Ren Qiqi, Cui Congshong, Peng You, Zhou Yingling, Zhang Hang, Chen Lin, Liu Zhenjie
Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Medicine (Baltimore). 2025 Apr 25;104(17):e42179. doi: 10.1097/MD.0000000000042179.
Metabolic syndromes (MetS) are complex metabolic disorders, the pathogenesis of which has not been fully elucidated. In recent years, the association between the gut microbiota and MetS has attracted widespread attention, but the causal relationship remains unclear. We performed a 2-sample Mendelian randomization analysis (MR) to examine whether the gut microbiota is causally related to MetS and its components to find a basis for potential diagnostic or intervention approaches for MetS. We utilized summary statistics from whole-genome association analyses of gut microbiota from the MiBioGen consortium and obtained MetS-related data from the UK Biobank, IEU Open GWAS project, and The Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC). MR analyses were performed using inverse variance weighted, MR-Egger, and weighted median. Sensitivity analyses were conducted to verify the robustness of the results. Among the 211 gut microbiota, we identified 8 that were significantly associated with the risk of MetS. Specifically, Lachnospiraceae (family), Veillonellaceae (family), Victivallaceae (family), Odoribacter (genus), and Olsenella (genus) may increase the risk of MetS, while Bifidobacteriaceae (family), Ruminococcaceae UCG-010 (genus), Actinobacteria (phylum) may decrease the risk of MetS. Additionally, we discovered that multiple microbiota are associated with various components of MetS, such as BMI, hypertension, and blood lipid levels. This study is the first to use MR methods to reveal the potential causal relationship between specific gut microbiota and MetS, providing a new perspective for understanding the pathogenesis of MetS, and offering important evidence for the development of gut microbiota-based prevention and treatment strategies for MetS.
代谢综合征（MetS）是复杂的代谢紊乱疾病，其发病机制尚未完全阐明。近年来，肠道微生物群与MetS之间的关联引起了广泛关注，但因果关系仍不明确。我们进行了一项两样本孟德尔随机化分析（MR），以检验肠道微生物群与MetS及其组成成分是否存在因果关系，从而为MetS潜在的诊断或干预方法寻找依据。我们利用了来自MiBioGen联盟肠道微生物群全基因组关联分析的汇总统计数据，并从英国生物银行、IEU开放GWAS项目以及葡萄糖和胰岛素相关性状荟萃分析联盟（MAGIC）获得了与MetS相关的数据。使用逆方差加权、MR-Egger和加权中位数进行MR分析。进行敏感性分析以验证结果的稳健性。在211种肠道微生物群中，我们鉴定出8种与MetS风险显著相关。具体而言，毛螺菌科（科）、韦荣球菌科（科）、胜利菌科（科）、气味杆菌属、奥尔森菌属可能会增加MetS风险，而双歧杆菌科（科）、瘤胃球菌科UCG-010（属）、放线菌门可能会降低MetS风险。此外，我们发现多种微生物群与MetS的各种组成成分相关，如体重指数、高血压和血脂水平。本研究首次使用MR方法揭示特定肠道微生物群与MetS之间的潜在因果关系，为理解MetS的发病机制提供了新视角，并为制定基于肠道微生物群的MetS防治策略提供了重要证据。
