Causal relationship between folate and thrombotic external hemorrhoids: A two-sample Mendelian Randomization analysis

BackgroundObservational epidemiologic investigations into the link between diabetes mellitus and preeclampsia (PE) have been conducted, but genetic evidence is still lacking. We utilized a two-sample Mendelian randomization (MR) analysis to shed light on the potential influence of type 2 diabetes mellitus (T2DM) on PE at the genetic prediction level.MethodsWe carried out a two-sample bidirectional MR analysis, utilizing genetic variants associated with T2DM (N=461,920) and PE (N=219,817) from the largest available genome-wide association studies. Using inverse variance weighting (IVW) and five validated approaches—MR-Egger, MR-RAPS, ConMix, weighted median, and weighted mode—we derived a potential causal association between T2DM and PE. The relationship between PE and T2DM was explored using reverse MR analysis.ResultsThe two-sample MR analysis indicated a causal link between T2DM and PE, with an odds ratio of 1.10 (95% CI, 1.02–1.18; P=0.01). The weighted mode method yielded an odds ratio of 1.22 (95% CI, 1.06–1.40; P=0.019), and the weighted median method produced an odds ratio of 1.19 (95% CI, 1.04–1.36; P=0.022). However, no significant association was detected in the MR-Egger analysis. Heterogeneity was noted in the analysis of T2DM and PE, but no significant horizontal pleiotropy was observed. The results of the reverse MR analysis indicated no significant causal association between PE and T2DM.ConclusionFor the first time, MR analysis showed a positive causal link from T2DM to PE, but not vice versa. The limited number of SNPs in reverse analysis may affect reliability. Future studies should use more instrumental variables to strengthen findings. Further experiments are also needed to explore underlying mechanisms.

Introduction: Gestational diabetes mellitus (GDM), heart disease (HD) and high body mass index (BMI) are strongly related to Alzheimer’s disease (AD) dementia in pregnant women. Therefore, we aimed to determine the total effects of GDM, heart disease, and high BMI on maternal AD dementia. Methods: We used data from the genome-wide association studies of European populations including more than 30,000 participants. We performed two-sample Mendelian randomization (MR) and multivariable MR (MVMR) to systematically estimate the direct effects of GDM, HD, and high BMI on maternal AD and dementia. Multiple sensitivity analyses involving classical MR approaches and expanded MR-pleiotropy residual sum and outlier analysis. Results: In two-sample MR analysis, the inverse-variance weighted method in our study demonstrated no significant causality between GDM and maternal dementia (β = −0.006 ± 0.0026, p = 0.82). This method also revealed no significant causality between high BMI and maternal dementia (β = 0.0024 ± 0.0043, p = 0.57), and it was supported by the MR-Egger regression results, which showed no causal effect of high BMI on maternal Alzheimer’s disease and dementia (β = 0.0027 ± 0.0096, p = 0.78). The IVW method showed no significant causal relationship between maternal HD and maternal Alzheimer’s disease and dementia (β = −0.05 ± 0.0042, p = 0.117) and MR-Egger regression analysis gave a similar result (β = −0.12 ± 0.0060, p = 0.079). In MVMR analysis, we found no significant causal relationship between GDM, high BMI, or HD and maternal Alzheimer’s disease and dementia (p = 0.94, 0.82, and 0.13, respectively). Thus, the MVMR estimates were consistent with our results from the two-sample MR analysis. We confirmed that these results showed no horizontal pleiotropy and enhanced the robustness of our results through multiple sensitivity analyses. Conclusion: In two-sample MR analysis, we found no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. These results differed from previous observational studies showing HD is a significant predictor of dementia. MVMR analysis supported no significant causal relationship between GDM, HD, high BMI and maternal AD and dementia. Sensitivity analysis broadly increased the robustness of two-sample MR and MVMR analysis results.

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.

