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DataSheet_1_Association of general health and lifestyle factors with the salivary microbiota – Lessons learned from the ADDITION-PRO cohort.zip (17.27 MB)

DataSheet_1_Association of general health and lifestyle factors with the salivary microbiota – Lessons learned from the ADDITION-PRO cohort.zip

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posted on 2022-11-16, 05:09 authored by Casper Sahl Poulsen, Nikoline Nygaard, Florentin Constancias, Evelina Stankevic, Timo Kern, Daniel R. Witte, Dorte Vistisen, Niels Grarup, Oluf Borbye Pedersen, Daniel Belstrøm, Torben Hansen
Introduction

Previous research indicates that the salivary microbiota may be a biomarker of oral as well as systemic disease. However, clarifying the potential bias from general health status and lifestyle-associated factors is a prerequisite of using the salivary microbiota for screening.

Materials & Methods

ADDDITION-PRO is a nationwide Danish cohort, nested within the Danish arm of the Anglo-Danish-Dutch Study of Intensive treatment in People with Screen-Detected Diabetes in Primary Care. Saliva samples from n=746 individuals from the ADDITION-PRO cohort were characterized using 16s rRNA sequencing. Alpha- and beta diversity as well as relative abundance of genera was examined in relation to general health and lifestyle-associated variables. Permutational multivariate analysis of variance (PERMANOVA) was performed on individual variables and all variables together. Classification models were created using sparse partial-least squares discriminant analysis (sPLSDA) for variables that showed statistically significant differences based on PERMANOVA analysis (p < 0.05).

Results

Glycemic status, hemoglobin-A1c (HbA1c) level, sex, smoking and weekly alcohol intake were found to be significantly associated with salivary microbial composition (individual variables PERMANOVA, p < 0.05). Collectively, these variables were associated with approximately 5.8% of the observed differences in the composition of the salivary microbiota. Smoking status was associated with 3.3% of observed difference, and smoking could be detected with good accuracy based on salivary microbial composition (AUC 0.95, correct classification rate 79.6%).

Conclusions

Glycemic status, HbA1c level, sex, smoking and weekly alcohol intake were significantly associated with the composition of the salivary microbiota. Despite smoking only being associated with 3.3% of the difference in overall salivary microbial composition, it was possible to create a model for detection of smoking status with a high correct classification rate. However, the lack of information on the oral health status of participants serves as a limitation in the present study. Further studies in other cohorts are needed to validate the external validity of these findings.

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