Causal effects of multiple exposures on endometrial cancer and its subtypes: A two-sample Mendelian randomized study

Causal effects of multiple exposures on endometrial cancer and its subtypes: A two-sample Mendelian randomized study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Causal effects of multiple exposures on endometrial cancer and its subtypes: A two-sample Mendelian randomized study Jing Cui, Bozhou Cui, Jie Yang, Yan Ding, Feixia Li, Tuoyang Hu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8340876/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Endometrial cancer (EC) is a common gynecological tumor in women, with complex causes. Some studies suggest that it is related to lifestyle, gastrointestinal diseases, reproductive factors, etc., but the causal relationship among them remains unclear. This study employed a two-sample Mendelian randomization method to investigate the causal relationship between these factors and EC. Methods: MR Analysis was conducted using publicly available GWAS data. Preliminary analysis was carried out using the IVW method, combined with the RAPS method to enhance robustness, and supplementary analysis was performed using MR-Egger, weighted median, simple mode and weighted mode. Heterogeneity and pleiotropy were evaluated by Cochran Q test, Leave-One-Out method, MR-Egger intercept test and MR-PRESSO method. Results: Ten exposure factors that constitute a causal relationship with EC and its subtypes were identified from aspects such as Lifestyle, Gastrointestinal disease, and Reproductive factors. Among them, Variation in diet, Salt added to food and Gastroesophageal reflux disease (GERD) were only positively correlated with the risk of endometrioid EC (ECEH). However, Ulcerative colitis and Comparative body size at age 10 were positively correlated with both ECEH and non-endometrioid EC (ECNEH). Furthermore, Average weekly beer plus cider intake, Celiac disease, Age first had sexual intercourse and Length of menstrual cycle were negatively correlated with ECEH only, while Parental longevity (mother's attained age) was negatively correlated with both ECEH and ECNEH. Conclusion: Our mendelian randomization analysis provides genetic evidence supportive of potential causal roles for ten exposure factors in the development of endometrial cancer subtypes (ECEH and ECNEH). These findings suggest that early screening for populations with relevant risk profiles and targeted interventions for modifiable factors could be considered in future strategies for the subtype-specific prevention and management of endometrial cancer. Further validation in clinical and experimental settings is required. exposure factors endometrial cancer mendelian randomization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Endometrial cancer (EC) is a common gynecological cancer in women, causing over 2% of cancer-related deaths worldwide [ 1 ]. In recent years, the incidence of EC has been increasing [ 2 ], and it is expected to continue to increase significantly in the next decade [ 3 ]. Actively understanding the risk factors related to the occurrence of EC is crucial for preventing its occurrence and reducing the incidence rate. The etiology of EC is complex. Previous studies have mostly focused on the risk correlations or causal relationships between metabolic factors [ 4 , 5 ], estrogen exposure [ 6 , 7 ] and EC, while paying little attention to factors such as lifestyle, gastrointestinal diseases, and reproduction. However, relevant studies [ 8 – 10 ] suggest that these factors may also play a certain role in the onset of EC, but the causal relationship has not been systematically explored. At the same time, most previous studies have been accustomed to treating overall EC as the research outcome, and rarely specifically exploring the causes of different EC subtypes (Bokhman's type 1/2) [ 11 ]. This has led to ongoing disputes between common risk factors and unique risk factors. Mendelian randomization studies are a statistical method that uses genetic variations as instrumental variables for causal relationship analysis [ 12 ]. It can effectively avoid interference from external factors, reverse causality, and other confounding factors, and has gradually become the primary choice for causal relationship analysis [ 13 ]. In this study, we used the two-sample MR analysis method to analyze GWAS data on multiple exposure factors and outcomes to reveal potential causal relationships between various controllable and uncontrollable exposure factors and endometrial cancer and its subtypes. Early intervention of controllable factors and regular screening of high-risk populations containing uncontrollable factors will be beneficial for the prevention and early detection of specific EC subtypes. 2. Methods 2.1 Study Design The two-sample MR method was used to analyze the exposure factors that have a causal relationship with EC and its subtypes. The design, implementation and reporting of this study followed the STROBE-MR guidelines, and the complete STROBE-MR checklist was provided as an additional document (Supplementary File 1). A total of 10 exposure factors in multiple aspects were analyzed for their causal relationships with the same outcome (see Fig. 1 for details). 2.2 Selection of Exposures and Data Source Based on previous epidemiological reports and biological pathogenesis, we selected exposure factors covering aspects such as Lifestyle, Gastrointestinal disease, and Reproductive factors to explore the potential causal relationships between these factors and EC and its subtypes. The basis for each exposure selection is detailed in Supplementary Table 1. All the GWAS data related to exposure and outcome are sourced from the IEU OpenGWAS database ( https://opengwas.io/datasets/ ) , with the data collection ending on November 23, 2025. Among them, the outcomes are "Endometrial cancer", and the subtypes are "Endometrial cancer (endometrioid histology)" and "Endometrial cancer (Non-endometrioid histology)". All GWAS summary statistics used in this study were obtained from published studies and public databases. No specific ethical approval or permission was required to access these data as they are de-identified summary-level data. Ethical approval for the original data collection was obtained in the respective primary studies (See Table 1 , Supplementary Excel File S3). Table 1 Summary of the GWAS data used in the MR analysis. Phenotype GWAS ID Year Sample size Number of SNPs Population Variation in diet ukb-b-2909 2018 460,884 9,851,867 European Salt added to food ukb-b-8121 2018 462,630 9,851,867 European Average weekly beer plus cider intake ukb-b-5174 2018 327,634 9,851,867 European Gastroesophageal reflux disease ebi-a-GCST90000514 2021 602,604 2,320,781 European Ulcerative colitis ieu-a-973 2011 26,405 1,243,971 European Celiac disease ebi-a-GCST005523 2011 23,649 97,422 European Age first had sexual intercourse ukb-b-6591 2018 406,457 9,851,867 European Length of menstrual cycle ukb-a-351 2017 30,245 10,894,596 European Comparative body size at age 10 ukb-a-34 2017 331,693 10,894,596 European Parental longevity (father's attained age) ebi-a-GCST006701 2017 415,311 11,489,837 European Parental longevity (mother's attained age) ebi-a-GCST006696 2017 412,937 11,490,494 European Endometrial cancer ebi-a-GCST006464 2018 121,885 9,470,555 European Endometrial cancer (endometrioid histology) ebi-a-GCST006465 2018 54,884 9,464,330 European Endometrial cancer (Non-endometrioid histology) ebi-a-GCST006466 2018 36,677 8,974,630 European 2.3 Selection of SNPs To ensure the stability and statistical efficacy of the exposure factor instrumental variables, a threshold of p < 5×10 − 8 was set as the criterion for selecting those significantly associated with the exposure. A strict linkage disequilibrium (LD) aggregation threshold (r2 < 0.001, within a 10 Mb window) was established. SNPs known to be related to the outcome variable or major confounding factors (p 10 were retained to reduce the bias from weak instrumental variables. Before the MR analysis, palindromic SNPs were excluded to ensure the robustness of the results. 2.4 MR Analysis In this study, we first employed the inverse variance weighting method (IVW), MR-Egger, weighted median, simple model, and weighted model to analyze the causal relationship between the exposure factors and endometrial cancer and its subtypes. The main purpose was to observe the analysis results of IVW and supplement them with the results obtained from the other four MR analysis methods. Given that both the exposure and the outcome originated from the IEU OpenGWAS database, there might be a horizontal multi-effect of the instrumental variable due to sample overlap, which could lead to false positive or false negative results in the final IVW analysis. Therefore, to minimize the interference caused by potential sample overlap as much as possible, we further used the MR-RAPS method to obtain more robust causal effect estimates. At the same time, the MR-Egger intercept test was used to assess the multi-effect, and if the intercept value was close to 0 and P > 0.05, it indicated the absence of horizontal multi-effect. The MR-PRESSO method was used to detect abnormal SNPs, and if such SNPs existed, they were corrected, and the Distortion Test was used to evaluate whether the abnormal SNPs would have a significant impact on the results. Finally, the P values, odds ratios (OR), 95% confidence intervals (CI), and SNPs in the IVW and RAPS analysis results were presented in a forest plot format. The Cochran Q test in MR-Egger and IVW methods was used to evaluate heterogeneity, and if P > 0.05, it indicated the absence of heterogeneity. The leave-one-out method was used to evaluate the influence of a single SNP on the causal relationship. A scatter plot was used to visually display the effect of SNPs on the exposure factor (X-axis), EC and subtypes (Y-axis), and a fitting line was used to show whether the causal effect directions of the six MR methods were consistent. 2.4 Statistical Analysis 3. Statistical analysis was conducted using the packages such as TwoSampleMR, ieugwasr, forestploter, and VariantAnnotation in the R software (version 4.4.3). 3. Results 4.1 Causal influence of exposure factors on EC and its subtypes MR method was used to assess evidence for potential causal relationships between 11 exposure factors (such as Lifestyle, Gastrointestinal disease, Reproductive factors) and EC and its subtypes. We mainly observed the analysis results of IVW and RAPS and presented them in the form of forest plots (Fig. 2 , Fig. 3 ). Among the IVW analysis results, the causal associations between Length of menstrual cycle and EC, and Parental longevity (father's attained age) and ECEH might be falsely positive due to sample overlap, while Variation in diet and EC, Parental longevity (mother's attained age) and ECNEH might be falsely negative due to interference. It is worth noting that in the RAPS analysis results, Variation in diet (OR = 5.795, 95% CI 1.110–30.250, P = 0.037), Salt added to food (OR = 1.447, 95% CI 1.018–2.056, P = 0.039) had a positive causal relationship with ECEH, while Average weekly beer plus cider intake (OR = 0.389, 95% CI 0.157–0.966, P = 0.042) had a negative causal relationship with ECEH. However, these exposure factors did not have causal relationships with ECNEH subtypes. In the gastrointestinal disease aspect, Gastroesophageal reflux disease (GERD) (OR = 1.404, 95% CI 1.217–1.620, P = 3.251e-06), Ulcerative colitis (OR = 1.034, 95% CI 1.004–1.064, P = 0.026) had a positive causal relationship with ECEH, while Celiac disease (OR = 0.955, 95% CI 0.928–0.982, P = 0.001) had a negative correlation with it. At the same time, Ulcerative colitis (OR = 1.148, 95% CI 1.064–1.239, P = 3.675e-04) also formed a positive causal relationship with ECNEH. In the reproductive factors aspect, Age first having sexual intercourse (OR = 0.761, 95% CI 0.622–0.931, P = 0.008), Length of menstrual cycle (OR = 0.668, 95% CI 0.507–0.881, P = 0.004) were negatively correlated with the occurrence of ECEH. In other respects, the comparative body size at the age of 10 has a positive causal relationship with ECEH (OR = 2.228, 95% CI 1.733–2.865, P = 4.215e-10) and ECNEH (OR = 2.184, 95% CI 1.284–3.716, P = 0.004), while Parental longevity (mother's attained age) has a negative causal relationship with ECEH (OR = 0.205, 95% CI 0.082–0.509, P = 0.001) and ECNEH (OR = 0.064, 95% CI 0.007–0.562, P = 0.013). Additionally, we conducted supplementary analyses using four other MR methods (see Supplementary Excel File S2 for details). 4.2 Characteristics of Selected SNPs After rigorous screening under specific conditions, SNPs closely related to each exposure factor were obtained. The corresponding summary information is presented in Supplementary Excel File S3. Upon observation, it was found that the F-statistic of all SNPs were greater than 10, with the lowest value being 29.7 and the highest being 832.3. This indicates that there is no possibility of weak instrumental variables. 