Mendelian randomization study shows no causal effects of polycystic ovarian syndrome on the risk of preeclampsia

Mendelian randomization study shows no causal effects of polycystic ovarian syndrome on the risk of preeclampsia | 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 Mendelian randomization study shows no causal effects of polycystic ovarian syndrome on the risk of preeclampsia Fufen Yin, Xiuju Yin, Junshu Xie, Ye Zhu, Xiaohong Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4010881/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 Background Previous studies have shown an association between polycystic ovary syndrome (PCOS) and the increased risk of developing preeclampsia (PE). However, other studies have not found an independent association between the two. A causal association between PCOS and PE remains unclear. The objective of this study was to determine whether PCOS has a causal relationship with PE. Methods A two-sample Mendelian randomization (MR) analysis was performed by using the inverse‐variance weighted (IVW), weighted median, MR‐Egger regression, simple mode, and weighted mode methods. We used the publicly available summary statistics data sets of genome‐wide association studies (GWAS) meta‐analyses for PCOS (N = 113238) as the exposure and a GWAS for PE (N = 267242) as the outcome. In addition, the heterogeneity, horizontal pleiotropy, and stability were assessed through several sensitivity analyses. Results 13 single nucleotide polymorphisms (SNPs) at genome-wide significance from GWASs on PCOS were selected as the instrumental variables (IVs). The results of all the methods including IVW, weighted median, MR‐Egger regression, simple mode, and weighted mode were consistent and showed no causal association between PCOS and PE ( P > 0.05) Conclusion The results of MR analysis support that PCOS may not be causally associated with an increased risk of PE. We suggest PCOS should not be presently included as a risk factor in obstetrical guidelines and prediction models for PE. To determine whether PCOS and PE are associated, further research is needed. Mendelian randomization Causal relationship Polycystic ovary syndrome Preeclampsia Figures Figure 1 Figure 2 Background Preeclampsia (PE) which complicates 2–8% of all pregnancies globally, is a significant cause of maternal and perinatal morbidity and mortality[ 1 , 2 ]. Polycystic ovary syndrome (PCOS) is reported to be associated with dyslipidemia, insulin resistance, infertility, hypertension, and adverse pregnancy outcomes[ 3 – 5 ]. Previous studies have shown that women with PCOS have a higher risk of developing PE[ 5 – 10 ], but the findings have been inconsistent. Some studies revealed that PCOS was not associated with an increased risk of PE[ 11 – 13 ]. Clinical guidelines outline numerous high and moderate risk factors associated with PE. These factors assist caregivers in determining when to administer aspirin for PE prevention and when to enhance pregnancy monitoring[ 1 , 14 ]. Currently, PCOS is not considered a risk factor for PE in international guidelines[ 15 ]. The current PE guidelines do not align with evidence indicating PCOS is a probable PE risk factor[ 16 ]. There is no robust causal link between PE and PCOS observed in observational studies due to confounding factors and reversals of causal relationships. Therefore, further research is required to establish a robust causal link between PE and PCOS. The Mendelian randomization method (MR) utilizes genetic information to examine causal relationships between exposures and outcomes[ 17 , 18 ]. Random distribution of genetic variants during meiosis enables MR to overcome the limitations of confounding and reverse causality that often plague observational studies[ 19 ]. The objective of this study was to search out whether PCOS is causally related to the risk of PE employing an MR analysis. Materials and methods Study design The causal association between PCOS and PE was conducted by a two-sample MR research. The instrumental variables were selected based on three key principles: (1) genetic variation is robustly correlated with exposure; (2) potential confounding factors are minimally correlated with genetic variation; and (3) the outcomes under investigation are not directly influenced by genetic variation[ 20 ]. This study examined the effect of PCOS on the risk of PE by using MR analysis. Data sources and selection of genetic variants The genome-wide association studies (GWAS) summary statistics for PCOS were obtained from a recent genomewide association meta-analysis study[ 21 ] that included 10,074 individuals diagnosed with PCOS and 103,164 healthy controls. The summary-level GWAS data for PE was from the IEU open GWAS project (ebi-a-GCST90018906)[ 22 ]. This step ensures that SNPs are valid instrument variables (IVs): (i) The SNPs are strongly correlated with exposure and significant with a p -value < 5.0×10 − 8 ; (ii) SNPs are independent of each other to avoid biases caused by linkage disequilibrium (r2 < 0.01 over a 10-kilobase (kb) region based on the European sample of 1000 Genomes data), and (iii) SNPs could impact other than exposure on the outcome. PhenoScanner ( http://www.phenoscanner.medschl.cam.ac.uk/ ) was used to determine whether the selected SNPs were associated with other traits at genome-wide significance levels. F-statistic of the selected SNPs was calculated to test the weak IV bias. The strength of the selected IV would be strong if the F-statistic was > 10[ 23 ]. Statistical methods We used the inverse-variance weighted (IVW) method as the primary analytical method in this MR study, which is an extension of the Wald ratio estimator based on the principles of meta-analysis[ 24 , 25 ]. Results of causal associations were presented as odds ratios (OR) and 95% confidence intervals (95% CI) with a significance threshold of P < 0.05. In addition to the IVW method, four additional MR methods (MR-Egger, weighted median, simple mode, and weighted mode) were also applied to assess causal associations. A series of sensitivity analyses were performed. The Cochran’s Q test was used to assess heterogeneity and the MR-Egger intercept was used to detect horizontal pleiotropy[ 26 , 27 ]. The leave-one-out sensitivity analysis was performed to evaluate the robustness of the results. All analyses in this study were performed based on R software (version 4.2.3) by the “TwoSampleMR” R package[ 28 ]. Tests were considered statistically significant at P < 0.05. Results Selection of genetic instrumental variables 14 independent SNPs with significant p -values < 5.0×10 − 8 were selected from GWASs on PCOS as the IVs (Table 1 ). rs853854 was then removed for being palindromic with intermediate allele frequencies. Finally, according to the above description, 13 SNPs are left for MR analysis after instrument selection and exposure-outcome data harmonization (Table 1 ). With a clumping window of 10,000 kb and linkage disequilibrium (LD) r2 > 0.01, all SNPs passed the test. In this study, all SNPs had an F statistic value greater than 10, and the mean F statistic value was 629.65, indicating low instrument bias risks. Table 1 Instrument single-nucleotide polymorphisms for Mendelian randomization analysis and their effects on PCOS SNP Chromosome Effect allele Other allele β value P value F rs10739076 9 A C 0.11 2.51E-08 583.702 rs11031005 11 T C -0.159 8.66E-13 722.417 rs11225154 11 A G 0.179 5.44E-11 619.919 rs13164856 5 T C 0.124 1.45E-10 686.436 rs1784692 11 T C 0.144 1.88E-10 684.227 rs1795379 12 T C -0.117 1.81E-09 571.935 rs2178575 2 A G 0.166 3.34E-14 809.619 rs2271194 12 A T 0.097 4.57E-09 521.175 rs7563201 2 A G -0.108 3.68E-10 659.043 rs7864171 9 A G -0.093 2.95E-08 484.848 rs804279 8 A T 0.128 3.76E-12 698.068 rs8043701 16 A T -0.127 9.61E-10 556.108 rs853854 20 A T -0.098 2.36E-09 540.831 rs9696009 9 A G 0.202 7.96E-11 587.935 SNP, single-nucleotide polymorphism; PCOS, polycystic ovary syndrome rs853854 was then removed for being palindromic with intermediate allele frequencies Mendelian randomization results The MR estimates of exposure (PCOS) on outcome (PE) are shown in Table 1 . Overall, there was no statistically significant causal effect of PCOS on the PE risk. The primary results of IVW showed that patient with PCOS was not statistically related to an increased risk of having PE (OR = 1.04, 95% CI: 0.84–1.30, P = 0.704). In addition, the MR-Egger, weighted median, simple mode, and weighted mode methods showed consistent results. ( P > 0.05, Table 2 and Fig. 1 ). Table 2 Mendelian randomization results of the causal effect of PCOS on PE Exposure Outcome nSNP Method OR (95% CI) P Heterogeneity test Pleiotropy test Cochran's Q P P Intercept PCOS PE 13 IVW 1.04 (0.84, 1.30) 0.704 25.385 0.01 Weighted median 1.12 (0.89, 1.42) 0.317 MR-Egger 1.71 (0.58, 5.05) 0.353 0.381 Simple mode 1.32 (0.89, 1.97) 0.192 Weighted mode 1.32 (0.91–1.91) 0.173 PCOS, polycystic ovary syndrome; PE, preeclampsia; IVW, inverse-variance weighted Sensitivity analysis and heterogeneity Leave-one-out sensitivity analysis results are shown in Fig. 2 as a forest plot. With one SNP removed, all error bars are on the right side of the zero line, indicating no single SNP was driving the causal link and the conclusion remains stable. The MR-Egger intercept showed no evidence of directional pleiotropy for PCOS ( P = 0.38, Table 1 ). A notable heterogeneity was detected with Cochran's Q statistic ( P < 0.05, Table 1 ). Discussion International consensus suggests screening for PE risk in early pregnancy to determine whether evidence-based preventative measures (such as aspirin) are necessary[ 1 , 29 ]. Clinical risk factors remain important for the prediction of PE even though adding ultrasonographic factors and biochemical markers to clinical risk factors can double the identification of women who will develop PE before 37 weeks of gestation (i.e. preterm or preeclampsia)[ 1 , 30 ]. Several studies have found an increased risk of developing PE among women with PCOS[ 6 – 8 , 31 – 35 ], but others have found only an association with hyperandrogenic or insulin-resistant phenotypes or failed to find an independent relationship[ 11 – 13 , 36 – 38 ]. It is unclear whether PCOS and PE are