Causal associations between systemic inflammation and polycystic ovary syndrome: a Mendelian randomisation study emphasising the role of CXCL11

Introduction

Polycystic ovary syndrome (PCOS) is a common and complex endocrine disorder affecting 11%–13% of women of reproductive age worldwide, with prevalence varying across ethnicities and diagnostic criteria.1 2 Characterised by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology, PCOS poses substantial challenges in both diagnosis and long-term management. In addition to reproductive implications, PCOS is associated with a wide range of metabolic disturbances—including insulin resistance, dyslipidaemia and obesity—as well as increased risks for type 2 diabetes, cardiovascular disease and psychological disorders.3 4

Recent studies have emphasised the critical role of chronic low-grade inflammation in the pathogenesis of PCOS. Elevated levels of proinflammatory markers such as interleukin-6 (IL-6), tumour necrosis factor-alpha, C-reactive protein and vascular endothelial growth factor have been consistently reported in women with PCOS.3 5–7 Furthermore, inflammatory pathways are tightly interconnected with endocrine and metabolic dysregulation—particularly hyperandrogenism and insulin resistance—creating a vicious cycle that exacerbates ovarian dysfunction.3 8 These insights suggest that immune-inflammatory mechanisms may represent a critical yet underexplored axis in the development and progression of PCOS.

However, most existing evidence is derived from cross-sectional or observational studies, which are inherently limited by confounding and reverse causation.9 Mendelian randomisation (MR) offers a robust alternative by using genetic variants as instrumental variables to infer potential causal relationships.10 Previous MR analyses have suggested associations between PCOS and certain inflammatory markers, yet the directionality and specificity of these associations remain poorly defined.5–7

Therefore, this study aims to investigate the causal relationships between systemic inflammatory cytokines and PCOS using a two-sample MR approach. By leveraging large-scale genome-wide association study (GWAS) data, we seek to clarify the causal roles of key inflammatory mediators in the pathophysiology of PCOS and, conversely, to determine whether PCOS itself influences systemic inflammatory profiles. This work may offer novel insights into disease mechanisms and identify potential targets for therapeutic intervention.

Materials and methods

Study overview

This MR study aimed to investigate the causal relationship between inflammatory cytokines and PCOS. The study adhered to the Strengthening the Reporting of Mendelian Randomization Studies guidelines and used publicly available datasets with prior ethical approval obtained for all original studies. A study diagram is provided in figure 1.

Figure 1

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Study flow diagram. This study performed a Mendelian randomisation analysis to determine if systemic inflammatory cytokines were causally associated with PCOS. PCOS, polycystic ovary syndrome; SNP: single nucleotide polymorphism.

Results

Sensitivity analyses and pleiotropy assessment

The MR-Egger regression analysis showed no evidence of directional pleiotropy for any of the four significant cytokines (figure 2). The intercept tests yielded non-significant results for C-X-C motif chemokine 11 (intercept=−0.0028, p=0.893), IL-13 (intercept=−0.0054, p=0.826), IL-10 (intercept=−0.0069, p=0.779) and adenosine deaminase (intercept=0.0089, p=0.794). Results of the horizontal pleiotropy analysis are presented in online supplemental Table S3.

Figure 2

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Circular plot of Mendelian randomisation study on inflammatory cytokines and PCOS by MR methods. Colours indicate beta values (red, high; blue, low). MR, Mendelian randomisation; PCOS, polycystic ovary syndrome.

Cochran’s Q statistics indicated no significant heterogeneity for C-X-C motif chemokine 11 (Q=21.1,p=0.969), IL-13 (Q=26.1, p=0.459) and adenosine deaminase (Q=1.4, p=0.839). IL-10 showed marginal evidence of heterogeneity (Q=42.9, p=0.060), but this did not substantially affect the main findings (online supplemental Table S4).

Individual single nucleotide polymorphism (SNP) effects and leave-one-out analysis

Leave-one-out sensitivity analyses demonstrated that no single SNP substantially influenced the overall causal estimates for any of the four cytokines (figure 3). Detailed SNP-specific results and their individual contributions to the causal estimates are presented in online supplemental Table S5. For C-X-C motif chemokine 11, all 36 SNPs showed consistent direction of effect, with rs148828177 showing the strongest individual effect.

