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Periodontitis is a chronic inflammatory, bacterially-driven disease of the tooth-supporting tissues that shares several risk factors and elements of host response with Alzheimer’s disease and related dementias (ADRD). Epidemiological studies have identified relatively consistent associations between adverse oral health conditions and ADRD. In this issue of the journal, a large study from the UK Biobank further explores these relationships along with MRI cognitive biomarkers. Despite its strength due to the large sample size, challenges in the study of periodontitis and neuroepidemiology markers include potential sampling bias, appropriate assessment of exposures, and the possibility of reverse causality.

AIMS: We sought to replicate findings from published genome-wide association studies, linking specific candidate gene loci with periodontitis-related clinical/microbial traits. METHODS: In the published GWAS, a total of 2,196 SNPs associated with periodontitis-related traits at a p≤5×10(−6) and mapped to 136 gene loci. The replication cohort included 1,124 individuals, 65–98 years old (67% female, 45% Hispanic, 30% Black, 23% White) with available genome-wide genotypes and full-mouth periodontal status. Microbial profiles using checkerboard DNA-DNA hybridization and 16SrRNA sequencing were available from 912 and 739 participants, respectively. FINDINGS: Using gene-specific p-values after linkage disequilibrium pruning, the following gene/phenotype associations replicated successfully: CLEC19A with edentulism and %teeth with PD≥4mm; IL37, HPVC1, TRPS1, ABHD12B, LDLRAD4, TGM3, GRK5 with %teeth with PD≥4mm; DAB2IP with presence of PD≥6mm; KIAA1715(LNPK), ROBO2, RAB28, LINC01017, NELL1, LDLRAD4(C18orF1), CRYBB2P1 with %teeth with CAL≥3 mm; RUNX2, LAMA2 with %teeth with CAL≥5 mm; and KIAA1715(LNPK) with high colonization by Aggregatibacter actinomycetemcomitans. In addition, CLEC19A, IQSEC1 and EMR1 associated with microbial abundance based on checkerboard data, LBP and NCR2 with abundance based on sequencing data, and NCR2 with microbial diversity based on sequencing data. CONCLUSIONS: Several gene loci identified in published GWAS as associated with periodontitis-related phenotypes replicated successfully in an elderly cohort.

Background: Periodontitis (a bacterially-driven, inflammatory disease) is a plausible risk factor for prediabetes and diabetes. We studied the association between clinical attachment loss (CAL – a cumulative measure of tooth-supporting tissues lost due to periodontitis), prediabetes, and glucose levels among non-diabetic younger adults. Hypothesis: We hypothesize that greater CAL is associated with higher levels of biomarkers of cardiometabolic risk cross-sectionally. Methods: We included n=1071 non-diabetic participants from the Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS) who underwent full-mouth periodontal examinations and provided fasting blood at baseline. Baseline enrollment occurred in two waves: Wave 1 (2011-2013; n=293) and Wave 2 (2016-2020; n=778). HbA1c and glucose were measured during clinical exams. Prediabetes was defined as fasting glucose between 100-125 mg/dL or HbA1c between 5.7-6.4% per American Diabetes Association guidelines. We computed prevalence ratios and 95% confidence intervals of prediabetes among 2 nd and 3 rd CAL tertiles (vs. 1 st tertile) via multivariable Poisson regression with robust variance estimation. Multivariable linear regression was used to assess the association between CAL tertiles (independent variable) and estimates of glucose and HbA1c. We adjusted for demographics, health variables, and study wave. Results: The mean age(SD) of participants was 32.3(9.6) years and 28% were male. Prediabetes prevalence was 8.7%. Multivariable adjusted prevalence ratios (95%CIs) for prediabetes in tertiles 2 and 3 (vs. 1) were 1.45(0.79,2.67) and 1.91(0.99,3.67), respectively, consistent with p for trend = 0.05 and stronger associations with continuous glucose and HbA1c (see Table ). Conclusion: CAL, a cumulative measure of periodontitis, was cross-sectionally associated with increased prediabetes prevalence, glucose and HbA1c.

Omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, are powerful means of generating comprehensive genome-level data sets on complex diseases. We have systematically assessed the transcriptome, microbiome, miRNome, and methylome of gingival and peri-implant tissues from human subjects and further studied the transcriptome of primary cells ex vivo, or in vitro after infection with periodontal pathogens.Our data offer new insight on the pathophysiology underlying periodontal and peri-implant diseases, a possible route to a better and earlier diagnosis of these highly prevalent chronic inflammatory diseases and thus, to a personalized and efficient treatment approach.Herein, we outline the laboratory steps required for the processing of periodontal cells and tissues for -omics analyses using current microarrays or next-generation sequencing technology.

Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences. Furthermore, machine learning methods facilitate the detection of additional patterns, beyond the mere identification of lists of features that differ between groups.Herein, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data using open-source tools. We outline a differential expression analysis pipeline that can be used for data from both arrays and sequencing experiments, and offers the possibility to account for random or fixed effects. Furthermore, we present an overview of the possibilities for a functional analysis of the obtained data including subsequent machine learning approaches in form of (i) supervised classification algorithms in class validation and (ii) unsupervised clustering in class discovery.