related due to limitations in adjusting for confounders, heterogeneous patient populations, and publication bias in prior studies. In MR, instruments are randomly assigned genotypes from birth, thereby reducing confounding and allowing the causal association between PE and PCOS to be more robust. Furthermore, MR is preferable to observational studies because it generates an unbiased, imprecise estimate for causal association as opposed to a precise, biased estimate[ 39 , 40 ]. MR analysis was used in this study to investigate whether PCOS is causally associated with PE risk with selected genetic instruments. The results were robust to pleiotropy. The estimates of causal association obtained from the weighted median, MR-Egger regression, simple mode, and weighted mode were consistent with the results of IVW analysis, thus confirming the result’s robustness to violation of MR assumptions. Results in this study support that PCOS was not causally associated with an increased risk of PE, which were similar to the conclusions of part of previous studies[ 11 – 13 ]. The use of aspirin may help prevent PE, especially in cases of the early onset subtype. Pregnancies at high risk for PE are offered aspirin prophylaxis based on either individual factors or multifactorial algorithms. The most commonly used PE prediction models do not include PCOS[ 14 , 41 , 42 ]. Our MR analysis offers evidence that PCOS, a potential risk factor, plays no significant role in the risk of PE. In line with current PE guidelines conflict with evidence that PCOS is a probable PE risk factor[ 16 ], we suggest PCOS should not be presently included as a risk factor in obstetrical guidelines and prediction models for PE. To determine whether PCOS and PE are associated, further research is needed. Due to the large sample size and the use of multiple uncorrelated SNPs associated with PCOS, this MR analysis minimizes residual confounding and reverse causality biases, thereby increasing the precision of the estimate. The MR study in this paper was conducted under the confirmation of the three critical assumptions. Multiple MR approaches, including IVW, weighted median, MR-Egger regression, simple mode, and weighted mode, supported the robustness of the results. In the leave-one-out sensitivity analysis, no single SNP drove the overall effect, demonstrating the accuracy and consistency of the findings. It is, to our knowledge, the first MR study to investigate the association between PCOS and PE on the European population with GWAS data sources for both exposure and outcome. There are several limitations to our study. First, we were not able to stratify the analysis by PCOS subtypes due to the lack of data on subtypes of disease exposure. There are many clinical phenotypes associated with PCOS, which can differ from one ethnic group to another[ 3 , 43 , 44 ]. Medical research and patient care are challenged by the wide range of clinical phenotypes[ 44 ]. Pregnancies with PCOS are at high risk of hypertensive disorders of pregnancy, gestational diabetes, and preterm delivery, and these risks vary based on their PCOS phenotype[ 5 , 45 ]. It is necessary to conduct further research to determine whether specific subgroups of patients with PCOS, including those with ovulatory dysfunction and biochemical hyperandrogenism, have a significant association with increased risk for PE. Second, the GWAS data set used mainly consisted of European ancestry populations to avoid confounding due to population stratification; Therefore, the present results may not apply to other ethnic groups, and further study is needed to better understand how these results may generalize to other populations. Third, there was no replication data set with a similar large number of PCOS cases. Conclusion In this MR study, results showed that PCOS was not significantly associated with the risk of PE. The association between PCOS and PE remains unclear, further investigation is necessary to determine if there are particular subgroups of patients with PCOS, who are consistently at increased risk for PE. Abbreviations PCOS Polycystic ovary syndrome PE Preeclampsia MR Mendelian randomization IVW Inverse-variance weighted GWAS Genome-wide association studies IVs Instrumental variables SNP Single nucleotide polymorphism Declarations Acknowledgements We would like to acknowledge the participants and investigators who provided the summary data available. Author contributions FFY designed the study, analyzed and interpreted the data, and drafted the manuscript. XJY, JSX and YZ analyzed and interpreted the data. XHZ concepted and designed the study and revised the manuscript. Funding This study was supported by the Research and Development Fund of Peking University People's Hospital (Grant No. RDJP2022-53) Data availability In the article, the original contributions are presented. For further inquiries, please contact the corresponding author. Competing interests The authors declare that they have no competing interests. References Rolnik DL, Nicolaides KH, Poon LC. 