Dr. Julie A. Reisz Haines
Department of Biochemistry and Molecular Genetics,
University of Colorado Anschutz Medical Campus, Aurora, CO, USA
Abstract:
The COVID-19 pandemic has opened countless scientific and medical questions into how the SARS-CoV-2 virus affects humans and alters host cell metabolism to fuel viral replication. In several distinct studies, we profiled the serum, plasma, and red blood cell metabolome in COVID patients using high throughput mass spectrometry-based metabolomics. We first evaluated serum metabolites of patients with COVID-19 (n = 33) compared to COVID-19-negative healthy controls (n = 16). Targeted and untargeted metabolomics analyses identified in COVID-19 + serum elevated tryptophan metabolism into the kynurenine pathway, which regulates inflammation and immunity and correlated with interleukin-6 (IL-6) levels. Increased circulating levels of free fatty acids and decreased acylcarnitines were also observed in COVID patients.
Metabolite levels in these pathways correlated with clinical laboratory markers of inflammation (i.e., IL-6 and C-reactive protein) and renal function (i.e., blood urea nitrogen). In a subsequent study, we analyzed plasma samples from acutely ill patients, testing positive (n=543) or negative (n=288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples. Significant changes in tryptophan/indole/kynurenine, fatty acid, and acylcarnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables. Omics data were correlated to detailed data on patient characteristics and coagulation to begin illustrating the metabolic heterogeneity associated with COVID-19 positivity.
Finally, the COVIDome Researcher Explorer Portal was presented as an open access tool for real time analysis of data (positive n = 73; negative n = 32) acquired on metabolomics, proteomics, transcriptomics, and other platforms. This tool (available at covidome.org) allows for visualization and statistical analysis of integrated data sets with the opportunity for data export and analysis using other tools. Together, the work presented here illustrates the utility of high throughput metabolomics in analyzing large clinically relevant sample sets for understanding how endogenous and exogenous factors affect systemic metabolism and perhaps inform patient outcome and best therapies.
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