Aberrant mucin expression and keratinization distinguishing severe from mild asthma revealed by interpretable machine learning
Sagar L. Kale, Augusta Vincent, Mark A. Ross, Isha Mehta, Michael J. Calderon, Richard P. Ramonell, Himanshu Setya, Jessica C. McCreary-Partyka, Huijuan Yuan, Stephanie A. Christenson, Prescott G. Woodruff, Mario Castro, Kaharu Sumino, Nizar N. Jarjour, Loren C. Denlinger, Benjamin Gaston, Eugene R. Bleecker, Deborah A. Meyers, Wendy C. Moore, Elliot Israel, Bruce D. Levy, David Mauger, Serpil Erzurum, Anthony Newbrough, Taylor J. Nee, Prabir Ray, Claudette M. St. Croix, Sally E. Wenzel, Jishnu Das, Anuradha Ray, Marc C. Gauthier
Sagar L. Kale, Augusta Vincent, Mark A. Ross, Isha Mehta, Michael J. Calderon, Richard P. Ramonell, Himanshu Setya, Jessica C. McCreary-Partyka, Huijuan Yuan, Stephanie A. Christenson, Prescott G. Woodruff, Mario Castro, Kaharu Sumino, Nizar N. Jarjour, Loren C. Denlinger, Benjamin Gaston, Eugene R. Bleecker, Deborah A. Meyers, Wendy C. Moore, Elliot Israel, Bruce D. Levy, David Mauger, Serpil Erzurum, Anthony Newbrough, Taylor J. Nee, Prabir Ray, Claudette M. St. Croix, Sally E. Wenzel, Jishnu Das, Anuradha Ray, Marc C. Gauthier
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Research Article Immunology Pulmonology

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

Abstract

Type 2 (T2) immune cells dominate the airways of patients with mild-moderate asthma (MMA) 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 patients with SA and MMA would reveal molecular signatures associated with more severe disease in the context of a complex immune response. Using our 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 2 separate asthma cohorts. Imaging of endobronchial biopsies revealed significantly higher KRT16 protein expression in SA compared with MMA that strongly correlated with MUC1 protein expression. Our study identifies dysregulated host-protective and maladaptive repair responses in SA distinguishing from MMA.

Authors

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

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Figure 6

KRT16 protein expression in patients with asthma in the airways of IMSA and relationship between KRT16 expression and lung function in both cohorts.

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KRT16 protein expression in patients with asthma in the airways of IMSA ...
(A) Representative immunofluorescence images of KRT16 protein expression in endobronchial biopsies of patients with SA and MMA in IMSA and (B) quantification as percentage KRT1+ pixel area per total tissue pixel area in the specimens. Data plotted as mean ± SEM and were analyzed by Mann-Whitney U test. Scale bar: 200 μm. (C) FEV1% predicted plotted against expression of KRT16 in RNA-seq data of airway brushings from patients with SA or MMA in the IMSA and SARP cohorts. Spearman’s nonparametric correlation with linear regression for all asthma (black with 95% CI) and severity specific linear regression lines (blue in MMA, red in SA) shown.