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Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study

The relationship between the gut microbiota, short chain fatty acid (SCFA) metabolism, and obesity remains unclear due to conflicting reports from studies with limited statistical power. Additionally, this association has rarely been explored in large scale diverse populations. Here, we investigated...

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Autores principales: Ecklu-Mensah, Gertrude, Choo-Kang, Candice, Gjerstad Maseng, Maria, Donato, Sonya, Bovet, Pascal, Bedu-Addo, Kweku, Plange-Rhule, Jacob, Forrester, Terrence E., Lambert, Estelle V., Rae, Dale, Luke, Amy, Layden, Brian T., O’Keefe, Stephen, Gilbert, Jack A., Dugas, Lara R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055249/
https://www.ncbi.nlm.nih.gov/pubmed/36993742
http://dx.doi.org/10.1101/2023.03.21.533195
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author Ecklu-Mensah, Gertrude
Choo-Kang, Candice
Gjerstad Maseng, Maria
Donato, Sonya
Bovet, Pascal
Bedu-Addo, Kweku
Plange-Rhule, Jacob
Forrester, Terrence E.
Lambert, Estelle V.
Rae, Dale
Luke, Amy
Layden, Brian T.
O’Keefe, Stephen
Gilbert, Jack A.
Dugas, Lara R.
author_facet Ecklu-Mensah, Gertrude
Choo-Kang, Candice
Gjerstad Maseng, Maria
Donato, Sonya
Bovet, Pascal
Bedu-Addo, Kweku
Plange-Rhule, Jacob
Forrester, Terrence E.
Lambert, Estelle V.
Rae, Dale
Luke, Amy
Layden, Brian T.
O’Keefe, Stephen
Gilbert, Jack A.
Dugas, Lara R.
author_sort Ecklu-Mensah, Gertrude
collection PubMed
description The relationship between the gut microbiota, short chain fatty acid (SCFA) metabolism, and obesity remains unclear due to conflicting reports from studies with limited statistical power. Additionally, this association has rarely been explored in large scale diverse populations. Here, we investigated associations between fecal microbial composition, predicted metabolic potential, SCFA concentrations, and obesity in a large (N = 1,934) adult cohort of African-origin spanning the epidemiologic transition, from Ghana, South Africa, Jamaica, Seychelles, and the United States (US). The greatest gut microbiota diversity and total fecal SCFA concentration was found in the Ghanaian population, while the lowest levels were found in the US population, respectively representing the lowest and the highest end of the epidemiologic transition spectrum. Country-specific bacterial taxa and predicted-functional pathways were observed, including an increased prevalence of Prevotella, Butyrivibrio, Weisella and Romboutsia in Ghana and South Africa, while Bacteroides and Parabacteroides were enriched in Jamaican and the US populations. Importantly, ‘VANISH’ taxa, including Butyricicoccus and Succinivibrio, were significantly enriched in the Ghanaian cohort, reflecting the participants’ traditional lifestyles. Obesity was significantly associated with lower SCFA concentrations, a decrease in microbial richness, and dissimilarities in community composition, and reduction in the proportion of SCFA synthesizing bacteria including Oscillospira, Christensenella, Eubacterium, Alistipes, Clostridium and Odoribacter. Further, the predicted proportions of genes in the lipopolysaccharide (LPS) synthesis pathway were enriched in obese individuals, while genes associated with butyrate synthesis via the dominant pyruvate pathway were significantly reduced in obese individuals. Using machine learning, we identified features predictive of metabolic state and country of origin. Country of origin could accurately be predicted by the fecal microbiota (AUC = 0.97), whereas obesity could not be predicted as accurately (AUC = 0.65). Participant sex (AUC = 0.75), diabetes status (AUC = 0.63), hypertensive status (AUC = 0.65), and glucose status (AUC = 0.66) could all be predicted with different success. Interestingly, within country, the predictive accuracy of the microbiota for obesity was inversely correlated to the epidemiological transition, being greatest in Ghana (AUC = 0.57). Collectively, our findings reveal profound variation in the gut microbiota, inferred functional pathways, and SCFA synthesis as a function of country of origin. While obesity could be predicted accurately from the microbiota, the variation in accuracy in parallel with the epidemiological transition suggests that differences in the microbiota between obesity and non-obesity may be larger in low-to-middle countries compared to high-income countries. Further examination of independent study populations using multi-omic approaches will be necessary to determine the factors that drive this association.
