Journal Article Epublish 11 citations
PubMed: 36355140 DOI: 10.3390/metabo12111058
Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia.
Metabolites 12(11)
Authors: Tushar H More, Bahareh Mozafari, Andre Märtens, Christian Herr, Philipp M Lepper, Guy Danziger, Thomas Volk, Sabrina Hoersch, Marcin Krawczyk, Katharina Guenther, Karsten Hiller, Robert Bals
Affiliations
- Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, 38106 Braunschweig, Germany.
- Department of Internal Medicine V-Pulmonology, Allergology and Critical Care Medicine, Saarland University, 66421 Homburg, Germany.
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, Saarland University, 66421 Homburg, Germany.
- Department of Internal Medicine II-Gastroenterology, Saarland University, 66421 Homburg, Germany.
- Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Saarland University Campus, 66123 Saarbrücken, Germany.
Abstract
Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.
MeSH
Blood, Machine Learning, Covid-19, Pneumonia, Metabolomics, Plasma
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