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A microbial causal mediation analytic tool for health disparity and applications in body mass index

BACKGROUND: Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework is available to analyze microbiome as a mediator between health disparity and clinical outcome, due to the unique structure of microbiome data, including high dimen...

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Autores principales: Wang, Chan, Ahn, Jiyoung, Tarpey, Thaddeus, Yi, Stella S., Hayes, Richard B., Li, Huilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882678/
https://www.ncbi.nlm.nih.gov/pubmed/36712075
http://dx.doi.org/10.21203/rs.3.rs-2463503/v1
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author Wang, Chan
Ahn, Jiyoung
Tarpey, Thaddeus
Yi, Stella S.
Hayes, Richard B.
Li, Huilin
author_facet Wang, Chan
Ahn, Jiyoung
Tarpey, Thaddeus
Yi, Stella S.
Hayes, Richard B.
Li, Huilin
author_sort Wang, Chan
collection PubMed
description BACKGROUND: Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework is available to analyze microbiome as a mediator between health disparity and clinical outcome, due to the unique structure of microbiome data, including high dimensionality, sparsity, and compositionality. METHODS: Considering the modifiable and quantitative features of microbiome, we propose a microbial causal mediation model framework, SparseMCMM_HD, to uncover the mediating role of microbiome in health disparities, by depicting a plausible path from a non-manipulable exposure (e.g. race or region) to a continuous outcome through microbiome. The proposed SparseMCMM_HD rigorously defines and quantifies the manipulable disparity measure that would be eliminated by equalizing microbiome profiles between comparison and reference groups. Moreover, two tests checking the impact of microbiome on health disparity are proposed. RESULTS: Through three body mass index (BMI) studies selected from the curatedMetagenomicData 3.4.2 package and the American gut project: China vs. USA, China vs. UK, and Asian or Pacific Islander (API) vs. Caucasian, we exhibit the utility of the proposed SparseMCMM_HD framework for investigating microbiome’s contributions in health disparities. Specifically, BMI exhibits disparities and microbial community diversities are significantly distinctive between the reference and comparison groups in all three applications. By employing SparseMCMM_HD, we illustrate that microbiome plays a crucial role in explaining the disparities in BMI between races or regions. 11.99%, 12.90%, and 7.4% of the overall disparity in BMI in China-USA, China-UK, and API-Caucasian comparisons, respectively, would be eliminated if the between-group microbiome profiles were equalized; and 15, 21, and 12 species are identified to play the mediating role respectively. CONCLUSIONS: The proposed SparseMCMM_HD is an effective and validated tool to elucidate the mediating role of microbiome in health disparity. Three BMI applications shed light on the utility of microbiome in reducing BMI disparity by manipulating microbial profiles.
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spelling pubmed-98826782023-01-28 A microbial causal mediation analytic tool for health disparity and applications in body mass index Wang, Chan Ahn, Jiyoung Tarpey, Thaddeus Yi, Stella S. Hayes, Richard B. Li, Huilin Res Sq Article BACKGROUND: Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework is available to analyze microbiome as a mediator between health disparity and clinical outcome, due to the unique structure of microbiome data, including high dimensionality, sparsity, and compositionality. METHODS: Considering the modifiable and quantitative features of microbiome, we propose a microbial causal mediation model framework, SparseMCMM_HD, to uncover the mediating role of microbiome in health disparities, by depicting a plausible path from a non-manipulable exposure (e.g. race or region) to a continuous outcome through microbiome. The proposed SparseMCMM_HD rigorously defines and quantifies the manipulable disparity measure that would be eliminated by equalizing microbiome profiles between comparison and reference groups. Moreover, two tests checking the impact of microbiome on health disparity are proposed. RESULTS: Through three body mass index (BMI) studies selected from the curatedMetagenomicData 3.4.2 package and the American gut project: China vs. USA, China vs. UK, and Asian or Pacific Islander (API) vs. Caucasian, we exhibit the utility of the proposed SparseMCMM_HD framework for investigating microbiome’s contributions in health disparities. Specifically, BMI exhibits disparities and microbial community diversities are significantly distinctive between the reference and comparison groups in all three applications. By employing SparseMCMM_HD, we illustrate that microbiome plays a crucial role in explaining the disparities in BMI between races or regions. 11.99%, 12.90%, and 7.4% of the overall disparity in BMI in China-USA, China-UK, and API-Caucasian comparisons, respectively, would be eliminated if the between-group microbiome profiles were equalized; and 15, 21, and 12 species are identified to play the mediating role respectively. CONCLUSIONS: The proposed SparseMCMM_HD is an effective and validated tool to elucidate the mediating role of microbiome in health disparity. Three BMI applications shed light on the utility of microbiome in reducing BMI disparity by manipulating microbial profiles. American Journal Experts 2023-01-13 /pmc/articles/PMC9882678/ /pubmed/36712075 http://dx.doi.org/10.21203/rs.3.rs-2463503/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Wang, Chan
Ahn, Jiyoung
Tarpey, Thaddeus
Yi, Stella S.
Hayes, Richard B.
Li, Huilin
A microbial causal mediation analytic tool for health disparity and applications in body mass index
title A microbial causal mediation analytic tool for health disparity and applications in body mass index
title_full A microbial causal mediation analytic tool for health disparity and applications in body mass index
title_fullStr A microbial causal mediation analytic tool for health disparity and applications in body mass index
title_full_unstemmed A microbial causal mediation analytic tool for health disparity and applications in body mass index
title_short A microbial causal mediation analytic tool for health disparity and applications in body mass index
title_sort microbial causal mediation analytic tool for health disparity and applications in body mass index
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9882678/
https://www.ncbi.nlm.nih.gov/pubmed/36712075
http://dx.doi.org/10.21203/rs.3.rs-2463503/v1
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