Aims/Background The association between rheumatic immune diseases and polycystic ovary syndrome (PCOS) remains elusive. The purpose of this study was to investigate the causal relationship between rheumatic immune diseases and the risk of PCOS through a two-sample Mendelian randomization (MR) analysis. Methods In the assessment of exposure variables, we chose systemic lupus erythematosus (SLE), polymyositis (PM), and rheumatoid arthritis (RA) as representative rheumatic immune diseases, while PCOS was designated as the outcome of interest. All data utilized in this investigation were obtained from the Medical Research Council Integrative Epidemiology Unit (MRC-IEU) database. A two-sample MR analysis was conducted using summary statistics for both the exposure and outcome variables, which were gathered from the genome-wide association study (GWAS) datasets. Single nucleotide polymorphisms (SNPs) significantly associated with rheumatic diseases were selected as instrumental variables (IVs) to estimate the causal effects on PCOS. The final results were analyzed using five MR analysis methods, namely MR-Egger, inverse variance weighted (IVW), weighted median (WM), simple mode, and weighted mode. Causal estimation of MR was primarily obtained using the IVW method. Sensitivity analyses were also conducted to evaluate pleiotropy and heterogeneity. Results In this two-sample MR analysis, a total of 1,000,246 participants were included. Among them, there were 647 cases of SLE, 44 cases of PM, 5539 cases of RA, and 797 cases of PCOS. The IVW approach indicated a causal relationship between RA and an increased risk of PCOS (odds ratio [OR] = 1.069, 95% confidence interval [CI] = 1.007–1.134, p = 0.041). The MR-Egger intercept and Cochran’s Q test (p > 0.005) further verified the stability of the MR results. However, no significant correlation was observed between the other two rheumatic immune diseases (PM and SLE) and the risk of developing PCOS (both p > 0.05). Conclusion This study suggests a potential causal association between RA and PCOS, while SLE and PM do not exhibit a causal association with PCOS, enhancing our comprehension of the etiological factors of PCOS and shedding light on prevention strategies for the disease. Additional research is required to elucidate the underlying biological mechanisms by which RA contributes to the progression of PCOS.

Previous studies have reported a complex relationship between inflammatory cytokines and kidney stone disease (KSD). The purpose of this paper is to investigate the potential causal impact of inflammatory cytokines on KSD by Mendelian randomization (MR) analysis. In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between inflammatory cytokines and kidney stone disease. Utilizing GWAS summary data of inflammatory cytokines and KSD, we performed the first two-sample MR analysis. Genetic variants in GWASs related to inflammatory cytokines were employed as instrumental variables (IVs). The data on cytokines were derived from 14,824 participants and analyzed by utilizing the Olink Target-96 Inflammation Panel. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Reverse MR analysis, Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. 91 cytokines were enrolled in the MR analysis after strict quality control of IV. The IVW analysis revealed 2 cytokines as risk factors for KSD: Cystatin D (OR 1.06, 95% CI 1.01-1.11), Fibroblast growth factor 5 (OR 1.06, 95% CI 1.00-1.12), suggesting they are positively associated with the occurrence of kidney stones. We also found 3 protective associations between cytokines and KSD: Artemin (OR 0.86, 95% CI 0.78-0.96), T-cell surface glycoprotein CD6 isoform (OR 0.92, 95% CI 0.88-0.98), STAM-binding protein (OR 0.83, 95% CI 0.69-0.99). There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our MR Egger's intercept test, Cochrane Q-test, and MR-PRESSO, which were all > 0.05. Our study explored a variety of inflammatory cytokines related to KSD through MR analysis, which validated several previous findings and provided some new potential biomarkers for KSD. However, the findings require further investigation to validate their exact functions in the pathogenesis and evolution of KSD.

