Investigating the Use of SARS-CoV-2 (COVID-19) Odor Expression as a Non-Invasive Diagnostic Tool-Pilot Study.
Investigating the Use of SARS-CoV-2 (COVID-19) Odor Expression as a Non-Invasive Diagnostic Tool-Pilot Study.
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DOI：
10.3390/diagnostics13040707
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发表时间：
2023-02-13
期刊：
影响因子：
3.6
通讯作者：
Furton, Kenneth G. G.
中科院分区：
文献类型：
--
作者：
Crespo-Cajigas, Janet;Gokool, Vidia A. A.;Torres, Andrea Ramirez;Forsythe, Liam;Abella, Benjamin S. S.;Holness, Howard K. K.;Johnson, Alan T. Charlie;Postrel, Richard;Furton, Kenneth G. G.
关键词：
自 COVID-19 大流行开始以来，人们对制定能够快速检测该疾病的措施产生了极大的兴趣。对 SARS-CoV-2 感染的快速筛查和初步诊断可以立即识别可能感染的个体并随后缓解疾病传播。在此，探索了使用非侵入性采样和低准备工作分析仪器来检测 SARS-CoV-2 感染者。从 SARS-CoV-2 阳性和阴性个体中获取手臭样本。使用固相微萃取 (SPME) 从收集的手臭样品中提取挥发性有机化合物 (VOC)，并使用气相色谱-质谱联用 (GC-MS) 进行分析。稀疏偏最小二乘判别分析 (sPLS-DA) 用于使用可疑变异样本子集开发预测模型。开发的 sPLS-DA 模型在仅根据 VOC 特征区分 SARS-CoV-2 阳性和阴性个体方面表现中等（准确度为 75.8% (±0.4)、灵敏度为 81.8%、特异性为 69.7%）。使用这种多变量数据分析初步获得了区分感染状态的潜在标志物。这项工作凸显了使用气味特征作为诊断工具的潜力，并为优化其他快速筛查传感器（例如电子鼻或检测犬）奠定了基础。
Since the beginning of the COVID-19 pandemic, there has been enormous interest in the development of measures that would allow for the swift detection of the disease. The rapid screening and preliminary diagnosis of SARS-CoV-2 infection allow for the instant identification of possibly infected individuals and the subsequent mitigation of the disease spread. Herein, the detection of SARS-CoV-2-infected individuals was explored using noninvasive sampling and low-preparatory-work analytical instrumentation. Hand odor samples were obtained from SARS-CoV-2-positive and -negative individuals. The volatile organic compounds (VOCs) were extracted from the collected hand odor samples using solid phase microextraction (SPME) and analyzed using gas chromatography coupled with mass spectrometry (GC-MS). Sparse partial least squares discriminant analysis (sPLS-DA) was used to develop predictive models using the suspected variant sample subsets. The developed sPLS-DA models performed moderately (75.8% (±0.4) accuracy, 81.8% sensitivity, 69.7% specificity) at distinguishing between SARS-CoV-2-positive and negative -individuals based on the VOC signatures alone. Potential markers for distinguishing between infection statuses were preliminarily acquired using this multivariate data analysis. This work highlights the potential of using odor signatures as a diagnostic tool and sets the groundwork for the optimization of other rapid screening sensors such as e-noses or detection canines.
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