Abstract：
Thyroid-associated ophthalmopathy (TAO) is the most common orbital disease in adults, with complex clinical manifestations and significant impacts on the life quality of patients. The current diagnosis of TAO lacks reliable biomarkers for early and non-invasive screening and detection, easily leading to poor prognosis. Therefore, it is essential to explore new methods for accurately predicting TAO development in its early stage. In this study, Raman spectroscopy, with non-destructive, label-free, and high-sensitivity characteristics, was used to analyze the differences in biochemical components of orbital adipocyte and tear samples between TAO and control groups. Furthermore, a multivariate analysis method (i.e., Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA)) was applied for data processing and analysis. Compared with controls, PCA-LDA yielded TAO diagnostic accuracies of 72.7% and 75.0% using orbital adipocytes and tears, respectively. Our proof-of-concept results suggest that Raman spectroscopy holds potential for exploring the underlying pathogenesis of TAO, and its potential application in early screening of other thyroid-associated diseases can be further expanded.
摘要：
甲状腺相关眼病（TAO）是成人最常见的眼眶疾病，临床表现复杂,对患者生活质量有显著影响。目前TAO的诊断缺乏可靠的早期和非侵入性筛查和检测的生物标志物。容易导致预后不良。因此,探索新的方法在早期准确预测TAO的发展至关重要。在这项研究中,拉曼光谱,非破坏性的，无标签，和高灵敏度特性，用于分析TAO和对照组之间眼眶脂肪细胞和泪液样品生化成分的差异。此外，多变量分析方法(即，主成分分析-线性判别分析（PCA-LDA）用于数据处理和分析。与对照组相比，PCA-LDA使用眼眶脂肪细胞和泪液产生的TAO诊断准确率分别为72.7%和75.0%，分别。我们的概念验证结果表明，拉曼光谱具有探索TAO潜在发病机理的潜力，及其在其他甲状腺相关疾病早期筛查中的潜在应用可进一步拓展。
