Genetically Predicted Circulating Concentrations of Micronutrients and Risk of Amyotrophic Lateral Sclerosis: A Mendelian Randomization Study

Amyotrophic lateral sclerosis (ALS) is a progressive and devastating neurodegenerative disease with increasing incidence and high mortality, resulting in a considerable socio-economic burden. Till now, plenty of studies have explored the potential relationship between circulating levels of various micronutrients and ALS risk. However, the observations remain equivocal and controversial. Thus, we conducted a two-sample Mendelian randomization (MR) study to investigate the causality between circulating concentrations of 9 micronutrients, including retinol, folate acid, vitamin B12, B6 and C, calcium, copper, zinc as well as magnesium, and ALS susceptibility. In our analysis, several single nucleotide polymorphisms were collected as instrumental variables from large-scale genome-wide association studies of these 9 micronutrients. Then, inverse variance weighted (IVW) approach as well as alternative MR-Egger regression, weighted median and MR-pleiotropy residual sum and outlier (MR-PRESSO) analyses were performed to evaluate causal estimates. The results from IVW analysis showed that there was no causal relationship of 9 micronutrients with ALS risk. Meanwhile, the three complementary approaches obtained similar results. Thus, our findings indicated that supplementation of these 9 micronutrients may not play a clinically effective role in preventing the occurrence of ALS.

Associations of sleep and circadian phenotypes with COVID-19 susceptibility and hospitalization: an observational cohort study based on the UK Biobank and a two-sample Mendelian randomization study

Study Objectives Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes. Methods Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Beta values and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods. Results In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR=1.24, 95% CI=1.02-1.5; daytime napping [sometimes vs. never]: RR=1.12, 95% CI=1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR= 1.04, 95% CI=1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes. Conclusions Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.

Non-Causal Effects of Asthma on COVID-19 Susceptibility and Severity

Background: Asthma is observationally associated with an increased risk of COVID-19, but the causality remains unclear. We aim to determine whether there is a casual role of asthma in susceptibility to SARS-CoV-2 infection or COVID-19 severity.Methods: Instrumental variables (IVs) for asthma and moderate-to-severe asthma were obtained from publicly available summary statistics from the most recent and largest genome-wide association study (GWAS), including 394 283 and 57 695 participants of European ancestry, respectively. The corresponding data for COVID-19 susceptibility, hospitalization and severe-disease were derived from the COVID-19 Host Genetics Initiative GWAS meta-analysis of up to 1 683 768 individuals of European descent. Causality was inferred between correlated traits by Mendelian Randomization analyses. Inverse-variance weighted method was used as the primary MR estimates and multiple alternate approaches and several sensitivity analyses were also conducted.Results: Our MR analysis revealed no causal effects of asthma on COVID-19 susceptibility, hospitalization or severe disease, with odds ratio (OR) of 0.994 (95% CI: 0.962–1.027), 1.020 (95% CI: 0.955–1.089), and 0.929 (95% CI: 0.836–1.032), respectively. Furthermore, using genetic variants for moderate-to-severe asthma, a similar pattern of results was observed for COVID-19 susceptibility (OR: 0.988, 95% CI: 0.946–1.031), hospitalization (OR: 0.967, 95% CI: 0.906–1.031), and severe disease (OR: 0.911, 95% CI: 0.823–1.009). The association of asthma and moderate-to-severe asthma with COVID-19 was overall robust to sensitivity analyses.Conclusion: Genetically predicted asthma was not associated with susceptibility to, or severity of, COVID-19 disease, indicating that asthma is unlikely to be a causal factor in the development of COVID-19.

The Effect of Circulating Zinc, Selenium, Copper and Vitamin K1 on COVID-19 Outcomes: A Mendelian Randomization Study

Background & Aims: Previous results from observational, interventional studies and in vitro experiments suggest that certain micronutrients possess anti-viral and immunomodulatory activities. In particular, it has been hypothesized that zinc, selenium, copper and vitamin K1 have strong potential for prophylaxis and treatment of COVID-19. We aimed to test whether genetically predicted Zn, Se, Cu or vitamin K1 levels have a causal effect on COVID-19 related outcomes, including risk of infection, hospitalization and critical illness. Methods: We employed a two-sample Mendelian Randomization (MR) analysis. Our genetic variants derived from European-ancestry GWAS reflected circulating levels of Zn, Cu, Se in red blood cells as well as Se and vitamin K1 in serum/plasma. For the COVID-19 outcome GWAS, we used infection, hospitalization or critical illness. Our inverse-variance weighted (IVW) MR analysis was complemented by sensitivity analyses including a more liberal selection of variants at a genome-wide sub-significant threshold, MR-Egger and weighted median/mode tests. Results: Circulating micronutrient levels show limited evidence of association with COVID-19 infection, with the odds ratio [OR] ranging from 0.97 (95% CI: 0.87–1.08, p-value = 0.55) for zinc to 1.07 (95% CI: 1.00–1.14, p-value = 0.06)—i.e., no beneficial effect for copper was observed per 1 SD increase in exposure. Similarly minimal evidence was obtained for the hospitalization and critical illness outcomes with OR from 0.98 (95% CI: 0.87–1.09, p-value = 0.66) for vitamin K1 to 1.07 (95% CI: 0.88–1.29, p-value = 0.49) for copper, and from 0.93 (95% CI: 0.72–1.19, p-value = 0.55) for vitamin K1 to 1.21 (95% CI: 0.79–1.86, p-value = 0.39) for zinc, respectively. Conclusions: This study does not provide evidence that supplementation with zinc, selenium, copper or vitamin K1 can prevent SARS-CoV-2 infection, critical illness or hospitalization for COVID-19.