AIM We investigated differential DNA methylation in gingival tissues in periodontal health, gingivitis, and periodontitis, and its association with differential mRNA expression. MATERIALS AND METHODS Gingival tissues were harvested from individuals and sites with clinically healthy and intact periodontium, gingivitis, and periodontitis. Samples were processed for differential DNA methylation and mRNA expression using the IlluminaEPIC (850 K) and the IlluminaHiSeq2000 platforms, respectively. Across the three phenotypes, we identified differentially methylated CpG sites and regions, differentially expressed genes (DEGs), and genes with concomitant differential methylation at their promoters and expression were identified. The findings were validated using our earlier databases using HG-U133Plus2.0Affymetrix microarrays and Illumina (450 K) methylation arrays. RESULTS We observed 43,631 differentially methylated positions (DMPs) between periodontitis and health, and 536 DMPs between gingivitis and health (FDR

BACKGROUND: The recently published clinical practice guideline (CPG) for the treatment of periodontitis in stages I-III provided evidence-based recommendations for the treatment of periodontitis patients, defined according to the 2018 classification. Stage IV periodontitis shares the severity and complexity characteristics of stage III periodontitis, but includes the anatomical and functional sequelae of tooth and periodontal attachment loss (tooth flaring and drifting, bite collapse, etc.), which require additional interventions following completion of active periodontal therapy.AIM: To develop an S3 Level CPG for the treatment of stage IV periodontitis, focusing on the implementation of inter-disciplinary treatment approaches required to treat/rehabilitate patients following associated sequelae and tooth loss.MATERIALS AND METHODS: This S3 Level CPG was developed by the European Federation of Periodontology (EFP), following methodological guidance from the Association of Scientific Medical Societies in Germany and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process. A rigorous and transparent process included synthesis of relevant research in 13 specifically commissioned systematic reviews, evaluation of the quality and strength of evidence, the formulation of specific recommendations and a structured consensus process with leading experts and a broad base of stakeholders.RESULTS: The S3 Level CPG for the treatment of stage IV periodontitis culminated in recommendations for different interventions, including orthodontic tooth movement, tooth splinting, occlusal adjustment, tooth- or implant-supported fixed or removable dental prostheses and supportive periodontal care. Prior to treatment planning, it is critically important to undertake a definitive and comprehensive diagnosis and case evaluation, obtain relevant patient information, and engage in frequent re-evaluations during and after treatment. The periodontal component of therapy should follow the CPG for the treatment of periodontitis in stages I-III.CONCLUSIONS: The present S3 Level CPG informs clinical practice, health systems, policymakers and, indirectly, the public on the available and most effective modalities to treat patients with stage IV periodontitis and to maintain a healthy dentition over lifetime, according to the available evidence at the time of publication.

Aims We conducted a randomized controlled trial to assess the clinical outcomes of two loading protocols involving either immediate or delayed prosthetic temporization of single implants placed at posterior, healed sites. Materials and methods Forty-nine patients in need of single implants at premolar or molar sites were randomized to receive a temporary crown either immediately after implant placement or 3 months later. Randomization was stratified by sex, implant location (premolar/molar) and arch (maxilla/mandible). Final implant screw-retained zirconia crowns with angulated screw channels were delivered at 5 months after surgery. Radiographic bone levels (primary outcome), peri-implant mucosal margin levels and peri-implant probing depths were recorded at baseline, 6 and 12 months after surgery. Results Both treatment arms showed similar patterns of soft tissue and bone re-modelling from the implant platform over 12 months [mean bone level change 1.6 mm (SD 1.0 mm) in the delayed, and 1.2 mm (SD 1.3 mm) in the immediate temporization group], with the majority of changes occurring within the first 6 months. Conclusions Immediate or delayed temporization of single implants placed at posterior healed sites resulted in largely similar 1-year outcomes with respect to peri-implant bone levels and soft tissue changes.

Background Successful dissemination of the new classification of periodontitis is facilitated by emphasis on the basic ground rules, clarification of ambiguities, and identification of "gray zones" where thoughtful application of the guidelines by an informed, experienced clinician is paramount to arrive at a correct Stage and Grade. Methods Highlighted ground rules are (1) Stage is a patient-based, not a tooth-based concept, therefore, a single Stage is assigned per patient; (2) Stage can shift upward over time, if the periodontal status deteriorates, but the initially assigned Stage is retained even after improvement post-therapy; (3) the complexity factors that determine Stage must be evaluated collectively, not in isolation, to arrive at a clinically meaningful assessment; (4) a single Grade is assigned to a patient based on a deliberate evaluation of the "biological fabric" of the case, in terms of history of/risk for further progression, interplay of risk factors, and the two-way effects of periodontitis or its treatment on general health; (v) shift of Grade over time is possible towards either direction, after thorough, collective, evaluation of changes in the above parameters. Exemplified gray zones include a radiographically intact patient with minimal attachment loss in older age; presence of "frank" periodontitis affecting a single tooth; and assessment of factors that do/do not lead to increased complexity of therapy. Conclusion Differentiating between Stage I/II versus Stage III/IV periodontitis is relatively uncomplicated; further distinction between Stages and correct assignment of Grade requires nuanced, thorough interpretation of a broad array of findings by a knowledgeable clinician.