Figure 3

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The causal relationships between systemic inflammatory cytokines and PCOS using different MR methods. Each panel represents the causal estimates for PCOS on a specific inflammatory cytokine: (A) C-X-C motif chemokine 11, (B) interleukin-13, (C) interleukin-10 (D) adenosine deaminase levels. The slope of each line corresponds to the causal estimates for each method. Individual SNP effects on the outcome (represented by points and vertical lines) against their effects on the exposure (represented by points and horizontal lines) are illustrated in the background. MR, Mendelian randomisation; PCOS, polycystic ovary syndrome; SNP, single nucleotide polymorphism.

Complementary analysis methods

The consistency of effect estimates across different MR methods (IVW, weighted median and weighted mode) further supported the robustness of our findings (figure 4). All four analytical approaches (IVW, MR-Egger, weighted median and weighted mode) showed consistent direction and magnitude of effects for the significant cytokines, particularly for C-X-C motif chemokine 11. Scatter plots of SNP effects on exposure vs outcome showed consistent patterns of association, particularly for C-X-C motif chemokine 11, which demonstrated the most stable and significant relationship with PCOS risk (figure 2).

Figure 4

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The leave-one-out plot of the causal relationships between four systemic inflammatory cytokines and PCOS. Each panel corresponds to MR estimates for a systemic inflammatory cytokine on PCOS: (A) C-X-C motif chemokine 11, (B) interleukin-13, (C) interleukin-10 and (D) adenosine deaminase levels. MR, Mendelian randomisation; PCOS, polycystic ovary syndrome.

Discussion

In this two-sample MR study, we explored the bidirectional causal relationship between systemic inflammatory regulators and the risk of PCOS. Our findings indicate that elevated levels of certain inflammatory markers—particularly CXCL11 and IL-13—may exert protective effects against PCOS, whereas PCOS itself appears to causally increase the levels of IL-10 and ADA. These insights shed new light on the complex interplay between inflammation and PCOS pathogenesis, underscoring the potential therapeutic utility of targeting inflammatory pathways in the management of PCOS.

CXCL11, a CXC chemokine that signals through the CXCR3 receptor, plays a central role in immune cell recruitment, particularly activated T cells and NK cells, to sites of inflammation or disease. Its dual functionality is evident in its pro-inflammatory role in autoimmune disorders and transplant rejection, as well as its immune-activating effects in cancer by promoting cytotoxic lymphocyte infiltration.19–21 These observations highlight the microenvironment-dependent regulation of adaptive immunity by CXCL11.

Our MR analysis revealed that genetically predicted higher circulating levels of CXCL11 were associated with a reduced risk of PCOS, suggesting a potential protective role of this chemokine in ovarian function. However, recent evidence highlights the context-dependent nature of CXCL11 in reproductive disorders. For instance, a study reported significantly elevated CXCL11 levels in the follicular fluid of patients with autoimmune thyroiditis (AIT), where it synergised with interferon-γ to recruit CXCR3+T lymphocytes, exacerbating ovarian inflammation and impairing folliculogenesis.22 This apparent contradiction—where CXCL11 appears protective in PCOS but pro-inflammatory in AIT—may reflect tissue-specific or disease-context-dependent pleiotropic effects. Additionally, a recent clinical study reported a strong correlation between serum CXCL11 levels and both prolactin and 17-OH progesterone levels in PCOS patients.23 These observations suggest that CXCL11 may influence key features of PCOS such as hyperandrogenism and dysregulation of the hypothalamic–pituitary–ovarian axis. Together, these findings support the emerging view of CXCL11 as a multifaceted player in PCOS pathophysiology. Therapeutic strategies targeting CXCL11 may thus require precision approaches, potentially involving tissue-specific delivery, to avoid paradoxical effects across different reproductive disorders.

