Harvest graft substitute for soft tissue volume augmentation around existing implants: A randomized, controlled and blinded multicenter trial.

BACKGROUND: Using a single-blind, randomized, controlled, multicenter, practice-based clinical trial, a volume-stable collagen matrix (VCMX) was compared with connective tissue graft (CTG) for soft tissue augmentation around existing dental implants. METHODS: Sixty patients (31 VCMX and 31 CTG) were included. The primary outcome was a soft tissue thickness change 3 mm below the gingival margin (GM). Secondary outcomes included clinical measures, such as keratinized tissue widths (KTw), probing pocket depths, and pink esthetic scores, and patient-reported outcomes (PRO). RESULTS: There were no significant differences between test and control patient demographics or clinical measures throughout the 1-year study. VCMX "grafts" were by design larger than CTG, and surgery time was less (27% less, p = 0.0005). Three millimeters below the GM (primary endpoint), tissue thickness increase was noninferior for VCMX compared with CTG (0.93 ± 0.80 mm vs. 1.10 ± 0.51 mm, respectively), inferior (by 0.25 mm) at 1 mm, and noninferior at 5 mm. Postoperative pain was significantly less for VCMX patients (p < 0.0001), but all other PRO measures, including esthetics and satisfaction, improved similarly for both therapies. CONCLUSIONS: Given the inclusion criteria for this study, namely soft tissue augmentation around existing implants with some evidence of KTw and minimal recession, VCMX provided soft tissue thickness and volume increases similar (noninferior) to CTG. Clinical measures and PRO were similar between therapies-site sensitivity and esthetics improved similarly for both therapies-but surgery time and pain following surgery were significantly less for VCMX.

Efficacy of a harvest graft substitute for recession coverage and soft tissue volume augmentation: A randomized controlled trial.

BACKGROUND: The autogenous connective tissue graft (CTG) with coronally advanced flap (CTG+CAF) is the "gold standard" for recession defect coverage; however, researchers continue to pursue lower morbidity, more convenient and unlimited supply harvest graft substitutes, including those that could provide soft tissue volume augmentation. METHODS: A randomized, controlled, double-masked comparison of a volume-stable collagen matrix (VCMX) versus CTG was conducted at four clinical investigation sites. Single, contralateral, within patient matched-pair, RT1 recession defects were treated with VCMX+CAF (test) and CTG+CAF (control). The primary efficacy end point was percent root coverage at 6 months. Secondary efficacy end points included clinical measures such as soft tissue volume, attachment level, and keratinized tissue width. Patient-reported outcomes included measures such as discomfort, esthetics, and overall satisfaction; 6-month end point results were followed for 1 year. RESULTS: Thirty patients received control and test therapies, and all patients were available for follow-up measures. Average percent root coverage for CTG+CAF was 90.5% ± 14.87% versus 70.7% ± 28.26% for VCMX+CAF, P <0.0001. Both therapies produced significant soft tissue volume increases (84.8 ± 47.43 mm3 control versus 48.90 ± 35.58 mm3 test, P = 0.0006). The test, harvest graft substitute produced less postoperative pain and was preferred by patients at the 6-month end point. All other end point measures were not significantly different. CONCLUSIONS: VCMX+CAF root coverage was inferior to CTG+CAF but produced less morbidity and was preferred by patients. Case/patient selection and surgical technique appear key to achieving successful results with the harvest graft alternative.

Periodontal disease classifications and incident coronary heart disease in the Atherosclerosis Risk in Communities study.