Complement plays a key role in immunosurveillance and homeostasis. When dysregulated or overactivated, complement can become a pathological effector, as seen in several inflammatory disorders, including periodontal disease. Recently, clinical correlative studies and preclinical mechanistic investigations have collectively demonstrated that complement is hyperactivated during periodontitis and that targeting its central component (C3) provides therapeutic benefit in nonhuman primates (NHPs). The preclinical efficacy of a C3-targeted drug candidate combined with excellent safety and pharmacokinetic profiles supported its use in a recent Phase IIa clinical study in which C3 inhibition resolved gingival inflammation in patients with periodontal disease. We posit that C3-targeted intervention might represent a novel and transformative host-modulation therapy meriting further investigation in Phase III clinical trials for the treatment of periodontitis.

Background A new periodontitis classification was recently introduced involving multidimensional staging and grading. The Study's aim was to assess if individuals well-trained in periodontics consistently used the new classification for patients with severe periodontitis. The secondary goal was to identify "gray zones" related to classifications. Methods Participants (raters) individually classified 10 pre-selected severe periodontitis cases using the 2017 World Workshop classification. An internet case-based study was conducted after inviting members from American Academy of Periodontology and European Federation of Periodontology. Gold-standard diagnoses were determined by five experts who developed the new periodontitis classification. Inter-reliability agreement among raters was assessed using Fleiss Kappa index with the jackknife method for linearly-weighted Kappa calculations. McNemar´s test was used to determine symmetry between raters and gold-standard panel. Results 103 raters participated and classified 9 clinical cases. Fleiss' Kappa values showed moderate inter-examiner consistency among raters for stage (K value: 0.49; 95%CI:0.19-0.79), grade (K value 0.50; 95%CI:0.30-0.70) and extent (K value: 0.51; 95%CI:0.23-0.77). When analyzed as composite (stage, grade, extent) a moderate inter-reliability was present among raters, k = 0.479 (K value: 0.47; 95%CI: 0.442 - 0.515). Agreement between raters and gold-standard panel was staging 76.6%; grading 82%; and extent 84.8%. In 6 of 9 cases 77-99% of raters consistently agreed with gold-standard panel, and other 3 cases had gray zone factors that reduced rater consistency. Conclusion Clinicians trained in the 2017 World Workshop periodontitis classification demonstrated moderate concordance in classifying 9 severe periodontitis cases, and in 6 of 9 cases raters consistently agreed with the gold-standard panel. This article is protected by copyright. All rights reserved.

A practical method to identify people who are most affected by periodontitis in their age group is currently unavailable. We focused on individuals with mean clinical attachment loss (CAL) above the 80th percentile within each of 10 age groups (5-y intervals between 30 and 74 y as well as ≥75 y). We developed predictive models using combined data from 2 cohorts (2009 to 2010 and 2011 to 2012) from the NHANES (National Health and Nutrition Examination Survey; development cohort [DC], n = 6,757), and we carried out external validation using data from a third NHANES cohort (2013 to 2014; validation cohort [VC], n = 3,447). We used 1) age-specific logistic regression models with stepwise selection to identify significant demographic variables, habits, medical conditions, and selected clinical periodontal parameters (proportion of teeth with probing depth ≥4 mm at incisors and molars and with visible [≥2 mm] recession) and to calculate propensity scores (PSs); 2) Youden’s J statistic to select optimum PS cutoffs to maximize diagnostic performance using receiver operating characteristic curves; and 3) bootstrap resampling with 1,000 replicates to validate the age-specific models and adjust the PS and optimal PS cutoffs for overfitting. The bootstrap-adjusted PSs were used as single predictors of mean CAL over the 80th percentile in the VC. The age-specific upper quintiles of mean CAL ranged between 1.63 and 3.24 mm in the DC and between 1.87 and 3.20 mm in the VC. The area under the curve of the models exceeded 0.85 in all age groups in the DC and 0.84 in the VC, indicating well-validated diagnostic performance. In the DC, sensitivity values ranged between 0.75 and 0.97 and exceeded 0.83 in 8 of 10 age groups. Corresponding values in the VC ranged between 0.56 and 0.89 and exceeded 0.68 in 8 of 10 age groups. We conclude that modeling that incorporates readily obtainable variables through a brief patient interview and an abbreviated periodontal examination accurately identifies individuals who are most affected by periodontitis in different ages.

Microbial communities along mucosal surfaces throughout the digestive tract are hypothesized as risk factors for impaired glucose regulation and the development of clinical cardiometabolic disease. We investigated whether baseline measures of subgingival microbiota predicted fasting plasma glucose (FPG) longitudinally. The Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS) enrolled 230 diabetes-free adults (77% female) aged 20 to 55 y (mean ± SD, 34 ± 10 y) from whom baseline subgingival plaque and longitudinal FPG were measured. DNA was extracted from subgingival plaque, and V3 to V4 regions of the 16S rRNA gene were sequenced. FPG was measured at baseline and again at 2 y; glucose change was defined as follow-up minus baseline. Multivariable linear models regressed 2-y glucose change onto baseline measures of community diversity and abundances of 369 individual taxa. A microbial dysbiosis index (MDI) summarizing top individual taxa associated with glucose change was calculated and used in regression models. Models were adjusted for age, sex, race/ethnicity, education, smoking status, body mass index, and baseline glucose levels. Statistical significance was based on the false discovery rate (FDR; -4, derived from the initial 369 hypothesis tests for specific taxa. Mean 2-y FPG change was 1.5 ± 8 mg/dL. Baseline levels of 9 taxa predicted FPG change (all FDR -4). Subgingival microbiota predict 2-y glucose change among diabetes-free men and women.

