Metabolomics study of COVID-19 patients in four different clinical stages.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is the coronavirus strain causing the respiratory pandemic COVID-19 (coronavirus disease 2019). To understand the pathobiology of SARS-CoV-2 in humans it is necessary to unravel the metabolic changes that are produced in the individuals once the infection has taken place. The goal of this work is to provide new information about the altered biomolecule profile and with that the altered biological pathways of patients in different clinical situations due to SARS-CoV-2 infection. This is done via metabolomics using HPLC-QTOF-MS analysis of plasma samples at COVID-diagnose from a total of 145 adult patients, divided into different clinical stages based on their subsequent clinical outcome (25 negative controls (non-COVID); 28 positive patients with asymptomatic disease not requiring hospitalization; 27 positive patients with mild disease defined by a total time in hospital lower than 10 days; 36 positive patients with severe disease defined by a total time in hospital over 20 days and/or admission at the ICU; and 29 positive patients with fatal outcome or deceased). Moreover, follow up samples between 2 and 3 months after hospital discharge were also obtained from the hospitalized patients with mild prognosis. The final goal of this work is to provide biomarkers that can help to better understand how the COVID-19 illness evolves and to predict how a patient could progress based on the metabolites profile of plasma obtained at an early stage of the infection. In the present work, several metabolites were found as potential biomarkers to distinguish between the end-stage and the early-stage (or non-COVID) disease groups. These metabolites are mainly involved in the metabolism of carnitines, ketone bodies, fatty acids, lysophosphatidylcholines/phosphatidylcholines, tryptophan, bile acids and purines, but also omeprazole. In addition, the levels of several of these metabolites decreased to "normal" values at hospital discharge, suggesting some of them as early prognosis biomarkers in COVID-19 at diagnose.

Valdés A ，Moreno LO ，Rello SR ，Orduña A ，Bernardo D ，Cifuentes A ... -  《Scientific Reports》

Metabolic predictors of COVID-19 mortality and severity: a survival analysis.

The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes. In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes. A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods. Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.

Abdallah AM ，Doudin A ，Sulaiman TO ，Jamil O ，Arif R ，Sada FA ，Yassine HM ，Elrayess MA ，Elzouki AN ，Emara MM ，Thillaiappan NB ，Cyprian FS ... -  《Frontiers in Immunology》

Safety and Efficacy of Imatinib for Hospitalized Adults with COVID-19: A structured summary of a study protocol for a randomised controlled trial.

Emadi A ，Chua JV ，Talwani R ，Bentzen SM ，Baddley J ... -  《Trials》

Metabolic Signatures Associated with Severity in Hospitalized COVID-19 Patients.

Marín-Corral J ，Rodríguez-Morató J ，Gomez-Gomez A ，Pascual-Guardia S ，Muñoz-Bermúdez R ，Salazar-Degracia A ，Pérez-Terán P ，Restrepo MI ，Khymenets O ，Haro N ，Masclans JR ，Pozo OJ ... -  《INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES》

The specific metabolome profiling of patients infected by SARS-COV-2 supports the key role of tryptophan-nicotinamide pathway and cytosine metabolism.

Blasco H ，Bessy C ，Plantier L ，Lefevre A ，Piver E ，Bernard L ，Marlet J ，Stefic K ，Benz-de Bretagne I ，Cannet P ，Lumbu H ，Morel T ，Boulard P ，Andres CR ，Vourc'h P ，Hérault O ，Guillon A ，Emond P ... -  《Scientific Reports》