Periodontitis and peri-implantitis biomarkers in human oral fluids and the null-allele mouse model

Tissue destruction associated with the periodontal disease progression is caused by a cascade of host and microbial factors and proteolytic enzymes. Aberrant laminin-332 (Ln-332), human beta defensin (hBD), and matrix metalloproteinase (MMP) functions have been found in oral inflammatory diseases. The null-allele mouse model appears as the next step in oral disease research. The MMP-8 knock-out mouse model allowed us to clarify the involvement of MMP-8 in vivo in oral and related inflammatory diseases where MMP-8 is suggested to play a key role in tissue destruction. The cleaved Ln-332 γ2-chain species has been implicated in the apical migration of sulcular epithelial cells during the formation of periodontal pockets. We demonstrated that increased Ln-332 fragment levels in gingival crevicular fluid (GCF) are strongly associated with the severity of inflammation in periodontitis. Porphyromonas gingivalis trypsin-like proteinase can cleave an intact Ln-332 γ2-chain into smaller fragments and eventually promote the formation of periodontal pockets. hBDs are components of an innate mucosal defense against pathogenic microbes. Our results suggest that P. gingivalis trypsin-like proteinase can degrade hBD and thus reduce the innate immune response. Elevated levels and the increased activity of MMPs have been detected in several pathological tissue-destructive conditions where MMPs are shown to cleave extracellular matrix (ECM) and basement membrane (BM) molecules and to facilitate tissue destruction. Elevated levels of MMP-8 have been reported in many inflammatory diseases. In periodontitis, MMP-8 levels in gingival crevicular fluid (GCF) and in peri-implant sulcular fluid (PISF) are elevated at sites of active inflammation, and the increased levels of MMP-8 are mainly responsible for collagenase activity, which leads to tissue destruction. MMP-25, expressed by neutrophils, is involved in inflammatory diseases and in ECM turnover. MMP-26 can degrade ECM components and serve as an activator of other MMP enzymes. We further confirmed that increased levels and activation of MMP-8, -25, and -26 in GCF, PISF, and inflamed gingival tissue are associated with the severity of periodontal/peri-implant inflammation. We evaluated the role of MMP-8 in P. gingivalis-induced periodontitis by comparing MMP-8 knock-out (MMP8-/-) and wild-type mice. Surprisingly, MMP-8 significantly attenuated P. gingivalis-induced site-specific alveolar bone loss. We also evaluated systemic changes in serum immunoglobulin and lipoprotein profiles among these mouse groups. P. gingivalis infection increased HDL/VLDL particle size in the MMP-8-/- mice, which is an indicator of lipoprotein responses during systemic inflammation. Serum total LPS and IgG antibody levels were enhanced in both mice groups. P. gingivalis-induced periodontitis, especially in MMP-8-/- mice, is associated with severe alveolar bone loss and with systemic inflammatory and lipoprotein changes that are likely to be involved in early atherosclerosis.

Early detection of type 2 diabetes mellitus in Chinese and Indian adult population

Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

Bootstrapping the Error Correction Model Cointegration Test

This paper is concerned with using the bootstrap to obtain improved critical values for the error correction model (ECM) cointegration test in dynamic models. In the paper we investigate the effects of dynamic specification on the size and power of the ECM cointegration test with bootstrap critical values. The results from a Monte Carlo study show that the size of the bootstrap ECM cointegration test is close to the nominal significance level. We find that overspecification of the lag length results in a loss of power. Underspecification of the lag length results in size distortion. The performance of the bootstrap ECM cointegration test deteriorates if the correct lag length is not used in the ECM. The bootstrap ECM cointegration test is therefore not robust to model misspecification.