Project description:BackgroundThyroid hormones (THs) play a crucial role in regulating various biological processes, particularly the normal development and functioning of the central nervous system (CNS). Epilepsy is a prevalent neurological disorder with multiple etiologies. Further in-depth research on the role of thyroid hormones in epilepsy is warranted.MethodsGenome-wide association study (GWAS) data for thyroid function and epilepsy were obtained from the ThyroidOmics Consortium and the International League Against Epilepsy (ILAE) Consortium cohort, respectively. A total of five indicators of thyroid function and ten types of epilepsy were included in the analysis. Two-sample Mendelian randomization (MR) analyses were conducted to investigate potential causal relations between thyroid functions and various epilepsies. Multiple testing correction was performed using Bonferroni correction. Heterogeneity was calculated with the Cochran's Q statistic test. Horizontal pleiotropy was evaluated by the MR-Egger regression intercept. The sensitivity was also examined by leave-one-out strategy.ResultsThe findings indicated the absence of any causal relationship between abnormalities in thyroid hormone and various types of epilepsy. The study analyzed the odds ratio (OR) between thyroid hormones and various types of epilepsy in five scenarios, including free thyroxine (FT4) on focal epilepsy with hippocampal sclerosis (IVW, OR = 0.9838, p = 0.02223), hyperthyroidism on juvenile absence epilepsy (IVW, OR = 0.9952, p = 0.03777), hypothyroidism on focal epilepsy with hippocampal sclerosis (IVW, OR = 1.0075, p = 0.01951), autoimmune thyroid diseases (AITDs) on generalized epilepsy in all documented cases (weighted mode, OR = 1.0846, p = 0.0346) and on childhood absence epilepsy (IVW, OR = 1.0050, p = 0.04555). After Bonferroni correction, none of the above results showed statistically significant differences.ConclusionThis study indicates that there is no causal relationship between thyroid-related disorders and various types of epilepsy. Future research should aim to avoid potential confounding factors that might impact the study.
Project description:IntroductionPrevious research has reported that the gut microbiota performs an essential role in sleep through the microbiome-gut-brain axis. However, the causal association between gut microbiota and sleep remains undetermined.MethodsWe performed a two-sample, bidirectional Mendelian randomization (MR) analysis using genome-wide association study summary data of gut microbiota and self-reported sleep traits from the MiBioGen consortium and UK Biobank to investigate causal relationships between 119 bacterial genera and seven sleep-associated traits. We calculated effect estimates by using the inverse-variance weighted (as the main method), maximum likelihood, simple model, weighted model, weighted median, and MR-Egger methods, whereas heterogeneity and pleiotropy were detected and measured by the MR pleiotropy residual sum and outlier method, Cochran's Q statistics, and MR-Egger regression.ResultsIn forward MR analysis, inverse-variance weighted estimates concluded that the genetic forecasts of relative abundance of 42 bacterial genera had causal effects on sleep-associated traits. In the reverse MR analysis, sleep-associated traits had a causal effect on 39 bacterial genera, 13 of which overlapped with the bacterial genera in the forward MR analysis.DiscussionIn conclusion, our research indicates that gut microbiota may be involved in the regulation of sleep, and conversely, changes in sleep-associated traits may also alter the abundance of gut microbiota. These findings suggest an underlying reciprocal causal association between gut microbiota and sleep.
Project description:IntroductionWe conducted a two-sample Mendelian randomization study to determine the associations of modifiable risk factors with epilepsy.MethodsFourteen potential risk factors for epilepsy were selected based on a systematic review of risk factors for epilepsy. Single-nucleotide polymorphisms associated with each exposure at the genome-wide significance threshold (p < 5×10-8 ) were proposed as instrumental variables from corresponding genome-wide association studies. Summary-level data for epilepsy were obtained from the FinnGen consortium (4,588 cases and 144 780 noncases). Potential causal associations (p < .05) were attempted for replication using UK Biobank data (901 cases and 395 209 controls).ResultsAmong 14 potential risk factors, 4 showed significant associations with epilepsy in FinnGen. All associations were directionally similar in UK Biobank and associated with epilepsy at p ≤ .004 in meta-analyses of FinnGen and UK Biobank data. The odds ratios of epilepsy were 1.46 (95% CI, 1.18, 1.82) for one unit increase in log odds ratio of having depression, 1.44 (95% CI, 1.13, 1.85) for one standard deviation increase in serum ferritin, 1.12 (95% CI, 1.04, 1.21) for one standard deviation increase in transferrin saturation, and 1.25 (95% CI, 1.09, 1.43) for one standard deviation increase in the prevalence of smoking initiation. There were suggestive associations of serum iron and magnesium with epilepsy. No association was observed for insomnia, blood pressure, alcohol consumption, or serum vitamin B12, 25-hydroxyvitamin D and calcium levels.ConclusionThis MR study identified several modifiable risk factors for adulthood epilepsy. Reducing prevalence of depression and smoking initiation should be considered as primary prevention strategies for epilepsy.
