Exhaled breath-based clusters in children with post-COVID condition

Area of Science:

• Metabolomics
• Biomarker Discovery
• Pediatric Health

Background:

• Pediatric post-COVID condition (PPCC) is a complex condition with varied symptoms.
• Identifying distinct patient subgroups is crucial for effective management.
• Exhaled breath analysis offers a non-invasive approach to disease characterization.

Purpose of the Study:

• To identify distinct phenotypes of pediatric post-COVID condition (PPCC).
• To discover exhaled volatile organic compound (VOC) biomarkers for patient stratification.
• To understand the metabolic underpinnings of PPCC heterogeneity.

Main Methods:

• Unsupervised clustering of exhaled breath metabolites from 54 children with PPCC.
• Comparison of identified clusters with clinical variables, including PROMIS fatigue scores.
• Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) to identify discriminatory VOCs.

Main Results:

• Two distinct PPCC phenotypes (clusters) were identified.
• Cluster 2, with 16 patients, showed more severe outcomes and comprised older girls.
• Six VOCs were identified as highly accurate biomarkers (AUROC=1) differentiating the two clusters, indicating metabolic and inflammatory disruptions.

Conclusions:

• This study successfully identified two distinct PPCC phenotypes using exhaled VOCs.
• Six VOCs serve as promising non-invasive biomarkers for stratifying PPCC patients.
• Further research with larger cohorts is needed to confirm findings and explore underlying mechanisms.