The severe COVID-19 pandemic requires the development of novel, rapid, accurate, and label-free techniques that facilitate the detection and discrimination of SARS-CoV-2 infected subjects. Raman spectroscopy has been used to diagnose COVID-19 in serum samples of suspected patients without clinical symptoms of COVID-19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID-19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID-19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID-19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID-19). A discriminant model based on partial least squares regression (PLS-DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID-19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID-19 infection.

中文翻译：

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通过拉曼光谱检测人血清中的 COVID-19 并检测到免疫球蛋白 IgM 和 IgG

严重的 COVID-19 大流行需要开发新型、快速、准确和无标记的技术，以促进对 SARS-CoV-2 感染对象的检测和鉴别。拉曼光谱已用于诊断没有 COVID-19 临床症状的疑似患者血清样本中的 COVID-19，但与对照（阴性 IgM 和 IgG）相比，其免疫球蛋白 M 和 G（IgM 和 IgG）检测呈阳性。使用色散拉曼光谱仪 (830 nm, 350 mW)，获得三份光谱。共使用了 94 个血清样本（54 个对照和 40 个 COVID-19）的 278 个光谱。通过主成分分析 (PCA) 评估的阳性 IgM 和 IgG 与对照之间的主要光谱差异，是分配给蛋白质的特征，包括白蛋白（在 COVID-19 组和 IgM/IgG 和 IgG 阳性组中较低）和分配给脂质、磷脂和类胡萝卜素的特征（在 COVID-19 组和 IgM/IgG 组中较高）积极的）。还发现了涉及核酸、色氨酸和免疫球蛋白的特征（COVID-19 组较高）。基于偏最小二乘回归 (PLS-DA) 的判别模型发现区分阳性 Ig 组与对照组的敏感性为 84.0%，特异性为 95.0%，准确度为 90.3%。在考虑单个 Ig 组与对照组时，发现灵敏度为 77.3%，特异性为 97.5%，准确度为 88.8%。IgM 组发现了更高的分类错误（没有成功分类）。