Study attempts to identify bacterial indicator species of obesity and metabolic syndrome in adult and pediatric patients

A study aiming to identify biomarker species associated with obesity and metabolic syndrome (MetS) was presented at the 52nd Annual Meeting & Exhibition of the AADOCR, held in conjunction with the 47th Annual Meeting of the CADR. The AADOCR/CADR Annual Meeting & Exhibition took place at the Oregon Convention Center in Portland on March 15-18, 2023.

The study, led by Tanveer Vasdev of the University of Iowa, analyzed 208 saliva and subgingival samples from periodontally, healthy, frequency-matched patients belonging to adult and pediatric obesity and MetS. Bacterial DNA isolated, V3-V4 region amplified, 16S sequencing performed on Illumina Miseq platform, annotated against HOMD database.

Indicspecies, DESeq2 packages from R studio, and TukeyHSD were used to determine indicator species and significantly differentially abundant species between the groups. A 2-fold log difference with a p-value less than 0.05 was set as a threshold for significance. Bacterial species that were identified in Indicspecies and that were identified as differentially significantly abundant by DESeq2 and Tukey HSD were determined to be 'indicator species' associated with MetS.

The study identified potential indicator bacterial species that are associated with adult and pediatric MetS in the oral microbiome. Treponema denticola emerged as an indicator species in pediatric MetS cohort in the salivary environment, while Prevotella scopos was identified as a potential indicator species of MetS in the salivary environment of our adult cohort. Acinetobacter johnsonii was identified as a potential indicator species of Adult MetS in the subgingival environment.

After a rigorous statistical analysis, pathogenic bacterial species such as Treponema, Prevotella, and Acinetobacter could be identified as keystone species associated with metabolic syndrome, even in the absence of clinical periodontal disease. The data needs to be further validated in larger cohorts and using mechanistic approaches.