BACKGROUND: A comparison of the salivary microbiome of non-diabetic and diabetic cohorts having periodontal health, gingivitis and periodontitis could reveal microbial signatures unique to each group that will increase understanding of the role of oral microbiota in the pathogenesis of disease, and assist with diagnosis and risk assessment for both periodontal disease and diabetes. METHODS: A group of individuals diagnosed with type 2 diabetes (T2D) was compared with a group without T2D. For both the diabetic and non-diabetic cohorts, three subgroups were established: periodontal health, gingivitis, and periodontitis. Salivary DNA was extracted (n = 146), polymerase chain reaction was performed to amplify 16S rRNA hypervariable region V3-V4, and constructed libraries were sequenced and subjected to bioinformatic and statistical analyses. RESULTS: Microbiome analysis resulted in 88 different genus level operational taxonomic units (OTUs) for differential abundance testing. Results were largely described by two trends. Trend 1 showed OTUs that increased in abundance with increasing periodontal disease, and in diabetics relative to non-diabetics. Trend 1 OTUs comprised a mix of primarily anaerobic commensals and potential periodontopathogens. Trend 2 was driven primarily by genera that decreased in abundance in those with diabetes relative to those without diabetes, which included other anaerobes associated with periodontal disease. Overall, oral microbial diversity decreased in diabetics and increased with progression of periodontal disease compared with periodontally healthy controls. CONCLUSION: Although select microbiota increased in both diabetes and periodontal disease progression, these genera decreased in co-existing diabetes and periodontal disease. These findings suggest that the genera abundance continues to change with additional stress imposed by co-existing conditions.
BACKGROUND: A comparison of the salivary microbiome of non-diabetic and diabetic cohorts having periodontal health, gingivitis and periodontitis could reveal microbial signatures unique to each group that will increase understanding of the role of oral microbiota in the pathogenesis of disease, and assist with diagnosis and risk assessment for both periodontal disease and diabetes. METHODS: A group of individuals diagnosed with type 2 diabetes (T2D) was compared with a group without T2D. For both the diabetic and non-diabetic cohorts, three subgroups were established: periodontal health, gingivitis, and periodontitis. Salivary DNA was extracted (n = 146), polymerase chain reaction was performed to amplify 16S rRNA hypervariable region V3-V4, and constructed libraries were sequenced and subjected to bioinformatic and statistical analyses. RESULTS: Microbiome analysis resulted in 88 different genus level operational taxonomic units (OTUs) for differential abundance testing. Results were largely described by two trends. Trend 1 showed OTUs that increased in abundance with increasing periodontal disease, and in diabetics relative to non-diabetics. Trend 1 OTUs comprised a mix of primarily anaerobic commensals and potential periodontopathogens. Trend 2 was driven primarily by genera that decreased in abundance in those with diabetes relative to those without diabetes, which included other anaerobes associated with periodontal disease. Overall, oral microbial diversity decreased in diabetics and increased with progression of periodontal disease compared with periodontally healthy controls. CONCLUSION: Although select microbiota increased in both diabetes and periodontal disease progression, these genera decreased in co-existing diabetes and periodontal disease. These findings suggest that the genera abundance continues to change with additional stress imposed by co-existing conditions.
Authors: R T Demmer; P Trinh; M Rosenbaum; G Li; C LeDuc; R Leibel; A González; R Knight; B Paster; P C Colombo; M Desvarieux; P N Papapanou; D R Jacobs Journal: J Dent Res Date: 2019-10-17 Impact factor: 6.116
Authors: Eric L Brown; Heather T Essigmann; Kristi L Hoffman; Noah W Palm; Sarah M Gunter; Joel M Sederstrom; Joseph F Petrosino; Goo Jun; David Aguilar; William B Perkison; Craig L Hanis; Herbert L DuPont Journal: Infect Immun Date: 2020-11-16 Impact factor: 3.609