Causal Effects of Genetically Predicted Endometriosis on Breast cancer: A Two-Sample Mendelian Randomization Study

Causal Effects of Genetically Predicted Endometriosis on Breast cancer: A Two-Sample Mendelian Randomization 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 Genetically Predicted Endometriosis on Breast cancer: A Two-Sample Mendelian Randomization Study Shuixin Yan, Jiadi Li, Jiafeng Chen, Yan Chen, Yu Qiu, Yuxin Zhou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2742000/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study used a Mendelian randomization (MR) approach to investigate the causal relationship between genetically predicted endometriosis (EMS) and breast cancer risk. A total of 122,977 cases and 105,974 controls were included in the analysis, with gene-level summary data obtained from the Breast Cancer Association Consortium. An inverse variance-weighting approach was applied to assess the causal relationship between EMS and breast cancer risk, and weighted median and MR-Egger regression methods were used to evaluate pleiotropy. Results showed a causal relationship between EMS and a decreased risk of overall breast cancer (odds ratio [OR] = 0.95; 95% CI 0.90–0.99, p = 0.02). Furthermore, EMS was associated with a lower risk for estrogen receptor (ER)-positive breast cancer in a subgroup analysis based on immunohistochemistry type (OR = 0.91; 95% CI 0.86–0.97, p = 0.005). However, there was no causal association between ER-negative breast cancer and survival (OR = 1.00; 95% CI 0.94–1.06, p = 0.89). Pleiotropy was not observed. These findings provide evidence of a relationship between EMS and reduced breast cancer risk in invasive breast cancer overall and specific tissue types, and support the results of a previous observational study. Further research is needed to elucidate the mechanisms underlying this association. mendelian randomization endometriosis breast cancer genetics pleiotropy Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction In 2020, there were approximately 2.3 million new breast cancer cases worldwide, accounting for 11.7% of all new cancer cases. Women have a high mortality rate due to breast cancer (15/10000) 1 . Depending on a woman’s advanced menopausal state and the status of the tumor receptors, breast cancer is a heterogeneous disease. The development of breast cancer is the result of a combination of internal and external factors. Some studies have identified certain risk factors for breast cancer, including age, family history, history of benign breast disease, history of estrogen use, lifestyle, obesity, and fertility 2 . Endometriosis (EMS) is one of the most prevalent diseases in women of childbearing age, with a prevalence of 5–10% 3 . Numerous epidemiological and clinical studies have shown that EMS is estrogen-dependent. Estradiol (E2) has been shown to promote adhesion, invasion, proliferation, apoptosis inhibition, and inflammatory response maintenance in ectopic lesions. Elevated estrogen levels in ectopic lesions in patients with EMS suggest that local estrogen metabolism plays an important role in EMS development 4 . Additionally, extensive epidemiological data indicate that chronic estrogen exposure increases the likelihood of breast cancer 5 . Therefore, whether there is an association between EMS and breast cancer is a question of interest. Previous observational studies have yielded inconsistent results in EMS and breast cancer risk examination, with most showing implied increased risk (standardized incidence ratio, 1.3; 95% confidence interval [CI], 1.1–1.4) 6 . However, in the most recent largest study, international collaboration on breast cancer research reported a recommendation for a reduced risk of invasive breast cancer in women who self-report EMS 7 . The relationship between EMS and breast cancer has not been systematically studied because of potential biases such as confounding factors or reverse causality. Therefore, there is no conclusive evidence that EMS contributes to breast cancer progression. Additional investigations are needed to draw definitive conclusions regarding the causality and biology of these associations. Mendelian randomization (MR) was used to overcome these limitations. This analytical method uses random genetic classification from parents to progeny to evaluate the association between EMS and breast cancer risk. When specific assumptions are met, this approach is largely independent of biases inherent in standard observational studies. A previous study has shown that EMS has a significant genetic component 8 , suggesting that MR may provide a way to examine the EMS-breast cancer relationship. Therefore, we sought to examine this association using information from recent genome-wide association studies (GWAS) on EMS and breast cancer. This study aimed to investigate genetically predicted EMS with the risk of overall breast cancer and cancer by estrogen receptor status (estrogen receptor-positive [ER+] and estrogen receptor-negative [ER−]) using MR methodology. 2 Materials And Methods 2.1 overall study design All data were obtained from published studies approved by the institutional review boards, and informed consent was obtained from the participants of the original study. Therefore, no further sanctions were required. The cause-and-effect relationship between EMS and breast cancer was analyzed using a two-sample MR study (including overall breast cancer and two immunohistochemical subtypes of breast cancer), and single nucleotide polymorphisms (SNPs) were defined as instrumental variables (IVs). The use of SNPs to model randomized controlled trials can help identify causal relationships between exposure characteristics (i.e., EMS) and outcome characteristics (i.e., breast cancer). 2.2 data sources 2.2.1 genetic instrument variants for exposure EMS data were obtained from the FinnGen project (FinnGen), including 2953 EMS cases and 68,969 control participants. The study was approved by the institutional review board, and informed consent was obtained from all participants in the original study. SNPs were selected based on the following criteria: i) SNPs strongly related to EMS with genome-wide significance (p <5×10 -8 ). ii) Independent of each other and to avoid bias owing to linkage disequilibrium (LD), the LD of SNPs related to EMS had to fulfill r² <0.001, with a window size of 10,000 kb. iii) The correlation between IV and exposure factors is typically determined using the F-statistic of the SNPs. In general, IVs with an F-statistic greater than 10 are regarded as unbiased. F-statistic = (β/SE) 2 . 2.2.2 study outcome: breast cancer The samples of participants in our study for genetic analysis were obtained from the Breast Cancer Association Consortium; a total of 122,977 cases and 105,974 controls were utilized, containing 38,197 ER+ cases and 21,468 ER- cases 9. For the Breast Cancer Association Consortium dataset, we recommend that the reader refer to the main GWAS manuscript and its supplementary material for more information on the consent protocols for the respective cohorts. 