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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-4010881","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276338428,"identity":"f5ebe968-1c08-48d2-b8ca-10ff43982c3b","order_by":0,"name":"Fufen Yin","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fufen","middleName":"","lastName":"Yin","suffix":""},{"id":276338429,"identity":"d139d724-d781-46bb-8bb0-b4c2a9479633","order_by":1,"name":"Xiuju Yin","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiuju","middleName":"","lastName":"Yin","suffix":""},{"id":276338430,"identity":"f9864716-25a0-4b5a-8098-c4029c3ec5af","order_by":2,"name":"Junshu Xie","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Junshu","middleName":"","lastName":"Xie","suffix":""},{"id":276338431,"identity":"1dd3c12d-9be2-4fd6-ae5a-c769833819ca","order_by":3,"name":"Ye Zhu","email":"","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ye","middleName":"","lastName":"Zhu","suffix":""},{"id":276338432,"identity":"78423740-b8af-4a26-b78d-8dd92b7fec41","order_by":4,"name":"Xiaohong Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3QMUsDMRTA8YRAuuS49YWU+hUigdZO/Sq96ZbOcoPYOwJZXU9QP8NNN6cEOt0H6ODgKdRJuEXRzba4uFxuFMxveQTef3hBKAj+oEV5GnZCR0VuuwwmsS/BP4mKmSvasrlQPB+YJLdlqlVksqTyJUTofftuHnFlEyOiB8AVIu3zrieh4+1MjZs9kXZj+H0NZIaoUquehMFyKiBzVG4KA2810HnOqOhLANIPAdIx6bCB6A6YtJ5EwmrKu8wBN1ifRznAkORSoMbJmOHDJ29Bcu25ZVGmNf8ybm3OXp9sd3W9vhnp9qUvOSLs99OzfoQ/BywFQRD8Y9/7qVBoIE3ECwAAAABJRU5ErkJggg==","orcid":"","institution":"Peking University People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xiaohong","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-03-04 06:59:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4010881/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4010881/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52062643,"identity":"e7780299-ea2a-4e3e-8ee1-43cf7253aa57","added_by":"auto","created_at":"2024-03-06 05:51:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":238793,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the causal effects of SNPs associated with polycystic ovary syndrome on preeclampsia\u003c/p\u003e","description":"","filename":"OnlineFig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4010881/v1/741c66c8df028986e389bdf2.png"},{"id":52062642,"identity":"df7c06ed-8d80-4e47-96c2-129005e57ec4","added_by":"auto","created_at":"2024-03-06 05:51:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":92718,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity analysis to investigate the causal association was driven by a unique SNP in preeclampsia\u003c/p\u003e","description":"","filename":"OnlineFig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4010881/v1/45c0a6851e33e3c5adb5bc1d.png"},{"id":58022483,"identity":"41514c6f-0e9d-4449-8f5f-adea7431bf19","added_by":"auto","created_at":"2024-06-10 05:35:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":721676,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4010881/v1/7b26ebe0-e883-434f-ad8a-677bfd1b4462.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mendelian randomization study shows no causal effects of polycystic ovarian syndrome on the risk of preeclampsia","fulltext":[{"header":"Background","content":"\u003cp\u003ePreeclampsia (PE) which complicates 2\u0026ndash;8% of all pregnancies globally, is a significant cause of maternal and perinatal morbidity and mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Polycystic ovary syndrome (PCOS) is reported to be associated with dyslipidemia, insulin resistance, infertility, hypertension, and adverse pregnancy outcomes[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Previous studies have shown that women with PCOS have a higher risk of developing PE[\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], but the findings have been inconsistent. Some studies revealed that PCOS was not associated with an increased risk of PE[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Clinical guidelines outline numerous high and moderate risk factors associated with PE. These factors assist caregivers in determining when to administer aspirin for PE prevention and when to enhance pregnancy monitoring[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Currently, PCOS is not considered a risk factor for PE in international guidelines[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The current PE guidelines do not align with evidence indicating PCOS is a probable PE risk factor[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is no robust causal link between PE and PCOS observed in observational studies due to confounding factors and reversals of causal relationships. Therefore, further research is required to establish a robust causal link between PE and PCOS. The Mendelian randomization method (MR) utilizes genetic information to examine causal relationships between exposures and outcomes[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Random distribution of genetic variants during meiosis enables MR to overcome the limitations of confounding and reverse causality that often plague observational studies[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The objective of this study was to search out whether PCOS is causally related to the risk of PE employing an MR analysis.