Polycystic ovary syndrome (PCOS) is a widespread endocrine condition that primarily affects women during their reproductive years. It is characterized by several typical clinical features, including hyperandrogenism (acne, hirsutism, and alopecia), menstrual irregularity (long menstrual cycles, oligo/anovulation), and the presence of polycystic ovaries [1, 2]. It has been estimated that in 2019, approximately 66.0 (95% uncertainty interval (UI): 46.0–86.3) million individuals were affected by PCOS worldwide, with an overall prevalence rate of 829.6 per 100,000 [3].

Despite the precise etiology and pathogenesis of PCOS remaining uncertain, available evidence suggests that its occurrence is shaped by a blend of genetic and environmental factors. Established risk factors for PCOS encompass genetic susceptibility [4], obesity [5] and insulin resistance (IR) [6, 7]. Vink et al. [4] conducted a study revealing that the similarity of PCOS among monozygotic twin sisters (tetrachoric r${}^{\mathrm{2}}$ 0.71) was approximately twice as pronounced compared to dizygotic twins or other sisters (tetrachoric r${}^{\mathrm{2}}$ 0.38). In recent times, there has been a heightened recognition of the detrimental effects of PCOS on psychological well-being [8]. In a meta-analysis conducted by Brutocao et al. [9], which included 57 studies and a total of 172,040 patients, it was discovered that women diagnosed with PCOS had a higher likelihood of experiencing clinical depression (odds ratio (OR) = 2.79; 95% confidence interval (CI): 2.23–3.50), anxiety (OR = 2.75; 95% CI: 2.10–3.60), bipolar disorder (OR = 1.78; 95% CI: 1.43–2.23), and obsessive-compulsive disorder (OR = 1.37; 95% CI: 1.22–1.55). Likewise, in a meta-analysis conducted by Cooney et al. [10], which covered 30 cross-sectional studies across 10 countries, it was observed that women diagnosed with PCOS had a higher probability of experiencing moderate to severe symptoms of depression and anxiety compared to non-PCOS controls.

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that arises and persists after an individual personally experiences, witnesses, or is confronted with one or more traumatic events. These events can involve the individual themselves or others, and the resulting symptoms can endure for a significant period of time, affecting their mental and emotional well-being [11]. The presence of comorbid mental disorders, including major depression, is commonly observed in individuals with PTSD. Moreover, those affected by PTSD face an elevated risk of suicidal ideation, substance abuse, and impaired occupational functioning [12]. Multiple medical conditions have been associated with a heightened vulnerability for developing PTSD. A recent meta-analysis revealed that the combined prevalence rate of PTSD among children and adolescents diagnosed with cancer was about 20.90% (95% CI: 13.28–29.73%) [13]. Among adult patients, in turn, there is a higher prevalence of post-traumatic stress disorder (PTSD) observed in those with chronic heart diseases (CHDs) when compared to those without CHDs (0.8% vs. 0.5%; adjusted prevalence ratio (Apr): 1.5, 95% CI: 1.2–1.8). [14]. In addition, a study conducted by Tay et al. [15] revealed that women with PCOS had a notably higher prevalence of PTSD compared to women without PCOS (adjusted odds ratio (OR) = 1.5, 95% confidence interval (CI): 1.1–1.9). Nevertheless, as this finding stems from a conventional observational epidemiological study, it is susceptible to potential biases, including confounding and reverse causation. Therefore, the causal relationship of the observed association remains ambiguous.

Mendelian randomization (MR) is a genetic epidemiological method that leverages single nucleotide polymorphisms (SNPs) strongly associated with the exposure of interest as instrumental variables (IVs). This approach enables the estimation of potential causal relationships between the exposure and the outcome in question [16]. Assuming that genotypes are randomly allocated during gamete formation and disease onset, the application of the IV approach effectively addresses the problems of confounding and reverse causation commonly encountered in observational studies. This approach helps address these concerns to a considerable extent [17, 18]. Therefore, the present study implemented a two-sample Mendelian randomization (MR) analysis to investigate the possible causal relationship between PCOS and PTSD.

The F-statistics for the IVs chosen for PCOS ranged from 30.64 to 57.45, while for PTSD they ranged from 30.25 to 38.44. These values $>$10 indicate that the IVs were less susceptible to weak instrument bias (Table 1).

Genetic predisposition to PCOS was found to be associated with an elevated risk of developing PTSD (OR = 1.11, 95% CI: 1.03–1.19, p = 7.27 $\times$ 10${}^{-3}$ for IVW) (Fig. 2). Sensitivity analyses using alternative MR methods consistently showed a statistically significant association, with similar effect estimates. Specifically, the maximum-likelihood method yielded an odds ratio (OR) of 1.11 (95% CI: 1.02–1.21, p = 0.021), and the MR-RAPS method yielded an OR of 1.12 (95% CI: 1.03–1.21, p = 6.76 $\times$ 10${}^{-3}$). The absence of outlier SNPs detected through the MR-PRESSO test strengthens the reliability of our findings. Moreover, the estimation between genetic predisposition to PCOS and the increasing risk of PTSD remained consistent, with comparable results (OR = 1.11, 95% CI: 1.02–1.21, p = 0.039). These additional findings further support the robustness of the observed relationship between PCOS genetics and the development of PTSD. MR-Egger regression analysis did not provide significant evidence of directional pleiotropy (p intercept = 0.187). This indicates that the basic assumption of Mendelian randomization is upheld and suggests that there is no substantial bias due to pleiotropic effects in our study (Fig. 3).

