The microbiome profiles in plaque swabs from 485 DZ (n = 280) and MZ (n = 205) twins between 5 and 11 years old (mean age = 7.8 ± 1.43 years) revealed an oral bacterial community composed of 297 operational taxonomic units (OTUs), clustered at 97% 16S rRNA gene sequence similarity (average number of sequence reads per subject: 22,000 ± 10,800). OTUs across all samples were mainly assigned to even proportions of three main phyla—Firmicutes (39.9% ± 14.5%), Proteobacteria (32.4% ± 14%), and Fusobacteria (9.2% ± 5.7%)—and followed in abundance by Actinobacteria (9.8% ± 6.8%) and Bacteroidetes (8.4% ± 4.8%). Spirochaetes and other minor phyla comprised less than 0.1% of the 16S rRNA gene sequence dataset. The most dominant OTUs were unclassified species affiliated with Veillonella, Neisseria, Streptococcus, and Pasteurellaceae (from ∼13% to 10% in abundance, respectively, ∼50% of all sequence reads), with all other OTUs not superseding more than 4% in relative abundance ( Figure 1 ).

(A and B) The barplot (A) and inset-stacked bar plot (B) show the relative abundances of main OTUs (> 1% in abundance) and phyla, respectively. OTUs in the barplot are sorted in order of mean abundance and standard error. The x axis in the inset-stacked plot represents the 485 twins sampled. Error bars = SEM.

An ordination analysis (principal coordinates plot) based on Bray-Curtis distance between twin pairs did not show bacterial community differences in MZ and DZ twin pairs discordant for dental caries in enamel or progressing to dentin ( Figures 2 A–2D ). That is, the overall bacterial community composition of plaque swabs did not predict dental caries in this cohort when controlling for host genotype. These visual patterns were confirmed by permutational multivariate analyses of variance (PERMANOVA) (p > 0.9, R< 0.01) and random forest analyses (out-of-bag estimate error rate = 60%–70%). However, there was a tendency for the healthy twins to cluster, somewhat consistently, away from diseased twin pairs along PCoA.2, in the MZ (t = −2.65, p = 0.018) and DZ twins (t = −2.10, p = 0.047), and only at the dentin level ( Figure S1 ). We did not see the same trend at the enamel level, or along PCoA.1 (p > 0.1). This observation indicates that caries that have progressed through dentin may have a compositional effect on the plaque microbiome that is not standard across twins; that is, the taxa involved are not the same for every twin pair. No microbiome composition differences were observed between MZ and DZ twins when considering individuals with past or present evidence of caries, as seen in pairs discordant for caries treatment, in both dentin and enamel ( Figure S2 ). Lastly, no differences were observed in terms of alpha diversity between diseased and healthy twins, regardless of zygosity or tooth surface ( Figure S3 ). Information on caries diagnosis on each individual twin can be seen in Table S1

(A–D) Principal coordinates ordination plots show that caries phenotype in dentin (A and B) and enamel (C and D) does not drive plaque microbiome composition in MZ (A and C) and dizygotic (B and D) twins, as demonstrated by PERMANOVA (p > 0.9, R 2 < 0.01). No, no caries presence; Yes, caries presence.

Upon closer inspection of the ordination patterns obtained ( Figure 2 ), it was observed that the majority of twin pairs tended to cluster together regardless of caries state. We thus tested the extent to which host genotype shaped oral microbiome composition in this twin cohort, independent of caries state. Bray-Curtis distances (expressed as distance between nodes on dendrogram) within the MZ twin group were indeed lower than those observed in the DZ twin set (p < 0.001) and in a group of randomly chosen unrelated individuals in both tooth layers ( Figures 3 A and 3D ). Furthermore, a circular dendrogram built on these distances confirmed that MZ twin pairs tended to cluster together in the same nodes (≤ 3 nodes apart) more frequently than DZ twins ( Figures 3 B, 3C, 3E, and 3F). Randomly selected unrelated individuals did not share nodes in the dendrogram.

(A–F) Both in enamel (A–C) and dentin (D–F), the oral microbiome of MZ twins was more similar than that of DZ twins or unrelated individuals, based on Bray-Curtis distances (expressed as distance between nodes on dendrogram) (A and D). Moreover, MZ twin pairs shared the terminal nodes of a Bray-Curtis distance dendrogram (B and E) more often compared to DZ or unrelated individuals (C and F).

