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Causal effects of endometriosis on SLE, RA and SS risk: evidence from meta-analysis and Mendelian randomization

BMC Pregnancy and Childbirth volume 24, Article number: 162 (2024) Cite this article

Background

Endometriosis is an underdiagnosed disorder that affects an estimated 6-10% of women of reproductive age. Endometriosis has been reported in epidemiological studies to be associated with autoimmune diseases. However, the relationship remains controversial.

Methods

A meta-analysis of observational studies was undertaken to evaluate the risk of autoimmune diseases in patients with endometriosis. The relevant studies were retrieved via the databases Medline, Embase and Web of Science until July 20, 2023. Mendelian randomization (MR) was subsequently utilized to scrutinize the causal influence of genetic predisposition toward endometriosis on three autoimmune diseases.

Results

The meta-analysis findings revealed a relationship between endometriosis and the onset of SLE (cohort studies: RR = 1.77, 95% confidence interval (CI): 1.47–2.13, I2 = 0%; Case-control and cross-sectional studies: OR = 5.23, 95% CI: 0.74–36.98, I2 = 98%), RA (cohort studies: RR = 2.18, 95% CI: 1.85–2.55, I2 = 92%; Case-control and cross-sectional studies: OR = 1.40, 95% CI: 1.19–1.64, I2 = 0%) and SS (cohort studies: RR = 1.49, 95% CI: 1.34–1.66, I2 = 0%). Similarly, in our MR study, the results of the inverse-variance-weighted (IVW) model suggested that genetic predisposition to endometriosis was causally associated with an increased risk for SLE (OR = 1.915, 95% CI: 1.204–3.045, p = 0.006) and RA (OR = 1.005, 95% CI: 1.001–1.009, p = 0.014).

Conclusions

Both our meta-analysis and MR study indicate that endometriosis increases the risk of autoimmune diseases. These findings not only broaden our understanding of the genetic mechanisms underlying the comorbidity of endometriosis and autoimmune diseases, but also offer a new strategy for autoimmune disease prevention.

Peer Review reports

Introduction

Endometriosis is an estrogen-dependent chronic inflammatory disease that affects approximately 7–10% of women worldwide. It is characterized by two main symptoms: pelvic pain and infertility [1]. Serval studies have indicated that endometriosis is associated with numerous diseases, including gastrointestinal diseases, malignancies, cardiovascular diseases, mental disorders and autoimmune diseases [2, 3]. The pathogenesis of endometriosis remains unclear, but the retrograde menstruation theory is currently widely accepted [4].

Autoimmune diseases affect 3–5% of the population, with some being organ-specific, like RA, and others involving multiple organs, such as SLE [5]. There have been many review articles discussing the immunological aspects of endometriosis [6, 7]. They believe that the changes in cell-mediated and humoral immunity in patients with endometriosis may be the reason for the increased risk of autoimmune diseases. However, there are few articles based on population-based observational studies. In an attempt to understand more about the risk of autoimmune diseases in endometriosis, we embarked on a meta-analysis by including cohort studies, cross-sectional studies and case–control studies.

Mendelian randomization (MR) analysis employs genetic variation as an instrumental variable, enabling the evaluation of relationships between an exposure and an outcome. By leveraging the random distribution of genetic variation, MR helps eliminate confounding factors and reverse causation, thus simulating the randomization process seen in a randomized controlled experiment [8,9,10]. The degree of the connection and the direction of causality between endometriosis and autoimmune diseases were evaluated in this study using MR. In this study, we employed a meta-analysis in conjunction with MR analysis to elucidate the causal relationship, strength of association, and direction of causality between endometriosis and three autoimmune diseases.

Methods

Meta-analysis

General information

We performed this meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [11]. The study protocol was registered at PROSPERO (CRD42023444650). (https://www.crd.york.ac.uk/PROSPERO/).

Search strategy

A search strategy was developed as presented in (Datasheet1: Table S1). Two researchers (TYT and YZ) conducted a comprehensive electronic literature search of the PubMed, Web of Science, and Embase databases from their inception until July 2023. No restrictions were applied regarding geographic area, language, or publication status. Additionally, the researchers manually reviewed the reference lists of relevant articles to identify any additional studies that may have been missed in the initial search.