4.3 Sensitivity and Heterogeneity Analysis The MR-Egger regression and IVW Cochran Q test method were used to evaluate whether there was heterogeneity in the MR analysis results (Table 2 ). Among them, the exposure factors that were causally related to EC, such as Salt added to food (MR-Egger Q = 148.970, P = 0.001; IVW Q = 149.441, P = 0.002), Celiac disease (MR-Egger Q = 63.508, P = 0.002; IVW Q = 64.412, P = 0.002), and Comparative body size at age 10 (MR-Egger Q = 206.946, p = 0.002; IVW Q = 210.981, P = 0.002), showed heterogeneity. The exposure factors that were causally related to ECEH, such as Variation in diet (MR-Egger Q = 23.047, P = 0.041), Salt added to food (MR-Egger Q = 144.332, P = 0.003; IVW Q = 144.401, P = 0.004), Celiac disease (MR-Egger Q = 57.730, p = 0.009; IVW Q = 57.731, P = 0.012), Comparative body size at age 10 (MR-Egger Q = 204.650, P = 0.003; IVW Q = 206.708, P = 0.003), and Ulcerative colitis (MR-Egger Q = 103.775, P = 0.013; IVW Q = 104.116, P = 0.015), also showed heterogeneity. Other factors did not show significant heterogeneity (P > 0.05). Further observation of the funnel plot revealed that the distribution of SNPs was basically symmetrical (Fig. 4 , Supplementary Fig. 1). Table 2 Heterogeneity test of the exposures from MR. Heterogeneity Test MR-Egger IVW Q Q(DF) P.value Q Q(DF) P.value Variation in diet EC 20.104 13 0.093 20.744 14 0.108 ECEH 23.047 13 0.041 23.566 14 0.052 Salt added to food EC 148.970 101 0.001 149.441 102 0.002 ECEH 144.332 101 0.003 144.401 102 0.004 Average weekly beer plus cider intake EC 22.083 18 0.228 25.604 19 0.142 ECEH 24.194 18 0.149 27.752 19 0.088 Gastroesophageal reflux disease EC 81.094 75 0.295 81.528 76 0.311 ECEH 79.314 75 0.345 79.683 76 0.364 Ulcerative colitis EC 78.667 78 0.458 79.185 79 0.473 ECEH 75.041 78 0.574 76.433 79 0.561 ECNEH 103.775 74 0.013 104.116 75 0.015 Celiac disease EC 63.508 35 0.002 64.412 36 0.002 ECEH 57.730 35 0.009 57.731 36 0.012 Age first had sexual intercourse EC 202.352 187 0.210 202.389 188 0.224 ECEH 219.473 188 0.058 219.488 189 0.064 Length of menstrual cycle ECEH 3.320 4 0.506 3.321 5 0.651 Comparative body size at age 10 EC 206.946 153 0.002 210.981 154 0.002 ECEH 204.650 153 0.003 206.708 154 0.003 ECNEH 163.308 154 0.288 163.689 155 0.301 Parental longevity (mother's attained age) EC 5.282 2 0.071 6.816 3 0.078 ECEH 1.750 2 0.417 2.822 3 0.420 ECNEH 4.702 2 0.095 4.732 3 0.192 The MR-PRESSO method was used to conduct a Global Test on all SNPs in the causal relationships, and it was found that there was pleiotropy in the causal relationship analysis between Age first had sexual intercourse and EC, ECEH (EC: P = 0.009; ECEH: P = 0.008). Abnormal SNPs were identified (EC: rs11030102, rs4873133; ECEH: rs4873133). After correction, the IVW effect size (EC: β = -0.235 vs. original β = -0.243; ECEH: β = -0.283 vs. original β = -0.316) was consistent in direction, and the P values of the Distortion Test were 0.923 and 0.749, respectively. The same significant pleiotropy was found for Comparative body size at age 10 and EC, ECEH (EC: P < 0.001; ECEH: P < 0.001), and the same abnormal SNPs were identified (rs3131934, rs73085586). After correction, the IVW effect size (EC: β = 0.662 vs. original β = 0.669; ECEH: β = 0.762 vs. original β = 0.764) was consistent in direction, and the P values of the Distortion Test were 0.951 and 0.990, respectively. The above analysis indicates that all abnormal SNPs do not affect the robustness of the original MR results. After conducting MR-Egger regression intercept analysis on all causal relationships, it was found that the intercept values were close to 0 and the P values were greater than 0.05, indicating no significant horizontal pleiotropy, further confirming the reliability of the MR results (Table 3 , Supplementary Excel File S4). Table 3 Pleiotropy test of the exposures from MR. Pleiotropy Test MR-Egger Intercept SE P.value Variation in diet EC -0.026 0.041 0.531 ECEH -0.028 0.052 0.598 Salt added to food EC 0.004 0.007 0.574 ECEH 0.002 0.008 0.827 Average weekly beer plus cider intake EC 0.024 0.014 0.108 ECEH 0.029 0.018 0.121 Gastroesophageal reflux disease EC -0.007 0.011 0.528 ECEH -0.008 0.013 0.556 Ulcerative colitis EC -0.004 0.006 0.476 ECEH -0.008 0.007 0.242 ECNEH -0.010 0.020 0.624 Celiac disease EC 0.004 0.006 0.485 ECEH -1.833E-04 0.007 0.980 Age first had sexual intercourse EC -0.001 0.006 0.854 ECEH -0.001 0.007 0.913 Length of menstrual cycle ECEH 3.529E-04 0.019 0.986 Comparative body size at age 10 EC -0.006 0.004 0.086 ECEH -0.005 0.004 0.217 ECNEH -0.006 0.009 0.550 Parental longevity (mother's attained age) EC -0.030 0.039 0.526 ECEH -0.030 0.029 0.409 ECNEH 0.012 0.108 0.920 The independent effect of the instrumental variable and the total effect of IVW (Fig. 5 , Supplementary Fig. 2) were visualized using a forest plot. The results showed that in the causal analysis of exposure factors and EC and subtypes, the confidence intervals of all SNPs overlapped highly and were consistent in direction, indicating low heterogeneity. Sensitivity analysis was conducted using the leave-one-out method, and the forest plot (Fig. 6 , Supplementary Fig. 3) showed that after removing any SNP, the effect estimates remained stable, indicating that the analysis results were not dominated by any single SNP. All of these further confirmed the robustness of the MR results. After conducting the analysis of multiplicity and sensitivity, SNPs were used for MR analysis, and the results were presented in the form of scatter plots (Fig. 7 , Supplementary Fig. 4). 4. Discussion Using a two-sample Mendelian randomization framework, this study provides novel genetic evidence suggesting potential causal roles for ten exposure factors across lifestyle, gastrointestinal, and reproductive domains in the development of endometrial cancer and its subtypes. To our knowledge, this is the first systematic MR investigation to simultaneously evaluate these diverse factors in relation to EC subtypes. If validated, these findings could inform future research aimed at multidimensional prevention strategies and risk stratification for early detection of specific EC subtypes. Heterogeneity was observed for several exposures (variations in diet, salt added to food, ulcerative colitis, celiac disease, and comparative body size at age 10) as indicated by Cochran’s Q test. However, subsequent analyses revealed no significant horizontal pleiotropy (MR-Egger intercept test) and no single influential SNP (leave-one-out analysis). We speculate that the observed heterogeneity might be attributable to unmeasured confounding factors, such as potential gender differences, given that the outcome population (EC patients) is exclusively female while the exposure GWAS were not sex stratified. To account for this heterogeneity, we employed a random-effects IVW model for these analyses. A genetically predicted longer menstrual cycle was associated with an increased risk of the endometrioid subtype (ECEH) but not with overall EC. One plausible explanation is that the overall EC estimate represents a combined effect of both ECEH and non-endometrioid (ECNEH) subtypes, and a null association at the overall level could be due to a dilution effect from the inverse or null association in the ECNEH subgroup. To address the potential bias from sample overlap between the exposure (menstrual cycle length) and outcome GWAS (both sourced from the IEU OpenGWAS project), we utilized the Robust Adjusted Profile Score (RAPS) method. The robustness of all primary findings was further assessed using MR-Egger regression and MR-PRESSO global tests.. In terms of Lifestyle, we found that variations in diet and salt added to food can increase the risk of ECEH, while average weekly beer and cider intake has a protective effect. Irregular diet, such as intermittent overeating and prolonged fasting, can cause fluctuations in blood sugar, increasing insulin resistance, and the body will secrete more insulin. Insulin, in addition to regulating sugar metabolism, is also an important growth regulatory factor, which can promote significant proliferation of endometrial cells and increase the risk of EC by [ 14 , 15 ]. At the same time, nocturnal eating or high-sugar and high-fat diets are likely to cause accumulation of visceral fat and lead to obesity. Previous studies [ 5 , 16 ] have suggested that obesity is an important risk factor for EC. Fat cells can release various inflammatory factors, among which IL-6, TNF-α, etc. are closely related to the onset of EC [ 17 ]. Moreover, fat cells can also release estrogen, which can stimulate endometrial hyperplasia through nuclear receptor pathways and membrane receptor pathways, promoting the occurrence of ECEH [ 18 ]. Therefore, all these emphasize the necessity of adjusting dietary habits and maintaining regular eating for the prevention of ECEH. Salt added to food can increase the risk of ECEH, possibly because long-term high-salt diet is more likely to trigger hypertension, which has been proven as an independent risk factor [ 19 ]. Hypertension can cause damage to the vascular endothelium of the endometrium and changes in the local microenvironment, creating conditions for the growth of cancer cells. At the same time, Liao et al. [ 20 ] found that a brief high-salt diet can cause epigenetic changes and generate continuous inflammatory activation through NF-κB and other signaling pathways, stimulating abnormal endometrial hyperplasia. The influence of alcohol on the risk of EC has always been controversial. A meta-analysis found [ 21 ] that alcohol is related to EC in a J-shaped relationship. Drinking less than one cup per day can reduce the risk of EC, while more than two cups can increase the risk of EC. A prospective study involving 68,067 nurses found [ 22 ] that moderate drinking can reduce the risk of EC by 22%. Some studies also suggest [ 23 ] that alcohol has no relation to the onset of EC. This study from the perspective of genetic prediction found that Average weekly beer and cider intake is negatively correlated with the risk of ECEH, possibly because compared with beer, beer and cider have lower alcohol concentrations, which is consistent with the conclusion that moderate drinking can reduce the risk of EC. Given that 4% of cancers worldwide are caused by alcohol [ 24 ], this conclusion should be interpreted with caution and more evidence is needed to confirm it. It is worth noting that the polyphenols contained in beer such as flavonoids and proanthocyanidins [ 25 ] have antioxidant and anti-inflammatory effects, which can reduce chronic inflammation and DNA damage in the endometrium. Meanwhile, the probiotic components in apple wine [ 25 ] may contain, through influencing the gut microbiota-estrogen axis, regulate endometrial hyperplasia [ 26 ]. This suggests that future research should pay more attention to the potential protective effects of non-alcoholic beer or apple wine components on ECEH. In the field of gastrointestinal diseases, this study found a positive causal relationship between gastroesophageal reflux disease (GERD) and endometrial cancer epithelial hyperplasia (ECEH). Obesity is a clear risk factor for GERD [ 27 ] and the strongest risk factor for ECEH [ 28 ]. The genetic instrumental variables related to GERD in this MR analysis may capture the genetic predisposition that leads to obesity. This genetic predisposition first causes obesity, and obesity then simultaneously becomes a common cause of GERD and ECEH. This study is the first to reveal this causal relationship from a genetic perspective, providing a new perspective for understanding the common causes of these two diseases. In addition, chronic esophageal inflammation caused by GERD itself may lead to a long-term low-level inflammatory state throughout the body [ 29 ]. This inflammatory environment may promote the occurrence and development of ECEH. Although this possibility is low and difficult to be completely distinguished from the inflammation related to obesity, we cannot completely rule out the weak direct contribution of chronic inflammation related to GERD to the risk of ECEH. This requires future experimental research to verify. Ulcerative colitis, as a chronic inflammatory disease, its association with colorectal cancer has been well recognized, but few people have paid attention to its association with gynecological malignancies, especially EC [ 30 ]. This study initially found that ulcerative colitis is positively causally related to ECEH and ECNEH subtypes, providing new research evidence in this direction. The characteristics of ulcerative colitis are intestinal mucosal barrier disruption and immune regulation disorder, leading to persistent, unrelenting local and systemic inflammation. It has become a well-known driver of various cancers. Inflammatory factors in the systemic circulation, such as TNF-a and IL-6, can reach the endometrium and directly promote the proliferation, invasion, and inhibition of apoptosis of endometrial cells through activating NF-kB and other signaling pathways. This inflammatory-driven carcinogenic mechanism is essentially hormone-independent. In ECEH, inflammation works in synergy with the high estrogen environment to accelerate estrogen-dependent cell proliferation. In ECNEH, inflammation plays a more central and independent role, directly driving events such as TP53 mutations, leading to malignant transformation in a low-estrogen environment [ 31 ]. Therefore, for women with ulcerative colitis, they should be regarded as high-risk groups for both EC subtypes. This calls for the inclusion of education and monitoring recommendations for EC in the long-term management guidelines for such patients. Celiac disease is an abnormal autoimmune reaction disease triggered by genetic susceptibility individuals consuming gluten [ 32 ]. This study found that celiac disease has an astonishingly negative causal relationship with the risk of ECEH, suggesting that it plays a protective role. The essence of celiac disease is an abnormal Th1 immune response to gluten antigens under HLA-DQ2/DQ8 restriction, and these immune cells may recognize antigen peptides expressed on the surface of ECEH cells, structurally similar to those, through a "molecular mimicry" mechanism. This cross-reaction may lead to early immune surveillance of early cancer cells and their clearance at an early stage. In addition, celiac disease patients often experience chronic diarrhea, malnutrition, and weight loss. Given that obesity is a significant risk factor for ECEH (as adipose tissue produces estrogen