Previous observational studies reported that ankylosing spondylitis is closely related to hypertension. However, it is still controversial whether the association between ankylosing spondylitis and hypertension is causal. The effects of ankylosing spondylitis on diastolic and systolic blood pressure deserve further investigation. The objective of our study is to explore whether ankylosing spondylitis is causally associated with blood pressure. A bidirectional two-sample Mendelian randomization (MR) analysis was performed by employing five Mendelian randomization analysis methods. MR Egger regression, weighted median, inverse variance weighted, and weight mode methods were performed in the two-sample Mendelian randomization analysis. We performed Mendelian randomization to investigate the association between ankylosing spondylitis (finn-b-M13_ANKYLOSPON) and hypertension (ukb-b-14057), diastolic blood pressure (ebi-a-GCST90000062) and systolic blood pressure (ebi-a-GCST90000059). We also performed reverse Mendelian randomization between exposures and outcomes. Another new validation cohort (ukb-b-18194) was also performed. The heterogeneity, horizontal pleiotropy, and possible outliers were examined in the MR analysis results. The inverse variance weighted results showed that ankylosing spondylitis has no genetic causal relationship with hypertension (p = 0.441, OR = 1.001, 95% CI: 0.999-1.002). The inverse variance weighted results showed that ankylosing spondylitis has no genetic causal relationship with systolic blood pressure (p = 0.301, OR = 1.006, 95% CI: 0.995-1.018). The inverse variance weighted results showed that ankylosing spondylitis has no genetic causal relationship with diastolic blood pressure (p = 0.778, OR = 1.002, 95% CI: 0.988-1.016). The reverse Mendelian randomization between exposures and outcomes is negative. Another new validation cohort also confirmed the results. No heterogeneity was observed by the MR-pleiotropy residual sum and outlier test. The "leave-one-out" analysis indicated that the results of MR analysis were not affected by a single nucleotide polymorphism. This study represents the first two-sample Mendelian randomization analysis aimed at investigating the causal genetic relationship between ankylosing spondylitis and blood pressure. Our Mendelian randomization analysis results revealed a lack of causal association between ankylosing spondylitis and hypertension, diastolic blood pressure, as well as systolic blood pressure.

BackgroundThe etiology of nonalcoholic fatty liver disease (NAFLD) involves a complex interaction of genetic and environmental factors. Previous observational studies have revealed that higher leptin levels are related to a lower risk of developing NAFLD, but the causative association remains unknown. We intended to study the causal effect between leptin and NAFLD using the Mendelian randomization (MR) study.MethodsWe performed a two-sample Mendelian randomization (TSMR) analysis using summary GWAS data from leptin (up to 50,321 individuals) and NAFLD (8,434 cases and 770,180 controls) in a European population. Instrumental variables (IVs) that satisfied the three core assumptions of Mendelian randomization were selected. The TSMR analysis was conducted using the inverse variance weighted (IVW) method, MR-Egger regression method, and weighted median (WM) method. To ensure the accuracy and stability of the study results, heterogeneity tests, multiple validity tests, and sensitivity analyses were conducted.ResultsThe findings of the TSMR correlation analysis between NAFLD and leptin were as follows: IVW method (odds ratio (OR) 0.6729; 95% confidence interval (95% CI) 0.4907–0.9235; P = 0.0142), WM method (OR 0.6549; 95% CI 0.4373–0.9806; P = 0.0399), and MR-Egger regression method (P = 0.6920). Additionally, the findings of the TSMR correlation analysis between NAFLD and circulating leptin levels adjusted for body mass index (BMI) were as follows: IVW method (OR 0.5876; 95% CI 0.3781–0.9134; P = 0.0181), WM method (OR 0.6074; 95% CI 0.4231–0.8721; P = 0.0069), and MR-Egger regression method (P = 0.8870). It has also been shown that higher levels of leptin are causally linked to a lower risk of developing NAFLD, suggesting that leptin may serve as a protective factor for NAFLD.ConclusionsUsing TSMR analysis and the GWAS database, we investigated the genetic relationship between elevated leptin levels and lowered risk of NAFLD in this study. However, further research is required to understand the underlying mechanisms.