Study selection

Two of the authors (TYT and YZ) initially screened the titles and abstracts of the studies to exclude those that appeared irrelevant. Then, they thoroughly read the full texts of the remaining studies to further exclude any studies that did not meet the eligibility criteria. Any disagreements between the two authors were resolved through discussion.

Eligible articles for this study had to satisfy the following criteria: 1) having a cohort, case–control or cross-sectional study design and published in English, 2) comparing the risk of autoimmune disease among women with/without endometriosis, 3) providing data on odds ratio (OR), risk ratio (RR), hazard ratio (HR), standardized incidence ratio (SIR), incidence rate ratio (IRR) for autoimmune disease. (Table 1).

Table 1 PICOS criteria for inclusion of studies
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Data extraction

Two authors (TYT and YZ) independently extracted data and a consensus was reached in case of any inconsistency.

Using a pre-designed data extraction form, the following information was meticulously recorded: title, the name of the primary author, publication year, country, average age, duration of follow-up, sample size, outcome assessment, risk estimate, corresponding 95% confidence intervals.

Assessing the Risk of Bias.

The Newcastle–Ottawa quality assessment scale (NOS) was used to evaluate the methodological quality of cohort study and case–control study included in the analysis [12]. In the absence of established standard criteria, we categorized studies with 0–3 stars, 4–6 stars, or 7–9 stars as low-quality, moderate-quality, or high-quality, respectively. To evaluate the methodological quality of cross-sectional studies, we used the criteria provided by the Agency for Healthcare Research and Quality (AHRQ) [13]. Each item in the assessment was assigned a score of '0' if it was answered as 'NO' or 'UNCLEAR', and a score of '1' if it was answered as 'YES'. The total score for each study was then calculated. Based on the total score, the article quality was categorized as low-quality (0–3), moderate-quality (4–7), or high-quality (8–11). Disagreements were resolved through discussion.

Statistical analysis

The meta-analysis was conducted using Review Manager 5.4. For cross-sectional and case–control studies, raw data were extracted to compute a odds ratio (OR) accompanied by 95% confidence intervals (CIs). For cohort studies, SIR, IRR and HR were treated as the relative risk (RR), and the pooled RR with a 95% confidence interval was calculated [14, 15]. To ensure a more accurate assessment of the relationships between endometriosis and SLE, RA and SS, categorical meta-analyses were conducted. The I2 statistic was used to evaluate the degree of heterogeneity among the included studies. If the I2 value exceeded 50% or the p-value was less than 0.05, indicating a high level of heterogeneity, a random-effects model was employed. Conversely, if the I2 value was below 50% or the p-value was greater than or equal to 0.05, a fixed-effect model was used in the meta-analysis. This approach helps to account for heterogeneity and provide more reliable results.

Mendelian randomization

Study design

The Mendelian randomization (MR) method is based on three key assumptions, which are summarized in Fig. 1. First, the selected SNPs must be significantly correlated with the exposure factor. Second, SNPs must be independent of potential confounding factors. Third, SNPs should not have a direct association with outcome.

Fig. 1
figure 1

Diagram for key assumptions of MR analyses. Exposure SNPs were used as the genetic instruments to investigate the causal effect of endometriosis on outcome. The directional arrows indicates that the genetic instruments (SNPs) are associated with the exposure and can only influence the outcome through the exposure. Dashed lines represent that the genetic instruments (SNPS) are independent of any confounding variables affecting the results

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Data source

For the study of endometriosis, we retrieved genome-wide association study (GWAS) summary data from Nilufer R et al. (PMID: 36,914,876) [16]. In this GWAS, a total of 60,694 patients with endometriosis and 701,926 controls of European and East Asian descent were included by the authors. Summary statistics of SLE are from Wang YF et al. (PMID: 33,536,424), including up to 12,653 participants (4,222 cases and 8,431 controls) of East Asian ancestry [17]. Summary statistics of RA are from Neale Lab, including up to 337,159 participants (3,730 cases and 333,429 controls) of European ancestry. The summary statistics of SS were obtained from the FinnGen consortium release data (1,290 cases and 213,145 controls).

Statistical analysis

Cochran's Q test was used in this MR study to determine whether there was variability in estimates of specific genetic variants [18]. Inverse variance weighted (IVW) analysis was the main technique employed [19]. In addition to IVW, further analyses were carried out utilizing the weighted median method [20], simple mode, weighted mode, and MR-egger regression method [21]. Finally, to guarantee the accuracy of the results, we tested and calibrated horizontal pleiotropic outliers in the IVW model using MR pleiotropy residual sum and outlier (MR-PRESSO) [22].

