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A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations

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 relati...

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Autores principales: Revers, Alma, Zhang, Xiang, Zwinderman, Aeilko H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529249/
https://www.ncbi.nlm.nih.gov/pubmed/34690956
http://dx.doi.org/10.3389/fmicb.2021.711861
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author Revers, Alma
Zhang, Xiang
Zwinderman, Aeilko H.
author_facet Revers, Alma
Zhang, Xiang
Zwinderman, Aeilko H.
author_sort Revers, Alma
collection PubMed
description 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.
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spelling pubmed-85292492021-10-22 A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations Revers, Alma Zhang, Xiang Zwinderman, Aeilko H. Front Microbiol Microbiology 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. Frontiers Media S.A. 2021-10-07 /pmc/articles/PMC8529249/ /pubmed/34690956 http://dx.doi.org/10.3389/fmicb.2021.711861 Text en Copyright © 2021 Revers, Zhang and Zwinderman. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Revers, Alma
Zhang, Xiang
Zwinderman, Aeilko H.
A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title_full A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title_fullStr A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title_full_unstemmed A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title_short A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
title_sort bayesian negative binomial hierarchical model for identifying diet–gut microbiome associations
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529249/
https://www.ncbi.nlm.nih.gov/pubmed/34690956
http://dx.doi.org/10.3389/fmicb.2021.711861
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