BACKGROUND: Periodontal disease has been linked to coronary heart disease (CHD), but studies have been inconclusive. This study investigates the link between periodontal disease and incident CHD. METHODS: Baseline periodontal data from a full-mouth periodontal exam (N = 6,300) and CHD outcomes through 2017 were obtained from the Atherosclerosis Risk in Communities Study. Periodontitis was defined by the Periodontal Profile Class System adapted to Stages (PPC stages) and the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) index. Competing risk models were used to determine hazard ratios (HR) for incident CHD, congestive heart failure (CHF), and other causes of death. Secondary analysis included myocardial infarction (MI) and fatal CHD. RESULTS: Females comprised 56% of participants and males 44% with a combined mean age of 62.3 years (range: 52 to 74). Participants were followed for an average of 16.7 (SD: 5.5) years. In a fully adjusted model, PPC stage VII (Severe Tooth Loss) was moderately significantly related to incident CHD, (HR 1.51 [1.11 to 2.09]). PPC stage V (Mild Tooth Loss/High Gingival Inflammation) was significant for fatal CHD (HR, 5.27 [1.80 to 15.4]) and PPC stage VII was significant for incident MI (HR, 1.59 [1.13 to 2.23]). The CDC/AAP definition was not significantly associated with incident CHD. CONCLUSIONS: Incident CHD was moderately significantly associated with a specific stage of periodontal disease characterized by severe tooth loss, while none of the categories of the CDC/AAP were significantly associated. Thus, while periodontal therapy may improve oral health, it may be effective at impacting CHD incidence in only certain groups of people.

Three-Dimensional Volumetric Changes After Socket Augmentation with Deproteinized Bovine Bone and Collagen Matrix.

PURPOSE: Socket augmentation decreases the magnitude of alveolar ridge resorption, but the literature is limited in respect to quantifying soft tissue remodeling. The aim of this study was to determine the volumetric and linear dimensional changes at the buccal surface for both hard and soft tissues after socket augmentation treated with a xenogeneic collagen matrix in combination with bone grafting. MATERIALS AND METHODS: Twenty-four individuals indicated for tooth extraction were enrolled in this investigation. Each participant was randomly assigned to one of two groups: (1) deproteinized bovine bone + collagen plug, or (2) deproteinized bovine bone + xenogeneic collagen matrix. A cone beam computed tomography scan was taken prior to extraction and at 6 months postextraction. Intraoral scanning images were taken at baseline, 3 months, and 6 months postextraction. Hard and soft tissue analyses were performed to compare linear ridge remodeling and volumetric changes by noncontact reverse-engineering software. RESULTS: Both groups showed bone and soft tissue remodeling. For hard tissue remodeling, there was no significant difference between the collagen plug and collagen matrix groups. For soft tissue remodeling, the collagen matrix group showed a reduced soft tissue loss compared with the collagen plug group. The volumetric analysis demonstrated that the mean buccal soft tissue volume loss for the collagen matrix group was 68.6 mm3 compared with 87.6 mm3 found in the collagen plug group (P = .009) over a 6-month period. CONCLUSION: This clinical investigation provides early evidence of using the total tissue volume to compare soft and hard tissue remodeling after socket augmentation. The results of this study demonstrated that the use of a xenogeneic collagen matrix reduced the buccal soft tissue loss after tooth extraction, but additional studies are necessary to evaluate the clinical significance of soft tissue augmentation after tooth extraction.

Advances in precision oral health.

The concept of precision dentistry as it relates to precision medicine is relatively new to the field of oral health. Precision dentistry is a contemporary, multifaceted, data-driven approach to oral health care that uses individual characteristics to stratify similar patients into phenotypic groups. The objective is to provide clinicians with the information that will allow them to improve treatment planning and a patient's response to treatment. Providers that use a precision oral health approach would move away from using an "average treatment" for all patients with a particular diagnosis and move toward more specific treatments for patients within each diagnostic subgroup. Precision dentistry requires a method or a model that places each individual in a subgroup where each member is the same as every other member in relation to the disease of interest. Precision dentistry is a paradigm shift that requires a new way of thinking about diagnostic categories. This approach uses patients' risk factor data (including, but not limited to, genetic, environmental, and health behavioral), rather than expert opinion or clinical presentation alone, to redefine traditional categories of health and disease. We review aspects of current efforts to allow precision dentistry to be realized and focus on one of the major innovations that may help precision dentistry to be practiced by periodontists, the World Workshop Model. Another approach is the Periodontal Profile Class system. These two approaches represent examples of supervised and unsupervised learning systems, respectively. This review compares and contrasts these two learning systems for their ability to classify patients into homogeneous disease and risk groups, as well as their feasibility at achieving the objective of enabling precision dentistry. We conclude that: (a) the World Workshop Model concept of stages and grades works as expected, in that periodontal status appears to be more serious in each successive stage. In addition, the seriousness and the complexity of the disease are greater as the grade increases within each stage. Stages and grades are important for precision dentistry because they consider the risk of future disease and the prognosis, and enable practitioners to use more signs, symptoms, and other associated factors when placing a patient in a diagnostic category; (b) the assignment of stages and grades using unsupervised learning systems is superior to using supervised learning systems for the prediction of 10-year tooth loss and 3-year attachment loss progression. In addition, the unsupervised learning approach (Periodontal Profile Class stages) results in stronger associations between the periodontal phenotypes and systemic diseases and conditions (prevalent diabetes, C-reactive protein, and incident stroke). This probably occurs because an unsupervised learning model produces more data-driven, mutually exclusive, homogeneous groups than a supervised learning model.

