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Allergy Asthma Immunol Res. 2018 Nov;10(6):628-647. doi: 10.4168/aair.2018.10.6.628.

Obesity-Associated Metabolic Signatures Correlate to Clinical and Inflammatory Profiles of Asthma: A Pilot Study.

Author information

1
Pneumology Group, Department of Integrated Traditional Chinese and Western Medicine, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, China.
2
Pneumology Group, Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, Chengdu, China.
3
Department of Integrated Traditional Chinese and Western Medicine, Xinqiao Hospital, Third Military University, Chongqing, China.
4
Center for Asthma and Respiratory Diseases, Department of Respiratory and Sleep Medicine, John Hunter Hospital, Hunter Medical Research Institute, University of Newcastle, New Lambton, NSW, Australia.
5
Department of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, China. wcums-respiration@hotmail.com.

Abstract

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.

KEYWORDS:

Asthma; endotype; metabolomics; obese asthma; obesity

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