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Periodontitis has low-prevalence, highly severe disease manifestations with an early onset and rapid progression. The diagnosis is based on severe destruction of the alveolar bone in adolescents and young adults. Genetic susceptibility variants and smoking are well-established risk factors, but their interactions in modifying disease susceptibility have not been studied. We aimed to identify genetic risk variants of early-onset periodontitis that unmask their effects on tobacco smoke exposure. To this end, we analyzed 79,780,573 common variants in 741 northwest Europeans diagnosed to have >30% bone loss at >2 teeth before 35 y of age, using imputed genotypes of the OmniExpress BeadChip. Never versus ever smokers were compared in a logistic regression analysis via a case-only approach. To explore the effect of tobacco smoke on the expression of the G×S-associated genes, cultures of primary gingival fibroblasts (n = 9) were exposed to cigarette smoke extract, and transcripts were quantified by reverse transcription polymerase chain reaction. We identified 16 loci for which our analysis suggested an association with G×S increased disease risk (P < 5 × 10-5). Nine loci had previously been reported to be associated with spirometric measures of pulmonary function by an earlier G×S genome-wide association study. Genome-wide significant cis expression quantitative trait loci were reported for G×S-associated single-nucleotide polymorphisms at ST8SIA1 and SOST, indicating a causal role of these genes in tobacco-related etiopathology. Notably, SOST is a negative regulator of bone growth, and ST8SIA1 has a role in tissue remodeling. Cigarette smoke extract significantly altered the expression of 2 associated genes: SSH1 (P = 5 × 10-07), which is required for NF-κB activation and innate immune responses to bacterial invasion, and ST8SIA1 (P = 0.0048). We conclude that the genetic predisposition to early-onset periodontitis is in part triggered by smoking and that tobacco smoke directly affects the expression of genes involved in bone homeostasis, tissue repair, and immune response. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: The link between bristle splaying and gingival recession is unclear. Methods: In a 12-month, parallel group, randomized, controlled clinical trial, 110 systemically healthy participants with pre-existing gingival recessions (pre-GR) were assigned to brush their teeth with either a manual (MT) or a powered toothbrush (PT). Every 3 months, toothbrushes and brush heads were replaced. Wear was measured using the Bristle-Splaying-Index (BSI), matched between groups and correlated to the change of pre-GR. Results: Data from 109 subjects (PT, 55; MT, 54) were analyzed. The overall mean BSI was found to be significantly lower ( p < 0.001) in the PT group (median 5.5; second and third quartile 1.9-10.0) as compared to the MT group (21.5; 15.0-30.5). After 12 months, pre-GR decreased significantly in the PT group (∆0.2 ± 0.1 mm; p < 0.001) and remained stable in the MT group (∆0.1 ± 0.1 mm; p > 0.05). In the MT group, higher BSI values were associated with a higher risk for increasing or stable recession over 12 months: odds ratio (95 % CI) = 27.9 (1.7; 452.9); p = 0.019. Conclusion: After a mean using time of 3 months, the PT group demonstrated a lower BSI than the MT group, and the greater bristle splaying was associated with a higher risk of increased (or stable) GR in subjects using a MT but not a PT. Clinical relevance: Compared to a manual toothbrush, powered toothbrushes seem to be utilized with less force and can be considered safe to use in patients with pre-existing gingival recession. [ABSTRACT FROM AUTHOR]

Background: Despite pleiotropic immunomodulatory effects of apolipoprotein E (apoE) in vitro, its effects on the clinical course of experimental autoimmune encephalomyelitis (EAE) and multiple sclerosis (MS) are still controversial. As sex hormones modify immunomodulatory apoE functions, they may explain contentious findings. This study aimed to investigate sex-specific effects of apoE on disease course of EAE and MS.Methods: MOG(35-55) induced EAE in female and male apoE-deficient mice was assessed clinically and histopathologically. apoE expression was investigated by qPCR. The association of the MS severity score (MSSS) and APOE rs429358 and rs7412 was assessed across 3237 MS patients using linear regression analyses.Results: EAE disease course was slightly attenuated in male apoE-deficient (apoE (-/-) ) mice compared to wildtype mice (cumulative median score: apoE (-/-)  = 2 [IQR 0.0-4.5]; wildtype = 4 [IQR 1.0-5.0]; n = 10 each group, p = 0.0002). In contrast, EAE was more severe in female apoE (-/-) mice compared to wildtype mice (cumulative median score: apoE (-/-)  = 3 [IQR 2.0-4.5]; wildtype = 3 [IQR 0.0-4.0]; n = 10, p = 0.003). In wildtype animals, apoE expression during the chronic EAE phase was increased in both females and males (in comparison to naïve animals; p < 0.001). However, in MS, we did not observe a significant association between MSSS and rs429358 or rs7412, neither in the overall analyses nor upon stratification for sex.Conclusions: apoE exerts moderate sex-specific effects on EAE severity. However, the results in the apoE knock-out model are not comparable to effects of polymorphic variants in the human APOE gene, thus pinpointing the challenge of translating findings from the EAE model to the human disease. [ABSTRACT FROM AUTHOR]