Genomics of periodontal disease and tooth morbidity.

In this review we critically summarize the evidence base and the progress to date regarding the genomic basis of periodontal disease and tooth morbidity (ie, dental caries and tooth loss), and discuss future applications and research directions in the context of precision oral health and care. Evidence for these oral/dental traits from genome-wide association studies first emerged less than a decade ago. Basic and translational research activities in this domain are now under way by multiple groups around the world. Key departure points in the oral health genomics discourse are: (a) some heritable variation exists for periodontal and dental diseases; (b) the environmental component (eg, social determinants of health and behavioral risk factors) has a major influence on the population distribution but probably interacts with factors of innate susceptibility at the person-level; (c) sizeable, multi-ethnic, well-characterized samples or cohorts with high-quality measures on oral health outcomes and genomics information are required to make decisive discoveries; (d) challenges remain in the measurement of oral health and disease, with current periodontitis and dental caries traits capturing only a part of the health-disease continuum, and are little or not informed by the underlying biology; (e) the substantial individual heterogeneity that exists in the clinical presentation and lifetime trajectory of oral disease can be identified and leveraged in a precision medicine framework or, if unappreciated, can hamper translational efforts. In this review we discuss how composite or biologically informed traits may offer improvements over clinically defined ones for the genomic interrogation of oral diseases. We demonstrate the utility of the results of genome-wide association studies for the development and testing of a genetic risk score for severe periodontitis. We conclude that exciting opportunities lie ahead for improvements in the oral health of individual patients and populations via advances in our understanding of the genomic basis of oral health and disease. The pace of new discoveries and their equitable translation to practice will largely depend on investments in the education and training of the oral health care workforce, basic and population research, and sustained collaborative efforts..

Periapical Microsurgery: A 4-dimensional Analysis of Healing Patterns.

INTRODUCTION: Currently, the success of periapical microsurgery is determined by the restoration of the lamina dura and the elimination of symptoms. However, inadequate site preservation may prevent later implant placement. Although not possible before, the advent of cone-beam computed tomographic imaging and computer-aided registration allows for indirect and accurate 3-dimensional analysis of the surgical site over time. This study analyzed the volumetric healing pattern of the buccal plate after periapical microsurgery, with a specific focus on the buccolingual thickness of bone and the regression of the surface contour of the cortical plate. METHODS: Thirty-seven patients were scheduled for follow-up at least 1 year after periapical microsurgery (median = 25 months, total range = 12-31 months). Volumetric healing was analyzed by converting preoperative and postoperative cone-beam computed tomographic images into digital 3-dimensional models. The models were then registered to be able to analyze the changes in volume over time. Analysis was completed using Geomagic software (3D Systems, Rock Hill, SC), which allowed for registration of the volumes, calculation of volume change, and calculation of the margin of error. RESULTS: Twelve cases qualified for volumetric analysis. The median volumetric reduction of the cortical plate was -24.9 mm3 (interquartile range = -8.94 to -67 mm3), with an average linear error of 0.7 mm. This corresponded to an average loss in buccolingual dimension of 0.1-0.25 mm. Regression of the cortical plate was within the margin of error in all cases. CONCLUSIONS: After periapical microsurgery, and in the absence of grafting materials or membranes, healing occurs with little to no regression of the buccal cortical plate.