Intracerebral hemorrhage (ICH), a subtype of stroke, is associated with high incidence and disability rates. The link between inflammatory circulating proteins and ICH is still not definitively established. Our research sets out to delve into this mystery by examining the potential causal connection between 91 such proteins and ICH, employing a sophisticated two-sample Mendelian randomization approach to get to the bottom of it. We obtained 91 SNPs associated with inflammatory circulating proteins from a genome-wide association study (GWAS). Two-sample and multivariable Mendelian randomization analyses were conducted, with inverse variance weighted (IVW) serving as the primary method to assess the relationship between exposure and outcome. To enhance the reliability of the findings, additional methods such as MR-Egger, weighted median, simple mode, and weighted mode were employed. Cochran's Q test was used to assess the heterogeneity of the SNPs, while MR-Egger regression and MR-PRESSO were applied to evaluate the directional pleiotropy of the instrumental variables. Univariate Mendelian randomization analysis identified a significant causal relationship between four inflammatory circulating proteins, Axin1 (odds ratio (OR): 0.77, 95% confidence intervals (CI): 0.61-0.96, P-value = 0.0239), CXCL1 (OR: 0.81, 95% CI: 0.68-0.96, P-value = 0.0190), CXCL9 (OR: 0.85, 95% CI: 0.74-0.98, P-value = 0.0256), and MCP4 (OR: 0.79, 95% CI: 0.69-0.90, P = 0.0007), and the risk of ICH. After adjusting for confounding factors such as body weight and alcohol consumption, multivariable Mendelian randomization analysis still demonstrated a significant causal relationship between these four proteins and ICH. Furthermore, after excluding hypertension as a confounder, MCP4 expression remained significantly associated with ICH. When adjusting for type 2 diabetes, both CXCL9 and MCP4 exhibited a significant causal relationship with ICH. Reverse Mendelian randomization analysis revealed a negative correlation between ICH (as the exposure) and the expression of seven inflammatory circulating proteins. In summary, our two-sample Mendelian randomization analysis, which operates in both directions, has revealed a likely causal link between four inflammatory proteins present in circulation and the risk of ICH. Keeping track of the expression levels of these inflammatory proteins may prove beneficial for both the prevention and management of ICH. There is a significant bidirectional causal relationship between inflammatory circulating proteins and the risk of intracerebral hemorrhage (ICH) onset. The expression levels of Axin1, CXCL1, CXCL9, and MCP4 are negatively correlated with the risk of ICH onset, suggesting that they may serve as potential important molecular targets for ICH.

Both anxiety and obesity have been implicated in hypertension development, with emerging evidence suggesting metabolic risk factors as potential mediators. Notably, obesity may partially mediate the link between anxiety and hypertension. However, the causal relationships among these factors remain unclear. To address this, we conducted a two-sample Mendelian randomization (MR) analysis to elucidate their causal relationship. We conducted a two-sample MR analysis using genome-wide association study (GWAS) summary statistics from European ancestry cohorts. The inverse-variance weighted (IVW) method was used as the primary analytical approach, with sensitivity analyses and heterogeneity tests conducted to ensure robustness. Additionally, a two-step MR approach was conducted to quantify the proportion of the anxiety-hypertension association mediated through obesity-related pathways. The two-sample MR analysis demonstrated significant causal effects of anxiety (OR = 1.025, 95% CI 1.011-1.038; P < 0.001) and obesity (OR = 1.010, 95% CI 1.007-1.013; P < 0.001) on hypertension risk. Bidirectional analysis revealed a unidirectional causal association between anxiety and obesity (OR = 1.518, 95% CI 1.044-2.206; P = 0.029), with no evidence of reverse causation from obesity to anxiety (OR = 1.014, 95% CI 0.990-1.039; P = 0.268). Mediation analysis estimated that 17.4% (95% CI 5.3-29.5%) of anxiety's total effect on hypertension risk was mediated through adiposity-related pathways. The two-sample MR analysis in this study confirmed a causal relationship between anxiety and hypertension. Obesity was found to partially mediate this association. Our causal estimates support weight management interventions as an effective psychosomatic strategy for preventing hypertension in individuals with anxiety, particularly due to the modifiable nature of obesity-related risk factors.

