The causal relationship of depression, anxiety, and neuroticism with endometriosis: A bidirectional 2-sample Mendelian randomization study

Zhang J, Jiaxun Zhang, Li T, Tie Li, Jinying Zhao, Zhao J, Jiapeng Chai, Chai J, Lin Wang, Wang L, Cao W, Wenxuan Cao, Jia Liu, Liu J, Fuchun Wang
Medicine · 2024 · vol. 103(28) , pp. e38823 · doi:10.1097/md.0000000000038823 · PMID:38996127 · PMC11245226 · W4400577598
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This Mendelian randomization study found genetic evidence that depression and neuroticism are risk factors for endometriosis, but not anxiety, and did not find bidirectional causation.

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This bidirectional 2-sample Mendelian randomization study used European-heritage GWAS summary data from the IEU OpenGWAS project to test causal relationships between depression, anxiety, neuroticism, and endometriosis, applying IVW as the primary method with sensitivity analyses for heterogeneity, pleiotropy, and outlier instruments. For the forward direction, genetic predisposition to depression showed a statistically significant increase in endometriosis risk (IVW OR=1.151, 95% CI 1.025–1.293, P=.017), with consistent support from a weighted median approach; heterogeneity and horizontal pleiotropy were not detected (Cochran Q P=.98; MR-Egger intercept P=.33). The paper states a limitation that the available excerpt reports the anxiety results only up to the point where no evidence of a causal relationship was being described, and it does not provide full quantitative findings here for anxiety or neuroticism. This paper is centrally about endometriosis — specifically, it uses Mendelian randomization to estimate causal effects between depression, anxiety, neuroticism, and endometriosis.

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Abstract

Endometriosis, identified by the abnormal growth of endometrial cells beyond the inner lining of the uterus, often manifests through symptoms like painful menstruation and challenges in conceiving. Observational studies suggest that endometriosis is often comorbid with mental disorders, including anxiety and depression. The nature of these connections, whether they are causal, is still debated and calls for further empirical evidence. We utilized a bidirectional 2-sample Mendelian randomization (MR) approach, harnessing genome-wide association study data to explore the connections among depression, anxiety, neuroticism, and endometriosis. To scrutinize the causative connections between mental health issues and endometriosis, Inverse Variance Weighting (IVW) was employed as the primary analytical tool, complemented by Weighted Median Estimation, Simple mode, Weighted mode, and MR-Egger regression for additional analysis. To examine the potential for reverse causation, reverse MR was applied. To strengthen the reliability of our findings, we carried out sensitivity analyses that included heterogeneity tests, tests for pleiotropy, and leave-one-out analyses. The IVW analysis revealed a significant correlation between the genetic inclination towards depression and a heightened risk of developing endometriosis [Odds Ratio (OR) = 1.151, 95% Confidence Interval (CI) = 1.025-1.293, P = .017]. Similarly, a genetic predisposition to neuroticism was significantly associated with an increased risk of endometriosis (OR = 1.128, 95% CI = 1.038-1.226, P = .004). However, no causative link was found between genetic susceptibility to anxiety and the occurrence of endometriosis. Reverse MR analysis did not support a bidirectional genetic susceptibility between endometriosis and psychiatric disorders. The MR analysis presents genetic data supporting the notion that depression and neuroticism are risk factors for endometriosis. Conversely, it found no evidence of a causal connection between anxiety and the development of endometriosis. Enhancing mental health treatment should be considered a preventive measure against endometriosis.
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Section 5

Our study findings identified depression and neuroticism as causal factors for the risk of endometriosis, while no causal relationship was found between anxiety and the risk of endometriosis. Furthermore, there is no causal relationship between endometriosis and depression, anxiety, or neuroticism. Future research will necessitate larger sample sizes to confirm causal relationships and explore mechanisms from diverse perspectives. This study offers new insights into the prevention and treatment of endometriosis, suggesting that early provision of psychosocial support may be beneficial for women diagnosed with endometriosis in clinical practice.