Comparing Initial Wound Healing and Osteogenesis of Porous Tantalum Trabecular Metal and Titanium Alloy Materials.

Porous tantalum trabecular metal (PTTM) has long been used in orthopedics to enhance neovascularization, wound healing, and osteogenesis; recently, it has been incorporated into titanium alloy dental implants. However, little is known about the biological responses to PTTM in the human oral cavity. We have hypothesized that, compared with conventional titanium alloy, PTTM has a greater expression of genes specific to neovascularization, wound healing, and osteogenesis during the initial healing period. Twelve subjects requiring at least 4 implants in the mandible were enrolled. Four 3 × 5mm devices, including 2 titanium alloy tapered screws and 2 PTTM cylinders, were placed in the edentulous mandibular areas using a split-mouth design. One device in each group was trephined for analysis at 2 and 4 weeks after placement. RNA microarray analysis and ingenuity pathway analysis were used to analyze osteogenesis gene expression and relevant signaling pathways. Compared to titanium alloy, PTTM samples exhibited significantly higher expressions of genes specific to cell neovascularization, wound healing, and osteogenesis. Several genes-including bone morphogenic proteins, collagens, and growth factors-were upregulated in the PTTM group compared to the titanium alloy control. PTTM materials may enhance the initial healing of dental implants by modifying gene expression profiles.

An experimental murine model to study periodontitis.

Periodontal disease (PD) is a common dental disease associated with the interaction between dysbiotic oral microbiota and host immunity. It is a prevalent disease, resulting in loss of gingival tissue, periodontal ligament, cementum and alveolar bone. PD is a major form of tooth loss in the adult population. Experimental animal models have enabled the study of PD pathogenesis and are used to test new therapeutic approaches for treating the disease. The ligature-induced periodontitis model has several advantages as compared with other models, including rapid disease induction, predictable bone loss and the capacity to study periodontal tissue and alveolar bone regeneration because the model is established within the periodontal apparatus. Although mice are the most convenient and versatile animal models used in research, ligature-induced periodontitis has been more frequently used in large animals. This is mostly due to the technical challenges involved in consistently placing ligatures around murine teeth. To reduce the technical challenge associated with the traditional ligature model, we previously developed a simplified method to easily install a bacterially retentive ligature between two molars for inducing periodontitis. In this protocol, we provide detailed instructions for placement of the ligature and demonstrate how the model can be used to evaluate gingival tissue inflammation and alveolar bone loss over a period of 18 d after ligature placement. This model can also be used on germ-free mice to investigate the role of human oral bacteria in periodontitis in vivo. In conclusion, this protocol enables the mechanistic study of the pathogenesis of periodontitis in vivo.

GWAS for Interleukin-1ß levels in gingival crevicular fluid identifies IL37 variants in periodontal inflammation.

There is no agnostic GWAS evidence for the genetic control of IL-1ß expression in periodontal disease. Here we report a GWAS for "high" gingival crevicular fluid IL-1ß expression among 4910 European-American adults and identify association signals in the IL37 locus. rs3811046 at this locus (p = 3.3 × 10-22) is associated with severe chronic periodontitis (OR = 1.50; 95% CI = 1.12-2.00), 10-year incident tooth loss (≥3 teeth: RR = 1.33; 95% CI = 1.09-1.62) and aggressive periodontitis (OR = 1.12; 95% CI = 1.01-1.26) in an independent sample of 4927 German/Dutch adults. The minor allele at rs3811046 is associated with increased expression of IL-1ß in periodontal tissue. In RAW macrophages, PBMCs and transgenic mice, the IL37 variant increases expression of IL-1ß and IL-6, inducing more severe periodontal disease, while IL-37 protein production is impaired and shows reduced cleavage by caspase-1. A second variant in the IL37 locus (rs2708943, p = 4.2 × 10-7) associates with attenuated IL37 mRNA expression. Overall, we demonstrate that IL37 variants modulate the inflammatory cascade in periodontal disease.

Periodontal profile classes predict periodontal disease progression and tooth loss.