Periodontal medicine is a term used to describe how periodontal infection/inflammation may impact extraoral health. Periodontitis has been linked to over 50 systemic diseases and conditions. As part of the Journal of Dental Research’s Centennial Celebration, this narrative review discusses periodontal medicine research done over the past 100 y, with particular focus on the effects of periodontal disease on 3 pathological conditions: cardiovascular disease, diabetes mellitus, and adverse pregnancy outcomes. We selected 29 total studies that were the “first” of their kind, as they provided novel observations or contributed to shifting paradigms as well as important studies that made strong contributions to progress in understanding relationships to the systemic conditions. These studies were organized in an overview timeline and broken down into timelines by topic: cardiovascular disease ( n = 10), diabetes ( n = 12), and adverse pregnancy outcomes ( n = 7). Overall, the majority of cross-sectional, case-control, and longitudinal studies have revealed positive associations between poor periodontal status and cardiovascular disease, diabetes metabolic control, and a number of adverse pregnancy outcomes, and these associations are upheld in systematic reviews. Findings from randomized controlled trials testing the effects of periodontal therapy on systemic health outcomes were conflicting and inconsistent. While there has been a great deal of progress, we highlight lessons learned and make comments and suggestions on a number of key aspects, including the heterogeneity of case definitions of periodontal disease across studies, accounting for features of the periodontal phenotype that are most relevant to the biological link between periodontitis and systemic outcomes, the role of other comorbid inflammatory conditions, selection of study participants, and timing and intensity of the periodontal intervention.

Introduction: Periodontal disease, resulting from inflammatory host-response to dysbiotic subgingival microbiota, has been associated with incident hypertension, heart attack, stroke and diabetes. Limited data exist investigating the prospective relationship between periodontal disease and incident heart failure (HF) and HF subtypes. We hypothesize that periodontal disease is associated with increased risk for heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF). Methods: We studied 6,707 participants enrolled in the Atherosclerosis Risk in Communities Study who received a full-mouth clinical periodontal examination at visit 4 (1996-1998) and had longitudinal follow-up starting in 2005. Participants were classified as being periodontally healthy, having periodontal disease (based on the Periodontal Profile Classification (PPC)), or being edentulous. Hospitalization records were reviewed, and HF events were adjudicated and classified as HFpEF, HFrEF or HF of unknown ejection fraction (HFunknownEF) from 2005-2018. We used multivariable-adjusted Cox proportional hazards models to assess the association between periodontal disease or edentulism and incident HF. Results: Among participants 58% had periodontitis and 19% were edentulous. During a median follow-up time of 13 years, 1,178 cases of incident HF occurred (350 HFpEF, 319 HFrEF and 509 HFunknownEF). Periodontal disease and being edentulous were both associated with increased risk for both HFpEF and HFrEF (Table). Conclusion: Periodontal disease measured in mid-life was associated with both incident HFpEF and HFrEF. Adverse microbial exposures underlying periodontal disease might represent a modifiable risk factor for inflammation-induced heart failure pathophysiology.

Genome-wide transcriptomic analyses in whole tissues reflect the aggregate gene expression in heterogeneous cell populations comprising resident and migratory cells, and they are unable to identify cell type–specific information. We used a computational method (population-specific expression analysis [PSEA]) to decompose gene expression in gingival tissues into cell type–specific signatures for 8 cell types (epithelial cells, fibroblasts, endothelial cells, neutrophils, monocytes/macrophages, plasma cells, T cells, and B cells). We used a gene expression data set generated using microarrays from 120 persons (310 tissue samples; 241 periodontitis affected and 69 healthy). Decomposition of the whole-tissue transcriptomes identified differentially expressed genes in each of the cell types, which mapped to biologically relevant pathways, including dysregulation of Th17 cell differentiation, AGE-RAGE signaling, and epithelial-mesenchymal transition in epithelial cells. We validated selected PSEA-predicted, differentially expressed genes in purified gingival epithelial cells and B cells from an unrelated cohort ( n = 15 persons), each of whom contributed with 1 periodontitis-affected and 1 healthy gingival tissue sample. Differential expression of these genes by quantitative reverse transcription polymerase chain reaction corroborated the PSEA predictions and pointed to dysregulation of biologically important pathways in periodontitis. Collectively, our results demonstrate the robustness of the PSEA in the decomposition of gingival tissue transcriptomes and its ability to identify differentially regulated transcripts in particular cellular constituents. These genes may serve as candidates for further investigation with respect to their roles in the pathogenesis of periodontitis.

The premise for the oral-systemic diseases relationship dates to the early 20th century with the introduction of the focal infection theory that posited that oral disease affects overall health and wellbeing. While the biological plausibility for the link has been supported by experimental animal models and observational studies in humans, findings from interventional studies in which periodontal therapy failed to alleviate systemic health outcomes have often been interpreted as evidence against periodontitis contribution to the etiology of systemic health conditions. One concept of causation assumes a one-to-one correspondence between cause and effect. Nevertheless, common chronic diseases to which periodontitis is associated have multifactorial etiologies. This commentary provides an overview of Rothman's "sufficient cause" model as a framework for consideration of the oral-systemic diseases link.