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spelling pubmed-100552492023-03-30 Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study Ecklu-Mensah, Gertrude Choo-Kang, Candice Gjerstad Maseng, Maria Donato, Sonya Bovet, Pascal Bedu-Addo, Kweku Plange-Rhule, Jacob Forrester, Terrence E. Lambert, Estelle V. Rae, Dale Luke, Amy Layden, Brian T. O’Keefe, Stephen Gilbert, Jack A. Dugas, Lara R. bioRxiv Article The relationship between the gut microbiota, short chain fatty acid (SCFA) metabolism, and obesity remains unclear due to conflicting reports from studies with limited statistical power. Additionally, this association has rarely been explored in large scale diverse populations. Here, we investigated associations between fecal microbial composition, predicted metabolic potential, SCFA concentrations, and obesity in a large (N = 1,934) adult cohort of African-origin spanning the epidemiologic transition, from Ghana, South Africa, Jamaica, Seychelles, and the United States (US). The greatest gut microbiota diversity and total fecal SCFA concentration was found in the Ghanaian population, while the lowest levels were found in the US population, respectively representing the lowest and the highest end of the epidemiologic transition spectrum. Country-specific bacterial taxa and predicted-functional pathways were observed, including an increased prevalence of Prevotella, Butyrivibrio, Weisella and Romboutsia in Ghana and South Africa, while Bacteroides and Parabacteroides were enriched in Jamaican and the US populations. Importantly, ‘VANISH’ taxa, including Butyricicoccus and Succinivibrio, were significantly enriched in the Ghanaian cohort, reflecting the participants’ traditional lifestyles. Obesity was significantly associated with lower SCFA concentrations, a decrease in microbial richness, and dissimilarities in community composition, and reduction in the proportion of SCFA synthesizing bacteria including Oscillospira, Christensenella, Eubacterium, Alistipes, Clostridium and Odoribacter. Further, the predicted proportions of genes in the lipopolysaccharide (LPS) synthesis pathway were enriched in obese individuals, while genes associated with butyrate synthesis via the dominant pyruvate pathway were significantly reduced in obese individuals. Using machine learning, we identified features predictive of metabolic state and country of origin. Country of origin could accurately be predicted by the fecal microbiota (AUC = 0.97), whereas obesity could not be predicted as accurately (AUC = 0.65). Participant sex (AUC = 0.75), diabetes status (AUC = 0.63), hypertensive status (AUC = 0.65), and glucose status (AUC = 0.66) could all be predicted with different success. Interestingly, within country, the predictive accuracy of the microbiota for obesity was inversely correlated to the epidemiological transition, being greatest in Ghana (AUC = 0.57). Collectively, our findings reveal profound variation in the gut microbiota, inferred functional pathways, and SCFA synthesis as a function of country of origin. While obesity could be predicted accurately from the microbiota, the variation in accuracy in parallel with the epidemiological transition suggests that differences in the microbiota between obesity and non-obesity may be larger in low-to-middle countries compared to high-income countries. Further examination of independent study populations using multi-omic approaches will be necessary to determine the factors that drive this association. Cold Spring Harbor Laboratory 2023-03-22 /pmc/articles/PMC10055249/ /pubmed/36993742 http://dx.doi.org/10.1101/2023.03.21.533195 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Ecklu-Mensah, Gertrude
Choo-Kang, Candice
Gjerstad Maseng, Maria
Donato, Sonya
Bovet, Pascal
Bedu-Addo, Kweku
Plange-Rhule, Jacob
Forrester, Terrence E.
Lambert, Estelle V.
Rae, Dale
Luke, Amy
Layden, Brian T.
O’Keefe, Stephen
Gilbert, Jack A.
Dugas, Lara R.
Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title_full Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title_fullStr Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title_full_unstemmed Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title_short Gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: The METS-Microbiome Study
title_sort gut microbiota and fecal short chain fatty acids differ with adiposity and country of origin: the mets-microbiome study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055249/
https://www.ncbi.nlm.nih.gov/pubmed/36993742
http://dx.doi.org/10.1101/2023.03.21.533195
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