Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium.

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and "precision," data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface-level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that results from GLIDE2 will decisively advance the knowledge base of mechanisms at play in oral, dental, and craniofacial health and disease and further catalyze international collaboration and data and resource sharing in genomics research.

Cell Type-Specific Decomposition of Gingival Tissue Transcriptomes.

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.

Age-Specific Predictive Models of the Upper Quintile of Periodontal Attachment Loss.

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.

Subgingival Microbiota and Longitudinal Glucose Change: The Oral Infections, Glucose Intolerance and Insulin Resistance Study (ORIGINS).

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; <0.05) or a Bonferroni-corrected P value of 1 × 10-4, 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 <0.05), among which Stomatobaculum sp oral taxon 097 and Atopobium spp predicted greater FPG change, while Leptotrichia sp oral taxon 498 predicted lesser FPG change (all 3 P values, Bonferroni significant). The MDI explained 6% of variation in longitudinal glucose change (P < 0.001), and baseline glucose levels explained 10% of variation (P < 0.0001). FPG change values ± SE in the third versus first tertile of the MDI were 4.5 ± 0.9 versus 1.6 ± 0.9 (P < 1 × 10-4). Subgingival microbiota predict 2-y glucose change among diabetes-free men and women.

Periodontal Medicine: 100 Years of Progress.

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.

Identification of Master Regulator Genes in Human Periodontitis.

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.

Periodontal Bacteria and Prediabetes Prevalence in ORIGINS: The Oral Infections, Glucose Intolerance, and Insulin Resistance Study.

Periodontitis and type 2 diabetes mellitus are known to be associated. The relationship between periodontal microbiota and early diabetes risk has not been studied. We investigated the association between periodontal bacteria and prediabetes prevalence among diabetes-free adults. ORIGINS (the Oral Infections, Glucose Intolerance and Insulin Resistance Study) cross sectionally enrolled 300 diabetes-free adults aged 20 to 55 y (mean ± SD, 34 ± 10 y; 77% female). Prediabetes was defined as follows: 1) hemoglobin A1c values ranging from 5.7% to 6.4% or 2) fasting plasma glucose ranging from 100 to 125 mg/dL. In 1,188 subgingival plaque samples, 11 bacterial species were assessed at baseline, including Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, and Actinomyces naeslundii. Full-mouth clinical periodontal examinations were performed, and participants were defined as having no/mild periodontitis vs. moderate/severe periodontitis per the definition of the Centers for Disease Control and Prevention / American Academy of Periodontology. Modified Poisson regression evaluated prediabetes prevalence across bacterial tertiles. Prevalence ratios and 95% confidence intervals for third vs. first tertiles are presented. All analyses were adjusted for cardiometabolic risk factors. All results presented currently arise from the baseline cross section. Prediabetes prevalence was 18%, and 58% of participants had moderate/severe periodontitis. Prevalence ratios (95% confidence intervals) summarizing associations between bacterial levels and prediabetes were as follows: A. actinomycetemcomitans, 2.48 (1.34, 4.58), P = 0.004; P. gingivalis, 3.41 (1.78, 6.58), P = 0.0003; T. denticola, 1.99 (0.992, 4.00), P = 0.052; T. forsythia, 1.95 (1.0, 3.84), P = 0.05; A. naeslundii, 0.46 (0.25, 0.85), P = 0.01. The prevalence ratio for prediabetes among participants with moderate/severe vs. no/mild periodontitis was 1.47 (0.78, 2.74), P = 0.23. Higher colonization levels of specific periodontal microbiota are associated with higher prediabetes prevalence among diabetes-free adults.

Gingival tissue transcriptomes identify distinct periodontitis phenotypes.

The currently recognized principal forms of periodontitis-chronic and aggressive-lack an unequivocal, pathobiology-based foundation. We explored whether gingival tissue transcriptomes can serve as the basis for an alternative classification of periodontitis. We used cross-sectional whole-genome gene expression data from 241 gingival tissue biopsies obtained from sites with periodontal pathology in 120 systemically healthy nonsmokers with periodontitis, with available data on clinical periodontal status, subgingival microbial profiles, and serum IgG antibodies to periodontal microbiota. Adjusted model-based clustering of transcriptomic data using finite mixtures generated two distinct clusters of patients that did not align with the current classification of chronic and aggressive periodontitis. Differential expression profiles primarily related to cell proliferation in cluster 1 and to lymphocyte activation and unfolded protein responses in cluster 2. Patients in the two clusters did not differ with respect to age but presented with distinct phenotypes (statistically significantly different whole-mouth clinical measures of extent/severity, subgingival microbial burden by several species, and selected serum antibody responses). Patients in cluster 2 showed more extensive/severe disease and were more often male. The findings suggest that distinct gene expression signatures in pathologic gingival tissues translate into phenotypic differences and can provide a basis for a novel classification.