2.3 statistical analysis It is essential to consider these hypotheses to provide a valid explanation for MR analysis 10 . (i) It is well-established that IVs are strongly related to EMS. (ii) Breast cancer is affected only by IVs due to EMS defects. (iii) No confounding factors were present in the relationship between EMS and breast cancer according to IVs. The results can be affected by genetic variation through a single pathway rather than by separate exposure, namely horizontal pleiotropy, which contradicts the assumptions of MR and may bias the causal estimates. Three different analytical methods were used in the MR analysis to prevent this. Each analysis was based on a different horizontal multiplicity model. The benefit of comparing these three results is that the consistency of the three methods makes the results more credible. The main analysis was performed using an inverse variance-weighting (IVW) approach, which provided the most accurate estimates but assumed that all SNPs were valid IVs. If one SNP does not meet the IVs assumption, the random-defect IVW will be used to generate a bias, which weighs each rate according to its standard error while considering possible heterogeneity. To satisfy the premise of a valid instrumental variable, the weighted median method requires at least 50% SNPs. After sorting the included SNPs based on the weights, we obtained the median of the corresponding distribution function according to the results of our experiments. Additionally, if the genetic instrument does not depend on pleiotropic effects, an effect estimate can be derived from MR-Egger regression. The pleiotropic effect was assessed using MR-Egger's intercept. Furthermore, a directional multiplicative effect cannot be proven if MR-Egger's intercept does not differ dramatically from zero. 2.4 sensitivity analysis Funnel plots can plot a single Wald ratio per SNP to display the directional level pleiotropy of the IVs. Nevertheless, the small number of IVs included makes it difficult to test for horizontal pleiotropy using funnel plots. The causal effect of the funnel plot was approximately symmetrical ( Figure 1 ). Leave-one-out analyses were performed to investigate whether estimates from IVW analyses were biased or dictated by individual SNPs, during meta-analyses that were conducted based on rerun IVW results for the remaining SNPs after omitting one SNP per succession. After removing each SNP, we performed MR analysis again systematically for the remaining SNPs. The results were consistent, indicating a significant causal relationship between the calculated results for all the SNPs ( F igur e 2 ). In MR analysis, the second hypothesis is that SNPs inject results only by modifying the exposure of interest, without other confounding pathways. Directional multidirectionality was examined to obtain the intercept and p-value using MR-Egger regression. No horizontal pleiotropy was observed in the intercept of the MR-Egger regression (p >0.05), further indicating that pleiotropy did not bias the causal effect. Furthermore, in the published GWAS, there was no evidence that the included EMS-associated SNPs were significantly associated with any phenotype except EMS, which indicates that the assumptions of the third MR were not violated. Additionally, we evaluated whether potential confounders 11 (body mass index and smoking) influenced the relativity between genetically 12 predicted EMS and breast cancer. Our results showed that the overall relationship between genetically predicted EMS and potential confounders was not significant ( Table 1 ). Consequently, there was no evidence that the genetic instruments of the five EMS-associated SNPs were significantly associated with any other phenotype on a genome-wide scale, supporting our third MR hypothesis, which is unlikely to be breached in our 10 study ( Table 1 ). The "Two sample MR" (version 0.5.6) software package was applied for MR and sensitivity analysis in R (version 3.6.2). 3 Results 3.1 instrumental variables for EMS The SNPs’ signatures of the EMS are shown in Table 2 . Finally, we selected five SNPs as the IVs. All genetic tools related to EMS were at a genome-wide significance level (p 10). Thus, none of the SNPs was susceptible to IVs. The causal effects of each genetic variant on breast cancer are shown in Figures 3 and 4. 3.2 mendelian randomization analyses for breast cancer We evaluated the causal relationship between EMS levels and breast cancer using IVW, MR-Egger, and weighted median regression (Table 3). Our findings suggest a reduced risk of breast cancer in patients with EMS (OR=0.95; 95% CI 0.90–0.99, p =0.02). Subgroup analysis based on the type of immunohistochemistry showed a higher risk of ER+ breast cancer in patients with EMS (OR=0.91% CI 0.86–0.97, p =0.005), whereas no significant correlation was observed between EMS and ER– breast cancer (OR=1.00; 95% CI 0.94–1.06, p =0.89) ( Table 3 ). 4 Discussion This study evaluated the causal relationship between EMS and breast cancer using a Mendelian randomization approach. We found that each SD increase in EMS predicted a 5.0% decrease in breast cancer risk. The inference still held in the subtype analysis; in patients with ER + breast cancer, each SD increase in EMS predicted a decrease in the risk of breast cancer by 8.1%; however, no causal relationship was observed in ER– patients. In addition, to exclude the possibility that this causal inference received confounding factors, potential confounding factors, such as obesity and smoking, were analyzed. Consequently, we considered that confounding factors did not confound the causal inference. Despite being benign, EMS also has the characteristics of a malignant tumor 13 . Many studies have investigated the relationship between EMS and breast cancer; however, no consistent conclusion has been reached. Some studies have confirmed that EMS increases the risk of breast cancer 14 15,16 . Few studies considered EMS protective against breast cancer 7 , 17 , 18 . Other studies have argued that there is no relationship between EMS and breast cancer 19 20 . The possible selection and detection biases in these studies could significantly hamper the data assessment. For example, the selection of women undergoing endometrial surgery in some studies has led to potential selection bias. Additionally, the choice to use a discharge diagnosis of EMS contributed to detection bias, as only severe cases were included in the study. Selection and detection bias excluded many patients with cancer from the study, which might have led to an inaccurate assessment of EMS developing into breast cancer. Simultaneously, some studies used a self-reported format (telephone callbacks and questionnaires), which may have led to recall bias. The fundamental pathological change in EMS is not proliferation of epithelial cells, but an increase in inflammation and cell survival resulting from apoptosis or diminished differentiation 21 . Inflammatory responses due to overproduction of reactive oxygen species are also present in breast cancer patients 22 . One study reported that women who underwent bilateral oophorectomy with hysterectomy because of EMS experienced a 58% decrease in breast cancer risk. This might be owing to an early interruption of the inflammatory process that could lead to breast cancer risk 23 . The function of estrogen is mediated by two estrogen receptors (ERα and ERβ). Studies on EMS have shown increased levels of ERβ and decreased levels of ERα in endometriotic tissue compared to that in the normal endometrium 24 , 25 . Reduced methylation of CpG islands in the ERβ gene promoter leads to increased expression levels in endometrial stromal cells, whereas hypermethylation silences ERβ expression. ERβ in endometrial stromal cells dominated the ERα promoter and deregulated