Background: Obesity is an important risk factor for diabetes, cardiovascular disease, and periodontal disease. Adipocytes appear to secrete proinflammatory cytokines which may be the molecules linking the pathogenesis of these diseases. We evaluated the relationship between obesity, periodontal disease, and diabetes mellitus insulin resistance as well as the plasma levels of tumor necrosis factor alpha (TNFα) and its soluble receptors (sTNFα) to assess the relationship of inflammation to obesity, diabetes, and periodontal infections.Methods: The relationship between periodontal disease, obesity, and insulin resistance was examined in the Third National Health and Nutrition Examination Survey (NHANES III). In a population of 12,367 non‐diabetic subjects, the variable body mass index (BMI) was used as an assessment of obesity and periodontal disease was assessed by mean clinical attachment loss. The plasma levels of TNFα and sTNFα were assessed in subsets of 1,221 adults from Erie County, New York, who represented the highest and lowest quartile of BMI. These subjects had extensive periodontal and medical evaluations.Results: In the NHANES III portion of the study, BMI was positively related to severity of periodontal attachment loss (P <0.001). Weighted multiple logistic regressions showed that this relationship is likely mediated by insulin resistance, since overweight individuals (with BMI ≥27 kg/m²) with high levels of insulin resistance (IR) exhibited an odds ratio of 1.48 (95% confidence interval 1.13 ‐ 1.93) for severe periodontal disease as compared to overweight subjects with low IR. In the Erie County adult population, the highest levels of TNFα and sTNFα receptors were found in those individuals in the highest quartile of BMI. A positive correlation of TNFα levels with periodontal disease was found only in those in the lowest quartile of BMI.Conclusions: Obesity is a significant predictor of periodontal disease and insulin resistance appears to mediate this relationship. Furthermore, obesity is associated with high plasma levels of TNFα and its soluble receptors, which in turn may lead to a hyperinflammatory state increasing the risk for periodontal disease and also accounting in part for insulin resistance. Further studies of the molecular basis of insulin resistance and its relationship to diabetes, periodontal disease, and obesity are necessary to fully test the hypothesis that adipocyte production of proinflammatory cytokines is a pathogenic factor linking obesity to diabetes and periodontal infections.

Currently, taxonomic interrogation of microbiota is based on amplification of 16S rRNA gene sequences in clinical and scientific settings. Accurate evaluation of the microbiota depends heavily on the primers used, and genus/species resolution bias can arise with amplification of non-representative genomic regions. The latest Illumina MiSeq sequencing chemistry has extended the read length to 300 bp, enabling deep profiling of large number of samples in a single paired-end reaction at a fraction of the cost. An increasingly large number of researchers have adopted this technology for various microbiome studies targeting the 16S rRNA V3–V4 hypervariable region. To expand the applicability of this powerful platform for further descriptive and functional microbiome studies, we standardized and tested an efficient, reliable, and straightforward workflow for the amplification, library construction, and sequencing of the 16S V1–V3 hypervariable region using the new 2 × 300 MiSeq platform. Our analysis involved 11 subgingival plaque samples from diabetic and non-diabetic human subjects suffering from periodontitis. The efficiency and reliability of our experimental protocol was compared to 16S V3–V4 sequencing data from the same samples. Comparisons were based on measures of observed taxonomic richness and species evenness, along with Procrustes analyses using beta(β)-diversity distance metrics. As an experimental control, we also analyzed a total of eight technical replicates for the V1–V3 and V3–V4 regions from a synthetic community with known bacterial species operon counts. We show that our experimental protocol accurately measures true bacterial community composition. Procrustes analyses based on unweighted UniFrac β-diversity metrics depicted significant correlation between oral bacterial composition for the V1–V3 and V3–V4 regions. However, measures of phylotype richness were higher for the V1–V3 region, suggesting that V1–V3 offers a deeper assessment of population diversity and community ecology for the complex oral microbiota. This study provides researchers with valuable experimental evidence for the selection of appropriate 16S amplicons for future human oral microbiome studies. We expect that the tested 16S V1–V3 framework will be widely applicable to other types of microbiota, allowing robust, time-efficient, and inexpensive examination of thousands of samples for population, phylogenetic, and functional crossectional and longitutidal studies.