BACKGROUND Peri-implantitis is a challenging condition to manage and is frequently treated using non-surgical debridement. The local delivery of antimicrobial agents has demonstrated benefit in mild to moderate cases of peri-implantitis. This study compared the safety and efficacy of chlorhexidine gluconate 2.5 mg chip (CHX chips) as an adjunctive treatment to subgingival debridement in patients afflicted with peri-implantitis. METHODS A multicenter, randomized, single-blind, two-arm, parallel Phase-3 study was conducted. Peri-implantitis patients with implant pocket depths (IPD) of 5-8 mm underwent subgingival implant surface debridement followed by repeated bi-weekly supragingival plaque removal and chlorhexidine chips application (ChxC group) for 12 weeks, or similar therapy but without application of ChxC (control group). All patients were followed for 24 weeks. Plaque and gingival indices were measured at every visit whereas IPD, recession, and bleeding on probing were assessed at 8, 12, 16, 24 week. RESULTS A total of 290 patients were included: 146 in the ChxC group and 144 in the control. At 24 weeks, a significant reduction in IPD (P = 0.01) was measured in the ChxC group (1.76 ± 1.13 mm) compared with the control group (1.54 ± 1.13 mm). IPD reduction of ≥2 mm was found in 59% and 47.2% of the implants in the ChxC and control groups, respectively (P = 0.03). Changes in gingival recession (0.29 ± 0.68 mm versus 0.15 ± 0.55 mm, P = 0.015) and relative attachment gain (1.47 ± 1.32 mm and 1.39 ± 1.27 mm, P = 0.0017) were significantly larger in the ChxC group. Patients in the ChxC group that were

Atherosclerosis is central to the pathology of cardiovascular diseases, a group of diseases in which arteries become occluded with atheromas that may rupture, leading to different cardiovascular events, such as myocardial infarction or ischemic stroke. There is a large body of epidemiologic and animal model evidence associating periodontitis with atherosclerotic disease, and many potential mechanisms linking these diseases have been elucidated. This chapter will update knowledge on these mechanisms, which generally fall into 2 categories: microbial invasion and infection of atheromas; and inflammatory and immunologic. With respect to the invasion and infection of atheromas, it is well established that organisms from the subgingival biofilm can enter the circulation and lodge in most distant tissues. Bacteremias resulting from oral interventions, and even oral hygiene activities, are well documented. More recently, indirect routes of entry of oral organisms (via phagocytes or dendritic cells) have been described for many oral organisms, into many tissues. Such organisms include the periodontal pathogens Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Prevotella intermedia, Tannerella forsythia, and Fusobacterium nucleatum. Intracellular survival of these organisms with dissemination to distant sites (The Trojan Horse approach) has been described. Their relative contribution to atheroma formation and progression has been studied mainly in experimental research, with results demonstrating that these organisms can invade endothelial cells and phagocytic cells within the atheroma, leading to pathogenic changes and progression of the atheroma lesion. The second category of mechanisms potentially linking periodontitis to atherosclerosis includes the dumping of inflammatory mediators originating from periodontal lesions into the systemic circulation. These inflammatory mediators, such as C-reactive protein, matrix metalloproteinases, fibrinogen, and other hemostatic factors, would further accelerate atheroma formation and progression, mainly through oxidative stress and inflammatory dysfunction. Moreover, direct effects on lipid oxidation have also been described. In summary, the evidence supports the concept that periodontitis enhances the levels of systemic mediators of inflammation that are risk factors for atherosclerotic diseases.

Background There is a sparsity of data describing the periodontal microbiome in elderly individuals. We analyzed the association of subgingival bacterial profiles and clinical periodontal status in a cohort of participants in the Washington Heights-Inwood Columbia Aging Project (WHICAP). Methods Dentate individuals underwent a full-mouth periodontal examination at six sites/tooth. Up to four subgingival plaque samples per person, each obtained from the mesio-lingual site of the most posterior tooth in each quadrant, were harvested and pooled. Periodontal status was classified according to the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) criteria as well as based on the percentage of teeth/person with pockets ≥4 mm deep. Bacterial DNA was isolated and was processed and analyzed using Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS). Differential abundance across the periodontal phenotypes was calculated using the R package DESeq2. α- and β-diversity metrics were calculated using DADA2-based clustering. Results The mean age of the 739 participants was 74.5 years, and 32% were male. Several taxa including Sneathia amnii-like sp., Peptoniphilaceae [G-1] bacterium HMT 113, Porphyromonas gingivalis, Fretibacterium fastidiosum, Filifactor alocis, and Saccharibacteria (TM7) [G-1] bacterium HMT 346 were more abundant with increasing severity of periodontitis. In contrast, species such as Veillonella parvula, Veillonella dispar, Rothia dentocariosa, and Lautropia mirabilis were more abundant in health. Microbial diversity increased in parallel with the severity and extent of periodontitis. Conclusions The observed subgingival bacterial patterns in these elderly individuals corroborated corresponding findings in younger cohorts and were consistent with the concept that periodontitis is associated with perturbations in the resident microbiome.

This editorial provides clarifications on the application of the Stage and Grade classification of periodontitis. In particular it describes: (1) how to apply the extent criterion to the defined Stage of the disease; and (2) how to calculate tooth loss because of periodontitis in Stage III and IV cases presenting with evidently hopeless (irrational to treat) teeth with a clinical definition of such teeth.