Type 2 diabetes (T2D) frequently co-occurs with respiratory system diseases such as chronic obstructive pulmonary disease (COPD), bronchial asthma, lung cancer, interstitial lung disease, and pulmonary tuberculosis. Although a potential association is noted between these conditions, the available research is limited. To investigate the causal relationship between patients with T2D and respiratory system diseases using two-sample Mendelian randomization analysis. Causal relationships were inferred using a two-sample Mendelian randomization (MR) analysis based on publicly available genome-wide association studies. We employed the variance inverse-weighted method as the primary analytical approach based on three key assumptions underlying MR analysis. To bolster the robustness and reliability of our results, we utilized MR Egger's intercept test to detect potential pleiotropy, Cochran's Q test to assess heterogeneity, funnel plots to visualize potential bias, and "leave-one-out" sensitivity analysis to ensure that our findings were not unduly influenced by any single genetic variant. The inverse variance weighted (IVW) analysis indicated a causal relationship between T2D and COPD [Odds Ratio (OR) = 0.87; 95% Confidence Interval (CI) = 0.82-0.96; p < 0.05]. No significant heterogeneity or pleiotropy were observed through their respective tests (p > 0.05), and the statistical power calculations indicated that the results were reliable. The IVW analysis showed a negative causal relationship between T2D and bronchial asthma [OR = 0.85; 95% CI = 0.81-0.89; p < 0.05]. However, the IVW under the random-effects model indicated heterogeneity (p < 0.05), suggesting instability in the results and requiring cautious interpretation. The study found a positive causal relationship between T2D and pulmonary tuberculosis (OR = 1.24, 95% CI = 1.05-1.45, p < 0.05). However, they exhibited pleiotropy (p < 0.05), indicating their instability. No correlation between T2D and interstitial lung disease or lung cancer was observed. T2D is negatively associated with COPD, suggesting that T2D may reduce the risk of developing COPD. A negative causal relationship between T2D and bronchial asthma has been observed, but the results exhibit heterogeneity. There is a positive causal relationship between T2D and pulmonary tuberculosis, yet the findings suggest the presence of pleiotropy. No significant causal relationship between T2D and lung cancer or interstitial lung disease was observed.

PurposeObesity is a strong risk factor for many diseases, with controversy regarding the cause(s) of tuberculosis (TB) reflected by contradictory findings. Therefore, a larger sample population is required to determine the relationship between obesity and TB, which may further inform treatment.MethodsObesity-related indicators and TB mutation data were obtained from a genome-wide association study database, while representative instrumental variables (IVs) were obtained by screening and merging. Causal relationships between exposure factors and outcomes were determined using two-sample Mendelian randomization (MR) analysis. Three tests were used to determine the representativeness and stability of the IVs, supported by sensitivity analysis.ResultsInitially, 191 single nucleotide polymorphisms were designated as IVs by screening, followed by two-sample MR analysis, which revealed the causal relationship between waist circumference [odds ratio (OR): 2.13 (95% confidence interval (CI): 1.19–3.80); p = 0.011] and TB. Sensitivity analysis verified the credibility of the IVs, none of which were heterogeneous or horizontally pleiotropic.ConclusionThe present study determined the causal effect between waist circumference and TB by two-sample MR analysis and found both to be likely to be potential risk factors.

Obesity is a strong risk factor for many diseases, with controversy regarding the cause(s) of tuberculosis (TB) reflected by contradictory findings. Therefore, a larger sample population is required to determine the relationship between obesity and TB, which may further inform treatment. Obesity-related indicators and TB mutation data were obtained from a genome-wide association study database, while representative instrumental variables (IVs) were obtained by screening and merging. Causal relationships between exposure factors and outcomes were determined using two-sample Mendelian randomization (MR) analysis. Three tests were used to determine the representativeness and stability of the IVs, supported by sensitivity analysis. Initially, 191 single nucleotide polymorphisms were designated as IVs by screening, followed by two-sample MR analysis, which revealed the causal relationship between waist circumference [odds ratio (OR): 2.13 (95% confidence interval (CI): 1.19-3.80); p = 0.011] and TB. Sensitivity analysis verified the credibility of the IVs, none of which were heterogeneous or horizontally pleiotropic. The present study determined the causal effect between waist circumference and TB by two-sample MR analysis and found both to be likely to be potential risk factors.