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003eStudy design\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe causal association between PCOS and PE was conducted by a two-sample MR research. The instrumental variables were selected based on three key principles: (1) genetic variation is robustly correlated with exposure; (2) potential confounding factors are minimally correlated with genetic variation; and (3) the outcomes under investigation are not directly influenced by genetic variation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This study examined the effect of PCOS on the risk of PE by using MR analysis.\u003c/p\u003e\n\u003ch3\u003eData sources and selection of genetic variants\u003c/h3\u003e\n\u003cp\u003eThe genome-wide association studies (GWAS) summary statistics for PCOS were obtained from a recent genomewide association meta-analysis study[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] that included 10,074 individuals diagnosed with PCOS and 103,164 healthy controls. The summary-level GWAS data for PE was from the IEU open GWAS project (ebi-a-GCST90018906)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This step ensures that SNPs are valid instrument variables (IVs): (i) The SNPs are strongly correlated with exposure and significant with a \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;5.0\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e ; (ii) SNPs are independent of each other to avoid biases caused by linkage disequilibrium (r2\u0026thinsp;\u0026lt;\u0026thinsp;0.01 over a 10-kilobase (kb) region based on the European sample of 1000 Genomes data), and (iii) SNPs could impact other than exposure on the outcome. PhenoScanner (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phenoscanner.medschl.cam.ac.uk/\u003c/span\u003e\u003cspan address=\"http://www.phenoscanner.medschl.cam.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to determine whether the selected SNPs were associated with other traits at genome-wide significance levels. F-statistic of the selected SNPs was calculated to test the weak IV bias. The strength of the selected IV would be strong if the F-statistic was \u0026gt;\u0026thinsp;10[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eStatistical methods\u003c/h3\u003e\n\u003cp\u003eWe used the inverse-variance weighted (IVW) method as the primary analytical method in this MR study, which is an extension of the Wald ratio estimator based on the principles of meta-analysis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Results of causal associations were presented as odds ratios (OR) and 95% confidence intervals (95% CI) with a significance threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. In addition to the IVW method, four additional MR methods (MR-Egger, weighted median, simple mode, and weighted mode) were also applied to assess causal associations.\u003c/p\u003e \u003cp\u003eA series of sensitivity analyses were performed. The Cochran\u0026rsquo;s Q test was used to assess heterogeneity and the MR-Egger intercept was used to detect horizontal pleiotropy[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The leave-one-out sensitivity analysis was performed to evaluate the robustness of the results.\u003c/p\u003e \u003cp\u003eAll analyses in this study were performed based on R software (version 4.2.3) by the \u0026ldquo;TwoSampleMR\u0026rdquo; R package[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Tests were considered statistically significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eSelection of genetic instrumental variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003e14 independent SNPs with significant \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;5.0\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e were selected from GWASs on PCOS as the IVs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). rs853854 was then removed for being palindromic with intermediate allele frequencies. Finally, according to the above description, 13 SNPs are left for MR analysis after instrument selection and exposure-outcome data harmonization (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). With a clumping window of 10,000 kb and linkage disequilibrium (LD) r2\u0026thinsp;\u0026gt;\u0026thinsp;0.01, all SNPs passed the test. In this study, all SNPs had an F statistic value greater than 10, and the mean F statistic value was 629.65, indicating low instrument bias risks.\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\u003eInstrument single-nucleotide polymorphisms for Mendelian randomization analysis and their effects on PCOS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"left\" 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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChromosome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEffect allele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOther allele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF\u003c/p\u003e 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\u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.81E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e571.935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers2178575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.34E-14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e809.619\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers2271194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.57E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e521.