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논문 기본 정보

자료유형
학술저널
저자정보
YING LIU (Shandong University) Jing Zheng (Third Military University) Hong-Ping Zhang (Sichuan University) Xin Zhang (Sichuan University) Lei Wang (Sichuan University) Lisa Wood (University of Newcastle) Gang Wang (Sichuan University)
저널정보
대한천식알레르기학회(구 대한알레르기학회) Allergy, Asthma & Immunology Research Allergy, Asthma & Immunology Research Vol.10 No.6
발행연도
2018.1
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628 - 647 (20page)

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Purpose: Obesity is associated with metabolic dysregulation, but the underlying metabolic signatures involving clinical and inflammatory profiles of obese asthma are largely unexplored. We aimed at identifying the metabolic signatures of obese asthma. Methods: Eligible subjects with obese (n = 11) and lean (n = 22) asthma underwent body composition and clinical assessment, sputum induction, and blood sampling. Sputum supernatant was assessed for interleukin (IL)-1β, -4, -5, -6, -13, and tumor necrosis factor (TNF)-α, and serum was detected for leptin, adiponectin and C-reactive protein. Untargeted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS)-based metabolic profiles in sputum, serum and peripheral blood monocular cells (PBMCs) were analyzed by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) and pathway topology enrichment analysis. The differential metabolites were further validated by correlation analysis with body composition, and clinical and inflammatory profiles. Results: Body composition, asthma control, and the levels of IL-1β, -4, -13, leptin and adiponectin in obese asthmatics were significantly different from those in lean asthmatics. OPLS-DA analysis revealed 28 differential metabolites that distinguished obese from lean asthmatic subjects. The validation analysis identified 18 potential metabolic signatures (11 in sputum, 4 in serum and 2 in PBMCs) of obese asthmatics. Pathway topology enrichment analysis revealed that cyanoamino acid metabolism, caffeine metabolism, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, pentose phosphate pathway in sputum, and glyoxylate and dicarboxylate metabolism, glycerolipid metabolism and pentose phosphate pathway in serum are suggested to be significant pathways related to obese asthma. Conclusions: GC-TOF-MS-based metabolomics indicates obese asthma is characterized by a metabolic profile different from lean asthma. The potential metabolic signatures indicated novel immune-metabolic mechanisms in obese asthma with providing more phenotypic and therapeutic implications, which needs further replication and validation.

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