Revers Alma, Zhang Xiang, Zwinderman Aeilko H
Department of Epidemiology and Data Science, Amsterdam University Medical Center, Amsterdam, Netherlands.
Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University, Utrecht, Netherlands.
Front Microbiol. 2021 Oct 7;12:711861. doi: 10.3389/fmicb.2021.711861. eCollection 2021.
The human gut microbiota composition plays an important role in human health. Long-term diet intervention may shape human gut microbiome. Therefore, many studies focus on discovering links between long-term diets and gut microbiota composition. This study aimed to incorporate the phylogenetic relationships between the operational taxonomic units (OTUs) into the diet-microbe association analysis, using a Bayesian hierarchical negative binomial (NB) model. We regularized the dispersion parameter of the negative binomial distribution by assuming a mean-dispersion association. A simulation study showed that, if over-dispersion is present in the microbiome data, our approach performed better in terms of mean squared error (MSE) of the slope-estimates compared to the standard NB regression model or a Bayesian hierarchical NB model without including the phylogenetic relationships. Data of the Healthy Life in an Urban Setting (HELIUS) study showed that for some phylogenetic families the (posterior) variances of the slope-estimates were decreasing when including the phylogenetic relationships into the analyses. In contrast, when OTUs of the same family were not similarly affected by the food item, some bias was introduced, leading to larger (posterior) variances of the slope-estimates. Overall, the Bayesian hierarchical NB model, with a dependency between the mean and dispersion parameters, proved to be a robust method for analyzing diet-microbe associations.
人类肠道微生物群组成在人类健康中发挥着重要作用。长期饮食干预可能会塑造人类肠道微生物组。因此，许多研究致力于发现长期饮食与肠道微生物群组成之间的联系。本研究旨在利用贝叶斯分层负二项式（NB）模型，将操作分类单元（OTU）之间的系统发育关系纳入饮食 - 微生物关联分析。我们通过假设均值 - 离散关联对负二项分布的离散参数进行正则化。一项模拟研究表明，如果微生物组数据中存在过度离散，与标准NB回归模型或不包括系统发育关系的贝叶斯分层NB模型相比，我们的方法在斜率估计的均方误差（MSE）方面表现更好。城市环境健康生活（HELIUS）研究的数据表明，对于一些系统发育家族，将系统发育关系纳入分析时，斜率估计的（后验）方差会减小。相反，当同一家族的OTU受食物项目的影响不同时，会引入一些偏差，导致斜率估计的（后验）方差更大。总体而言，均值和离散参数之间存在依赖性的贝叶斯分层NB模型被证明是分析饮食 - 微生物关联的一种稳健方法。
