Rationale: Pediatric asthma is heterogeneous, with varied clinical presentations and treatment responses. Metabolomic profiling may uncover shared and unique biological mechanisms across clinical traits that characterize pediatric asthma.
Objectives: To characterize the varied clinical presentation of pediatric asthma by examining the metabolome's relationship with 22 clinical traits, categorized into 5 phenotypic domains: airway hyperresponsiveness (AHR), atopy, lung function (LF), blood eosinophil (B-EOS), and blood neutrophil (B-NEU).
Methods: Metabolomic profiling was conducted on plasma samples from children in the Childhood Asthma Management Program (CAMP) (n=953) and the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n=1,155) studies. We identified domain-specific and multi-domain metabolites using a fixed-effect meta-analysis of generalized linear models between metabolites and 22 clinical traits. Metabolomic Risk Scores (MRSs) were developed to summarize the metabolic processes for each domain at the patient level.
Measurements and main results: There were 154 unique metabolites significantly associated with at least one of 22 clinical traits (q-value<0.05). Histamine and kynurenine were significant across 4 domains, while 7 metabolites-12,13-diHOME, azelate, sebacate, PC(P-36:0)/PC(O-36:1), taurine, nudifloramide, and niacinamide-were significant across 3. Notable domain-specific metabolites include n-oleoyl dopamine for AHR, 9-cis-retinoic acid for lung function, phosphatidylcholines for B-EOS, and 2-hydroxybutyric acid for B-NEUT. We then applied the domain-specific MRSs to previously identified patient clusters, enabling a more comprehensive characterization of each endotype.
Conclusion: This study demonstrated the power of the metabolome to capture the heterogeneity in the clinical presentation of pediatric asthma and to develop clinically relevant MRSs that inform our understanding of specific metabotypes to guide targeted treatment approaches.
Keywords: Asthma; Metabolomics; Metabolomics Risk Score; Metabotypes; Phenotypes.