its activity, which facilitated the suppression of ERα levels, leading to an altered ERβ:ERα ratio in tissues 26 . It was shown that in breast cancer, the expression of ERβ was decreased compared to that in normal tissues, suggesting a protective effect of ERβ against ERα-induced overproliferation 27 . Women diagnosed with EMS in the postmenopausal period have an increased risk of breast cancer. It is possible that a higher Erβ level in women with EMS leads to a better prognosis. Our study also found a protective effect of EMS against ER + breast cancer but not against ER– breast cancer. The consensus among clinicians and researchers is that estrogen increases the risk of laparoscopically visible EMS and associated pelvic pain, and that targeting cyclooxygenase-2 in the estrogen biosynthesis pathway and the prostaglandin pathway decreases or eliminates laparoscopically visible EMS and pelvic pain 28 , 29 . Women younger than 40 years of age had a reduced risk of developing breast cancer when diagnosed with EMS compared with women older than 40 years. The reduced risk among younger women may be because of their exposure to anti-estrogenic drugs. The increased risk in menopausal women may be owing to a common risk factor between postmenopausal EMS and breast cancer 15 . Thus, the use of anti-estrogen drugs in patients with EMS might reduce the risk of breast cancer. It has been shown that when comparing DNA repair capacity (DRC) in both EMS and breast cancer, women with EMS were 10% less likely to have low DRC compared to women without EMS, and those diagnosed with EMS at 38 years of age were 40% less likely to have low DRC. A low DRC is an important risk factor for breast cancer, as reported in the literature and in the same group of women. The mechanisms associated with the protection of breast cancer by EMS and the positive association between EMS and DRC remain largely unknown. Some drugs may also alter DRC, indirectly affecting the risk of breast cancer. As more is known about the molecular similarities between EMS and breast cancer, this knowledge should provide more effective strategies to prevent and treat both conditions 17 . The standardized incidence of in situ breast cancer increased in the 40- to 59-year-old age group; however, patients with EMS aged 40 years or older might undergo breast imaging more frequently than the general population, which could potentially increase the detection and prompt treatment of in situ cancer and thus reduce breast cancer risk 30 . This study has several strengths. The MR analysis was used for the first time to evaluate the causal association between EMS and breast cancer. Since genetic mutations are inherited from the parental generation, they do not receive external environmental influences and are therefore not subject to reverse causality, which is often present in observational studies. Additionally, we excluded the influence of potential confounding factors. Moreover, we derived these data from published GWAS data. The GWAS data contained 2,953 cases and 68,969 controls, which is a large sample size that made our study more convincing. This study also has some limitations. First, our study indicated that EMS reduced the risk of breast cancer and provided more insight into the clinical disease. However, this has limitations in clinical application since one cannot make people with a high risk of breast cancer develop EMS, which would be difficult to achieve and unethical. Second, only a weak protective effect was observed. Third, our study population was limited to European ancestors, and further studies are needed to determine whether this is feasible in other populations. In conclusion, these findings provide evidence of an association between EMS and reduced breast cancer risk, with the strongest correlation observed in ER + breast cancer. These results are in agreement with those of our previous analysis of a large pooled epidemiological study. Further studies are needed to understand the mechanisms underlying this association. Declarations funding This research was funded by the Ningbo Clinical Medical Research Center for Thoracic Malignancies (（2021L002）) and The Fourth Round of Ningbo Medical Key Disciplines Construction Plan (2022-F03). conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. author contributions SY，JL and WW designed the study. SY and JL conducted research. JC , YZ ,YC and YQ analyzed the data. SY and JL wrote this paper. SY1† and JL2† contributed equally to this work and share first authorship. All authors contributed to the article and approved the submitted version. acknowledgments The authors would like to thank all the genetics consortiums for making the GWAS summary data publicly available. ethics statement Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Consent to participate Informed consent was obtained from all individual participants included in the study. Consent to publish Authors are responsible for correctness of the statements provided in the manuscript. See also Authorship Principles. The Editor-in-Chief reserves the right to reject submissions that do not meet the guidelines described in this section. References Sung, H. et al. 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SNP Gene Chr EA OA EAF. β SE p F 1 rs10122243 - 9 T C 0.4116 0.1771 0.0279 2.26E-10 40.29292 2 rs11031005 LOC105376607 11 C T 0.1697 -0.2401 0.0372 1.10E-10 41.658 3 rs1551642 - 4 C T 0.2707 -0.1865 0.0312 2.32E-09 35.73127 4 rs1971256 CCDC170 6 C T 0.2214 0.2217 0.0335 3.58E-11 43.79674 5 rs61778046 CDC42-AS1 1 T G 0.1903 0.2428 0.0353 5.83E-12 47.30946 TABLE 3 | Mendelian randomization estimates of the causality between genetically predicted EMS and breast cancer Outcome IVW method MR-Egger Weighted median method OR (95% CI) p value OR (95% CI) p value OR (95% CI) p value Breast cancer overall 0.95(0.90,0.99) 0.02 0.73(0.56,0.94) 0.10 0.95(0.90,0.99) 0.04 ER-positive breast cancer 0.91(0.86,0.97) 0.005 0.71(0.45,1.12) 0.24 0.91(0.85,0.98) 0.01 ER-negative breast cancer 1.00(0.94,1.06) 0.89 0.75(0.49,1.17) 0.30 1.00(0.92,1.07) 0.99 Additional Declarations No competing interests reported. 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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-2742000","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":187049141,"identity":"8e7dbc8a-02ff-4ece-b555-4977f33cd14d","order_by":0,"name":"Shuixin Yan","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Shuixin","middleName":"","lastName":"Yan","suffix":""},{"id":187049142,"identity":"7a32e36c-7bc6-43e0-bb64-7cf6f89924f7","order_by":1,"name":"Jiadi Li","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Jiadi","middleName":"","lastName":"Li","suffix":""},{"id":187049143,"identity":"1ad750c6-ee9a-43d3-aedb-241ab38a7d0f","order_by":2,"name":"Jiafeng Chen","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Jiafeng","middleName":"","lastName":"Chen","suffix":""},{"id":187049144,"identity":"65d2d310-a70b-4d71-bfad-7efa0b803c46","order_by":3,"name":"Yan Chen","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Chen","suffix":""},{"id":187049145,"identity":"16ab83d6-5cf8-4a92-8be2-e6e51616ff44","order_by":4,"name":"Yu Qiu","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Qiu","suffix":""},{"id":187049146,"identity":"1d8c1e5f-c092-4560-b2b9-9b366d4a2a4f","order_by":5,"name":"Yuxin