Related Experiment Video
Updated: Mar 1, 2026
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
A longitudinal comparative analysis of serum metabolomic signatures in children with SARS-CoV-2 infection and MIS-C
A Lo Vecchio1, V Discepolo2,3, L Pierri2
1Section of Pediatrics, Department of Translational Medical Sciences, Clinical Research Center DEMeTra, University of Naples Federico II, Naples, Italy. andrea.lovecchio@unina.it.
Insights
Children with COVID-19 exhibit unique metabolic changes, including inflammation and altered glucose and lipid pathways. These metabolic signatures differ in Multisystem Inflammatory Syndrome in Children (MIS-C) and normalize upon recovery.
Area of Science:
- Biochemistry
- Pediatrics
- Infectious Diseases
Background:
- While SARS-CoV-2 (COVID-19) typically causes mild illness in children, a subset develops Multisystem Inflammatory Syndrome in Children (MIS-C).
- Metabolic pathway dysregulation is documented in adult COVID-19, but data in pediatric populations are scarce.
- This study investigates serum metabolomic profiles in children with COVID-19, examining associations with age, sex, and disease severity.
Purpose of the Study:
- To characterize the serum metabolomic signature of pediatric COVID-19.
- To compare metabolomic profiles between children with acute SARS-CoV-2 infection, MIS-C, and healthy controls.
- To explore the relationship between metabolomic changes, clinical parameters, and disease outcomes.
Main Methods:
- Prospective observational cohort study including 92 children with acute SARS-CoV-2 infection, 7 with MIS-C, and 41 age- and sex-matched controls.
- Serum samples collected at admission, acute phase, discharge, and remission.
- Metabolomic analysis performed using Gas Chromatography Mass Spectroscopy (GC-MS).
Main Results:
- A distinct metabolomic signature characterized by inflammation, reactive oxygen species, and glycerolipid pathways was identified in children with acute SARS-CoV-2 infection compared to controls.
- Metabolomic profile alterations correlated with age, disease status, and severity, normalizing upon disease resolution.
- Children with MIS-C presented a unique metabolomic signature distinct from both COVID-19 patients and controls.
Conclusions:
- Pediatric COVID-19 is associated with a characteristic metabolomic signature involving glucose and amino acid metabolism, which varies by age and clinical presentation.
- Metabolomics offers valuable insights into host-viral interactions in pediatric COVID-19.
- Metabolomic profiling may aid in identifying early predictors of disease progression and outcomes in children.
Background:
SARS-CoV-2 infection usually has a mild course in childhood, yet few children develop a Multisystem Inflammatory Syndrome (MIS-C). Several metabolic pathways have been found to be dysregulated in adults with COVID-19, yet data are lacking in children. Here we investigate serum metabolomic features of children with COVID-19 in relation to age, sex and both clinical and biochemical severity.
Methods:
We carried out a prospective observational comparative cohort study enrolling 92 children (48 M, mean age 3.69 ± 5.1 years) with acute SARS-CoV-2 infection and 7 with MIS-C along with 41 age- and sex-matched controls. Sera collected at admission, acute phase, discharge and remission were analyzed by Gas Chromatography Mass Spectroscopy.
Results:
Here we identify a distinct signature featuring inflammation, reactive oxygen species and glicerolipids pathways in children with acute SARS-CoV-2 infection compared to controls (permutation test p = 0.0015). Metabolomic profile changes are associated with age, disease status and disease severity, while a normalization of these changes is observed at disease resolution. MIS-C children showed a unique signature compared to age-/sex-matched COVID-19 patients or controls.
Conclusions:
Pediatric COVID-19 has a characteristic metabolomic signature featuring glucose and aminoacid metabolism, that varies with age and disease phenotype. Our study supports the value of metabolomics to unveil pathways related to host-viral interaction that may also help identify early predictors of disease evolution.