Molecular differences between chronic and aggressive periodontitis.

The 2 major forms of periodontitis, chronic (CP) and aggressive (AgP), do not display sufficiently distinct histopathological characteristics or microbiological/immunological features. We used molecular profiling to explore biological differences between CP and AgP and subsequently carried out supervised classification using machine-learning algorithms including an internal validation. We used whole-genome gene expression profiles from 310 'healthy' or 'diseased' gingival tissue biopsies from 120 systemically healthy non-smokers, 65 with CP and 55 with AgP, each contributing with ≥ 2 'diseased' gingival papillae (n = 241; with bleeding-on-probing, probing depth ≥ 4 mm, and clinical attachment loss ≥ 3 mm), and, when available, a 'healthy' papilla (n = 69; no bleeding-on-probing, probing depth ≤ 4 mm, and clinical attachment loss ≤ 4 mm). Our analyses revealed limited differences between the gingival tissue transcriptional profiles of AgP and CP, with genes related to immune responses, apoptosis, and signal transduction overexpressed in AgP, and genes related to epithelial integrity and metabolism overexpressed in CP. Different classifying algorithms discriminated CP from AgP with an area under the curve ranging from 0.63 to 0.99. The small differences in gene expression and the highly variable classifier performance suggest limited dissimilarities between established AgP and CP lesions. Future analyses may facilitate the development of a novel, 'intrinsic' classification of periodontitis based on molecular profiling.

MicroRNAs and their target genes in gingival tissues.

To gain insights into the in vivo function of miRNAs in the context of periodontitis, we examined the occurrence of miRNAs in healthy and diseased gingival tissues and validated their in silico-predicted targets through mRNA profiling using whole-genome microarrays in the same specimens. Eighty-six individuals with periodontitis contributed 198 gingival papillae: 158 'diseased' (bleeding-on-probing, PD > 4 mm, and AL ≥ 3 mm) and 40 'healthy' (no bleeding, PD ≤ 4 mm, and AL ≤ 2 mm). Expression of 1,205 miRNAs was assessed by microarrays, followed by selected confirmation by quantitative RT-PCR. Predicted miRNA targets were identified and tested for enrichment by Gene Set Enrichment Analysis (GSEA). Enriched gene sets were grouped in functional categories by DAVID and Ingenuity Pathway Analysis. One hundred fifty-nine miRNAs were significantly differentially expressed between healthy and diseased gingiva. Four miRNAs (hsa-miR-451, hsa-miR-223, hsa-miR-486-5p, hsa-miR-3917) were significantly overexpressed, and 7 (hsa-miR-1246, hsa-miR-1260, hsa-miR-141, hsa-miR-1260b, hsa-miR-203, hsa-miR-210, hsa-miR-205*) were underexpressed by > 2-fold in diseased vs. healthy gingiva. GSEA and additional filtering identified 60 enriched miRNA gene sets with target genes involved in immune/inflammatory responses and tissue homeostasis. This is the first study that concurrently examined miRNA and mRNA expression in gingival tissues and will inform mechanistic experimentation to dissect the role of miRNAs in periodontal tissue homeostasis and pathology.

"Gum bug, leave my heart alone!"--epidemiologic and mechanistic evidence linking periodontal infections and atherosclerosis.

Evidence from epidemiologic studies suggests that periodontal infections are independently associated with subclinical and clinical atherosclerotic vascular disease. Although the strength of the reported associations is modest, the consistency of the data across diverse populations and a variety of exposure and outcome variables suggests that the findings are not spurious or attributable only to the effects of confounders. Analysis of limited data from interventional studies suggests that periodontal treatment generally results in favorable effects on subclinical markers of atherosclerosis, although such analysis also indicates considerable heterogeneity in responses. Experimental mechanistic in vitro and in vivo studies have established the plausibility of a link between periodontal infections and atherogenesis, and have identified biological pathways by which these effects may be mediated. However, the utilized models are mostly mono-infections of host cells by a limited number of 'model' periodontal pathogens, and therefore may not adequately portray human periodontitis as a polymicrobial, biofilm-mediated disease. Future research must identify in vivo pathways in humans that may (i) lead to periodontitis-induced atherogenesis, or (ii) result in treatment-induced reduction of atherosclerosis risk. Data from these studies will be essential for determining whether periodontal interventions have a role in the primary or secondary prevention of atherosclerosis.

Enhanced monocyte migration and pro-inflammatory cytokine production by Porphyromonas gingivalis infection.

