This study utilized Mendelian randomization (MR) analysis to explore the causal relationship between circulating cytokines and polycystic ovary syndrome (PCOS), and to identify potential biomarkers of PCOS mechanisms. Genetic instrumental variables for cytokines were derived from 2 large-scale genome-wide association studies (GWAS) involving 8293 and 14,824 European participants. Summary statistics from a GWAS meta-analysis (10,074 PCOS cases and 103,164 controls of European ancestry) were used in the discovery phase of MR analysis. Replication analysis utilized another GWAS meta-analysis dataset (3609 cases and 229,788 controls). The primary analysis employed the inverse-variance weighted (IVW) method, with secondary methods including constrained maximum likelihood model averaging, weighted median, and weighted mode. Meta-analysis was combined with MR results, while heterogeneity and horizontal pleiotropy were assessed using leave-one-out, MR-Egger intercept test, and Mendelian Randomization Pleiotropy Residual Sum and Outlier. Sensitivity analysis confirmed the robustness of the results. Reverse MR analysis was used to explore the association of PCOS with the identified cytokines. Meta-analysis revealed that increased CCL4 (C-C motif chemokine 4) levels were associated with a higher risk of PCOS (odds ratio [OR] = 1.123, 95% confidence interval [CI]: 1.056-1.195
P <
.002). Decreased PCOS risk was linked to CXCL11 (C-X-C motif chemokine 11, OR = 0.930, 95% CI: 0.890-0.970
IVW-false discovery rate [FDR] P = 4.85 × 10-4) and CD6 (T-cell surface glycoprotein CD6 isoform, OR = 0.730, 95% CI: 0.890-0.970
IVW-FDR P = .008). Sensitivity analysis confirmed the robustness of the findings. MR analysis suggests a potential causal link between alterations in CCL4, CXCL11, CD6, and PCOS risk, highlighting the role of cytokines in PCOS development and progression, warranting further investigation.