Characteristics of oral microbiota in postmenopausal women

Background: Postmenopausal osteoporosis (PMO), a prevalent bone disease triggered by estrogen deficiency - induced bone mass reduction and deterioration of bone tissue microarchitecture, escalates the risk of fragility fractures. Recent research has highlighted the pivotal role of oral and gut microbiota in PMO development, giving rise to the "oral - gut - bone axis" concept. However, the composition and functional characteristics of oral microbiota across different bone loss stages, as well as its diagnostic potential, remain unclear.Methods: A total of 21 postmenopausal women, aged 50 - 60, were recruited for the study. Based on bone mineral density (BMD) measurements from dual - energy X - ray absorptiometry (DXA), participants were divided into osteopenia, osteoporosis, and healthy groups. Saliva and dental plaque samples were collected for metagenomic sequencing to analyze microbial diversity and community composition, with differences identified via LEfSe analysis. KEGG pathway analysis was used to reveal variations in microbial functions. Based on these analyses, predictive models for bone density status were constructed using LASSO regression and random forest algorithms.Results: Significant differences in salivary microbial community structures were found between the osteoporosis and healthy groups (P=0.041). LEfSe analysis revealed higher abundance of Aggregatibacter, Haemophilus haemolyticus, Haemophilus sputorum, Pasteurellaceae, Neisseria elongata, Aggregatibacter segnis, and Aggregatibacter aphrophilus in the osteopenia group, and higher abundance of Streptococcus pneumoniae and Haemophilus paraphrohaemolyticus in the osteoporosis group compared to the healthy group. The random forest models for osteopenia vs. health and osteoporosis vs. health achieved AUC values of 0.816 and 0.735, respectively, demonstrating good predictive performance. Functional analysis using LEfSe identified differential KEGG pathways, including glycan biosynthesis and metabolism in cancer, choline metabolism in cancer, and the cGMP-PKG signaling pathway. The random forest models also highlighted key functional pathways contributing to group differentiation.Conclusion: This exploratory study employed metagenomic sequencing to investigate the oral microbiota-PMO relationship. We identified BMD status-associated compositional and functional alterations. A predictive model based on differential microbes showed promise, and functional analysis suggested involvement of inflammatory and metabolic pathways. These findings provide preliminary evidence for an exploratory link between oral microbiota and PMO, highlighting its potential as a candidate for non-invasive risk assessment and warranting further validation.