At least three phenotypes exist among periodontitis patients

Evaluation of health screening data for factors associated with peri-implant bone loss

PURPOSE

Systemic health has a profound effect on dental treatment. The aim of this study was to evaluate peri-implant bone loss and health screening data to discover factors that may influence peri-implant diseases.

METHODS

This study analyzed the panoramic X-rays of patients undergoing health screenings at the Health Promotion Center at Seoul St. Mary's Hospital in 2018, to investigate the relationship between laboratory test results and dental data. The patients' physical data, such as height, weight, blood pressure, hematological and urine analysis data, smoking habits, number of remaining teeth, alveolar bone level, number of implants, and degree of bone loss around the implant, were analyzed for correlations. Their associations with glycated hemoglobin, glucose, blood urea nitrogen (BUN), creatinine, and severity of periodontitis were evaluated using univariate and multivariate regression analysis.

RESULTS

In total, 2,264 patients opted in for dental health examinations, of whom 752 (33.2%) had undergone dental implant treatment. These 752 patients had a total of 2,658 implants, and 129 (17.1%) had 1 or more implants with peri-implant bone loss of 2 mm or more. The number of these implants was 204 (7%). Body mass index and smoking were not correlated with peri-implant bone loss. Stepwise multivariate regression analysis revealed that the severity of periodontal bone loss (moderate bone loss: odds ratio [OR], 3.154; 95% confidence interval [CI], 1.175-8.475 and severe bone loss: OR, 7.751; 95% CI, 3.003-20) and BUN (OR, 1.082; 95% CI, 1.027-1.141) showed statistically significant predictive value. The severity of periodontitis showed greater predictive value than the biochemical parameters of blood glucose, renal function, and liver function.

CONCLUSIONS

The results of this study showed that periodontal bone loss was a predictor of peri-implant bone loss, suggesting that periodontal disease should be controlled before dental treatment. Diligent maintenance care is recommended for patients with moderate to severe periodontal bone loss.

Three periodontitis phenotypes: Bone loss patterns, antibiotic-surgical treatment and the new classification

AIM

To compare three periodontitis clusters (A, B and C) for alveolar bone loss (ABL) patterns, antibiotic prescriptions and surgeries and to relate them to the new classification of periodontitis.

MATERIALS AND METHODS

ABL patterns, prescription of systemic antibiotics and the number of surgeries were retrieved for all patients (n = 353) in the clusters. Comparisons and possible predictors for antibiotics were assessed, and results also evaluated in relation to the new classification.

RESULTS

Cluster A is characterized by angular defects often affecting the first molars and localized stage III/IV grade C periodontitis. Cluster B contains mainly localized or generalized stage III/IV, grade C patients. Cluster C contains mainly patients with generalized stage III/IV grade C periodontitis. Patients in cluster A received significantly more antibiotics compared to B and C (78% vs. 23% and 17%); the predictors for antibiotic prescription were young age and localized ABL. No differences in numbers of periodontal surgeries were observed between clusters (A = 1.0 ± 1.4, B = 1.3 ± 1.4 and C = 1.3 ± 1.5).

CONCLUSIONS

Within stage III/IV grade C periodontitis, we could detect three clusters of patients. The distinct localized ABL pattern and younger age in cluster A presumably prompted clinicians to prescribe antibiotics.

The role of inflammation and genetics in periodontal disease

Periodontitis is a complex disease: (a) various causative factors play a role simultaneously and interact with each other; and (b) the disease is episodic in nature, and bursts of disease activity can be recognized, ie, the disease develops and cycles in a nonlinear fashion. We recognize that various causative factors determine the immune blueprint and, consequently, the immune fitness of a subject. Normally, the host lives in a state of homeostasis or symbiosis with the oral microbiome; however, disturbances in homeostatic balance can occur, because of an aberrant host response (inherited and/or acquired during life). This imbalance results from hyper- or hyporesponsiveness and/or lack of sufficient resolution of inflammation, which in turn is responsible for much of the disease destruction seen in periodontitis. The control of this destruction by anti-inflammatory processes and proresolution processes limits the destruction to the tissues surrounding the teeth. The local inflammatory processes can also become systemic, which in turn affect organs such as the heart. Gingival inflammation also elicits changes in the ecology of the subgingival environment providing optimal conditions for the outgrowth of gram-negative, anaerobic species, which become pathobionts and can propagate periodontal inflammation and can further negatively impact immune fitness. The factors that determine immune fitness are often the same factors that determine the response to the resident biofilm, and are clustered as follows: (a) genetic and epigenetic factors; (b) lifestyle factors, such as smoking, diet, and psychosocial conditions; (c) comorbidities, such as diabetes; and (d) local and dental factors, as well as randomly determined factors (stochasticity). Of critical importance are the pathobionts in a dysbiotic biofilm that drive the viscious cycle. Focusing on genetic factors, currently variants in at least 65 genes have been suggested as being associated with periodontitis based on genome-wide association studies and candidate gene case control studies. These studies have found pleiotropy between periodontitis and cardiovascular diseases. Most of these studies point to potential pathways in the pathogenesis of periodontal disease. Also, most contribute to a small portion of the total risk profile of periodontitis, often limited to specific racial and ethnic groups. To date, 4 genetic loci are shared between atherosclerotic cardiovascular diseases and periodontitis, ie, CDKN2B-AS1(ANRIL), a conserved noncoding element within CAMTA1 upstream of VAMP3, PLG, and a haplotype block at the VAMP8 locus. The shared genes suggest that periodontitis is not causally related to atherosclerotic diseases, but rather both conditions are sequelae of similar (the same?) aberrant inflammatory pathways. In addition to variations in genomic sequences, epigenetic modifications of DNA can affect the genetic blueprint of the host responses. This emerging field will yield new valuable information about susceptibility to periodontitis and subsequent persisting inflammatory reactions in periodontitis. Further studies are required to verify and expand our knowledge base before final cause and effect conclusions about the role of inflammation and genetic factors in periodontitis can be made.

