RESUMEN
The genetic basis of oral health has long been theorized, but little information exists on the heritable variance in common oral and dental disease traits explained by the human genome. We sought to add to the evidence base of heritability of oral and dental traits using high-density genotype data in a well-characterized community-based cohort of middle-age adults. We used genome-wide association (GWAS) data combined with clinical and biomarker information in the Dental Atherosclerosis Risk In Communities (ARIC) cohort. Genotypes comprised SNPs directly typed on the Affymetrix Genome-Wide Human SNP Array 6.0 chip with minor allele frequency of >5% (n = 656,292) or were imputed using HapMap II-CEU (n = 2,104,905). We investigated 30 traits including "global" [e.g., number of natural teeth (NT) and incident tooth loss], clinically defined (e.g., dental caries via the DMFS index, periodontitis via the CDC/AAP and WW17 classifications), and biologically informed (e.g., subgingival pathogen colonization and "complex" traits). Heritability (i.e., variance explained; h2) was calculated using Visscher's Genome-wide Complex Trait Analysis (GCTA), using a random-effects mixed linear model and restricted maximum likelihood (REML) regression adjusting for ancestry (10 principal components), age, and sex. Heritability estimates were modest for clinical traits-NT = 0.11 (se = 0.07), severe chronic periodontitis (CDC/AAP) = 0.22 (se = 0.19), WW17 Stage 4 vs. 1/2 = 0.15 (se = 0.11). "High gingival index" and "high red complex colonization" had h2 > 0.50, while a periodontal complex trait defined by high IL-1ß GCF expression and Aggregatibacter actinomycetemcomitans subgingival colonization had the highest h2 = 0.72 (se = 0.32). Our results indicate that all GWAS SNPs explain modest levels of the observed variance in clinical oral and dental measures. Subgingival bacterial colonization and complex phenotypes encompassing both bacterial colonization and local inflammatory response had the highest heritability, suggesting that these biologically informed traits capture aspects of the disease process and are promising targets for genomics investigations, according to the notion of precision oral health.
Asunto(s)
Caries Dental , Estudio de Asociación del Genoma Completo , Fenotipo , Caries Dental/genética , Caries Dental/microbiología , Genotipo , Humanos , Polimorfismo de Nucleótido Simple/genéticaRESUMEN
BACKGROUND: Periodontal disease and diabetes are widespread comorbid conditions that are detrimental to oral and overall health. Dentists' performing chairside screenings for undiagnosed diabetes mellitus (UDM) can be beneficial to both patients and providers. The authors determined UDM rates in a population-based study and whether UDM and periodontal disease were independently associated. METHODS: Data from 7,343 participants in the Atherosclerosis Risk in Communities study visit 4 were used to determine rates of UDM by periodontal status, edentulism, and body mass index. The authors used a χ2 test or analysis of variance, along with a 2-stage logistic regression model, to determine relationships with UDM. UDM was defined as no self-reported diabetes and blood glucose levels (fasting glucose ≥ 126 milligrams/deciliter or nonfasting glucose > 200 mg/dL). Periodontal disease was defined using the Periodontal Profile Classes system adapted to stages and the Centers for Disease Control and Prevention and American Academy of Periodontology index. RESULTS: UDM rates overall were 5.6%. The highest rates occurred in patients who were obese and edentulous (12.6%) and obese and had severe periodontal disease (12.2%). Significant associations were found for UDM and severe periodontal disease (Periodontal Profile Classes system stage IV) (odds ratio, 1.78; 95% confidence interval, 1.10 to 2.88). Edentulism was significantly associated with UDM in the Periodontal Profile Classes system model (odds ratio, 1.87; 95% confidence interval, 1.27 to 2.75) and Centers for Disease Control and Prevention and American Academy of Periodontology index (odds ratio, 1.70; 95% confidence interval, 1.08 to 2.67). Hyperglycemia was found in participants of all body mass index categories. CONCLUSIONS: UDM is significantly associated with obesity, edentulism, and periodontitis. These characteristics could help dentists identify patients at higher risk of developing DM. Patients without these characteristics still have UDM, so dentists performing chairside diabetes screening for all patients would yield additional benefit. PRACTICAL IMPLICATIONS: Dental offices are a major point of contact within the US health care system. Diabetes screening in this setting can provide important health information with direct relevance to patient care.
Asunto(s)
Diabetes Mellitus , Enfermedades Periodontales , Índice de Masa Corporal , Odontólogos , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/epidemiología , Humanos , Tamizaje Masivo , Enfermedades Periodontales/diagnóstico , Enfermedades Periodontales/epidemiología , Enfermedades no DiagnosticadasRESUMEN
PURPOSE: To determine whether periodontal disease is positively associated with incident diabetes across the continuum of body mass levels (BMI) and test the hypothesis that the periodontal risk for incident diabetes is modified by BMI. METHODS: We included 5569 diabetes-free participants from Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities study and followed them until 2018. Periodontal disease status was classified by periodontal profile class (PPC)-Stages , and incident diabetes was based on participant report of physician diagnosis. We estimated the hazard ratios (HR) for diabetes using a competing risk model for each PPC-Stage. We assessed multiplicative interactions between periodontal disease and BMI (as a continuous variable) on risk of diabetes. RESULTS: During a median time of 19.4 years of follow-up, 1348 incident diabetes cases and 1529 deaths occurred. Compared to the "Health/Incidental Disease" stage, participants with PPC "Severe Periodontal Disease" or "Severe Tooth Loss" stage and lower BMI had elevated risk for diabetes adjusting for demographic, smoking, education, and biological variables when accounting for death as a competing risk with HRs of 1.76 (95% CI 1.10-2.80) and 2.11 (95% CI 1.46-3.04), respectively. The interaction between PPC-Stages and BMI was significant (Pâ =â 0.01). No significant associations of PPC-Stages with incident diabetes were present when BMI was above 31 kg/m2. CONCLUSION: Periodontal disease was associated with incident diabetes, especially in nonobese participants. Dentists should be aware that periodontal disease is associated with incident diabetes but the association may be modified for patient's at higher BMI levels.