ABSTRACT
Brazil has the second highest COVID-19 death rate while Rio de Janeiro is among the states with the highest rate in the country. Although effective vaccines have been developed, it is anticipated that the ongoing COVID-19 pandemic will transition into an endemic state. Under this scenario, it is worrisome that the underlying molecular mechanisms associated with the disease clinical evolution from mild to severe, as well as the mechanisms leading to long COVID are not yet fully understood. In this study, 1H Nuclear Magnetic Resonance spectroscopy and Liquid Chromatography-Mass spectrometry-based metabolomics were used to identify potential pathways and metabolites involved in COVID-19 pathophysiology and disease outcome. Between April and July 2020, 35 plasma samples from patients with confirmed severe COVID-19 from two reference centers in Rio de Janeiro, and 12 samples from non-infected control subjects, were collected and included in this study. Of the 35 samples from COVID-19 patients, 18 were from survivors and 17 from non-survivors. We observed that patients with severe COVID-19 had their plasma metabolome significantly changed if compared to control subjects. We observed lower levels of glycerophosphocholine and other choline-related metabolites, serine, glycine, and betaine, indicating a dysregulation in methyl donors and one-carbon metabolism. Importantly, non-survivors had higher levels of creatine/creatinine, 4-hydroxyproline, gluconic acid and N-acetylserine compared to survivors and controls, reflecting uncontrolled inflammation, liver and kidney dysfunction, and insulin resistance in these patients. Lipoprotein dynamics and amino acid metabolism were also altered in severe COVID-19 subjects. Several changes were greater in women, thus patient's sex should be considered in pandemic surveillance to achieve better disease stratification and improve outcomes. The incidence of severe outcome after hospital discharge is very high in Brazil, thus these metabolic alterations may be used to monitor patients' organs and tissues and to understand the pathophysiology of long-post COVID-19.
Subject(s)
Chronobiology Disorders , Kidney Diseases , Death , COVID-19 , InflammationABSTRACT
BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.