Sensitivity analysis

To detect potential pleiotropy, we conducted the MR-Egger test and interpreted a P-value greater than 0.05 for the MR-Egger intercept as an absence of horizontal pleiotropy [23]. To assess the stability of the results, leave-one-out sensitivity analyses were conducted, wherein a single SNP was excluded in each iteration. This analysis helps determine if any single SNP is driving the observed associations. Funnel plots and forest plots were generated to visually explore the existence of pleiotropy, which is when a genetic variant affects multiple traits or outcomes. A two-sided p-value of less than 0.05 was considered as suggestive of significance. All the analyses were performed using the "Two-Sample-MR" and "MR-PRESSO" packages in R software, specifically Version 4.2.3.

Results

Meta-analysis

Study selection and characteristics

A flowchart of the process of choosing the specific literature is shown in Fig. 2. Tables 2 and 3 provide a detailed summary of key features for the 13 included research. In brief, 3 (23.1%) investigations were conducted in North America, 4 (30.8%) in Europe, and 6 (46.2%) in Asia. In terms of study design, one (7.8%) study was cross-sectional, four (30.8%) were case–control studies, and eight (61.5%) were cohort studies (four prospective cohort studies and four retrospective cohort studies).

Fig. 2
figure 2

The flowchart of meta-analysis

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Table 2 Characteristics of case–control and cross-sectional studies
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Table 3 Characteristics of cohort studies
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Quality assessment

According to the information provided, the researchers used the Agency for Healthcare Research and Quality (AHRQ) rating criteria to assess the quality of cross-sectional studies included in their analysis. Additionally, the Newcastle–Ottawa Scale (NOS) was used to evaluate the quality of case–control and cohort studies. The results of this assessment can be found in Tables 4 and 5, which presumably shows that all the publications included in the study were rated as high or moderate quality based on the use of AHRQ and NOS criteria.

Table 4 NOS assessment for case–control and cross-sectional studies
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Table 5 AHRQ assessment for cross-sectional studies
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Data synthesis

Endometriosis and SLE

Eight studies were included in a meta-analysis comparing the risk of SLE in individuals with endometriosis and those without endometriosis, involving 477,501 individuals and 113,318 endometriosis cases [24,25,26,27,28,29,30,31]. For case–control and cross-sectional studies, we did not find a significant association between the two conditions. For cohort studies, with low heterogeneity, the pooled risk of SLE was greater in individuals with endometriosis than in those without endometriosis (RR = 1.77, 95% CI 1.47–2.13; I2 = 0%) (Fig. 3).

Fig. 3
figure 3

Forest plots of studies. (A) the association of endometriosis with SLE risk; (B) the association of endometriosis with RA risk; (C) the association of endometriosis with SS risk

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Endometriosis and RA

Six studies were included in a meta-analysis comparing the risk of RA in individuals with endometriosis and those without endometriosis, involving 434,377 individuals and 73,006 endometriosis cases [25, 30,31,32,33,34]. Case–control and cross-sectional studies have described the association between endometriosis and RA (OR = 1.40, 95% CI 1.19–1.64; I2 = 0%). For cohort studies, with high heterogeneity, we observed similar trends in the results (RR = 1.89, 95% CI 1.04–3.42; I2 = 92%) (Fig. 3).

Endometriosis and SS

Three studies were included in a meta-analysis comparing the risk of SS in individuals with endometriosis and those without endometriosis, involving 215,006 individuals and 56,074 endometriosis cases [28, 30, 35]. For cohort studies, with low heterogeneity, the pooled risk of SS was greater in individuals with endometriosis than in those without endometriosis (RR = 1.49, 95% CI 1.34–1.66; I2 = 0%) (Fig. 3).

Mendelian randomization study

Genetic associations between endometriosis and SLE, RA, and SS risk

Using the random-model IVW, we discovered a link between each standard rise in endometriosis risk and a faster development to SLE (OR = 1.915, 95% CI: 1.204–3.045, p = 0.006) and RA (OR = 1.005, 95% CI: 1.001–1.009, p = 0.014). However, no causal relationship was found between endometriosis and SS. (Fig. 4).

