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Asthma is a chronic pulmonary condition involving inflammation of the airways, hyper-reactivity, and reversible obstruction of the airways. This condition can significantly impact a person's quality of life, making breathing difficult and leading to distressing symptoms.
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Asthma is a chronic respiratory condition for which new therapeutic avenues, including anti-inflammatory drugs like mast cell stabilizers and anti-IgE treatments, continue to be developed.
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Machine learning implicates the IL-18 signaling axis in severe asthma.

Matthew J Camiolo1,2, Xiuxia Zhou3, Qi Wei3

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|September 30, 2021
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Summary

Researchers identified a specific gene expression pattern in severe asthma patients with poor lung function. This pattern, linked to inflammation and specific gene activation, points to Interleukin-18 Receptor 1 (IL18R1) as a potential driver of severe asthma.

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Area of Science:

  • Pulmonary Medicine
  • Genomics
  • Immunology

Background:

  • Asthma exhibits significant heterogeneity, complicating treatment strategies.
  • Previous studies identified gene expression links to asthma characteristics but generated complex gene lists.
  • The Severe Asthma Research Program (SARP) cohort provides valuable data for understanding asthma subtypes.

Purpose of the Study:

  • To identify distinct transcriptional signatures within the SARP cohort using unsupervised clustering.
  • To uncover novel gene sets and pathways involved in severe asthma pathogenesis.
  • To validate identified biomarkers in an independent cohort.

Main Methods:

  • Unsupervised clustering of bronchial epithelial cell gene expression data from the SARP cohort.
  • Supervised machine learning to identify a predictive gene set for asthma phenotypes.
  • Validation of gene expression and protein levels in lung tissue and external cohorts.

Main Results:

  • A transcriptional signature identified a cluster of exacerbation-prone asthma patients with impaired lung function.
  • This cluster showed mixed inflammation and hallmarks of NF-κB and AP-1 activation despite corticosteroid use.
  • A 31-gene signature accurately classified patients, and IL18R1 (IL-18 Receptor 1) was identified as a key gene negatively associated with lung function.

Conclusions:

  • IL18R1 expression and downstream signaling (NF-κB, AP-1) are implicated in severe asthma pathogenesis.
  • This study highlights an effective approach for gene and pathway discovery in complex diseases like asthma.
  • Targeting IL-18 signaling may offer new therapeutic avenues for severe asthma.