Mechanisms linking periodontitis and diabetes

Background + Aims

• The subgingival microbiome (the community of microorganisms beneath the gumline) contributes to periodontal health and disease. Dysbiosis describes a disruption in this community that can promote inflammation and destruction of the tissues supporting teeth.
• This study aimed to:
  • Examine associations between dietary patterns and subgingival microbial composition in the ORIGINS study.

Materials + Methods

• Cross-sectional analysis of 651 adults aged 20–55 without diabetes, providing 890 plaque samples.
• Food questionnaires generated 2 dietary quality scores: the Alternate Healthy Eating Index (AHEI) and A Priori Diet Quality Score (APDQS).
  • Both scores assess overall dietary quality, with higher scores indicating a healthier dietary pattern.
  • Alternate Healthy Eating Index (AHEI): Assesses 11 food and nutrient components linked to chronic disease risk. These include fruit, vegetables, whole grains, nuts/legumes, sugary drinks, red/processed meat, sodium, different types of fat and alcohol. Higher scores generally reflect greater consumption of plant foods and unsaturated fats, and lower consumption of sugary drinks, processed meat, trans fats and sodium.
  • A Priori Diet Quality Score (APDQS): Assesses food groups according to their expected relationship with cardiovascular health. It rewards greater consumption of favourable foods, such as vegetables, fruit, whole grains, fish and low-fat dairy, and lower consumption of unfavourable foods, such as processed meat, fried potatoes, pastries and sugary drinks. Foods with uncertain or neutral associations, such as eggs and shellfish, are classified separately. “A priori” means these classifications were established before analysing the study’s results.
• 16S rRNA gene sequencing, which identifies bacteria through their genetic signatures, assessed microbial composition.
• Adjusted analyses compared microbial measures across diet-quality quartiles.

Results

• Both dietary scores were associated with lower Faith’s phylogenetic diversity (p=0.01) and Observed richness(p=0.04).
  • Richness measures the number of bacterial types detected; phylogenetic diversity reflects how evolutionarily different they are.
• Higher AHEI scores were associated with lower disease-associated-to-health-associated bacterial ratios across all three comparisons; APDQS showed this association only for Treponema.
• Lower diversity is not inherently beneficial – interpretation depends on which organisms are present and the clinical context.

Limitations