The impact of endometriosis on cardiovascular and cerebrovascular diseases: A Mendelian randomization study

Endometriosis has been linked to several systemic complications, including cardiovascular disease (CVD), atrial fibrillation (AF), heart failure (HF), hypertension, stroke, and ischemic stroke. The potential causal relationship between endometriosis and these diseases remains poorly understood. This Mendelian randomization (MR) study employed two-sample analyses to explore the associations between endometriosis and disease outcomes using data from large-scale genome-wide association studies (GWAS). The primary analysis method was the inverse variance weighted (IVW) method, which was supplemented by weighted median, weighted mode, and MR Egger methods. Our primary analysis revealed no significant causal association between endometriosis and cardiovascular or cerebrovascular diseases, including CVD, HF, stroke, ischemic stroke, and hypertension. Despite initial indications of a possible genetic link between endometriosis and AF (OR = 132.357; 95 percent CI: 1.126 –15,551.291; p = .045), this association was not robust. Sensitivity tests, including the “leave-one-out” analysis, showed the results to be unstable, and MR-weighted median analyses confirmed the lack of consistency in these findings. This MR study does not support a causal role of endometriosis in major cardiovascular or cerebrovascular diseases. The unstable association with AF may reflect residual pleiotropy or limited power, underscoring the need for validation in larger, diverse cohorts.

Over the last 40 years, there has been a continuous decrease in both incidence and mortality rates associated with cardiovascular disease (CVD). Nevertheless, CVD continues to represent a significant global health challenge (Townsend et al. Citation2022; Vaduganathan et al. Citation2022). This issue is particularly pronounced in developing areas, where nearly 80 percent of CVD cases worldwide now emerge in low- and middle-income countries (Alhuneafat et al. Citation2024; Zhao et al. Citation2019). In these regions, the challenges associated with CVD are exacerbated by rapid population aging and urbanization, which are contributing to the escalating prevalence of these conditions (Alhuneafat et al. Citation2024; Zhao et al. Citation2019). Over the past few decades, grassroots initiatives have significantly contributed to increasing awareness regarding the impact of CVD on women (Vogel et al. Citation2021). As of 2019, there were approximately 275.2 million cases of CVD among women globally, with a 95 percent uncertainty interval ranging from 261.4 million to 289.8 million (Vogel et al. Citation2021). Traditional risk factors, such as smoking, unhealthy dietary habits, and obesity, affect both genders; however, emerging evidence suggests that reproductive health factors unique to women – like menstrual cycle characteristics, gestational diabetes, gestational hypertension, and pregnancy loss – are linked to premature mortality due to non-communicable diseases (Roeters van Lennep et al. Citation2023; Smyk et al. Citation2024; Wan et al. Citation2024). Endometriosis is characterized by the presence of endometrial tissue (including glands and stroma) outside the uterine cavity. Clinically, it presents through symptoms such as dysmenorrhea, irregular menstrual cycles, chronic pelvic pain, and infertility (Hou et al. Citation2024; Tulandi and Vercellini Citation2024; Wan et al. Citation2024). Interestingly, endometriosis shares several biological hallmarks with malignant tumors, such as invasiveness, implantability, and recurrence, and it may contribute to long-term cancer risk. The global prevalence of endometriosis has shown a steady increase over recent years, affecting an estimated 10 percent to 15 percent of women worldwide (Marchandot et al. Citation2022). Though limited, some studies have indicated potential links between endometriosis and cardiovascular conditions like CVD and stroke (Mu et al. Citation2016; Okoth et al. Citation2021). In a retrospective cohort analysis conducted by Okoth and colleagues (Okoth et al. Citation2021) comprising 279,759 women between 1995 and 2018, an adjusted odds ratio (aOR) of 1.24 (95 percent confidence interval [CI] 1.13–1.37) was observed for the combined outcome of ischemic heart disease, heart failure (HF), and cerebrovascular disease in women with endometriosis. Moreover, endometriosis was associated with a 1.40-fold (95 percent CI 1.22–1.61) increase in the risk of ischemic heart disease, and a 1.19-fold (95 percent CI 1.04–1.36) rise in the risk of cerebrovascular disease (Mu et al. Citation2016). Despite these findings, cardiovascular and cerebrovascular disorders are multifaceted with various clinical subtypes, and observational studies may be confounded by external variables. Advancements in understanding the genetic underpinnings of endometriosis have paved the way for Mendelian randomization (MR) analyses to investigate potential causal relationships between risk factors – such as endometriosis – and diseases like CVD (Carter et al. Citation2021; Ottensmann et al. Citation2023; Relton and Davey Smith Citation2012; Richardson et al. Citation2022). Our research aims to leverage these genetic insights and analytical techniques to explore the correlation between genetically predicted endometriosis and cardiovascular outcomes, including CVD, atrial fibrillation (AF), HF, hypertension, stroke, and ischemic stroke. Based on the shared pathophysiological mechanisms of chronic inflammation, hormonal dysregulation, and genetic susceptibility, we hypothesize that genetically predicted endometriosis causally increases the risk of cardiovascular and cerebrovascular diseases, particularly AF, through systemic inflammation, endothelial dysfunction, and autonomic nervous system dysregulation. We leverage MR to test this hypothesis, minimizing confounding biases inherent in observational studies. While our study leverages large-scale European GWAS data to minimize confounding, the homogeneity of these cohorts may limit extrapolation to non-European populations. For instance, endometriosis prevalence and cardiovascular risk profiles vary significantly across races – partly due to genetic admixture, socioenvironmental factors (e.g., healthcare disparities), and lifestyle differences.