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers7563201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.68E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e659.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers7864171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.95E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e484.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers804279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.76E-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e698.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers8043701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.61E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e556.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers853854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.36E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e540.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers9696009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.96E-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e587.935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSNP, single-nucleotide polymorphism; PCOS, polycystic ovary syndrome\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ers853854 was then removed for being palindromic with intermediate allele frequencies\u003c/p\u003e\n\u003ch3\u003eMendelian randomization results\u003c/h3\u003e\n\u003cp\u003eThe MR estimates of exposure (PCOS) on outcome (PE) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Overall, there was no statistically significant causal effect of PCOS on the PE risk. The primary results of IVW showed that patient with PCOS was not statistically related to an increased risk of having PE (OR\u0026thinsp;=\u0026thinsp;1.04, 95% CI: 0.84\u0026ndash;1.30, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.704). In addition, the MR-Egger, weighted median, simple mode, and weighted mode methods showed consistent results. (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eMendelian randomization results of the causal effect of PCOS on PE\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHeterogeneity test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePleiotropy test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCochran's Q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Intercept\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.04 (0.84, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12 (0.89, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.71 (0.58, 5.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.381\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.32 (0.89, 1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.32 (0.91\u0026ndash;1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\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\u003ePCOS, polycystic ovary syndrome; PE, preeclampsia; IVW, inverse-variance weighted\u003c/p\u003e\n\u003ch3\u003eSensitivity analysis and heterogeneity\u003c/h3\u003e\n\u003cp\u003eLeave-one-out sensitivity analysis results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e as a forest plot. With one SNP removed, all error bars are on the right side of the zero line, indicating no single SNP was driving the causal link and the conclusion remains stable. The MR-Egger intercept showed no evidence of directional pleiotropy for PCOS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.38, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A notable heterogeneity was detected with Cochran's Q statistic (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eInternational consensus suggests screening for PE risk in early pregnancy to determine whether evidence-based preventative measures (such as aspirin) are necessary[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Clinical risk factors remain important for the prediction of PE even though adding ultrasonographic factors and biochemical markers to clinical risk factors can double the identification of women who will develop PE before 37 weeks of gestation (i.e. preterm or preeclampsia)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Several studies have found an increased risk of developing PE among women with PCOS[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], but others have found only an association with hyperandrogenic or insulin-resistant phenotypes or failed to find an independent relationship[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It is unclear whether PCOS and PE are related due to limitations in adjusting for confounders, heterogeneous patient populations, and publication bias in prior studies.