A comprehensive assessment of demographic, environmental, and host genetic associations with gut microbiome diversity in healthy individuals

Petar Scepanovic, Flavia Hodel, Stanislas Mondot, Valentin Partula, Allyson Byrd, Christian Hammer, Cécile Alanio, Jacob Bergstedt, Etienne Patin, Mathilde Touvier, Olivier Lantz, Matthew L Albert, Darragh Duffy, Lluis Quintana-Murci, Jacques Fellay, Milieu Intérieur Consortium, Laurent Abel, Andres Alcover, Hugues Aschard, Kalla Astrom, Philippe Bousso, Pierre Bruhns, Ana Cumano, Caroline Demangel, Ludovic Deriano, James Di Santo, Françoise Dromer, Darragh Duffy, Gérard Eberl, Jost Enninga, Jacques Fellay, Odile Gelpi, Ivo Gomperts-Boneca, Milena Hasan, Serge Hercberg, Olivier Lantz, Claude Leclerc, Hugo Mouquet, Sandra Pellegrini, Stanislas Pol, Antonio Rausell, Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Vassili Soumelis, Frédéric Tangy, Eric Tartour, Antoine Toubert, Mathilde Touvier, Marie-Noëlle Ungeheuer, Matthew L Albert, Lluis Quintana-Murci, Petar Scepanovic, Flavia Hodel, Stanislas Mondot, Valentin Partula, Allyson Byrd, Christian Hammer, Cécile Alanio, Jacob Bergstedt, Etienne Patin, Mathilde Touvier, Olivier Lantz, Matthew L Albert, Darragh Duffy, Lluis Quintana-Murci, Jacques Fellay, Milieu Intérieur Consortium, Laurent Abel, Andres Alcover, Hugues Aschard, Kalla Astrom, Philippe Bousso, Pierre Bruhns, Ana Cumano, Caroline Demangel, Ludovic Deriano, James Di Santo, Françoise Dromer, Darragh Duffy, Gérard Eberl, Jost Enninga, Jacques Fellay, Odile Gelpi, Ivo Gomperts-Boneca, Milena Hasan, Serge Hercberg, Olivier Lantz, Claude Leclerc, Hugo Mouquet, Sandra Pellegrini, Stanislas Pol, Antonio Rausell, Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Vassili Soumelis, Frédéric Tangy, Eric Tartour, Antoine Toubert, Mathilde Touvier, Marie-Noëlle Ungeheuer, Matthew L Albert, Lluis Quintana-Murci

Abstract

Background: The gut microbiome is an important determinant of human health. Its composition has been shown to be influenced by multiple environmental factors and likely by host genetic variation. In the framework of the Milieu Intérieur Consortium, a total of 1000 healthy individuals of western European ancestry, with a 1:1 sex ratio and evenly stratified across five decades of life (age 20-69), were recruited. We generated 16S ribosomal RNA profiles from stool samples for 858 participants. We investigated genetic and non-genetic factors that contribute to individual differences in fecal microbiome composition.

Results: Among 110 demographic, clinical, and environmental factors, 11 were identified as significantly correlated with α-diversity, ß-diversity, or abundance of specific microbial communities in multivariable models. Age and blood alanine aminotransferase levels showed the strongest associations with microbiome diversity. In total, all non-genetic factors explained 16.4% of the variance. We then searched for associations between > 5 million single nucleotide polymorphisms and the same indicators of fecal microbiome diversity, including the significant non-genetic factors as covariates. No genome-wide significant associations were identified after correction for multiple testing. A small fraction of previously reported associations between human genetic variants and specific taxa could be replicated in our cohort, while no replication was observed for any of the diversity metrics.

Conclusion: In a well-characterized cohort of healthy individuals, we identified several non-genetic variables associated with fecal microbiome diversity. In contrast, host genetics only had a negligible influence. Demographic and environmental factors are thus the main contributors to fecal microbiome composition in healthy individuals.

Trial registration: ClinicalTrials.gov identifier NCT01699893.

Keywords: 16S rRNA gene sequencing; Demographics; Environment; GWAS; Genomics; Gut; Healthy; Human; Microbiome.

Conflict of interest statement

C.H., A.B., and M.L.A. are employees of Genentech Inc., a member of The Roche Group. The other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Non-genetic variables. Six categories of non-genetic variables investigated in this study. In the parenthesis are the number of variables per each category and for each two representative examples. Full description of the variables is available in Additional file 2: Table S1
Fig. 2
Fig. 2
Gut microbiome diversity. a Box-plots of relative abundances of 8 phyla that were observed in more than 10% of the donors. Outliers are also represented. b Violin plot of Simpson’s diversity index values observed among MI study participants. c Multidimensional scaling plot of Bray-Curtis dissimilarity matrix with study participants colored according to relative abundance of Firmicutes
Fig. 3
Fig. 3
Association of non-genetic variables with Simpson’s index. Significant variables from the univariate test and their Spearman ρ values (right-hand side). Heatmap represents the ANOVA’s p values from the multivariable test, and the asterisks denote the statistical significance (***p < 0.001, **p < 0.01, *p < 0.05). The results for other α-diversity metrics are available in Additional file 2: Table S3
Fig. 4
Fig. 4
Association of non-genetic variables with Bray-Curtis index. Significant variables from the univariate test and their R2 values (right-hand side). Heatmap represents the PERMANOVA’s p values from the multivariable test, and the asterisks denote the statistical significance (***p < 0.001, **p < 0.01, *p < 0.05). The results for other β-diversity metrics are available in Additional file 2: Table S5
Fig. 5
Fig. 5
Results of genome-wide association study between host genetic variants and microbiome diversity metrics. a Manhattan plot for Simpson’s diversity metric (representative α-diversity metric). The dashed horizontal line denotes the genome-wide significance threshold (Pα-threshold < 1.25 × 10−8). b Manhattan plot for Bray-Curtis dissimilarity matrix (representative ß-diversity index). The dashed horizontal line denotes the genome-wide significance threshold (Pβ-threshold < 1.67 × 10−8)

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Source: PubMed

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