Study design We executed this MR study consistently with the STROBE-MR guidelines (Supplementary Table S1) (Skrivankova et al. Citation2020, Citation2021; Richardson et al. Citation2021). We sought to establish the causal effects of genetically determined endometriosis on cardiovascular and cerebrovascular diseases as previously described. The validity of instrumental variables (IVs) utilized in establishing causal relationships hinges upon three pivotal criteria (Kong et al. Citation2023; Yao et al. Citation2024): Relevance (strong association with exposure), Independence (absence of links to confounders that may influence both exposure and outcome), and Exclusion Restriction (influences outcome solely via exposure). For our study, GWAS summary statistics were sourced from credible consortia, focused mainly on European descendants (Barton et al. Citation2021; Nielsen et al. Citation2018; Richardson et al. Citation2022; Sakaue et al. Citation2021; van der Harst and Verweij Citation2018; Willer et al. Citation2013; Xue et al. Citation2018; Yengo et al. Citation2018). Ethical compliance details for each referenced GWAS are provided therein. Data sources Data compilation included associated exposures and outcomes, which are delineated in . These were amassed over the period commencing September 1, 2024, through December 31, 2024. For genetic insights regarding endometriosis, we harnessed results from a GWAS that documented findings of 426,933 European individuals. CVD instances, encompassing various manifestations like myocardial infarction and chronic stable angina, were extracted based on information from the CARDIoGRAMplusC4D consortium, which integrates data concerning 60,801 cases alongside 123,504 control subjects (Nikpay et al. Citation2015). Data for other outcomes, HF (Sakaue et al. Citation2021), AF (Nielsen et al. Citation2018), stroke (Malik et al. Citation2018), ischemic stroke (Sakaue et al. Citation2021), and hypertension from relevant GWAS meta-analyses were likewise extracted. Selection of genetic instruments and data harmonization Given the polygenic nature of endometriosis and limited GWAS hits at p < 5e − 08, a relaxed threshold (p < 1e − 05) was adopted to identify sufficient IVs. This approach is justified by prior MR studies of complex traits (Zheng and Zheng Citation2023); SNPs that were closely linked were eliminated through clumping methods (r^2 0.8) were used. SNPs associated with potential confounders of the outcomes were removed according to the searching results in LDlink (https://ldlink.nih.gov/?tab=ldtrait) and VannoPortal (http://www.mulinlab.org/vportal/index.html accessed on December 31, 2024). We then chose 13 independent SNPs linked to endometriosis to serve as instrumental variables (IVs) (Supplementary Table S2). This choice was validated by F-statistics greater than 10, demonstrating robust instrument strength (Burgess and Thompson Citation2011). The formula calculating the F-statistic integrates various factors such as allele frequency and standard errors to determine the effect. The F-statistic, reflecting the variance (R2) that SNPs explain for each exposure, is calculated using the formula R2(N-2)/(1 − R2). Additionally, R2 is derived from (2 × EAF × (1 − EAF) × beta2)/[(2 × EAF × (1 – EAF) × beta2) + (2 × EAF × (1 – EAF) × N × (SE (beta)2)], where EAF denotes the effect allele frequency, beta represents the genetic impact on physical activity, N is the cohort size in the GWAS examining SNP-activity links, and SE (beta) reflects the genetic effect’s standard error (Papadimitriou et al. Citation2020). Statistical analysis Analyses ran on R version 4.3.3, using packages namely TwoSampleMR, MendelianRandomization, and MRPRESSO (Ma and He Citation2023; Sanderson et al. Citation2020). Statistical significance was predicated on p-values less than 0.05. For our primary analysis, we applied the inverse-variance weighted approach which combines results from each SNP using multiplicative random-effect meta-analysis. Heterogeneity – a potential indicator of horizontal pleiotropy (and violation of MR assumptions) – was assessed using Cochran’s Q-statistic. To test for potential bias from horizontal pleiotropy, we performed a series of sensitivity analyses. These included the weighted median and mode-based estimation, MR-Egger regression, and the MR-PRESSO analysis. Each method relaxes certain MR assumptions such that a consistent effect across the multiple methods should be more robust against bias from horizontal pleiotropy (Burgess et al. Citation2017).

