Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

The influences of blood lipids and lipid-regulatory medications on the risk of bladder cancer have long been suspected, and previous findings remain controversial. We aimed to assess the causality between blood lipids or lipid-regulatory medications and bladder cancer susceptibility by means of a comprehensive Mendelian Randomization (MR) study. Genetic proxies from genome-wide association studies (GWAS) of four blood lipid traits and lipid-lowering variants in genes encoding the targets of lipid-regulatory medications were employed. The largest ever GWAS data of blood lipids and bladder cancer involving up to 440,546 and 205,771 individuals of European ancestry were extracted from UK Biobank and FinnGen Project Round 6, respectively. A two-sample bidirectional MR study was performed using the inverse variance weighted as the main method. The heterogeneity, horizontal pleiotropy, MR Steiger, and leave-one-out analyses were also conducted as sensitivity tests. There was indicative evidence that genetically predicted low-density lipoprotein cholesterol (LDL-C) affected bladder cancer susceptibility based on 146 single nucleotide polymorphisms (SNPs) with an odds ratio (OR) of 0.776 (95% confidence interval [CI] = 0.625-0.965, p = 0.022). However, this result became non-significant after two SNPs that possibly drove the effect were removed as demonstrated by leave-one-out analysis. The reversed MR analysis suggested that bladder cancer could not affect serum lipid levels. No causal relationship was found between the lipid-lowering effect of lipid-regulatory medications (fibrates, probucol, statins, ezetimibe, proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors, and evinacumab) and the risk of bladder cancer. No heterogeneity or pleiotropy was found (all p > 0.05). This MR study revealed for the first time, using the most recent and comprehensive GWAS data to date, that genetically predicted total cholesterol (TC) and the lipid-lowering effect of lipid-regulatory medications had no causal association with bladder cancer susceptibility. We also verified claims from early studies that low-density lipoprotein cholesterol (HDL-C), LDL-C, and triglyceride (TG) are not related to bladder cancer susceptibility either. The current study indicated that lipid metabolism may not be as important in the tumorigenesis of bladder cancer as previously believed.

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.

Physical weakness is associated with cortical structures, but the exact causes remain to be investigated. Therefore, we utilized Mendelian randomization (MR) analysis to uncover the underlying connection between frailty and cortical structures. The Genome-Wide Association Study (GWAS) on frailty pooled data from publicly available sources such as the UK Biobank and included five indicators of frailty: weakness, walking speed, weight loss, physical activity, and exhaustion. GWAS data on cerebral cortical structure were obtained from the ENIGMA consortium, and we assessed the causal relationship between hereditary frailty and cortical surface area (SA) or cortical thickness (TH). Inverse variance weighting (IVW) was used as the primary estimate, and heterogeneity and multidimensionality were monitored by MR-PRESSO to detect outliers. Additionally, MR-Egger, Cochran's Q test, and weighted median were employed. At the aggregate level, there was no causal relationship between frailty and cortical thickness or surface area. At the regional level, frailty was associated with the thickness of the middle temporal lobe, parahippocampus, rostral middle frontal lobe, lower parietal lobe, anterior cingulate gyrus, upper temporal lobe, lateral orbital frontal cortex, pericardial surface area, rostral middle frontal lobe, upper temporal lobe, rostral anterior cingulate gyrus, lower parietal lobe, and upper parietal lobe. These results were nominally significant, and sensitivity analyses did not detect any multidirectionality or heterogeneity, suggesting that the results of our analyses are reliable. The results of our analyses suggest a potential causal relationship between somatic weakness and multiple regions of cortical structure. However, the specific mechanisms of influence remain to be investigated. Preliminary results from our analysis suggest that the effects of physical frailty on cortical structures are influenced by various factors related to frailty exposure. This relationship has been documented, and it is therefore both feasible and meaningful to build on existing research to explore the clinical significance of the relationship.

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.

