Liu Xueying, Lin Zhongliang, Zhu Kejing, He Renke, Jiang Zhaoying, Wu Haiyan, Yu Jiaen, Luo Qinyu, Sheng Jianzhong, Pan Jiaxue, Huang Hefeng
Department of Obstetrics and Gynecology, Center for Reproductive Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
Key Laboratory of Reproductive Genetics, Department of Reproductive Endocrinology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Asia Pac J Clin Nutr. 2025 Feb;34(1):57-65. doi: 10.6133/apjcn.202502_34(1).0005.
Previous studies have reported there were associations between ovarian function and dietary factors, metabolic factors and gut microbiota. However, it is unclear whether causal associations exist. We aimed to explore the causal relationship of these factors with risk of primary ovarian failure (POF).
Two-sample Mendelian randomization (MR) analysis was performed to genetically predict the causal effects of dietary and metabolic factors and gut microbiota on POF. The inverse variance weighted (IVW) method was used as the primary statistical method. A series of sensitivity analyses, including weighted median, MR-Egger, simple mode, weighted mode methods, and leave-one-out analysis, were conducted to assess the robustness of the MR analysis results.
IVW analysis revealed that cigarettes smoked per day, coffee intake and cooked vegetable intake were not causally correlated with POF at the genetic level. However, POF were associated with fresh fruit intake, BMI, Eubacterium (hallii group), Eubacterium (ventriosum group), Adlercreutzia, Intestinibacter, Lachnospiraceae (UCG008), and Terrisporobacter. These findings were robust according to extensive sensitivity analyses.
This study identified several dietary factors, metabolic factors and gut microbiota taxa that may be causally implicated in POF, potentially offering new therapeutic targets.
既往研究报道卵巢功能与饮食因素、代谢因素及肠道微生物群之间存在关联。然而,因果关联是否存在尚不清楚。我们旨在探讨这些因素与原发性卵巢功能不全(POF)风险之间的因果关系。
采用两样本孟德尔随机化(MR)分析,从基因层面预测饮食、代谢因素及肠道微生物群对POF的因果效应。采用逆方差加权(IVW)法作为主要统计方法。进行了一系列敏感性分析,包括加权中位数法、MR-Egger法、简单模式法、加权模式法及逐一剔除分析,以评估MR分析结果的稳健性。
IVW分析显示,每日吸烟量、咖啡摄入量及熟蔬菜摄入量在基因水平上与POF无因果关联。然而,POF与新鲜水果摄入量、体重指数、真杆菌(哈氏菌群)、真杆菌(腹菌菌群)、 Adlercreutzia菌属、肠杆菌属、毛螺菌科(UCG008)及地芽孢杆菌属有关。根据广泛的敏感性分析,这些发现具有稳健性。
本研究确定了几种可能与POF存在因果关系的饮食因素、代谢因素及肠道微生物分类群,可能提供新的治疗靶点。