Fig. 4
figure 4

Associations of genetic predisposition to endometriosis with SLE, RA, and SS risk

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Sensitivity analysis

Cochran's Q test findings revealed that these SNPs exhibited no heterogeneity. We found no evidence of directional pleiotropy using MR Egger intercepts and MR-PRESSO (Datasheet 2). The leave-one-out analysis produced a stable result when each SNP was eliminated, as shown in Datasheet 3.

Discussion

Many previous studies have found a link between endometriosis and autoimmune disorders, a literature review was compiled on the topic (Datasheet1:Table S2). We employ meta-analysis and MR to investigate causative associations between endometriosis and SLE, RA, and SS risk. To our knowledge, the latest and probably only meta-analysis was published in 2019 [36]. Due to the inability of cross-sectional and case–control studies to resolve the issue of the temporal relationship between endometriosis and autoimmune diseases, their research faced challenges in determining the sequence of disease development and manifestation, as well as potential causal relationships. Compared to this study, our study comprises more studies in patients with endometriosis, including newer and larger cohort studies. We aimed to investigate the causal effect of endometriosis on SLE, RA and SS. As the first report to employ MR in investigating the causal association between endometriosis and the risk of SLE, RA, and SS, our study eliminates confounding factors and reverse causality effects, which may yield more reliable results.

The meta-analysis findings reveal that endometriosis patients are more likely to develop SLE and SS, which is consistent with the results of the meta-analysis from 2019. However, in contrast to previous studies, we found that endometriosis also increases the risk of RA. The discrepancy in findings between the two studies may be due to the fact that the 2019 study only had two cohort studies available for inclusion. We observed that only a limited number of studies accounted for the effects of confounding factors, which may influence the level of the risk. Smoking, alcohol usage, caffeine consumption, and a lack of exercise have all been linked to an increased risk of endometriosis [37]. These lifestyle and environmental factors have also been linked to an increased susceptibility to cancer occurrence [38]. At the same time, the number of included studies was relatively small, which poses a risk of generating spurious associations. Therefore, we encourage more researchers to further investigate the association by employing prospective cohort study designs.

We also utilize a two-sample MR approach to further investigate the impact of endometriosis on the risk of autoimmune diseases. We employ independent loci associated with endometriosis identified from the largest available genome-wide association studies (GWAS) to date. All SNPs were identified in the PhenoScanner database (http://www.phenoscanner.medschl.cam.ac.uk/) to exclude SNPs related to confounding factors. With MR, we found that endometriosis is linked with a higher risk of SLE and RA, which supports prior meta-analyses.

The imbalance of the immune system may explain the the observed impact of endometriosis on autoimmune diseases in clinical practice [39,40,41]. Previous studies have demonstrated that elevated expression of IL-6, IL-15, and TGF-β1 in patients with endometriosis can reduce the activity of NK cells [42,43,44]. It has been observed that patients with endometriosis often have an increase in neutrophils and macrophages in their peritoneal fluid [45, 46]. In the latest meta-analysis to date, Riccio et al. suggested that there is an increase in B lymphocytes and excessive production of autoantibodies in endometriosis [47]. These alterations play an important role in mediating the pathogenesis of autoimmune diseases [48,49,50].

Estrogen also plays an important role in the development of endometriosis and autoimmune diseases. Endometriosis is an estrogen-dependent disease, and the disruption of estrogen signaling leads to hormonal imbalance, which causes its symptoms [51]. Targeting estrogen is still considered the optimal approach for controlling the progression and inflammation of endometriosis [52]. Estrogen has also been found to regulate the immune system and contribute to the transduction pathways of autoimmunity by activating its nuclear receptor AhR [53]. Estrogen raises the risk of autoimmune diseases by raising the generation of type 1 interferon and promoting the survival of B cells that create pathogenic IgG autoantibodies [54].

Firstly, pleiotropy has always been an important issue in Mendelian randomization. However, neither the MR-Egger nor the MR-PRESSO analyses revealed any indication of horizontal pleiotropy, indicating a very low level of pleiotropic bias. Secondly, the observational studies collected in our meta-analysis did not consider the influence of mediation effects. For example, patients with endometriosis exhibited an increased susceptibility to sedentary behavior [3]. Sedentary behavior is also acknowledged as a risk factor for autoimmune diseases [55]. Finally, our study did not examine the effect of endometriosis on the prognosis of autoimmune disorders due to a lack of data. Therefore, more studies are warranted to elucidate the possible relation between the two conditions.