BACKGROUND: Current periodontal disease taxonomies have limited utility for predicting disease progression and tooth loss; in fact, tooth loss itself can undermine precise person-level periodontal disease classifications. To overcome this limitation, the current group recently introduced a novel patient stratification system using latent class analyses of clinical parameters, including patterns of missing teeth. This investigation sought to determine the clinical utility of the Periodontal Profile Classes and Tooth Profile Classes (PPC/TPC) taxonomy for risk assessment, specifically for predicting periodontal disease progression and incident tooth loss. METHODS: The analytic sample comprised 4,682 adult participants of two prospective cohort studies (Dental Atherosclerosis Risk in Communities Study and Piedmont Dental Study) with information on periodontal disease progression and incident tooth loss. The PPC/TPC taxonomy includes seven distinct PPCs (person-level disease pattern and severity) and seven TPCs (tooth-level disease). Logistic regression modeling was used to estimate relative risks (RR) and 95% confidence intervals (CI) for the association of these latent classes with disease progression and incident tooth loss, adjusting for examination center, race, sex, age, diabetes, and smoking. To obtain personalized outcome propensities, risk estimates associated with each participant's PPC and TPC were combined into person-level composite risk scores (Index of Periodontal Risk [IPR]). RESULTS: Individuals in two PPCs (PPC-G: Severe Disease and PPC-D: Tooth Loss) had the highest tooth loss risk (RR = 3.6; 95% CI = 2.6 to 5.0 and RR = 3.8; 95% CI = 2.9 to 5.1, respectively). PPC-G also had the highest risk for periodontitis progression (RR = 5.7; 95% CI = 2.2 to 14.7). Personalized IPR scores were positively associated with both periodontitis progression and tooth loss. CONCLUSIONS: These findings, upon additional validation, suggest that the periodontal/tooth profile classes and the derived personalized propensity scores provide clinical periodontal definitions that reflect disease patterns in the population and offer a useful system for patient stratification that is predictive for disease progression and tooth loss.

Periodontal profile class is associated with prevalent diabetes, coronary heart disease, stroke, and systemic markers of C-reactive protein and interleukin-6.

BACKGROUND: This paper focuses on the Periodontal Profile Class (PPC) System that may be more informative and representative of periodontitis phenotypes than current case definitions of periodontitis. This study illustrates the unique aspects of the PPC compared with other periodontal indices for studying associations between periodontal disease and prevalent systemic conditions. METHODS: We computed odds ratios and 95% confidence intervals to compare associations between periodontal disease and prevalent systemic conditions using our new PPC and two traditional indices. We used the Bayesian Information Criterion (BIC) to determine the fit of the model and the magnitude of the contribution attributable to periodontal disease beyond traditional risk factors. The Atherosclerosis Risk in Communities (ARIC) Study (1996-1998) results were compared with results from the combined National Health and Nutrition Examination Survey 2009-2014 datasets. RESULTS: In the ARIC Study, high gingival inflammation, tooth loss, severe tooth loss, and severe disease PPC components were significantly associated with diabetes, coronary heart disease (CHD), high-sensitivity C-reactive protein, and interleukin (IL)-6, while only severe disease was associated with stroke. Severe disease was associated with CHD using the Centers for Disease Control/American Academy of Periodontology index, and the European Periodontal index was associated with CHD and IL-6. CONCLUSIONS: The addition of the PPC to traditional variables associated with prevalent diabetes, stroke, CHD, and systemic measures of inflammation resulted in very strong improvement of the overall models, while the traditional indices were less likely to be associated and, if present, the associations were weaker. The PPC system provides specific insight into the individuals and periodontal characteristics of the phenotype that are associated with systemic conditions that may be useful in designing treatment interventions.

In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P3 ) system.

