The Oral Microbiome Throughout Pregnancy: A Scoping Review

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES

This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning.

METHODS

A nested case-control study was conducted in a prospective cohort of 580 Chinese pregnant women, with 23 LBW cases and 23 healthy delivery controls matched for age and smoking habit. Saliva samples were collected at early and late pregnancy, and microbiome profiles were analyzed through 16S rRNA gene sequencing.

RESULTS

The relative abundance of Streptococcus was over-represented (median 0.259 vs. 0.116) and Saccharibacteria_TM7 was under-represented (median 0.033 vs. 0.068) in the LBW case group than in controls (p < 0.001, p = 0.015 respectively). Ten species were identified as microbiome biomarkers of LBW by LEfSe analysis, which included 7 species within the genus of Streptococcus or as part of 'nutritionally variant streptococci' (NVS), 2 species of opportunistic pathogen Leptotrichia buccalis and Gemella sanguinis (all LDA score>3.5) as risk biomarkers, and one species of Saccharibacteria TM7 as a beneficial biomarker (LDA= -4.5). The machine-learning model based on these 10 distinguished oral microbiota species could predict LBW, with an accuracy of 82 %, sensitivity of 91 %, and specificity of 73 % (AUC-ROC score 0.89, 95 % CI: 0.75-1.0). Results of α-diversity showed that mothers who delivered LBW infants had less stable salivary microbiota construction throughout pregnancy than the control group (measured by Shannon, p = 0.048; and Pielou's, p = 0.021), however the microbiome diversity did not improve the prediction accuracy of LBW.

CONCLUSIONS

A machine-learning oral microbiome model shows promise in predicting low-birth-weight delivery. Even in cases where oral health is not significantly compromised, opportunistic pathogens or rarer taxa associated with adverse pregnancy outcomes can still be identified in the oral cavity.

CLINICAL SIGNIFICANCE

This study highlights the potential complexity of the relationship between oral microbiome and pregnancy outcomes, indicating that mechanisms underlying the association between oral microbiota and adverse pregnancy outcomes may involve complex interactions between host factors, microbiota, and systemic conditions. Using machine learning to develop a predictive model based on specific oral microbiota biomarkers provides a potential for personalized medicine approaches. Future prediction models should incorporate clinical metadata to be clinically useful for improving maternal and child health.

Untangling Associations of Microbiomes of Pregnancy and Preterm Birth

This review illuminates the complex interplay between various maternal microbiomes and their influence on preterm birth (PTB), a driving and persistent contributor to neonatal morbidity and mortality. Here, we examine the dynamics of oral, gastrointestinal (gut), placental, and vaginal microbiomes, dissecting their roles in the pathogenesis of PTB. Importantly, focusing on the vaginal microbiome and PTB, the review highlights (1) a protective role of Lactobacillus species; (2) an increased risk with select anaerobes; and (3) the influence of social health determinants on the composition of vaginal microbial communities.

Preterm Infants' Airway Microbiome: A Scoping Review of the Current Evidence

The aim of this scoping review was to investigate and synthesize existing evidence on the airway microbiome of preterm infants to outline the prognostic and therapeutic significance of these microbiomes within the preterm population and identify gaps in current knowledge, proposing avenues for future research. We performed a scoping review of the literature following the Arskey and O'Malley framework. In accordance with our inclusion criteria and the intended purpose of this scoping review, we identified a total of 21 articles. The investigation of the airway microbiome in preterm infants has revealed new insights into its unique characteristics, highlighting distinct dynamics when compared to term infants. Perinatal factors, such as the mode of delivery, chorioamnionitis, the respiratory support, and antibiotic treatment, could impact the composition of the airway microbiome. The 'gut-lung axis', examining the link between the lung and gut microbiome as well as modifications in respiratory microbiome across different sites and over time, has also been explored. Furthermore, correlations between the airway microbiome and adverse outcomes, such as bronchopulmonary dysplasia (BPD), have been established. Additional research in neonatal care is essential to understand the early colonization of infants' airways and explore methods for its optimization. The critical opportunity to shape long-term health through microbiome-mediated effects likely lies within the neonatal period.

Periodontal pathogens of the interdental microbiota in a 3 months pregnant population with an intact periodontium

Steroid hormones and the oral microbiota of pregnant women both appear as cumulative risk factors for gingivitis. This cross-sectional study, using real-time PCR, investigated the composition and diversity of the microbiota in interdental spaces of 3 months pregnant women with intact periodontium according the 2018 EFP/AAP classification. Bacteria identified were belonged to the red (Porphyromonas gingivalis Treponema denticola, and Tanerella forsythia), orange (Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Parvimonas micra), and green (Eikenella corrodens and A. actinomycetencomitans) Socransky complexes. Approximatively 109.11 bacteria were counted per interdental space in pregnant women. Bacteria from the red complex represented 33.80% versus 62.81% for the orange group versus 3.39% for the green group of the total number spread over the 3 groups. Dietary habits and physical activity did not have a significant impact on interdental microbiota, although a decrease in the median amount of 9 periodontopathogens was observed when fruit and vegetable consumption increased. Pregnant women who brushed their teeth at least twice a day had lower counts of total bacteria and 9 periodontal pathogens than those who brushed less. In 3 months pregnant women at high risk of periodontal disease (>30% bleeding sites), the dendogram revealed 2 clusters of the 9 periodontopathogens. This provides further support for the "key pathogen" hypothesis, among which Porphyromonas gingivalis plays a key role, indicating that specific bacteria in limited quantities can influence the host immune system and convert the microbiota from symbiotic to dysbiotic to induce inflammatory disorder. As a result, this study reported that 3 months pregnant women with healthy periodontium had high levels of interdental bleeding and a dysbiotic microbiota with periodontal pathogens of the Socransky orange and red complexes. These subjects were therefore potentially at increased risk of developing periodontal disease and, consequently, an adverse pregnancy outcome. So, preventive oral prophylaxis measures, in particular individual interdental prophylaxis, should be implemented as soon as pregnancy is established.