Availability of data and materials

The 42 SNPs selected for endometriosis are provided in Datasheet2 Table S1. The data that support the findings of this study are openly available in an open website (https://gwas.mrcieu.ac.uk/). All data generated or analysed during this study are included in this published article and datasheet.

Abbreviations

Fig:

Figure

GWAS:

Genome-wide association study

IVW:

Inverse-variance-weighted

MR:

Mendelian randomization

References

  1. Giudice LC, Kao LC. Endometriosis Lancet. 2004;364:1789–99. https://doi.org/10.1016/S0140-6736(04)17403-5.

    Article  PubMed  Google Scholar 

  2. Koller D, Pathak GA, Wendt FR, Tylee DS, Levey DF, Overstreet C, et al. Epidemiologic and Genetic Associations of Endometriosis With Depression, Anxiety, and Eating Disorders. JAMA Netw Open. 2023;6: e2251214. https://doi.org/10.1001/jamanetworkopen.2022.51214.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Parazzini F, Esposito G, Tozzi L, Noli S, Bianchi S. Epidemiology of endometriosis and its comorbidities. Eur J Obstet Gynecol Reprod Biol. 2017;209:3–07. https://doi.org/10.1016/j.ejogrb.2016.04.021.

    Article  CAS  PubMed  Google Scholar 

  4. Burney RO, Giudice LC. Pathogenesis and pathophysiology of endometriosis. Fertil Steril. 2012;98:511–9. https://doi.org/10.1016/j.fertnstert.2012.06.029.

    Article  CAS  PubMed  Google Scholar 

  5. Wang L, Wang FS, Gershwin ME. Human autoimmune diseases: a comprehensive update. J Intern Med. 2015;278:369–95. https://doi.org/10.1111/joim.12395.

    Article  CAS  PubMed  Google Scholar 

  6. Paul DW, Braun DP. Immunology of endometriosis. Best Pract Res Clin Obstet Gynaecol. 2004;18:245–63. https://doi.org/10.1016/j.bpobgyn.2004.02.001.

    Article  Google Scholar 

  7. Symons LK, Miller JE, Kay VR, Marks RM, Liblik K, Koti M, et al. The Immunopathophysiology of Endometriosis. Trends Mol Med. 2018;24:748–62. https://doi.org/10.1016/j.molmed.2018.07.004.

    Article  CAS  PubMed  Google Scholar 

  8. Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37:658–65. https://doi.org/10.1002/gepi.21758.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey SG. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27:1133–63. https://doi.org/10.1002/sim.3034.

    Article  MathSciNet  PubMed  Google Scholar 

  10. Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1–22. https://doi.org/10.1093/ije/dyg070.

    Article  PubMed  Google Scholar 

  11. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Plos Med. 2009;6: e1000097. https://doi.org/10.1371/journal.pmed.1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Norris JM, Simpson BS, Ball R, Freeman A, Kirkham A, Parry MA, et al. A Modified Newcastle-Ottawa Scale for Assessment of Study Quality in Genetic Urological Research. Eur Urol. 2021;79:325–6. https://doi.org/10.1016/j.eururo.2020.12.017.

    Article  PubMed  Google Scholar 

  13. Soffin EM, Gibbons MM, Ko CY, Kates SL, Wick E, Cannesson M, et al. Evidence Review Conducted for the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery: Focus on Anesthesiology for Total Knee Arthroplasty. Anesth Analg. 2019;128:441–53. https://doi.org/10.1213/ANE.0000000000003564.

    Article  PubMed  Google Scholar 

  14. Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiol Rev. 1987;9:1–30. https://doi.org/10.1093/oxfordjournals.epirev.a036298.

    Article  CAS  PubMed  Google Scholar 

  15. Siristatidis C, Sergentanis TN, Kanavidis P, Trivella M, Sotiraki M, Mavromatis I, et al. Controlled ovarian hyperstimulation for IVF: impact on ovarian, endometrial and cervical cancer–a systematic review and meta-analysis. Hum Reprod Update. 2013;19:105–23. https://doi.org/10.1093/humupd/dms051.

