Jia-Lei Tao1,2, Yan-Zhen Chen3, Qi-Gang Dai1,2, Man Tian4, Shou-Chuan Wang1,2, Jin-Jun Shan1,2, Jian-Jian Ji1,2, Li-Li Lin1,2, Wei-Wei Li1,2, Bin Yuan1,2. 1. Department of Paediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China. 2. Jiangsu Key Laboratory of Paediatric Respiratory Disease, Institute of Paediatrics, Nanjing University of Chinese Medicine, Nanjing, China. 3. Oncology Department, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China. 4. Respiratory Department, Nanjing Children's Hospital affiliated to Nanjing Medical University, Nanjing, China.
Abstract
BACKGROUND AND OBJECTIVE: Asthma is a global problem and complex disease suited for metabolomic profiling. This study explored the candidate biomarkers specific to paediatric asthma and provided insights into asthmatic pathophysiology. METHODS: Children (aged 6-11 years) meeting the criteria for healthy control (n = 29), uncontrolled asthma (n = 37) or controlled asthma (n = 43) were enrolled. Gas chromatography-mass spectrometry was performed on urine samples of the patients to explore the different types of metabolite profile in paediatric asthma. Additionally, we employed a comprehensive strategy to elucidate the relationship between significant metabolites and asthma-related genes. RESULTS: We identified 51 differential metabolites mainly related to dysfunctional amino acid, carbohydrate and purine metabolism. A combination of eight candidate metabolites, including uric acid, stearic acid, threitol, acetylgalactosamine, heptadecanoic acid, aspartic acid, xanthosine and hypoxanthine (adjusted P < 0.05 and fold-change >1.5 or <0.67), showed excellent discriminatory performance for the presence of asthma and the differentiation of poor-controlled or well-controlled asthma, and area under the curve values were >0.97 across groups. Enrichment analysis based on these targets revealed that the Fc receptor, intracellular steroid hormone receptor signalling pathway, DNA damage and fibroblast proliferation were involved in inflammation, immunity and stress-related biological progression of paediatric asthma. CONCLUSION: Metabolomic analysis of patient urine combined with network-biology approaches allowed discrimination of asthma profiles and subtypes according to the metabolic patterns. The results provided insight into the potential mechanism of paediatric asthma.
BACKGROUND AND OBJECTIVE:Asthma is a global problem and complex disease suited for metabolomic profiling. This study explored the candidate biomarkers specific to paediatric asthma and provided insights into asthmatic pathophysiology. METHODS:Children (aged 6-11 years) meeting the criteria for healthy control (n = 29), uncontrolled asthma (n = 37) or controlled asthma (n = 43) were enrolled. Gas chromatography-mass spectrometry was performed on urine samples of the patients to explore the different types of metabolite profile in paediatric asthma. Additionally, we employed a comprehensive strategy to elucidate the relationship between significant metabolites and asthma-related genes. RESULTS: We identified 51 differential metabolites mainly related to dysfunctional amino acid, carbohydrate and purine metabolism. A combination of eight candidate metabolites, including uric acid, stearic acid, threitol, acetylgalactosamine, heptadecanoic acid, aspartic acid, xanthosine and hypoxanthine (adjusted P < 0.05 and fold-change >1.5 or <0.67), showed excellent discriminatory performance for the presence of asthma and the differentiation of poor-controlled or well-controlled asthma, and area under the curve values were >0.97 across groups. Enrichment analysis based on these targets revealed that the Fc receptor, intracellular steroid hormone receptor signalling pathway, DNA damage and fibroblast proliferation were involved in inflammation, immunity and stress-related biological progression of paediatric asthma. CONCLUSION: Metabolomic analysis of patient urine combined with network-biology approaches allowed discrimination of asthma profiles and subtypes according to the metabolic patterns. The results provided insight into the potential mechanism of paediatric asthma.