Is Hearing Impairment Causally Associated With Falls? Evidence From a Two-Sample Mendelian Randomization Study

The correlation between obesity and primary open-angle glaucoma (POAG) has not yet been fully established. The aim of this study was to investigate the causal relationship between obesity and POAG by a two-sample Mendelian randomization (MR) study. In this study, body mass index (BMI), an index to evaluate general obesity, and waist and hip circumference, indices to evaluate abdominal obesity, were selected as exposures in MR analysis. Single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables (IVs). Summary data from genome-wide association studies (GWASs) based on a European ancestry by Locke et al., with regard to BMI, and Shungin et al., with regard to waist and hip circumference, were used. Genetic predictors of POAG were obtained from public GWAS summary data. To assess the causal effect of obesity on POAG, the inverse variance-weighted (IVW) method was used as the primary method, and other methods, such as MR–Egger, weighted median, simple mode, and weighted mode, were also used as complementary analyses. Finally, we performed Cochran’s Q statistic to assess heterogeneity, and sensitivity analysis was performed to evaluate the reliability and stability of the MR results. MR analysis showed that BMI has a positive effect on the risk of POAG, with 1 standard deviation (SD) increase in BMI; the risk of POAG increases by approximately 90.9% [OR = 1.909; 95% CI= (1.225, 2.975); p = 0.0042)] (analyzed by IVW); there were no heterogeneity and pleiotropy in the result; and waist circumference also had a positive effect on the risk of POAG [OR = 2.319; 95% CI= (1.071, 5.018); p = 0.033)] analyzed by weighted median. As hip circumference increases, with 1 SD increase in hip circumference, the risk of POAG increases by approximately 119% [OR = 2.199; 95% CI= (1.306, 3.703); p = 0.00305)] estimated by IVW, there were not heterogeneity and pleiotropy as for the result. Our study for the first time confirms that obesity might increase the risk of POAG using two-sample MR analysis. These results might provide guidance on the prevention and treatment of POAG.

Observational studies suggest a potential link between obesity and constipation, but existing results are conflicting. Therefore, we conducted a Mendelian randomization (MR) study and meta-analysis to assess the causal relationship between obesity and the risk of constipation. In this study, independent genetic variants closely related to constipation were acquired from a genome-wide association study (GWAS) to analyze the relationship between genetically predisposed obesity and the risk of constipation. Waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and body mass index (BMI) were collected from the GWAS. Then, the causal relationship between constipation and obesity was explored using a two-sample MR study in both directions. The robustness of the results was evaluated using sensitivity analysis. Furthermore, a systemic review and meta-analysis were performed to calculate relative risks (RRs) with corresponding 95% confidence intervals (95% CIs). Subgroup analyses stratified by age and obesity degree were completed. To evaluate whether the current studies were affected by unmeasured confounders, E-values of each study were determined. In MR analysis, the incidence of constipation increased with the increase in BMI [inverse variance-weighted (IVW) odds ratio (OR) = 1.138 (1.029, 1.260), p = 0.012]. In addition, constipation was impacted by WC [IVW OR = 1.220 (1.061, 1.402), p = 0.005]. However, there was no evidence that WHR [IVW OR = 1.833 (0.826, 4.065), p = 0.136] or HC [IVW OR = 0.949, (0.836, 1.077), p = 0.415] has a causal effect on constipation. In reverse MR analysis, there was no evidence supporting the causality between constipation and obesity [BMI IVW OR = 1.010 (0.998, 1.022), p = 0.089; WHR IVW OR = 1.000 (0.946, 1.057), p = 0.994; WC IVW OR = 1.008 (0.995, 1.022), p = 0.217; HC IVW OR = 0.996 (0.982, 1.011), p = 0.626]. In the meta-analysis, 14 eligible articles were included, involving 43,488 subjects. According to the results of the meta-analysis, the risk of obesity and overweight significantly increased the risk of constipation [RR = 1.145 (0.952, 1.376)]. This was consistent with the MR analysis results. Moreover, overweight and obesity were significantly related to a higher constipation risk among children [overweight RR = 1.112 (0.943, 1.312); obesity RR = 1.407 (1.282, 1.544)]. Additionally, overweight in adults could decrease the risk of constipation [RR = 0.940 (0.827, 1.068)]. Nevertheless, no significant association was observed between obesity in adults and the risk of constipation [RR = 1.000 (0.768, 1.303)]. Sensitivity analysis revealed the robustness of our findings. In this combined MR study and meta-analysis, obesity is associated with an increased risk of constipation. The MR analysis demonstrates the causal relationship between genetically predisposed obesity and the risk of constipation. More research is required to investigate the potential correlation between obesity and the risk of constipation and associated mechanisms.

