Predictive modeling of gingivitis severity and susceptibility via oral microbiota

Abstract

Predictive modeling of human disease based on the microbiota holds great potential yet remains challenging. Here, 50 adults underwent controlled transitions from naturally occurring gingivitis, to healthy gingivae (baseline), and to experimental gingivitis (EG). In diseased plaque microbiota, 27 bacterial genera changed in relative abundance and functional genes including 33 flagellar biosynthesis-related groups were enriched. Plaque microbiota structure exhibited a continuous gradient along the first principal component, reflecting transition from healthy to diseased states, which correlated with Mazza Gingival Index. We identified two host types with distinct gingivitis sensitivity. Our proposed microbial indices of gingivitis classified host types with 74% reliability, and, when tested on another 41-member cohort, distinguished healthy from diseased individuals with 95% accuracy. Furthermore, the state of the microbiota in naturally occurring gingivitis predicted the microbiota state and severity of subsequent EG (but not the state of the microbiota during the healthy baseline period). Because the effect of disease is greater than interpersonal variation in plaque, in contrast to the gut, plaque microbiota may provide advantages in predictive modeling of oral diseases.

Comparison of red autofluorescing plaque and disclosed plaque—a cross-sectional study

“…Furthermore, the assumption that only old plaque causes gingival bleeding does not take the microbiological characteristics of the plaque biofilm into account. Studies relating oral plaque microbiota to gingival inflammation do exist, but these evaluate total plaque or saliva rather than the old and young portions of plaque separately [29, 30]. A recent cross-sectional study in orally healthy participants has reported that the correlation between plaque and bleeding scores on average is low [31].…”

Effects of Specimen Collection Methodologies and Storage Conditions on the Short-Term Stability of Oral Microbiome Taxonomy

“…Perturbations of oral microbiota are associated with many common dental conditions, including periodontal disease (4), gingivitis (5,6), and dental caries (7). A number of studies show statistical associations between poor oral health and coronary heart disease (8), endocarditis, preterm birth (9), and exacerbations of existing chronic conditions, such as diabetes and osteoporosis (10), although whether these associations are causal is uncertain.…”

Application of Meta‐Mesh on the analysis of microbial communities from human associated‐habitats

“…From the results (Figure 8) we found that the distribution of taxa Streptococcaceae, Actinomycineae, Micrococcineae and Prevotellaceae had significant different between gingival status (Wilcoxon Rank-sum Test P-value < 0.001). Among them, Prevotellaceae was abundant in gingivitis samples (I and E), while other three taxa were abundant in healthy samples (B), which has also been verified by the previous works in Huang, et al, 2014 [26]. We also measured the correlation between the taxa pattern and the MGI and calculated the Pearson correlation coefficient (R).…”

“…150 samples were collected from 50 hosts' saliva in 3 stages: naturally occurring gingivitis (I), healthy gingivae (B) and experimental gingivitis (E) by Huang, et al, 2014 [26]. The Mazza Gingival Index (MGI) of each stage for the host was recorded to reflect the gingival conditions from medical aspect.…”