Serum metabolomics reveals pathways and biomarkers associated with asthma pathogenesis

Summary Background Asthma is a chronic inflammatory disease caused by complex interactions of genetic, epigenetic, and environmental factors. For this reason, new approaches are required to clarify the pathogenesis of asthma by systemic review. Objective We applied a 1H‐NMR metabolomics approach to...

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Veröffentlicht in:Clinical and experimental allergy 2013-04, Vol.43 (4), p.425-433
Hauptverfasser: Jung, J., Kim, S.-H., Lee, H.-S., Choi, G. S., Jung, Y.-S., Ryu, D. H., Park, H.-S., Hwang, G.-S.
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Sprache:eng
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Zusammenfassung:Summary Background Asthma is a chronic inflammatory disease caused by complex interactions of genetic, epigenetic, and environmental factors. For this reason, new approaches are required to clarify the pathogenesis of asthma by systemic review. Objective We applied a 1H‐NMR metabolomics approach to investigate the altered metabolic pattern in sera from patients with asthma and sought to identify the mechanism underlying asthma and potential biomarkers. Method A global profile of sera from patients with asthma (n = 39) and controls (n = 26) was generated using 1H‐NMR spectroscopy coupled with multivariate statistical analysis. Endogenous metabolites in serum were rapidly measured using the target‐profiling procedure. Results Multivariate statistical analysis showed a clear distinction between patients with asthma and healthy subjects. Sera of asthma patients were characterized by increased levels of methionine, glutamine, and histidine and by decreased levels of formate, methanol, acetate, choline, O‐phosphocholine, arginine, and glucose. The metabolites detected in the sera of patients with asthma are involved in hypermethylation, response to hypoxia, and immune reaction. Furthermore, the levels of serum metabolites from patients with asthma correlated with asthma severity; in particular, lipid metabolism was altered in patients with lower forced expiratory volume in 1 s percentage (FEV1%) predicted values. In addition, potential biomarkers showed strong predictive power in ROC analysis, and the presence of asthma in external validation models was predicted with high accuracy (90.9% for asthma and 100% for control subjects). Conclusion & Clinical Relevance These data showed that 1H‐NMR‐based metabolite profiling of serum may be useful for the effective diagnosis of asthma and a further understanding of its pathogenesis.
ISSN:0954-7894
1365-2222
DOI:10.1111/cea.12089