The precise association between green tea intake and gastrointestinal disorders remains controversial. This study aimed to investigate the potential causal association between green tea intake and gastrointestinal disorders through a two-sample Mendelian randomization (MR) study. Utilizing publicly accessible data from genome-wide association studies (GWAS), we identified SNPs strongly linked with the study variables from multiple large databases to serve as instrumental variables (IVs). MR analyses were executed utilizing the inverse variance weighting (IVW) method, with the resultant effect estimates serving as the primary outcome measure. In addition, a multivariate MR design was performed to adjust for smoking and alcohol consumption. To ensure the robustness of our findings, a series of sensitivity analyses were conducted to assess reliability. Univariable MR analysis revealed suggestive associations between green tea intake and gastroesophageal reflux (OR = 0.9950, 95% CI 0.9900-1.0000, p IVW = 0.047), diverticulosis (OR = 0.9998, 95% CI 0.9996-1.0000, p IVW = 0.030), Crohn's disease (OR = 1.0001, 95% CI 1.0000-1.0002, p IVW = 0.019), and cholangitis was observed (OR = 1.0440, 95% CI 1.0100-1.0790, p IVW = 0.011). Multivariate MR analysis indicated after controlling for potential confounders, greater green tea consumption was suggestively associated with the decreased risk of oesophagitis (OR = 0.9667, 95% CI: 0.9405-0.9936, p IVW = 0.016) and gastric cancer (OR = 0.9810, 95% CI: 0.9628-0.9996, p IVW = 0.046). Nevertheless, multivariate MR analysis also showed that greater green tea consumption was suggestively associated with the increased risk of Crohn's disease (OR = 1.0001, 95% CI: 1.0000-1.0002, p IVW = 0.007). Sensitivity analyses confirmed that these results were reliable. Our study provides suggestive evidence that genetically predicted green tea intake is causally associated with the risk of oesophagitis, gastric cancer and Crohn's disease, but a larger GWAS database is needed for validation.

In order to elucidate the correlation and its pathways between liver diseases and vascular dementia (VaD). We performed two-sample Mendelian randomization (MR) study. We performed a two-sample MR study using summary-level genome-wide association study (GWAS) data for 4 liver diseases (nonalcoholic fatty liver disease [NAFLD], nonalcoholic steatohepatitis [NASH], alcoholic liver disease [ALD], and fibrosis/cirrhosis [FACOL]) and VaD. Inverse variance weighted (IVW) served as the primary analysis, complemented by a suite of sensitivity analyses (Cochran Q test, MR-Egger regression and MR pleiotropy residual sum and outlier [MR-PRESSO]). Furthermore, multivariable MR (MVMR) was conducted to adjust for key metabolic traits, including fasting glucose and triglycerides. The IVW analysis indicated that no significant causal associations were found between any of the 4 liver diseases and the risk of VaD. Sensitivity analyses indicated that the results for NAFLD and FACOL may be affected by heterogeneity, and NAFLD may also be affected by horizontal pleiotropy. Crucially, after adjusting for genetic liability to elevated triglycerides or fasting glucose in MVMR analyses, the initially null association for NAFLD became significant, revealing a protective effect against VaD. Associations for other liver diseases remained null after adjustment. This MR study found no direct causal link between liver diseases and VaD. However, adjusting for glucose or triglycerides revealed a potential protective effect of NAFLD, suggesting metabolic factors may confound the association. Further research is warranted to disentangle the complex relationship between these health conditions.