Project description:ObjectivesEpilepsy and amyotrophic lateral sclerosis (ALS) are common neurological disorders. The association between the two disorders has been raised in observational studies. However, it is uncertain to what extent they have mutual causal effects. In this study, we aimed to investigate their causal association using a two-sample Mendelian randomization (MR) method.MethodsWe performed a two-sample bidirectional MR analysis to evaluate the causal association of epilepsy with the risk of ALS. Publicly published genome-wide association study statistics for epilepsy and ALS were used in the study. The primary analysis included genetic variants with a p value of less than 1 × 10-5 as instrumental variables. We applied several alternative methods, including inverse variance weighting, weighted median, simple mode, weighted mode, MR-Egger regression and MR pleiotropy residual sum and outlier, and statistical graphs to assess the associations of epilepsy and its subtype with the risk of ALS. Reverse MR analyses were also performed to examine the association of ALS with the risk of epilepsy.ResultsThe primary MR analysis found no causal effect of epilepsy on risk of ALS (odds ration [OR]: 1.133, 95% confidence interval [CI]: 0.964-1.332, p = .130). Among subtypes of epilepsy, it also failed to observe any causal association between general epilepsy and ALS (OR: 1.036, 95% CI: 0.969-1.108, P = .300). However, focal epilepsy contributed to an increase in the risk of ALS (OR: 1.177, 95% CI: 1.027-1.348, p = .019). Moreover, the investigation of reverse causalities did not reveal significant results.ConclusionsThe current study supports a causal influence of focal epilepsy on ALS risk. Future studies are needed to explore its potential role in ALS.
Project description:BackgroundDysbiosis of gut microbiota has been linked to numerous diseases, including cancer. The unique role of gut microbiota in urological tumors is gaining prominence. However, it is still controversial whether the dysbiosis of gut microbiota should be one of the etiological factors of bladder cancer (BCa), prostate cancer (PCa) or kidney cancer (KCa).Materials and methodsThe microbiome genome-wide association study (GWAS) from the MiBioGen consortium (18,340 samples of 24 population-based cohorts) was utilized as the exposure data. Additionally, outcomes data (951 BCa cases and 307,092 controls; 1,631 KCa cases and 238,678 controls; 79,148 PCa cases and 61,106 controls) were extracted from the GWAS of the FinnGen and PRACTICAL consortia. To detect the potential causative bacterial traits for BCa, PCa, and KCa, a two-sample Mendelian randomization (MR) analysis was performed, employing the inverse-variance weighted or Wald ratio method. Sensitivity analyses were subsequently conducted to explore the robustness of the primary results. Finally, the reverse MR analysis was undertaken to mitigate the reverse causation.ResultsThis study suggested that Bifidobacterium (p = 0.030), Actinobacteria (p = 0.037 for phylum, 0.041 for class), and Ruminococcustorques group (p = 0.018), exhibited an association with an increased risk of BCa using either the inverse-variance weighted or Wald ratio method. By utilizing the Wald ratio method, Allisonella (p = 0.004, p = 0.038) was associated with a decreased risk of BCa and PCa, respectively. Furthermore, Ruminococcustorques group (p = 0.028) and Erysipelatoclostridium (p = 0.048) were causally linked to an elevated risk of KCa.ConclusionsThis MR study supports that genetically predicted gut microbiota is causally related to BCa, PCa and KCa. Additionally, distinct bacterial traits are identified in relation to each tumor type.