Causal relationship between endometriosis and cardiovascular and cerebrovascular diseases This study enabled the identification of 13 SNPs associated with endometriosis traits and outcomes. Each SNP was subjected to an F-test, yielding F-values from 20 to 46—all exceeding the threshold of 10—indicating a low likelihood of weak instrument bias and affirming the data results’ credibility (Supplementary Table S3). The analysis did not reveal any signs of horizontal pleiotropy for which the p-values for Egger’s intercept were above 0.05 (Supplementary Table S4). Likewise, the funnel plot pointed to an absence of noticeable bias in the study (Supplementary Figure S1). displays the MR analysis findings as ORs for endometriosis and outcomes including CVD, HF, stroke, ischemic stroke, and hypertension. Endometriosis did not appear to correlate with investigated outcomes as detailed in Supplementary Table S5. illustrates scatter plots depicting each SNP’s potential effects on outcomes. Furthermore, the robustness of our findings was assessed through a “leave-one-out” sensitivity analysis. This iterative exclusion test underscored that no solitary SNP had a significant impact on the overall result, underscoring the conclusion’s stability and dependability between endometriosis and cardiovascular and cerebrovascular diseases, as shown in . Causal relationship between endometriosis and atrial fibrillation displays the MR analysis findings as ORs for endometriosis and outcomes including CVD, HF, stroke, ischemic stroke, and hypertension. Endometriosis showed a genetic correction with A, with OR = 132.357; 95 percent CI (1.126–15551.291); p = .045. However, with a “leave-one-out” sensitivity analysis, the results did not hold up in the “leave-one-out” sensitivity test, as shown in . Furthermore, additional MR-weighted median analyses, detailed in Supplementary Table S5, highlighted the instability of these results analyzed by the IVW method. In other databases, results were similarly non-significant, p > .05 as shown in Supplementary Table S5. Collectively, these sensitivity tests indicate that the apparent association between endometriosis and AF is unreliable and cannot be considered robust evidence for causality.

Our study, through rigorous MR analysis, unveiled no substantial evidence connecting endometriosis to the risk of major cardiovascular and cerebrovascular outcomes. The potential link uncovered between endometriosis and AF is particularly intriguing. Although the odds ratio indicated a significant genetic correlation, the results displayed instability when subjected to the “leave-one-out” sensitivity analysis and MR-weighted median analyses, indicating that a single or few SNPs may be disproportionately influencing the results. Endometriosis is recognized as a systemic condition characterized by widespread inflammation, largely driven by elevated levels of proinflammatory cytokines, alterations in immune cell populations, and circulating microRNAs. Additionally, this disorder has been found to impact metabolic activities in the liver and adipose tissue, contributing to systemic inflammation, oxidative stress, endothelial dysfunction, and a lipid profile that promotes atherosclerosis – all factors potentially elevating the risk of cardiovascular illnesses (Havers-Borgersen et al. Citation2024; Hou et al. Citation2024; Smyk et al. Citation2024). Recent studies have highlighted an increased cardiovascular risk associated with endometriosis. In a retrospective matched cohort study involving 56,090 women diagnosed with endometriosis and 223,669 healthy controls, those with endometriosis exhibited a heightened risk of atherosclerosis-related cardiovascular diseases, such as ischemic heart disease and cerebrovascular disorders (Okoth et al. Citation2021). This finding has been corroborated by two other research groups (Okoli et al. Citation2023; Parsa et al. Citation2025). Some studies have also suggested that hysterectomy and oophorectomy may elevate cardiovascular disease risk, although the association appears to become non-significant upon adjusting for cardiovascular risk factors (Howard et al. Citation2005). In a Taiwanese cohort study conducted in 2021, Chiang et al. (Citation2021) identified a link between endometriosis and two composite outcomes: myocardial infarction with heart failure and ischemic or hemorrhagic stroke – though individual outcomes were not separately analyzed, and adjustments for potential confounders were limited. In a comprehensive nationwide analysis, Havers et al. reported a long-term association between endometriosis and an increased risk of acute myocardial infarction, ischemic stroke, and HF (Havers-Borgersen et al. Citation2024). These associations persisted even after extensive adjustments and across five sensitivity analyses for composite outcomes. Further, Farland et al. observed that in multivariable models accounting for potential confounders, women with endometriosis had a 34 percent heightened stroke risk compared to those without endometriosis (Farland et al. Citation2022). Meanwhile, the Japan Nurses’ Health Study, cross-sectional