Zhou","email":"","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Yuxin","middleName":"","lastName":"Zhou","suffix":""},{"id":187049147,"identity":"fde6ecf9-6923-4ba0-af8a-eaabb3b1d50d","order_by":6,"name":"Weizhu Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie3PIQvCQBTA8TcObuVwdTD0M7xxMBSGfpUbg0sT/AimJcFq8yuYtE4PtQjWBcNAsKpYFhbcsrLNZrh/eOn9eDwAne4Pw6QcAhKghGyzB/rD9qRj0tBdTGTYjkBJehbzHPbYGdNGkkZulhWXICbAuY8JAVPtV3XESyOOgt0qElwjvHSASZnWk/HaFraqiOIR3gjYzGsim1xgRYzY6aMypk1kVF4BISpCqANtyOB0f9kiUTwmlLgzlCFt+gWPMnjmheou5+dnlhf+0DLVoZZ8Rn9b1+l0Ot233oP1ULEEcvDrAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Lihuili Hos-pital, Ningbo University","correspondingAuthor":true,"prefix":"","firstName":"Weizhu","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2023-03-27 12:29:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2742000/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2742000/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35000829,"identity":"c5794934-e3f7-47fb-85ff-f8ebb47ddbd8","added_by":"auto","created_at":"2023-03-29 19:12:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70672,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plots to visualize overall heterogeneity of MR estimates for the effect of EMS on breast cancer. IVW indicates inverse-variance weighted; and MR, Mendelian randomization.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/f2545323e51e186d2c2e42ba.jpg"},{"id":35000826,"identity":"7599d799-69e8-4f7f-973d-6936dd41c436","added_by":"auto","created_at":"2023-03-29 19:12:10","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68202,"visible":true,"origin":"","legend":"\u003cp\u003eLeave-one-out plot to visualize causal effect of Cystatin C on total osteoporosis risk when leaving one SNP out.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/45c1e638df3eb9d7c92149f0.jpg"},{"id":35000828,"identity":"768cc9f8-ec59-4ea0-b1f8-670bb31d5429","added_by":"auto","created_at":"2023-03-29 19:12:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":113290,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot to visualize causal effect of EMS on overall breast cancer, ER(+)breast cancer and ER(-) breast cancer risk. The slope of the straight line indicates the magnitude of the causal association. IVW indicates inverse-variance weighted; and MR, Mendelian randomization.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/9aec7103d95fb0bb56c2663e.jpg"},{"id":35000827,"identity":"8c9163f2-f816-4e56-b05d-f3df456396a8","added_by":"auto","created_at":"2023-03-29 19:12:10","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":89908,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots showing beta (±standard error) and p-values of the single-SNP 2SMR analysis between endometriosis and overall breast cancer, ER(+)breast cancer and ER(-) breast cance\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/46b4b052e123ccfe47d5cdc6.jpg"},{"id":35000870,"identity":"2ff076f9-9fb1-42dd-903c-331c6dc61b01","added_by":"auto","created_at":"2023-03-29 19:12:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":533390,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/602df5b8-fb63-40ad-ba98-390a829f7e0f.pdf"},{"id":35000850,"identity":"23283868-7061-44c0-880e-68dd00379a1d","added_by":"auto","created_at":"2023-03-29 19:12:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":478715,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2742000/v1/288e4e07-e50b-41bf-be15-ab68ca4cb17a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal Effects of Genetically Predicted Endometriosis on Breast cancer: A Two-Sample Mendelian Randomization Study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eIn 2020, there were approximately 2.3\u0026nbsp;million new breast cancer cases worldwide, accounting for 11.7% of all new cancer cases. Women have a high mortality rate due to breast cancer (15/10000) \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Depending on a woman\u0026rsquo;s advanced menopausal state and the status of the tumor receptors, breast cancer is a heterogeneous disease. The development of breast cancer is the result of a combination of internal and external factors. Some studies have identified certain risk factors for breast cancer, including age, family history, history of benign breast disease, history of estrogen use, lifestyle, obesity, and fertility \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEndometriosis (EMS) is one of the most prevalent diseases in women of childbearing age, with a prevalence of 5\u0026ndash;10% \u003csup\u003e3\u003c/sup\u003e. Numerous epidemiological and clinical studies have shown that EMS is estrogen-dependent. Estradiol (E2) has been shown to promote adhesion, invasion, proliferation, apoptosis inhibition, and inflammatory response maintenance in ectopic lesions. Elevated estrogen levels in ectopic lesions in patients with EMS suggest that local estrogen metabolism plays an important role in EMS development \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Additionally, extensive epidemiological data indicate that chronic estrogen exposure increases the likelihood of breast cancer \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Therefore, whether there is an association between EMS and breast cancer is a question of interest. Previous observational studies have yielded inconsistent results in EMS and breast cancer risk examination, with most showing implied increased risk (standardized incidence ratio, 1.3; 95% confidence interval [CI], 1.1\u0026ndash;1.4) \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, in the most recent largest study, international collaboration on breast cancer research reported a recommendation for a reduced risk of invasive breast cancer in women who self-report EMS \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The relationship between EMS and breast cancer has not been systematically studied because of potential biases such as confounding factors or reverse causality. Therefore, there is no conclusive evidence that EMS contributes to breast cancer progression. Additional investigations are needed to draw definitive conclusions regarding the causality and biology of these associations.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) was used to overcome these limitations. This analytical method uses random genetic classification from parents to progeny to evaluate the association between EMS and breast cancer risk. When specific assumptions are met, this approach is largely independent of biases inherent in standard observational studies. A previous study has shown that EMS has a significant genetic component \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, suggesting that MR may provide a way to examine the EMS-breast cancer relationship. Therefore, we sought to examine this association using information from recent genome-wide association studies (GWAS) on EMS and breast cancer.\u003c/p\u003e \u003cp\u003eThis study aimed to investigate genetically predicted EMS with the risk of overall breast cancer and cancer by estrogen receptor status (estrogen receptor-positive [ER+] and estrogen receptor-negative [ER\u0026minus;]) using MR methodology.