Proteomics and Informatics for Understanding Phases and Identifying Biomarkers in COVID-19 Disease

• Published in: Journal of proteome research Vol. 19; no. 11; pp. 4219 - 4232
• Main Authors: Whetton, Anthony D, Preston, George W, Abubeker, Semira, Geifman, Nophar
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 06.11.2020
• Subjects: Artificial Intelligence; Betacoronavirus; biomarkers; Biomarkers - analysis; blood coagulation; C-reactive protein; complications (disease); Coronavirus Infections - blood; Coronavirus Infections - diagnosis; Coronavirus Infections - metabolism; Coronavirus Infections - physiopathology; COVID-19; COVID-19 infection; data collection; Diagnosis, Computer-Assisted; Humans; immunoglobulins; inflammation; lactate dehydrogenase; mass spectrometry; mortality; Pandemics; patients; Pneumonia, Viral - blood; Pneumonia, Viral - diagnosis; Pneumonia, Viral - metabolism; Pneumonia, Viral - physiopathology; Prognosis; proteome; Proteomics; research and development; Reviews; RNA; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; therapeutics; COVID-19; SARS-CoV-2; proteomics; assay; marker; diagnosis; biomarker; prognosis; artificial intelligence
• ISSN: 1535-3893; 1535-3907; 1535-3907
• DOI: 10.1021/acs.jproteome.0c00326

The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that fuller definitions of patient status, trajectory, sequelae, and responses to therapy are now required. There is accumulating evidencefrom studies of both COVID-19 and the related disease SARSthat protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase), and the inflammatory response (e.g., C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. To be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g., using mass spectrometry) but also informatics approaches via which to derive actionable information from large data sets. Here we review applications of proteomics to COVID-19 and SARS and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.