The association of arterial stiffness index with cerebrovascular and cardiometabolic disease: A Mendelian randomization study

Background: Arterial stiffness index (ASI) is a potential risk factor for cerebrovascular and cardiometabolic diseases, but the causal links between them are inconclusive. The aim is to evaluate the causal effects of ASI on cerebrovascular and cardiometabolic diseases by Mendelian randomization (MR). Methods: Two-sample MR analysis was performed to infer causal links. Genetic variants significantly associated with ASI were extracted. The inverse variance weighted method was used for estimating the effects. Sensitivity analysis was performed to test heterogeneity or pleiotropy. Results: MR analysis indicated an effect of genetically predicted ASI on the risk of ischemic stroke (IS) of all causes (OR = 1.894, 95% CI 1.210–2.965, p = 0.005). No links were identified between genetically predicted ASI and other cerebrovascular or cardiometabolic diseases (all p > 0.05). Subgroup analysis of IS etiologies found a suggestive association between genetically predicted ASI and large artery atherosclerosis stroke (LAS) (OR = 3.726, 95% CI 1.230–11.286, p = 0.020). There were no effects of ASI on IS due to cardioembolism or small vessel occlusion. Conclusion: The current MR analysis suggested that genetically predicted ASI was associated with higher risk of IS of all causes. The results and the underlying pathways or mechanisms between ASI and IS needs further investigation.

Assessment of bidirectional relationships between 98 genera of the human gut microbiota and amyotrophic lateral sclerosis: a 2-sample Mendelian randomization study

Background Growing evidence suggests a mutual interaction between gut microbiome alterations and ALS pathogenesis. However, previous studies were susceptible to potential confounding factors and reverse causation bias, likely leading to inconsistent and biased results. Objectives To decipher the potentially mutual relationship between gut microbiota and ALS, we used a bidirectional two-sample MR approach to examine the associations between the gut microbiome and ALS. Results Using the inverse variance-weighted method, OTU10032 unclassified Enterobacteriaceae species-level OTU and unclassified Acidaminococcaceae were associated with a higher risk of ALS (per relative abundance: OR, 1.04; 95% CI, 1.01–1.07; P = 0.011 and OR, 1.02; 95% CI, 1.01–1.04; P = 0.009, respectively). Importantly, Gamma-Glu-Phe was showed potential deleterious effects on the risk of ALS (genetically predicted per a 1-standard deviation increase in the level of Gamma-Glu-Phe: OR, 1.96; 95% CI, 1.50–2.55; P = 0.012). Sensitivity analysis of the two candidate genera and metabolites using the MR-Egger and weighted-median methods produced similar estimates, and no horizontal pleiotropy or outliers were observed. Intriguingly, genetically predicted ALS was associated with an increase in the relative abundance of OTU4607_Sutterella (per 1-unit higher log odds: β, 2.23; 95% CI, 1.27–3.18; P = 0.020) and Lactobacillales_ORDER (per 1-unit higher log odds: β, 0.51; 95% CI, 0.09–0.94; P = 0.019). Conclusions Our findings provide novel evidence supporting the bidirectional relationship between the gut microbiota and ALS. These results may contribute to designing microbiome- and microbiome-dependent metabolite interventions in future ALS clinical trials.

Genetically Predicted Higher Educational Attainment Decreases the Risk of COVID-19 Susceptibility and Severity: A Mendelian Randomization Study

Background: Prior observational studies indicated that lower educational attainment (EA) is associated with higher COVID-19 risk, while these findings were vulnerable to bias from confounding factors. We aimed to clarify the causal effect of EA on COVID-19 susceptibility, hospitalization, and severity using Mendelian randomization (MR).Methods: We identified genetic instruments for EA from a large genome-wide association study (GWAS) (n = 1,131,881). Summary statistics for COVID-19 susceptibility (112,612 cases and 2,474,079 controls), hospitalization (24,274 cases and 2,061,529 controls), and severity (8,779 cases and 1,001,875 controls) were obtained from the COVID-19 Host Genetics Initiative. We used the single-variable MR (SVMR) and the multivariable MR (MVMR) controlling intelligence, income, body mass index, vigorous physical activity, sedentary behavior, smoking, and alcohol consumption to estimate the total and direct effects of EA on COVID-19 outcomes. Inverse variance weighted was the primary analysis method. All the statistical analyses were performed using R software.Results: Results from the SVMR showed that genetically predicted higher EA was correlated with a lower risk of COVID-19 susceptibility [odds ratio (OR) 0.86, 95% CI 0.84–0.89], hospitalization (OR 0.67, 95% CI 0.62–0.73), and severity (OR 0.67, 95% CI 0.58–0.79). EA still maintained its effects in most of the MVMR.Conclusion: Educational attainment is a predictor for susceptibility, hospitalization, and severity of COVID-19 disease. Population with lower EA should be provided with a higher prioritization to public health resources to decrease the morbidity and mortality of COVID-19.

