Liu Wanjun, Fang Xiaojie, Zhou Yong, Dou Lihong, Dou Tongyi
School of Life and Pharmaceutical Sciences, Dalian University of Technology, Panjin 124221, China; Department of Scientific Research, KMHD, Shenzhen 518126, China.
Guangdong Provincial Hospital of Chinese Medicine, Guangzhou 510120, China.
Microbes Infect. 2022 Mar;24(2):104892. doi: 10.1016/j.micinf.2021.104892. Epub 2021 Oct 19.
Gut microbiota is believed to play a crucial role in obesity. However, the consistent findings among published studies regarding microbiome-obesity interaction are relatively rare, and one of the underlying causes could be the limited sample size of cohort studies. In order to identify gut microbiota changes between normal-weight individuals and obese individuals, fecal samples along with phenotype information from 2262 Chinese individuals were collected and analyzed. Compared with normal-weight individuals, the obese individuals exhibit lower diversity of species and higher diversity of metabolic pathways. In addition, various machine learning models were employed to quantify the relationship between obesity status and Body mass index (BMI) values, of which support vector machine model achieves best performance with 0.716 classification accuracy and 0.485 R score. In addition to two well-established obesity-associated species, three species that have potential to be obesity-related biomarkers, including Bacteroides caccae, Odoribacter splanchnicus and Roseburia hominis were identified. Further analyses of functional pathways also reveal some enriched pathways in obese individuals. Collectively, our data demonstrates tight relationship between obesity and gut microbiota in a large-scale Chinese population. These findings may provide potential targets for the prevention and treatment of obesity.
肠道微生物群被认为在肥胖中起着关键作用。然而，已发表的关于微生物群与肥胖相互作用的研究中，一致的研究结果相对较少，其中一个潜在原因可能是队列研究的样本量有限。为了确定正常体重个体和肥胖个体之间肠道微生物群的变化，我们收集并分析了来自2262名中国个体的粪便样本以及表型信息。与正常体重个体相比，肥胖个体表现出较低的物种多样性和较高的代谢途径多样性。此外，我们采用了各种机器学习模型来量化肥胖状态与体重指数（BMI）值之间的关系，其中支持向量机模型表现最佳，分类准确率为0.716，R评分为0.485。除了两种已确定的与肥胖相关的物种外，还鉴定出三种有潜力成为肥胖相关生物标志物的物种，包括粪拟杆菌、内脏气味杆菌和霍氏罗氏菌。对功能途径的进一步分析还揭示了肥胖个体中一些富集的途径。总体而言，我们的数据表明在大规模中国人群中肥胖与肠道微生物群之间存在紧密关系。这些发现可能为肥胖的预防和治疗提供潜在靶点。
