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. 2021 Jan 29;11(1):2618.
doi: 10.1038/s41598-021-82311-3.

Ethnicity influences the gut microbiota of individuals sharing a geographical location: a cross-sectional study from a middle-income country

Affiliations

Ethnicity influences the gut microbiota of individuals sharing a geographical location: a cross-sectional study from a middle-income country

Jacky Dwiyanto et al. Sci Rep. .

Abstract

No studies have investigated the influence of ethnicity in a multi-ethnic middle-income country with a long-standing history of co-habitation. Stool samples from 214 Malaysian community members (46 Malay, 65 Chinese, 49 Indian, and 54 Jakun) were collected. The gut microbiota of the participants was investigated using 16S amplicon sequencing. Ethnicity exhibited the largest effect size across participants (PERMANOVA Pseudo-F = 4.24, R2 = 0.06, p = 0.001). Notably, the influence of ethnicity on the gut microbiota was retained even after controlling for all demographic, dietary factors and other covariates which were significantly associated with the gut microbiome (PERMANOVA Pseudo-F = 1.67, R2 = 0.02, p = 0.002). Our result suggested that lifestyle, dietary, and uncharacterized differences collectively drive the gut microbiota variation across ethnicity, making ethnicity a reliable proxy for both identified and unidentified lifestyle and dietary variation across ethnic groups from the same community.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Shannon (a) and Pielou’s (b) α-diversity indices across Bristol stool scale, body mass index, household income, and ethnicity with ANOVA statistical comparison.
Figure 2
Figure 2
Factors significantly associated (p < 0.05) with the gut microbiome and their effect sizes determined through univariate PERMANOVA analysis.
Figure 3
Figure 3
Principal coordinate analysis of the Segamat participants classified based on their ethnicity, ordinated using Euclidean distance matrix.
Figure 4
Figure 4
Multi-ethnic comparison of (a) gut enterotype profiles analyzed using Dirichlet Multinomial Model, and (b) Prevotella:Bacteroides ratio analyzed using linear mixed model (likelihood ratio test p < 0.05).
Figure 5
Figure 5
Taxa which were significantly differentially abundant across ethnicity in Segamat as analyzed using ALDEx2 generalized linear model (FDR < 0.1). Description: IM Indian–Malay, JI Jakun–Indian.
Figure 6
Figure 6
Predicted pathways which were significantly differentially abundant across ethnicity in Segamat as analyzed using ALDEx2 generalized linear model (FDR < 0.1). Description: CI Chinese–Indian, IM Indian–Malay, JM Jakun–Malay.

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