Tangwanichgapong Kamonchanok, Klanrit Poramaporn, Chatchawal Patutong, Wongwattanakul Molin, Pongskul Cholatip, Chaichit Rajda, Hormdee Doosadee
Division of Periodontology, Department of Oral Biomedical Sciences, Faculty of Dentistry, Khon Kaen University, Khon Kaen 40002, Thailand; Research Group of Chronic Inflammatory Oral Diseases and Systemic Diseases Associated with Oral Health, Department of Oral Biomedical Sciences, Faculty of Dentistry, Khon Kaen University, Khon Kaen 40002, Thailand.
Division of Oral Diagnosis, Department of Oral Biomedical Sciences, Faculty of Dentistry, Khon Kaen University, Khon Kaen 40002, Thailand; Research Group of Chronic Inflammatory Oral Diseases and Systemic Diseases Associated with Oral Health, Department of Oral Biomedical Sciences, Faculty of Dentistry, Khon Kaen University, Khon Kaen 40002, Thailand.
Photodiagnosis Photodyn Ther. 2025 Apr;52:104502. doi: 10.1016/j.pdpdt.2025.104502. Epub 2025 Jan 30.
The increasing prevalence of chronic kidney disease (CKD) and its terminal stage, end-stage renal disease (ESRD), raises the importance of an accurate, early, and point-of-care method to diagnose and monitor patients. Saliva is a potential point-of-care diagnostic biofluid for its simple collection and ability to reflect systemic health status. This study investigated salivary spectral signatures in ESRD patients and their diagnostic potential compared to healthy controls.
Saliva samples were collected from 24 ESRD patients undergoing hemodialysis and 24 age/sex-matched healthy controls. The dried saliva samples were analyzed using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy in the 4000-400 cm⁻¹ range. Chemometric analyses, including Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), were applied to preprocessed spectra to identify discriminatory spectral features and establish classification models.
Second derivative spectroscopic analysis of ATR-FTIR spectra revealed distinctive spectral patterns in dried ESRD saliva samples, including characteristic peak shifts observed in both the amide I secondary structures (from 1636 cm in controls to 1629 cm in ESRD) and carbohydrate (from 1037 cm in controls to 1042 cm in ESRD) regions. PCA demonstrated clear clustering patterns across key biological spectral regions, including the lipid CH stretching region (3000-2800 cm), the fingerprint region (1800-900 cm), and their combination (3000-2800 cm + 1800-900 cm). PLS models based on the fingerprint region achieved optimal diagnostic performance (87.5-100 % accuracy, 75-100 % sensitivity, and 100 % specificity). Biochemical markers associated with ESRD revealed variations in lipids, protein, sugar moieties, carbohydrates, and nucleic acids, reflecting the underlying pathological changes in CKD, with the most prominent band at ∼1405 cm.
ATR-FTIR analysis of dried saliva demonstrated potential as a non-invasive diagnostic tool for ESRD. This approach could complement existing diagnostic methods, particularly in resource-limited settings or for frequent monitoring requirements.
慢性肾脏病（CKD）及其终末期——终末期肾病（ESRD）的患病率不断上升，这凸显了一种准确、早期且即时检测的方法对于诊断和监测患者的重要性。唾液因其采集简便且能够反映全身健康状况，是一种潜在的即时检测诊断生物流体。本研究调查了ESRD患者的唾液光谱特征及其与健康对照相比的诊断潜力。
收集了24例接受血液透析的ESRD患者和24例年龄/性别匹配的健康对照的唾液样本。使用衰减全反射傅里叶变换红外光谱（ATR-FTIR）在4000 - 400 cm⁻¹范围内对干燥的唾液样本进行分析。化学计量学分析，包括主成分分析（PCA）和偏最小二乘判别分析（PLS-DA），应用于预处理后的光谱，以识别具有区分性的光谱特征并建立分类模型。
ATR-FTIR光谱的二阶导数光谱分析揭示了干燥的ESRD唾液样本中独特的光谱模式，包括在酰胺I二级结构（从对照中的1636 cm移至ESRD中的1629 cm）和碳水化合物区域（从对照中的1037 cm移至ESRD中的1042 cm）均观察到特征峰位移。PCA在关键生物光谱区域展示了清晰的聚类模式，包括脂质CH伸缩区域（3000 - 2800 cm）、指纹区域（1800 - 900 cm）及其组合（3000 - 2800 cm + 1800 - 900 cm）。基于指纹区域的PLS模型实现了最佳诊断性能（准确率87.5 - 100%，灵敏度75 - 100%，特异性100%）。与ESRD相关的生化标志物显示脂质、蛋白质、糖部分、碳水化合物和核酸存在变化，反映了CKD的潜在病理变化，最显著的谱带在约1405 cm处。
对干燥唾液进行ATR-FTIR分析显示出作为ESRD无创诊断工具的潜力。这种方法可以补充现有的诊断方法，特别是在资源有限的环境中或对于频繁监测需求的情况下。
