Pro-inflammatory profiles in cardiovascular disease patients with peri-implantitis.

BACKGROUND: To investigate the pro-inflammatory cytokine profiles in patients with or without cardiovascular disease (CVD) and with or without peri-implantitis. METHODS: Serum, peri-implant crevicular fluid (PICF), and gingival crevicular fluid (GCF) were collected from patients with (n = 82) or without CVD (n = 46) at the most severe peri-implantitis site including sites with periodontitis. A panel of proinflammatory molecules including high-sensitivity C-reactive protein (hsCRP), fibrinogen, interleukin-1 beta (IL-1ß), IL-6, plasma tumor necrosis factor-alpha (TNF-α), matrix metallo-proteinase-8 (MMP-8), osteoprotegerin (OPG), vascular endothelial growth factor (VEGF), IL-17, IL-8, tissue inhibitor of metalloproteinase-2 (TIMP-2), myeloperoxidase (MPO), and prostaglandin E2 (PGE2 ) were analyzed using human custom Quantibody arrays. Krunskal-Wallis test was used to compare groups. The diagnostic ability of each biomarker was assessed using chi-square test and ROC analysis. RESULTS: Serum IL-1ß, TNF-α and fibrinogen were significantly higher in CVD patients than those without. Serum fibrinogen displayed a trend of higher concentration in patients with radiographic bone loss (RBL) ≥2 mm (P = 0.08). PICF TNF-α exhibited a significantly higher detection level in the CVD patients that is coincided with the local peri-implant inflammation. In addition, PICF MMP-8 was significantly higher in the RBL ≥2 mm sites than the healthy implants; whereas IL-1ß, IL-8, MMP-8, and TIMP-2 proved to be the significant predictors for peri-implant disease. GCF TNF-α collected from patients with periodontitis was significantly associated with CVD cases. CONCLUSION: The augmented expression of local and systemic pro-inflammatory cytokines found in the current study supports the weak association between the chronic peri-implantitis with increasing severity and CVD.

Crevicular fluid biomarkers and periodontal disease progression.

AIM: Assess the ability of a panel of gingival crevicular fluid (GCF) biomarkers as predictors of periodontal disease progression (PDP). MATERIALS AND METHODS: In this study, 100 individuals participated in a 12-month longitudinal investigation and were categorized into four groups according to their periodontal status. GCF, clinical parameters and saliva were collected bi-monthly. Subgingival plaque and serum were collected bi-annually. For 6 months, no periodontal treatment was provided. At 6 months, patients received periodontal therapy and continued participation from 6 to 12 months. GCF samples were analysed by ELISA for MMP-8, MMP-9, Osteoprotegerin, C-reactive Protein and IL-1ß. Differences in median levels of GCF biomarkers were compared between stable and progressing participants using Wilcoxon Rank Sum test (p = 0.05). Clustering algorithm was used to evaluate the ability of oral biomarkers to classify patients as either stable or progressing. RESULTS: Eighty-three individuals completed the 6-month monitoring phase. With the exception of GCF C-reactive protein, all biomarkers were significantly higher in the PDP group compared to stable patients. Clustering analysis showed highest sensitivity levels when biofilm pathogens and GCF biomarkers were combined with clinical measures, 74% (95% CI = 61, 86). CONCLUSIONS: Signature of GCF fluid-derived biomarkers combined with pathogens and clinical measures provides a sensitive measure for discrimination of PDP (ClinicalTrials.gov NCT00277745).