through aromatase) [ 27 ], the genetic predisposition to celiac disease may lead to persistently lower circulating estrogen levels throughout life, thereby exerting a continuous protective effect. In the "Reproductive Factors" section, the relationship between "Age at First Sexual Intercourse" and ECEH is inversely causal. This means that individuals with a genetic predisposition to having earlier sexual activity have a significantly increased lifetime risk of developing ECEH. Exposure to estrogen is a high-risk factor for ECEH [ 18 ]. During the sexual behavior process, oxytocin and estrogen are released, and the younger the age of first sexual intercourse, the earlier one is exposed to high levels of estrogen fluctuations. At the same time, early sexual behavior can affect the physical and mental health of teenagers and exacerbate endocrine disorders, leading to abnormal proliferation and apoptosis of the endometrium [ 33 ]. All of these emphasize the importance of conducting sexual education among teenagers. Previous epidemiological studies have found that irregular menstrual cycles are a high-risk factor for EC [ 34 ], but the potential causal relationship has not been explored. In this study, we discovered from a genetic perspective that the "Length of Menstrual Cycle" has a negative causal relationship with ECEH, that is, a shorter menstrual cycle is a high-risk factor for ECEH. A shorter menstrual cycle means more frequent follicular development, ovulation, and estrogen fluctuations. Each cycle's estrogen peak will continuously stimulate the proliferation of the endometrium. At the same time, women with a shortened menstrual cycle have an increased number of ovulatory cycles throughout their lifetime, more times of endometrial proliferation and shedding, and more opportunities for cell division or DNA replication errors, increasing the rate of endometrial malignancy. Therefore, this suggests that clinicians should regularly screen for ECEH in such high-risk women. In other respects, we found that the comparative body size at the age of 10 has a positive causal relationship with both ECEH and ECNEH. Obesity is a known high-risk factor for EC [ 16 ]. This study shifted the obesity-related risk window for EC from adulthood to childhood, indicating that obesity exposure in early life has its own independent carcinogenic potential. Children are a critical period for fat tissue development, and obesity at this stage leads to an irreversible increase in the number of fat cells, resulting in poorer metabolic health and a greater tendency towards obesity in adulthood. As a systemic chronic low-grade inflammatory state, childhood obesity means that the carcinogenic inflammatory environment has already been initiated, and there is a greater probability of developing EC. Moreover, both EC subtypes are causally affected, meaning that childhood obesity can act through both the classical estrogen pathway and non-estrogen-dependent pathways. All of these emphasize the necessity of weight management in children for preventing the occurrence of future EC. We also found that Parental longevity (the attained age of the mother) has an inverse causal relationship with ECEH and ECNEH, while Parental longevity (the attained age of the father) does not have such a causal connection. That is, only the genetic prediction of the mother's longevity shows a robust protective effect on the risks of both EC subtypes. Previous studies have found that parental longevity can reduce the all-cause mortality risk of children [ 35 ]. At the same time, the offspring of long-lived parents have a lower cancer rate [ 36 ]. However, these studies are limited to observational studies. This study provides reliable genetic causal evidence for these associations through MR analysis methods. It is well known that longevity is closely related to DNA damage repair ability, telomere length maintenance, etc. [ 37 ]. In this study, only the mother's longevity can reduce the risk of EC in the offspring, possibly because the daughter inherits the long-lived allele with strong DNA repair ability on the mother's X chromosome, thereby reducing the risk of EC. Mitochondrial DNA inheritance may also play a role, providing a microenvironment with low oxidative stress for endometrial cells, thereby reducing the risk of cell carcinogenesis. These remind us that when assessing the risk of female EC, the mother's lifespan should be regarded as a family history indicator with much more information value than the father's lifespan, that is, women with a clear maternal longevity family history may have a lower baseline risk of EC. At the same time, we are reminded that subsequent related studies should prioritize the search for genetic variations related to longevity and cancer protection on the X chromosome and mitochondrial genome. Limitations This study has several limitations that warrant consideration. First, all exposure and outcome data were sourced from the IEU OpenGWAS database. Although we employed methods such as MR-RAPS, MR-PRESSO, and MR-Egger to assess and mitigate potential bias arising from sample overlap, the possibility of residual bias cannot be entirely ruled out. Furthermore, the lack of access to GWAS data from external independent databases currently precludes external validation, which limits the generalizability of our findings. Second, inherent limitations of using summary-level data from public databases may affect our results. These include potential inconsistencies in phenotype definitions across studies and the presence of unmeasured or residual confounding factors that cannot be fully evaluated within the MR framework. Therefore, future studies combining data from multiple large-scale databases are needed to enhance the robustness of these findings. Ultimately, causal inference would be strengthened by validation through well-designed randomized controlled trials. Conclusion This two-sample Mendelian randomization study provides novel genetic evidence supporting potential causal roles for ten exposure factors in the development of endometrial cancer histological subtypes. Our findings suggest that future risk stratification models and preventive strategies could benefit from distinguishing between non-modifiable factors (which may inform targeted screening) and modifiable factors (which may present opportunities for intervention). Further research is required to evaluate the clinical utility and feasibility of these approaches. Declarations Funding This work was supported by Scientific Research Program Project of Health Industry in Gansu Province (No. GSWSKY2021-027). Clinical trial number Not available. Ethics approval and consent to participate Not available. Consent for publication All authors reviewed and approved the final manuscript. Competing interests The authors declare no competing interests. Author Contributions Yucun Wang: Design research plans and provide guidance for the revision of key contents of the article. Jing Cui, Bozhou Cui: Responsible for statistical analysis, chart presentation and article writing. Jie Yang, Yan Ding, Feixia Li: Assist in statistical analysis, check spelling and grammar. Tuoyang Hu, Jiaojiao Zhu, Xiaoying Chang: Provide critical revisions. Jing Cui, Bozhou Cui, Yucun Wang:Responsible for the original data in the research, all authors have decided to submit for publication. Data sharing statement: Statistical analysis data and research results can be provided to researchers through the first author or corresponding author. This data will be retained for five years after the article is published. Acknowledgments: no. References Clarke, M.A., et al., Association of Endometrial Cancer Risk With Postmenopausal Bleeding in Women: A Systematic Review and Meta-analysis. JAMA Intern Med, 2018. 178(9): p. 1210-1222. Crosbie, E.J., et al., Endometrial cancer. Lancet, 2022. 399(10333): p. 1412-1428. E, F., et al., - Alcohol intake and endometrial cancer risk: a meta-analysis of prospective. - Br J Cancer. 2010 Jun 29;103(1):127-31. doi: 10.1038/sj.bjc.6605698. Epub 2010, (- 1532-1827 (Electronic)): p. - 127-31. Glubb, D.M., X. Wang, and T.A. O'Mara, Independent Effects of Hypothyroidism and Obesity on Endometrial Cancer Risk Revealed by Mendelian Randomisation. Biomedicines, 2025. 13(7). Tong, Y., et al., Causal impact of obesity class stratification and endometrial cancer subtypes: an integrated Mendelian randomization and Global Burden of Disease Study 2021 analysis. Int J Surg, 2025. 111(10): p. 6783-6801. Fan, J., et al., Estrogen Promotes Endometrial Cancer Development by Modulating ZNF626, SLK, and RFWD3 Gene Expression and Inducing Immune Inflammatory Changes. Biomedicines, 2025. 13(2). Johansson, Å., et al., Investigating the Effect of Estradiol Levels on the Risk of Breast, Endometrial, and Ovarian Cancer. J Endocr Soc, 2022. 6(8): p. bvac100. Farina, S., et al., Environment, lifestyle, and cancer in women. Int J Gynaecol Obstet, 2025. 171 Suppl 1(Suppl 1): p. 138-146. Yao, X., et al., Causal Relationship between Gut Microbiota and Endometrial Cancer: A Two-Sample Mendelian Randomization Study. Int J Med Sci, 2025. 22(12): p. 3142-3153. Gao, Y., et al., Fertility-sparing treatment for patients with endometrial cancer: a bibliometric analysis from 2000 to 2024. Front Oncol, 2025. 15: p. 1567806. Bokhman, J.V., Two pathogenetic types of endometrial carcinoma. Gynecol Oncol, 1983. 15(1): p. 10-7. Davies, N.M., M.V. Holmes, and G. Davey Smith, Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. Bmj, 2018. 362: p. k601. Chang, L., G. Zhou, and J. Xia, mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations. Metabolites, 2023. 13(7). Hernandez, A.V., et al., Insulin resistance and endometrial cancer risk: A systematic review and meta-analysis. Eur J Cancer, 2015. 51(18): p. 2747-58. Santos Fortes Dos Reis, V.M., et al., Effects of Metformin Treatment Against Endometrial Cancer Cells Cultured In Vitro or Grafted into Female Balb/C Nude Mice: Insights into Cell Response and IGF-1R and PI3K/AKT/mTOR Signaling Pathways. Cell Biochem Biophys, 2025. Hazelwood, E., et al., Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis. BMC Med, 2022. 20(1): p. 125. Zheng, H.T., et al., Circulating inflammatory markers and risk of endometrial cancer: A systematic review and meta-analysis. Cancer Epidemiol, 2024. 93: p. 102662. Yu, K., et al., Estrogen Receptor Function: Impact on the Human Endometrium. Front Endocrinol (Lausanne), 2022. 13: p. 827724. Habeshian, T.S., et al., Hypertension and Risk of Endometrial Cancer: A Pooled Analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2). Cancer Epidemiol Biomarkers Prev, 2024. 33(6): p. 788-795. Liao, Y., et al., Transient high salt intake causes epigenetic changes and leads to persistent inflammatory activation to produce "salt memory". J Nutr Biochem, 2023. 115: p. 109281. Friberg, E., et al., Alcohol intake and endometrial cancer risk: a meta-analysis of prospective studies. Br J Cancer, 2010. 103(1): p. 127-31. Je, Y., I. De Vivo, and E. Giovannucci, Long-term alcohol intake and risk of endometrial cancer in the Nurses' Health Study, 1980-2010. Br J Cancer, 2014. 111(1): p. 186-94. Zhou, Q., et al., Does alcohol consumption modify the risk of endometrial cancer? A dose-response meta-analysis of prospective studies. Arch Gynecol Obstet, 2017. 295(2): p. 467-479. Rumgay, H., et al., Alcohol and Cancer: Epidemiology and Biological Mechanisms. Nutrients, 2021. 13(9). Wynne, J.L. and P.B. Wilson, Got Beer? A Systematic Review of Beer and Exercise. Int J Sport Nutr Exerc Metab, 2021. 31(5): p. 438-450. Baker, J.M., L. Al-Nakkash, and M.M. Herbst-Kralovetz, Estrogen-gut microbiome axis: Physiological and clinical implications. Maturitas, 2017. 103: p. 45-53. Liu, X., et al., Sex-specific association of visceral and abdominal subcutaneous adipose tissue with gastroesophageal reflux disease: a large-scale perspective cohort study. BMC Gastroenterol, 2025. 25(1): p. 635. Guo, C., et al., Novel Metabolic-Prognostic Integration Reveals TCF21-Mediated Mitochondrial Regulation in Endometrial Cancer. Mol Carcinog, 2025. 64(12): p. 1981-1999. Altomare, A., et al., Gastroesophageal reflux disease: Update on inflammation and symptom perception. World J Gastroenterol, 2013. 19(39): p. 6523-8. Trigo, M., et al., Association of repeated endoscopic inflammation with dysplasia and colorectal cancer in ulcerative colitis. Rev Esp Enferm Dig, 2025. Stodden, G.R., et al., Loss of Cdh1 and Trp53 in the uterus induces chronic inflammation with modification of tumor microenvironment. Oncogene, 2015. 34(19): p. 2471-82. Bakhtiari, S. and M. Rostami-Nejad, Emerging markers in celiac disease. Adv Clin Chem, 2025. 129: p. 123-189. Lara, L.A.S. and C.H.N. Abdo, Age at Time of Initial Sexual Intercourse and Health of Adolescent Girls. J Pediatr Adolesc Gynecol, 2016. 29(5): p. 417-423. Wang, S., et al., Menstrual cycle characteristics and incident cancer: a prospective cohort study. Hum Reprod, 2022. 37(2): p. 341-351. Thalén, A. and A. Ledberg, Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort. BMC Geriatr, 2024. 24(1): p. 207. Del Risco Kollerud, R., et al., The risk of cancer in the offspring and parental length of life. Cancer Epidemiol, 2017. 48: p. 8-15. Meyer, D.H., A.A. Maklakov, and B. Schumacher, Aging by the clock and yet without a program. Nat Aging, 2025. 5(10): p. 1946-1956. