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Background <p>Despite substantial clinical and biological heterogeneity, asthma severity is often classified by treatment intensity, which may inadequately reflect underlying pathobiology. We aimed to characterize plasma metabolomic profiles associated with treatment-defined severity among patients with clinically well-controlled asthma receiving guidance-based inhaled corticosteroid (ICS) therapy.</p> Methods <p>In this prospective cross-sectional study, patients with well-controlled asthma, defined by Asthma Control Test scores &gt; 20 and consistent ICS use without recent exacerbations, were enrolled. Plasma samples were analyzed using proton nuclear magnetic resonance spectroscopy and liquid chromatography–mass spectrometry. After asthma severity was defined by ICS dose requirement, metabolomic differences were evaluated between severe and non-severe asthma. The significant metabolites were identified through elastic net–assisted variable selection and Firth’s penalized logistic regression adjusting for clinical covariates. Probabilistic relationships among these metabolites and severity were further explored using Bayesian network modeling.</p> Results <p>Fifty-five patients were included. Lactate and pyruvate levels were significantly elevated in the severe asthma group. In multivariable analyses adjusting for clinical covariates, pyruvate (adjusted odds ratio (aOR) = 10.239 [95% CI = 1.320–19480.301], P-value = 0.025) and dimethylamine (aOR = 12.693 [95% CI = 1.292–628.175], P-value = 0.028) were associated with treatment-defined severity. Bayesian network analysis further supported the direct probabilistic associations of these metabolites with asthma severity. Subgroup analyses confirmed consistent trends across clinical strata, suggesting that distinct metabolic states may underlie higher ICS requirements despite stable symptom control.</p> Conclusion <p>In clinically stable asthma, elevated pyruvate and dimethylamine were associated with greater ICS requirements, suggesting that metabolomic profiling may aid in refining endotypes and personalizing anti-inflammatory therapy beyond symptom-based assessment.</p>

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Plasma metabolomic signatures associated with inhaled corticosteroid requirements in clinically stable asthma: a prospective cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月26日

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  • Hyun Woo Lee,
  • Young Jin Pyung,
  • Sohee Oh,
  • Jung-Kyu Lee,
  • Eun Young Heo,
  • Cheol-Heui Yun,
  • Deog Kyeom Kim

摘要

Background

Despite substantial clinical and biological heterogeneity, asthma severity is often classified by treatment intensity, which may inadequately reflect underlying pathobiology. We aimed to characterize plasma metabolomic profiles associated with treatment-defined severity among patients with clinically well-controlled asthma receiving guidance-based inhaled corticosteroid (ICS) therapy.

Methods

In this prospective cross-sectional study, patients with well-controlled asthma, defined by Asthma Control Test scores > 20 and consistent ICS use without recent exacerbations, were enrolled. Plasma samples were analyzed using proton nuclear magnetic resonance spectroscopy and liquid chromatography–mass spectrometry. After asthma severity was defined by ICS dose requirement, metabolomic differences were evaluated between severe and non-severe asthma. The significant metabolites were identified through elastic net–assisted variable selection and Firth’s penalized logistic regression adjusting for clinical covariates. Probabilistic relationships among these metabolites and severity were further explored using Bayesian network modeling.

Results

Fifty-five patients were included. Lactate and pyruvate levels were significantly elevated in the severe asthma group. In multivariable analyses adjusting for clinical covariates, pyruvate (adjusted odds ratio (aOR) = 10.239 [95% CI = 1.320–19480.301], P-value = 0.025) and dimethylamine (aOR = 12.693 [95% CI = 1.292–628.175], P-value = 0.028) were associated with treatment-defined severity. Bayesian network analysis further supported the direct probabilistic associations of these metabolites with asthma severity. Subgroup analyses confirmed consistent trends across clinical strata, suggesting that distinct metabolic states may underlie higher ICS requirements despite stable symptom control.

Conclusion

In clinically stable asthma, elevated pyruvate and dimethylamine were associated with greater ICS requirements, suggesting that metabolomic profiling may aid in refining endotypes and personalizing anti-inflammatory therapy beyond symptom-based assessment.