    Article  CAS  PubMed  Google Scholar 

  16. Rahmioglu N, Mortlock S, Ghiasi M, Møller PL, Stefansdottir L, Galarneau G, et al. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions. Nat Genet. 2023;55:423–36. https://doi.org/10.1038/s41588-023-01323-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wang YF, Zhang Y, Lin Z, Zhang H, Wang TY, Cao Y, et al. Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups. Nat Commun. 2021;12:772. https://doi.org/10.1038/s41467-021-21049-y.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bowden J, Del GMF, Minelli C, Davey SG, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med. 2017;36:1783–802. https://doi.org/10.1002/sim.7221.

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  19. Yang J, Ferreira T, Morris AP, Medland SE, Madden PA, Heath AC, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 2012;44(369–75):S1-03. https://doi.org/10.1038/ng.2213.

    Article  CAS  Google Scholar 

  20. Bowden J, Davey SG, Haycock PC, Burgess S. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator. Genet Epidemiol. 2016;40:304–14. https://doi.org/10.1002/gepi.21965.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bowden J, Davey SG, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25. https://doi.org/10.1093/ije/dyv080.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50:693–8. https://doi.org/10.1038/s41588-018-0099-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32:377–89. https://doi.org/10.1007/s10654-017-0255-x.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Fan YH, Leong PY, Chiou JY, Wang YH, Ku MH, Wei JC. Association between endometriosis and risk of systemic lupus erythematosus. Sci Rep. 2021;11:532. https://doi.org/10.1038/s41598-020-79954-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Harris HR, Costenbader KH, Mu F, Kvaskoff M, Malspeis S, Karlson EW, et al. Endometriosis and the risks of systemic lupus erythematosus and rheumatoid arthritis in the Nurses’ Health Study II. Ann Rheum Dis. 2016;75:1279–84. https://doi.org/10.1136/annrheumdis-2015-207704.

    Article  CAS  PubMed  Google Scholar 

  26. Lin YH, Yang YC, Chen SF, Hsu CY, Shen YC. Risk of systemic lupus erythematosus in patients with endometriosis: A nationwide population-based cohort study. Arch Gynecol Obstet. 2020;302:1197–203. https://doi.org/10.1007/s00404-020-05726-9.

    Article  PubMed  Google Scholar 

  27. Matorras R, Ocerin I, Unamuno M, Nieto A, Peiró E, Burgos J, et al. Prevalence of endometriosis in women with systemic lupus erythematosus and Sjogren’s syndrome. Lupus. 2007;16:736–40. https://doi.org/10.1177/0961203307081339.

    Article  CAS  PubMed  Google Scholar 

  28. Nielsen NM, Jørgensen KT, Pedersen BV, Rostgaard K, Frisch M. The co-occurrence of endometriosis with multiple sclerosis, systemic lupus erythematosus and Sjogren syndrome. Hum Reprod. 2011;26:1555–9. https://doi.org/10.1093/humrep/der105.

    Article  PubMed  Google Scholar 

  29. Porpora MG, Scaramuzzino S, Sangiuliano C, Piacenti I, Bonanni V, Piccioni MG, et al. High prevalence of autoimmune diseases in women with endometriosis: a case-control study. Gynecol Endocrinol. 2020;36:356–9. https://doi.org/10.1080/09513590.2019.1655727.

    Article  CAS  PubMed  Google Scholar 

  30. Sinaii N, Cleary SD, Ballweg ML, Nieman LK, Stratton P. High rates of autoimmune and endocrine disorders, fibromyalgia, chronic fatigue syndrome and atopic diseases among women with endometriosis: a survey analysis. Hum Reprod. 2002;17:2715–24. https://doi.org/10.1093/humrep/17.10.2715.

    Article  CAS  PubMed  Google Scholar 

  31. Yoshii E, Yamana H, Ono S, Matsui H, Yasunaga H. Association between allergic or autoimmune diseases and incidence of endometriosis: A nested case-control study using a health insurance claims database. Am J Reprod Immunol. 2021;86: e13486. https://doi.org/10.1111/aji.13486.

    Article  PubMed  Google Scholar 

  32. Chen SF, Yang YC, Hsu CY, Shen YC. Risk of Rheumatoid Arthritis in Patients with Endometriosis: A Nationwide Population-Based Cohort Study. J Womens Health (Larchmt). 2021;30:1160–4. https://doi.org/10.1089/jwh.2020.8431.