Project description:Introduction: Certain growth factors (GFs) are associated with constipation, but few studies has analyzed the causal associations between the two. Therefore, this study used two-sample Mendelian randomization (MR) to systematically analyze the causal associations between GF levels and constipation based on data from genome-wide association studies (GWAS). Methods: Both GF and constipation data were obtained from European populations. GFs, as an exposure variable, were obtained from a genetic map of the human plasma proteome containing 3,301 samples, another GWAS dataset on 90 circulating proteins containing 30,931 samples, and a GWAS dataset containing 3,788 samples. Constipation, as an outcome variable, was obtained from the FinnGen project containing 26,919 cases and 282,235 controls and another UK Biobank dataset containing 3,328 cases and 459,682 controls. Single-nucleotide polymorphisms strongly associated with GFs were regarded as instrumental variables. Inverse-variance weighting, MR-Egger regression, weight median, simple mode, and weight mode methods were used to determine genetic associations. Cochran's Q test, Egger intercept, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier tests were used to analyze sensitivity. Results: The IVW analysis based on FinnGen showed that NGFI-A-binding protein 2 and vascular endothelial growth factor receptor 2 were inversely associated with constipation, and that fibroblast growth factor 7 and transforming growth factor beta receptor II levels were positively associated with constipation. The IVW analysis based on UK Biobank showed that proheparin-binding epidermal growth factor, platelet-derived growth factor AA, and vascular endothelial growth factor121 were inversely associated with constipation. Conclusion: This study showed that some GFs are genetically associated with the risk of constipation.
Project description:BackgroundObservational studies have indicated the association of alteration of adipokines with Alzheimer's disease (AD). However, it remains unclear whether the associations are causal.ObjectiveTo determine the causal associations between adipokines and AD.MethodsA Mendelian randomization (MR) method was applied to investigate the causal relationships of adipokines, including adiponectin and resistin, with risk of AD. Genetic proxies from genome-wide association studies (GWAS) of adiponectin and resistin were selected as instrumental variables. GWAS summary statistics for AD were extracted as outcome.ResultsIn this study, we found evidence of the causal effects of adiponectin on AD (OR: 0.850, 95% CI: 0.731-0.990, p = 0.037). However, no relationship between resistin and AD (OR: 0.936, 95% CI: 0.851-1.029, p = 0.171) was detected. In the reverse causation analysis, null associations of AD were found for adiponectin and resistin (all p > 0.05).ConclusionsThis study provides evidence of causality between adiponectin and risk of AD. However, no genetic susceptibility of resistin was discovered for AD.
Project description:BackgroundLower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.Methods and findingsWe used summary statistics from genome-wide association studies (GWAS) of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Of 74 single nucleotide polymorphisms (SNPs) that predict educational attainment, 57 (or their highly correlated proxies) were present in the smoking initiation, cigarettes per day and smoking cessation GWAS, and 72 in the cotinine GWAS. Various complementary MR techniques (inverse variance weighted regression, MR Egger, weighted median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report [e.g. inverse variance weighted beta -2.25, 95% confidence interval (CI) -3.81, -0.70, P = 0.005] and cotinine levels [e.g. inverse variance weighted beta -0.34, 95% CI -0.67, -0.01, P = 0.057]), and greater likelihood of smoking cessation among smokers (inverse variance weighted beta 0.65, 95% CI 0.35, 0.95, P = 5.54 × 10-5). Less consistent across the different techniques were associations between educational attainment and smoking initiation.ConclusionsOur findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.
Project description:Prostate cancer (PCa) is a common form of malignancy among men. The associations between socioeconomic status (SES) indicators and PCa risks remain incompletely elucidated. Through two-sample Mendelian randomization (MR), this research seeks to assess the causal links between 4 genetically predicted SES indicators-average total household income before tax, the Townsend deprivation index at recruitment, unemployed status and college or university degree in the household-and PCa. Genetic variants were extracted from publicly available genome-wide association studies (GWAS) under stringent threshold as instrumental variables (IVs). We employed the inverse variance weighted (IVW), weighted median, weighted mode and MR-Egger to estimate the causal effect, with sensitivity analyses such as Cochran's Q tests, MR-Egger, MR-PRESSO and leave-one-out performed to detect potential heterogeneity and pleiotropy. Our MR analysis revealed a causal association between unemployment and prostate cancer (OR: 3.07, 95%CI:1.12-8.42, P = 0.03). No causal associations were identified between other SES components and prostate cancer. The MR-PRESSO suggested 2 outliers in the association between college or university degree in household and prostate cancer, which rendered the association significant after outliers were removed. The heterogeneity and pleiotropy are unlikely to affect our causal estimate. Our results indicated that unemployment poses a potential risk factor for the incidence of PCa. The findings highlight the necessity for further exploration into the underlying etiology of PCa.