The place of high-tech methods of molecular biology in clinical laboratory diagnostics of various diseases and the development of a system of biomarkers as an important component of diagnostic research is currently attracting the closest attention of the scientific community. In this paper, an attempt is made to use high-tech metagenomic analysis to solve problems that arise due to the high frequency of association of periodontal diseases with systemic pathology, in particular, with type 2 diabetes mellitus. The aim of the study was to determine the taxonomic and metabolic features of the microbiome of periodontal tissues in periodontal diseases associated with type 2 diabetes mellitus, as a model of the ratio of local and systemic effects of periodontal pathogenic bacteria. The study included 16S shotgun sequencing of bacterial DNA as part of biological material from periodontal pockets/dentoalveolar furrows of 46 people - 15 patients with chronic periodontitis associated with type 2 diabetes mellitus, 15 patients with chronic periodontitis unrelated to systemic pathology, as well as 16 healthy people in the control group, followed by bioinformatic processing of the data obtained. The obtained data allowed us to establish the taxonomic features of the periodontal microbiome in the association of chronic periodontitis with type 2 diabetes mellitus, which included the predominance of representatives of the families Prevotellaceae and Spirochaetaceae in its composition. The features of metabolic processes in periodontal tissues with the participation of the microbiome were also revealed, which consisted in an increase in the exchange of cysteine and methionine against the background of a decrease in the metabolism of pyrimidine, methane, sphingolipids, and the synthesis of fatty acids, which are of diagnostic value in assessing the condition of patients with type 2 diabetes mellitus.
No clinical trial protocols linked to this paper
Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.PICO Elements
No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.
Paper Details
MeSH Terms
Associated Data
No associated datasets or code repositories found for this paper.
Related Papers
Related paper suggestions will be available in future updates.