    Article  PubMed  Google Scholar 

  33. Merlino LA, Cerhan JR, Criswell LA, Mikuls TR, Saag KG. Estrogen and other female reproductive risk factors are not strongly associated with the development of rheumatoid arthritis in elderly women. Semin Arthritis Rheum. 2003;33:72–82. https://doi.org/10.1016/s0049-0172(03)00084-2.

    Article  CAS  PubMed  Google Scholar 

  34. Xue YH, You LT, Ting HF, Chen YW, Sheng ZY, Xie YD, et al. Increased risk of rheumatoid arthritis among patients with endometriosis: a nationwide population-based cohort study. Rheumatology (Oxford). 2021;60:3326–33. https://doi.org/10.1093/rheumatology/keaa784.

    Article  PubMed  Google Scholar 

  35. Chao YH, Liu CH, Pan YA, Yen FS, Chiou JY, Wei JC. Association Between Endometriosis and Subsequent Risk of Sjögren’s Syndrome: A Nationwide Population-Based Cohort Study. Front Immunol. 2022;13: 845944. https://doi.org/10.3389/fimmu.2022.845944.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Shigesi N, Kvaskoff M, Kirtley S, Feng Q, Fang H, Knight JC, et al. The association between endometriosis and autoimmune diseases: a systematic review and meta-analysis. Hum Reprod Update. 2019;25:486–503. https://doi.org/10.1093/humupd/dmz014.

    Article  PubMed  PubMed Central  Google Scholar 

  37. McLeod BS, Retzloff MG. Epidemiology of endometriosis: an assessment of risk factors. Clin Obstet Gynecol. 2010;53:389–96. https://doi.org/10.1097/GRF.0b013e3181db7bde.

    Article  PubMed  Google Scholar 

  38. Xiao XY, Chen Q, Shi YZ, Li LW, Hua C, Zheng H. Risk factors of systemic lupus erythematosus: an overview of systematic reviews and Mendelian randomization studies. Adv Rheumatol. 2023;63:42. https://doi.org/10.1186/s42358-023-00323-1.

    Article  PubMed  Google Scholar 

  39. Kolanska K, Alijotas-Reig J, Cohen J, Cheloufi M, Selleret L, D’Argent E, et al. Endometriosis with infertility: A comprehensive review on the role of immune deregulation and immunomodulation therapy. Am J Reprod Immunol. 2021;85: e13384. https://doi.org/10.1111/aji.13384.

    Article  CAS  PubMed  Google Scholar 

  40. Vanni VS, Villanacci R, Salmeri N, Papaleo E, Delprato D, Ottolina J, et al. Concomitant autoimmunity may be a predictor of more severe stages of endometriosis. Sci Rep. 2021;11:15372. https://doi.org/10.1038/s41598-021-94877-z.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. Khizroeva J, Nalli C, Bitsadze V, Lojacono A, Zatti S, Andreoli L, et al. Infertility in women with systemic autoimmune diseases. Best Pract Res Clin Endocrinol Metab. 2019;33: 101369. https://doi.org/10.1016/j.beem.2019.101369.

    Article  CAS  PubMed  Google Scholar 

  42. Guo SW, Du Y, Liu X. Platelet-derived TGF-β1 mediates the down-modulation of NKG2D expression and may be responsible for impaired natural killer (NK) cytotoxicity in women with endometriosis. Hum Reprod. 2016;31:1462–74. https://doi.org/10.1093/humrep/dew057.

    Article  CAS  PubMed  Google Scholar 

  43. Kang YJ, Jeung IC, Park A, Park YJ, Jung H, Kim TD, et al. An increased level of IL-6 suppresses NK cell activity in peritoneal fluid of patients with endometriosis via regulation of SHP-2 expression. Hum Reprod. 2014;29:2176–89. https://doi.org/10.1093/humrep/deu172.

    Article  CAS  PubMed  Google Scholar 

  44. Yu JJ, Sun HT, Zhang ZF, Shi RX, Liu LB, Shang WQ, et al. IL15 promotes growth and invasion of endometrial stromal cells and inhibits killing activity of NK cells in endometriosis. Reproduction. 2016;152:151–60. https://doi.org/10.1530/REP-16-0089.

    Article  CAS  PubMed  Google Scholar 

  45. Berbic M, Schulke L, Markham R, Tokushige N, Russell P, Fraser IS. Macrophage expression in endometrium of women with and without endometriosis. Hum Reprod. 2009;24:325–32. https://doi.org/10.1093/humrep/den393.