Host Genetic and Environmental Drivers of Plaque Microbiome Composition

2) of a phenotypic trait among individuals in a given population is defined as the amount of the variation in that trait due to genetic variation. In order to determine the amount of variation due to genetic and environmental effects driving specific taxa in the oral microbiome of this twin cohort, two approaches were followed: (1) calculating intraclass correlation coefficients (ICCs) on the abundance of each taxon within MZ and DZ twin pairs, and (2) assessing the additive genetic and environmental factors driving OTU abundance as determined by the ACE model ( Eaves et al., 1978 Eaves L.J.

Last K.A.

Young P.A.

Martin N.G. Model-fitting approaches to the analysis of human behaviour. Heritability (H) of a phenotypic trait among individuals in a given population is defined as the amount of the variation in that trait due to genetic variation. In order to determine the amount of variation due to genetic and environmental effects driving specific taxa in the oral microbiome of this twin cohort, two approaches were followed: (1) calculating intraclass correlation coefficients (ICCs) on the abundance of each taxon within MZ and DZ twin pairs, and (2) assessing the additive genetic and environmental factors driving OTU abundance as determined by the ACE model (), controlling for sex and age. The ACE model, applied here to the full cohort regardless of caries states, assumes that the variability of a given OTU is explained by additive (A) genetic effects, the shared/common (C) environment, and non-shared/unique environmental (E) factors. To these ends, the OTU count data were first normalized (see STAR Methods ) and filtered so that all OTUs were present in at least 50% of all individuals. This process yielded a set of 91 OTUs used for all variance partition analyses. Heritability was calculated on the full cohort, independent of oral health state.

A value (A = 65.4% [q < 1e−10], C = 0%, E = 34.5%), followed by Veillonella oral taxon (A = 59.6% [q < 1e−10], C = 0%, E = 40%), Pasteurellaceae (A = 58.1% [q < 1e−10], C = 0%, E = 41.8%), and Corynebacterium durum (A = 54.3% [q < 4.1e−5], C = 1%, E = 49.3%). Values for other potentially heritable taxa along with their statistical significance, including Leptotrichia and Abiotrophia, can be seen in Figure 4 Heritability of Oral Microbes According to ICC and the ACE Model Show full caption (A) Intra-class correlation coefficients (ICC) are higher in MZ twins than in DZ twins or unrelated individuals. Plotted are swarm boxplots representing interquartile ranges (IQRs) of ICC medians (dark lines in the boxes), the lowest and highest values within 1.5 times IQR from the first and third quartiles (whiskers above and below the boxes), and outliers (warm symbols beyond the whiskers). Asterisks show statistical significance based on Kruskal-Wallis tests, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001. (B) Hierarchically clustered heatmap (Euclidean distances, complete linkage algorithm) of ACE values showing the taxa that exhibit the highest heritability values (A) (numbered 1–12). (C) Heritability measures (A) are strongly correlated with values obtained from Falconer’s formula (2∗(ICC mz -ICC dz )), according to Pearson’s rho = 0.8, p < 0.0001. The shaded area on the scatterplot and numbers correspond to taxa in the heatmap with high heritability (A) and high Falconer’s values. All ACE values can be seen in Table S2 Mean ICCs were significantly higher in MZ than in DZ twin pairs and in any kind of twin compared to randomly selected subjects (Kruskal-Wallis test, p < 0.001) ( Figure 4 A). Thus, OTUs in the dental plaque of MZ twin pairs covaried more often than observed in DZ pairs or unrelated individuals. Subsequently, we applied the ACE model to the 91 OTU set, controlling for sex and age across all subjects, revealing that the greatest proportion of the variation in the plaque microbiome of this twin cohort was explained by non-shared (E = 51.5% ± 11.7%) followed by shared factors (C = 29.1% ± 16%). Mean variance due to additive genetic factors (A) in this OTU set was 19.3% ± 17.8%, with 12 OTUs showing the highest additive genetic control (A > 40%, FDR-q < 0.001) and lower variance due to shared environmental or non-shared unique factors (C and E, respectively) ( Table S2 ). Among the highly heritable OTUs, Prevotella pallens exhibited the greatestvalue (A = 65.4% [q < 1e−10], C = 0%, E = 34.5%), followed by Veillonella oral taxon (A = 59.6% [q < 1e−10], C = 0%, E = 40%), Pasteurellaceae (A = 58.1% [q < 1e−10], C = 0%, E = 41.8%), and Corynebacterium durum (A = 54.3% [q < 4.1e−5], C = 1%, E = 49.3%). Values for other potentially heritable taxa along with their statistical significance, including Leptotrichia and Abiotrophia, can be seen in Table S2 and Figure 4 B.