BackgroundPelvic floor dysfunction (PFD) is an extremely widespread urogynecologic disorder, the prevalence of which increases with aging. PFD has severely affected women’s quality of life and has been called a social cancer. While previous studies have identified risk factors such as vaginal delivery and obesity for PFD, other reproductive factors, including age at menarche (AAMA), have been largely overlooked. Therefore, we used a Mendelian randomization (MR) study for the first time to investigate the potential causal relationship between reproductive factors and PFD.MethodsWe obtained summary statistics from genome-wide association studies (GWAS) for female genital prolapse (FGP), stress urinary incontinence (SUI), and five reproductive factors. Two-sample Mendelian randomization analysis (TSMR) was performed to explore the causal associations between these factors. The causal effects of reproductive factors on FGP and SUI were primarily estimated using the standard inverse variance weighting (IVW) method, with additional complementary and sensitivity analyses conducted using multiple approaches. A multivariate Mendelian randomization (MVMR) study was also conducted to adjust for pleiotropic effects and possible sources of selection bias and to identify independent exposure factors.ResultsOur findings revealed that advanced age at first sexual intercourse (AFS) and age at first birth (AFB) exhibited negative causal effects on both FGP and SUI. AAMA showed negative causal effects solely on FGP, while age at last live birth (ALB) and age at menopause (AAMO) did not demonstrate any causal effect on either FGP or SUI. And the MVMR results showed that AFB and AFS had independent negative causal effects on FGP and SUI, respectively.ConclusionsThis study, for the first time, investigates the causal relationship between reproductive factors and PFD. The results suggested a causal relationship between some reproductive factors, such as AFB and AFS, and PFD, but there were significant differences between FGPand SUI. Therefore, future studies should explore the underlying mechanisms and develop preventive measures for reproductive factors to reduce the disease burden of PFD.

Establishing new approaches for the prevention and treatment of stroke relies on identifying modifiable risk factors that contribute to the development of this complex disease. Mendelian randomization (MR) studies, analogous to naturally occurring randomized trials, can assess causality of potentially modifiable biomarkers and offer new insights into biological pathways. Stroke is the second leading cause of death worldwide and the chief determinant of long-term disability. Stroke is a heterogeneous disease arising from several distinct underlying pathologies and is typically classified as ischemic or hemorrhagic, and further subclassified using imaging data. Ischemic stroke (IS), including its 3 main subtypes: small vessel disease, large vessel disease, and cardioembolic stroke, accounts for ≈80% of stroke and is the result of an interrupted blood supply, leading to localized areas of ischemia in the brain. Small vessel disease may be a consequence of nonatherosclerotic, as well as atherosclerotic, mechanisms that result in an occlusion of the small perforating arteries, whereas large vessel disease results from occlusions or emboli from plaque rupture in larger vessels, such as a carotid artery. Cardioembolic stroke arises typically from emboli from the heart. By contrast, hemorrhagic stroke is a consequence of intracerebral hemorrhage (bleeding into the brain) or subarachnoid hemorrhage (bleeding into the subarachnoid space). These diverse stroke subtypes have distinct underlying pathologies reflecting different risk factor distributions. MR studies, using genetic variants as instrumental variables, afford a powerful approach to assessing causality of risk factors and avoid biases inherent in observational studies, including confounding and reverse causation. This review considers the contribution of MR studies to stroke epidemiology and their relevance to understanding risk factors and new therapeutic targets for stroke. Meta-analyses of large prospective studies have enhanced our knowledge of classical and emerging risk factors for stroke.1–4 Classical risk factors for stroke include nonmodifiable characteristics, …

BackgroundPrevious studies have suggested some relationship between endometriosis (EMS) and inflammatory bowel disease (IBD). However, the causal relationship between the two diseases remains unknown. Our aim was to investigate whether...

BackgroundAs the number of COVID-19 deaths continues to rise worldwide, the identification of risk factors for the disease is an urgent issue, and it remains controversial whether atherogenic lipid-related traits including serum apolipoprotein B, low-density lipoprotein (LDL)-cholesterol, and triglyceride levels, are risk factors. The aim of this study was to estimate causal effects of lipid-related traits on COVID-19 risk in the European population using a two-sample Mendelian randomization (MR) approach.MethodsWe used summary statistics from a genome-wide association study (GWAS) that included 441,016 participants from the UK Biobank as the exposure dataset of lipid-related traits and from COVID-19 Host Genetics Initiative GWAS meta-analyses of European ancestry as the outcome dataset for COVID-19 susceptibility (32,494 cases and 1,316,207 controls), hospitalization (8316 cases and 1,549,095 controls), and severity (4792 cases and 1,054,664 controls). We performed two-sample MR analyses using the inverse variance weighted (IVW) method. As sensitivity analyses, the MR-Egger regression, weighted median, and weighted mode methods were conducted as were leave-one-out sensitivity analysis, the MR-PRESSO global test, PhenoScanner searches, and IVW multivariable MR analyses. A P value below 0.0055 with Bonferroni correction was considered statistically significant.ResultsThis MR study suggested that serum apolipoprotein B or LDL-cholesterol levels were not significantly associated with COVID-19 risk. On the other hand, we inferred that higher serum triglyceride levels were suggestively associated with higher risks of COVID-19 susceptibility (odds ratio [OR] per standard deviation increase in lifelong triglyceride levels, 1.065; 95% confidence interval [CI], 1.001–1.13; P = 0.045) and hospitalization (OR, 1.174; 95% CI, 1.04–1.33; P = 0.012), and were significantly associated with COVID-19 severity (OR, 1.274; 95% CI, 1.08–1.50; P = 0.004). Sensitivity and bidirectional MR analyses suggested that horizontal pleiotropy and reverse causation were unlikely.ConclusionsOur MR study indicates a causal effect of higher serum triglyceride levels on a greater risk of COVID-19 severity in the European population using the latest and largest GWAS datasets to date. However, as the underlying mechanisms remain unclear and our study might be still biased due to possible horizontal pleiotropy, further studies are warranted to validate our findings and investigate underlying mechanisms.