Intro

In gynecology, endometriosis is recognized as a chronic inflammatory condition characterized by the abnormal growth of endometrial-like tissue outside the uterine lining, particularly on the pelvic peritoneum, ovaries, and rectovaginal septum. [ 1 ] It affects approximately 10% of women during their reproductive years, with infertility rates among these women reaching up to 50%. [ 2 , 3 ] While the etiology and progression of endometriosis remain largely unknown, factors involving hormonal, neural, and immune responses are considered key in symptom manifestation. [ 4 ] The primary symptoms include dysmenorrhea, chronic pelvic pain, dyspareunia, fatigue, and infertility, [ 5 , 6 ] with the nonspecific nature of these symptoms often leading to delayed diagnosis. [ 7 ] Endometriosis presents a chronic challenge in both diagnosis and treatment, demanding considerable time and medical resources and placing a significant economic and social strain on affected women. [ 8 ] In the United States, endometriosis-related healthcare expenditures are estimated to be around $22 billion yearly, while treatment, work absenteeism, and medical expenses in the UK amount to approximately £12.5 billion. [ 9 ] Furthermore, there is growing recognition that the experience of symptoms may be intertwined with psychological distress and associated emotional states, including depression and anxiety disorders. [ 10 ] There is a growing body of evidence linking endometriosis with neuropsychiatric conditions like anxiety, depression, and neuroticism. [ 11 ] Research indicates that endometriosis may adversely affect mental health, and women affected by the condition potentially may face an increased risk of psychological distress due to pain. [ 12 ] Moreover, studies have highlighted that concurrent conditions such as depression and anxiety can worsen endometriosis symptoms, contribute to a poorer prognosis, and diminish overall quality of life. [ 13 , 14 ] Neuroticism, a personality trait closely associated with negative emotions and a higher risk of psychiatric disorders, often manifests as emotional instability, irritability, anxiety, tension, and hypersensitivity. [ 15 ] This trait is connected to various health issues, both mental and physical, and research has found that individuals with endometriosis tend to report neuroticism scores above the norm. [ 16 , 17 ] The World Health Organization identifies anxiety and depressive disorders as leading contributors to the global disease burden. [ 18 ] Therefore, establishing causal relationships is imperative, as it could reveal whether interventions addressing mental health issues could potentially mitigate the burden of endometriosis, and vice versa. [ 19 ] Individuals affected by endometriosis often endure persistent, non pain, [ 20 ] intensifying the risk of developing depression and other mental health comorbidities. [ 21 ] In recent years, Mendelian randomization (MR) has emerged as a widely utilized approach for examining potential causal relationships between exposure factors and outcome variables from a genetic standpoint. MR utilizes ubiquitous genetic variants, known as single nucleotide polymorphisms (SNPs), as instrumental variables (IVs) for the purpose of approximating randomized controlled trials in the realm of genetics. This methodology capitalizes on the random assortment of alleles from parents to offspring, a process unaffected by common confounding factors such as environmental influences, socioeconomic status, and lifestyle choices. [ 22 , 23 ] MR benefits from a plausible temporal sequence for inferring causal associations, thereby mitigating confounding biases and the risk of reverse causation, resulting in research findings that closely reflect real-world scenarios. To explore the potential causal relationship between psychiatric disorders (such as anxiety, depression, and neuroticism) and endometriosis, we conducted a 2-sample MR analysis using publicly available genome-wide association study (GWAS) datasets.

Author

Conceptualization: Jiaxun Zhang. Writing – original draft: Jiaxun Zhang. Formal analysis: Tie Li, Jinying Zhao. Supervision: Tie Li. Data curation: Jiapeng Chai, Lin Wang. Investigation: Wenxuan Cao. Writing – review & editing: Jia Liu, Fuchun Wang. Funding acquisition: Fuchun Wang.

