Jia Ming-Jie, Zhou Li, Liu Xing-Ning, Li Hui-Lin
The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Institute of Depression and Comorbidity, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Front Med (Lausanne). 2024 Dec 3;11:1433612. doi: 10.3389/fmed.2024.1433612. eCollection 2024.
To investigate the association between polycystic ovary syndrome (PCOS) and inflammatory proteins, and to identify and quantify the role of serum metabolites as potential mediators.
Utilizing summary-level data from a genome-wide association study (GWAS), we conducted a two-sample Mendelian Randomization (MR) analysis, a genetic approach that uses genetic variants as instrumental variables to assess the causal relationships between risk factors and outcomes. This analysis involved genetically predicted PCOS (1,639 cases and 218,970 controls) and inflammatory proteins (14,824 participants of primarily European descent). Additionally, a two-step MR analysis was performed to quantify the proportion of the effect of serum metabolites-mediated inflammatory proteins on PCOS. The Inverse Variance Weighted (IVW) method, a statistical technique used within MR to combine data from multiple genetic variants, was used to estimate the causal effects.
The IVW method revealed that the inflammatory proteins IFN-γ (-value = 0.037, OR = 1.396, 95% CI = 1.020-1.910) and CCL7 (-value = 0.033, OR = 1.294, 95% CI = 1.021-1.641) were associated with an increased risk of PCOS, while IL-6 (-value = 0.015, OR = 0.678, 95% CI = 0.495-0.929) and MMP-10 (-value = 0.025, OR = 0.753, 95% CI = 0.587-0.967) were associated with a decreased risk. No significant evidence suggested an effect of genetically predicted PCOS on inflammatory proteins. The serum metabolite X-11444 was found to mediate 5.44% (95% CI: 10.8-0.0383%) of the effect of MMP-10 on PCOS.
This study not only introduces novel causal associations between inflammatory proteins and PCOS but also highlights the mediating role of serum metabolites in these associations. By applying MR, we were able to minimize confounding and reverse causality, offering robust insights into the biological mechanisms underlying PCOS. These findings advance the understanding of PCOS pathogenesis, particularly in relation to inflammatory pathways and serum metabolite interactions, and suggest potential therapeutic targets that could inform future clinical interventions aimed at mitigating inflammation-related PCOS risks.
研究多囊卵巢综合征（PCOS）与炎症蛋白之间的关联，并确定和量化血清代谢物作为潜在介导因子的作用。
利用全基因组关联研究（GWAS）的汇总水平数据，我们进行了两样本孟德尔随机化（MR）分析，这是一种利用基因变异作为工具变量来评估风险因素与结局之间因果关系的遗传方法。该分析涉及基因预测的PCOS（1639例病例和218970例对照）和炎症蛋白（主要为欧洲血统的14824名参与者）。此外，进行了两步MR分析以量化血清代谢物介导的炎症蛋白对PCOS影响的比例。使用逆方差加权（IVW）方法（一种在MR中用于合并来自多个基因变异数据的统计技术）来估计因果效应。
IVW方法显示，炎症蛋白IFN-γ（P值=0.037，OR=1.396，95%CI=1.020-1.910）和CCL7（P值=0.033，OR=1.294，95%CI=1.021-1.641）与PCOS风险增加相关，而IL-6（P值=0.015，OR=0.678，95%CI=0.495-0.929）和MMP-10（P值=0.025，OR=0.753，95%CI=0.587-0.967）与风险降低相关。没有显著证据表明基因预测的PCOS对炎症蛋白有影响。发现血清代谢物X-11444介导了MMP-10对PCOS影响的5.44%（95%CI：10.8-0.0383%）。
本研究不仅揭示了炎症蛋白与PCOS之间新的因果关联，还突出了血清代谢物在这些关联中的介导作用。通过应用MR，我们能够最大限度地减少混杂因素和反向因果关系，为PCOS潜在的生物学机制提供有力见解。这些发现推进了对PCOS发病机制的理解，特别是在炎症途径和血清代谢物相互作用方面，并提示了潜在的治疗靶点，可为未来旨在减轻与炎症相关的PCOS风险的临床干预提供参考。
