Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning

Type 2 (T2) immune cells dominate the airways of mild-moderate asthma (MMA) patients with a more complex Type 1 (T1)-T2 mixed immune response evident in treatment-refractory severe asthma (SA). We hypothesized that comparing the transcriptomes of the airway epithelium of SA and MMA patients would reveal molecular signatures associated with more severe disease in the context of a complex immune response. Using our novel interpretable machine learning tool, SLIDE, meaningful latent factors (context-specific gene co-expression networks) were revealed that distinguished SA from MMA. Unexpectedly, an aberrant high expression of normally host-protective, membrane-tethered and IFN-inducible mucins, MUC1 and MUC4, was identified in SA. Gene networks in the significant latent factors discriminating SA from MMA corresponded to enrichment of a keratinization program in SA airways. Keratinization was marked by increased expression of the stress keratin KRT16, signifying squamous metaplasia suggesting adaptive reprogramming of the airway epithelium in response to chronic stress. These mucins and KRT16 were inversely associated with lung function in two separate asthma cohorts. Imaging of endobronchial biopsies revealed significantly higher KRT16 protein expression in SA compared to MMA that strongly correlated with MUC1 protein expression. Our study identifies dysregulated host-protective and maladaptive repair responses in SA distinguishing from MMA.

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Publication Details

Journal
JCI Insight
Published
2026-07-30
DOI
https://doi.org/10.1172/jci.insight.202442
Primary Topic
Asthma and respiratory diseases
Type
article
Field-Weighted Citation Impact
0.00

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article

Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning

Nizar N. Jarjour, Stephanie A. Christenson, Wendy C. Moore, Isha Mehta et al.
JCI Insight
Asthma and respiratory diseases
article

Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning

Nizar N. Jarjour, Stephanie A. Christenson, Wendy C. Moore, Isha Mehta, Mario Castro, Claudette M. St. Croix, Anuradha Ray, Marc Gauthier, Elliot Israel, Bruce David Levy, J.C. McCreary-Partyka, Deborah A. Meyers, Huijuan Yuan, Prescott G. Woodruff, Prabir Ray, Jishnu Das, Anthony Newbrough, Taylor Nee, Sagar L. Kale, Serpil Erzurum, Eugene R. Bleecker, Loren C. Denlinger, Mark A. Ross, Richard P. Ramonell, Himanshu Setya, Kaharu Sumino, Augusta M. Vincent, Benjamin Gaston, Sally E. Wenzel, Michael J. Calderon, David Mauger
article en

Abstract

Type 2 (T2) immune cells dominate the airways of mild-moderate asthma (MMA) patients with a more complex Type 1 (T1)-T2 mixed immune response evident in treatment-refractory severe asthma (SA). We hypothesized that comparing the transcriptomes of the airway epithelium of SA and MMA patients would reveal molecular signatures associated with more severe disease in the context of a complex immune response. Using our novel interpretable machine learning tool, SLIDE, meaningful latent factors (context-specific gene co-expression networks) were revealed that distinguished SA from MMA. Unexpectedly, an aberrant high expression of normally host-protective, membrane-tethered and IFN-inducible mucins, MUC1 and MUC4, was identified in SA. Gene networks in the significant latent factors discriminating SA from MMA corresponded to enrichment of a keratinization program in SA airways. Keratinization was marked by increased expression of the stress keratin KRT16, signifying squamous metaplasia suggesting adaptive reprogramming of the airway epithelium in response to chronic stress. These mucins and KRT16 were inversely associated with lung function in two separate asthma cohorts. Imaging of endobronchial biopsies revealed significantly higher KRT16 protein expression in SA compared to MMA that strongly correlated with MUC1 protein expression. Our study identifies dysregulated host-protective and maladaptive repair responses in SA distinguishing from MMA.

JCI Insight
Brigham and Women's Hospital (US), Pennsylvania State University (US), University of Wisconsin–Madison (US), University of Arizona (US), University of Kansas (US), University of Pittsburgh (US), Washington University in St. Louis (US), Riley Hospital for Children (US), Cleveland Clinic Lerner College of Medicine (US), Pulmonary and Allergy Associates (US), Wake Forest University (US), Indiana University – Purdue University Indianapolis (US)
National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Allergy and Infectious Diseases
Reduced inequalities
Openalex Percentile: Top 10%
Asthma and respiratory diseases
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