Methods

The IEU OpenGWAS project ( https://gwas.mrcieu.ac.uk ) provides the most comprehensive GWAS datasets available for psychiatric disorders and endometriosis, all of which pertain to individuals of European heritage. Psychiatric disorders encompass 3 phenotypes: depression, anxiety, and neuroticism. For depression, the research involved analyzing 24,184,163 SNPs across a sample size of 449,414 (13,559 cases and 435,855 controls). The anxiety study included 16,380,449 SNPs within 210,623 participants (12,513 cases and 198,110 controls). Neuroticism was explored through 9851,867 SNPs in a cohort of 374,323. For endometriosis, the dataset contained 16,377,306 SNPs among 77,257 individuals (8288 cases and 68,969 controls). The dataset’s detailed information is listed in Table 1 . GWAS data summary information in this study. GWAS = genome-wide association study, SNPs = single nucleotide polymorphisms. All analyses are based on publicly available data, and the initial research obtained ethical approval and consent. Therefore, ethical approval from an ethics committee is not required. For MR, IVs must satisfy 3 assumptions: [ 24 , 25 ] IVs must be closely related to the exposure; the instrument variable is unrelated to confounding factors; the instrument variable is associated with the outcome only through exposure. A bidirectional MR design overview for psychiatric disorders and endometriosis is presented in Figure 1 . Hence, we first selected SNPs for anxiety and depression traits with P  < 5 × 10 -6 indicating strong association. For neuroticism SNPs, due to their abundance, we set the threshold to P  < 5 × 10 -8 for strong association. [ 26 ] Secondly, we removed SNPs in linkage disequilibrium with r 2  < 0.001 and kb = 10,000 to ensure SNP independence. [ 27 ] Thirdly, we eliminated palindromic SNPs and extracted the remaining SNPs from GWAS results, excluding any missing SNPs. Fourthly, we executed a genome-wide significance search in the Phenoscanner V2 database for phenotypes associated with IVs to determine if these SNPs are linked to potential risk factors. [ 28 ] Finally, we quantified the robustness of genetic variation by calculating the F -statistic, with values under 10 indicating insufficient strength in the instrumental variable, leading to its exclusion. [ 29 ] To assess the effectiveness of the selected independent variables (IVs) more thoroughly, the calculation of the R 2 and F statistics for the SNPs was performed using the formulas: R 2 = 2 × E A F × ( 1 − E A F ) × β 2 , and the F statistic: F = [ R 2 × ( N − 2 ) ] / ( 1 − R 2 ) . [ 30 ] In this context, EAF stands for the effect allele frequency, β symbolizes the estimated genetic impact of each SNP on the exposure GWAS data, and N refers to the sample size of the exposure GWAS dataset. Exploring the bidirectional MR study design to assess the causal impact of psychiatric disorders on endometriosis. The red analysis focused on how the severity of psychiatric disorders might cause an increased risk of endometriosis, whereas the blue analysis investigated the opposite relationship. After completing these procedures, we selected specific SNPs as the ultimate IVs for conducting the 2-sample MR analysis. Additionally, to evaluate the likelihood of reverse causality, a reverse MR analysis was performed. When screening for SNPs associated with endometriosis, a P value < 5 × 10 −8 indicated a strong association, with other specific analytical processes being the same as those used in the 2-sample MR analysis. The primary strategy for establishing causality was the inverse variance weighting (IVW) method, [ 31 ] supplemented by additional techniques such as MR-Egger, [ 32 ] Weighted Median Estimation, [ 33 ] Simple mode, [ 34 ] and Weighted mode analyses. [ 34 ] These methods, utilizing SNPs as IVs, are specifically designed to validate the causal relationships between exposure factors and outcomes. For each approach, the Odds Ratio (OR), 95% Confidence Interval (CI), and P value were calculated. To ensure the robustness of our research, we employed various methods in our sensitivity analyses. These approaches included tests for heterogeneity, assessments of pleiotropy, and leave-one-out analyses to evaluate all our MR findings. [ 35 ] Multiple methods were employed for sensitivity analysis. Heterogeneity analysis was primarily conducted to check the consistency of selected SNPs in estimating causal effects. Cochran Q test was employed to evaluate the heterogeneity among individual SNP estimates in the IVW and MR-Egger models, where a statistically significant result suggests notable heterogeneity in the analysis. Assessing the presence of pleiotropy is crucial for evaluating the reliability of MR results. [ 36 ] The MR-Egger intercept test was used to measure pleiotropy levels among SNPs. When the intercept term achieves statistical significance in the MR-Egger test, it signals significant horizontal pleiotropy in the MR analysis. Additionally, a “leave-one-out” sensitivity analysis was conducted, involving the removal of individual SNPs to detect any outliers in IVs that could substantially impact the outcome. [ 37 ] The statistical evaluations were performed using R (version 4.3.2), employing the 2-sample MR (version 0.5.7) and MRPRESSO (version 1.0) packages to execute 2-Sample Mendelian Randomization (TSMR) studies. The criterion for statistical significance was a 2-sided P value of less than 0.05. No additional ethical approval was required because the current study was based on public data and published articles.