\u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003ch2\u003e2.1 overall study design\u003c/h2\u003e\n\u003cp\u003eAll data were obtained from published studies approved by the institutional review boards, and informed consent was obtained from the participants of the original study. Therefore, no further sanctions were required. The cause-and-effect relationship between EMS and breast cancer was analyzed using a two-sample MR study (including overall breast cancer and two immunohistochemical subtypes of breast cancer), and single nucleotide polymorphisms (SNPs) were defined as instrumental variables (IVs). The use of SNPs to model randomized controlled trials can help identify causal relationships between exposure characteristics (i.e., EMS) and outcome characteristics (i.e., breast cancer).\u003c/p\u003e\n\u003ch2\u003e2.2 data sources\u003c/h2\u003e\n\u003ch3\u003e2.2.1 genetic instrument variants for exposure\u003c/h3\u003e\n\u003cp\u003eEMS data were obtained from the FinnGen project (FinnGen), including 2953 EMS cases and 68,969 control participants. The study was approved by the institutional review board, and informed consent was obtained from all participants in the original study. SNPs were selected based on the following criteria: i) SNPs strongly related to EMS with genome-wide significance (p \u0026lt;5\u0026times;10\u003csup\u003e-8\u003c/sup\u003e). ii) Independent of each other and to avoid bias owing to linkage disequilibrium (LD), the LD of SNPs related to EMS had to fulfill r\u0026sup2; \u0026lt;0.001, with a window size of 10,000 kb. iii) The correlation between IV and exposure factors is typically determined using the F-statistic of the SNPs. In general, IVs with an F-statistic greater than 10 are regarded as unbiased. F-statistic = (\u0026beta;/SE)\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003e2.2.2 study outcome: breast cancer\u003c/h3\u003e\n\u003cp\u003eThe samples of participants in our study for genetic analysis were obtained from the Breast Cancer Association Consortium; a total of 122,977 cases and 105,974 controls were utilized, containing 38,197 ER+ cases and 21,468 ER- cases 9. For the Breast Cancer Association Consortium dataset, we recommend that the reader refer to the main GWAS manuscript and its supplementary material for more information on the consent protocols for the respective cohorts.\u003c/p\u003e\n\u003ch2\u003e2.3 statistical analysis\u003c/h2\u003e\n\u003cp\u003eIt is essential to consider these hypotheses to provide a valid explanation for MR analysis \u003csup\u003e10\u003c/sup\u003e. (i) It is well-established that IVs are strongly related to EMS. (ii) Breast cancer is affected only by IVs due to EMS defects. (iii) No confounding factors were present in the relationship between EMS and breast cancer according to IVs. The results can be affected by genetic variation through a single pathway rather than by separate exposure, namely horizontal pleiotropy, which contradicts the assumptions of MR and may bias the causal estimates. Three different analytical methods were used in the MR analysis to prevent this. Each analysis was based on a different horizontal multiplicity model. The benefit of comparing these three results is that the consistency of the three methods makes the results more credible. The main analysis was performed using an inverse variance-weighting (IVW) approach, which provided the most accurate estimates but assumed that all SNPs were valid IVs. If one SNP does not meet the IVs assumption, the random-defect IVW will be used to generate a bias, which weighs each rate according to its standard error while considering possible heterogeneity. To satisfy the premise of a valid instrumental variable, the weighted median method requires at least 50% SNPs. After sorting the included SNPs based on the weights, we obtained the median of the corresponding distribution function according to the results of our experiments. Additionally, if the genetic instrument does not depend on pleiotropic effects, an effect estimate can be derived from MR-Egger regression. The pleiotropic effect was assessed using MR-Egger's intercept. Furthermore, a directional multiplicative effect cannot be proven if MR-Egger's intercept does not differ dramatically from zero.\u003c/p\u003e\n\u003ch2\u003e2.4 sensitivity analysis\u003c/h2\u003e\n\u003cp\u003eFunnel plots can plot a single Wald ratio per SNP to display the directional level pleiotropy of the IVs. Nevertheless, the small number of IVs included makes it difficult to test for horizontal pleiotropy using funnel plots. The causal effect of the funnel plot was approximately symmetrical (\u003cstrong\u003eFigure 1\u003c/strong\u003e). Leave-one-out analyses were performed to investigate whether estimates from IVW analyses were biased or dictated by individual SNPs, during meta-analyses that were conducted based on rerun IVW results for the remaining SNPs after omitting one SNP per succession. After removing each SNP, we performed MR analysis again systematically for the remaining SNPs. The results were consistent, indicating a significant causal relationship between the calculated results for all the SNPs (\u003cstrong\u003eF\u003c/strong\u003e\u003cstrong\u003eigur\u003c/strong\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003cstrong\u003e 2\u003c/strong\u003e). In MR analysis, the second hypothesis is that SNPs inject results only by modifying the exposure of interest, without other confounding pathways. Directional multidirectionality was examined to obtain the intercept and p-value using MR-Egger regression. No horizontal pleiotropy was observed in the intercept of the MR-Egger regression (p \u0026gt;0.05), further indicating that pleiotropy did not bias the causal effect. Furthermore, in the published GWAS, there was no evidence that the included EMS-associated SNPs were significantly associated with any phenotype except EMS, which indicates that the assumptions of the third MR were not violated. Additionally, we evaluated whether potential confounders \u003csup\u003e11\u003c/sup\u003e (body mass index and smoking) influenced the relativity between genetically \u003csup\u003e12\u003c/sup\u003e predicted EMS and breast cancer. Our results showed that the overall relationship between genetically predicted EMS and potential confounders was not significant (\u003cstrong\u003eTable 1\u003c/strong\u003e). Consequently, there was no evidence that the genetic instruments of the five EMS-associated SNPs were significantly associated with any other phenotype on a genome-wide scale, supporting our third MR hypothesis, which is unlikely to be breached in our \u003csup\u003e10\u003c/sup\u003e study (\u003cstrong\u003eTable 1\u003c/strong\u003e). The \"Two sample MR\" (version 0.5.6) software package was applied for MR and sensitivity analysis in R (version 3.6.2).\u003c/p\u003e"},{"header":"3 Results","content":"\u003ch2\u003e3.1 instrumental variables for EMS\u003c/h2\u003e\n\u003cp\u003eThe SNPs\u0026rsquo; signatures of the EMS are shown in \u003cstrong\u003eTable 2\u003c/strong\u003e. Finally, we selected five SNPs as the IVs. All genetic tools related to EMS were at a genome-wide significance level (p \u0026lt;5\u0026times;10\u0026minus;8, F \u0026gt;10). Thus, none of the SNPs was susceptible to IVs. The causal effects of each genetic variant on breast cancer are shown in \u003cstrong\u003eFigures 3 and 4.