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Causal Relationship Between Lung Function and Atrial Fibrillation: A Two Sample Univariable and Multivariable, Bidirectional Mendelian Randomization Study.

ABSTRACT: Background: Observational studies have identified impaired lung function accessed by forced expiratory volume in one second (FEV1), forced vital capacity (FVC) or the ratio of FEV1 over FVC (FEV1/FVC) as an independent risk factor for atrial fibrillation (AF). However, the result may be affected by confounders or reverse causality. Methods: We performed univariable MR (uvMR), multivariable MR (mvMR) and bidirectional two-sample MR to jointly estimate the causality of lung function with AF. Apart from the inverse variance weighted (IVW) approach as the main MR analysis, three complementary sensitive analyses approaches including MR-Egger regression, weighted median (WM) MR and Pleiotropy Residual Sum and Outlier (MR-PRESSO) in uvMR as well as mvMR-Egger and mvMR-PRESSO in mvMR were applied to control for pleiotropy. Linkage disequilibrium score (LDSC) regression was applied to estimate genetic correlation between lung function and AF. Results: All forward and reverse uvMR analyses consistently suggested absent causal relations between lung function and AF risk [forward IVW: odds ratio (OR)_FEV1 = 1.031, 95% CI = 0.909-1.169, P = 0.630; OR_FVC = 1.002, 95% CI = 0.834-1.204, P = 0.982; OR_FEV1/FVC = 1.076, 95% CI = 0.966-1.199, P = 0.182; reverse IVW: OR_FEV1 = 0.986, 95% CI = 0.966-1.007, P = 0.187; OR_FVC = 0.985, 95% CI = 0.965-1.006, P = 0.158; OR_FEV1/FVC = 0.994, 95% CI = 0.973-1.015, P = 0.545]. The forward MR-Egger showed that each standard deviation (SD) increase in FEV1/FVC was related to a higher AF risk (OR = 1.502, 95% CI = 1.178-1.915, P = 0.006) without heterogeneity (Q_pval = 0.064), but pleiotropy effect exist (intercept = -0.017, P = 0.012). However, this significant effect disappeared after adjustment of FEV1 and FVC (OR = 1.523, 95% CI = 0.445-5.217, P = 0.503) in mvMR. No evidence was found for independent causal effects of FEV1 and FVC on AF in mvMR analysis by using mvIVW method (OR_FEV1 = 0.501, 95% CI = 0.056-4.457, P = 0.496; OR_FVC = 1.969, 95% CI = 0.288-13.474, P = 0.490). Notably, the association between lung function and AF were replicated using the FinnGen cohort data. Conclusions: Our findings reported no coheritability between lung function and AF, and failed to find substantial causal relation between decreased lung function and risk of AF. However, lung function and AF were both associated with inflammation, which may be potential pathway, warranting further study.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC8635999 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:We performed univariable and multivariable Mendelian randomization (MR) analysis to evaluate the association between blood lipids and risk of atrial fibrillation (AF), including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), Apolipoprotein A1, and Apolipoprotein B. Data on the single nucleotide polymorphisms (SNPs) related to blood lipids were obtained from the UK Biobank study with more than 300,000 subjects of White British European ancestry, and data for AF were from the latest meta-analysis of Genome-wide association study (GWASs) with six independent cohorts with more than 1,000,000 subjects of European ancestry. The univariable MR analysis was conducted to explore whether genetic evidence of individual lipid-related traits was significantly associated with AF risks and multivariable MR analysis with three models was performed to assess the independent effects of lipid-related traits. The IVW estimate showed that genetically predicted LDL-C (OR: 1.016, 95% CI: 0.962-1.073, p = 0.560), HDL-C (OR: 0.951, 95% CI: 0.895-1.010, p = 0.102), TG (OR: 0.961, 95% CI: 0.889-1.038, p = 0.313), Apolipoprotein A1 (OR: 0.978, 95% CI: 0.933-1.025, p = 0.356), and Apolipoprotein B (OR: 1.008, 95% CI: 0.959-1.070, p = 0.794) were not causally associated with the risk of AF. Sample mode (OR: 0.852, 95% CI: 0.731-0.993, p = 0.043) and weighted mode (OR: 0.907, 95% CI: 0.841-0.979, p = 0.013) showed that a 1-unit increase in TG (mmol/L) was causally associated with a 14.8% and 9.3% relative decrease in AF risk, respectively. The multivariable MR analysis with model 1, 2, and 3 indicated that TG, LDL-C, HDL-C, Apolipoprotein A1, and Apolipoprotein B were not associated with the lower risk for AF. Our multivariable Mendelian randomization analysis (MVMR) finding suggested no genetic evidence of lipid traits was significantly associated with AF risk. Furthermore, more work is warranted to confirm the potential association between lipid traits and AF risks.

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.

Project description:BackgroundWhether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders.MethodsUnivariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium.ResultsWe observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD.ConclusionsOur results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.

Project description:BackgroundAccumulating evidence suggests that the gut microbiota and its metabolites may be involved in autoimmune hypothyroidism. However, the causal association between gut microbiota, metabolites and autoimmune hypothyroidism remains to be determined.MethodsInstrumental variables were screened from the GWAS datasets of 211 gut microbiota taxonomic groups, gut microbiota-derived metabolites, and autoimmune hypothyroidism. Univariable Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) were used to analyse the potential causal relationship between autoimmune hypothyroidism, these metabolites, or these microbiota. During the MR analysis, we alternated multiple MR methods with different model assumptions to assess the consistency and robustness of the findings: inverse variance weighted (IVW), weighted median, MR pleiotropy residual sum and outlier (MRPRESSO) and MR-Egger methods. Reverse MR analysis was performed to assess the possibility of reverse causality. Finally, enrichment analyses were used to investigate potential biofunctions.ResultsThe IVW results of univariable MR showed that the phyla Actinobacteria, genus DefluviitaleaceaeUCG011, genus Eggerthella, family Defluviitaleaceae, genus Subdoligranulum, genus RuminococcaceaeUCG011, and genus Intestinimonas were associated with autoimmune hypothyroidism. After FDR adjustment, the absence of a causal relationship between gut microbiota and autoimmune hypothyroidism (PFDR > 0.05) suggested a possible marginal association. The results on gut metabolites showed that N-(3-furoyl)glycine, pipecolate, phenylalanine, allantoin, indololactate and alanine were associated with autoimmune hypothyroidism. After FDR correction, only indololactate was associated with hypothyroidism (OR=1.592; 95% CI, 1.228-2.065; PFDR= 0.036). Family Defluviitaleaceae and genus DefluviitaleaceaeUCG011 were suggestively significant in the MVMR. The results of reverse MR analysis showed no reverse causality between autoimmune hypothyroidism and the identified gut microbiota. Enrichment analysis revealed that several key regulatory pathways were significantly enriched.ConclusionThis study supported that there were beneficial or detrimental causal effects of gut microbiota and its metabolites on autoimmune hypothyroidism risk, which provides more theoretical support for mechanistic research on the "thyroid-gut" axis.

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Causal Relationship Between Lung Function and Atrial Fibrillation: A Two Sample Univariable and Multivariable, Bidirectional Mendelian Randomization Study.

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