    Article  CAS  PubMed  Google Scholar 

  46. Milewski Ł, Dziunycz P, Barcz E, Radomski D, Roszkowski PI, Korczak-Kowalska G, et al. Increased levels of human neutrophil peptides 1, 2, and 3 in peritoneal fluid of patients with endometriosis: association with neutrophils, T cells and IL-8. J Reprod Immunol. 2011;91:64–70. https://doi.org/10.1016/j.jri.2011.05.008.

    Article  CAS  PubMed  Google Scholar 

  47. Riccio L, Baracat EC, Chapron C, Batteux F, Abrão MS. The role of the B lymphocytes in endometriosis: A systematic review. J Reprod Immunol. 2017;123:29–34. https://doi.org/10.1016/j.jri.2017.09.001.

    Article  CAS  PubMed  Google Scholar 

  48. Dang VD, Stefanski AL, Lino AC, Dörner T. B- and Plasma Cell Subsets in Autoimmune Diseases: Translational Perspectives. J Invest Dermatol. 2022;142:811–22. https://doi.org/10.1016/j.jid.2021.05.038.

    Article  CAS  PubMed  Google Scholar 

  49. Fresneda AM, McLaren Z, Wright HL. Neutrophils in the Pathogenesis of Rheumatoid Arthritis and Systemic Lupus Erythematosus: Same Foe Different M.O. Front Immunol 2021;12:649693. https://doi.org/10.3389/fimmu.2021.649693

  50. Zhang C, Tian Z. NK cell subsets in autoimmune diseases. J Autoimmun. 2017;83:22–30. https://doi.org/10.1016/j.jaut.2017.02.005.

    Article  CAS  PubMed  Google Scholar 

  51. Marquardt RM, Kim TH, Shin JH, Jeong JW. Progesterone and Estrogen Signaling in the Endometrium: What Goes Wrong in Endometriosis? Int J Mol Sci 2019;20. https://doi.org/10.3390/ijms20153822

  52. Dolmans MM, Donnez J. Emerging Drug Targets for Endometriosis. Biomolecules 2022;12. https://doi.org/10.3390/biom12111654

  53. Merrheim J, Villegas J, Van Wassenhove J, Khansa R, Berrih-Aknin S, le Panse R, et al. Estrogen, estrogen-like molecules and autoimmune diseases. Autoimmun Rev. 2020;19: 102468. https://doi.org/10.1016/j.autrev.2020.102468.

    Article  CAS  PubMed  Google Scholar 

  54. Hughes GC, Choubey D. Modulation of autoimmune rheumatic diseases by oestrogen and progesterone. Nat Rev Rheumatol. 2014;10:740–51. https://doi.org/10.1038/nrrheum.2014.144.

    Article  CAS  PubMed  Google Scholar 

  55. Pinto AJ, Roschel H, de Sá PA, Lima FR, Pereira R, Silva CA, et al. Physical inactivity and sedentary behavior: Overlooked risk factors in autoimmune rheumatic diseases? Autoimmun Rev. 2017;16:667–74. https://doi.org/10.1016/j.autrev.2017.05.001.

    Article  PubMed  Google Scholar 

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Funding

This work was supported by National innovation and entrepreneurship training program [SRIEP202104].

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Authors and Affiliations

  1. Children’s Hospital of Chongqing Medical University, Chongqing, China

    Tianyou Tang & Yi Zhong

  2. The First Medicine College, Chongqing Medical University, Chongqing, China

    Sipei Xu

  3. The Second Medicine College, Chongqing Medical University, Chongqing, China

    Huilin Yu

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  1. Tianyou Tang
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  4. Huilin Yu
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Contributions

Conceptualization: T.Y.T. Software: T.Y.T. Data curation: H.L.Y. and Y.Z. Writing – original draft: T.Y.T. Visualization: S.P.X. The work reported in the paper has been performed by the authors, unless clearly specified in the text. All authors reviewed the manuscript.

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Correspondence to Tianyou Tang.

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Tang, T., Zhong, Y., Xu, S. et al. Causal effects of endometriosis on SLE, RA and SS risk: evidence from meta-analysis and Mendelian randomization. BMC Pregnancy Childbirth 24, 162 (2024). https://doi.org/10.1186/s12884-024-06347-9

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Keywords

BMC Pregnancy and Childbirth

ISSN: 1471-2393

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