Gout and susceptibility and severity of COVID-19: A bidirectional Mendelian randomization analysis.
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ABSTRACT:
SUBMITTER: Peng H
PROVIDER: S-EPMC9212781 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Observational data from China, the United States, France, and Italy suggest that chronological age is an adverse COVID-19 outcome risk factor, with older patients having a higher severity and mortality rate than younger patients. Most studies have gotten the same view. However, the role of aging in COVID-19 adverse effects is unclear. To more accurately assess the effect of aging on adverse COVID-19, we conducted this bidirectional Mendelian randomization (MR) study. Epigenetic clocks and telomere length were used as biological indicators of aging. Data on epigenetic age (PhenoAge, GrimAge, Intrinsic HorvathAge, and HannumAge) were derived from an analysis of biological aging based on genome-wide association studies (GWAS) data. The telomere length data are derived from GWAS and the susceptibility and severity data are derived from the COVID-19 Host Genetics Initiative (HGI). Firstly, epigenetic age and telomere length were used as exposures, and following a screen for appropriate instrumental variables, we used random-effects inverse variance weighting (IVW) for the main analysis, and combined it with other analysis methods (e.g., MR Egger, Weighted median, simple mode, Weighted mode) and multiple sensitivity analysis (heterogeneity analysis, horizontal multiplicity analysis, "leave-one-out" analysis). For reducing false-positive rates, Bonferroni corrected significance thresholds were used. A reverse Mendelian randomization analysis was subsequently performed with COVID-19 susceptibility and severity as the exposure. The results of the MR analysis showed no significant differences in susceptibility to aging and COVID-19. It might suggest that aging is not a risk factor for COVID-19 infection (P-values are in the range of 0.05-0.94). According to the results of our analysis, we found that aging was not a risk factor for the increased severity of COVID-19 (P > 0.05). However, severe COVID-19 can cause telomere lengths to become shorter (beta = -0.01; se = 0.01; P = 0.02779). In addition to this, severe COVID-19 infection can slow the acceleration of the epigenetic clock "GrimAge" (beta = -0.24, se = 0.07, P = 0.00122), which may be related to the closely correlation of rs35081325 and COVID-19 severity. Our study provides partial evidence for the causal effects of aging on the susceptibility and severity of COVID-19.
| S-EPMC9538153 | biostudies-literature
Project description:BackgroundObservational 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.MethodsSummary 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.ResultsThe 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.ConclusionOur 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.
| S-EPMC9485491 | biostudies-literature
Project description:BackgroundEpidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses.Methods and findingsWe selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10-8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10-5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10-5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null.ConclusionsIn this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.
| S-EPMC7971850 | biostudies-literature
Project description:BackgroundThe severe acute respiratory syndrome coronavirus in 2019 (COVID-19) is still spreading and causing deaths worldwide, which further increased the burden of chronic diseases. Dyslipidemia is a common metabolic syndrome, which is a major risk factor for cardiovascular disease. However, studies on whether there is a direct causal relationship between COVID-19 and the exacerbation of hyperlipidemia are still scarce.MethodsTwo-sample Mendelian randomization was conducted using publicly available summary statistics from independent cohorts of European ancestry. For COVID-19 and hyperlipidemia, we used data from the ieu open GWAS project database. Inverse variance-weighted, mendelian randomization Egger, weighted median, simple mode, and weighted mode mendelian randomization analyses were performed, together with a range of sensitivity analyses.ResultsThere is no direct causal relationship between COVID-19 and dyslipidemia, regardless of COVID-19 severity or either dyslipidemic outcome. In combination with previous studies, the reason for the clinical outcome that COVID-19 increased the burden of dyslipidemia may be due to the exacerbation of pre-existing disease caused by COVID-19.ConclusionsCOVID-19 has no direct causal relationship with dyslipidemia.
| S-EPMC10560011 | biostudies-literature
Project description:Background: Carnitine, a potential substitute or supplementation for dexamethasone, might protect against COVID-19 based on its molecular functions. However, the correlation between carnitine and COVID-19 has not been explored yet, and whether there exists causation is unknown. Methods: A two-sample Mendelian randomization (MR) analysis was conducted to explore the causal relationship between carnitine level and COVID-19. Significant single nucleotide polymorphisms from genome-wide association study on carnitine (N = 7,824) were utilized as exposure instruments, and summary statistics of the susceptibility (N = 1,467,264), severity (N = 714,592) and hospitalization (N = 1,887,658) of COVID-19 were utilized as the outcome. The causal relationship was evaluated by multiplicative random effects inverse variance weighted (IVW) method, and further verified by another three MR methods including MR Egger, weighted median, and weighted mode, as well as extensive sensitivity analyses. Results: Genetically determined one standard deviation increase in carnitine amount was associated with lower susceptibility (OR: 0.38, 95% CI: 0.19-0.74, P: 4.77E-03) of COVID-19. Carnitine amount was also associated with lower severity and hospitalization of COVID-19 using another three MR methods, though the association was not significant using the IVW method but showed the same direction of effect. The results were robust under all sensitivity analyses. Conclusions: A genetic predisposition to high carnitine levels might reduce the susceptibility and severity of COVID-19. These results provide better understandings on the role of carnitine in the COVID-19 pathogenesis, and facilitate novel therapeutic targets for COVID-19 in future clinical trials.