BackgroundObservational studies reported an association between psoriasis and risk of lung cancer. However, whether psoriasis is causally associated with lung cancer is unclear.MethodsGenetic summary data of psoriasis were retrieved from two independent genome-wide association studies (GWAS). Genetic information of lung cancer was retrieved from GWAS of International Lung Cancer Consortium. A set of quality control steps were conducted to select instrumental tools. We performed two independent two-sample Mendelian randomization (MR) analyses and a meta-analysis based on the two independent MR estimates to assess the causal relationship between psoriasis and lung cancer (LUCA) as well as its subtypes, squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD).ResultsBetween-SNP heterogeneity was present for most MR analyses, whereas horizontal pleiotropy was not detected for all MR analyses. Multiplicative random-effect inverse variance weighted (IVW-MRE) method was therefore selected as the primary MR approach. Both IVW-MRE estimates from the two independent MR analyses suggested that there was no significant causal relationship between psoriasis and LUCA as well as its histological subtypes. Sensitivity analyses using other four MR methods gave similar results. Meta-analysis of the two IVW-MRE derived MR estimates yielded an odds ratio (OR) of 1.00 (95% CI 0.95–1.06) for LUCA, 1.01 (95% CI 0.93–1.08) for LUSC, and 0.97 (95% CI 0.90–1.06) for LUAD.ConclusionOur results do not support a genetic association between psoriasis and lung cancer and its subtypes. More population-based and experimental studies are warranted to further dissect the complex correlation between psoriasis and lung cancer.

The purpose of this study was to investigate the causal relationship between gastroesophageal reflux disease (GERD) and hypertension using a two-sample Mendelian randomization analysis. The associated data of GERD with hypertension were derived from the genome-wide association study (GWAS) database, and two-sample Mendelian randomization (MR) analysis was performed using methods including inverse variance weighting (IVW), MR-Egger, and weighted median (WM) to investigate the causal association between GERD and hypertension. A total of 16 single nucleotide polymorphisms (SNPs) strongly associated with GERD were screened out, and the IVW suggested a causal relationship between GERD and hypertension (OR: 1.057; 95% CI: 1.044-1.071; P < 0.05). The weighted median also showed a similar relationship (OR: 1.051, 95% CI: 1.032-1.07; P < 0.05). In addition, no heterogeneity or horizontal pleiotropy was observed, suggesting a robustness of the outcome. There is a positive causal relationship between GERD and hypertension.

Aims/hypothesis: The association between gastroesophageal reflux disease (GERD) and rheumatoid arthritis (RA) has been reported by many observational studies in the Asian population. This study aimed to examine the bidirectional causal effects between GERD and RA by two-sample Mendelian randomization (MR) analyses using genetic evidence. Methods: Two-sample Mendelian randomization analyses were performed to determine the causal effect of GERD (129,080 cases vs. 602,604 control participants) on RA (6,236 cases vs. 147,221 control participants) and RA on GERD, respectively. The inverse-variance weighted (IVW) method was used as the primary analysis. Weighted median and MR-Egger regression were taken as supplementary analyses. Cochran's Q test evaluated the heterogeneity. Horizontal pleiotropy was detected by estimating the intercept term of MR-Egger regression. Furthermore, multivariable MR analyses were performed to exclude the influence of confounding factors, including the years of schooling, BMI, and time spent watching television, between GERD and RA. Result: Both univariate MR (UVMR) and multivariable MR (MVMR) provided valid evidence that RA was causally and positively influenced by GERD (UVMR: OR = 1.49, 95% CI = 1.25-1.76, p = 6.18*10-6; MVMR: OR = 1.69, 95% CI = 1.24-2.31, p = 8.62*10-4), whereas GERD was not influenced by RA (UVMR: OR = 1.03, 95% CI = 1.00-1.06, p = 0.042; MVMR: OR = 1.04, 95% CI = 1.00-1.07, p = 0.0271). Conclusion: Our comprehensive bidirectional MR analysis found that for the European population, GERD can induce the occurrence of RA (OR = 1.69, p < 0.00125), whereas RA only has no significant influence on GERD. In particular, patients with GERD are suffering a 69% increased risk of RA occurrence, which means GERD is a substantial risk factor for RA.