Numerous studies have consistently demonstrated that a considerable proportion of patients with major depressive disorder (MDD) frequently exhibit pronounced dyslipidaemia. However, the causal dynamics between MDD and dyslipidaemia remain elusive. To comprehensively disentangle the genetic causality between MDD and various phenotypes of blood lipids, thereby facilitating the advancement of management strategies for these conditions. We conducted a two-sample univariable Mendelian randomisation (MR) analysis using different models, including the inverse variance weighted (IVW) method and causal analysis using the summary effect (CAUSE) estimates, as well as a multivariable MR analysis. This analysis used summary statistics from genome-wide association studies (GWAS) of MDD and five lipid traits: low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, total cholesterol and triglycerides (TG), encompassing 5 237 893 individuals of European and East Asian ancestries. For MDD, a total of 598 701 individuals were included, with 500 199 individuals of European ancestry (Ncase=170 756, Ncontrol=329 443) and 98 502 of East Asian ancestry (Ncase=12 588, Ncontrol=85 914). Lipid data were collected from 4 639 192 individuals through the Global Lipids Genetics Consortium (European, N=4 096 085; East Asian, N=543 107). Next, we used the two-step MR to explore the mediating factors between MDD and TG, and the risk factors affecting TG through MDD. Finally, we conducted a GWAS meta-analysis and enrichment analysis. In univariable MR, we observed a negative causal effect of low-density lipoprotein on MDD in both European populations (IVW: odds ratio (OR): 0.972, 95% confidence interval (CI) 0.947 to 0.998, p=0.037) and East Asian populations (IVW: OR: 0.928, 95% CI 0.864 to 0.997, p=0.042). Additionally, we identified a bidirectional causal relationship between TG and MDD, with TG having a causal effect on MDD (IVW: OR: 1.052, 95% CI 1.020 to 1.085, p=0.001) and MDD having a causal effect on TG (IVW: OR: 1.075, 95% CI 1.047 to 1.104, p<0.001). Multivariable MR analysis further supported the role of TG in MDD (OR: 1.205, 95% CI 1.034 to 1.405, p=0.017). CAUSE estimates indicated that the causal model of MDD on TG provided a better fit than the sharing model (p=0.003), while the association of TG on MDD was more likely due to horizontal correlated pleiotropy than causality. Mediation analyses revealed that waist-hip ratio (WHR) mediated 69% of the total causal effect of MDD on TG, while other identified risk factors exhibited lower mediating proportions either mediated through MDD (≤17%) or originating from MDD (≤29%). The GWAS meta-analysis highlighted potential pathways related to lipid processes and nucleosome assembling, with significant cell types identified in brain regions and liver tissues. The findings indicate that genetic proxies of MDD are associated with elevated levels of TG, with WHR serving as a clinical indicator of the association. This suggests that interventions targeting WHR may be effective in reducing TG levels in patients with MDD.

