Metabolite, protein, and tissue dysfunction associated with COVID-19 disease severity

Authors

Ali Rahnavard, Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA. rahnavard@gwu.edu.
Brendan Mann, Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Abhigya Giri, Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Ranojoy Chatterjee, Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.
Keith A. Crandall, Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, 20052, USA.

Document Type

Journal Article

Publication Date

7-16-2022

Journal

Scientific reports

Volume

12

Issue

1

DOI

10.1038/s41598-022-16396-9

Abstract

Proteins are direct products of the genome and metabolites are functional products of interactions between the host and other factors such as environment, disease state, clinical information, etc. Omics data, including proteins and metabolites, are useful in characterizing biological processes underlying COVID-19 along with patient data and clinical information, yet few methods are available to effectively analyze such diverse and unstructured data. Using an integrated approach that combines proteomics and metabolomics data, we investigated the changes in metabolites and proteins in relation to patient characteristics (e.g., age, gender, and health outcome) and clinical information (e.g., metabolic panel and complete blood count test results). We found significant enrichment of biological indicators of lung, liver, and gastrointestinal dysfunction associated with disease severity using publicly available metabolite and protein profiles. Our analyses specifically identified enriched proteins that play a critical role in responses to injury or infection within these anatomical sites, but may contribute to excessive systemic inflammation within the context of COVID-19. Furthermore, we have used this information in conjunction with machine learning algorithms to predict the health status of patients presenting symptoms of COVID-19. This work provides a roadmap for understanding the biochemical pathways and molecular mechanisms that drive disease severity, progression, and treatment of COVID-19.

APA Citation

Rahnavard, Ali; Mann, Brendan; Giri, Abhigya; Chatterjee, Ranojoy; and Crandall, Keith A., "Metabolite, protein, and tissue dysfunction associated with COVID-19 disease severity" (2022). GW Authored Works. Paper 1295.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/1295

Department

Biostatistics and Bioinformatics