Liu Siyuan, Li Fan, Cai Yunjia, Ren Linan, Sun Lin, Gang Xiaokun, Wang Guixia
Department of Endocrinology and Metabolism, The First Hospital of Jilin University, Changchun, Jilin, China.
Department of Gastroenterology, The First Hospital of Jilin University, Changchun, Jilin, China.
Front Cell Infect Microbiol. 2024 Feb 5;14:1352109. doi: 10.3389/fcimb.2024.1352109. eCollection 2024.
Numerous studies have demonstrated the influence of gut microbiota on the development of obesity. In this study, we utilized Mendelian randomization (MR) analysis to investigate the gut microbiota characteristics among different types of obese patients, aiming to elucidate the underlying mechanisms and provide novel insights for obesity treatment.
Two-sample multivariable Mendelian randomization (MR) analysis was employed to assess causal relationships between gut microbiota and various obesity subtypes. Gut microbiota data were obtained from the international consortium MiBioGen, and data on obese individuals were sourced from the Finnish National Biobank FinnGen. Eligible single-nucleotide polymorphisms (SNPs) were selected as instrumental variables. Various analytical methods, including inverse variance weighted (IVW), MR-Egger regression, weighted median, MR-RAPS, and Lasso regression, were applied. Sensitivity analyses for quality control included MR-Egger intercept tests, Cochran's Q tests, and leave-one-out analyses and others.
Mendelian randomization studies revealed distinct gut microbiota profiles among European populations with different obesity subtypes. Following multivariable MR analysis, we found that [: 0.842, : 0.766-0.926, Adjusted value: 0.028] independently reduced the risk of obesity induced by excessive calorie intake, while [: 4.252, : 2.177-8.307, Adjusted value: 0.002] independently increased the risk of medication-induced obesity. For localized adiposity, [: 0.213, : 0.115-0.395, Adjusted value: <0.001] acted as a protective factor. In the case of extreme obesity with alveolar hypoventilation, [: 0.724, : 0.609-0.860, Adjusted value: 0.035] reduced the risk of its occurrence. Additionally, six gut microbiota may have potential roles in the onset of different types of obesity. Specifically, the torques group may increase the risk of its occurrence. and may serve as protective factors in the onset of Drug-induced obesity. , , and , on the other hand, could potentially increase the risk of Drug-induced obesity. No evidence of heterogeneity or horizontal pleiotropy among SNPs was found in the above studies (all values for Q test and MR-Egger intercept > 0.05).
Gut microbiota abundance is causally related to obesity, with distinct gut microbiota profiles observed among different obesity subtypes. Four bacterial species, including , , and independently influence the development of various types of obesity. Probiotic and prebiotic supplementation may represent a novel approach in future obesity management.
众多研究已证明肠道微生物群对肥胖症发展的影响。在本研究中，我们利用孟德尔随机化（MR）分析来探究不同类型肥胖患者的肠道微生物群特征，旨在阐明潜在机制，并为肥胖症治疗提供新的见解。
采用两样本多变量孟德尔随机化（MR）分析来评估肠道微生物群与各种肥胖亚型之间的因果关系。肠道微生物群数据来自国际联盟MiBioGen，肥胖个体的数据则源自芬兰国家生物银行FinnGen。选择符合条件的单核苷酸多态性（SNP）作为工具变量。应用了多种分析方法，包括逆方差加权（IVW）、MR-Egger回归、加权中位数、MR-RAPS和套索回归。质量控制的敏感性分析包括MR-Egger截距检验、 Cochr an's Q检验、留一法分析等。
孟德尔随机化研究揭示了欧洲不同肥胖亚型人群中不同的肠道微生物群特征。经过多变量MR分析，我们发现[：0.842，：0.766 - 0.926，调整后值：0.028]独立降低了因热量摄入过多导致的肥胖风险，而[：4.252，：2.177 - 8.307，调整后值：0.002]独立增加了药物性肥胖的风险。对于局部肥胖，[：0.213，：0.115 - 0.395，调整后值：<0.001]起到保护作用。在伴有肺泡低通气的极端肥胖情况下，[：0.724，：0.609 - 0.860，调整后值：0.035]降低了其发生风险。此外，六种肠道微生物群可能在不同类型肥胖的发病中具有潜在作用。具体而言，torques组可能增加其发生风险。和可能在药物性肥胖的发病中作为保护因素。另一方面，、和可能潜在增加药物性肥胖的风险。在上述研究中未发现SNP之间存在异质性或水平多效性的证据（所有Q检验和MR-Egger截距的P值>0.05）。
肠道微生物群丰度与肥胖症存在因果关系，在不同肥胖亚型中观察到不同的肠道微生物群特征。四种细菌物种，包括、、和独立影响各种类型肥胖症的发展。补充益生菌和益生元可能是未来肥胖管理的一种新方法。