Association between depression and sleep apnoea: a Mendelian randomisation study

BackgroundStudies have reported a close relationship between depression and sleep apnoea, yet it is unknown whether these are causally related. Thus, we aimed to determine whether depression is associated with the aetiology of sleep apnoea.MethodsWe used publicly available genetic summary data from two large consortia, the Psychiatric Genomics Consortium, with data from 36 single-nucleotide polymorphisms (SNPs) closely associated with major depressive disorder (MDD) and UK Biobank, including 456 736 patients with sleep apnoea and 766 964 controls. For Mendelian randomisation (MR) analysis, we used the inverse-variance weighted method, weighted median method, MR-Egger regression, MR pleiotropy residual sum, and outlier test to retrieve summary data. Analyses were performed using the “TwoSampleMR” package in R.ResultsOf the 36 SNPs associated with MDD, we found statistically significant evidence of a potential causal effect of MDD on the risk of sleep apnoea (odds ratio 1.004, 95% confidence interval: 1.001–1.006, p=0.001). Similar results were obtained using the MR-Egger and weighted median methods. Additionally, we found no heterogeneity or pleiotropy.ConclusionsOur findings suggest that depression slightly increases the risk of sleep apnoea. Further investigation of the potential biological mechanisms is necessary.

Simple Coagulation Profile as Predictor of Mortality in Adults Admitted with COVID-19: A Meta-Analysis

Context: COVID-19 severe manifestations must be detected as soon as possible. One of the essential poor characteristics is the involvement of coagulopathy. Simple coagulation parameters, including prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (aPTT), and platelet, are widely accessible in many health centers. Objectives: This meta-analysis aimed to determine the association between simple coagulation profiles and COVID-19 in-hospital mortality. Method: We systematically searched five databases for studies measuring simple coagulation parameters in COVID-19 on admission. The random-effects and inverse-variance weighting were used in the study, which used a standardized-mean difference of coagulation profile values. The odds ratios were computed using the Mantel-Haenszel formula for dichotomous variables. Results: This meta-analysis comprised a total of 30 studies (9,175 patients). In our meta-analysis, we found that non-survivors had a lower platelet count [SMD = -0.56 (95% CI: -0.79 to -0.33), P < 0.01; OR = 3.00 (95% CI: 1.66 to 5.41), P < 0.01], prolonged PT [SMD = 1.22 (95%CI: 0.71 to 1.72), P < 0.01; OR = 1.86 (95%CI: 1.43 to 2.43), P < 0.01], prolonged aPTT [SMD = 0.24 (95%CI: -0.04 to 0.52), P = 0.99], and increased INR [SMD = 2.21 (95%CI: 0.10 to 4.31), P = 0.04] than survivors. Conclusions: In COVID-19 patients, abnormal simple coagulation parameters on admission, such as platelet, PT, and INR, were associated with mortality outcomes.

Age-specific effects of body size on fracture risk in later life: A lifecourse Mendelian randomization study

Musculoskeletal conditions, including fractures, can have severe and long-lasting consequences. Higher body mass index in adulthood is widely acknowledged to be protective for most fracture sites, indicated through previous clinical and epidemiological observational research. However, the association between weight and bone health is complex and sources of bias, induced by confounding factors, may have distorted earlier findings. Employing a lifecourse Mendelian randomization (MR) approach by using genetic instruments to separate effects at different life stages, this investigation aims to explore how prepubertal and adult body size independently influence fracture risk in later life.Using data from a large UK-based prospective cohort, univariable and multivariable MR with inverse variance weighted meta-analysis were conducted to simultaneously estimate the effects of age-specific genetic proxies for body size (n=453,169) on the odds of fracture in later life (n=416,795). A two-step MR framework was additionally applied to elucidate potential mediators. Univariable and multivariable MR indicated strong evidence that higher body size in childhood reduced fracture risk in later life (OR, 95% CI: 0.89, 0.82 to 0.96, P=0.005 and OR, 95% CI: 0.76, 0.69 to 0.85, P=1×10−6, respectively). Conversely, higher body size in adulthood increased fracture risk (OR, 95% CI: 1.08, 1.01 to 1.16, P=0.023 and OR, 95% CI: 1.26, 1.14 to 1.38, P=2×10−6, respectively). Two-step MR analyses suggested that the effect of higher body size in childhood on reduced fracture risk was mediated by its influence on higher estimated bone mineral density (eBMD) in adulthood.This investigation provides novel evidence that higher body size in childhood has a direct effect on reduced fracture risk in later life through its influence on increased eBMD. Results indicate that higher body size in adulthood is a risk factor for fractures, opposing findings from earlier research. Protective effect estimates previously observed are likely attributed to childhood effects.