\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003e3.2 mendelian randomization analyses for breast cancer\u003c/h2\u003e\n\u003cp\u003eWe evaluated the causal relationship between EMS levels and breast cancer using IVW, MR-Egger, and weighted median regression (Table 3). Our findings suggest a reduced risk of breast cancer in patients with EMS (OR=0.95; 95% CI 0.90\u0026ndash;0.99, p =0.02). Subgroup analysis based on the type of immunohistochemistry showed a higher risk of ER+ breast cancer in patients with EMS (OR=0.91% CI 0.86\u0026ndash;0.97, p =0.005), whereas no significant correlation was observed between EMS and ER\u0026ndash; breast cancer (OR=1.00; 95% CI 0.94\u0026ndash;1.06, p =0.89) (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study evaluated the causal relationship between EMS and breast cancer using a Mendelian randomization approach. We found that each SD increase in EMS predicted a 5.0% decrease in breast cancer risk. The inference still held in the subtype analysis; in patients with ER\u0026thinsp;+\u0026thinsp;breast cancer, each SD increase in EMS predicted a decrease in the risk of breast cancer by 8.1%; however, no causal relationship was observed in ER\u0026ndash; patients. In addition, to exclude the possibility that this causal inference received confounding factors, potential confounding factors, such as obesity and smoking, were analyzed. Consequently, we considered that confounding factors did not confound the causal inference.\u003c/p\u003e\n\u003cp\u003eDespite being benign, EMS also has the characteristics of a malignant tumor \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Many studies have investigated the relationship between EMS and breast cancer; however, no consistent conclusion has been reached. Some studies have confirmed that EMS increases the risk of breast cancer \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e 15,16\u003c/sup\u003e. Few studies considered EMS protective against breast cancer \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Other studies have argued that there is no relationship between EMS and breast cancer \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e 20\u003c/sup\u003e. The possible selection and detection biases in these studies could significantly hamper the data assessment. For example, the selection of women undergoing endometrial surgery in some studies has led to potential selection bias. Additionally, the choice to use a discharge diagnosis of EMS contributed to detection bias, as only severe cases were included in the study. Selection and detection bias excluded many patients with cancer from the study, which might have led to an inaccurate assessment of EMS developing into breast cancer. Simultaneously, some studies used a self-reported format (telephone callbacks and questionnaires), which may have led to recall bias.\u003c/p\u003e\n\u003cp\u003eThe fundamental pathological change in EMS is not proliferation of epithelial cells, but an increase in inflammation and cell survival resulting from apoptosis or diminished differentiation \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Inflammatory responses due to overproduction of reactive oxygen species are also present in breast cancer patients \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. One study reported that women who underwent bilateral oophorectomy with hysterectomy because of EMS experienced a 58% decrease in breast cancer risk. This might be owing to an early interruption of the inflammatory process that could lead to breast cancer risk \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe function of estrogen is mediated by two estrogen receptors (ER\u0026alpha; and ER\u0026beta;). Studies on EMS have shown increased levels of ER\u0026beta; and decreased levels of ER\u0026alpha; in endometriotic tissue compared to that in the normal endometrium \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Reduced methylation of CpG islands in the ER\u0026beta; gene promoter leads to increased expression levels in endometrial stromal cells, whereas hypermethylation silences ER\u0026beta; expression. ER\u0026beta; in endometrial stromal cells dominated the ER\u0026alpha; promoter and deregulated its activity, which facilitated the suppression of ER\u0026alpha; levels, leading to an altered ER\u0026beta;:ER\u0026alpha; ratio in tissues \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. It was shown that in breast cancer, the expression of ER\u0026beta; was decreased compared to that in normal tissues, suggesting a protective effect of ER\u0026beta; against ER\u0026alpha;-induced overproliferation \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Women diagnosed with EMS in the postmenopausal period have an increased risk of breast cancer. It is possible that a higher Er\u0026beta; level in women with EMS leads to a better prognosis. Our study also found a protective effect of EMS against ER\u0026thinsp;+\u0026thinsp;breast cancer but not against ER\u0026ndash; breast cancer.\u003c/p\u003e\n\u003cp\u003eThe consensus among clinicians and researchers is that estrogen increases the risk of laparoscopically visible EMS and associated pelvic pain, and that targeting cyclooxygenase-2 in the estrogen biosynthesis pathway and the prostaglandin pathway decreases or eliminates laparoscopically visible EMS and pelvic pain \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Women younger than 40 years of age had a reduced risk of developing breast cancer when diagnosed with EMS compared with women older than 40 years. The reduced risk among younger women may be because of their exposure to anti-estrogenic drugs. The increased risk in menopausal women may be owing to a common risk factor between postmenopausal EMS and breast cancer \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Thus, the use of anti-estrogen drugs in patients with EMS might reduce the risk of breast cancer.\u003c/p\u003e\n\u003cp\u003eIt has been shown that when comparing DNA repair capacity (DRC) in both EMS and breast cancer, women with EMS were 10% less likely to have low DRC compared to women without EMS, and those diagnosed with EMS at 38 years of age were 40% less likely to have low DRC. A low DRC is an important risk factor for breast cancer, as reported in the literature and in the same group of women. The mechanisms associated with the protection of breast cancer by EMS and the positive association between EMS and DRC remain largely unknown. Some drugs may also alter DRC, indirectly affecting the risk of breast cancer. As more is known about the molecular similarities between EMS and breast cancer, this knowledge should provide more effective strategies to prevent and treat both conditions \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe standardized incidence of in situ breast cancer increased in the 40- to 59-year-old age group; however, patients with EMS aged 40 years or older might undergo breast imaging more frequently than the general population, which could potentially increase the detection and prompt treatment of in situ cancer and thus reduce breast cancer risk \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThis study has several strengths. The MR analysis was used for the first time to evaluate the causal association between EMS and breast cancer. Since genetic mutations are inherited from the parental generation, they do not receive external environmental influences and are therefore not subject to reverse causality, which is often present in observational studies. Additionally, we excluded the influence of potential confounding factors. Moreover, we derived these data from published GWAS data. The GWAS data contained 2,953 cases and 68,969 controls, which is a large sample size that made our study more convincing.