Metabolomics analysis in schoolchildren and adolescents with COVID-19 treated at HCFMUSP

• Grant number: 21/06343-3
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date until: July 01, 2022
• End date until: February 28, 2025
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Patricia Palmeira Daenekas Jorge
• Grantee: Yingying Zheng
• Host Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated scholarship(s): 23/11594-0 - Untargeted metabolomic profiling from adolescents recovered of COVID-19, BE.EP.DR

Abstract

The agent called "Severe Acute Respiratory Syndrome Coronavirus-2" (SARS-CoV-2) and its associated disease, "Coronavirus Disease 2019" (COVID-19) has affected children and adolescents, with an incidence ranging from 1.2% to 2%. Autopsies performed on schoolchildren and adolescents who acquired COVID-19 revealed lesions in multiple organs. In COVID-19 survivors, persistent inflammation may occur, in which isolated or concomitant aggressions of various organs and systems are observed, leading to a potential chronic condition, impacting health-related aspects of quality of life. Untargeted metabolomics analysis is an innovative methodology based on the qualitative analysis of the largest possible number of metabolites, belonging to different chemical classes, contained in a biological system. Due to the possible multiple impairment of organs and systems, and also the lack of knowledge of the long-term sequelae caused by COVID-19 in pediatric patients, the metabolomics analysis is able to increase the understanding of pathological mechanisms, enabling the detection of biomarkers for diagnosis and prognosis and for the development of new treatments. Objective: To perform untargeted metabolomics comparison of pediatric patients recovered from COVID-19 (COV group) with pediatric patients non-diagnosed with COVID-19 (group C). Methods: The number of samples in both groups is 50. For group C, participants must have negative PCR and IgG tests for SARS-CoV-2. In the COV group patients fulfilled the following inclusion criteria: 1) diagnosed with COVID-19 in the year 2020, 3 to 6 months and one year before sample collection; 2) confirmation of infection by SARS-CoV-2 (by real-time RT-PCR or serology); 3) age at diagnosis between 7 and 18 years and; 4) previously healthy individual or with a pre-existing chronic condition. Items 3 and 4 will also be applied to group C. Plasma samples obtained 3 to 6 months and one year after COVID-19 diagnosis will be used for analysis of untargeted metabolomics by means of high performance liquid chromatography coupled with mass spectrometry, and the data obtained will be compared to the databases METLIN and HMDB. Statistical analysis: The results will be expressed as median or mean and compared using the Mann-Whitney or Student t test, according to the normality of the data; data represented by categorical variables will be presented as frequency and compared by Fisher's exact test or Pearson's chi-square test, as appropriate. For the metabolomics analysis, the MetaboAnalyst 4.0 and/or statistical systems in R will be used. MetaboAnalyst, KEGG or similar will be used for the biological interpretation of the dysregulated metabolic pathways. The logistic regression model with covariates will be built with each metabolite differentially expressed to investigate which metabolites were altered by the conditions of the individuals. Values of p less than 0.05 will be considered significant. (AU)