Background It is generally acknowledged that those with diabetes mellitus (DM) have at least a 10-fold risk for cardiovascular disease (CVD). However, patients with DM have been shown with a lower incidence of abdominal aortic aneurysm (AAA) in epidemiological data. Related research has illustrated that the aortic may be protected in the hyperglycemic microenvironment while the causality of this relationship is still uncertain. Purpose Here, we undertake a two sample Mendelian randomization (MR) study to evaluate whether DM genetically influences the risk of AAA. Methods We analyzed the genetic summary data from the DIAGRAM (Diabetes Genetics Replication And Meta-analysis) consortium and MRC-IEU (Integrative Epidemiology Unit) consortium. Base on the result from GIAGRAM consortium (26488 DM cases and 83964 controls), 25 single nucleotide polymorphisms (SNPs) associated with DM as the instrumental variables in MR study. Then, for each of the 25 SNPs associated with DM, we retrieved their summary data from MRC-IEU Consortium (263 cases and 462747controls). Inverse-variance weighting (IVW) was conducted to obtain the associations of DM with AAA and several sensitivity analyses were also performed to assess the potential violation of MR assumptions. Results DM was not significantly associated with risk of AAA (odds ratio [OR], 1.ehz746.1092; 95% confidence interval [CI], 0.9998–1.0002; P, 0.9622). Weighted median (OR, 1.0002; 95% CI, 0.9999–1.0005; P, 0.1992) and MR Egger analysis (OR, 1.0003; 95% CI, 0.9995–1.0012; P, 0.4071) suggested similar effect estimates of DM on AAA. With the large P value for the intercept, the result of MR-Egger regression method indicated no evidence for the presence of horizontal pleiotropy (Egger regression intercept, 3.9e-05, P, 0.384). In a leave-one-out analysis, no single SNP was observed with strong driving effect of DM on AAA. Conclusions Through 25 genetically identified SNPs in this two sample MR study, DM is not associated the risk of AAA this large study using two-sample MR, which did not support the result from previous epidemiological data. In conclusions, this large MR study provides evidence to suggest that DM may not be causally associated with AAA.

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.

This study aims to investigate the causal relationship between primary Sjögren’s syndrome (SS) and multiple sclerosis (MS) using a two-sample Mendelian randomization (MR) analysis to provide insights into their common mechanisms and implications for therapeutic strategies. We utilized data from Genome-Wide Association Studies (GWAS) for primary SS (1,290 cases and 213,145 controls) and MS (4,888 cases and 10,395 controls), restricted to European ancestry. Instrumental variables (IVs) were selected based on genetic variants associated with primary SS. The primary MR method was Inverse Variance Weighted (IVW), supplemented by MR Egger, Weighted Median, Simple Mode, and Weighted Mode algorithms to assess the bidirectional causal relationships between MS and primary SS. Sensitivity analyses, including MR-PRESSO and leave-one-out analysis, were conducted to ensure the robustness of our findings. After excluding SNPs with pleiotropic effects, 42 and 5 SNPs were identified as robust IVs for primary SS and MS, respectively. Our analysis revealed a significant protective effect of MS on primary SS, with IVW showing an OR of 0.896 (95% CI: 0.841–0.954, P = 0.001). No significant heterogeneity or horizontal pleiotropy was detected, supporting the reliability of the results. Our findings suggest a potential protective effect of MS against primary SS, indicating a negative causal association between these two autoimmune diseases. This adds valuable genetic evidence to the understanding of the complex interplay between primary SS and MS, offering new avenues for research and therapeutic interventions.

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study. Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated. The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL). IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

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.

To investigate the causal relationship between circulating serum homocysteine (Hcy) levels and osteoporosis (OP). Using public datasets gathered from independently published genome-wide association studies (GWAS), Mendelian randomization (MR) analysis was done to investigate the causal influence of Hcy on OP. SNPs were selected from a meta-analysis of GWAS on Hcy concentrations in 44,147 individuals of European ancestry. Meanwhile, SNPs of individuals of European descent for OP were extracted from the Genetic Factors of Osteoporosis Consortium (GEFOS) UK Biobank. The odds ratio (OR) of inverse variance weighted (IVW) approaches was established as the primary outcome. Moreover, weighted median (WM) and MR-Egger regressions were included in the sensitivity analysis. There were no causal effects of Hcy on forearm bone mineral density and lumbar bone mineral density according to IVW, MR-Egger, and WM analyses (all p > 0.05). In the IVW, we discovered the causality between genetically predicted Hcy and heel bone mineral density (H-BMD) with an OR of 0.96 [95% confidence interval (CI) = 0.927–0.990, p = 0.011]. In the additional sensitivity analysis, WM regression (OR = 0.97, 95% CI = 0.995–1.076, p = 0.084) and MR-Egger regression (OR = 0.98, 95% CI = 0.918–1.049, p = 0.609) yielded values that were comparable in direction but less precise. The MR-Egger intercept, funnel plot, and IVW all indicate the absence of any discernible directional pleiotropy. The leave-one-out analysis revealed that a single SNP did not influence the results of the MR analysis. In conclusion, our MR investigation revealed evidence of a causal relationship between circulating serum Hcy levels and H-BMD, but not OP in the European population. However, larger sample sizes are needed in the future to get more reliable conclusions.