Results

By extracting outcome GWAS data and merging exposure and outcome datasets, while removing palindromic SNPs and outliers, we identified the final IVs to assess the causal association between depression, anxiety, neuroticism, and endometriosis consist of 21, 17, and 106 SNPs, respectively. In the reverse MR analysis, aimed at assessing the effect of endometriosis on depression, anxiety, and neuroticism, we extracted 11 SNPs for depression, 11 SNPs for anxiety, and 8 SNPs for neuroticism. The study revealed that the F-statistics for IVs in this MR analysis surpassed 20, suggesting minimal risk of weak instrumental variable bias, as demonstrated in S1, Supplemental Digital Content, http://links.lww.com/MD/N125 and S2, Supplemental Digital Content, http://links.lww.com/MD/N126 tables. Furthermore, after consulting the human genotype–phenotype association database, no SNPs associated with potential risk factors were identified. The MR findings regarding the impact of depression on endometriosis are illustrated in Figures 2 and 3 . Employing the IVW method with 21 depression-associated SNPs as IVs, a notable association was observed between genetic predisposition to depression and a heightened risk of developing endometriosis (OR = 1.151, 95% CI = 1.025–1.293, P  = .017). This association persisted in the weighted median analysis, indicating consistent results across different MR approaches. The Cochran Q test for heterogeneity showed no evidence of heterogeneity among the IVs according to the IVW and MR-Egger results ( P  = .98). Moreover, the MR-Egger regression indicated no signs of potential horizontal pleiotropy (Egger intercept = 0.013, P  = .33). A scatter plot further confirmed the absence of any directional pleiotropy, supporting the reliability of these results. Association between depression, anxiety, neuroticism, and endometriosis. SNPs = single nucleotide polymorphisms; MR = Mendelian randomization; OR = odds ratio; LCI = lower confidence intervals; UCI = upper confidence intervals. Effects of depression on endometriosis. (A) Forrest plot; (B) scatterplot; (C) leave-one-out plot. The MR findings regarding the influence of anxiety on endometriosis are illustrated in Figure 2 . Using 17 anxiety-associated SNPs as IVs and employing the IVW method, we found no evidence of a causal relationship between anxiety and endometriosis (OR = 1.042, 95% CI = 0.921–1.179, P  = .516). This conclusion remained consistent in the weighted median analysis, and the MR-Egger intercept test showed no indications of horizontal pleiotropy (Egger intercept = 0.011, P  = .43). The MR results concerning the impact of neuroticism on endometriosis are presented in Figures 2 and 4 . Analyzing 106 SNPs associated with neuroticism as IVs via the IVW method revealed compelling evidence linking neuroticism to an increased risk of endometriosis (OR = 1.128, 95% CI = 1.038–1.226, P  = .004; Figure 2 ). However, the IVW results ( P  = .01) and MR-Egger ( P  = .02) both demonstrate significant heterogeneity. Additionally, the MR-Egger regression did not suggest horizontal pleiotropy (Egger intercept = -0.015, P  = .21). Further validation through leave-one-out analysis and scatter plots confirmed that no single SNP was driving the observed causal relationship. Effects of neuroticism on endometriosis. (A) Forrest plot; (B) scatterplot; (C) leave-one-out plot. The MR findings regarding the influence of endometriosis on psychiatric disorders are illustrated in Figure 5 . Utilizing 11 SNPs associated with endometriosis as IVs, our analysis using the IVW method revealed no significant association with depression (OR = 0.997, 95% CI: 0.920–1.097, P  = .931). Similarly, the examination of anxiety using the same 11 SNPs showed no discernible causal connection (OR = 1.009, 95% CI: 0.947–1.074, P  = .791). Moreover, employing 8 SNPs linked to endometriosis for neuroticism analysis via the IVW method yielded no apparent causal link (OR = 1.010, 95% CI: 0.964–1.058, P  = .669). Therefore, the MR findings suggest no causal associations between endometriosis and either depression, anxiety, or neuroticism. Association between endometriosis and depression, anxiety, and neuroticism. SNPs = single nucleotide polymorphisms; MR = Mendelian randomization; OR = odds ratio; LCI = lower confidence intervals; UCI = upper confidence intervals.

