Microbial Signatures Mapping of High and Normal Blood Glucose Participants in the Generation 100 Study

Area of Science:

• Microbiome research
• Metabolic health
• Human gut microbiota

Background:

• Intestinal dysbiosis is associated with metabolic disorders like insulin resistance and type 2 diabetes mellitus (T2DM).
• Early stages of T2DM and insulin resistance are potentially reversible, highlighting the need for early detection markers.
• Understanding gut microbiome alterations in relation to glucose metabolism is crucial for preventative strategies.

Purpose of the Study:

• To compare the gut microbiome composition between older adults with elevated fasting blood glucose and those with normal glucose levels.
• To identify specific microbial signatures associated with glucose dysregulation.
• To explore the potential of gut bacteria as early biomarkers for prediabetes and T2DM.

Main Methods:

• Cross-sectional comparison of gut microbiome data from 65 older adults (Generation 100 Study).
• High-throughput sequencing of the bacterial 16S rRNA gene for metagenomic profiling.
• Correlation analysis of microbial profiles with clinical measures, including fasting blood glucose.

Main Results:

• Significantly reduced microbial alpha diversity in the high glucose group.
• Distinct microbial beta diversity patterns observed between high and normal glucose groups.
• Specific phyla (Synergistes, Elusimicobia, Euryarchaeota, Verrucomicrobia, Proteobacteria) decreased in high glucose individuals.
• P. copri (ASV 909561) was significantly elevated in the high glucose group, suggesting potential as an early T2DM marker.
• Fusobacterium genus was significantly increased in the normal glucose group compared to the high glucose group.

Conclusions:

• Gut microbiome alterations are evident in individuals with elevated fasting blood glucose.
• Specific microbial shifts, including decreased diversity and altered abundance of certain bacteria, are associated with glucose dysregulation.
• Findings suggest potential microbial biomarkers for early detection of prediabetic states and T2DM, guiding future translational research and interventions.