Introduction: Nitric oxide (NO) is important for cardiometabolic health. The enterosalivary nitrate-nitrite-NO pathway generates NO following oral microbiota-mediated production of salivary nitrite. We investigated the association between the abundance of genes in this pathway and cardiometabolic biomarkers. Hypothesis: Microbial genes favoring increased oral nitrite generation are associated with better cardiometabolic profile. Methods: We enrolled 784 diabetes-free adults in the Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS). Subgingival plaques were collected from 6-8 teeth/participant. 16S rRNA microbial genes (Illumina, MiSeq) were sequenced; PICRUSt2 estimated abundance of microbial genes in the nitrate-nitrite pathway associated with either nitrite generation or depletion. Gene abundance was summed within each group, and a ratio between nitrite generation to depletion (GDR) was calculated; higher levels suggest increased nitrite generating capacity. Systolic and diastolic blood pressure were measured and HbA1C, insulin, and glucose levels were determined in fasting blood. Z-scores were calculated for cardiometabolic biomarkers and averaged to form a cardiometabolic z-score (CMZ-score). Adjusted multivariable linear models were used to regress the CMZ-score and individual Z-scores on GDR. Results: Participants were 69% female and aged 19-58 years (mean=32±9). Mean CMZ-score was 0.00±0.7. Mean (range) GDR was 1.88 (0.22-7.84). Mean CMZ-scores (SE) across GDR quartiles were 0.17 (0.06), 0.01 (0.05), -0.04 (0.05), and -0.14 (0.05), p-value for trend=0.02. Linear regression coefficients summarizing associations between GDR and individual Z-scores (Table) show lower Z-score for systolic and diastolic blood pressure, HbA1C, and insulin levels in those with higher GDR. Conclusions: Increased capacity for nitrite production by oral bacteria, assessed through a metagenome estimation approach, is associated with lower levels of cardiometabolic risk.

This chapter presents fundamental concepts related to risk assessment and causal inference in the health sciences. It discusses the processes involved in the identification of risk and causative factors for diseases based on the counterfactual framework and contemporary sufficient component cause models. It provides definitions of commonly used terms, and exemplifies their use. It demonstrates why causal inference is made at the population rather than the individual level, and discusses its relevance to personalized medicine and future epidemiological research.

Background To explore the hypothesis that maternal periodontitis is associated with increased risk for Intrauterine Growth Restriction (IUGR), we examined the risk of IUGR in relation to periodontal treatment before, during and after pregnancy. Methods We conducted a retrospective cohort analysis of insurance claims data from 2009 to 2012 for women who delivered a singleton live birth (n = 32,168). IUGR was examined as a function of type and timing of dental treatment, adjusting for potential confounders in logistic regression. Sensitivity analysis evaluated the potential effects of unmeasured confounding. Results Women who received periodontal treatment after delivery, indicating the presence of untreated periodontal disease during pregnancy, had significantly higher odds of IUGR compared to women who received no periodontal treatment (adjusted OR 1.5, 95% CI 1.2, 1.8). Conclusions Periodontal treatment provided in the immediate postpartum period, a proxy for periodontitis during gestation, was associated with increased risk of IUGR. Electronic supplementary material The online version of this article (10.1186/s12903-018-0623-2) contains supplementary material, which is available to authorized users.

Background The enterosalivary nitrate‐nitrite‐nitric oxide pathway is an alternative pathway of nitric oxide generation, potentially linking the oral microbiome to insulin resistance and blood pressure (BP). We hypothesized that increased abundance of nitrate‐reducing oral bacteria would be associated with lower levels of cardiometabolic risk cross‐sectionally. Methods and Results ORIGINS (Oral Infections, Glucose Intolerance, and Insulin Resistance Study) enrolled 300 diabetes mellitus–free adults aged 20 to 55 years (mean=34±10 years) (78% women). Microbial DNA was extracted from subgingival dental plaque (n=281) and V3–V4 regions of the 16S rRNA gene were sequenced to measure the relative abundances of 20 a priori – selected taxa with nitrate‐reducing capacity. Standardized scores of each taxon's relative abundance were summed, producing a nitrate‐reducing taxa summary score ( NO 3 TSS ) for each participant. Natural log‐transformed homeostatic model assessment of insulin resistance, plasma glucose, systolic BP, and diastolic BP were regressed on NO 3 TSS in multivariable linear regressions; prediabetes mellitus and hypertension prevalence were regressed on NO 3 TSS using modified Poisson regression models. Nitrate‐reducing bacterial species represented 20±16% of all measured taxa. After multivariable adjustment, a 1‐ SD increase in NO 3 TSS , was associated with a −0.09 (95% CI , −0.15 to −0.03) and −1.03 mg/dL (95% CI , −1.903 to −0.16) lower natural log‐transformed homeostatic model assessment of insulin resistance and plasma glucose, respectively. NO 3 TSS was associated with systolic BP only among patients without hypertension; 1‐ SD increase in NO 3 TSS was associated with −1.53 (95% CI , −2.82 to −0.24) mm Hg lower mean systolic BP. No associations were observed with prediabetes mellitus and hypertension. Conclusions A higher relative abundance of oral nitrate‐reducing bacteria was associated with lower insulin resistance and plasma glucose in the full cohort and with mean systolic BP in participants with normotension.