Discussion

Numerous studies have explored the link between endometriosis and psychiatric disorders such as anxiety, depression, and neuroticism. [ 38 – 40 ] However, establishing a clear causal relationship between these conditions has proven elusive, with current observational studies deemed unreliable due to inherent biases and confounding factors. Despite various attempts to confirm a direct association, resolving this matter remains challenging. Certain studies suggest that psychological factors like anxiety and depression may adversely impact the physiological functions of endometriosis. [ 41 , 42 ] Further research has shown that individuals diagnosed with endometriosis exhibit a higher prevalence of anxiety and depression compared to their counterparts in control groups. [ 43 , 44 ] However, these investigations are constrained by their inability to establish a definitive causal link between anxiety, depression, and endometriosis, thus limiting their conclusions to mere correlations. Recognizing these limitations, we employed MR as a strategy to evaluate the potential roles of anxiety, depression, and neuroticism in the development of endometriosis. In our investigation, we applied the 2-sample MR approach to ascertain the causative connections between psychiatric conditions and endometriosis. The outcomes demonstrated a significant positive correlation between depression and neuroticism with endometriosis, but no causal relationship was observed between anxiety and the risk of developing endometriosis. Moreover, we ruled out the reverse causality between these psychiatric disorders and endometriosis. These findings offer fresh insights into the management and prevention of endometriosis. Significant heterogeneity was found in the SNPs for neuroticism, which might introduce a certain degree of bias into the results. Nevertheless, the heterogeneity was considered acceptable since we employed a random-effects model. Endometriosis, marked by menstrual pain and infertility, is a chronic condition necessitating prolonged management and treatment. [ 45 ] Available treatment modalities encompass hormonal medication, surgery, and psychological interventions. [ 46 – 48 ] As there is no definitive cure, treatment primarily targets symptom control and improvement. [ 49 ] Early diagnosis and effective treatment are imperative, underscoring the importance of employing tailored psychological therapy approaches to bolster prevention, early detection, and optimal disease management. [ 50 ] Meissner et al’s research demonstrated that psychosomatic therapy, utilizing somatosensory stimulation techniques including acupuncture, not only significantly improved the overall pain, physical, and mental quality of life for endometriosis patients within a 3-month follow-up but also sustained these improvements at 6 and 24 months post-therapy. [ 51 ] Similarly, Hansen et al observed noteworthy enhancements in pain management and quality of life through mindfulness and psychoeducation. [ 52 ] Given the intricate interplay between psychological and physiological processes, [ 53 ] studies have indicated that psychotherapy can facilitate neural transmission, mitigate stress responses, and regulate immune functions, offering a dual therapeutic benefit for both the disease and associated psychological concerns. [ 54 ] Given the decreased quality of life among women with endometriosis compared to those without the condition, psychological interventions capable of enhancing the quality of life are of considerable value. [ 55 ] Psychological stress can trigger elevated expression of inflammatory markers and other neurophysiological changes, [ 56 ] while psychotherapy, by mitigating psychological stress and bolstering emotional management skills, can indirectly ameliorate physiological symptoms and improve quality of life. Thus, within the framework of holistic medicine, managing endometriosis requires a comprehensive approach. In addition to conventional medical and surgical options, this encompasses lifestyle and dietary modifications, mental health interventions, and the utilization of alternative therapies. Depression and neuroticism may influence the occurrence and development of endometriosis through various mechanisms. Studies indicate that emotional or psychological disorders can alter visceral sensitivity by reducing pain thresholds, [ 57 ] and prolonged negative emotions such as depression and neuroticism can decrease these thresholds. Adverse psychological stimuli can activate the neurobiological pathway of the hypothalamic–pituitary–adrenal axis, [ 58 ] increasing the secretion of corticotropin-releasing hormone (CRH) and posterior pituitary hormones, leading to abnormal uterine contractions and localized ischemia, which trigger dysmenorrhea. [ 59 ] CRH, known for its pro-inflammatory properties, is highly expressed at endometriotic lesion sites. [ 60 ] Additionally, depression and neuroticism can result in unhealthy lifestyles and behaviors, including erratic eating patterns and insufficient physical activity, potentially elevating the risk of developing endometriosis. [ 61 – 63 ] Furthermore, a range of biological abnormalities related to depression and anxiety, including dysregulation of the neuroendocrine system and immune system modulation, may also contribute to a heightened risk of endometriosis. These mechanisms align with our research findings, further supporting the validity and importance of this theoretical model. We conducted a bidirectional MR study to elucidate the causal relationships between depression, anxiety, neuroticism, and endometriosis, facilitating further research. Our study offers the following advantages. This study is the first to employ bidirectional MR to explore the causal relationship between psychiatric disorders and endometriosis, effectively addressing the issue of reverse causation. In addition, we utilized publicly available databases and ensured the robustness of our results through stringent selection of IVs, multiple MR methods, and pleiotropy testing. Finally, all included populations were of European descent, which minimized confounding biases and provided more reliable causal inferences. This study has several limitations. Firstly, the study sample exclusively comprises individuals from European populations, without considering the potential confounding impact of racial factors on the mediation of endometriosis. Secondly, the observed phenotypic associations might be influenced by factors like depression and neuroticism, possibly increasing the diagnostic rate of endometriosis patients, and they may be associated with other comorbid diseases affecting the observed phenotypic associations. Lastly, the current scope of GWAS data lacks sufficient breadth; hence, further investigations using larger GWAS datasets are crucial.

Acknowledgments

For the data used in these analyses, we gratefully acknowledge the IEU open GWAS project ( https://gwas.mrcieu.ac.uk ).

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