BACKGROUND AND OBJECTIVE: Porphyromonas gingivalis, a major periodontal pathogen, has been reported to be involved in atherogenesis. In order to further understand this pathogen's link with systemic inflammation and vascular disease, we investigated its influence on murine monocytes and macrophages from three different sources. MATERIAL AND METHODS: Concanavalin A-elicited peritoneal macrophages, peripheral blood monocyte-derived macrophages and WEHI 274.1 monocytes were infected with either P. gingivalis 381 or its non-invasive fimbriae-deficient mutant, DPG3. RESULTS: Infection with P. gingivalis 381 markedly induced monocyte migration and significantly enhanced production of the pro-inflammatory cytokines, tumor necrosis factor-alpha and interleukin-6. Consistent with a role for this pathogen's major fimbriae and/or its invasive capacity, infection with DPG3 had a minimal effect on both monocyte attraction and pro-inflammatory cytokine production. CONCLUSION: Since monocyte recruitment and activation are important steps in the development of vascular inflammation and atherosclerosis, these results suggest that P. gingivalis infection may be involved in these processes.

Periodontitis is associated with cognitive impairment among older adults: analysis of NHANES-III.

BACKGROUND: Periodontitis is ubiquitous and associated with serological evidence of exposure to periodontal organisms, systemic inflammation and vascular disease. Dementia is a major public health problem likely related to a complex interaction between genetics and diseases associated with systemic inflammation, including diabetes, smoking and stroke. METHODS: To assess relationships between systemic exposure to periodontal pathogens and cognitive test outcomes, data were analysed from the Third National Health and Nutrition Examination Survey (NHANES-III), a nationally representative cross sectional observational study among older adults. We included 2355 participants >or=60 years who completed measures of cognition and Poryphyromonas gingivalis IgG. Using SUDAAN, logistic regression models examined the association of P gingivalis IgG with cognitive test performance. RESULTS: Poor immediate verbal memory (<5/9 points) was prevalent in 5.7% of patients, and 6.5% overall had impaired delayed recall (<4/9); 22.1% had difficulty with serial subtractions (<5/5 trials correct). Individuals with the highest P gingivalis IgG (>119 ELISA Units (EU)) were more likely to have poor delayed verbal recall (OR 2.89, 95% CI 1.14 to 7.29) and impaired subtraction (OR 1.95, 95% CI 1.22 to 3.11) than those with the lowest (

Granulocyte chemotactic protein 2 (gcp-2/cxcl6) complements interleukin-8 in periodontal disease.

BACKGROUND AND OBJECTIVE: Mucosal inflammatory responses are orchestrated largely by pro-inflammatory chemokines. The chemokine granulocyte chemotactic protein 2 (CXCL6) is involved in neutrophil recruitment and migration. Previous studies have shown that granulocyte chemotactic protein 2 is up-regulated during mucosal inflammation (e.g. in inflammatory bowel disease), similarly to the functionally and structurally related chemokine interleukin-8. Nevertheless, unlike interleukin-8, a role of granulocyte chemotactic protein 2 in gingival inflammation has not been yet demonstrated. In this study we aimed to evaluate the expression of the chemokine granulocyte chemotactic protein 2 in clinically healthy vs. diseased gingival tissues and to explore possible correlations with clinical and microbiological markers of periodontitis. MATERIAL AND METHODS: Gene expression in 184 'diseased' and 63 'healthy' gingival tissue specimens from 90 patients with periodontitis was analyzed using Affymetrix U133Plus2.0 arrays. The expression of granulocyte chemotactic protein 2 was further confirmed by real-time reverse transcription-polymerase chain reaction, western blotting and enzyme-linked immunosorbent assay, while the localization of granulocyte chemotactic protein 2 in gingival tissues was analyzed by immunohistochemistry. Plaque samples from the adjacent periodontal pockets were collected and evaluated for 11 species of periodontal bacteria using checkerboard DNA-DNA hybridizations. RESULTS: Among all known chemokines, GCP-2 expression was the most up-regulated (3.8-fold, p < 1.1 x 10(-16)), in 'diseased' vs. 'healthy' tissue as compared to a 2.6-fold increased expression of interleukin-8 mRNA (p < 1.2 x 10(-15)). Increased expression of granulocyte chemotactic protein 2 correlated with higher levels of 'red' and 'orange' complex pathogens and with increased probing depth, but not with attachment loss. Immunohistochemistry showed that granulocyte chemotactic protein 2 was expressed in gingival vascular endothelium. CONCLUSION: The level of expression of granulocyte chemotactic protein 2 correlates with the severity of periodontitis and appears to act as a hitherto unrecognized functional adjunct to interleukin-8 in diseased gingival tissues.