| S-EPMC8656944 | biostudies-literature
Project description:The clinical management of patients with COVID-19 and cancer is a Gordian knot that has been discussed widely but has not reached a consensus. We introduced two-sample Mendelian randomization to investigate the causal association between a genetic predisposition to cancers and COVID-19 susceptibility and severity. Moreover, we also explored the mutation landscape, expression pattern, and prognostic implications of genes involved with COVID-19 in distinct cancers. Among all of the cancer types we analyzed, only the genetic predisposition to lung adenocarcinoma was causally associated with increased COVID-19 severity (OR = 2.93, β = 1.074, se = 0.411, p = 0.009) with no obvious heterogeneity (Q = 17.29, p = 0.24) or symmetry of the funnel plot. In addition, the results of the pleiotropy test demonstrated that instrument SNPs were less likely to affect COVID-19 severity via approaches other than lung adenocarcinoma cancer susceptibility (p = 0.96). Leave-one-out analysis showed no outliers in instrument SNPs, whose elimination rendered alterations in statistical significance, which further supported the reliability of the MR results. Broad mutation and differential expression of these genes were also found in cancers, which may provide valuable information for developing new treatment modalities for patients with both cancer and COVID-19. For example, ERAP2, a risk factor for COVID-19-associated death, is upregulated in lung squamous cancer and negatively associated with patient prognosis. Hence, ERAP2-targeted treatment may simultaneously reduce COVID-19 disease severity and restrain cancer progression. Our results highlighted the importance of strengthening medical surveillance for COVID-19 deterioration in patients with lung adenocarcinoma by showing their causal genetic association. For these patients, a delay in anticancer treatment, such as chemotherapy and surgery, should be considered.
| S-EPMC8818950 | biostudies-literature
Project description:Observational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome the limitations of observational studies, e.g., unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, we applied a two-sample, bidirectional, univariable, and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released in January 2021). In single-variable Generalized Summary MR analysis, the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06-1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased the risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate.
| S-EPMC8027711 | biostudies-literature
Project description: Not available
| S-EPMC9561435 | biostudies-literature
Project description:IntroductionObservational studies have reported an association between polycystic ovary syndrome (PCOS) and COVID-19, but a definitive causal relationship has not been established. This study aimed to assess this association using two-way two-sample Mendelian randomization (MR).MethodsA summary of PCOS characteristics was compiled using the PCOS summary statistics from the Apollo University of Cambridge Repository. COVID-19 susceptibility and severity statistics, including hospitalization and extremely severe disease, were obtained from genome-wide association studies from the COVID-19 Host Genetics Initiative. The primary analysis used the inverse variance-weighted method, supplemented by the weighted median, MR-Egger, and MR-PRESSO methods.ResultsThe forward MR analysis showed no significant impact of PCOS on COVID-19 susceptibility, hospitalization, or severity (OR = 0.983, 1.011, 1.014; 95% CI = 0.958-1.008, 0.958-1.068, 0.934-1.101; and p = 0.173, 0.68, 0.733; respectively). Similarly, reverse MR analysis found no evidence supporting COVID-19 phenotypes as risk or protective factors for PCOS (OR = 1.041, 0.995, 0.944; 95% CI = 0.657-1.649, 0.85-1.164, 0.843-1.058; and p = 0.864, 0.945, 0.323; respectively). Consequently, no significant association between any COVID-19 phenotype and PCOS was established.ConclusionThis MR study suggested that PCOS is not a causal risk factor for the susceptibility and severity of COVID-19. The associations identified in previous observational studies might be attributable to the presence of comorbidities in the patients.
| S-EPMC10515223 | biostudies-literature
Project description:This study aimed to evaluate the host genetic liability of coronavirus disease 2019 (covid-19) with platelet traits using the Mendelian randomization (MR) approach. We conducted a bidirectional two-sample MR using summary statistics from the largest genome-wide association study of three variables, covid-19 severity (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2] infection, covid-19 hospitalization, and severe covid-19, N = ~1 059 456-1 557 411) and four platelet traits (mean platelet volume [MPV], plateletcrit, platelet distribution width, and platelet count; N = 408 112). Inverse-variance weighted (IVW), median weighted, MR-Egger, and contamination mixture methods were used to estimate the causal association. Null and inconsistent associations in the IVW and sensitivity analyses were observed for SARS-CoV-2 infection and covid-19 hospitalization with platelet traits. For severe covid-19, significant associations with MPV and platelet count were observed in the IVW and sensitivity analyses, with the betaIVW of 0.01 (95% confidence interval [CI]: 0.005-0.016, p = 3.51 × 10-4 ) and -0.009 (95% CI: -0.015 to -0.002, p = 0.008) per doubling in odds of severe covid-19, respectively. Conversely, null associations were observed for platelet traits with covid-19 traits. In conclusion, host genetic liability to severe covid-19 was causally associated with increased MPV and reduced platelet count, which may provide insights into evaluating hypercoagulability and thromboembolic events in covid-19 patients.
| S-EPMC9348324 | biostudies-literature