BACKGROUND: This paper focuses on Periodontal Profile Class (PPC), a component of the Periodontal Profile Phenotype (P3 ) System that may be more representative of the periodontitis phenotype than current case definitions of periodontitis. Data illustrate the unique aspects of the PPC compared with other commonly used periodontal classification indices. METHODS: Latent Class Analysis (LCA) identified discrete classes of individuals grouped by tooth-level clinical parameters. The analysis defined seven distinct periodontal profile classes (PPC A through G) and seven distinct tooth profile classes (TPC A through G). This LCA classification was an entirely data-derived agnostic process without any preconceived presumptions of what constituted disease. RESULTS: Comparing the PPC with the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) and European indices, the PPC is unique in that it contains four disease classes not traditionally used. Less than half of individuals classified as Healthy by both the CDC/AAP and European indices were Healthy using the PPC. About 25% of those classified as Severe by CDC/AAP and European indices were PPC-Severe. The remainder spread out over the High Gingival Index, Posterior Disease, Tooth Loss, and Severe Tooth Loss phenotypes. CONCLUSIONS: The PPC classification provides a significant departure from the traditional clinical case status indices that have been used, but has resulted in clinical phenotypes that are quite familiar to most clinicians who take notice of the distribution of missing teeth, areas of recession, diminished periodontal support, and other aspects of the dentition while conducting a periodontal examination. The mutually exclusive categories provided by the PPC system provide periodontal clinical summaries that can be an important component of precision dentistry.

Periodontal Disease, Regular Dental Care Use, and Incident Ischemic Stroke.

BACKGROUND AND PURPOSE: Periodontal disease is independently associated with cardiovascular disease. Identification of periodontal disease as a risk factor for incident ischemic stroke raises the possibility that regular dental care utilization may reduce the stroke risk. METHODS: In the ARIC (Atherosclerosis Risk in Communities) study, pattern of dental visits were classified as regular or episodic dental care users. In the ancillary dental ARIC study, selected subjects from ARIC underwent fullmouth periodontal measurements collected at 6 sites per tooth and classified into 7 periodontal profile classes (PPCs). RESULTS: In the ARIC study 10 362 stroke-free participants, 584 participants had incident ischemic strokes over a 15-year period. In the dental ARIC study, 6736 dentate subjects were assessed for periodontal disease status using PPC with a total of 299 incident ischemic strokes over the 15-year period. The 7 levels of PPC showed a trend toward an increased stroke risk (χ2 trend P<0.0001); the incidence rate for ischemic stroke/1000-person years was 1.29 for PPC-A (health), 2.82 for PPC-B, 4.80 for PPC-C, 3.81 for PPC-D, 3.50 for PPC-E, 4.78 for PPC-F, and 5.03 for PPC-G (severe periodontal disease). Periodontal disease was significantly associated with cardioembolic (hazard ratio, 2.6; 95% confidence interval, 1.2-5.6) and thrombotic (hazard ratio, 2.2; 95% confidence interval, 1.3-3.8) stroke subtypes. Regular dental care utilization was associated with lower adjusted stroke risk (hazard ratio, 0.77; 95% confidence interval, 0.63-0.94). CONCLUSIONS: We confirm an independent association between periodontal disease and incident stroke risk, particularly cardioembolic and thrombotic stroke subtype. Further, we report that regular dental care utilization may lower this risk for stroke.

Derivation and Validation of the Periodontal and Tooth Profile Classification System for Patient Stratification.

BACKGROUND: The goal of this study is to use bioinformatics tools to explore identification and definition of distinct periodontal and tooth profile classes (PPCs/TPCs) among a cohort of individuals by using detailed clinical measures at the tooth level, including both periodontal measurements and tooth loss. METHODS: Full-mouth clinical periodontal measurements (seven clinical parameters) from 6,793 individuals from the Dental Atherosclerosis Risk in Communities Study (DARIC) were used to identify PPC. A custom latent class analysis (LCA) procedure was developed to identify clinically distinct PPCs and TPCs. Three validation cohorts were used: NHANES (2009 to 2010 and 2011 to 2012) and the Piedmont Study population (7,785 individuals). RESULTS: The LCA method identified seven distinct periodontal profile classes (PPCs A to G) and seven distinct tooth profile classes (TPCs A to G) ranging from health to severe periodontal disease status. The method enabled identification of classes with common clinical manifestations that are hidden under the current periodontal classification schemas. Class assignment was robust with small misclassification error in the presence of missing data. The PPC algorithm was applied and confirmed in three distinct cohorts. CONCLUSIONS: The findings suggest PPC and TPC using LCA can provide robust periodontal clinical definitions that reflect disease patterns in the population at an individual and tooth level. These classifications can potentially be used for patient stratification and thus provide tools for integrating multiple datasets to assess risk for periodontitis progression and tooth loss in dental patients.

