Coagulation factors and the incidence of COVID-19 severity: Mendelian randomization analyses and supporting evidence.
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ABSTRACT:
SUBMITTER: Zhou Y
PROVIDER: S-EPMC8181534 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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:Background We conducted Mendelian randomization analyses investigating the linear associations of genetically proxied inhibition of different coagulation factors with risk of common cardiovascular diseases. Methods and Results Genetic instruments proxying coagulation factor inhibition were identified from genome-wide association studies for activated partial thromboplastin time and prothrombin time in BioBank Japan (up to 58 110 participants). Instruments were identified for 9 coagulation factors (fibrinogen alpha, beta, and gamma chain; and factors II, V, VII, X, XI, and XII). Age- and sex-adjusted estimates for associations of the instruments with the outcomes were derived from UK Biobank and the FinnGen, CARDIoGRAMplusC4D (Coronary Artery Disease Genome-wide Replication and Meta-analysis), and MEGASTROKE consortia with numbers of incident and prevalent cases of 820 to 60 810. Genetically proxied inhibition of fibrinogen alpha, beta, and gamma chain, factor II, and factor XI were associated with reduced risk of venous thromboembolism (P<0.001). With the exception of fibrinogen beta and factor II, inhibition of these factors was also associated with reduced risk of any ischemic stroke and cardioembolic stroke (P≤0.002). Genetically proxied inhibition of fibrinogen beta and gamma were associated with reduced large-artery stroke risk (P=0.001). There were suggestive protective associations of genetically proxied inhibition of factors V, VII, and X with ischemic stroke (P<0.05), and suggestive adverse associations of genetically proxied inhibition of factors II and XII with subarachnoid hemorrhage. Conclusions This study supports targeting fibrinogen and factor XI for reducing venous thromboembolism and ischemic stroke risk, and showed suggestive evidence that inhibition of factors V, VII, and X might reduce ischemic stroke risk.
| S-EPMC8174173 | biostudies-literature
Project description: Not available
| S-EPMC9212781 | biostudies-literature
Project description:Emerging evidence supports a link between environmental factors-including air pollution and chemical exposures, climate, and the built environment-and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and coronavirus disease 2019 (COVID-19) susceptibility and severity. Climate, air pollution, and the built environment have long been recognized to influence viral respiratory infections, and studies have established similar associations with COVID-19 outcomes. More limited evidence links chemical exposures to COVID-19. Environmental factors were found to influence COVID-19 through four major interlinking mechanisms: increased risk of preexisting conditions associated with disease severity; immune system impairment; viral survival and transport; and behaviors that increase viral exposure. Both data and methodologic issues complicate the investigation of these relationships, including reliance on coarse COVID-19 surveillance data; gaps in mechanistic studies; and the predominance of ecological designs. We evaluate the strength of evidence for environment-COVID-19 relationships and discuss environmental actions that might simultaneously address the COVID-19 pandemic, environmental determinants of health, and health disparities.
| S-EPMC10044492 | biostudies-literature
Project description:Previous studies reported associations between obesity measured by body mass index (BMI) and coronavirus disease 2019 (COVID-19). However, BMI is calculated only with height and weight and cannot distinguish between body fat mass and fat-free mass. Thus, it is not clear if one or both of these measures are mediating the relationship between obesity and COVID-19. Here, we used Mendelian randomization (MR) to compare the independent causal relationships of body fat mass and fat-free mass with COVID-19 severity. We identified single nucleotide polymorphisms associated with body fat mass and fat-free mass in 454,137 and 454,850 individuals of European ancestry from the UK Biobank, respectively. We then performed two-sample MR to ascertain their effects on severe COVID-19 (cases: 4,792; controls: 1,054,664) from the COVID-19 Host Genetics Initiative. We found that an increase in body fat mass by one standard deviation was associated with severe COVID-19 (odds ratio (OR)body fat mass = 1.61, 95% confidence interval [CI]: 1.28-2.04, P = 5.51 × 10-5; ORbody fat-free mass = 1.31, 95% CI: 0.99-1.74, P = 5.77 × 10-2). Considering that body fat mass and fat-free mass were genetically correlated with each other (r = 0.64), we further evaluated independent causal effects of body fat mass and fat-free mass using multivariable MR and revealed that only body fat mass was independently associated with severe COVID-19 (ORbody fat mass = 2.91, 95% CI: 1.71-4.96, P = 8.85 × 10-5 and ORbody fat-free mass = 1.02, 95%CI: 0.61-1.67, P = 0.945). In summary, this study demonstrates the causal effects of body fat accumulation on COVID-19 severity and indicates that the biological pathways influencing the relationship between COVID-19 and obesity are likely mediated through body fat mass.