\u003c/p\u003e \u003cp\u003eIn MR, instruments are randomly assigned genotypes from birth, thereby reducing confounding and allowing the causal association between PE and PCOS to be more robust. Furthermore, MR is preferable to observational studies because it generates an unbiased, imprecise estimate for causal association as opposed to a precise, biased estimate[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. MR analysis was used in this study to investigate whether PCOS is causally associated with PE risk with selected genetic instruments. The results were robust to pleiotropy. The estimates of causal association obtained from the weighted median, MR-Egger regression, simple mode, and weighted mode were consistent with the results of IVW analysis, thus confirming the result\u0026rsquo;s robustness to violation of MR assumptions. Results in this study support that PCOS was not causally associated with an increased risk of PE, which were similar to the conclusions of part of previous studies[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe use of aspirin may help prevent PE, especially in cases of the early onset subtype. Pregnancies at high risk for PE are offered aspirin prophylaxis based on either individual factors or multifactorial algorithms. The most commonly used PE prediction models do not include PCOS[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Our MR analysis offers evidence that PCOS, a potential risk factor, plays no significant role in the risk of PE. In line with current PE guidelines conflict with evidence that PCOS is a probable PE risk factor[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], we suggest PCOS should not be presently included as a risk factor in obstetrical guidelines and prediction models for PE. To determine whether PCOS and PE are associated, further research is needed.\u003c/p\u003e \u003cp\u003eDue to the large sample size and the use of multiple uncorrelated SNPs associated with PCOS, this MR analysis minimizes residual confounding and reverse causality biases, thereby increasing the precision of the estimate. The MR study in this paper was conducted under the confirmation of the three critical assumptions. Multiple MR approaches, including IVW, weighted median, MR-Egger regression, simple mode, and weighted mode, supported the robustness of the results. In the leave-one-out sensitivity analysis, no single SNP drove the overall effect, demonstrating the accuracy and consistency of the findings. It is, to our knowledge, the first MR study to investigate the association between PCOS and PE on the European population with GWAS data sources for both exposure and outcome.\u003c/p\u003e \u003cp\u003eThere are several limitations to our study. First, we were not able to stratify the analysis by PCOS subtypes due to the lack of data on subtypes of disease exposure. There are many clinical phenotypes associated with PCOS, which can differ from one ethnic group to another[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Medical research and patient care are challenged by the wide range of clinical phenotypes[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Pregnancies with PCOS are at high risk of hypertensive disorders of pregnancy, gestational diabetes, and preterm delivery, and these risks vary based on their PCOS phenotype[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. It is necessary to conduct further research to determine whether specific subgroups of patients with PCOS, including those with ovulatory dysfunction and biochemical hyperandrogenism, have a significant association with increased risk for PE. Second, the GWAS data set used mainly consisted of European ancestry populations to avoid confounding due to population stratification; Therefore, the present results may not apply to other ethnic groups, and further study is needed to better understand how these results may generalize to other populations. Third, there was no replication data set with a similar large number of PCOS cases.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this MR study, results showed that PCOS was not significantly associated with the risk of PE. The association between PCOS and PE remains unclear, further investigation is necessary to determine if there are particular subgroups of patients with PCOS, who are consistently at increased risk for PE.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003ePCOS Polycystic ovary syndrome\u003c/p\u003e \u003cp\u003ePE Preeclampsia\u003c/p\u003e \u003cp\u003eMR Mendelian randomization\u003c/p\u003e \u003cp\u003eIVW Inverse-variance weighted\u003c/p\u003e \u003cp\u003eGWAS Genome-wide association studies\u003c/p\u003e \u003cp\u003eIVs Instrumental variables\u003c/p\u003e \u003cp\u003eSNP Single nucleotide polymorphism\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the participants and investigators who provided the summary data available.