Unique etiologic, demographic, and pathologic characteristics of localized aggressive periodontitis support classification as a distinct subcategory of periodontitis

BACKGROUND

Localized aggressive periodontitis (LAgP) occurs in 2% of African-American adolescents but only 0.15% of white adolescents. First molars and incisors are affected by rapid onset and progression.

METHODS

This nonsystematic critical review evaluated published data for LAgP and chronic periodontitis (CP), focusing on potential differences in epidemiology, microbiology, immunology, genetics, and response to therapy.

RESULTS

LAgP differs from CP by localization to incisors and first molars, early onset and rapid progression in adolescents and young adults, and a 10-fold higher prevalence in populations of African or Middle Eastern origin, often with strong familial aggregation. The bacterium Aggregatibacter actinomycetemcomitans and hyperresponsive neutrophils are frequently observed. Antibiotic and nonsurgical therapies are highly effective.

CONCLUSIONS

LAgP differs in many ways from the far more common CP that affects older adults. The substantial evidence of dissimilarities summarized in this review strongly supports the classification of LAgP as a distinct form of periodontitis.

PRACTICAL IMPLICATIONS

Classifying LAgP as a distinct subcategory of periodontitis will encourage future research and does not conflict with the newly proposed "staging and grading" system. The silent onset and rapid progression of LAgP make early diagnosis and frequent follow-up with patients essential for effective treatment.

Hidden noise in immunologic parameters might explain rapid progression in early-onset periodontitis

To investigate in datasets of immunologic parameters from early-onset and late-onset periodontitis patients (EOP and LOP), the existence of hidden random fluctuations (anomalies or noise), which may be the source for increased frequencies and longer periods of exacerbation, resulting in rapid progression in EOP. Principal component analysis (PCA) was applied on a dataset of 28 immunologic parameters and serum IgG titers against periodontal pathogens derived from 68 EOP and 43 LOP patients. After excluding the PCA parameters that explain the majority of variance in the datasets, i.e. the overall aberrant immune function, the remaining parameters of the residual subspace were analyzed by computing their sample entropy to detect possible anomalies. The performance of entropy anomaly detection was tested by using unsupervised clustering based on a log-likelihood distance yielding parameters with anomalies. An aggregate local outlier factor score (LOF) was used for a supervised classification of EOP and LOP. Entropy values on data for neutrophil chemotaxis, CD4, CD8, CD20 counts and serum IgG titer against Aggregatibacter actinomycetemcomitans indicated the existence of possible anomalies. Unsupervised clustering confirmed that the above parameters are possible sources of anomalies. LOF presented 94% sensitivity and 83% specificity in identifying EOP (87% sensitivity and 83% specificity in 10-fold cross-validation). Any generalization of the result should be performed with caution due to a relatively high false positive rate (17%). Random fluctuations in immunologic parameters from a sample of EOP and LOP patients were detected, suggesting that their existence may cause more frequently periods of disease activity, where the aberrant immune response in EOP patients result in the phenotype "rapid progression".

Clinical presentation of two phenotypes of tooth wear patients

OBJECTIVE

To assess the clinical presentation of wear lesions in two phenotypes of tooth wear (TW) patients based on distribution and morphological features of wear.

MATERIALS AND METHODS

103 patients (mean age = 43.1 years) were divided into two groups based on cluster analysis; cluster A (61 patients) and cluster B (42 patients). The distribution of wear lesions, scores of presence or absence of 10 defined morphological TW criteria and number of teeth fulfilling each criteria were compared between groups. Intra- and inter-examiner reliability of the 10 TW criteria was determined by Cohen's kappa and intraclass correlation coefficient.

RESULTS

While cluster A had more wear in maxillary anterior teeth and mandibular molars compared with the same opposing tooth groups (p < 0.001, p < 0.007 respectively), there were no differences for cluster B. Cluster A was characterized by higher prevalence of 4 chemical morphological criteria and the highest number of teeth affected by one chemical criteria, whereas cluster B had a higher prevalence of one mechanical criteria and higher number of teeth affected by an additional mechanical criteria. Both intra- and inter-examiner values for the defined TW criteria were fair to excellent.

CONCLUSION

The results may indicate a more chemical background for TW in cluster A and mechanical background in cluster B. Furthermore, clinicians may use certain clinical features of TW to distinguish between individuals who belong to a specific TW cluster with a presumed chemical or mechanical etiology. These preliminary findings need to be confirmed in future studies.