A new periodontitis classification scheme has been adopted, in which forms of the disease previously recognized as "chronic" or "aggressive" are now grouped under a single category ("periodontitis") and are further characterized based on a multi-dimensional staging and grading system. Staging is largely dependent upon the severity of disease at presentation as well as on the complexity of disease management, while grading provides supplemental information about biological features of the disease including a history-based analysis of the rate of periodontitis progression; assessment of the risk for further progression; analysis of possible poor outcomes of treatment; and assessment of the risk that the disease or its treatment may negatively affect the general health of the patient. Necrotizing periodontal diseases, whose characteristic clinical phenotype includes typical features (papilla necrosis, bleeding, and pain) and are associated with host immune response impairments, remain a distinct periodontitis category. Endodontic-periodontal lesions, defined by a pathological communication between the pulpal and periodontal tissues at a given tooth, occur in either an acute or a chronic form, and are classified according to signs and symptoms that have direct impact on their prognosis and treatment. Periodontal abscesses are defined as acute lesions characterized by localized accumulation of pus within the gingival wall of the periodontal pocket/sulcus, rapid tissue destruction and are associated with risk for systemic dissemination.

Aim We investigated the cross-sectional relationship between periodontal status and arterial stiffness, assessed through a novel Pulse Wave Imaging methodology. Methods Eighty volunteers were enrolled (39% male, age range 24–78 years) and 33 pairs were formed of periodontitis patients/periodontally healthy controls, matched by age and gender. A full-mouth periodontal examination was performed and the degree of stiffness of the right and left carotid arteries was assessed by measuring pulse wave velocity (PWV) and the uniformity in pulse wave propagation (R2). Wilcoxon signed-rank tests for paired observations were used to compare periodontitis patients and healthy controls. Univariate and multivariate analyses were performed to analyze the association between PWV and R2 and potential explanatory variables. Results Patients with periodontitis had a statistically significantly lower uniformity in wave propagation (R2) than controls (p = .01), but PWV did not differ between the two groups. Univariate analysis showed a significant negative association between R2 and periodontitis, body mass index and smoking; periodontitis remained statistically associated with R2 in the multivariate analyses. Conclusions Patients with periodontitis and no established cardiovascular disease presented with lower degree of uniformity in the transmission of the pulse wave through the carotid arteries, suggesting an association between periodontitis and arterial stiffness/functional alterations.

Inflammation might link microbial exposures to insulin resistance. We investigated the cross-sectional association between periodontal microbiota, inflammation and insulin resistance.The Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS) enrolled 152 diabetes-free adults (77% female) aged 20-55 years (mean = 34 ± 10). Three hundred and four subgingival plaque samples were analysed using the Human Oral Microbe Identification Microarray to measure the relative abundances of 379 taxa. C-reactive protein, interleukin-6, tumour necrosis factor-α and adiponectin were assessed from venous blood and their z-scores were summed to create an inflammatory score (IS). Insulin resistance was defined via the HOMA-IR. Associations between the microbiota and both inflammation and HOMA-IR were explored using multivariable linear regressions; mediation analyses assessed the proportion of the association explained by inflammation.The IS was inversely associated with Actinobacteria and Proteobacteria and positively associated with Firmicutes and TM7 (p-values 0.05). Proteobacteria levels were associated with insulin resistance (p 0.05). Inflammation explained 30-98% of the observed associations between levels of Actinobacteria, Proteobacteria or Firmicutes and insulin resistance (p-values 0.05). Eighteen individual taxa were associated with inflammation (p 0.05) and 22 with insulin resistance (p 0.05). No findings for individual taxa met Bonferroni-adjusted statistical significance.Bacterial measures were related to inflammation and insulin resistance among diabetes-free adults.

Electronic dental records (EDR) provide access to a vast repository of clinical information which may be used for analyzing dental care delivery. The goal of this study was identification of determinants of implant survival and development of implant failure prediction model using large data set of intact and failed implant parameters extracted from EDR. A retrospective analysis of 19 variables reflecting patient, surgeon and dental treatment characteristics of 800 dental implants was performed using discriminant analysis to develop a predictive model identifying potential implant failure based on characteristics routinely available in a clinical care setting. The intact and failed implant characteristics were compared using the Goodman and Kruskal's lambda test, the point-biserial test, the chi-square test, and ANOVA test. A stepwise discriminant analysis reduced model dimensionality from 19 to 4 features. The final discriminant analysis model included the following variables: non-temporary implant, pre-op antibiotics, immunocompromised status, and gender. Overall, 72% of implant failure cases and 62% of intact implants were correctly identified by the resulting discriminant function. As the final predictive feature set is readily available in EDR, the resulting algorithm may be implemented as a clinical decision support module embedded into EDR to promote personalized approach in dental implant patients.

Objective Alterations in the microbiome, including the periodontal microbiome, may be a risk factor for rheumatoid arthritis (RA). Most studies that have analyzed this association are relatively small, focus primarily on a single periodontal pathogen (Porphyromonas gingivalis), and are not population based. This study was undertaken to investigate the association between elevated serum levels of IgG antibodies to 19 periodontal species and the prevalence of rheumatoid factor (RF) in a large nationally representative sample of adults. Methods The Third National Health and Nutrition Examination Survey (NHANES-III) is a cross-sectional sample of the noninstitutionalized US population (n = 33,994). Our study population included all dentate participants who were 60 years and older, did not have RA as defined by a modified version of the American College of Rheumatology 1987 criteria, and had complete data for both serum IgG antibodies against periodontal bacteria and serum RF antibody titer (n = 2,461). Results Adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) summarizing the relationship between the 19 periodontal serum IgG antibodies and RF seropositivity ranged from 0.53 (95% CI 0.29–0.97) to 1.27 (95% CI 0.79–2.06), and 17 of the 19 observed ORs were