All OTUs affiliated with the genus Streptococcus showed the highest proportion of their variability explained by the twins’ shared and unique environment (mean A = 9.5% ± 9.8%, C = 42% ± 18.2%, E = 49% ± 16.3%). For instance, an unclassified Streptococcus (likely related to Streptococcus mitis, according to a phylogenetic tree constructed with the BLAST tree view) (A = 5%, C = 62% [q < 1e−10], E = 24%) and Streptococcus salivarius (A = 0%, C = 62% [q < 1e−10], E = 37%) were the taxa with the highest proportion of their variability explained by shared environment, along with other unclassified streptococci. Streptococcus mutans, a known cariogenic taxon, and Streptococcus anginosus were shown to be mainly modulated by unique, non-shared environmental forces ( Table S2 and Figure 4 B). These observations suggest that the dominance of streptococci in the human oral cavity is not primarily driven by genetic factors and that environmental forces may be their main determinants. Other OTUs with a higher proportion of their variation explained by the twins’ shared environment (highest C value) include unclassified Selenomonas, Capnocytophaga, Actinomycetales, and Neisseria oralis ( Table S2 Figure 4 B).

Bodmer, 1961 Bodmer W.F. Figure 5 Highly Heritable Taxa Covary Significantly between MZ Twin Pairs Show full caption (A–D) Abundances of P. pallens (A and B) and unclassified Veillonella (C and D). The taxa with the highest heritability values correlated significantly between twin pairs, with stronger associations between MZ (A and C) (Pearson’s rho > 0.5, p < 0.001) compared to DZ individuals (B and D). To strengthen our heritability calculations, we also used Falconer’s (F) formula (), which determines the heritability of a given trait based on the differences between ICCs in MZ and DZ twins (F = 2 × [ICCmz − ICCdz]). The average F value for this dataset was 0.25 ± 0.23. Providing complementary data to our previous heritability results, Falconer’s values correlated strongly with the proportion of the variation explained by additive genetic factors in this dataset (Pearson’s rho = 0.8, p = 2.2e−16) ( Figure 4 C). P. pallens and Veillonella-oral taxon not only exhibited the highest heritability and Falconer’s values but also covaried more strongly among MZ compared with DZ twins (Pearson’s rho > 0.5, p = 2.2e−16) ( Figure 5 ). We also observed significant positive correlations between additive genetic effects (A values) and ICCs in MZ twins ( Figure S4 A). This was in contrast to insignificant or negative correlations between heritability A and ICC values in DZ and unrelated individuals, respectively ( Figures S3 B and S3C). Likewise, the data showed significantly negative correlations between the proportion of the variation determined by additive genetic effects and that explained by shared environment ( Figure S4 D).

Goodrich et al., 2014 Goodrich J.K.

Waters J.L.

Poole A.C.

Sutter J.L.

Koren O.

Blekhman R.

Beaumont M.

Van Treuren W.

Knight R.

Bell J.T.

et al. Human genetics shape the gut microbiome. We also compared the broad sense heritability values obtained herein with those presented by Goodrich et al. for gut microbes (). This comparison indicated that, in contrast with the gut microbiome, oral bacteria may be more influenced by additive genetic effects (oral microbiome, A = 19%, Falconer’s = 0.25; gut microbiome, A = 12%, Falconer’s = 0.14; p < 2e−5); while the gut microbiome exhibits higher influence of shared environmental factors (gut microbiome, C = 29%; oral microbiome, C = 8%; p = 4.1e−51). Likewise, the gut microbiome shows a significantly higher influence of unique non-shared forces (E = 78% versus 51% in the gut and oral cavity, respectively; p = 8.5e−56).

Schloissnig et al., 2013 Schloissnig S.

Arumugam M.

Sunagawa S.

Mitreva M.

Tap J.

Zhu A.

Waller A.

Mende D.R.

Kultima J.R.

