Periodontitis-specific molecular signatures in gingival crevicular fluid

Abstract

Background and Objective Periodontitis is currently diagnosed almost entirely on gross clinical manifestations that have been in situ for more than 50 years without significant improvement. The general objective of this study was, therefore, to evaluate whether mid-infrared spectroscopy can be used to identify disease-specific molecular alterations to the overall biochemical profile of tissues and body fluids. Material and Methods A total of 190 gingival crevicular fluid samples were obtained from periodontitis (n = 64), gingivitis (n = 61) and normal sites (n = 65). Corresponding infrared absorption spectra of gingival crevicular fluid samples were acquired and processed, and the relative contributions of key functional groups in the infrared spectra were analysed. The qualitative assessment of clinical relevance of these gingival crevicular fluid spectra was interpreted with the multivariate statistical analysis-linear discriminant analysis. Results Using infrared spectroscopy, we have been able to identify four molecular signatures (representing vibrations in amide I, amide II/tyrosine rings and symmetric and asymmetric stretching vibrations of phosphodiester groups in DNA) in the gingival crevicular fluid of subjects with periodontitis or gingivitis and healthy control subjects that clearly demarcate healthy and diseased periodontal tissues. Furthermore, the diagnostic accuracy for distinction between periodontally healthy and periodontitis sites revealed by multivariate classification of gingival crevicular fluid spectra was 98.4% for a training set of samples and 93.1% for a validation set. Conclusion We have established that mid-infrared spectroscopy can be used to identify periodontitis-specific molecular signatures in gingival crevicular fluid and to confirm clinical diagnoses. Future longitudinal studies will assess whether mid-infrared spectroscopy represents a potential prognostic tool, recognized as key to advancement of periodontics.

Diagnosis of Periodontal Disease from Saliva Samples Using Fourier Transform Infrared Microscopy Coupled with Partial Least Squares Discriminant Analysis

“…Xiang and co-workers differentiated periodontitis and gingivitis with high accuracy (93.1%) by analyzing the GCF using mid-infrared spectroscopy. 26 Their success might be explained by the fact that the GCF contains products directly related to periodontal disease, such as products and enzymes of the causative bacteria. Using our system, we were able to diagnose periodontal disease with high accuracy by analyzing saliva samples with FT-IR microscopy.…”

“…24,25 Importantly, Xiang et al used mid-infrared spectroscopy to analyze the gingival crevicular fluid (GCF) in order to determine differences between periodontitis, gingivitis, and normal sites. 26 Whole saliva consists of a mixture of fluids such as water, proteins, and electrolytes secreted by the salivary glands; non-salivary components derived from the GCF; oral bacteria, including their enzymes and bacterial products; viruses and fungi; blood and serum cells, desquamated epithelial cells; and food debris. 27,28 Therefore, it is thought that the saliva of patients with periodontal disease contains not only pathogenic bacteria and their products but also immunological proteins secreted during the biological response.…”

An Update on Novel Non‐Invasive Approaches for Periodontal Diagnosis

“…53 However, IR analysis of GCF, unlike traditional biochemical analyses, measures the total contents of GCF and may prove to be a more powerful diagnostic and prognostic tool for periodontal diseases as our data suggested. 57 In the recent study, 57 we used IR spectroscopy to characterize GCF from healthy, gingivitis, and periodontitis sites and determined specific spectral signatures that clearly demarcated healthy and diseased tissues.We were able to show that, even in unprocessed spectral data (Fig. 4), subtle differences in spectral band intensity and positions arising from the three major components, i.e., lipid, protein and DNA, were observed in GCF from healthy, gingivitis, and periodontitis groups.…”

Diagnosis and Monitoring of Gingivitis in vivo Using Non-Invasive Technology - Infrared Spectroscopy

“…), and the environment of the bond. In the last fifteen years, IR spectroscopists have taken advantage of this molecular information, in combination with pattern recognition/classification methods, to explore its potential as a powerful tool for the diagnoses of various diseases based upon the spectra of biological fluids, including amniotic fluid, lipid profiles, synovial fluid, saliva and gingival crevicular fluid to predict fetal lung maturity (Liu et al, 1998), diagnose heart disease (Liu et al, 2002) and rheumatoid arthritis (Eysel et al, 1997), assess global diabetes-associated alterations and evaluate periodontal inflammations (Xiang et al, 2010), respectively. The IR spectrum of saliva and GCF is a rich source of information regarding the oral cavity and associated inflammation.…”

“…More relevant to gingivitis, our group recently has employed IR spectroscopy to characterize GCF from healthy, gingivitis and periodontitis sites and determined specific spectral signatures that clearly demarcate healthy and diseased tissues (Xiang et al, 2010). With the FSD method which can narrow effective bandwidths, enhance resolution, and increase available discriminatory data (Surewicz et al, 1988), we were able to reveal subtle differences in spectral band intensity and positions arising from the three major www.intechopen.com Diagnosis and Monitoring of Gingivitis in vivo Using Non-Invasive Technology -Infrared Spectroscopy 131 components, i.e., lipid, protein and DNA observed in GCF from healthy, gingivitis and periodontitis groups.…”