Li Xiaopei, Li Yan, Zhang Bumei, Wang Jianmei, Yang Yang, Du Yongrui
Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin, China.
Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
J Ovarian Res. 2025 Apr 3;18(1):69. doi: 10.1186/s13048-025-01647-w.
Polycystic ovary syndrome is a prevalent gynecological condition affecting primarily women of childbearing age. It is characterized by elevated androgen levels, ovulatory dysfunction, and morphological abnormalities. Despite extensive research from various perspectives, the etiology and pathogenesis of PCOS remain unclear. While controversial, many believe that individuals with PCOS exhibit a chronic low-grade inflammatory state. Cytokines play diverse roles in the initiation and progression of inflammation, contributing to this inflammatory milieu. Therefore, the aim of this study was to utilize publicly available genome-wide association study data to explore the potential causal relationship between cytokines and PCOS.
To accurately investigate the causal relationship between cytokines and PCOS, we initially defined cytokines using the GeneCrad and then identified cytokines in two independent large-scale plasma proteins. Subsequently, we employed a two-sample Mendelian randomization analysis framework. A series of quality control procedures were implemented to select eligible instrumental variables closely associated with the exposure. MR analysis was conducted using genome-wide association studies of PCOS in two independent European ancestry groups. Cochran, s Q test, MR-Egger and intercept test were employed to assess heterogeneity and pleiotropy in PCOS. Co-localization analysis, summary-data-based Mendelian randomization analysis, and HEIDI testing were utilized to further corroborate the relationship between positive findings and PCOS. Finally, systematical Mendelian randomization analysis between healthy lifestyle factors and PCOS-related proteins was conducted to identify which proteins could act as interventional targets by lifestyle changes.
In our investigation, we performed Mendelian randomization analysis on 33 cytokines in relation to PCOS using data from the deCODE and the Fenland. Our findings revealed that the plasma level of IL6R emerges as a notable protective factor against PCOS, exhibiting a substantial effect size. Moreover, we identified CCL22 as a significant risk factor for PCOS, a finding that was similarly validated and supported by independent cohorts.
Our Mendelian randomization analysis, leveraging genome-wide association study data from a sizable population cohort, unequivocally delineated a causal relationship between IL6R and PCOS. These results underscore the involvement of cytokines in the pathogenesis of PCOS and highlight their potential as promising therapeutic targets for addressing this intricate disease.
多囊卵巢综合征是一种常见的妇科疾病，主要影响育龄女性。其特征为雄激素水平升高、排卵功能障碍和形态异常。尽管从各种角度进行了广泛研究，但多囊卵巢综合征的病因和发病机制仍不清楚。虽然存在争议，但许多人认为多囊卵巢综合征患者表现出慢性低度炎症状态。细胞因子在炎症的起始和进展中发挥着多种作用，促成了这种炎症环境。因此，本研究的目的是利用公开可用的全基因组关联研究数据，探索细胞因子与多囊卵巢综合征之间的潜在因果关系。
为了准确研究细胞因子与多囊卵巢综合征之间的因果关系，我们首先使用GeneCrad定义细胞因子，然后在两个独立的大规模血浆蛋白中鉴定细胞因子。随后，我们采用了两样本孟德尔随机化分析框架。实施了一系列质量控制程序，以选择与暴露密切相关的合格工具变量。使用两个独立的欧洲血统群体的多囊卵巢综合征全基因组关联研究进行孟德尔随机化分析。采用 Cochr an's Q检验、MR-Egger和截距检验来评估多囊卵巢综合征中的异质性和多效性。共定位分析、基于汇总数据的孟德尔随机化分析和HEIDI检验被用于进一步证实阳性结果与多囊卵巢综合征之间的关系。最后，对健康生活方式因素与多囊卵巢综合征相关蛋白之间进行系统的孟德尔随机化分析，以确定哪些蛋白可以通过生活方式改变作为干预靶点。
在我们的研究中，我们使用来自deCODE和Fenland的数据对33种与多囊卵巢综合征相关的细胞因子进行了孟德尔随机化分析。我们的研究结果表明，IL6R的血浆水平是预防多囊卵巢综合征的一个显著保护因素，具有很大的效应量。此外，我们确定CCL22是多囊卵巢综合征的一个重要危险因素，这一发现同样得到了独立队列的验证和支持。
我们的孟德尔随机化分析利用了来自大量人群队列的全基因组关联研究数据，明确界定了IL6R与多囊卵巢综合征之间的因果关系。这些结果强调了细胞因子参与多囊卵巢综合征的发病机制，并突出了它们作为治疗这一复杂疾病的有前景的治疗靶点的潜力。
