Independent Research Unit Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Neusässer Str. 47, 86156, Augsburg, Germany.
Microbiome. 2021 Mar 16;9(1):61. doi: 10.1186/s40168-020-00969-9.
The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study.
Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant's gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5.
The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract.
肠道微生物群通过多种机制影响人类健康,并且与一系列非传染性疾病的发展有关。饮食是影响健康和疾病中微生物与宿主相互作用的一个已知因素。然而,基于使用基于人群的研究进行大规模分析的发现很少。我们的目的是在奥格斯堡合作健康研究(KORA)FF4 研究中调查习惯性饮食摄入与肠道微生物组结构的横断面关系。
使用 16S rRNA 基因扩增子测序分析粪便微生物群。应用潜在 Dirichlet 分配(LDA)对 1992 名参与者的样本进行分析,以确定研究人群中的 20 个微生物亚群。随后,通过 20 个亚群的独特组合来描述每个参与者的肠道微生物组。通过重复 24 小时食物清单和食物频率问卷评估习惯性饮食摄入与 20 个亚群之间的关联,以及代谢疾病/危险因素的患病率与亚群之间的关联,采用多元调整 Dirichlet 回归模型进行评估。在进行多次测试调整后,20 个微生物亚群中有 8 个与习惯性饮食显著相关,而 20 个微生物亚群中有 9 个与一种或多种代谢疾病/危险因素的患病率相关。亚群 5(Faecalibacterium、Lachnospiracea incertae sedis、Gemmiger、Roseburia)和 14(Coprococcus、Bacteroides、Faecalibacterium、Ruminococcus)与饮食的关联特别强。例如,亚群 5 概率较高的参与者的替代健康饮食指数和地中海饮食评分较高,摄入水果、蔬菜、豆类和全谷物等食物的量也较高,而患有 2 型糖尿病的参与者亚群 5 的概率较低。
本分析中确定的习惯性饮食、代谢疾病和微生物亚群之间的关联不仅扩展了饮食-微生物群-疾病关系的现有知识,还表明某些微生物群可能通过饮食干预进行调节,从而有可能影响人类健康。此外,LDA 似乎是解释人类肠道微生物组潜在结构的有力工具。然而,本分析中观察到的亚群和关联需要在进一步的研究中进行复制。