The development of ankylosing spondylitis (AS) is closely related to autoimmune system dysfunction. Type 1 diabetes mellitus (T1DM) is an autoimmune disease that is a risk factor for many diseases. This study aimed to investigate the causal relationship between T1DM mellitus and AS genetically. A genome-wide association study (GWAS) of causal relationships between exposure (T1DM) and outcome (AS) was performed using summary data from the GWAS database. We conducted a two-sample Mendelian randomization (MR) study of these two diseases. Inverse variance weighting (IVW) was used as the primary analysis method, with MR Egger, weighted median, and weighted mode used as supplementary methods. Sensitivity analyses were performed using Cochran's Q test, MR-Egger intercept, MR-Pleiotropy RESidual Sum and outlier methods, leave-one-out analysis, and funnel plots. A total of 11 single nucleotide polymorphisms (SNPs)were identified for instrumental variables(IVs) for MR analysis.IVW found that T1DM was causally associated with AS ((IVW: OR = 1.0006 (95% CI 1.0001, 1.0011), p = 0.0057; MR-Egger: OR = 1.0003 (95% CI 0.9995, 1.0012), p = 0.4147; weighted median: OR = 1.0006 (95% CI 1.0003, 1.0008), p = 0.0001; weighted mode: OR = 1.0007 (95% CI 1.0005, 1.0009), p = 0.0001). No horizontal pleiotropy was found for the MR-Egger intercept, and leave -one-out analysis found that the results remained stable after the removal of individual SNPs. The results of the two-sample MR analysis supported a causal relationship between T1DM and AS risk.

To explore the causal association between genetically predicted Epstein–Barr virus (EBV) infection and breast, cervical, endometrial, and ovarian cancers. Public data from genome-wide association studies of EBV infection and cancers were used to perform a two-sample Mendelian randomization (MR) study. The inverse variance weighted (IVW) method was the main analysis method, while the weighted median, weighted mode, and MR-Egger methods were used to test the robustness of the IVW results. Cochran’s Q-test, MR-Egger regression, MR-PRESSO, and leave-one-out methods were used to detect heterogeneity, horizontal pleiotropy, outliers, and SNPs driving the results, respectively. There were no statistically significant causal associations between genetically predicted EBV infection and genetically predicted endometrial (OR = 1.55, 95%CI: 0.71–3.37, P = 0.27), cervical (OR = 0.96, 95%CI: 0.42–2.22, P = 0.93), ovarian (OR = 1.55, 95%CI: 0.72–3.33, P = 0.26), or breast (OR = 1.02, 95%CI: 0.79–1.33, P = 0.85) cancers. The raw MR-PRESSO analyses support the IVW results but detected one outlier for the endometrial cancer analysis. After removing the outlier, a suggestive association was observed between EBV infection and endometrial cancer (OR = 2.43, 95%CI: 1.19–4.95, P = 0.024). Cochran’s Q-test detected heterogeneity for endometrial cancer (P = 0.04). The MR-Egger regression analysis revealed no horizontal pleiotropy. The leave-one-out analysis revealed no SNPs driving the results by themselves. This MR study showed a possible causal association between EBV infection and the risk of endometrial cancer. This association warrants additional study.

Previous studies have reported that the inappropriate use of allopurinol may increase the risk of cerebrovascular accidents, but some studies have also confirmed that allopurinol is a protective factor against stroke. To clarify whether there is a relevant causal relationship between allopurinol and cerebral infarction, we conducted a two-sample Mendelian randomization (MR) study. Data on single nucleotide polymorphisms (SNPs) associated with allopurinol and genome-wide association studies of cerebral infarction were obtained from the genome-wide association study (GWAS) web site. Five basic MR analyses were performed using MR-Egger regression, weighted median (WM1), inverse variance weighting (IVW), weighted mode (WM2), and simple mode. Sensitivity analysis was subsequently performed to detect horizontal pleiotropy, heterogeneity, and potential outliers. The final analysis results were mainly based on the IVW estimates. A total of 10 SNPs were used as instrumental variables (IVs). MR analysis [(IVW: odds ratio (OR) = 1.053, 95% confidence interval (CI): 1.019-1.088, P = 0.002), (WM1: OR = 1.053, 95% CI: 1.009-1.098, P = 0.017), (WM2: OR = 1.050, 95% CI: 1.008-1.095, P = 0.044), (MR Egger: Q = 4.285, P = 0.830)] showed a positive causal association between allopurinol and the risk of cerebral infarction. Sensitivity analysis such as horizontal pleiotropy and heterogeneity increased the reliability of this result. The results of this study provide direct evidence that there is a causal relationship between allopurinol and cerebral infarction and that allopurinol may increase the risk of cerebral infarction.

