The association between gut microbiota composition and cardiometabolic parameters in healthy adults.

BACKGROUND

The human gut microbiota comprises approximately 100 trillion microbial cells and produces a wide range of metabolites. Its composition is shaped by factors such as geography, dietary habits, and genetic background. Dysbiosis-an imbalance in this microbial ecosystem-has been associated with the development of metabolic diseases. This study aimed to characterize the gut microbiota composition in adults without diagnosed chronic diseases and assess its potential associations with cardiometabolic parameters.

METHODS

Volunteers over the age of 18 residing in Izmir province who met the inclusion criteria were enrolled in the study. Fecal and blood samples were collected from all participants. Bacterial DNA from fecal samples was extracted, and the full-length 16 S rRNA was amplified. Full-length 16 S rRNA PCR amplicons were sequenced using Oxford Nanopore Technologies. Taxonomic classification, Firmicutes/Bacteroidetes ratio, and Shannon index were determined using Massbiome Fecal Microbiome Analysis (Massive Bioinformatics, Türkiye). Dominant bacterial genera were also analyzed using the Epi2Me database. Blood samples were analyzed for metabolic health markers. Associations between bacterial taxa and blood-based metabolic parameters were examined statistically.

RESULTS

A total of 82 participants were included in the study. According to BMI, 34 (41.4%) of the participants were classified as having a healthy weight, 23 (28.1%) as overweight, and 25 (30.5%) as obese. Segatella (Prevotella) copri was identified as the dominant species in most participants (51%). Other dominant species included Ruminococcus torques (13%), Faecalibacterium prausnitzii (13%), Faecalitalea cylindroides (5%), Bacteroides uniformis (4%), and Phocaeicola vulgatus (3%). S. copri was identified as the dominant bacterial species in 45 participants (54.8%) according to the Epi2Me database. The Shannon index and Firmicutes/Bacteroidetes ratio varied among the three BMI groups. Both Lachnospira and Ruminococcus genera had a significant negative correlation with BMI, indicating that higher levels of BMI are associated with lower abundances of these genera. In the regression analysis, Lachnospira was found to be less abundant at higher HbA1c levels. HOMA-IR was found to be a significant predictor for the relative abundance of Vescimonas. Ruthenibacterium is found to be more abundant at higher HDL levels.

CONCLUSION

The dominant bacterial taxa differed from those reported in other populations, suggesting region-specific microbial profiles. Notably, specific gut microbial genera were associated with metabolic health indicators, including BMI, HbA1c, HOMA-IR, and HDL level. These findings underscore the potential role of gut microbiota in metabolic regulation and support the need for further region-specific research. This study is among the few in Türkiye focusing on healthy adults and contributes to the understanding of gut microbiota in relation to cardiometabolic parameters.