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFFY designed the study, analyzed and interpreted the data, and drafted the manuscript. XJY, JSX and YZ analyzed and interpreted the data. XHZ concepted and designed the study and revised the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Research and Development Fund of Peking University People\u0026apos;s Hospital (Grant No. RDJP2022-53)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the article, the original contributions are presented. For further inquiries, please contact the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRolnik DL, Nicolaides KH, Poon LC. Prevention of preeclampsia with aspirin. 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BJOG. 2014;121:575\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeerakiet S, Srisombut C, Rojanasakul A, Panburana P, Thakkinstian A, Herabutya Y. Prevalence of gestational diabetes mellitus and pregnancy outcomes in Asian women with polycystic ovary syndrome. Gynecol Endocrinol. 2004;19:134\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBautista LE, Smeeth L, Hingorani AD, Casas JP. Estimation of bias in nongenetic observational studies using mendelian triangulation. Ann Epidemiol. 2006;16:675\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang RZ, Yang YX, Li HQ, Shen XN, Chen SD, Cui M, et al. Genetically determined low income modifies Alzheimer's disease risk. Ann Transl Med. 2021;9:1222.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaz S, Koren A, Levin C. Attention, response inhibition and brain event-related potential alterations in adults with beta-thalassaemia major. Br J Haematol. 2019;186:580\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGestational Hypertension and Preeclampsia. ACOG Practice Bulletin Summary, Number 222. Obstet Gynecol. 2020;135:1492\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDumesic DA, Oberfield SE, Stener-Victorin E, Marshall JC, Laven JS, Legro RS. Scientific Statement on the Diagnostic Criteria, Epidemiology, Pathophysiology, and Molecular Genetics of Polycystic Ovary Syndrome. Endocr Rev. 2015;36:487\u0026ndash;525.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFauser BC, Tarlatzis BC, Rebar RW, Legro RS, Balen AH, Lobo R, et al. Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group. Fertil Steril. 2012;97:28\u0026ndash;e3825.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOberley TD, Gonzalez A, Lauchner LJ, Oberley LW, Li JJ. Characterization of early kidney lesions in estrogen-induced tumors in the Syrian hamster. Cancer Res. 1991;51:1922\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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, Causal relationship, Polycystic ovary syndrome, Preeclampsia","lastPublishedDoi":"10.21203/rs.3.rs-4010881/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4010881/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePrevious studies have shown an association between polycystic ovary syndrome (PCOS) and the increased risk of developing preeclampsia (PE). However, other studies have not found an independent association between the two. A causal association between PCOS and PE remains unclear. The objective of this study was to determine whether PCOS has a causal relationship with PE.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA two-sample Mendelian randomization (MR) analysis was performed by using the inverse‐variance weighted (IVW), weighted median, MR‐Egger regression, simple mode, and weighted mode methods. We used the publicly available summary statistics data sets of genome‐wide association studies (GWAS) meta‐analyses for PCOS (N\u0026thinsp;=\u0026thinsp;113238) as the exposure and a GWAS for PE (N\u0026thinsp;=\u0026thinsp;267242) as the outcome. In addition, the heterogeneity, horizontal pleiotropy, and stability were assessed through several sensitivity analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e13 single nucleotide polymorphisms (SNPs) at genome-wide significance from GWASs on PCOS were selected as the instrumental variables (IVs). The results of all the methods including IVW, weighted median, MR‐Egger regression, simple mode, and weighted mode were consistent and showed no causal association between PCOS and PE (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe results of MR analysis support that PCOS may not be causally associated with an increased risk of PE. We suggest PCOS should not be presently included as a risk factor in obstetrical guidelines and prediction models for PE. To determine whether PCOS and PE are associated, further research is needed.\u003c/p\u003e","manuscriptTitle":"Mendelian randomization study shows no causal effects of polycystic ovarian syndrome on the risk of preeclampsia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-06 05:51:33","doi":"10.21203/rs.3.rs-4010881/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":"5125efaa-79cd-4677-91ba-41d2da313135","owner":[],"postedDate":"March 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-18T04:48:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-06 05:51:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4010881","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4010881","identity":"rs-4010881","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}