Significance: A noninvasive method based on surface-enhanced Raman spectroscopy (SERS) of tears was proposed as a support for diagnosing neurodegenerative pathologies, including different forms of dementia and Alzheimer’s disease (AD). In this field, timely and reliable discrimination and diagnosis are critical aspects for choosing a valid medical therapy, and new methods are highly required. Aim: The aim is to evince spectral differences in SERS response of human tears from AD affected, mild cognitive impaired (MCI), and healthy control (Ctr) subjects. Approach: Human tears were characterized by SERS coupled with multivariate data analysis. Thirty-one informed subjects (Ctr, MCI, and AD) were considered. Results: Average SERS spectra from Ctr, MCI, and AD subjects evidenced differences related to lactoferrin and lysozyme protein components. Quantitative changes were also observed by determining the intensity ratio between selected bands. We also constructed a classification model that discriminated among AD, MCI, and Ctr subjects. The model was built using the scores obtained by performing principal component analysis on specific spectral regions (i-PCA). Conclusions: The results are very encouraging with interesting perspectives for medical applications as support of clinical diagnosis and discrimination of AD from other forms of dementia.

中文翻译：

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眼泪的表面增强拉曼光谱：用于神经退行性疾病识别的诊断工具。

意义：提出了一种基于眼泪表面增强拉曼光谱 (SERS) 的非侵入性方法，以支持诊断神经退行性疾病，包括不同形式的痴呆症和阿尔茨海默病 (AD)。在该领域，及时可靠的鉴别诊断是选择有效药物治疗的关键，迫切需要新的方法。目的：目的是证明来自受 AD 影响、轻度认知障碍 (MCI) 和健康对照 (Ctr) 受试者的人类眼泪的 SERS 响应光谱差异。方法：人类眼泪的特征是 SERS 加上多变量数据分析。考虑了 31 名知情受试者（Ctr、MCI 和 AD）。结果：来自 Ctr、MCI 和 AD 受试者的平均 SERS 光谱证明了与乳铁蛋白和溶菌酶蛋白成分相关的差异。通过确定所选条带之间的强度比，还观察到数量变化。我们还构建了一个区分 AD、MCI 和 Ctr 对象的分类模型。该模型是使用通过对特定光谱区域 (i-PCA) 执行主成分分析获得的分数构建的。结论：结果非常令人鼓舞，具有有趣的医学应用前景，支持临床诊断和区分 AD 与其他形式的痴呆症。