Summary statistics of 191 gut microbiota traits (N = 18,340), 1,400 plasma metabolite traits (N = 8,299), 128 peripheral cell counts (blood cells, N = 408,112; immune cells, N = 3,757), 41 inflammatory cytokine traits (N = 8,293), and 6 obesity traits were obtained from publicly available genome-wide association studies. Two-sample Mendelian randomization (MR) analysis was applied to infer the causal links using inverse variance-weighted, maximum likelihood, MR-Egger, weighted median, weighted mode, and Wald ratio methods. Several sensitivity analyses were also utilized to ensure reliable MR results. Finally, we used mediation analysis to identify the pathway from gut microbiota to obesity mediated by plasma metabolites, peripheral cells, and inflammatory cytokines.
MR revealed a causal effect of 44 gut microbiota taxa, 281 plasma metabolites, 27 peripheral cells, and 8 inflammatory cytokines on obesity. Among them, five shared causal gut microbiota taxa belonged to the phylum Actinobacteria, order Bifidobacteriales, family Bifidobacteriaceae, genus Lachnospiraceae UCG008, and species Eubacterium nodatum group. Furthermore, we screened 42 shared causal metabolites, 7 shared causal peripheral cells, and 1 shared causal inflammatory cytokine. Based on known causal metabolites, we observed that the metabolic pathways of D-arginine, D-ornithine, linoleic acid, and glycerophospholipid metabolism were closely related to obesity. Finally, mediation analysis revealed 20 mediation relationships, including the causal pathway from gut microbiota to obesity, mediated by 17 metabolites, 2 peripheral cells, and 1 inflammatory cytokine. Sensitivity analysis represented no heterogeneity or pleiotropy in this study.
Our findings support a causal relationship among gut microbiota, plasma metabolites, peripheral cells, inflammatory cytokines, and obesity. These biomarkers provide new insights into the mechanisms underlying obesity and contribute to its prevention, diagnosis, and treatment.
■191个肠道微生物群特征的汇总统计(N=18,340),1,400个血浆代谢物性状(N=8,299),128个外周细胞计数(血细胞,N=408,112;免疫细胞,N=3,757),41种炎性细胞因子性状(N=8,293),和6个肥胖性状来自公开的全基因组关联研究。双样本孟德尔随机化(MR)分析被用来推断因果联系使用逆方差加权,最大似然,MR-Egger,加权中位数,加权模式,和沃尔德比率法。还利用了一些灵敏度分析来确保可靠的MR结果。最后,我们使用中介分析来确定由血浆代谢物介导的从肠道菌群到肥胖的途径,外周细胞,和炎性细胞因子。
■MR揭示了44个肠道微生物群的因果效应,281种血浆代谢物,27个外周细胞,和8种炎症细胞因子对肥胖的影响。其中,五个共有的因果肠道微生物群属于放线菌门,订购双歧杆菌,双歧杆菌科,落叶松科属UCG008,和新杆菌群。此外,我们筛选了42个共有的因果代谢物,7个共有的因果外周细胞,和1个共有的致病性炎性细胞因子。基于已知的因果代谢物,我们观察到D-精氨酸的代谢途径,D-鸟氨酸,亚油酸,甘油磷脂代谢与肥胖密切相关。最后,调解分析揭示了20种调解关系,包括从肠道微生物群到肥胖的因果途径,由17种代谢物介导,2个外周细胞,和1个炎症细胞因子。敏感性分析在这项研究中没有异质性或多效性。
■我们的研究结果支持肠道微生物群之间的因果关系,血浆代谢物,外周细胞,炎性细胞因子,和肥胖。这些生物标志物为肥胖的潜在机制提供了新的见解,并有助于预防肥胖。诊断,和治疗。