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The aim of the present study was to construct a biological age score reflecting one’s physiologic capability and aging condition with respect to tooth loss over 10 y. From the follow-up to the population-based Study of Health in Pomerania (i.e., SHIP-2), 2,049 participants were studied for their baseline biomarker measures 10 y before (i.e., in SHIP-0). Metabolic and periodontal data were regressed onto chronological age to construct a score designated as “biological age.” For either sex separately, the impact of this individualized score was used to predict tooth loss in the follow-up cohort in comparison with each participant’s chronological age. Outcome data after 10 y with respect to tooth loss, periodontitis, obesity, and inflammation were shown to be better for biologically younger subjects than as expected by their chronological age, whereas for the older subjects, data were worse. Especially for tooth loss, a striking increase was observed in subjects whose biological age at baseline appeared to be higher than their chronological age. Biological age produced significantly better tooth loss predictions than chronological age (P < 0.001). Areas under receiver operating characteristic curves for tooth loss of ≥3 teeth in men during follow-up were 0.811 and 0.745 for biological and chronological age, respectively. For women, these figures were 0.788 and 0.724. For total tooth loss, areas under the curve were 0.890 and 0.749 in men and 0.872 and 0.752 in women. Biological age combines various measures into a single score and allows identifying individuals at increased risk of tooth loss.
Evidence is limited regarding whether periodontal treatment improves hemoglobin A1c (HbA1c) among people with prediabetes and periodontal disease, and it is unknown whether improvement of metabolic status persists >3 mo. In an exploratory post hoc analysis of the multicenter randomized controlled trial “Antibiotika und Parodontitis” (Antibiotics and Periodontitis)—a prospective, stratified, double-blind study—we assessed whether nonsurgical periodontal treatment with or without an adjunctive systemic antibiotic treatment affects HbA1c and high-sensitivity C-reactive protein (hsCRP) levels among periodontitis patients with normal HbA1c (≤5.7%, n = 218), prediabetes (5.7% < HbA1c < 6.5%, n = 101), or unknown diabetes (HbA1c ≥ 6.5%, n = 8) over a period of 27.5 mo. Nonsurgical periodontal treatment reduced mean pocket probing depth by >1 mm in both groups. In the normal HbA1c group, HbA1c values remained unchanged at 5.0% (95% CI, 4.9% to 6.1%) during the observation period. Among periodontitis patients with prediabetes, HbA1c decreased from 5.9% (95% CI, 5.9% to 6.0%) to 5.4% (95% CI, 5.3% to 5.5%) at 15.5 mo and increased to 5.6% (95% CI, 5.4% to 5.7%) after 27.5 mo. At 27.5 mo, 46% of periodontitis patients with prediabetes had normal HbA1c levels, whereas 47.9% remained unchanged and 6.3% progressed to diabetes. Median hsCRP values were reduced in the normal HbA1c and prediabetes groups from 1.2 and 1.4 mg/L to 0.7 and 0.7 mg/L, respectively. Nonsurgical periodontal treatment may improve blood glucose values among periodontitis patients with prediabetes (ClinicalTrials.gov NCT00707369).
Prediction models learn patterns from available data (training) and are then validated on new data (testing). Prediction modeling is increasingly common in dental research. We aimed to evaluate how different model development and validation steps affect the predictive performance of tooth loss prediction models of patients with periodontitis. Two independent cohorts (627 patients, 11,651 teeth) were followed over a mean ± SD 18.2 ± 5.6 y (Kiel cohort) and 6.6 ± 2.9 y (Greifswald cohort). Tooth loss and 10 patient- and tooth-level predictors were recorded. The impact of different model development and validation steps was evaluated: 1) model complexity (logistic regression, recursive partitioning, random forest, extreme gradient boosting), 2) sample size (full data set or 10%, 25%, or 75% of cases dropped at random), 3) prediction periods (maximum 10, 15, or 20 y or uncensored), and 4) validation schemes (internal or external by centers/time). Tooth loss was generally a rare event (880 teeth were lost). All models showed limited sensitivity but high specificity. Patients’ age and tooth loss at baseline as well as probing pocket depths showed high variable importance. More complex models (random forest, extreme gradient boosting) had no consistent advantages over simpler ones (logistic regression, recursive partitioning). Internal validation (in sample) overestimated the predictive power (area under the curve up to 0.90), while external validation (out of sample) found lower areas under the curve (range 0.62 to 0.82). Reducing the sample size decreased the predictive power, particularly for more complex models. Censoring the prediction period had only limited impact. When the model was trained in one period and tested in another, model outcomes were similar to the base case, indicating temporal validation as a valid option. No model showed higher accuracy than the no-information rate. In conclusion, none of the developed models would be useful in a clinical setting, despite high accuracy. During modeling, rigorous development and external validation should be applied and reported accordingly.
Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites (n = 284) obtained by mass spectrometry among a subsample (n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites (n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.
Abstract
Aim
The aim of this study was to evaluate the effect of non‐surgical periodontal therapy on circulating levels of the systemic inflammation‐associated biomarkers orosomucoid (ORM), high‐sensitivity C‐reactive protein (hsCRP), chemerin, and retinol‐binding protein 4 (RBP4) in overweight or normal‐weight patients with periodontitis at 27.5 months after therapy.
Materials and methods
This exploratory subanalysis includes patients from the ABPARO‐trial (ClinicalTrials.gov NCT00707369). The per‐protocol collective provided untreated periodontitis patients with high (≥28 kg/m2) or moderate (21–24 kg/m2) BMI. Out of the per‐protocol collective, 80 patients were randomly selected and stratified for BMI group, sex, and treatment group (antibiotics/placebo), resulting in 40 overweight and normal‐weight patients. Patients received non‐surgical periodontal therapy and maintenance at 3‐month intervals. Plasma samples from baseline and 27.5 months following initial treatment were used to measure the concentrations of ORM, hsCRP, chemerin, and RBP4.
Results
At the 27.5‐month examination, ORM and hsCRP decreased noticeably in the overweight group (ORM: p = .001, hsCRP: p = .004) and normal‐weight patients (ORM: p = .007, hsCRP: p < .001). Chemerin decreased in the overweight group (p = .048), and RBP4 concentrations remained stable.
Conclusion
Non‐surgical periodontal therapy reduced systemically elevated inflammation‐associated biomarkers in periodontitis patients. These improvements were more pronounced in overweight patients than in normal‐weight patients.
The long-term effectiveness of powered toothbrushes (PTBs) and interdental cleaning aids (IDAs) on a population level is unproven. We evaluated to what extent changes in PTB and IDA use may explain changes in periodontitis, caries, and tooth loss over the course of 17 y using data for adults (35 to 44 y) and seniors (65 to 74 y) from 3 independent cross-sectional surveys of the German Oral Health Studies (DMS). Oaxaca decomposition analyses assessed to what extent changes in mean probing depth (PD), number of caries-free surfaces, and number of teeth between 1) DMS III and DMS V and 2) DMS IV and DMS V could be explained by changes in PTB and IDA use. Between DMS III and V, PTB (adults: 33.5%; seniors: 28.5%) and IDA use (adults: 32.5%; seniors: 41.4%) increased along with an increase in mean PD, number of caries-free surfaces, and number of teeth. Among adults, IDA use contributed toward increased number of teeth between DMS III and V as well as DMS IV and V. In general, the estimates for adults were of lower magnitude. Among seniors between DMS III and V, PTB and IDA use explained a significant amount of explained change in the number of caries-free surfaces (1.72 and 5.80 out of 8.44, respectively) and the number of teeth (0.49 and 1.25 out of 2.19, respectively). Between DMS IV and V, PTB and IDA use contributed most of the explained change in caries-free surfaces (0.85 and 1.61 out of 2.72, respectively) and the number of teeth (0.25 and 0.46 out of 0.94, respectively) among seniors. In contrast to reported results from short-term clinical studies, in the long run, both PTB and IDA use contributed to increased number of caries-free healthy surfaces and teeth in both adults and seniors.
The aims of this study were to 1) determine if continuous eruption occurs in the maxillary teeth, 2) assess the magnitude of the continuous eruption, and 3) evaluate the effects of continuous eruption on the different periodontal parameters by using data from the population-based cohort of the Study of Health in Pomerania (SHIP). The jaw casts of 140 participants from the baseline (SHIP-0) and 16-y follow-up (SHIP-3) were digitized as 3-dimensional models. Robust reference points were set to match the tooth eruption stage at SHIP-0 and SHIP-3. Reference points were set on the occlusal surface of the contralateral premolar and molar teeth, the palatal fossa of an incisor, and the rugae of the hard palate. Reference points were combined to represent 3 virtual occlusal planes. Continuous eruption was measured as the mean height difference between the 3 planes and rugae fix points at SHIP-0 and SHIP-3. Probing depth, clinical attachment levels, gingiva above the cementoenamel junction (gingival height), and number of missing teeth were clinically assessed in the maxilla. Changes in periodontal variables were regressed onto changes in continuous eruption after adjustment for age, sex, number of filled teeth, and education or tooth wear. Continuous tooth eruption >1 mm over the 16 y was found in 4 of 140 adults and averaged to 0.33 mm, equaling 0.021 mm/y. In the total sample, an increase in continuous eruption was significantly associated with decreases in mean gingival height (B = −0.34; 95% CI, −0.65 to −0.03). In a subsample of participants without tooth loss, continuous eruption was negatively associated with PD. This study confirmed that continuous eruption is clearly detectable and may contribute to lower gingival heights in the maxilla.