BackgroundRecent research has established the correlation between gut microbiota and periodontitis via oral-gut axis. Intestinal dysbiosis may play a pivotal bridging role in extra-oral inflammatory comorbidities caused by periodontitis. However, it is unclear whether the link is merely correlative or orchestrated by causative mechanistic interactions. This two-sample Mendelian randomization (MR) study was performed to evaluate the potential bidirectional causal relationships between gut microbiota and periodontitis.Materials and MethodsA two-sample MR analysis was performed using summary statistics from genome-wide association studies (GWAS) for gut microbiota (n = 18,340) and periodontitis (cases = 12,251; controls = 22,845). The inverse-variance weighted (IVW) method was used for the primary analysis, and we employed sensitivity analyses to assess the robustness of the main results. The PhenoScanner database was then searched for pleiotropy SNPs associated with potential confounders. In order to identify the possibly influential SNPs, we further conducted the leave-one-out analysis. Finally, a reverse MR analysis was performed to evaluate the possibility of links between periodontitis and genetically predicted gut microbiota alternation.Results2,699 single nucleotide polymorphisms (SNPs) associated with 196 microbiota genera were selected as instrumental variables (IVs). IVW method suggested that order Enterobacteriales (OR: 1.35, 95% CI 1.10–1.66), family Bacteroidales S24.7group (OR: 1.22, 95% CI 1.05–1.41), genus Lachnospiraceae UCG008 (OR: 1.16, 95% CI 1.03–1.31), genus Prevotella 7 (OR: 1.11, 95% CI 1.01–1.23), and order Pasteurellales (OR: 1.12, 95% CI 1.00–1.26) may be associated with a higher risk of periodontitis, while genus Ruminiclostridium 6 may be linked to a lower risk (OR: 0.82, 95% CI 0.70–0.95). The sensitivity and heterogeneity analyses yielded no indication of horizontal pleiotropy or heterogeneity. Only the association between order Enterobacteriales and the likelihood of periodontitis remained consistent across all alternative MR approaches. In the reverse MR analysis, four microbiota genera were genetically predicted to be down-regulated in periodontitis, whereas two were predicted to be up-regulated.ConclusionsThe present MR analysis demonstrated the potential bidirectional causal relationships between gut microbiota and periodontitis. Our research provided fresh insights for the prevention and management of periodontitis. Future research is required to support the finding of our current study.

BackgroundAlthough anxiety disorders are one of the most prevalent mental disorders, their underlying biological mechanisms have not yet been fully elucidated. In recent years, genetically determined metabolites (GDMs) have been used to reveal the biological mechanisms of mental disorders. However, this strategy has not been applied to anxiety disorders. Herein, we explored the causality of GDMs on anxiety disorders through Mendelian randomization study, with the overarching goal of unraveling the biological mechanisms.MethodsA two-sample Mendelian randomization (MR) analysis was implemented to assess the causality of GDMs on anxiety disorders. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas four different GWAS datasets of anxiety disorders were the outcomes. Notably, all datasets were acquired from publicly available databases. A genetic instrumental variable (IV) was used to explore the causality between the metabolite and anxiety disorders for each metabolite. The MR Steiger filtering method was implemented to examine the causality between metabolites and anxiety disorders. The standard inverse variance weighted (IVW) method was first used for the causality analysis, followed by three additional MR methods (the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods) for sensitivity analyses in MR analysis. MR-Egger intercept, and Cochran’s Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. Bonferroni correction was used to determine the causative association features (P < 1.03 × 10–4). Furthermore, metabolic pathways analysis was performed using the web-based MetaboAnalyst 5.0 software. All statistical analysis were performed in R software. The STROBE-MR checklist for the reporting of MR studies was used in this study.ResultsIn MR analysis, 85 significant causative relationship GDMs were identified. Among them, 11 metabolites were overlapped in the four different datasets of anxiety disorders. Bonferroni correction showing1-linoleoylglycerophosphoethanolamine (ORfixed-effect IVW = 1.04; 95% CI 1.021–1.06; Pfixed-effect IVW = 4.3 × 10–5) was the most reliable causal metabolite. Our results were robust even without a single SNP because of a “leave-one-out” analysis. The MR-Egger intercept test indicated that genetic pleiotropy had no effect on the results (intercept = − 0.0013, SE = 0.0006, P = 0.06). No heterogeneity was detected by Cochran’s Q test (MR-Egger. Q = 7.68, P = 0.742; IVW. Q = 12.12, P = 0.436). A directionality test conducted by MR Steiger confirmed our estimation of potential causal direction (P < 0.001). In addition, two significant pathways, the “primary bile acid biosynthesis” pathway (P = 0.008) and the “valine, leucine, and isoleucine biosynthesis” pathway (P = 0.03), were identified through metabolic pathway analysis.ConclusionThis study provides new insights into the causal effects of GDMs on anxiety disorders by integrating genomics and metabolomics. The metabolites that drive anxiety disorders may be suited to serve as biomarkers and also will help to unravel the biological mechanisms of anxiety disorders.

