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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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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. |
format | Online Article Text |
id | pubmed-8529249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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