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Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China
BACKGROUND AND OBJECTIVE: Asthma as a chronic heterogeneous disease seriously affects the quality of life. Incorrect identification for its clinical phenotypes lead to a huge waste of medical resources. Metabolomic technique as a novel approach to explore the pathogenesis of diseases have not been u...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174811/ https://www.ncbi.nlm.nih.gov/pubmed/30345296 http://dx.doi.org/10.1155/2018/2860521 |
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author | Pang, Zhiqiang Wang, Guoqiang Wang, Cuizhu Zhang, Weijie Liu, Jinping Wang, Fang |
author_facet | Pang, Zhiqiang Wang, Guoqiang Wang, Cuizhu Zhang, Weijie Liu, Jinping Wang, Fang |
author_sort | Pang, Zhiqiang |
collection | PubMed |
description | BACKGROUND AND OBJECTIVE: Asthma as a chronic heterogeneous disease seriously affects the quality of life. Incorrect identification for its clinical phenotypes lead to a huge waste of medical resources. Metabolomic technique as a novel approach to explore the pathogenesis of diseases have not been used to study asthma based on their clear defined inflammatory phenotypes. This study is aimed to distinguish the divergent metabolic profile in different asthma phenotypes and clarify the pathogenesis of them. METHODS: Participants including eosinophilic asthmatics (EA, n=13), noneosinophilic asthmatics (NEA, n=16), and healthy controls (HC, n=15) were enrolled. A global profile of untargeted serum metabolomics was identified with Ultra Performance Liquid Chromatography–Mass Spectrometry technique. RESULTS: Multivariate analysis was performed and showed a clear distinction between EA, NEA, and HC. A total of 18 different metabolites were recognized between the three groups based on OPLS-DA model and involved in 10 perturbed metabolic pathways. Glycerophospholipid metabolism, retinol metabolism, and sphingolipid metabolism were identified as the most significant changed three pathways (impact > 0.1 and -log(P) > 4) between the phenotypes. CONCLUSIONS: We showed that the different inflammatory phenotypes of asthma involve the immune regulation, energy, and nutrients metabolism. The clarified metabolic profile contributes to understanding the pathophysiology of asthma phenotypes and optimizing the therapeutic strategy against asthma heterogeneity. |
format | Online Article Text |
id | pubmed-6174811 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-61748112018-10-21 Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China Pang, Zhiqiang Wang, Guoqiang Wang, Cuizhu Zhang, Weijie Liu, Jinping Wang, Fang Biomed Res Int Research Article BACKGROUND AND OBJECTIVE: Asthma as a chronic heterogeneous disease seriously affects the quality of life. Incorrect identification for its clinical phenotypes lead to a huge waste of medical resources. Metabolomic technique as a novel approach to explore the pathogenesis of diseases have not been used to study asthma based on their clear defined inflammatory phenotypes. This study is aimed to distinguish the divergent metabolic profile in different asthma phenotypes and clarify the pathogenesis of them. METHODS: Participants including eosinophilic asthmatics (EA, n=13), noneosinophilic asthmatics (NEA, n=16), and healthy controls (HC, n=15) were enrolled. A global profile of untargeted serum metabolomics was identified with Ultra Performance Liquid Chromatography–Mass Spectrometry technique. RESULTS: Multivariate analysis was performed and showed a clear distinction between EA, NEA, and HC. A total of 18 different metabolites were recognized between the three groups based on OPLS-DA model and involved in 10 perturbed metabolic pathways. Glycerophospholipid metabolism, retinol metabolism, and sphingolipid metabolism were identified as the most significant changed three pathways (impact > 0.1 and -log(P) > 4) between the phenotypes. CONCLUSIONS: We showed that the different inflammatory phenotypes of asthma involve the immune regulation, energy, and nutrients metabolism. The clarified metabolic profile contributes to understanding the pathophysiology of asthma phenotypes and optimizing the therapeutic strategy against asthma heterogeneity. Hindawi 2018-09-23 /pmc/articles/PMC6174811/ /pubmed/30345296 http://dx.doi.org/10.1155/2018/2860521 Text en Copyright © 2018 Zhiqiang Pang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Pang, Zhiqiang Wang, Guoqiang Wang, Cuizhu Zhang, Weijie Liu, Jinping Wang, Fang Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title | Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title_full | Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title_fullStr | Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title_full_unstemmed | Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title_short | Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China |
title_sort | serum metabolomics analysis of asthma in different inflammatory phenotypes: a cross-sectional study in northeast china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174811/ https://www.ncbi.nlm.nih.gov/pubmed/30345296 http://dx.doi.org/10.1155/2018/2860521 |
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