ObjectivePrevious studies have shown that human immunodeficiency virus (HIV) infection is associated with hypertension; however, the results of these studies are affected by a variety of confounding factors. There is no definite evidence to prove a causal relationship between these two factors. This study aimed to investigate the causal relationship between HIV infection and hypertension.MethodsA two-sample Mendelian randomization (MR) study was conducted using genome-wide association study (GWAS) statistics published online. The data were collected mainly from the OpenGWAS and FinnGen databases. The HIV database contained 357 HIV patients and 218,435 control patients; the hypertension database contained 54,358 patients and 408,652 control patients; and the blood pressure database contained 436,424 samples. Random effect inverse variance weighting (IVW) was used as the main analysis method, weighted median and Mr-Egger analysis methods were used to ensure the accuracy of the results, and Cochran’s Q test and Mr-Egger regression methods were used to detect heterogeneity and correct multiple horizontal effects. Finally, the leave-one-out method was used to analyse the reliability of the test results. In order to further verify the research results, different databases were used and the same statistical method was used for a replication analysis. In order to prevent false positive results caused by multiple tests, Bonferroni correction is used to correct the statistical results.ResultsAfter screening, a total of 9 SNPs (single-nucleotide polymorphisms) were selected as the instrumental variable (IV) used in this study. The IVW MR analysis results showed a causal relationship between HIV infection and the risk of hypertension (IVW: OR = 1.001, P = 0.03). When systolic blood pressure was the outcome, the IVW method results were positive (OR = 1.004, P = 0.01280), and when diastolic blood pressure was the outcome, the weighted median method results were positive (OR = 1.004, P = 0.04570). According to the sensitivity analysis, the results of this study were unlikely to be affected by heterogeneity and horizontal pleiotropy. The leave-one-out analysis showed that the results of this study did not change significantly with the elimination of a single SNP. In replication analysis, when diastolic blood pressure was taken as the outcome, the weighted median method was positive (OR = 1.042, P = 0.037). Sensitivity analysis shows that there is heterogeneity, but there is no horizontal pleiotropy. The leave-one-out analysis showed that the results of this study did not change significantly with the elimination of a single SNP.ConclusionAs the first exploratory study using MR method to study the causal relationship between HIV infection and hypertension and blood pressure, this study found that HIV infection may increase systolic and diastolic blood pressure and increase the risk of hypertension. PLWH, as a high-risk group of cardiovascular and cerebrovascular diseases, should prevent the occurrence of hypertension in order to further improve their quality of life. However, this study also has some limitations. The results of the relationship between HIV infection and hypertension and blood pressure may be affected by the lack of statistical efficacy. In order to further confirm this conclusion, more large-scale RCT or genetic studies should be carried out.

Purpose Diabetic retinopathy (DR) is a common microvascular complication of diabetes. Previous observation studies identified the association between Galectins (Gal) and the risk of DR, but the causal relationship between Gal and the risk of DR is still unclear. This study aimed to explore the causal associations between circulating galectins (Gal) family levels and the risk of diabetic retinopathy (DR) and its phenotypes including proliferative DR (PDR), background DR (BDR), and severe non-proliferative background DR (SNPDR) using two-sample Mendelian randomization (MR) analysis. Methods The single nucleotide polymorphism (SNP) as instrumental variables (IVs) were identified from previous genome-wide association studies (GWAS). Qualified SNPs associated with Gals were selected via strict screening process. The causal association between Gal family levels and the risk of DR was analyzed using MR analysis. The main MR method was Inverse variance weighted (IVW). Causal estimates before and after outlier removal were presented as odds ratio (OR) with 95% confidence interval (CI). Results The results of IVW indicated that Gal-4 levels were causally related to elevated risk of DR (OR = 1.068, 95%CI: 1.006–1.133), and PDR (OR = 1.084, 95%CI: 1.004–1.169). Gal-3 had causal effect on the risk of SNPDR (OR = 1.455, 95%CI: 1.103–1.919). Gal-3 binding protein was causally associated with higher risk of SNPDR (OR = 1.295, 95%CI: 1.014–1.654). In addition, Gal-9 had causal association with decreased risk of SNPDR (OR = 0.669, 95%CI: 0.491–0.911). Leave-one-out analysis depicted that no individual SNP could affect the causal associations of Gal-4 with DR and PDR, Gal-3, Gal-3 binding protein and Gal-9 with SNPDR. Conclusion Gal-4 levels were causally related to elevated risk of DR, and PDR. Gal-3 and Gal-3 binding protein had causal effect on increased risk of SNPDR while Gal-9 had causal effect on decreased risk of SNPDR.

