Youngja H Park1, Anne M Fitzpatrick2, Carl Angelo Medriano3, Dean P Jones4. 1. College of Pharmacy, Korea University, Sejong City, Korea. Electronic address: yjhwang@korea.ac.kr. 2. Department of Pediatrics, Emory University, Atlanta, Ga. 3. College of Pharmacy, Korea University, Sejong City, Korea. 4. Department of Medicine, Emory University, Atlanta, Ga.
Abstract
BACKGROUND: Corticosteroid (CS) treatment has been established as the first anti-inflammatory treatment for adults and children with asthma. However, a subset of patients fails to respond to combined systemic and inhaled CS treatment. OBJECTIVE: This study was aimed at further understanding CS resistance among children with severe asthma. METHODS: High-resolution metabolomics was performed on urine samples from CS-respondent (n = 15) and CS-nonrespondent (n = 15) children to determine possible urine biomarkers related to CS resistance. The metabolic phenotypes of CS responders and CS nonresponders were analyzed using bioinformatics including Manhattan plot with false- discovery rate, hierarchical cluster analysis, Kyoto Encyclopedia Genes and Genomes, and Mummichog pathway analysis. RESULTS: The 2-way hierarchical cluster analysis study determined 30 metabolites showing significantly different levels between CS responders and CS nonresponders. The important metabolites annotated were 3,6-dihydronicotinic acid (126.05 m/z, RT: 106, [M+H]+), 3-methoxy-4-hydroxyphenyl(ethylene)glycol (185.05 m/z, RT: 155, [M+H]+), 3,4-dihydroxy-phenylalanine (198.07 m/z, RT: 446, [M+H]+), γ-glutamylcysteine (236.06 m/z, RT: 528, [M+S(34)+H]+), Cys-Gly, (253.06 m/z, RT: 528, [M-NH3+H]+), and reduced Flavin mononucleotide (517.0794 m/z, RT: 533, [M+NaCl]+). Tyrosine metabolism, degradation of aromatic compounds, and glutathione metabolism are suggested to be significant pathways relating to CS resistance. CONCLUSIONS: High-resolution metabolomics is a promising approach in asthma research. Five candidate markers were identified to be related to CS-resistant children with severe asthma. These compounds, upon validation, may contribute further in the understanding of CS resistance among children with severe asthma through the use of urine.
BACKGROUND: Corticosteroid (CS) treatment has been established as the first anti-inflammatory treatment for adults and children with asthma. However, a subset of patients fails to respond to combined systemic and inhaled CS treatment. OBJECTIVE: This study was aimed at further understanding CS resistance among children with severe asthma. METHODS: High-resolution metabolomics was performed on urine samples from CS-respondent (n = 15) and CS-nonrespondent (n = 15) children to determine possible urine biomarkers related to CS resistance. The metabolic phenotypes of CS responders and CS nonresponders were analyzed using bioinformatics including Manhattan plot with false- discovery rate, hierarchical cluster analysis, Kyoto Encyclopedia Genes and Genomes, and Mummichog pathway analysis. RESULTS: The 2-way hierarchical cluster analysis study determined 30 metabolites showing significantly different levels between CS responders and CS nonresponders. The important metabolites annotated were 3,6-dihydronicotinic acid (126.05 m/z, RT: 106, [M+H]+), 3-methoxy-4-hydroxyphenyl(ethylene)glycol (185.05 m/z, RT: 155, [M+H]+), 3,4-dihydroxy-phenylalanine (198.07 m/z, RT: 446, [M+H]+), γ-glutamylcysteine (236.06 m/z, RT: 528, [M+S(34)+H]+), Cys-Gly, (253.06 m/z, RT: 528, [M-NH3+H]+), and reduced Flavin mononucleotide (517.0794 m/z, RT: 533, [M+NaCl]+). Tyrosine metabolism, degradation of aromatic compounds, and glutathione metabolism are suggested to be significant pathways relating to CS resistance. CONCLUSIONS: High-resolution metabolomics is a promising approach in asthma research. Five candidate markers were identified to be related to CS-resistant children with severe asthma. These compounds, upon validation, may contribute further in the understanding of CS resistance among children with severe asthma through the use of urine.
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