| S-EPMC9381824 | biostudies-literature
Project description:BackgroundRecent omic studies prioritised several drug targets associated with coronavirus disease 2019 (COVID-19) severity. However, little evidence was provided to systematically estimate the effect of drug targets on COVID-19 severity in multiple ancestries.MethodsIn this study, we applied Mendelian randomization (MR) and colocalization approaches to understand the putative causal effects of 16,059 transcripts and 1608 proteins on COVID-19 severity in European and effects of 610 proteins on COVID-19 severity in African ancestry. We further integrated genetics, clinical and literature evidence to prioritise drug targets. Additional sensitivity analyses including multi-trait colocalization and phenome-wide MR were conducted to test for MR assumptions.FindingsMR and colocalization prioritized four protein targets, FCRL3, ICAM5, ENTPD5 and OAS1 that showed effect on COVID-19 severity in European ancestry. One protein target, SERPINA1 showed a stronger effect in African ancestry but much weaker effect in European ancestry (odds ratio [OR] in Africans=0.369, 95%CI=0.203 to 0.668, P = 9.96 × 10-4; OR in Europeans=1.021, 95%CI=0.901 to 1.157, P = 0.745), which suggested that increased level of SERPINA1 will reduce COVID-19 risk in African ancestry. One protein, ICAM1 showed suggestive effect on COVID-19 severity in both ancestries (OR in Europeans=1.152, 95%CI=1.063 to 1.249, P = 5.94 × 10-4; OR in Africans=1.481, 95%CI=1.008 to 2.176; P = 0.045). The OAS1, SERPINA1 and ICAM1 effects were replicated using updated COVID-19 severity data in the two ancestries respectively, where alternative splicing events in OAS1 and ICAM1 also showed marginal effects on COVID-19 severity in Europeans. The phenome-wide MR of the prioritised targets on 622 complex traits provided information on potential beneficial effects on other diseases and suggested little evidence of adverse effects on major complications.InterpretationOur study identified six proteins as showing putative causal effects on COVID-19 severity. OAS1 and SERPINA1 were targets of existing drugs in trials as potential COVID-19 treatments. ICAM1, ICAM5 and FCRL3 are related to the immune system. Across the six targets, OAS1 has no reliable instrument in African ancestry; SERPINA1, FCRL3, ICAM5 and ENTPD5 showed a different level of putative causal evidence in European and African ancestries, which highlights the importance of more powerful ancestry-specific GWAS and value of multi-ancestry MR in informing the effects of drug targets on COVID-19 across different populations. This study provides a first step towards clinical investigation of beneficial and adverse effects of COVID-19 drug targets.FundingNo.
| S-EPMC9235320 | biostudies-literature
Project description: Not available
| S-EPMC9852317 | biostudies-literature
Project description:AbstractMotivationIn recent years, Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods.Implementationmrrobust is freely available as a Stata package.General featuresThe package includes inverse variance weighted estimation, as well as a range of median, modal and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualizing each estimate either individually or simultaneously. The package also provides statistics such as IGX2, which are useful in assessing attenuation bias in causal estimates.AvailabilityThe software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].
| S-EPMC6659377 | biostudies-other