\u003c/p\u003e\n\u003cp\u003eThis study also has some limitations. First, our study indicated that EMS reduced the risk of breast cancer and provided more insight into the clinical disease. However, this has limitations in clinical application since one cannot make people with a high risk of breast cancer develop EMS, which would be difficult to achieve and unethical. Second, only a weak protective effect was observed. Third, our study population was limited to European ancestors, and further studies are needed to determine whether this is feasible in other populations.\u003c/p\u003e\n\u003cp\u003eIn conclusion, these findings provide evidence of an association between EMS and reduced breast cancer risk, with the strongest correlation observed in ER\u0026thinsp;+\u0026thinsp;breast cancer. These results are in agreement with those of our previous analysis of a large pooled epidemiological study. Further studies are needed to understand the mechanisms underlying this association.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003efunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Ningbo Clinical Medical Research Center for Thoracic Malignancies (（2021L002）) and The Fourth Round of Ningbo Medical Key Disciplines Construction Plan (2022-F03).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003econflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eauthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSY，JL and WW designed the study. SY and JL conducted research. JC , YZ ,YC and YQ analyzed the data. SY and JL wrote this paper. SY1\u0026dagger; and JL2\u0026dagger; contributed equally to this work and share first authorship. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eacknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the genetics consortiums for making the GWAS summary data publicly available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eethics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors are responsible for correctness of the statements provided in the manuscript. See also Authorship Principles. The Editor-in-Chief reserves the right to reject submissions that do not meet the guidelines described in this section.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung, H. et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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Acta Obstet Gynecol Scand (2019) 98, 1113-1119, doi:10.1111/aogs.13609.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTABLE 1 |\u0026nbsp;\u003c/strong\u003eCausal effects between genetically predicted EMS and confounders and mediators\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003eOutcomes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003eCausal effect(95%CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e\u0026nbsp;P value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003eObesity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.85(0.72,1.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003eDrinking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.93(0.81,1.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.32\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003eSmoke\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.93(0.70,1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"33.333333333333336%\"\u003e\n\u003cp\u003e0.65\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 2\u0026nbsp;\u003c/strong\u003e| List of genetic instruments for EMS and log odds ratios of osteoporosis risk by each instrumental SNPs (GWAS signifificance with p \u0026lt; 5 \u0026times; 10\u0026minus;8 and linkage disequilibrium. threshold with R2 \u0026lt; 0.001).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 4.1894%;\" valign=\"top\" width=\"5.809859154929577%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 14.2077%;\" valign=\"top\" width=\"12.852112676056338%\"\u003e\n\u003cp\u003eSNP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 19.3078%;\" valign=\"top\" width=\"16.549295774647888%\"\u003e\n\u003cp\u003eGene\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.6466%;\" valign=\"top\" width=\"6.161971830985915%\"\u003e\n\u003cp\u003eChr\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 4.918%;\" valign=\"top\" width=\"5.457746478873239%\"\u003e\n\u003cp\u003eEA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.2823%;\" valign=\"top\" width=\"5.633802816901408%\"\u003e\n\u003cp\u003eOA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.9253%;\" valign=\"top\" width=\"9.154929577464788%\"\u003e\n\u003cp\u003eEAF.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 9.2896%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e\u0026beta;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.561%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003eSE\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.3789%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003ep\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 11.2933%;\" valign=\"top\" width=\"10.387323943661972%\"\u003e\n\u003cp\u003eF\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 4.1894%;\" valign=\"top\" width=\"5.809859154929577%\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 14.2077%;\" valign=\"top\" width=\"12.852112676056338%\"\u003e\n\u003cp\u003ers10122243\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 19.3078%;\" valign=\"top\" width=\"16.549295774647888%\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.6466%;\" valign=\"top\" width=\"6.161971830985915%\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 4.918%;\" valign=\"top\" width=\"5.457746478873239%\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.2823%;\" valign=\"top\" width=\"5.633802816901408%\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.9253%;\" valign=\"top\" width=\"9.154929577464788%\"\u003e\n\u003cp\u003e0.4116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 9.2896%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e0.1771\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.561%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e0.0279\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.3789%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e2.26E-10\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 11.2933%;\" valign=\"top\" width=\"10.387323943661972%\"\u003e\n\u003cp\u003e40.29292\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 4.1894%;\" valign=\"top\" width=\"5.809859154929577%\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 14.2077%;\" valign=\"top\" width=\"12.852112676056338%\"\u003e\n\u003cp\u003ers11031005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 19.3078%;\" valign=\"top\" width=\"16.549295774647888%\"\u003e\n\u003cp\u003eLOC105376607\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.6466%;\" valign=\"top\" width=\"6.161971830985915%\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 4.918%;\" valign=\"top\" width=\"5.457746478873239%\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.2823%;\" valign=\"top\" width=\"5.633802816901408%\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.9253%;\" valign=\"top\" width=\"9.154929577464788%\"\u003e\n\u003cp\u003e0.1697\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 9.2896%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e-0.2401\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.561%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e0.0372\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.3789%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e1.10E-10\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 