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx SupplementaryS1.xlsx SupplementaryS2.xlsx SupplementaryS3.xlsx SupplementaryS4.xlsx SupplementaryFile1.docx SupplementaryFigure1.tif SupplementaryFigure2.tif SupplementaryFigure3.tif SupplementaryFigure4.tif Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 13 Jan, 2026 Editor assigned by journal 13 Jan, 2026 Editor invited by journal 19 Dec, 2025 Submission checks completed at journal 18 Dec, 2025 First submitted to journal 18 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8340876","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":575178964,"identity":"6d54afec-89fb-4728-b959-9492963976cb","order_by":0,"name":"Jing Cui","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Cui","suffix":""},{"id":575178965,"identity":"7351acec-5c6a-44c8-8fdb-9352c003a90a","order_by":1,"name":"Bozhou Cui","email":"","orcid":"","institution":"Tangdu Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bozhou","middleName":"","lastName":"Cui","suffix":""},{"id":575178966,"identity":"36e8c8d5-8747-467b-8383-376dfea94e6b","order_by":2,"name":"Jie Yang","email":"","orcid":"","institution":"Gansu Provincial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Yang","suffix":""},{"id":575178968,"identity":"eb0f0e60-ebd3-4aec-84d4-7c01dd2819f5","order_by":3,"name":"Yan Ding","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ding","suffix":""},{"id":575178969,"identity":"f2a5d4bf-96f0-4ee2-a814-528f72f6cb21","order_by":4,"name":"Feixia Li","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Feixia","middleName":"","lastName":"Li","suffix":""},{"id":575178970,"identity":"8d229756-80ee-42dd-b8ae-3cf94d065d75","order_by":5,"name":"Tuoyang Hu","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Tuoyang","middleName":"","lastName":"Hu","suffix":""},{"id":575178971,"identity":"6235ad47-8a9f-411b-920a-5b483036dca1","order_by":6,"name":"Jiaojiao Zhu","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Jiaojiao","middleName":"","lastName":"Zhu","suffix":""},{"id":575178972,"identity":"c4d2db85-8c98-4a1d-b99b-680aff09d19c","order_by":7,"name":"Xiaoying Chang","email":"","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":false,"prefix":"","firstName":"Xiaoying","middleName":"","lastName":"Chang","suffix":""},{"id":575178974,"identity":"6164b1a7-bec7-4737-8840-92483f56f298","order_by":8,"name":"Yucun Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3RPQrCMBTA8ZZAXJ64xg88QyQQFAWvUhE6RU9Q1KmT6AU8hOAFhOBzUVy7OXS0gy7ipLbdXGpGwfyXZHg/yCOOY7P9YHybH71mheQ31jAlvqiGXk7AlOjBGnPiGJD9UV8gIO4GCdaioA1OSe/WRUQexn4XkBKJdCgUpg8D348KyVZJUZ4Bled5K1Y0JQxkMTklGWEgQuBaPQ1IP1IiLs844xRa8Sg0IJ0oke4KPc6yXUYLBvTbLvykxDUJXtNlSLCu7pNmpaSxkKTR2sdf0C/jWeT2MJiy2Wy2P+4NACFGmtCNlXgAAAAASUVORK5CYII=","orcid":"","institution":"Cancer Hospital of Gansu Province","correspondingAuthor":true,"prefix":"","firstName":"Yucun","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-12-12 02:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8340876/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8340876/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100425840,"identity":"9f515363-6b19-489c-9454-ea6214ac3dad","added_by":"auto","created_at":"2026-01-16 14:19:00","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2072356,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptCleanVersion.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/e360e72bd6e4b9855411723d.docx"},{"id":100426296,"identity":"37fe05bb-afbd-4632-9c68-f1f844672360","added_by":"auto","created_at":"2026-01-16 14:19:17","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10408,"visible":true,"origin":"","legend":"","description":"","filename":"e4dc01d91376446f87c2cf356d8b7017.json","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/e4d1413fe467cf92608883f1.json"},{"id":100425845,"identity":"f98d62e0-ae39-422b-b65a-89c741b7ffb5","added_by":"auto","created_at":"2026-01-16 14:19:01","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2397832,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/66b2e220ea5df2d0898ef9ff.tif"},{"id":100426156,"identity":"d97859d3-319d-4b3c-bfcb-acd02e9c0008","added_by":"auto","created_at":"2026-01-16 14:19:13","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3525900,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/46191c73174abf037d4c84d6.tif"},{"id":100426035,"identity":"5f06f15b-54f8-4505-8a1f-9cdb315a5c1c","added_by":"auto","created_at":"2026-01-16 14:19:10","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3591092,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/d006bf040a2fde6a70dfd1de.tif"},{"id":100546568,"identity":"b95ae082-c31b-49bd-910d-7776e7fa02d5","added_by":"auto","created_at":"2026-01-19 08:10:51","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3676756,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/e007626885650a8ebbc85e09.tif"},{"id":100546886,"identity":"364afb59-4b32-4729-b2df-b4047610c7a9","added_by":"auto","created_at":"2026-01-19 08:13:03","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":120130,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/0c8ff8ec16f02e2d1cf1584a.docx"},{"id":100425941,"identity":"e5664dee-a9fb-4190-b544-7d73bacf49d5","added_by":"auto","created_at":"2026-01-16 14:19:06","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12071,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/0e669647cf0b3f8e8162532b.xlsx"},{"id":100425830,"identity":"ce22bc60-637e-4027-8a29-18ba35ad6e4c","added_by":"auto","created_at":"2026-01-16 14:18:58","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":41788,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/294c9029eab39623c58a0936.xlsx"},{"id":100546421,"identity":"8dd83d09-cfa0-4ca4-b094-2b42e94bfe89","added_by":"auto","created_at":"2026-01-19 08:08:23","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110681,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/8f7271db254116e5155ae9f2.xlsx"},{"id":100425937,"identity":"605bb848-bbd6-49f1-92c8-53c470303c53","added_by":"auto","created_at":"2026-01-16 14:19:06","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11310,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/0f3e24c678ea5b7faab1dd7b.xlsx"},{"id":100426298,"identity":"21c9aff3-39ba-4596-8d78-7db3b0231438","added_by":"auto","created_at":"2026-01-16 14:19:17","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51980,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/b473c5e7b09830bae0d4aac9.docx"},{"id":100425846,"identity":"ce43438c-eb85-423d-8c96-f1d4e88789ce","added_by":"auto","created_at":"2026-01-16 14:19:01","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":118830,"visible":true,"origin":"","legend":"","description":"","filename":"e4dc01d91376446f87c2cf356d8b70171enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/3433a9d3081971c83ce19b34.xml"},{"id":100426153,"identity":"b4e625b3-7326-4b6a-9c58-67372ed55f6f","added_by":"auto","created_at":"2026-01-16 14:19:13","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":294858,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/b6a91df8685cbb3979a36ac9.jpeg"},{"id":100426018,"identity":"2d7a6e35-84e4-41e8-a61b-669adb1bf00f","added_by":"auto","created_at":"2026-01-16 14:19:09","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":167014,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/3143985c48751dc4a912bdfb.png"},{"id":100426144,"identity":"55acf4fa-fe14-4d09-be25-bf0bd1f4c55b","added_by":"auto","created_at":"2026-01-16 14:19:12","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":168000,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/cfd2fb35143c5f95ca831f37.png"},{"id":100426023,"identity":"89f1552c-a9fa-45c9-8fb9-ba0afe502f67","added_by":"auto","created_at":"2026-01-16 14:19:09","extension":"jpeg","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":271092,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/c79bf3f02d2eb2be8300f737.jpeg"},{"id":100425844,"identity":"dc195700-9fad-493b-890d-e726f91b8996","added_by":"auto","created_at":"2026-01-16 14:19:00","extension":"jpeg","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":521316,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/964b709ec76ec943d9860c20.jpeg"},{"id":100426151,"identity":"99852d1e-3df3-443b-96d1-80864b8937b6","added_by":"auto","created_at":"2026-01-16 14:19:13","extension":"jpeg","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":483896,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/a2df59ac9c5a91e2d0579beb.jpeg"},{"id":100426089,"identity":"3e46aef1-f923-4e7b-aa94-1811f89f9542","added_by":"auto","created_at":"2026-01-16 14:19:12","extension":"jpeg","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":496156,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/b331e1a06de6395bf4276a5f.jpeg"},{"id":100425861,"identity":"bb46529e-d937-47d8-8098-9d2e62180de4","added_by":"auto","created_at":"2026-01-16 14:19:03","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":49972,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/8a7f76849a94f5dd249aa210.png"},{"id":100426038,"identity":"c6e1bdeb-614e-4acc-a68a-e30349877387","added_by":"auto","created_at":"2026-01-16 14:19:10","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161214,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/34fbc7c55325c4f1d2f0cea9.png"},{"id":100425866,"identity":"d4ed4c19-62c0-4348-8a36-4654ea83f65c","added_by":"auto","created_at":"2026-01-16 14:19:03","extension":"png","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162179,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/101b441ae97cffbd27045a30.png"},{"id":100426240,"identity":"d625fb72-d14e-4e09-9ca6-9bfd64d130e0","added_by":"auto","created_at":"2026-01-16 14:19:15","extension":"png","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":33209,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/66f2434b4ad79f0461133b9b.png"},{"id":100426188,"identity":"e13904ac-47d2-4e60-9f92-2bae3f3c7a42","added_by":"auto","created_at":"2026-01-16 14:19:14","extension":"png","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":104952,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/568725ca9d71ad682906b708.png"},{"id":100426082,"identity":"52d4b0fb-5181-4dee-bf95-82b79198aef3","added_by":"auto","created_at":"2026-01-16 14:19:11","extension":"png","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101324,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/b36f44230384e5444a397c41.png"},{"id":100425858,"identity":"77573613-0dbb-46d8-a37b-88f96a32e76c","added_by":"auto","created_at":"2026-01-16 14:19:02","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":63680,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/2ae0349601fd2923c1d2db76.png"},{"id":100425874,"identity":"104491ad-f098-4e76-ace6-5b9fc68fb6b1","added_by":"auto","created_at":"2026-01-16 14:19:04","extension":"xml","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117267,"visible":true,"origin":"","legend":"","description":"","filename":"e4dc01d91376446f87c2cf356d8b70171structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/520a8b2662953f7058da800a.xml"},{"id":100425951,"identity":"7478f153-92f1-4986-9f55-e6f23646675f","added_by":"auto","created_at":"2026-01-16 14:19:07","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126861,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/ccd285965e2923a1f1cc2733.html"},{"id":100426074,"identity":"da976150-00df-4011-aafd-674d8b2a5096","added_by":"auto","created_at":"2026-01-16 14:19:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":151395,"visible":true,"origin":"","legend":"\u003cp\u003eSummary plot of MR Analysis performed between exposure factors and endometrial cancer\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/a756ad6bc160b7fe311d7120.png"},{"id":100426017,"identity":"41aafa5a-11ee-493d-ae92-8b16c26b0de7","added_by":"auto","created_at":"2026-01-16 14:19:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":287931,"visible":true,"origin":"","legend":"\u003cp\u003eThe causal relationship between exposure factors and endometrial cancer using IVW method.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/0aba66cd9a5cf166b6e4dbca.png"},{"id":100425852,"identity":"3a49445a-64f0-4146-b588-dcc8358eb26e","added_by":"auto","created_at":"2026-01-16 14:19:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":294717,"visible":true,"origin":"","legend":"\u003cp\u003eThe causal relationship between exposure factors and endometrial cancer using RAPS method.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/8e5d779d4c06e83e656751e1.png"},{"id":100426293,"identity":"4ac87508-6a46-439b-84ea-2b82d075e927","added_by":"auto","created_at":"2026-01-16 14:19:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":68242,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative funnel plots.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/599af52e7e2c5ca22ba910e1.png"},{"id":100426191,"identity":"3eec2c1a-6f2f-48ba-b7f5-b9a88e9d9257","added_by":"auto","created_at":"2026-01-16 14:19:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":480939,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative forest plots.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/f43fe36cd9b6f3b6f613a102.png"},{"id":100425862,"identity":"477c93d0-9bd4-47b7-9c8b-3fc772025c86","added_by":"auto","created_at":"2026-01-16 14:19:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":457465,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative leave-one-out plots.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/91af1605feb6f4df57813b41.png"},{"id":100426032,"identity":"b8063d8f-667c-49bd-9ff7-c68016e5cd65","added_by":"auto","created_at":"2026-01-16 14:19:10","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":308837,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative scatter plots.