Evaluation of risk factors for COVID-19 severity or death and their relationship to metabolic pathways.

Background: Since the state of alarm was declared due to the COVID-19 pandemic, hospitals have been the main ones in charge of registering the therapeutic follow-up of affected people. The analysis of these data has allowed those different biochemical markers have been identified as predictors of the severity of the disease, but most of the published studies tend to be eminently descriptive and do not propose a biochemical hypothesis to explain the alteration of the results they are showing. Our objective is to recognize the main metabolic processes that are occurring in COVID-19 patients, as well as the identification of clinical parameters that are decisive to predict the severity of the disease. Methods: A multivariate analysis was carried out from the clinical parameters collected in the database of the HM hospitals in Madrid, to determine the most relevant variables to predict the severity of the disease. Chemometric methods allow these variables to be obtained by applying a classification strategy with PLS-LDA. Findings and interpretation: The variables that most contribute to separation are age in men and, in both sexes, the concentration of lactate dehydrogenase, urea and C-reactive protein.Oxygen deficiency in the tissues, due to the loss of functionality of the lungs, could be affecting the muscle tissue with special severity. Inflammation and tissue damage is related to increased LDH and CRP. The loss of muscle mass and the increase in the concentration of urea and LDH is explained by the adaptation of muscle metabolism to this oxygen deficiency. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profits sectors.

A metabolic readout of the urine metabolome of COVID-19 patients.

Analysis of urine samples from COVID-19 patients by 1H NMR reveals important metabolic alterations due to SAR-CoV-2 infection. Previous studies have identified biomarkers in urine that reflect metabolic alterations in COVID-19 patients. We have used 1H NMR to better define these metabolic alterations since this technique allows us to obtain a broad profile of the metabolites present in urine. This technique offers the advantage that sample preparation is very simple and gives us very complete information on the metabolites present. To detect these alterations, we have compared urine samples from COVID-19 patients (n = 35) with healthy people (n = 18). We used unsupervised (Robust PCA) and supervised (PLS-LDA) multivariate analysis methods to evaluate the differences between the two groups: COVID-19 and healthy controls. The differences focus on a group of metabolites related to energy metabolism (glucose, ketone bodies, glycine, creatinine, and citrate) and other processes related to bacterial flora (TMAO and formic acid) and detoxification (hippuric acid). The alterations in the urinary metabolome shown in this work indicate that SARS-CoV-2 causes a metabolic change from a normal situation of glucose consumption towards a gluconeogenic situation and possible insulin resistance.