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, 16 (12), e2006842
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Gut Microbiota Diversity Across Ethnicities in the United States

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Gut Microbiota Diversity Across Ethnicities in the United States

Andrew W Brooks et al. PLoS Biol.

Abstract

Composed of hundreds of microbial species, the composition of the human gut microbiota can vary with chronic diseases underlying health disparities that disproportionally affect ethnic minorities. However, the influence of ethnicity on the gut microbiota remains largely unexplored and lacks reproducible generalizations across studies. By distilling associations between ethnicity and differences in two US-based 16S gut microbiota data sets including 1,673 individuals, we report 12 microbial genera and families that reproducibly vary by ethnicity. Interestingly, a majority of these microbial taxa, including the most heritable bacterial family, Christensenellaceae, overlap with genetically associated taxa and form co-occurring clusters linked by similar fermentative and methanogenic metabolic processes. These results demonstrate recurrent associations between specific taxa in the gut microbiota and ethnicity, providing hypotheses for examining specific members of the gut microbiota as mediators of health disparities.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Gut microbiota composition and distinguishability by ethnicity, sex, age, and BMI.
(A) The average relative abundance of dominant microbial families for each ethnicity. (B–E) Principle coordinates analysis plots of microbiota Bray–Curtis beta diversity and ANOSIM distinguishability for: (B) Ethnicity, (C) Sex, (D) Age, (E) BMI. In B–E, each point represents the microbiota of a single sample, and colors reflect metadata for that sample. Caucasian points are reduced in size to allow clearer visualization, and p-values are not corrected across factors that have different underlying population distributions. Data available at https://github.com/awbrooks19/microbiota_and_ethnicity. BMI, body mass index.
Fig 2
Fig 2. Ethnicity associates with diversity and composition of the gut microbiota.
(A) Center lines of each boxplot depict the median by which ethnicities were ranked from low (left) to high (right); the lower and upper ends of each box represent the 25th and 75th percentiles, respectively; whiskers denote the 1.5 interquartile range; and black dots represent individual samples. Lines in the middle of violin plots depict the mean, and p-values are Bonferroni corrected within each data set. (B) Left extending violin plots represent intraethnic distances for each ethnicity, and right extending violin plots depict all interethnic distances. Center lines depict the mean beta diversity. Significance bars above violin plots depict Bonferroni corrected pairwise Mann–Whitney U comparisons of the intra-intra- and intra-interethnic distances. (C) Within each ethnicity, OTUs shared by at least 50% of samples. Colored lines represent a robust ordinary least squares regression within OTUs of each ethnicity, shaded regions represent the 95% confidence interval, R2 denotes the regression correlation, the OTUs column indicates the number of OTUs with >50% ubiquity for that ethnicity, Mean A/U is the average abundance/ubiquity ratio, and the padj is the regression significance adjusted and Bonferroni corrected for the number of ethnicities. Data available at https://github.com/awbrooks19/microbiota_and_ethnicity. OTU, operational taxonomic unit.
Fig 3
Fig 3. Microbiota distinguishability and classification ability across ethnicities.
(A) ANOSIM distinguishability between all combinations of ethnicities. Symbols depict specific ethnicities included in the ANOSIM tests, and boxes denote the R-value as a heatmap, in which white indicates increasing and black indicates decreasing distinguishability relative to the R-value with all ethnicities. (B) Average ROC curves (for 10-fold cross-validation) and prediction performance metrics for one-versus-all RF classifiers for each ethnicity, using SMOTE [33] and down subsampling approaches for training. Data available at https://github.com/awbrooks19/microbiota_and_ethnicity. ANOSIM, analysis of similarity; RF, random forest; ROC, receiver operating characteristic; SMOTE, synthetic minority oversampling technique.
Fig 4
Fig 4. Ethnicity-associated taxa match between the HMP and AGP.
Bar plots depict the log10 transformed relative abundance for individuals possessing the respective taxon within each ethnicity, ubiquity appears above (AGP) or below (HMP) bars, and the 25th and 75th percentiles are shown with extending whiskers. Mann–Whitney U tests evaluate differences in abundance and ubiquity for all individuals between pairs of ethnicities; for example, the direction of change in Victivallaceae is driven by ubiquity while abundance is higher for those possessing the taxon. Significance values are Bonferroni corrected for the six tests within each taxon and data set, and bold p-values indicate that significance (p < 0.05) and direction of change replicate in the AGP and HMP. Data available at https://github.com/awbrooks19/microbiota_and_ethnicity. AGP, American Gut Project; HMP, Human Microbiome Project.
Fig 5
Fig 5. Christensenellaceae variably associate with BMI across ethnicities.
Boxplots of BMI for individuals without (unfilled boxplots) and with (filled boxplots) Christensenellaceae. Significance was determined using one-tailed Mann–Whitney U tests for lower continuous BMI values. Black lines indicate the mean relative abundance; the lower and upper end of each box represent the 25th and 75th percentiles, respectively; and whiskers denote the 1.5 interquartile range. Data available at https://github.com/awbrooks19/microbiota_and_ethnicity. BMI, body mass index.

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