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/43ccb2a182f80c63731c2a91.png"},{"id":100554121,"identity":"75da57a7-c637-4387-8baa-8e251450fc17","added_by":"auto","created_at":"2026-01-19 08:38:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2975058,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/1e5c1474-a1bf-431e-ae88-a8a63b17f9e1.pdf"},{"id":100425842,"identity":"977dc3aa-2808-475d-95cd-f4809fa11365","added_by":"auto","created_at":"2026-01-16 14:19:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":51980,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/8352bced53412faf1f558e1c.docx"},{"id":100425967,"identity":"b38f403e-9e6d-49be-be29-a87e19dae791","added_by":"auto","created_at":"2026-01-16 14:19:08","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12071,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/1690de5a6efa760c2fe7cf72.xlsx"},{"id":100425827,"identity":"4f890efd-aed8-41ab-9942-9e0b6255034f","added_by":"auto","created_at":"2026-01-16 14:18:57","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":41788,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/8bfb1ecfd0220b9088f1c289.xlsx"},{"id":100426294,"identity":"5d823382-c5c1-4770-88ff-aa3e542ead35","added_by":"auto","created_at":"2026-01-16 14:19:17","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":110681,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/a477268e23f7aa894049b56b.xlsx"},{"id":100426022,"identity":"6a407d35-fc60-4fec-ae00-9b19b8dea541","added_by":"auto","created_at":"2026-01-16 14:19:09","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":11310,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/4ff05b0da3a6590e24ccca0a.xlsx"},{"id":100425888,"identity":"52df3912-9dc6-4a9b-ae6e-929e8866befb","added_by":"auto","created_at":"2026-01-16 14:19:05","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":120130,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/dccf2cbae2b9e4efd30cd292.docx"},{"id":100426314,"identity":"71ae4e52-70cd-4f37-b1fc-8f4ca7968b92","added_by":"auto","created_at":"2026-01-16 14:19:19","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2397832,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/f62f5cb0c474ebac790bb702.tif"},{"id":100425987,"identity":"42ec0a1e-ea82-440a-8c73-8789d106e7fd","added_by":"auto","created_at":"2026-01-16 14:19:08","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":3525900,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/aa926762a117bc643f2bdcca.tif"},{"id":100426072,"identity":"73d6397f-d3d8-4350-bac2-d8c907b6ea51","added_by":"auto","created_at":"2026-01-16 14:19:11","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":3591092,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/e5871b55e5ff9197814bd7ac.tif"},{"id":100426279,"identity":"78234c87-1786-4307-9efc-f29d82e2987f","added_by":"auto","created_at":"2026-01-16 14:19:16","extension":"tif","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":3676756,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-8340876/v1/97e3a7d935837bc980057a9f.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal effects of multiple exposures on endometrial cancer and its subtypes: A two-sample Mendelian randomized study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEndometrial cancer (EC) is a common gynecological cancer in women, causing over 2% of cancer-related deaths worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In recent years, the incidence of EC has been increasing [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and it is expected to continue to increase significantly in the next decade [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Actively understanding the risk factors related to the occurrence of EC is crucial for preventing its occurrence and reducing the incidence rate.\u003c/p\u003e \u003cp\u003eThe etiology of EC is complex. Previous studies have mostly focused on the risk correlations or causal relationships between metabolic factors [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], estrogen exposure [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and EC, while paying little attention to factors such as lifestyle, gastrointestinal diseases, and reproduction. However, relevant studies [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] suggest that these factors may also play a certain role in the onset of EC, but the causal relationship has not been systematically explored. At the same time, most previous studies have been accustomed to treating overall EC as the research outcome, and rarely specifically exploring the causes of different EC subtypes (Bokhman's type 1/2) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This has led to ongoing disputes between common risk factors and unique risk factors.\u003c/p\u003e \u003cp\u003eMendelian randomization studies are a statistical method that uses genetic variations as instrumental variables for causal relationship analysis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It can effectively avoid interference from external factors, reverse causality, and other confounding factors, and has gradually become the primary choice for causal relationship analysis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we used the two-sample MR analysis method to analyze GWAS data on multiple exposure factors and outcomes to reveal potential causal relationships between various controllable and uncontrollable exposure factors and endometrial cancer and its subtypes. Early intervention of controllable factors and regular screening of high-risk populations containing uncontrollable factors will be beneficial for the prevention and early detection of specific EC subtypes.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design\u003c/h2\u003e \u003cp\u003eThe two-sample MR method was used to analyze the exposure factors that have a causal relationship with EC and its subtypes. The design, implementation and reporting of this study followed the STROBE-MR guidelines, and the complete STROBE-MR checklist was provided as an additional document (Supplementary File 1). A total of 10 exposure factors in multiple aspects were analyzed for their causal relationships with the same outcome (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for details).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Selection of Exposures and Data Source\u003c/h2\u003e \u003cp\u003eBased on previous epidemiological reports and biological pathogenesis, we selected exposure factors covering aspects such as Lifestyle, Gastrointestinal disease, and Reproductive factors to explore the potential causal relationships between these factors and EC and its subtypes. The basis for each exposure selection is detailed in Supplementary Table\u0026nbsp;1. All the GWAS data related to exposure and outcome are sourced from the IEU OpenGWAS database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://opengwas.io/datasets/\u003c/span\u003e\u003cspan address=\"https://opengwas.io/datasets/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, with the data collection ending on November 23, 2025. Among them, the outcomes are \"Endometrial cancer\", and the subtypes are \"Endometrial cancer (endometrioid histology)\" and \"Endometrial cancer (Non-endometrioid histology)\". All GWAS summary statistics used in this study were obtained from published studies and public databases. No specific ethical approval or permission was required to access these data as they are de-identified summary-level data. Ethical approval for the original data collection was obtained in the respective primary studies (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary Excel File S3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the GWAS data used in the MR analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGWAS ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNumber of SNPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariation in diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-b-2909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e460,884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,851,867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt added to food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-b-8121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e462,630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,851,867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage weekly beer plus cider intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-b-5174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e327,634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,851,867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroesophageal reflux disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST90000514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e602,604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,320,781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUlcerative colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eieu-a-973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26,405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,243,971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeliac disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST005523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23,649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97,422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge first had sexual intercourse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-b-6591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e406,457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,851,867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of menstrual cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-a-351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30,245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,894,596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparative body size at age 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eukb-a-34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e331,693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10,894,596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental longevity (father's attained age)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST006701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e415,311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11,489,837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental longevity (mother's attained age)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST006696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e412,937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11,490,494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrial cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST006464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e121,885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,470,555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrial cancer (endometrioid histology)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST006465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54,884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9,464,330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrial cancer (Non-endometrioid histology)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eebi-a-GCST006466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36,677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8,974,630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Selection of SNPs\u003c/h2\u003e \u003cp\u003eTo ensure the stability and statistical efficacy of the exposure factor instrumental variables, a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e was set as the criterion for selecting those significantly associated with the exposure. A strict linkage disequilibrium (LD) aggregation threshold (r2\u0026thinsp;\u0026lt;\u0026thinsp;0.001, within a 10 Mb window) was established. SNPs known to be related to the outcome variable or major confounding factors (p\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) were excluded. The strength of the instrumental variables was evaluated using the F statistic, and SNPs with F\u0026thinsp;\u0026gt;\u0026thinsp;10 were retained to reduce the bias from weak instrumental variables. Before the MR analysis, palindromic SNPs were excluded to ensure the robustness of the results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 MR Analysis\u003c/h2\u003e \u003cp\u003eIn this study, we first employed the inverse variance weighting method (IVW), MR-Egger, weighted median, simple model, and weighted model to analyze the causal relationship between the exposure factors and endometrial cancer and its subtypes. The main purpose was to observe the analysis results of IVW and supplement them with the results obtained from the other four MR analysis methods. Given that both the exposure and the outcome originated from the IEU OpenGWAS database, there might be a horizontal multi-effect of the instrumental variable due to sample overlap, which could lead to false positive or false negative results in the final IVW analysis. Therefore, to minimize the interference caused by potential sample overlap as much as possible, we further used the MR-RAPS method to obtain more robust causal effect estimates. At the same time, the MR-Egger intercept test was used to assess the multi-effect, and if the intercept value was close to 0 and P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, it indicated the absence of horizontal multi-effect. The MR-PRESSO method was used to detect abnormal SNPs, and if such SNPs existed, they were corrected, and the Distortion Test was used to evaluate whether the abnormal SNPs would have a significant impact on the results. Finally, the P values, odds ratios (OR), 95% confidence intervals (CI), and SNPs in the IVW and RAPS analysis results were presented in a forest plot format. The Cochran Q test in MR-Egger and IVW methods was used to evaluate heterogeneity, and if P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, it indicated the absence of heterogeneity. The leave-one-out method was used to evaluate the influence of a single SNP on the causal relationship. A scatter plot was used to visually display the effect of SNPs on the exposure factor (X-axis), EC and subtypes (Y-axis), and a fitting line was used to show whether the causal effect directions of the six MR methods were consistent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003e3. Statistical analysis was conducted using the packages such as TwoSampleMR, ieugwasr, forestploter, and VariantAnnotation in the R software (version 4.4.3).