COVID-19: A Systematic Review of Metabolomics Data and Predicting Potential Biomarkers Based on Pathway Analysis

The COVID-19 pandemic is a worldwide disaster in medicine, public health, and the economy. Many details of COVID-19 are currently unknown. This study aims to offer dysregulated metabolic profiles as potential biomarkers for SARS-CoV-2 infection by analyzing identified COVID-19 metabolites. We searched PubMed, Web of Science, EMBASE, and Scopus for metabolomics studies on COVID-19 patients. Studies investigating COVID-19 metabolite changes and utilizing mass spectrometry-based techniques are included. Two reviewers separately retrieved pertinent data for each selected publication. Differences of opinion among the reviewers were settled via conversation, and a final judgment was obtained. The online MetaboAnalyst 3.0 was used to conduct the pathway analysis of COVID-19. This study comprised 31 investigations with QUADOMICS quality evaluation. We isolated modified metabolites that have been found in at least three other investigations. The metabolomics data in response to SARS-CoV-2 alter at the metabolite expression level, leading to dysregulation of major metabolic pathways, including carbohydrates, amino acids, and lipids associated with COVID-19. The pathway analysis of metabolic reprogramming across different biological samples demonstrated a significant role in amino acid metabolism, including phenylalanine, tyrosine, and tryptophan production, in the severity of COVID-19. This review showed dysregulated metabolic profiling for identifying individuals with high severity of COVID-19. These results provide an understanding of metabolic pathways and how dysregulated metabolic profiling reflects the severity of COVID-19 in the general population. The high frequency of changed metabolites might be used as COVID-19 biomarkers for early detection, and significant metabolic routes could reveal new information about pathogenesis and lead to potential treatment targets.