Oral Biol Res.  2022 Mar;46(1):10-20. 10.21851/obr.46.01.202203.10.

Correlation analysis of the oral mucosal microbiome and diabetes mellitus using microbial DNA in elderly male subjects

Affiliations
  • 1Resident, Department of Periodontology, Dental Hospital, Veterans Health Service Medical Center, Seoul, Republic of Korea
  • 2Research Assistant, Research Institute of Veterans Health Service Medical Center, Seoul, Republic of Korea
  • 3Professor, Department of Periodontology, Research Institute for Periodontal Regeneration, College of Dentistry, Yonsei University, Seoul, Republic of Korea
  • 4Chair, Department of Laboratory Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea
  • 5Chair, Department of Periodontology, Dental Hospital, Veterans Health Service Medical Center, Seoul, Republic of Korea

Abstract

Oral microbiomes are associated with various systemic diseases, and the need for a deeper understanding of oral microbiomes has garnered substantial research interest. The differences between oral mucosal microbiomes of individuals with and without diabetes were analyzed in this study, to improve disease evaluation and therapeutic development. Mucosal samples were collected from 10 and 16 individuals with and without diabetes, respectively, during an implant-uncovering procedure. Subsequently, genomic DNA from the samples was used for 16S rRNA sequencing, and the compositions of the microbiomes were compared between the two groups. There were no significant differences in the alpha and beta diversities of the groups of individuals with and without diabetes. However, the group of individuals with/without diabetes presented a relatively higher abundance of the Corynebacteriaceae family (p=0.004) and the genus Corynebacterium (p=0.019). Our findings serve as a basis for future studies on the association between diabetes and bacterial species in the aforementioned taxonomic groups. The divergence between our results and past studies indicates the need for a unified study design for sample collection and the methods used for statistical analysis, when implementing a bioinformatics-based approach to assess microbiome sequencing data from oral mucosal samples.

Keyword

Diabetes mellitus; Microbiome; Oral mucosa; 16s rRNA
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