\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Causal influence of exposure factors on EC and its subtypes\u003c/h2\u003e \u003cp\u003eMR method was used to assess evidence for potential causal relationships between 11 exposure factors (such as Lifestyle, Gastrointestinal disease, Reproductive factors) and EC and its subtypes. We mainly observed the analysis results of IVW and RAPS and presented them in the form of forest plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the IVW analysis results, the causal associations between Length of menstrual cycle and EC, and Parental longevity (father's attained age) and ECEH might be falsely positive due to sample overlap, while Variation in diet and EC, Parental longevity (mother's attained age) and ECNEH might be falsely negative due to interference. It is worth noting that in the RAPS analysis results, Variation in diet (OR\u0026thinsp;=\u0026thinsp;5.795, 95% CI 1.110\u0026ndash;30.250, P\u0026thinsp;=\u0026thinsp;0.037), Salt added to food (OR\u0026thinsp;=\u0026thinsp;1.447, 95% CI 1.018\u0026ndash;2.056, P\u0026thinsp;=\u0026thinsp;0.039) had a positive causal relationship with ECEH, while Average weekly beer plus cider intake (OR\u0026thinsp;=\u0026thinsp;0.389, 95% CI 0.157\u0026ndash;0.966, P\u0026thinsp;=\u0026thinsp;0.042) had a negative causal relationship with ECEH. However, these exposure factors did not have causal relationships with ECNEH subtypes. In the gastrointestinal disease aspect, Gastroesophageal reflux disease (GERD) (OR\u0026thinsp;=\u0026thinsp;1.404, 95% CI 1.217\u0026ndash;1.620, P\u0026thinsp;=\u0026thinsp;3.251e-06), Ulcerative colitis (OR\u0026thinsp;=\u0026thinsp;1.034, 95% CI 1.004\u0026ndash;1.064, P\u0026thinsp;=\u0026thinsp;0.026) had a positive causal relationship with ECEH, while Celiac disease (OR\u0026thinsp;=\u0026thinsp;0.955, 95% CI 0.928\u0026ndash;0.982, P\u0026thinsp;=\u0026thinsp;0.001) had a negative correlation with it. At the same time, Ulcerative colitis (OR\u0026thinsp;=\u0026thinsp;1.148, 95% CI 1.064\u0026ndash;1.239, P\u0026thinsp;=\u0026thinsp;3.675e-04) also formed a positive causal relationship with ECNEH. In the reproductive factors aspect, Age first having sexual intercourse (OR\u0026thinsp;=\u0026thinsp;0.761, 95% CI 0.622\u0026ndash;0.931, P\u0026thinsp;=\u0026thinsp;0.008), Length of menstrual cycle (OR\u0026thinsp;=\u0026thinsp;0.668, 95% CI 0.507\u0026ndash;0.881, P\u0026thinsp;=\u0026thinsp;0.004) were negatively correlated with the occurrence of ECEH. In other respects, the comparative body size at the age of 10 has a positive causal relationship with ECEH (OR\u0026thinsp;=\u0026thinsp;2.228, 95% CI 1.733\u0026ndash;2.865, P\u0026thinsp;=\u0026thinsp;4.215e-10) and ECNEH (OR\u0026thinsp;=\u0026thinsp;2.184, 95% CI 1.284\u0026ndash;3.716, P\u0026thinsp;=\u0026thinsp;0.004), while Parental longevity (mother's attained age) has a negative causal relationship with ECEH (OR\u0026thinsp;=\u0026thinsp;0.205, 95% CI 0.082\u0026ndash;0.509, P\u0026thinsp;=\u0026thinsp;0.001) and ECNEH (OR\u0026thinsp;=\u0026thinsp;0.064, 95% CI 0.007\u0026ndash;0.562, P\u0026thinsp;=\u0026thinsp;0.013). Additionally, we conducted supplementary analyses using four other MR methods (see Supplementary Excel File S2 for details).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Characteristics of Selected SNPs\u003c/h2\u003e \u003cp\u003eAfter rigorous screening under specific conditions, SNPs closely related to each exposure factor were obtained. The corresponding summary information is presented in Supplementary Excel File S3. Upon observation, it was found that the F-statistic of all SNPs were greater than 10, with the lowest value being 29.7 and the highest being 832.3. This indicates that there is no possibility of weak instrumental variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Sensitivity and Heterogeneity Analysis\u003c/h2\u003e \u003cp\u003eThe MR-Egger regression and IVW Cochran Q test method were used to evaluate whether there was heterogeneity in the MR analysis results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among them, the exposure factors that were causally related to EC, such as Salt added to food (MR-Egger Q\u0026thinsp;=\u0026thinsp;148.970, P\u0026thinsp;=\u0026thinsp;0.001; IVW Q\u0026thinsp;=\u0026thinsp;149.441, P\u0026thinsp;=\u0026thinsp;0.002), Celiac disease (MR-Egger Q\u0026thinsp;=\u0026thinsp;63.508, P\u0026thinsp;=\u0026thinsp;0.002; IVW Q\u0026thinsp;=\u0026thinsp;64.412, P\u0026thinsp;=\u0026thinsp;0.002), and Comparative body size at age 10 (MR-Egger Q\u0026thinsp;=\u0026thinsp;206.946, p\u0026thinsp;=\u0026thinsp;0.002; IVW Q\u0026thinsp;=\u0026thinsp;210.981, P\u0026thinsp;=\u0026thinsp;0.002), showed heterogeneity. The exposure factors that were causally related to ECEH, such as Variation in diet (MR-Egger Q\u0026thinsp;=\u0026thinsp;23.047, P\u0026thinsp;=\u0026thinsp;0.041), Salt added to food (MR-Egger Q\u0026thinsp;=\u0026thinsp;144.332, P\u0026thinsp;=\u0026thinsp;0.003; IVW Q\u0026thinsp;=\u0026thinsp;144.401, P\u0026thinsp;=\u0026thinsp;0.004), Celiac disease (MR-Egger Q\u0026thinsp;=\u0026thinsp;57.730, p\u0026thinsp;=\u0026thinsp;0.009; IVW Q\u0026thinsp;=\u0026thinsp;57.731, P\u0026thinsp;=\u0026thinsp;0.012), Comparative body size at age 10 (MR-Egger Q\u0026thinsp;=\u0026thinsp;204.650, P\u0026thinsp;=\u0026thinsp;0.003; IVW Q\u0026thinsp;=\u0026thinsp;206.708, P\u0026thinsp;=\u0026thinsp;0.003), and Ulcerative colitis (MR-Egger Q\u0026thinsp;=\u0026thinsp;103.775, P\u0026thinsp;=\u0026thinsp;0.013; IVW Q\u0026thinsp;=\u0026thinsp;104.116, P\u0026thinsp;=\u0026thinsp;0.015), also showed heterogeneity. Other factors did not show significant heterogeneity (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Further observation of the funnel plot revealed that the distribution of SNPs was basically symmetrical (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHeterogeneity test of the exposures from MR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003eHeterogeneity Test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ(DF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP.value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ(DF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP.value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariation in diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt added to food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e149.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e144.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e144.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage weekly beer plus cider intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroesophageal reflux disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e81.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUlcerative colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e76.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e104.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeliac disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge first had sexual intercourse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e202.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e202.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e219.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of menstrual cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparative body size at age 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e206.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e210.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e204.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e206.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e163.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental longevity (mother's attained age)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe MR-PRESSO method was used to conduct a Global Test on all SNPs in the causal relationships, and it was found that there was pleiotropy in the causal relationship analysis between Age first had sexual intercourse and EC, ECEH (EC: P\u0026thinsp;=\u0026thinsp;0.009; ECEH: P\u0026thinsp;=\u0026thinsp;0.008). Abnormal SNPs were identified (EC: rs11030102, rs4873133; ECEH: rs4873133). After correction, the IVW effect size (EC: β = -0.235 vs. original β = -0.243; ECEH: β = -0.283 vs. original β = -0.316) was consistent in direction, and the P values of the Distortion Test were 0.923 and 0.749, respectively. The same significant pleiotropy was found for Comparative body size at age 10 and EC, ECEH (EC: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; ECEH: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the same abnormal SNPs were identified (rs3131934, rs73085586). After correction, the IVW effect size (EC: β\u0026thinsp;=\u0026thinsp;0.662 vs. original β\u0026thinsp;=\u0026thinsp;0.669; ECEH: β\u0026thinsp;=\u0026thinsp;0.762 vs. original β\u0026thinsp;=\u0026thinsp;0.764) was consistent in direction, and the P values of the Distortion Test were 0.951 and 0.990, respectively. The above analysis indicates that all abnormal SNPs do not affect the robustness of the original MR results. After conducting MR-Egger regression intercept analysis on all causal relationships, it was found that the intercept values were close to 0 and the P values were greater than 0.05, indicating no significant horizontal pleiotropy, further confirming the reliability of the MR results (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Excel File S4).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePleiotropy test of the exposures from MR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ePleiotropy Test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP.value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariation in diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt added to food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage weekly beer plus cider intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroesophageal reflux disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUlcerative colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeliac disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.833E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge first had sexual intercourse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of menstrual cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.529E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparative body size at age 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental longevity (mother's attained age)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECNEH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe independent effect of the instrumental variable and the total effect of IVW (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Supplementary Fig.\u0026nbsp;2) were visualized using a forest plot. The results showed that in the causal analysis of exposure factors and EC and subtypes, the confidence intervals of all SNPs overlapped highly and were consistent in direction, indicating low heterogeneity. Sensitivity analysis was conducted using the leave-one-out method, and the forest plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Supplementary Fig.\u0026nbsp;3) showed that after removing any SNP, the effect estimates remained stable, indicating that the analysis results were not dominated by any single SNP. All of these further confirmed the robustness of the MR results. After conducting the analysis of multiplicity and sensitivity, SNPs were used for MR analysis, and the results were presented in the form of scatter plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Supplementary Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eUsing a two-sample Mendelian randomization framework, this study provides novel genetic evidence suggesting potential causal roles for ten exposure factors across lifestyle, gastrointestinal, and reproductive domains in the development of endometrial cancer and its subtypes. To our knowledge, this is the first systematic MR investigation to simultaneously evaluate these diverse factors in relation to EC subtypes. If validated, these findings could inform future research aimed at multidimensional prevention strategies and risk stratification for early detection of specific EC subtypes. Heterogeneity was observed for several exposures (variations in diet, salt added to food, ulcerative colitis, celiac disease, and comparative body size at age 10) as indicated by Cochran\u0026rsquo;s Q test. However, subsequent analyses revealed no significant horizontal pleiotropy (MR-Egger intercept test) and no single influential SNP (leave-one-out analysis). We speculate that the observed heterogeneity might be attributable to unmeasured confounding factors, such as potential gender differences, given that the outcome population (EC patients) is exclusively female while the exposure GWAS were not sex stratified. To account for this heterogeneity, we employed a random-effects IVW model for these analyses. A genetically predicted longer menstrual cycle was associated with an increased risk of the endometrioid subtype (ECEH) but not with overall EC. One plausible explanation is that the overall EC estimate represents a combined effect of both ECEH and non-endometrioid (ECNEH) subtypes, and a null association at the overall level could be due to a dilution effect from the inverse or null association in the ECNEH subgroup. To address the potential bias from sample overlap between the exposure (menstrual cycle length) and outcome GWAS (both sourced from the IEU OpenGWAS project), we utilized the Robust Adjusted Profile Score (RAPS) method. The robustness of all primary findings was further assessed using MR-Egger regression and MR-PRESSO global tests..