Seredin Pavel, Litvinova Tatiana, Ippolitov Yuri, Goloshchapov Dmitry, Peshkov Yaroslav, Chae Boknam, Freitas Raul O, Maia Francisco C B
Department of Solid-State Physics and Nanostructures, Voronezh State University, 394018 Voronezh, Russia.
Department of Pediatric Dentistry with Orthodontia, Voronezh State Medical University, 394006 Voronezh, Russia.
Int J Mol Sci. 2025 May 14;26(10):4693. doi: 10.3390/ijms26104693.
This study applies multivariate data analysis to deconvolute the spectral profiles of the Amide III region in the infrared spectra of gingival crevicular fluid (GCF). This reveals the impact of major oral diseases, such as dental caries and periodontal diseases, on the transformation of the secondary structure of GCF proteins. A two-stage analytical approach was employed: first, principal component analysis (PCA) was performed to establish the main factors of variation in the data, followed by pairwise comparisons of the samples based on the results of the Amide III profile deconvolution. The analysis also accounted for comorbidities, such as oncological and gastrointestinal diseases. This approach allowed for the identification of subtle differences in the composition and conformation of the secondary structure of GCF proteins while accounting for the superposition of multiple influencing factors. This methodology was effective in identifying biomarkers of oral diseases in GCF. For the first time, it has been demonstrated that the relative content of the β-sheet-associated component in the spectral profile of the secondary structure element of the protein fraction of GCF serves as a statistically significant marker for dental caries, regardless of the presence or absence of other diseases. Additionally, a significant decrease in the relative content of α-helix structures was observed in GCF from patients with oncological diseases. The changes in the spectral profile of the Amide III band of GCF identified in this study have not been previously detected using molecular spectroscopy, correlated with the secondary structure of proteins, or analyzed using multivariate analysis methods.
本研究应用多元数据分析对龈沟液（GCF）红外光谱中酰胺III区域的光谱轮廓进行解卷积。这揭示了诸如龋齿和牙周疾病等主要口腔疾病对GCF蛋白质二级结构转变的影响。采用了两阶段分析方法：首先，进行主成分分析（PCA）以确定数据中的主要变异因素，然后根据酰胺III轮廓解卷积的结果对样本进行成对比较。该分析还考虑了合并症，如肿瘤和胃肠道疾病。这种方法能够在考虑多种影响因素叠加的情况下，识别GCF蛋白质二级结构组成和构象的细微差异。该方法有效地识别了GCF中口腔疾病的生物标志物。首次证明，无论是否存在其他疾病，GCF蛋白质组分二级结构元素光谱轮廓中与β-折叠相关组分的相对含量可作为龋齿的统计学显著标志物。此外，在肿瘤疾病患者的GCF中观察到α-螺旋结构的相对含量显著降低。本研究中确定的GCF酰胺III带光谱轮廓的变化，此前尚未通过分子光谱检测到，未与蛋白质二级结构相关联，也未使用多元分析方法进行分析。