in nature, indicated that women with endometriosis faced a two-fold increased risk of transient ischemic attacks or cerebral infarctions compared to their counterparts without the condition (Nagai et al. Citation2015). These findings underscore the variability in outcomes from previous observational research, with most studies indicating an elevated risk of coronary heart disease and cerebral infarction linked to endometriosis, while others note increased risks of hypertension and heart failure. Variations in study populations, assessment criteria, and confounding variables compromise the reliability of these conclusions. One potential reason for our negative findings could be that the inflammatory and metabolic mechanisms linked to endometriosis do not independently contribute to cardiovascular risks when genetic predispositions are accounted for. Another reason could be the heterogeneity and complexity of endometriosis, where the severity and specific manifestations of the condition might differ significantly among individuals, influencing the overall cardiovascular outcomes inconsistently in population studies. Furthermore, previous observational studies may have overestimated the cardiovascular risks due to biases inherent in their designs, such as selection bias, recall bias, and inadequate control of confounding variables. These factors might have contributed to the apparent associations observed, which our Mendelian Randomization study, designed to control for these biases, did not replicate. The stability observed in leave-one-out sensitivity analysis can be attributed to the biological coherence of our genetic instruments. For instance, SNPs such as rs999418 (inflammation), rs7766106 (lipid/glucose metabolism), and rs4876346 (metabolic syndrome) directly implicate pathways shared by endometriosis and CVD. Their minimal individual impact on overall results likely reflects the polygenic nature of endometriosis, where no single variant dominates causal pathways. Conversely, SNPs with weaker effects (e.g., intergenic variants) may operate through distal regulatory mechanisms, contributing marginally to the pooled estimates. In the exploration of the correlation between endometriosis and arrhythmia, only two significant studies have been conducted. One extensive retrospective cohort study in the UK by Okoth et al. revealed an association, indicating that individuals with endometriosis have a heightened risk of developing arrhythmia, with an adjusted hazard ratio of 1.26 (95 percent CI: 1.11–1.43, p = .001) (Okoth et al. Citation2021). Another study by Havers et al. demonstrated a long-term link between endometriosis and increased incidences of arrhythmias, such as AF, advanced second and third-degree atrioventricular block, and the necessity for cardiac devices, excluding episodes of cardiac arrest, ventricular tachycardia, or sinoatrial dysfunction (Havers-Borgersen et al. Citation2024). Although the exact mechanisms by which endometriosis may contribute to the development of AF are not entirely clear, several potential pathways have been proposed, including inflammatory processes, hormonal imbalances, and dysfunction of the autonomic nervous system. Regarding the potential association between endometriosis and AF, our results must be interpreted with caution due to substantial methodological concerns. Although a nominally significant OR was obtained in some MR approaches (e.g., p = .045), the “leave-one-out” sensitivity analysis and MR weighted median methods revealed significant instability, implying that this finding may be driven by chance or unmeasured pleiotropy rather than a true biological relationship. This unreliability likely stems from the limited number of genetic instruments (only 13 SNPs for endometriosis), which increases susceptibility to outlier SNPs, or from horizontal pleiotropy where genetic variants influence AF via pathways independent of endometriosis (e.g., through inflammatory cytokines or estrogen signaling). Consequently, we cannot exclude the possibility of false positives due to random variation, and the evidence remains insufficient to support a causal link at this time. To advance this inquiry, future studies should prioritize investigations of gene–environment interactions – for instance, examining how environmental factors (e.g., oral contraceptives, physical activity, or obesity) modify genetic risks for AF in endometriosis patients. Such approaches could uncover modifying effects that account for the observed heterogeneity and provide deeper insights into potential shared mechanisms. Strengths and limitations of the research methodology Our research demonstrates several advantages concerning causal inference. First, the MR method excels over conventional observational studies by reducing the impact of unmeasured confounders and avoiding issues of reverse causality. Next, we utilized GWAS data from two large cohorts: exposure data from Europeans in the UK Biobank and outcome statistics from a mixed-European population. By strategically choosing these groups, we effectively decreased the possibility of sample overlap, thus