\u003c/p\u003e \u003cp\u003eIn terms of Lifestyle, we found that variations in diet and salt added to food can increase the risk of ECEH, while average weekly beer and cider intake has a protective effect. Irregular diet, such as intermittent overeating and prolonged fasting, can cause fluctuations in blood sugar, increasing insulin resistance, and the body will secrete more insulin. Insulin, in addition to regulating sugar metabolism, is also an important growth regulatory factor, which can promote significant proliferation of endometrial cells and increase the risk of EC by [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. At the same time, nocturnal eating or high-sugar and high-fat diets are likely to cause accumulation of visceral fat and lead to obesity. Previous studies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] have suggested that obesity is an important risk factor for EC. Fat cells can release various inflammatory factors, among which IL-6, TNF-α, etc. are closely related to the onset of EC [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Moreover, fat cells can also release estrogen, which can stimulate endometrial hyperplasia through nuclear receptor pathways and membrane receptor pathways, promoting the occurrence of ECEH [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, all these emphasize the necessity of adjusting dietary habits and maintaining regular eating for the prevention of ECEH. Salt added to food can increase the risk of ECEH, possibly because long-term high-salt diet is more likely to trigger hypertension, which has been proven as an independent risk factor [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hypertension can cause damage to the vascular endothelium of the endometrium and changes in the local microenvironment, creating conditions for the growth of cancer cells. At the same time, Liao et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found that a brief high-salt diet can cause epigenetic changes and generate continuous inflammatory activation through NF-κB and other signaling pathways, stimulating abnormal endometrial hyperplasia. The influence of alcohol on the risk of EC has always been controversial. A meta-analysis found [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] that alcohol is related to EC in a J-shaped relationship. Drinking less than one cup per day can reduce the risk of EC, while more than two cups can increase the risk of EC. A prospective study involving 68,067 nurses found [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] that moderate drinking can reduce the risk of EC by 22%. Some studies also suggest [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] that alcohol has no relation to the onset of EC. This study from the perspective of genetic prediction found that Average weekly beer and cider intake is negatively correlated with the risk of ECEH, possibly because compared with beer, beer and cider have lower alcohol concentrations, which is consistent with the conclusion that moderate drinking can reduce the risk of EC. Given that 4% of cancers worldwide are caused by alcohol [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], this conclusion should be interpreted with caution and more evidence is needed to confirm it. It is worth noting that the polyphenols contained in beer such as flavonoids and proanthocyanidins [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] have antioxidant and anti-inflammatory effects, which can reduce chronic inflammation and DNA damage in the endometrium. Meanwhile, the probiotic components in apple wine [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] may contain, through influencing the gut microbiota-estrogen axis, regulate endometrial hyperplasia [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This suggests that future research should pay more attention to the potential protective effects of non-alcoholic beer or apple wine components on ECEH.\u003c/p\u003e \u003cp\u003eIn the field of gastrointestinal diseases, this study found a positive causal relationship between gastroesophageal reflux disease (GERD) and endometrial cancer epithelial hyperplasia (ECEH). Obesity is a clear risk factor for GERD [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and the strongest risk factor for ECEH [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The genetic instrumental variables related to GERD in this MR analysis may capture the genetic predisposition that leads to obesity. This genetic predisposition first causes obesity, and obesity then simultaneously becomes a common cause of GERD and ECEH. This study is the first to reveal this causal relationship from a genetic perspective, providing a new perspective for understanding the common causes of these two diseases. In addition, chronic esophageal inflammation caused by GERD itself may lead to a long-term low-level inflammatory state throughout the body [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This inflammatory environment may promote the occurrence and development of ECEH. Although this possibility is low and difficult to be completely distinguished from the inflammation related to obesity, we cannot completely rule out the weak direct contribution of chronic inflammation related to GERD to the risk of ECEH. This requires future experimental research to verify. Ulcerative colitis, as a chronic inflammatory disease, its association with colorectal cancer has been well recognized, but few people have paid attention to its association with gynecological malignancies, especially EC [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This study initially found that ulcerative colitis is positively causally related to ECEH and ECNEH subtypes, providing new research evidence in this direction. The characteristics of ulcerative colitis are intestinal mucosal barrier disruption and immune regulation disorder, leading to persistent, unrelenting local and systemic inflammation. It has become a well-known driver of various cancers. Inflammatory factors in the systemic circulation, such as TNF-a and IL-6, can reach the endometrium and directly promote the proliferation, invasion, and inhibition of apoptosis of endometrial cells through activating NF-kB and other signaling pathways. This inflammatory-driven carcinogenic mechanism is essentially hormone-independent. In ECEH, inflammation works in synergy with the high estrogen environment to accelerate estrogen-dependent cell proliferation. In ECNEH, inflammation plays a more central and independent role, directly driving events such as TP53 mutations, leading to malignant transformation in a low-estrogen environment [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, for women with ulcerative colitis, they should be regarded as high-risk groups for both EC subtypes. This calls for the inclusion of education and monitoring recommendations for EC in the long-term management guidelines for such patients. Celiac disease is an abnormal autoimmune reaction disease triggered by genetic susceptibility individuals consuming gluten [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This study found that celiac disease has an astonishingly negative causal relationship with the risk of ECEH, suggesting that it plays a protective role. The essence of celiac disease is an abnormal Th1 immune response to gluten antigens under HLA-DQ2/DQ8 restriction, and these immune cells may recognize antigen peptides expressed on the surface of ECEH cells, structurally similar to those, through a \"molecular mimicry\" mechanism. This cross-reaction may lead to early immune surveillance of early cancer cells and their clearance at an early stage. In addition, celiac disease patients often experience chronic diarrhea, malnutrition, and weight loss. Given that obesity is a significant risk factor for ECEH (as adipose tissue produces estrogen through aromatase) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the genetic predisposition to celiac disease may lead to persistently lower circulating estrogen levels throughout life, thereby exerting a continuous protective effect.\u003c/p\u003e \u003cp\u003eIn the \"Reproductive Factors\" section, the relationship between \"Age at First Sexual Intercourse\" and ECEH is inversely causal. This means that individuals with a genetic predisposition to having earlier sexual activity have a significantly increased lifetime risk of developing ECEH. Exposure to estrogen is a high-risk factor for ECEH [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. During the sexual behavior process, oxytocin and estrogen are released, and the younger the age of first sexual intercourse, the earlier one is exposed to high levels of estrogen fluctuations. At the same time, early sexual behavior can affect the physical and mental health of teenagers and exacerbate endocrine disorders, leading to abnormal proliferation and apoptosis of the endometrium [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. All of these emphasize the importance of conducting sexual education among teenagers. Previous epidemiological studies have found that irregular menstrual cycles are a high-risk factor for EC [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], but the potential causal relationship has not been explored. In this study, we discovered from a genetic perspective that the \"Length of Menstrual Cycle\" has a negative causal relationship with ECEH, that is, a shorter menstrual cycle is a high-risk factor for ECEH. A shorter menstrual cycle means more frequent follicular development, ovulation, and estrogen fluctuations. Each cycle's estrogen peak will continuously stimulate the proliferation of the endometrium. At the same time, women with a shortened menstrual cycle have an increased number of ovulatory cycles throughout their lifetime, more times of endometrial proliferation and shedding, and more opportunities for cell division or DNA replication errors, increasing the rate of endometrial malignancy. Therefore, this suggests that clinicians should regularly screen for ECEH in such high-risk women.\u003c/p\u003e \u003cp\u003eIn other respects, we found that the comparative body size at the age of 10 has a positive causal relationship with both ECEH and ECNEH. Obesity is a known high-risk factor for EC [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This study shifted the obesity-related risk window for EC from adulthood to childhood, indicating that obesity exposure in early life has its own independent carcinogenic potential. Children are a critical period for fat tissue development, and obesity at this stage leads to an irreversible increase in the number of fat cells, resulting in poorer metabolic health and a greater tendency towards obesity in adulthood. As a systemic chronic low-grade inflammatory state, childhood obesity means that the carcinogenic inflammatory environment has already been initiated, and there is a greater probability of developing EC. Moreover, both EC subtypes are causally affected, meaning that childhood obesity can act through both the classical estrogen pathway and non-estrogen-dependent pathways. All of these emphasize the necessity of weight management in children for preventing the occurrence of future EC.\u003c/p\u003e \u003cp\u003eWe also found that Parental longevity (the attained age of the mother) has an inverse causal relationship with ECEH and ECNEH, while Parental longevity (the attained age of the father) does not have such a causal connection. That is, only the genetic prediction of the mother's longevity shows a robust protective effect on the risks of both EC subtypes. Previous studies have found that parental longevity can reduce the all-cause mortality risk of children [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. At the same time, the offspring of long-lived parents have a lower cancer rate [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, these studies are limited to observational studies. This study provides reliable genetic causal evidence for these associations through MR analysis methods. It is well known that longevity is closely related to DNA damage repair ability, telomere length maintenance, etc. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In this study, only the mother's longevity can reduce the risk of EC in the offspring, possibly because the daughter inherits the long-lived allele with strong DNA repair ability on the mother's X chromosome, thereby reducing the risk of EC. Mitochondrial DNA inheritance may also play a role, providing a microenvironment with low oxidative stress for endometrial cells, thereby reducing the risk of cell carcinogenesis. These remind us that when assessing the risk of female EC, the mother's lifespan should be regarded as a family history indicator with much more information value than the father's lifespan, that is, women with a clear maternal longevity family history may have a lower baseline risk of EC. At the same time, we are reminded that subsequent related studies should prioritize the search for genetic variations related to longevity and cancer protection on the X chromosome and mitochondrial genome.