Re: A critical assessment of interleukin-1 (IL-1) genotyping when used in a genetic susceptibility test for severe chronic periodontitis. Greenstein G, Hart TC (2002;73:231-247)

A novel predictive approach for GVHD after allogeneic SCT based on clinical variables and cytokine gene polymorphisms

Despite considerable advances in our understanding of the pathophysiology of graft-versus-host disease (GVHD), its prediction remains unresolved and depends mainly on clinical data. The aim of this study is to build a predictive model based on clinical variables and cytokine gene polymorphism for predicting acute GVHD (aGVHD) and chronic GVHD (cGVHD) from the analysis of a large cohort of HLA-identical sibling donor allogeneic stem cell transplant (allo-SCT) patients. A total of 25 SNPs in 12 cytokine genes were evaluated in 509 patients. Data were analyzed using a linear regression model and the least absolute shrinkage and selection operator (LASSO). The statistical model was constructed by randomly selecting 85% of cases (training set), and the predictive ability was confirmed based on the remaining 15% of cases (test set). Models including clinical and genetic variables (CG-M) predicted severe aGVHD significantly better than models including only clinical variables (C-M) or only genetic variables (G-M). For grades 3-4 aGVHD, the correct classification rates (CCR1) were: 100% for CG-M, 88% for G-M, and 50% for C-M. On the other hand, CG-M and G-M predicted extensive cGVHD better than C-M (CCR1: 80% vs. 66.7%, respectively). A risk score was calculated based on LASSO multivariate analyses. It was able to correctly stratify patients who developed grades 3-4 aGVHD (P < .001) and extensive cGVHD (P < .001). The novel predictive models proposed here improve the prediction of severe GVHD after allo-SCT. This approach could facilitate personalized risk-adapted clinical management of patients undergoing allo-SCT.

Identification of pathogen and host-response markers correlated with periodontal disease

BACKGROUND

Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm.

METHODS

One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers.

RESULTS

Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5).

CONCLUSIONS

Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.

Periodontal disease at the biofilm-gingival interface

BACKGROUND

A molecular epidemiologic study provided the opportunity to characterize the biology of the biofilm-gingival interface (BGI) in 6,768 community-dwelling subjects.

METHODS

Disease classifications and multivariable models were developed using clinical, microbial, inflammatory, and host-response data. The purpose was to identify new clinical categories that represented distinct biologic phenotypes based upon DNA checkerboard analyses of eight plaque bacteria, serum immunoglobulin G (IgG) titers to 17 bacteria, and the gingival crevicular fluid (GCF) levels of 16 inflammatory mediators. Five BGI clinical conditions were defined using probing depths (PDs) and bleeding on probing (BOP) scores. Subjects with all PDs < or = 3 mm were grouped as BGI-healthy (14.3% of sample) or BGI-gingivitis (BGI-G, 15.1%). Subjects with one or more PDs > or = 4 mm [deep lesion (DL)] were divided into low BOP (18.0%), moderate BOP (BGI-DL/MB, 39.7%), and severe BOP (BGI-DL/SB, 12.9%).

RESULTS

Subjects with BGI-G had increased levels of Campylobacter rectus-specific serum IgG levels (P = 0.01), and those with BGI-DL/SB had increased IgG levels to Porphyromonas gingivalis (P < 0.0003) and C. rectus (P < 0.01). BGI-DL/SB subjects had an excessive GCF interleukin (IL)-1beta and prostaglandin E2 response and an enhanced chronic inflammatory response with significant increases in GCF IL-6 and monocyte chemotactic peptide-1. Within BGI-DL/SB subjects, more severe pocketing and BOP were associated with higher levels of GCF IL-1beta, not higher microbial counts or plaque scores.

CONCLUSIONS

New BGI classifications create categories with distinct biologic phenotypes. The increased titers of C. rectus IgG among 68.5% of the BGI-G subjects and elevated P. gingivalis titers among BGI-DL/MB and BGI-DL/SB subjects (63.8% and 75.7%, respectively) are strongly supportive of the microbial specificity of pathogenesis for BGI categories.

Oral health, atherosclerosis, and cardiovascular disease

During the last two decades, there has been an increasing interest in the impact of oral health on atherosclerosis and subsequent cardiovascular disease (CVD). The advent of the inflammation paradigm in coronary pathogenesis stimulated research in chronic infections caused by a variety of micro-organisms-such as Chlamydia pneumoniae, Helicobacter pylori, and cytomegalovirus-as well as dental pathogens, since these chronic infections are thought to be involved in the etiopathogenesis of CVD by releasing cytokines and other pro-inflammatory mediators (e.g., C-reactive protein [CRP], tumor necrosis factor [TNF-alpha]) that may initiate a cascade of biochemical reactions and cause endothelial damage and facilitate cholesterol plaque attachment. Yet, due to the multi-factorial nature of dental infection and CVD, confirming a causal association is difficult, and the published results are conflicting. The main deficit in the majority of these studies has been the inadequate control of numerous confounding factors, leading to an overestimation and the imprecise measurement of the predictor or overadjustment of the confounding variables, resulting in underestimation of the risks. A meta-analysis of prospective and retrospective follow-up studies has shown that periodontal disease may increase the risk of CVD by approximately 20% (95% confidence interval [CI], 1.08-1.32). Similarly, the reported risk ratio between periodontal disease and stroke is even stronger, varying from 2.85 (CI 1.78-4.56) to 1.74 (CI 1.08-2.81). The association between peripheral vascular disease and oral health parameters has been explored in only two studies, and the resultant relative risks among individuals with periodontitis were 1.41 (CI 1.12-1.77) and 2.27 (CI 1.32-3.90), respectively. Overall, it appears that periodontal disease may indeed contribute to the pathogenesis of cardiovascular disease, although the statistical effect size is small.