Fig. 2.

MR effect estimates for associations of exposures with the risk of outcomes. *p-value of the intercept from MR-Egger regression. SNP, single nucleotide polymorphism; MR-RAPS, Mendelian randomization-Robust Adjusted Profile Score; MR-PRESSO, MR Pleiotropy RESidual Sum and Outlier; PCOS, polycystic ovary syndrome; PTSD, post-traumatic stress disorder; OR, odds ratio; CI, confidence interval.

Fig. 3.

Plot of the effect size and 95% CIs of each SNP on PCOS and PTSD risk. The x-axis plots the previously published b-estimate for the association of each SNP with PCOS. The y-axis plots the bestimate for the association of each SNP with risk of PTSD. Error bars indicate 95% CIs of the effect estimates. Slopes of the orange green blue and purple lines represent the combined causal effect estimates using the IVW method, maximum-likelihood method, MR-PRESSO test and MR-RAPS method. IVW, inverse-variance weighted; SNP, single nucleotide polymorphism; MR-RAPS, Mendelian randomization-Robust Adjusted Profile Score; MR-PRESSO, MR Pleiotropy RESidual Sum and Outlier; PCOS, polycystic ovary syndrome; PTSD, post-traumatic stress disorder.

During our scan of the SNPs assigned as IVs in the GWAS Catalog, we obtained three SNPs (rs11031005, rs13164856, and rs2271194) that showed associations with other traits or phenotypes (Supplementary Table S2). After excluding these SNPs, the association between PCOS and PTSD remained statistically significant (OR = 1.09, 95% CI: 1.00–1.20, p = 0.044) using the IVW method, indicating that the relationship between PCOS and PTSD is robust even without these particular SNPs.

The reverse MR analysis indicated that genetic predisposition to PTSD was not significantly associated with the risk of PCOS (OR = 1.15, 95% CI: 0.69–1.91, p = 0.586) using the IVW method. The sensitivity analyses, including the maximum-likelihood method (OR = 1.15, 95% CI: 0.69–1.91, p = 0.587) and MR-RAPS (OR = 1.15, 95% CI: 0.67–1.98, p = 0.613), consistently yielded similar causal effect estimates (Fig. 2). The results from leave-one-out method illustrated that the combined effect estimates were consistent after removing SNPs in turn (Supplementary Fig. S1).

In this study, we employed a bidirectional MR approach to examine the potential causal link between PCOS and PTSD. Our findings revealed a significant causality between genetic susceptibility to PCOS and the developing risk of PTSD. The results remained consistent and robust across various sensitivity analyses utilizing different MR methods and alternative instrumental variable sets. These results indicate the stability of our findings. Conversely, we observe non-significant evidence between genetic predisposition to PTSD and the increasing risk of PCOS.

Previous observational studies have demonstrated a significant association of PCOS condition and PTSD onset. For instance, a cross-sectional analysis including 89 women with PCOS and 456 women without PCOS revealed that PCOS was strongly associated with an increased risk of PTSD (OR = 2.2, 95% CI: 1.7–2.8, p 0.001). Even when consider multiple important factors such as body mass index (BMI), education, employment, smoking status, alcohol use, physical activity level, adverse childhood experience, social support, and perceived stress, the association between PCOS and PTSD remained robust. After adjusting for these confounding variables, the odds of developing PTSD were still significantly higher in individuals with PCOS (adjusted odds ratio = 1.5, 95% CI: 1.1–1.9, p = 0.008). This suggests that PCOS is independently associated with an increased likelihood of experiencing PTSD [15]. Our findings consistently demonstrated that genetically predicted PCOS was associated with a heightened risk of developing PTSD. By leveraging the assumption that exposure-related genetic variants are randomly allocated during conception, we utilized genetic variants associated with PCOS risk as instrumental variables. This approach allowed us to assess the impact of PCOS on the likelihood of developing PTSD, while minimizing the influence of confounding factors such as socioeconomic status or education level, as well as the potential bias from reverse causation.