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis study has several limitations that warrant consideration. First, all exposure and outcome data were sourced from the IEU OpenGWAS database. Although we employed methods such as MR-RAPS, MR-PRESSO, and MR-Egger to assess and mitigate potential bias arising from sample overlap, the possibility of residual bias cannot be entirely ruled out. Furthermore, the lack of access to GWAS data from external independent databases currently precludes external validation, which limits the generalizability of our findings. Second, inherent limitations of using summary-level data from public databases may affect our results. These include potential inconsistencies in phenotype definitions across studies and the presence of unmeasured or residual confounding factors that cannot be fully evaluated within the MR framework. Therefore, future studies combining data from multiple large-scale databases are needed to enhance the robustness of these findings. Ultimately, causal inference would be strengthened by validation through well-designed randomized controlled trials.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis two-sample Mendelian randomization study provides novel genetic evidence supporting potential causal roles for ten exposure factors in the development of endometrial cancer histological subtypes. Our findings suggest that future risk stratification models and preventive strategies could benefit from distinguishing between non-modifiable factors (which may inform targeted screening) and modifiable factors (which may present opportunities for intervention). Further research is required to evaluate the clinical utility and feasibility of these approaches.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Scientific Research Program Project of Health Industry in Gansu Province (No. GSWSKY2021-027).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYucun Wang: Design research plans and provide guidance for the revision of key contents of the article. Jing Cui, Bozhou Cui: Responsible for statistical analysis, chart presentation and article writing. Jie Yang, Yan Ding, Feixia Li: Assist in statistical analysis, check spelling and grammar. Tuoyang Hu, Jiaojiao Zhu, Xiaoying Chang: Provide critical revisions. Jing Cui, Bozhou Cui, Yucun Wang:Responsible for the original data in the research, all authors have decided to submit for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing statement:\u0026nbsp;\u003c/strong\u003eStatistical analysis data and research results can be provided to researchers through the first author or corresponding author. This data will be retained for five years after the article is published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments: no.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eClarke, M.A., et al., \u003cem\u003eAssociation of Endometrial Cancer Risk With Postmenopausal Bleeding in Women: A Systematic Review and Meta-analysis.\u003c/em\u003e JAMA Intern Med, 2018. 178(9): p. 1210-1222.\u003c/li\u003e\n\u003cli\u003eCrosbie, E.J., et al., \u003cem\u003eEndometrial cancer.\u003c/em\u003e Lancet, 2022. 399(10333): p. 1412-1428.\u003c/li\u003e\n\u003cli\u003eE, F., et al., \u003cem\u003e- Alcohol intake and endometrial cancer risk: a meta-analysis of prospective.\u003c/em\u003e - Br J Cancer. 2010 Jun 29;103(1):127-31. doi: 10.1038/sj.bjc.6605698. Epub 2010, (- 1532-1827 (Electronic)): p. - 127-31.\u003c/li\u003e\n\u003cli\u003eGlubb, D.M., X. Wang, and T.A. O\u0026apos;Mara, \u003cem\u003eIndependent Effects of Hypothyroidism and Obesity on Endometrial Cancer Risk Revealed by Mendelian Randomisation.\u003c/em\u003e Biomedicines, 2025. 13(7).\u003c/li\u003e\n\u003cli\u003eTong, Y., et al., \u003cem\u003eCausal impact of obesity class stratification and endometrial cancer subtypes: an integrated Mendelian randomization and Global Burden of Disease Study 2021 analysis.\u003c/em\u003e Int J Surg, 2025. 111(10): p. 6783-6801.\u003c/li\u003e\n\u003cli\u003eFan, J., et al., \u003cem\u003eEstrogen Promotes Endometrial Cancer Development by Modulating ZNF626, SLK, and RFWD3 Gene Expression and Inducing Immune Inflammatory Changes.\u003c/em\u003e Biomedicines, 2025. 13(2).\u003c/li\u003e\n\u003cli\u003eJohansson, \u0026Aring;., et al., \u003cem\u003eInvestigating the Effect of Estradiol Levels on the Risk of Breast, Endometrial, and Ovarian Cancer.\u003c/em\u003e J Endocr Soc, 2022. 6(8): p. bvac100.\u003c/li\u003e\n\u003cli\u003eFarina, S., et al., \u003cem\u003eEnvironment, lifestyle, and cancer in women.\u003c/em\u003e Int J Gynaecol Obstet, 2025. 171 Suppl 1(Suppl 1): p. 138-146.\u003c/li\u003e\n\u003cli\u003eYao, X., et al., \u003cem\u003eCausal Relationship between Gut Microbiota and Endometrial Cancer: A Two-Sample Mendelian Randomization Study.\u003c/em\u003e Int J Med Sci, 2025. 22(12): p. 3142-3153.\u003c/li\u003e\n\u003cli\u003eGao, Y., et al., \u003cem\u003eFertility-sparing treatment for patients with endometrial cancer: a bibliometric analysis from 2000 to 2024.\u003c/em\u003e Front Oncol, 2025. 15: p. 1567806.\u003c/li\u003e\n\u003cli\u003eBokhman, J.V., \u003cem\u003eTwo pathogenetic types of endometrial carcinoma.\u003c/em\u003e Gynecol Oncol, 1983. 15(1): p. 10-7.\u003c/li\u003e\n\u003cli\u003eDavies, N.M., M.V. Holmes, and G. Davey Smith, \u003cem\u003eReading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians.\u003c/em\u003e Bmj, 2018. 362: p. k601.\u003c/li\u003e\n\u003cli\u003eChang, L., G. Zhou, and J. Xia, \u003cem\u003emGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations.\u003c/em\u003e Metabolites, 2023. 13(7).\u003c/li\u003e\n\u003cli\u003eHernandez, A.V., et al., \u003cem\u003eInsulin resistance and endometrial cancer risk: A systematic review and meta-analysis.\u003c/em\u003e Eur J Cancer, 2015. 51(18): p. 2747-58.\u003c/li\u003e\n\u003cli\u003eSantos Fortes Dos Reis, V.M., et al., \u003cem\u003eEffects of Metformin Treatment Against Endometrial Cancer Cells Cultured In Vitro or Grafted into Female Balb/C Nude Mice: Insights into Cell Response and IGF-1R and PI3K/AKT/mTOR Signaling Pathways.\u003c/em\u003e Cell Biochem Biophys, 2025.\u003c/li\u003e\n\u003cli\u003eHazelwood, E., et al., \u003cem\u003eIdentifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis.\u003c/em\u003e BMC Med, 2022. 20(1): p. 125.\u003c/li\u003e\n\u003cli\u003eZheng, H.T., et al., \u003cem\u003eCirculating inflammatory markers and risk of endometrial cancer: A systematic review and meta-analysis.\u003c/em\u003e Cancer Epidemiol, 2024. 93: p. 102662.\u003c/li\u003e\n\u003cli\u003eYu, K., et al., \u003cem\u003eEstrogen Receptor Function: Impact on the Human Endometrium.\u003c/em\u003e Front Endocrinol (Lausanne), 2022. 13: p. 827724.\u003c/li\u003e\n\u003cli\u003eHabeshian, T.S., et al., \u003cem\u003eHypertension and Risk of Endometrial Cancer: A Pooled Analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2).\u003c/em\u003e Cancer Epidemiol Biomarkers Prev, 2024. 33(6): p. 788-795.\u003c/li\u003e\n\u003cli\u003eLiao, Y., et al., \u003cem\u003eTransient high salt intake causes epigenetic changes and leads to persistent inflammatory activation to produce \u0026quot;salt memory\u0026quot;.\u003c/em\u003e J Nutr Biochem, 2023. 115: p. 109281.\u003c/li\u003e\n\u003cli\u003eFriberg, E., et al., \u003cem\u003eAlcohol intake and endometrial cancer risk: a meta-analysis of prospective studies.\u003c/em\u003e Br J Cancer, 2010. 103(1): p. 127-31.\u003c/li\u003e\n\u003cli\u003eJe, Y., I. De Vivo, and E. Giovannucci, \u003cem\u003eLong-term alcohol intake and risk of endometrial cancer in the Nurses\u0026apos; Health Study, 1980-2010.\u003c/em\u003e Br J Cancer, 2014. 111(1): p. 186-94.\u003c/li\u003e\n\u003cli\u003eZhou, Q., et al., \u003cem\u003eDoes alcohol consumption modify the risk of endometrial cancer? A dose-response meta-analysis of prospective studies.\u003c/em\u003e Arch Gynecol Obstet, 2017. 295(2): p. 467-479.\u003c/li\u003e\n\u003cli\u003eRumgay, H., et al., \u003cem\u003eAlcohol and Cancer: Epidemiology and Biological Mechanisms.\u003c/em\u003e Nutrients, 2021. 13(9).\u003c/li\u003e\n\u003cli\u003eWynne, J.L. and P.B. Wilson, \u003cem\u003eGot Beer? A Systematic Review of Beer and Exercise.\u003c/em\u003e Int J Sport Nutr Exerc Metab, 2021. 31(5): p. 438-450.\u003c/li\u003e\n\u003cli\u003eBaker, J.M., L. Al-Nakkash, and M.M. Herbst-Kralovetz, \u003cem\u003eEstrogen-gut microbiome axis: Physiological and clinical implications.\u003c/em\u003e Maturitas, 2017. 103: p. 45-53.\u003c/li\u003e\n\u003cli\u003eLiu, X., et al., \u003cem\u003eSex-specific association of visceral and abdominal subcutaneous adipose tissue with gastroesophageal reflux disease: a large-scale perspective cohort study.\u003c/em\u003e BMC Gastroenterol, 2025. 25(1): p. 635.\u003c/li\u003e\n\u003cli\u003eGuo, C., et al., \u003cem\u003eNovel Metabolic-Prognostic Integration Reveals TCF21-Mediated Mitochondrial Regulation in Endometrial Cancer.\u003c/em\u003e Mol Carcinog, 2025. 64(12): p. 1981-1999.\u003c/li\u003e\n\u003cli\u003eAltomare, A., et al., \u003cem\u003eGastroesophageal reflux disease: Update on inflammation and symptom perception.\u003c/em\u003e World J Gastroenterol, 2013. 19(39): p. 6523-8.\u003c/li\u003e\n\u003cli\u003eTrigo, M., et al., \u003cem\u003eAssociation of repeated endoscopic inflammation with dysplasia and colorectal cancer in ulcerative colitis.\u003c/em\u003e Rev Esp Enferm Dig, 2025.\u003c/li\u003e\n\u003cli\u003eStodden, G.R., et al., \u003cem\u003eLoss of Cdh1 and Trp53 in the uterus induces chronic inflammation with modification of tumor microenvironment.\u003c/em\u003e Oncogene, 2015. 34(19): p. 2471-82.\u003c/li\u003e\n\u003cli\u003eBakhtiari, S. and M. Rostami-Nejad, \u003cem\u003eEmerging markers in celiac disease.\u003c/em\u003e Adv Clin Chem, 2025. 129: p. 123-189.\u003c/li\u003e\n\u003cli\u003eLara, L.A.S. and C.H.N. Abdo, \u003cem\u003eAge at Time of Initial Sexual Intercourse and Health of Adolescent Girls.\u003c/em\u003e J Pediatr Adolesc Gynecol, 2016. 29(5): p. 417-423.\u003c/li\u003e\n\u003cli\u003eWang, S., et al., \u003cem\u003eMenstrual cycle characteristics and incident cancer: a prospective cohort study.\u003c/em\u003e Hum Reprod, 2022. 37(2): p. 341-351.\u003c/li\u003e\n\u003cli\u003eThal\u0026eacute;n, A. and A. Ledberg, \u003cem\u003eConsequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort.\u003c/em\u003e BMC Geriatr, 2024. 24(1): p. 207.\u003c/li\u003e\n\u003cli\u003eDel Risco Kollerud, R., et al., \u003cem\u003eThe risk of cancer in the offspring and parental length of life.\u003c/em\u003e Cancer Epidemiol, 2017. 48: p. 8-15.\u003c/li\u003e\n\u003cli\u003eMeyer, D.H., A.A. Maklakov, and B. Schumacher, \u003cem\u003eAging by the clock and yet without a program.\u003c/em\u003e Nat Aging, 2025. 5(10): p. 1946-1956.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"exposure factors, endometrial cancer, mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-8340876/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8340876/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eEndometrial cancer (EC) is a common gynecological tumor in women, with complex causes. Some studies suggest that it is related to lifestyle, gastrointestinal diseases, reproductive factors, etc., but the causal relationship among them remains unclear. This study employed a two-sample Mendelian randomization method to investigate the causal relationship between these factors and EC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e MR Analysis was conducted using publicly available GWAS data. Preliminary analysis was carried out using the IVW method, combined with the RAPS method to enhance robustness, and supplementary analysis was performed using MR-Egger, weighted median, simple mode and weighted mode. Heterogeneity and pleiotropy were evaluated by Cochran Q test, Leave-One-Out method, MR-Egger intercept test and MR-PRESSO method.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Ten exposure factors that constitute a causal relationship with EC and its subtypes were identified from aspects such as Lifestyle, Gastrointestinal disease, and Reproductive factors. Among them, Variation in diet, Salt added to food and Gastroesophageal reflux disease (GERD) were only positively correlated with the risk of endometrioid EC (ECEH). However, Ulcerative colitis and Comparative body size at age 10 were positively correlated with both ECEH and non-endometrioid EC (ECNEH). Furthermore, Average weekly beer plus cider intake, Celiac disease, Age first had sexual intercourse and Length of menstrual cycle were negatively correlated with ECEH only, while Parental longevity (mother's attained age) was negatively correlated with both ECEH and ECNEH.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Our mendelian randomization analysis provides genetic evidence supportive of potential causal roles for ten exposure factors in the development of endometrial cancer subtypes (ECEH and ECNEH). These findings suggest that early screening for populations with relevant risk profiles and targeted interventions for modifiable factors could be considered in future strategies for the subtype-specific prevention and management of endometrial cancer. Further validation in clinical and experimental settings is required.\u003c/p\u003e","manuscriptTitle":"Causal effects of multiple exposures on endometrial cancer and its subtypes: A two-sample Mendelian randomized study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 14:09:00","doi":"10.21203/rs.3.rs-8340876/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-01-13T15:59:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-13T05:06:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-19T07:46:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-18T13:17:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2025-12-18T13:07:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33dc78b6-9806-4d71-95bb-f55ea7205be5","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-16T14:09:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 14:09:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8340876","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8340876","identity":"rs-8340876","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}