Institute for Biodiagnostics, National Research Council of Canada, Winnipeg, MB, Canada.
J Periodontal Res. 2010 Jun;45(3):345-52. doi: 10.1111/j.1600-0765.2009.01243.x. Epub 2010 Mar 9.
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.
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.
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 PO2- 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.
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.
目前，牙周炎几乎完全是根据 50 多年来原位存在的明显临床症状来诊断的，而且没有明显改善。因此，本研究的总体目标是评估中红外光谱是否可用于识别组织和体液整体生化特征的疾病特异性分子改变。
共采集 190 份牙周炎（n=64）、牙龈炎（n=61）和正常部位（n=65）的龈沟液样本。获取和处理龈沟液样本的相应红外吸收光谱，并分析红外光谱中关键功能基团的相对贡献。使用多元统计分析-线性判别分析对这些龈沟液光谱的临床相关性进行定性评估。
使用红外光谱，我们能够在牙周炎或牙龈炎和健康对照受试者的龈沟液中识别出四个分子特征（代表酰胺 I、酰胺 II/酪氨酸环以及 DNA 中磷酸二酯基团的对称和不对称 PO2-伸缩振动的振动），这些特征清楚地区分了健康和患病的牙周组织。此外，通过对龈沟液光谱的多元分类，区分牙周健康和牙周炎部位的诊断准确性在训练集样本中为 98.4%，在验证集样本中为 93.1%。
我们已经确定，中红外光谱可用于识别龈沟液中的牙周炎特异性分子特征，并确认临床诊断。未来的纵向研究将评估中红外光谱是否代表一种潜在的预后工具，被认为是牙周病进展的关键。