Psychiatric disorders in individuals with PCOS are influenced by intricate mechanisms. One contributing factor is the presence of PCOS-related manifestations, including acne, hirsutism, obesity, and infertility. These physical features can potentially diminish self-esteem and amplify psychological distress among affected women. Furthermore, hormonal imbalances associated with PCOS can also impact mental well-being. A study by Marsh et al. [27] demonstrated that individuals with PCOS exhibited lower levels of positive mood and higher levels of trait anxiety in comparison to control groups. Moreover, elevated levels of total testosterone and insulin, as well as insulin resistance, were found to be associated with increased scores in trait anger and anger expression [28]. The hormonal imbalance in individuals with PCOS can also impact the microstructure of white matter, thereby affecting cognitive function [29] and work efficiency [30] in PCOS patients. Furthermore, hyperparathyroidism is a significant clinical manifestation observed in PCOS, and it can influence mood disorders and impulsivity in both women with and without PCOS [28, 31, 32]. Lastly, there is evidence suggesting that women with PCOS may exhibit an increased responsiveness of the hypothalamic-pituitary-adrenal (HPA) axis, which could contribute to the development of psychiatric disorders through disrupted stress responses [33, 34]. While these explanations offer biologically plausible connections, additional research is needed to elucidate the precise underlying mechanisms through which PCOS contributes to the development of PTSD.

The application of genetic variants as IVs in MR analyses greatly addresses the challenge of confounding present in conventional observational studies. Nevertheless, it is important to acknowledge several limitations in our study. Certain limitations should be considered when interpreting the results of our study. Firstly, the participants were predominantly of European descent, which raises the question of generalizability to other ethnic populations. Additional research is warranted to assess the generalizability of our findings across diverse populations. Furthermore, it is worth noting that the lack of a statistically significant association between PTSD and PCOS in our study may be influenced by the limited statistical power and the relatively small size of the instrumental variable used in the Mendelian randomization analysis. Thus, additional studies with larger sample sizes are warranted to further investigate the potential relationship between PTSD and PCOS. To address concerns regarding the validity of the MR study, we took measures to ensure the selection of appropriate instrumental variables (IVs). Specifically, we included independent SNPs that reached the genome-wide significance level (p 5 $\times$ 10${}^{-8}$) and demonstrated strong instrument strength (i.e., F-statistic $>$10) in our analysis. Additionally, we applied a linkage disequilibrium (LD) threshold of r${}^{\mathrm{2}}$ 0.01 to avoid the inclusion of SNPs in high LD. These rigorous criteria were implemented to enhance the reliability of our results and minimize potential biases associated with instrumental variable selection. Finally, one potential limitation of our MR study is the presence of pleiotropy. To address this concern, we conducted various MR approaches to examine the possibility of pleiotropic effects. Fortunately, our findings did not indicate any evidence of pleiotropy affecting the causal relationship between PCOS and the risk of developing PTSD. Moreover, we took an additional step to mitigate potential pleiotropic effects by specifically selecting SNPs that were solely associated with the exposures of interest. We accomplished this by excluding SNPs associated with other phenotypes, as determined through the GWAS Catalog. By employing these strategies, we aimed to minimize the impact of pleiotropy on our results and enhance the validity of our findings.

Through the utilization of a genetic epidemiological approach, our study revealed a potential causality between genetic predisposition to PCOS and an increasing odd of PTSD. This finding indicates a potential causal relationship between PCOS and PTSD. Nevertheless, it is crucial to delve deeper into the underlying mechanisms that link PCOS to the development of PTSD. Further investigation in this area will provide valuable insights and contribute to a comprehensive understanding of the interplay between PCOS and PTSD.

CI, confidence interval; GWAS, genome-wide association studies; IV, instrumental variable; IVW, inverse-variance weighted; LD, linkage disequilibrium; MR, mendelian randomization; OR, odds ratio; PCOS, polycystic ovary syndrome; PGC-PTSD, Psychiatric Genomics Consortium Post-traumatic Stress Disorder; PRESSO, Pleiotropy RESidual Sum and Outlier; PTSD, post-traumatic stress disorder; RAPS, Robust Adjusted Profile Score; SNPs, single nucleotide polymorphisms.

The datasets generated and/or analyzed during the current study are available in the genome-wide association studies repository. (PCOS: https://doi.org/10.17863/CAM.36024. PTSD: https://www.med.unc.edu/pgc/download-results/)

XZ and JS performed the literature review, conducted data analysis, interpreted findings, and drafted the manuscript. BL and MCD carried on data analysis and interpreted findings. BXW, XWC and YFH mainly conducted on the data collation and checked the manuscript. YYM and FQ directed analytic strategy, supervised the study from conception to completion and revised drafts of the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work to take public responsibility for appropriate portions of the content and agreed to be accountable for all aspects of the work in ensuring that questions related to its accuracy or integrity.

Since this project is based on the statistical analysis of publicly available databases and published studies, ethics approval and consent to participate is not applicable.

The author sincerely thanks the researchers and participants of the original GWAS for their collection and management of large-scale data resources, as well as those who actively participated in this study.

This research was funded by National Natural Science Foundation of China (No. 82074476); Traditional Chinese Medicine Scientific Project of Zhejiang Province for the Excellent Young Scholars (No. 2021ZQ055).

The authors declare no conflict of interest. Fan Qu is serving as one of the Guest editors of this journal. We declare that Fan Qu had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to Michael H. Dahan.