Effects of periodontal therapy on serum C-reactive protein, sE-selectin, and tumor necrosis factor-alpha secretion by peripheral blood-derived macrophages in diabetes. A pilot study.

BACKGROUND AND OBJECTIVE: Diabetes is associated with an increased risk for vascular disease and periodontitis. The aim of this study was to assess the effects of periodontal treatment in diabetes with respect to alterations in the pro-inflammatory potential of peripheral blood mononuclear cells. MATERIAL AND METHODS: Ten patients with diabetes and moderate to severe periodontitis received full-mouth subgingival debridement. Blood samples for serum/plasma and mononuclear cell isolation were collected prior to and 4 wk after therapy. Mononuclear cells were analyzed by flow cytometry and stimulated with lipopolysaccharide or ionomycin/phorbol ester to determine the pro-inflammatory capacity of macrophages and lymphocytes, respectively. RESULTS: Following periodontal treatment, all patients demonstrated a significant improvement in clinical periodontal status (p < 0.05), despite only modest reduction in subgingival bacterial load or homologous serum immunoglobulin G titers. CD14(+) blood monocytes decreased by 47% (p < 0.05), and the percentage of macrophages spontaneously releasing tumor necrosis factor-alpha decreased by 78% (p < 0.05). There were no significant changes in the capacity of lymphocytes to secrete interferon-gamma. Among a number of serum inflammatory markers tested, high-sensitivity-C-reactive protein significantly decreased by 37% (p < 0.01) and soluble E-selectin decreased by 16.6% (p < 0.05). CONCLUSION: These data suggest a reduced tendency for monocyte/macrophage-driven inflammation with periodontal therapy and a potential impact on atherosclerosis-related complications in diabetic individuals.

Fcgamma receptor polymorphisms and periodontal status: a prospective follow-up study.

AIMS: The aims of this study were to assess: (i) the distribution of Fcgamma receptor polymorphisms among patients with chronic periodontitis ("cases") and control subjects with no/minimal loss of periodontal tissue support in a Caucasian population; (ii) whether these polymorphisms can serve as severity markers for periodontitis; and (iii) whether they have any bearing on the response to periodontal therapy. METHODS: The study sample consisted of 132 cases and 73 controls of comparable age and gender. Full-mouth periodontal status was assessed. Subgingival plaque (PL) samples and blood samples were obtained and analysed with respect to 19 bacterial species and homologous serum immunoglobulin G titres. Polymorphisms in the Fcgamma receptor IIa (131R/H) and IIIb (NA1/NA2) were assessed by polymerase chain reaction. Patients underwent periodontal therapy and were followed up at 4 and 30 months. RESULTS: Neither polymorphism showed a skewed distribution among cases and controls. At baseline, periodontitis patients with Fcgamma RIIa-H/H131 genotype had more PL and deeper pockets than patients in other genotype groups (p < 0.05). Both bacterial levels and antibody titres were unrelated to genotype. The longitudinal analysis failed to detect an association between genotype and response to periodontal therapy. CONCLUSIONS: The present data failed to demonstrate a clinically relevant relationship between the Fcgamma receptor IIa (131R/H) or IIIb (NA1/NA2) polymorphism and periodontal status.

Infection with a periodontal pathogen induces procoagulant effects in human aortic endothelial cells.

BACKGROUND: Multiple studies have demonstrated a link between periodontal infections and vascular disease. Porphyromonas gingivalis, a major periodontal pathogen, has been shown to adhere to and invade endothelial cells. OBJECTIVE: In order to dissect mechanisms underlying these observations, we assessed the role of P. gingivalis infection in modulating properties of endothelial cells linked to atherothrombosis. METHODS: Primary human aortic endothelial cells (HAEC) were infected with either P. gingivalis 381 or its non-invasive fimbriae-deficient mutant, DPG3. Markers of coagulation and thrombosis were assessed 8 h and 18 h postinfection in cell lysates and supernatants. RESULTS: Infection with P. gingivalis 381 significantly enhanced tissue factor expression and activity, and suppressed levels of tissue factor pathway inhibitor. Furthermore, P. gingivalis infection decreased levels and activity of tissue plasminogen activator, and enhanced plasminogen activator inhibitor-1 antigen and activity. Consistent with an important role for bacterial adhesion/invasion in this setting, infection with DPG3 failed to induce procoagulant properties in HAEC. Most of the above effects of P. gingivalis 381 were more apparent at the later time point (18 h postinfection). This suggests that P. gingivalis infection, rather than having an immediate and direct effect, might activate pathways that, in turn, trigger endothelial procoagulant mechanisms. CONCLUSIONS: Taken together these data demonstrate for the first time that infection with a periodontal pathogen induces procoagulant responses in HAEC.