Abstract
Background: The outbreak of coronavirus disease 2019 (COVID-19) has led to substantial infections and mortality around the world. Fast screening and diagnosis are thus crucial to quick isolation and clinical intervention. Methods: Patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A/B, and respiratory syncytial virus (RSV), as well as healthy controls, were included in this study. All viral infections were confirmed by reverse transcriptase PCR (RT-PCR). The serum samples were measured by attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR). Multivariate and statistical analysis was performed to differentiate between or among groups. Findings: We found that the most discriminatory bands for COVID-19 vs. control classification were amide I, amide II, and νs(PO2−) in original spectra and centered at 1632, 1545, 1400, 1079, and 1037 cm-1 in the second derivative infrared (SD-IR) spectra. Normal controls, non-severe, and severe COVID-19 patients were well separated by unsupervised methods. ATR FT-IR coupled with partial least square discriminant analysis (PLS-DA) was effective to differentiate COVID-19 from normal controls and other respiratory viral infections with the area under the receiver operating characteristic curve (AUROC) of 0·9866 (95%CI 0·9721-0·9939). Interpretation: The band centered at 1633 cm-1 in the SD-IR spectra is mainly attributed to the β-pleated sheet structure from immunoglobulins. Increases in antibody levels and dysregulation of phospholipids can be derived from the measured spectra. The serum FT-IR spectra exhibited “chemical fingerprints” towards different viral infections.Funding Statement: This work was funded by the National Natural Science Foundation of China (52041701).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: This study was approved by the Ethics Committees from TsinghuaUniversity and Peking Union Medical College Hospital.
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