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. 2016 Mar 31:6:23745.
doi: 10.1038/srep23745.

Analysis of the association between host genetics, smoking, and sputum microbiota in healthy humans

Mi Young Lim  1 , Hyo Shin Yoon  1 , Mina Rho  2 , Joohon Sung  3 , Yun-Mi Song  4 , Kayoung Lee  5 , GwangPyo Ko  1   6   7
Affiliations

Analysis of the association between host genetics, smoking, and sputum microbiota in healthy humans

Mi Young Lim et al. Sci Rep. .

Abstract

Recent studies showing clear differences in the airway microbiota between healthy and diseased individuals shed light on the importance of the airway microbiota in health. Here, we report the associations of host genetics and lifestyles such as smoking, alcohol consumption, and physical activity with the composition of the sputum microbiota using 16S rRNA gene sequence data generated from 257 sputum samples of Korean twin-family cohort. By estimating the heritability of each microbial taxon, we found that several taxa, including Providencia and Bacteroides, were significantly influenced by host genetic factors. Smoking had the strongest effect on the overall microbial community structure among the tested lifestyle factors. The abundances of Veillonella and Megasphaera were higher in current-smokers, and increased with the pack-year value and the Fagerstrom Test of Nicotine Dependence (FTND) score. In contrast, Haemophilus decreased with the pack-year of smoking and the FTND score. Co-occurrence network analysis showed that the taxa were clustered according to the direction of associations with smoking, and that the taxa influenced by host genetics were found together. These results demonstrate that the relationships among sputum microbial taxa are closely associated with not only smoking but also host genetics.

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Figures

Figure 1
Figure 1. Composition of the sputum microbiota.
(a) Pie chart of the average relative abundances of the families. (b) Bar chart of relative abundances of the genera across each sampled sputum microbiome.
Figure 2
Figure 2. Influences of host genetic factors on the sputum microbiota.
(a) Bray-Curtis distances between the sputum microbiota of monozygotic (MZ) twin pairs, dizygotic (DZ) twin pairs, family members of the twin pairs, and unrelated individuals belonging to the various twin families (mean ± s.e.m.; *P < 0.05 for two sample t-test via 1,000 Monte Carlo permutations). (b) Heritability estimates (H2r) of sputum microbial taxa (mean ± s.e.m.). Genera with significant heritability (H2r > 0.3) are shown.
Figure 3
Figure 3. Associations of lifestyle factors with sputum microbiota.
(a) Non-metric multidimensional scaling (NMDS) plot of genus composition. Points represent samples that are colored according to pack-years of smoking. Gray points indicate samples with missing pack-year values. The black arrows indicate significant correlations with the ordination, whereas the gray arrows indicate non-significant correlations. (b) Significant associations between pack-years of smoking and microbial taxa. The r-coefficient and q-value shown in each plot were determined by MaAsLin analysis.
Figure 4
Figure 4. Effects of smoking and host genetics on specific microbial taxa.
(a) Scatter plot of q-values for the association of each genus with pack-years of smoking (x-axis; from MaAsLin analysis) versus q-values for the heritability of each genus (y-axis; from SOLAR analysis). Red, blue, and green points represent genera that are significantly associated with pack-years of smoking, host genetics, and both, respectively. (b) Correlation network of the smoking (pack-years)- or host genetics-associated genera. Pink and light blue nodes indicate genera positively and negatively associated with smoking, respectively. Gray nodes indicate genera not significantly associated with smoking. The border of each node is colored according to the heritability (black: significant heritability with H2r > 0.3; gray: significant heritability with H2r < 0.3; white: non-significant heritability). Edges represent significant positive (dark gray) or negative (light gray) correlations between the nodes they connect. The width of the edge represents the degree of correlations.
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