11.2933%;\" valign=\"top\" width=\"10.387323943661972%\"\u003e\n\u003cp\u003e41.658\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 4.1894%;\" valign=\"top\" width=\"5.809859154929577%\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 14.2077%;\" valign=\"top\" width=\"12.852112676056338%\"\u003e\n\u003cp\u003ers1551642\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 19.3078%;\" valign=\"top\" 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width=\"10.387323943661972%\"\u003e\n\u003cp\u003e43.79674\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 4.1894%;\" valign=\"top\" width=\"5.809859154929577%\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 14.2077%;\" valign=\"top\" width=\"12.852112676056338%\"\u003e\n\u003cp\u003ers61778046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 19.3078%;\" valign=\"top\" width=\"16.549295774647888%\"\u003e\n\u003cp\u003eCDC42-AS1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.6466%;\" valign=\"top\" width=\"6.161971830985915%\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 4.918%;\" valign=\"top\" width=\"5.457746478873239%\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 5.2823%;\" valign=\"top\" width=\"5.633802816901408%\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.9253%;\" valign=\"top\" width=\"9.154929577464788%\"\u003e\n\u003cp\u003e0.1903\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 9.2896%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e0.2428\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.561%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e0.0353\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 8.3789%;\" valign=\"top\" width=\"8.450704225352112%\"\u003e\n\u003cp\u003e5.83E-12\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 11.2933%;\" valign=\"top\" width=\"10.387323943661972%\"\u003e\n\u003cp\u003e47.30946\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 3 |\u003c/strong\u003e\u0026nbsp;Mendelian randomization estimates of the causality between genetically predicted EMS and breast cancer\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"2.807017543859649%\"\u003e\n\u003cp\u003eOutcome\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003eIVW method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"9.12280701754386%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"21.403508771929825%\"\u003e\n\u003cp\u003eMR-Egger\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"8.596491228070175%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003eWeighted median method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"10.701754385964913%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"2.807017543859649%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"9.12280701754386%\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"21.403508771929825%\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"8.596491228070175%\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"10.701754385964913%\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"2.807017543859649%\"\u003e\n\u003cp\u003eBreast cancer overall\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.95(0.90,0.99)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"9.12280701754386%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"21.403508771929825%\"\u003e\n\u003cp\u003e0.73(0.56,0.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"8.596491228070175%\"\u003e\n\u003cp\u003e0.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.95(0.90,0.99)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"10.701754385964913%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"2.807017543859649%\"\u003e\n\u003cp\u003eER-positive breast cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.91(0.86,0.97)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"9.12280701754386%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"21.403508771929825%\"\u003e\n\u003cp\u003e0.71(0.45,1.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"8.596491228070175%\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.91(0.85,0.98)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"10.701754385964913%\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd valign=\"top\" width=\"2.807017543859649%\"\u003e\n\u003cp\u003eER-negative breast cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e1.00(0.94,1.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"9.12280701754386%\"\u003e\n\u003cp\u003e0.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"21.403508771929825%\"\u003e\n\u003cp\u003e0.75(0.49,1.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"8.596491228070175%\"\u003e\n\u003cp\u003e0.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"19.82456140350877%\"\u003e\n\u003cp\u003e1.00(0.92,1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd valign=\"top\" width=\"10.701754385964913%\"\u003e\n\u003cp\u003e0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"mendelian randomization, endometriosis, breast cancer, genetics, pleiotropy","lastPublishedDoi":"10.21203/rs.3.rs-2742000/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2742000/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study used a Mendelian randomization (MR) approach to investigate the causal relationship between genetically predicted endometriosis (EMS) and breast cancer risk. A total of 122,977 cases and 105,974 controls were included in the analysis, with gene-level summary data obtained from the Breast Cancer Association Consortium. An inverse variance-weighting approach was applied to assess the causal relationship between EMS and breast cancer risk, and weighted median and MR-Egger regression methods were used to evaluate pleiotropy. Results showed a causal relationship between EMS and a decreased risk of overall breast cancer (odds ratio [OR]\u0026thinsp;=\u0026thinsp;0.95; 95% CI 0.90\u0026ndash;0.99, p\u0026thinsp;=\u0026thinsp;0.02). Furthermore, EMS was associated with a lower risk for estrogen receptor (ER)-positive breast cancer in a subgroup analysis based on immunohistochemistry type (OR\u0026thinsp;=\u0026thinsp;0.91; 95% CI 0.86\u0026ndash;0.97, p\u0026thinsp;=\u0026thinsp;0.005). However, there was no causal association between ER-negative breast cancer and survival (OR\u0026thinsp;=\u0026thinsp;1.00; 95% CI 0.94\u0026ndash;1.06, p\u0026thinsp;=\u0026thinsp;0.89). Pleiotropy was not observed. These findings provide evidence of a relationship between EMS and reduced breast cancer risk in invasive breast cancer overall and specific tissue types, and support the results of a previous observational study. Further research is needed to elucidate the mechanisms underlying this association.\u003c/p\u003e","manuscriptTitle":"Causal Effects of Genetically Predicted Endometriosis on Breast cancer: A Two-Sample Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-29 19:12:05","doi":"10.21203/rs.3.rs-2742000/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2436be02-a0f2-47af-a567-e6c868c32306","owner":[],"postedDate":"March 29th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-29T19:12:08+00:00","versionOfRecord":[],"versionCreatedAt":"2023-03-29 19:12:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2742000","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2742000","identity":"rs-2742000","version":["v1"]},"buildId":"0SHbDDIpRTBOrFPTvp6pu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}