Although prior observational studies have suggested that patients with non-alcohol fatty liver disease (NAFLD) may have a higher risk of coronary artery calcification (CAC), these findings remain controversial. This study aimed to explore the causal association between NAFLD and CAC at genetic level by two-sample Mendelian randomization (MR) analysis. Utilizing summary-level data from multiple large-scale genome-wide association studies (GWAS) in European populations, a two-sample MR analysis was initially conducted to explore the potential causal association between NAFLD and CAC. The results of the MR analysis were pooled through random-effect meta-analysis. The inverse variance weighting (IVW) method served as the primary approach for MR analysis. Additionally, the weighted median, MR-Egger and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods was applied for sensitivity analysis. Summary-level data on liver fatty content was utilized for validation analysis, while summary-level data on cirrhosis served as positive control, further ensuring the validity and robustness of our findings. Reverse MR analysis was performed to assess the association between CAC and NAFLD, employing instrument variables derived from CAC. The MR analysis indicated that genetically predicted NAFLD had no effects on the risk of CAC (Beta: 0.01, 95% CI: -0.02 to 0.03, P = 0.74). Likewise, the reverse MR analysis found no significant genetic association between CAC and NAFLD (OR: 1.00, 95% CI: 0.96 to 1.06, P = 0.88). Validation analysis yielded consistent results, showing no significant association between fatty liver content and CAC. Our two-sample MR analysis did not support that there is a causal association between NAFLD and CAC at genetic level. The association between NAFLD and CAC reported in some previous observational studies may rely on NAFLD complicated with metabolic disorders, rather than being directly linked to the hepatic steatosis.

Liver hepatocellular carcinoma (LIHC) exhibits a multifactorial etiology, insidious onset, and a significantly low 5-year survival rate. We aimed to evaluate the causal impact of exposure factors (Alzheimer's disease, platelet count, ambidextrousness, cigarettes smoked per day, alcohol consumption, and endocarditis) on the risk of LIHC using a two-sample Mendelian randomization (MR) study. Independent single nucleotide polymorphisms (SNPs) strongly associated with Alzheimer's disease, platelet count, ambidextrousness, daily cigarette consumption, alcohol intake, and endocarditis were selected as instrumental variables (IVs) from the corresponding genome-wide association studies (GWAS). Genetic summary statistics for LIHC came from a GWAS that included 168 cases and 372,016 controls of European individuals. Multivariable MR analyses were performed to find the causal association between 6 exposure factors and LIHC risk. The inverse-variance weighted (IVW)-MR was employed as the primary analysis, and the MR-Egger regression, LASSO regression, and weighted Median approaches were performed as complementary analyses. Multivariable MR analysis showed causal association between Alzheimer's disease [Odds ratio (OR) = 0.9999, 95% confidence intervals (CI) = 0.9998-0.9999, p = 0.0010], platelet count (OR = 0.9997, 95% CI = 0.9995-0.9999, p = 0.0066), alcohol consumption (OR = 0.9994, 95% CI = 0.9990-0.9999, p = 0.0098) and the LIHC outcome. After IVW-MR, MR-Egger and LASSO tests, the results are still significant. Next, we used different MR Methods to analyze platelet count, alcohol consumption, and Alzheimer's disease separately. Moreover, both funnel plots and MR-Egger intercepts provided compelling evidence to refute the presence of directional pleiotropy in the association between platelet count, alcohol consumption, Alzheimer's disease and the risk of LIHC. The IVW-MR analysis revealed a significant causal association between an elevated platelet count and a reduced risk of LIHC (OR = 0.9996, 95% CI= 0.9995-0.9998, p = 0.0005). Similarly, the analysis of weighted median revealed a negative correlation between platelet count and the risk of LIHC (OR = 0.9995, 95% CI = 0.9993-0.9999; p = 0.0160). Conversely, we observed a positive causal effect of alcohol consumption on the incidence of LIHC (OR = 1.0004, 95% CI = 0.9999-1.0009). However, no significant causal relationship was found between alcohol assumption, Alzheimer's disease, and LIHC susceptibility. A significant causal relationship exists between platelet count, alcohol consumption, Alzheimer's disease, and an increased risk of LIHC. The study presents compelling evidence for a genetically predicted decreased susceptibility to LIHC based on platelet count. The research implies that elevated platelet count may serve as a protective mechanism against LIHC. These findings may inform clinical strategies for LIHC prevention.

