses were conducted. RESULTS: Both per-standard deviation (SD) increase in genetically predicted BMI and lifetime smoking were associated with about two-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P < 0.05). Per-SD increase in genetically predicted physical activity was associated with decreased risks of severe respiratory COVID-19 (odds ratio [OR] = 0.19; 95% confidence interval [CI], 0.05, 0.74; P = 0.02), but not with COVID-19 hospitalization (OR = 0.44; 95% CI 0.18, 1.07; P = 0.07). No evidence of association was found for genetically predicted alcohol consumption. Similar results were found across robust Mendelian randomisation methods. CONCLUSIONS: Evidence is found that BMI and smoking causally increase and physical activity might causally decrease the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.