Similarly, IL-13 demonstrated a nominally protective effect in our analysis, although this association did not remain statistically significant after correction for multiple testing. IL-13 is a well-characterised anti-inflammatory cytokine that modulates immune responses by promoting T-helper 2 cell differentiation and enhancing immune tolerance.24 In PCOS, dysregulated immune function contributes to chronic low-grade inflammation, which is thought to exacerbate the disorder’s metabolic and reproductive features. Several studies have shown that IL-13 may play a role in modulating key aspects of PCOS, including immune responses and inflammatory pathways. One study observed elevated IL-13 levels in the follicular fluid of PCOS patients, suggesting a potential role in modulating local immune responses.25 Another study reported that IL-13 may influence the balance between pro- and anti-inflammatory signals in PCOS, with effects that may vary according to body mass index.26 In addition, IL-13 has been shown to participate in immune regulation in obesity-related inflammation, a common feature of PCOS.27 While its association with PCOS risk was not statistically significant after multiple testing adjustment in our study, the directionality and consistency of the findings suggest that IL-13 may remain a relevant modulator of PCOS-associated immune dysfunction and merits further investigation.

In our study, genetically predicted levels of IL-10 and ADA were also nominally associated with reduced PCOS risk, although these associations did not meet statistical significance after correction. IL-10 is an anti-inflammatory cytokine known for suppressing pro-inflammatory responses and promoting immune tolerance.28 29 The nominal association observed here aligns with its immunoregulatory role and suggests a potential protective effect in PCOS. However, several observational studies have reported reduced circulating IL-10 levels in PCOS patients compared with healthy controls,30 31 suggesting a deficiency in anti-inflammatory signalling as a contributor to PCOS-associated inflammation. The discrepancy between our MR findings and previous observational studies may reflect differences in study design: MR relies on germline genetic variants as proxies for lifelong exposure, minimising confounding and reverse causation, whereas cross-sectional studies may capture disease-related secondary changes in cytokine levels.

ADA is a key enzyme in purine metabolism and is also involved in immune activation and T-cell function.32 33 Previous studies have reported increased ADA activity in women with PCOS, particularly in those with obesity or insulin resistance.34 35 In contrast, our MR analysis found a nominal inverse association between genetically predicted ADA levels and PCOS risk. This apparent inconsistency may reflect differences between genetically determined basal ADA expression and acquired elevations secondary to metabolic or inflammatory stress. It is also possible that different ADA isoforms, or tissue-specific expression patterns, exert divergent biological effects that are not adequately captured by current GWAS-based summary statistics. Future studies employing bidirectional MR, tissue-specific expression analyses and longitudinal inflammatory profiling are needed to further clarify the causal and temporal dynamics of ADA in PCOS pathogenesis.

The clinical implications of our findings are potentially important, as they suggest that therapeutic strategies targeting CXCL11—a cytokine with a robust inverse association with PCOS—may offer a novel avenue for disease management. Given the multifactorial nature of PCOS, interventions that modulate inflammatory signalling pathways involved in insulin resistance, hyperandrogenism and ovarian dysfunction may help alleviate both metabolic and reproductive manifestations of the disorder. Although IL-13, IL-10 and ADA showed nominal associations with reduced PCOS risk, these findings did not remain significant after correction for multiple testing and should be interpreted with caution. Further investigation is warranted to explore their potential roles in PCOS pathophysiology and therapeutic development.

Several limitations of our study should be noted. While MR provides a robust framework to infer causality, it relies on key assumptions, including the validity of genetic instruments, absence of horizontal pleiotropy and minimal confounding by population stratification. Although we performed comprehensive sensitivity analyses to address these issues, the possibility of residual bias cannot be excluded. In addition, our use of summary statistics from GWAS limits the assessment of population-specific effects, particularly in non-European populations with distinct genetic backgrounds. Finally, MR captures lifetime genetic predisposition and may not reflect dynamic or tissue-specific cytokine regulation.

In conclusion, our study provides genetic evidence supporting the role of systemic inflammation in PCOS, with CXCL11 emerging as a promising therapeutic target. Further studies in diverse populations and experimental models are needed to validate these findings.