The causal genetic relationship between common parenteral manifestations of inflammatory bowel disease (IBD) and urolithiasis remains unclear because their timing is difficult to determine. This study investigated the causal genetic association between IBD and urolithiasis using Mendelian randomization (MR) based on data from large population-based genome-wide association studies (GWASs). A two-sample MR analysis was performed to assess the potential relationship between IBD and urolithiasis. Specific single nucleotide polymorphism data were obtained from GWASs, including IBD (n = 59957) and its main subtypes, Crohn's disease (CD) (n = 40266) and ulcerative colitis (UC) (n = 45975). Summarized data on urolithiasis (n = 218792) were obtained from different GWAS studies. A random-effects model was analyzed using inverse-variance weighting, MR-Egger, and weighted medians. Genetic predisposition to IBD and the risk of urolithiasis were significantly associated [odds ratio (OR), 1.04 (95% confidence interval [CI], 1.00-.08), P = 0.01]. Consistently, the weighted median method yielded similar results [OR, 1.06 (95% CI, 1.00-1.12), P = 0.02]. The MR-Egger method also demonstrated comparable findings [OR, 1.02 (95% CI, 0.96-1.08), P = 0.45]. Both funnel plots and MR-Egger intercepts indicated no directional pleiotropic effects between IBD and urolithiasis. CD was strongly associated with it in its subtype analysis [OR, 1.04 (95% CI, 1.01-1.07), P = 0.01], and UC was also causally associated with urolithiasis, although the association was not significant [OR, 0.99 (95% CI, 0.95-1.03), P = 0.71]. A unidirectional positive causal correlation was identified between IBD and urolithiasis, with varying degrees of association observed among the different subtypes of IBD. Recognizing the increased incidence of urolithiasis in patients with IBD is crucial in clinical practice. Early detection and surveillance of IBD, improved patient awareness, adoption of preventive strategies, and promotion of collaborative efforts among healthcare providers regarding treatment methodologies are vital for improving patient outcomes.

BackgroundHepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide. Multiple observational studies demonstrated a negative association between the use of antithrombotic agents and the risk of HCC. However, the precise causal relationship between these factors remains uncertain. Therefore, our study used a two-sample Mendelian randomization (MR) analysis to assess the causal link between these two factors.MethodThe summary statistics of single nucleotide polymorphisms (SNPs) associated with the use of antithrombotic agents were acquired from a genome-wide association study (GWAS) performed on individuals of European descent. A two-sample MR analysis was performed using the inverse variance weighting (IVW), the weighted median estimate, the MR-Egger regression, and the weighted-mode estimate. Sensitivity analysis of the primary findings was performed using MR-PRESSO, MR-Egger regression, Cochran’s Q test, and Leave-one-out analysis.ResultsTen SNPs associated with the use of antithrombotic agents were selected as instrumental variables. The MR analysis performed using the four methods mentioned above revealed a negative causal association between the use of antithrombotic agents and HCC. Univariate MR estimates based on the inverse variance weighting (IVW) method suggested a negative causal association between the use of antithrombotic agents and HCC [odds ratio (OR) 0.444, 95% confidence interval (CI) 0.279 to 0.707, P = 0.001]. The other methods also produced similar results. No heterogeneity and horizontal pleiotropy were found.ConclusionOur findings suggested an inverse causal association of antithrombotic agents with the risk of HCC.