Martin J.

et al. Genomic variation landscape of the human gut microbiome. However, these observations may be explained by the fact that the twin cohort in Goodrich et al. is significantly older (23–86 years old) and suggest that the strong interpersonal variation (personalization) of the human microbiome () increases with age. To test hypotheses about oral microbiome heritability at different ages, we split the cohort into three different age groups (5–7 [n = 181], 7–9 [n = 179], and 9–11 [n = 125]). The results show that mean heritability (A) estimates across the core OTU set do not change with the age ranges examined in this study (p > 0.1, Figure S5 A). Nonetheless, heritability estimates for specific OTUs vary significantly among the three different age groups. For instance, heritability estimates for P. pallens, the most heritable OTU in the dataset, are high among 5- to 7-year-olds (A = 0.77, p = 2.2e−16), diminish among 7- to 9-year-olds (A = 0.47, p = 1e−10), and disappear among 9- to 11-year-olds (A = 0, p = 1) ( Figure S5 B). Thus, there was high variability in heritability (A) estimates of specific OTUs across the three age groups, with just one OTU showing relative stability (unclassified Leptotrichia) ( Figure S5 C). Variation in C and E estimates for particular OTUs was also observed; nonetheless, Streptococcus spp. seemed to maintain high and constant C estimates across the three age groups ( Figure S5 C). Additionally, the data show that while heritability estimates remained unchanged among the age groups, C and E estimates were significantly modified; for example, the influence of shared environment (C) decreased from 6 to 11 years old at the expense of individual/unique environmental variation (E) ( Figure S5 A).

A critical question regarding genetic and environmental determinants of the human microbiome centers on exploring how each of these fractions is associated with health and disease and other phenotypic or lifestyle traits. Therefore, we used heritability information obtained on the core OTU set and explored how oral microbes influenced by additive genetic effects, shared environment, or unique non-shared factors correlated with caries diagnosis, oral health practices, diet, and age in the full cohort. Information on oral health practices, diet, and age of each individual twin can be seen in Table S1

Figure 6 Genetic and Environmental Determinants of the Oral Microbiome in Connection to Oral Health Show full caption (A and B) Wilcoxon rank-sum tests identified taxa distinguishing caries-positive versus caries-negative individuals (p < 0.05) in enamel (A) and dentin (B), as shown by log2 fold changes of transformed data. Black, gray, and white circles denote OTUs with a greater proportion of their variation explained by additive genetic (A > C and E), shared environmental (C > A and E), and non-shared unique environmental factors (E > A and C), respectively. (C and D) P. pallens (C) associated with a healthy state, decreased in abundance as children aged, while the environmentally driven Tannerella (D), predictive of caries, showed the opposite trend. All models are based on nonlinear regression adjusted by sex and zygosity (Q < 0.01, locally weighted scatterplot smoother [LOWESS]). Minus and plus signs next to each taxon name indicate taxa associated with caries-negative and caries-positive states, respectively (other taxa following a decreasing trend can be seen in Figure S6 A). First, a Wilcoxon rank-sum test was used to determine if OTUs driven by genetic, environmental, and non-shared/unique forces were also associated with caries-positive and caries-negative states in each tooth layer (enamel and dentin) (p < 0.05). These tests were performed in the full cohort, randomly selecting individuals from each pair to assess OTU prevalence in caries-negative and caries-positive groups. The tests revealed that P. pallens and unclassified Veillonella, two heritable OTUs (A > C and E), were associated with a healthy state in enamel. Other OTUs indicative of a caries-free state in the outer tooth layer were Streptococcus, S. anginosus, Cardiobacterium, Actinomycetaceae, and Corynebacterium. These taxa showed both greater shared and unique/non-shared environmental variation (C > A and E or E > A and C). All the taxa associated with dental caries in enamel or progressing into dentin had a greater portion of their variation explained by unique or shared environmental factors ( Figures 6 A and 6B ). In contrast, none of the taxa we identified as heritable showed associations to disease.

Taxa influenced by genetic or environmental effects and associated with oral health or disease were also impacted by age. For instance, P. pallens, the most heritable OTU, decreased in abundance as child age increased to 6–11 years old (q < 0.001, nonlinear least-squares best fit, locally weighted scatterplot smoother [LOWESS]) ( Figure 6 C). When other OTUs associated with a caries-free state also covaried with age, they did so in a decreasing manner (e.g., S. anginosus, unclassified Streptococcus, Actinomycetaceae, and Corynebacterium [Q < 0.001]) ( Figure S6 A). These OTUs were influenced by both shared and non-shared environmental forces. Tannerella, an OTU significantly modulated by unique environmental variation, was the only caries-associated OTU that also covaried with age and did so in an increasing manner (q < 0.001) ( Figure 6 D).