Analytic approaches confined to fold-change comparisons of gene expression patterns between states of health and disease are unable to distinguish between primary causal disease drivers and secondary noncausal events. Genome-wide reverse engineering approaches can facilitate the identification of candidate genes that may distinguish between causal and associative interactions and may account for the emergence or maintenance of pathologic phenotypes. In this work, we used the algorithm for the reconstruction of accurate cellular networks (ARACNE) to analyze a large gene expression profile data set (313 gingival tissue samples from a cross-sectional study of 120 periodontitis patients) obtained from clinically healthy ( n = 70) or periodontitis-affected ( n = 243) gingival sites. The generated transcriptional regulatory network of the gingival interactome was subsequently interrogated with the master regulator inference algorithm (MARINA) and gene expression signature data from healthy and periodontitis-affected gingiva. Our analyses identified 41 consensus master regulator genes (MRs), the regulons of which comprised between 25 and 833 genes. Regulons of 7 MRs ( HCLS1, ZNF823, XBP1, ZNF750, RORA, TFAP2C, and ZNF57) included >500 genes each. Gene set enrichment analysis indicated differential expression of these regulons in gingival health versus disease with a type 1 error between 2% and 0.5% and with >80% of the regulon genes in the leading edge. Ingenuity pathway analysis showed significant enrichment of 36 regulons for several pathways, while 6 regulons (those of MRs HCLS1, IKZF3, ETS1, NHLH2, POU2F2, and VAV1) were enriched for >10 pathways. Pathways related to immune system signaling and development were the ones most frequently enriched across all regulons. The unbiased analysis of genome-wide regulatory networks can enhance our understanding of the pathobiology of human periodontitis and, after appropriate validation, ultimately identify target molecules of diagnostic, prognostic, or therapeutic value.

Aim We conducted a cross-sectional study of the prevalence, extent and severity of periodontitis in a tri-ethnic cohort of ≥65 year-old participants of the Washington-Heights Inwood Community Aging Project (WHICAP). Methods 1,130 individuals (57% of eligible invitees) participated in a full-mouth periodontal examination that included assessments of bleeding on probing, pocket depth and clinical attachment loss (CAL) at six sites/tooth. Results Participants had a mean age of 75.4 years (SD 6.7), were predominantly female (66.6%) and Hispanic (44.7%), and of middle/low educational attainment (~82%). The prevalence of edentulism was 14.7%, and an average of 17.1 teeth (SD 8.0) was present among the dentate. The prevalence of moderate/severe periodontitis according to the CDC/AAP definition was 77.5%. Pockets ≥6 mm were found in 50.2% of the sample, affecting an average of 5.7% of teeth/person. Corresponding figures for CAL≥5 mm were 71.4% and 23.6%, respectively. In multivariable models, male gender, being Black or Hispanic, and no dental visit within the prior year were associated with higher proportion of teeth with CAL ≥5 mm. Conclusions The prevalence, extent and severity of periodontitis were higher than the US national average in this urban elderly sample, suggesting substantial unmet periodontal treatment needs.

AIM To cross-sectionally analyse the submucosal microbiome of peri-implantitis (PI) lesions at different severity levels. MATERIALS AND METHODS Microbial signatures of 45 submucosal plaque samples from untreated PI lesions obtained from 30 non-smoking, systemically healthy subjects were assessed by 16s sequencing. Linear mixed models were used to identify taxa with differential abundance by probing depth, after correction for age, gender, and multiple samples per subject. Network analyses were performed to identify groups of taxa with mutual occurrence or exclusion. Subsequently, the effects of peri-implant probing depth on submucosal microbial dysbiosis were calculated using the microbial dysbiosis index. RESULTS In total, we identified 337 different taxa in the submucosal microbiome of PI. Total abundance of 12 taxa correlated significantly with increasing probing depth; a significant relationship with lower probing depth was found for 16 taxa. Network analysis identified two mutually exclusive complexes associated with shallow pockets and deeper pockets, respectively. Deeper peri-implant pockets were associated with significantly increased dysbiosis. CONCLUSION Increases in peri-implant pocket depth are associated with substantial changes in the submucosal microbiome and increasing levels of dysbiosis.

OBJECTIVE We used epidemiologic data of clinical periodontal status from two population-based samples in two countries, United States and Germany, to examine 1) the impact of age on the relative contribution of recession and pocketing on the distribution of clinical attachment loss, and 2) whether it is feasible to define age-dependent thresholds for severe periodontitis. METHODS The analytical sample was based on persons aged ≥30 and included 10,713 individuals in the United States, participants in NHANES 2009 to 2014, and 3,071 individuals in Pomerania, Germany, participants in the SHIP-Trend 2008 to 2012. NHANES used a full-mouth examination protocol to collect data on recession (R), pocket depth (PD) and clinical attachment loss (CAL) for six sites/tooth on a maximum of 28 teeth; SHIP-Trend used a half-mouth examination at four sites/tooth. In both samples, percentile distributions of mean CAL/person were generated for each 5-year age interval. Age-dependent thresholds defining the upper quintile of mean CAL were calculated for both samples. The topographic intraoral distribution of CAL and the relative contribution of R and PD on CAL was assessed. RESULTS Mean CAL increased linearly with age in both samples and was higher in SHIP-Trend than NHANES across the age spectrum. In contrast, mean PD was constant across age groups in both populations. R contributed increasingly to CAL with age, especially after 45 to 49 years. Upper quintile mean CAL thresholds in NHANES were