Empathy differences by gender and specialty preference in medical students: a study in Brazil.

OBJECTIVE: We have conducted this study to assess medical students' empathy and to examine empathy differences by students' socio-demographic characteristics, including gender, and specialty preference. METHODS: We have conducted a cross-sectional and descriptive research. Among 595 medical students registered at the Federal University of Santa Catarina (Brazil) in 2012, we have selected a sample of 320 enrolled in the first, third, fifth, seventh, ninth, eleventh, and in the last semester of the course. The response rate obtained was 70.6% (n=226). Data was collected by using a self-report questionnaire, and the variables analyzed included course semester, socio-demographic characteristics (such as age, gender, household monthly income and parents level of education), students' specialty preference, and empathy assessed by the Jefferson Scale of Empathy. We have used descriptive statistics, 95% Confidence Interval for percentages, Student's t-test, and Analysis of Variance to analyze the data. RESULTS: Mean empathy among students was (M=119.7, SD=9.9), with no difference by according to semester (F=1.5, p=.2). Empathy means were higher among females (M=118.3, SD=10.6) than among males (M=121.0, SD=9.3, t=-2.1, p=.032). Students who preferred a people-oriented specialty obtained significantly higher mean scores (M=121.5, SD=8.1) in comparison to students who preferred technology-oriented specialties (M=118.0, SD=11.3, t=2.4, p=.02). CONCLUSIONS: Our study has found consistently high scores of empathy among medical students enrolled in all levels of training at the Federal University of Santa Catarina, and higher empathy among women and students who intend to pursue a people-oriented specialty. Conclusions on higher empathy among medical students require further study.

Genome-wide association study of biologically informed periodontal complex traits offers novel insights into the genetic basis of periodontal disease.

Genome-wide association studies (GWAS) of chronic periodontitis (CP) defined by clinical criteria alone have had modest success to-date. Here, we refine the CP phenotype by supplementing clinical data with biological intermediates of microbial burden (levels of eight periodontal pathogens) and local inflammatory response (gingival crevicular fluid IL-1ß) and derive periodontal complex traits (PCTs) via principal component analysis. PCTs were carried forward to GWAS (∼2.5 million markers) to identify PCT-associated loci among 975 European American adult participants of the Dental ARIC study. We sought to validate these findings for CP in the larger ARIC cohort (n = 821 participants with severe CP, 2031-moderate CP, 1914-healthy/mild disease) and an independent German sample including 717 aggressive periodontitis cases and 4210 controls. We identified six PCTs with distinct microbial community/IL-1ß structures, although with overlapping clinical presentations. PCT1 was characterized by a uniformly high pathogen load, whereas PCT3 and PCT5 were dominated by Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis, respectively. We detected genome-wide significant signals for PCT1 (CLEC19A, TRA, GGTA2P, TM9SF2, IFI16, RBMS3), PCT4 (HPVC1) and PCT5 (SLC15A4, PKP2, SNRPN). Overall, the highlighted loci included genes associated with immune response and epithelial barrier function. With the exception of associations of BEGAIN with severe and UBE3D with moderate CP, no other loci were associated with CP in ARIC or aggressive periodontitis in the German sample. Although not associated with current clinically determined periodontal disease taxonomies, upon replication and mechanistic validation these candidate loci may highlight dysbiotic microbial community structures and altered inflammatory/immune responses underlying biological sub-types of CP.

Gingival crevicular fluid as a source of biomarkers for periodontitis.

