Tobacco exposure associated with oral microbiota oxygen utilization in the New York City Health and Nutrition Examination Study

Abstract

Purpose: The effect of tobacco exposure on the oral microbiome has not been established.

Methods: We performed amplicon sequencing of the 16S ribosomal RNA gene V4 variable region to estimate bacterial community characteristics in 259 oral rinse samples, selected based on self-reported smoking and serum cotinine levels, from the 2013-2014 New York City Health and Nutrition Examination Study. We identified differentially abundant operational taxonomic units (OTUs) by primary and secondhand tobacco exposure, and used "microbe set enrichment analysis" to assess shifts in microbial oxygen utilization.

Results: Cigarette smoking was associated with depletion of aerobic OTUs (Enrichment Score test statistic ES = -0.75, P = .002) with a minority (29%) of aerobic OTUs enriched in current smokers compared with never smokers. Consistent shifts in the microbiota were observed for current cigarette smokers as for nonsmokers with secondhand exposure as measured by serum cotinine levels. Differential abundance findings were similar in crude and adjusted analyses.

Conclusions: Results support a plausible link between tobacco exposure and shifts in the oral microbiome at the population level through three lines of evidence: (1) a shift in microbiota oxygen utilization associated with primary tobacco smoke exposure; (2) consistency of abundance fold changes associated with current smoking and shifts along the gradient of secondhand smoke exposure among nonsmokers; and (3) consistency after adjusting for a priori hypothesized confounders.

Keywords: 16S; Human microbiome; Microbiota; Oral health; RNA; Ribosomal; Smoking; Tobacco.

Figure 1:

Principal coordinates analysis based on the weighted UniFrac distance. Dots in the ordination plot are samples from never smokers with negligible serum cotinine (blue, n=43) and current cigarette smokers (red, n=86); ellipsis indicating where 95% of observations are expected for each group. A separation between cigarette smokers and never smokers is present and is statistically significant (R² = 0.051, PERMANOVA p<0.001). A gradient also exists for the entire sample (n=259) by measured continuous serum cotinine level (R² =0.0485, PERMANOVA p = 0.001).

Figure 2:

Adjusted multivariate differential analysis between current cigarette smokers (n=86) and never smokers (n=43). Starting from the 46 OTUs identified as differentially abundant from the crude model, adjusting for confounders OTU differentially abundant were reduced to 21.

Figure 3:

Comparison between 212 coefficients for current (n=86) vs. never smokers (n=43) from crude and adjusted negative binomial log-linear regression (adjusted for age, sex, race/ethnicity, self-reported physical activity, education, diabetes status, self-reported gum disease). Points in the scatter plot represent all differentially abundant OTUs, regardless of statistical significance, with black dot OTUs significant with the Wald test in crude analyses; coordinates are determined by the log₂ fold change resulting from the crude analysis between current and never smokers (x axis) and the log₂ fold change from the adjusted analysis between current and never smokers (y axis).

Figure 4:

Comparison of log₂ OTU fold changes between a) crude analyses of smokers (n=86) vs non-smokers with no detectable serum cotinine (n=43), and b) analysis of continuous cotinine levels among non-smokers exposed to secondhand smoke (n=38). Plot shows 121 OTUs that passed the edgeR filter for low-variance variables, including 28 OTUs that are differentially abundant in smokers (FDR <0.05, indicated in black). Coefficients for these two contrasts, involving different measures of exposure on different individuals, are positively correlated (Pearson Correlation = 0.58, p = 0.0013 for 28 OTUs; Pearson Correlation = 0.40, p = 5e-6 for all 121 OTUs)