Urinary Metabolomic Profiling Reveals Biological Pathways and Predictive Signatures Associated with Childhood Asthma

Abstract

Shuxian Li,1,* Jinling Liu,1,* Junfen Zhou,1,2 Yingshuo Wang,1 Fang Jin,1 Xiaoyang Chen,3 Jun Yang,4,5 Zhimin Chen1 1Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China; 2Department of Pediatrics, Wenling Maternal and Child Health Care Hospital, Wenling, Zhejiang 317500, China; 3Developmental and Behavioral Department, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang 310052, China; 4Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang 310013, China; 5Department of Toxicology, Hangzhou Normal University School of Public Health, Hangzhou, Zhejiang 310016, China*These authors contributed equally to this workCorrespondence: Zhimin ChenDepartment of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, 3333 Binsheng Road, Hangzhou, Zhejiang 310052, ChinaTel [phone]Fax [phone]Email [email protected] YangDepartment of Toxicology, Hangzhou Normal University, Hangzhou, Zhejiang 310016, ChinaTel/Fax + 86 571 8820 8141Email [email protected]: Despite considerable efforts, the pathogenic mechanisms of asthma are still incompletely understood, due to its heterogeneous nature. However, metabolomics can offer a global view of a biological system, making it a valuable tool for further elucidation of mechanisms and biomarker discovery in asthma.Methods: GC-MS–based metabolomic analysis was conducted for comparison of urine metabolic profiles between asthmatic children (n=30) and healthy controls (n=30).Results: An orthogonal projections to latent structures discriminant–analysis model revealed a clear separation of the asthma and control groups (R2x=0.137, R2y=0.947, Q2=0.82). A total of 20 differential metabolites were identified as discriminant factors, of which eleven were significantly increased and nine decreased in the asthma group compared to the control group. Pathway-enrichment analysis based on these differential metabolites indicated that sphingolipid metabolism, protein biosynthesis, and citric acid cycle were strongly associated with asthma. Among the identified metabolites, 2-hydroxybutanoic acid showed excellent discriminatory performance for distinguishing asthma from healthy controls, with an AUC of 0.969.Conclusion: Our study revealed significant changes in the urine metabolome of asthma patients. Several perturbed pathways (eg, sphingolipid metabolism and citric acid cycle) may be related to asthma pathogenesis, and 2-hydroxybutanoic acid could serve as a potential biomarker for asthma diagnosis.Keywords: asthma, metabolomics, sphingolipid metabolism, citric acid cycle, biomarker

Keywords

• asthma
• metabolomics
• sphingolipid metabolism
• citric acid cycle
• biomarker.