Abstract
Aim
To examine the associations between bone turnover markers and periodontitis in two cross‐sectional population‐based studies.
Materials and Methods
We used data from two independent adult samples (N = 4993), collected within the Study of Health in Pomerania project, to analyse cross‐sectional associations of N‐procollagen type 1 amino‐terminal propeptide (P1NP), C‐terminal cross‐linking telopeptide, osteocalcin, bone‐specific alkaline phosphatase (BAP), fibroblast growth factor 23, wingless‐type mouse mammary tumour virus integration site family member 5a (WNT5A), and sclerostin values with periodontitis. Confounder‐adjusted gamma and fractional response regression models were applied.
Results
Positive associations were found for P1NP with mean pocket probing depth (PPD; eβ=1.008; 95% confidence interval [CI]: 1.001–1.015), mean clinical attachment loss (mean CAL; eβ=1.027; 95% CI: 1.011–1.044), and proportion of sites with bleeding on probing (%BOP; eβ=1.055; 95% CI: 1.005–1.109). Similar associations were seen for BAP with %BOP (eβ=1.121; 95% CI: 1.042–1.205), proportion of sites with PPD ≥4 mm (%PPD4) (eβ=1.080; 95% CI: 1.005–1.161), and sclerostin with %BOP (eβ=1.308; 95% CI: 1.005–1.704). WNT5A was inversely associated with mean PPD (eβ=0.956; 95% CI: 0.920–0.993) and %PPD4 (eβ=0.794; 95% CI: 0.642–0.982).
Conclusions
This study revealed scattered associations of P1NP, BAP, WNT5A, and sclerostin with periodontitis, but the results are contradictory in the overall context. Associations reported in previous studies could not be confirmed.
Periodontitis is a multifactorial disease. The aim of this explorative study was to investigate the role of Interleukin-(IL)-1, IL-4, GATA-3 and Cyclooxygenase-(COX)-2 polymorphisms after non-surgical periodontal therapy with adjunctive systemic antibiotics (amoxicillin/metronidazole) and subsequent maintenance in a Caucasian population. Analyses were performed using blood samples from periodontitis patients of a multi-center trial (ClinicalTrials.gov NCT00707369=ABPARO-study). Polymorphisms were analyzed using quantitative real-time PCR. Clinical attachment levels (CAL), percentage of sites showing further attachment loss (PSAL) ≥1.3 mm, bleeding on probing (BOP) and plaque score were assessed. Exploratory statistical analysis was performed. A total of 209 samples were genotyped. Patients carrying heterozygous genotypes and single-nucleotide-polymorphisms (SNP) on the GATA-3-IVS4 +1468 gene locus showed less CAL loss than patients carrying wild type. Heterozygous genotypes and SNPs on the IL-1A-889, IL-1B +3954, IL-4-34, IL-4-590, GATA-3-IVS4 +1468 and COX-2-1195 gene loci did not influence CAL. In multivariate analysis, CAL was lower in patients carrying GATA-3 heterozygous genotypes and SNPs than those carrying wild-types. For the first time, effects of different genotypes were analyzed in periodontitis progression after periodontal therapy and during supportive treatment using systemic antibiotics demonstrating a slight association of GATA-3 gene locus with CAL. This result suggests that GATA-3 genotypes are a contributory but non-essential risk factor for periodontal disease progression.
Background
Observational and in-vivo research suggested a bidirectional relationship between depression and periodontitis. We estimated the genetic correlation and examined directionality of causation.
Methods
The study used summary statistics from published genome wide association studies, with sample sizes ranging from 45,563 to 797,563 individuals of European ancestry. We performed linkage disequilibrium score regression (LDSC) to estimate global correlation and used Heritability Estimation from Summary Statistics (ρ-HESS) to further examine local genetic correlation. Latent Heritable Confounder Mendelian randomization (LHC-MR), Causal Analysis using Summary Effect estimates (CAUSE), and conventional MR approaches assessed bidirectional causation.
Results
LDSC observed only weak genetic correlation (rg = 0.06, P-Value = 0.619) between depression and periodontitis. Analysis of local genetic correlation using ρ-HESS did not reveal loci of significant local genetic covariance. LHC-MR, CAUSE and conventional MR models provided no support for bidirectional causation between depression and periodontitis, with odds ratios ranging from 1.00 to 1.06 in either direction.
Conclusions
Results do not support shared heritability or a causal connection between depression and periodontitis.