lowering the likelihood of Type 1 errors. Furthermore, a range of sensitivity checks has verified the consistency of our initial findings, showing minimal effects from pleiotropy. Moreover, further replication studies have reinforced these findings. Despite these strengths, our study is not without shortcomings. Initially, the association uncovered between endometriosis and CVD is only a piece of a more intricate puzzle. Subsequent studies are imperative to untangle additional mechanisms underlying this relationship (Liu et al. Citation2025; Meng et al. Citation2023, Citation2025). While MR-Egger and MR-PRESSO indicated no significant horizontal pleiotropy (Egger intercept p > .05; Supplementary Table S4), we acknowledge limitations: (i) MR-Egger assumes instrument strength is independent of pleiotropy (InSIDE assumption), which may not hold if pleiotropic effects correlate with SNP-exposure associations; (ii) MR-PRESSO may underestimate bias when outlier SNPs are few or weakly influential. Moreover, the genetic IVs selected do not account for all endometriosis phenotypic variability. Yet, an F-statistic exceeding 10 for the AF genetic instruments indicates minimal concerns regarding weak instrument bias. While interplay was detected between endometriosis-associated genetic variants and AF utilizing leave-one-out analysis. Our findings are primarily generalizable to European-ancestry populations. Given that endometriosis exhibits higher prevalence among Asian women and more severe symptoms in Black women compared to White women and that cardiovascular risk factors like hypertension and diabetes disproportionately affect non-European groups, the absence of multi-ancestry data represents a critical limitation (Katon, Plowden, and Marsh Citation2023). Genetic variants instrumental in European populations may lack relevance or exhibit pleiotropic effects in others due to divergent linkage disequilibrium patterns or gene–environment interactions. Thus, replicating these analyses in cohorts like the Million Veteran Program (Koyama et al. Citation2024) or China Biobank (Chen et al. Citation2024) is essential to ensure broader applicability. Future research should focus on three priorities: genetic mechanisms of AF in endometriosis, diverse population studies expanding to multi-ethnic cohorts (e.g., Asian, African), biological mechanism validation in vitro and in vivo models.

While our primary analysis revealed no significant causal relationship between endometriosis and cardiovascular or cerebrovascular diseases, a potential genetic association with AF was observed. However, this link was not robust in sensitivity analyses (e.g., leave-one-out and weighted median methods), indicating it may arise from pleiotropy or limited statistical power. Thus, the association between endometriosis and AF warrants rigorous validation in larger, genetically diverse cohorts. Future studies should prioritize elucidating shared mechanisms – such as chronic inflammation, autonomic dysfunction, or estrogen signaling – that might concurrently drive endometriosis progression and AF pathogenesis. Additionally, investigating gene–environment interactions (e.g., hormonal therapies or lifestyle factors) could clarify modifiable risks. Author contributions DY-L and YS-Y contributed to the conception and design of the study. DY-L and YS-Y contributed to drafting of the manuscript. TT-Y obtained funding. All authors contributed to the acquisition or interpretation of data, proof reading of the manuscript for important intellectual content, and the final approval of the version to be published. Availability of data and materials All the GWAS data, at summary-level, utilized for the analyses are accessible to the public, as represented in . Ethics approval and consent to participate Since all the summary-level GWAS data used in the analyses are in the public domain, obtaining ethical approval for this study was not necessary. Ethical approval for the different GWASs is specified in the respective GWAS publications cited in the manuscript. Supplemental material Supplementary Table S5.csv Download Comma-Separated Values File (9.4 KB)Supplementary Table S5.csvSupplementary Table S4.csv Download Comma-Separated Values File (806 B)Supplementary Table S4.csvSupplementary Table S3.csv Download Comma-Separated Values File (1.3 KB)Supplementary Table S3.csvSupplementary Table S1 STROBE MR checklist.pdf Download PDF (120.9 KB)Supplementary Table S1 STROBE MR checklist.pdfSupplementary Table S2.csv Download Comma-Separated Values File (274 B)Supplementary Table S2.csvSupplementary Figure S1.tif Download TIFF Image (3.3 MB)Supplementary Figure S1.tifAcknowledgments The authors are grateful to the participants of all the GWASs used in this manuscript and the investigators who made these GWAS data publicly available. Disclosure statement The authors affirm that they have no interests in competition. Supplemental material Supplemental data for this article can be accessed online at https://doi.org/10.1080/03630242.2025.2539819 Additional information Funding

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