In evaluating the pathogenesis of periodontal diseases, the diagnostic potential of gingival crevicular fluid has been extensively explored during the last twenty years, from initially just confirming health and disease states to more recently investigating it as a potential prognostic tool. As host susceptibility is a critical determinant in periodontal disease pathogenesis, the inflammatory mediator levels present in gingival crevicular fluid represent relevant risk indicators for disease activity. Considerable work has been carried out to identify the many different cytokine inflammatory pathways and microbial stimuli that are associated with periodontal disease pathogenesis. Now, 'omics' approaches aim to summarize how these pathways interact and probably converge to create critical inflammatory networks. More recently, gingival crevicular fluid metabolomics appears promising as an additional diagnostic method. Biofilm structure and the host inflammatory response to the microbial challenge may induce specific inflammatory signatures. Host genetics and epigenetics may also modulate microbial colonization, adding to the multiplicity of potential causal pathways. Omics analyses of gingival crevicular fluid, measuring microbial and host interactions in association with the onset and progression of periodontal diseases, still show the potential to expand the landscape for the discovery of diagnostic, prognostic and therapeutic markers.

TLR4, NOD1 and NOD2 mediate immune recognition of putative newly identified periodontal pathogens.

Periodontitis is a polymicrobial inflammatory disease that results from the interaction between the oral microbiota and the host immunity. Although the innate immune response is important for disease initiation and progression, the innate immune receptors that recognize both classical and putative periodontal pathogens that elicit an immune response have not been elucidated. By using the Human Oral Microbe Identification Microarray (HOMIM), we identified multiple predominant oral bacterial species in human plaque biofilm that strongly associate with severe periodontitis. Ten of the identified species were evaluated in greater depth, six being classical pathogens and four putative novel pathogens. Using human peripheral blood monocytes (HPBM) and murine bone-marrow-derived macrophages (BMDM) from wild-type (WT) and Toll-like receptor (TLR)-specific and MyD88 knockouts (KOs), we demonstrated that heat-killed Campylobacter concisus, Campylobacter rectus, Selenomonas infelix, Porphyromonas endodontalis, Porphyromonas gingivalis, and Tannerella forsythia mediate high immunostimulatory activity. Campylobacter concisus, C. rectus, and S. infelix exhibited robust TLR4 stimulatory activity. Studies using mesothelial cells from WT and NOD1-specific KOs and NOD2-expressing human embryonic kidney cells demonstrated that Eubacterium saphenum, Eubacterium nodatum and Filifactor alocis exhibit robust NOD1 stimulatory activity, and that Porphyromonas endodontalis and Parvimonas micra have the highest NOD2 stimulatory activity. These studies allowed us to provide important evidence on newly identified putative pathogens in periodontal disease pathogenesis showing that these bacteria exhibit different immunostimulatory activity via TLR4, NOD1, and NOD2 (Clinicaltrials.gov NCT01154855).

The Novel ASIC2 Locus is Associated with Severe Gingival Inflammation.

An increasing body of evidence suggests a significant genetic regulation of inflammatory response mechanisms; however, little is known regarding the genetic determinants of severe gingival inflammation (GI). We conducted a genome-wide association study of severe GI among 4077 European American adults, participants in the Dental Atherosclerosis Risk In Communities cohort. The severe GI trait was defined dichotomously using the 90th percentile of gingival index ≥2 extent score. Genotyping was performed with the Affymetrix 6.0 array platform and an imputed set of 2.5 million markers, based on HapMap Phase II CEU build 36, was interrogated. Genetic models were based on logistic regression and controlled for ancestry (10 principal components), sex, age, and examination center. One locus on chromosome 17 met genome-wide statistical significance criteria-lead single nucleotide polymorphism (SNP): rs11652874 [minor allele frequency=0.06, intronic to ASIC2 (acid sensing ionic channel-2, formerly named ACCN1); odds ratio=2.1, 95% confidence interval=1.6-2.7, p=3.9×10-8]. This association persisted among subjects with severe periodontitis and was robust to adjustment for microbial plaque index. Moreover, the minor [G] allele was associated with higher levels of severe GI in stratified analyses among subsets of participants with high load of either "red" or "orange" complex pathogens, although this association was not statistically significant. While these results will require replication in independent samples and confirmation by mechanistic studies, this locus appears as a promising candidate for severe gingival inflammation. Our findings suggest that genetic variation in ASIC2 is significantly associated with severe gingival inflammation and the association is plaque-independent.