Journal of oral microbiology · 2024
Impact of HbA1c control and type 2 diabetes mellitus exposure on the oral microbiome profile in the elderly population.
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Zeng Xin, Huang Shuqi, Ye Xin, Song Siping, He Jing, Hu Liwei, Deng Sicheng, Liu Fan
Аннотация
OBJECTIVE: To investigate the associations of the oral microbiome status with diabetes characteristics in elderly patients with type 2 diabetes mellitus.
METHODS: A questionnaire was used to assess age, sex, smoking status, drinking status, flossing frequency, T2DM duration and complications, and a blood test was used to determine the glycated haemoglobin (HbA1c) level. Sequencing of the V3-V4 region of the 16S rRNA gene from saliva samples was used to analyze the oral microbiome.
RESULTS: Differential analysis revealed that Streptococcus and Weissella were significantly enriched in the late-stage group, and Capnocytophaga was significantly enriched in the early-stage group. Correlation analysis revealed that diabetes duration was positively correlated with the abundance of Streptococcus (r= 0.369, p= 0.007) and negatively correlated with the abundance of Cardiobacterium (r= -0.337, p= 0.014), and the level of HbA1c was not significantly correlated with the oral microbiome. Network analysis suggested that the poor control group had a more complex microbial network than the control group, a pattern that was similar for diabetes duration. In addition, Streptococcus has a low correlation with other microorganisms.
CONCLUSION: In elderly individuals, Streptococcus emerges as a potential biomarker linked to diabetes, exhibiting elevated abundance in diabetic patients influenced by disease exposure and limited bacterial interactions.
METHODS: A questionnaire was used to assess age, sex, smoking status, drinking status, flossing frequency, T2DM duration and complications, and a blood test was used to determine the glycated haemoglobin (HbA1c) level. Sequencing of the V3-V4 region of the 16S rRNA gene from saliva samples was used to analyze the oral microbiome.
RESULTS: Differential analysis revealed that Streptococcus and Weissella were significantly enriched in the late-stage group, and Capnocytophaga was significantly enriched in the early-stage group. Correlation analysis revealed that diabetes duration was positively correlated with the abundance of Streptococcus (r= 0.369, p= 0.007) and negatively correlated with the abundance of Cardiobacterium (r= -0.337, p= 0.014), and the level of HbA1c was not significantly correlated with the oral microbiome. Network analysis suggested that the poor control group had a more complex microbial network than the control group, a pattern that was similar for diabetes duration. In addition, Streptococcus has a low correlation with other microorganisms.
CONCLUSION: In elderly individuals, Streptococcus emerges as a potential biomarker linked to diabetes, exhibiting elevated abundance in diabetic patients influenced by disease exposure and limited bacterial interactions.