The molecular mechanisms responsible for the "atopic march" of allergic skin disease to allergic airway disease are incompletely understood. Secreted phospholipase A2 group X (sPLA2-X) is implicated in human asthma and modulates airway hyperresponsiveness (AHR) and inflammation in murine models of allergic asthma. We developed a complete proteolytic allergen model of dermal sensitization followed by airway challenge to mimic the "atopic march" and examined the role of sPLA2-X in regulating peripheral allergen sensitization, AHR, and airway inflammation. Pla2g10-/- mice receiving both house dust mite (HDM) peripheral sensitization and airway challenge had attenuated AHR relative to WT mice and lower airway eosinophils. Transgenic C57BL/6 hPLA2G10 mice (only expressing the human sPLA2-X gene) receiving treatment with a small molecule inhibitor of sPLA2-X (ROC0929) during the dermal sensitization phase demonstrated attenuated AHR and a reduction HDM-specific tissue-resident memory CD4+ T cells in the lung. Thus, sPLA2-X acts as an endogenous adjuvant to facilitate allergic sensitization in the periphery, which leads to AHR and airway inflammation following inhalation of the allergen. These results provide proof of concept that inhibition of sensitization in the periphery with a sPLA2-X inhibitor modulates subsequent allergen-induced airway dysfunction.

Rationale Thickening of the basement membrane zone (BMZ) has often been identified in airway biopsies of individuals with asthma, but the relationship of BMZ thickness with airway dysfunction and inflammation is incompletely understood. Objectives Characterize the relationship between BMZ thickness and airway physiology, immune cell infiltration, and airway gene expression. Methods We used design-based stereology to measure BMZ thickness in endobronchial biopsy samples obtained from 10 healthy control subjects and 31 individuals with asthma not receiving asthma-directed anti-inflammatory therapies (only using as needed albuterol for the study period). BMZ thickness was correlated with measures of airway physiology, sputum inflammatory markers, airway wall immunopathology, and gene expression from airway epithelial brushings. Results Individuals with asthma had a significantly thicker BMZ relative to healthy controls. BMZ thickness was negatively correlated with age and positively correlated with higher baseline lung function (FVC), mast cell (MC) infiltration of the airway epithelial compartment, and expression of type 2 (T2) inflammatory genes in the airway. Thickening of the BMZ was not significantly associated with the bronchodilator response, direct airway hyperresponsiveness (AHR) to methacholine, indirect AHR in the form of exercise-induced bronchoconstriction, T1 or T3 inflammation, or airway eosinophilia. Conclusions MC infiltration of the airway epithelial compartment and T2 inflammation are significantly associated with a thickened BMZ in asthma.

RATIONALE:The mechanisms responsible for promoting allergic asthma remain incompletely understood, particularly the role of the crosstalk between innate immune cells and airway epithelium in coordinating the response to inhaled allergen. OBJECTIVE:Identify transcriptional responses to allergen exposure in human airway samples and ex vivo airway epithelial cell (AEC) model systems. METHODS:RNA-sequencing (RNA-seq) analyses were performed on induced sputum samples from individuals with allergic asthma that underwent inhaled allergen challenge. We integrated these results with a single cell RNA-seq (scRNA-seq) data set of epithelial brushings obtained before and after segmental allergen challenge (SAC). Finally, we performed RNA-seq analyses of primary AECs following house dust mite exposure in the context of priming with IL-13 (simulating a type-2 (T2) environment) or IFN-γ (simulating a type-1 (T1) environment). RESULTS:Distinct kinetic patterns were identified in the diverse inflammatory response to allergen in induced sputum samples, including activation of mast cell (MC) and AEC genes. Using the SAC scRNA-seq data set, we demonstrated that MCs modestly increase in the airways following SAC and are a key source of IL5 and IL18 expression. In contrast, basophils are near absent in the airways at baseline but are present in the airways following allergen challenge and are key sources of IL4 and IL13 expression. RNA-seq analyses of AECs in ex vivo culture demonstrate a core AEC allergen response enriched in genes associated with glycolysis and cadherin binding but is significantly altered in the presence of either IL-13 or IFN-γ exposure. Finally, we integrate these data sets to demonstrate that basophil chemotaxis to the airways in allergic asthma is partly mediated by epithelial-derived CCL26. CONCLUSION:Allergen challenge promotes diverse pro-inflammatory transcriptional responses in the airways, and MCs, basophils, and AECs play distinct but critical roles in coordinating this response. However, airway responses to allergen may vary considerably based on the baseline airway inflammatory endotype.

Rationale: The epithelial compartment of the airway wall is infiltrated by eosinophils (EOS) in individuals with asthma, and the density of intraepithelial EOS (EOSIE) is associated with airway dysfunction (Al-Shaikhly ERJ 2022) and distinct type-2 (T2) and non-T2 mechanisms of airway inflammation. IL-33 is an epithelial-derived alarmin with pleotropic function that has been implicated in asthma and we have previously identified significant associations between the density of EOSIE and expression of the IL-33 receptor (IL1RL1). We subsequently have demonstrated that IL-33 stimulation of human blood EOS promotes both T2 (IL13) and non-T2 (IFNG) gene expression (Murphy AJRCCM 2023). Given that EOSIE exist in immediate proximity to airway epithelial cells (AECs) within the epithelial compartment, we aimed to study to effect of IL-33 on bidirectional communication between AECs and EOS. Methods: EOS were isolated from the peripheral blood of 3 human donors with allergic disease and cocultured with primary AECs obtained from 4 healthy adult donors that were fully differentiated at air-liquid interface. IL-33 (10 ng/mL) or a media control was added to the coculture system for 24 hours. RNA was isolated from both AECs and EOS, which underwent bulk RNA-sequencing (RNA-seq) analysis (Figure 1A). Results: First, we evaluated the effect of IL-33 stimulation on EOS cocultured with AECs, which identified 324 DEGs (FDR <0.25) and included increased EOS expression of THBS1, CCL2, CXCR4, and SIGLEC10 (Figure 1B). These DEGs were enriched for pathways related to leukocyte migration, cell-cell adhesion, degranulation, IL-4 and IL-13 signaling, and IFN-γ signaling. Next, we compared the effect of the presence of EOS on the AEC response to IL-33, which identified 327 DEGs (FDR <0.25) and included increased AEC expression of PTGES, IL13RA1, TNFSF10, and ORMDL3 (Figure 1C). These DEGs were enriched for pathways related to lipid metabolism as well as cholesterol, steroid biosynthesis, and glycosaminoglycan biosynthesis. Conclusions: EOS transcriptional programs are significantly altered following IL-33 stimulation in the presence of AECs, including increased expression of pro-inflammatory genes implicated in both T2- and non-T2 mechanisms of inflammation in asthma. Similarly, AEC transcriptional responses to IL-33 are significantly altered upon exposure to EOS, including increased expression of prostaglandin E synthase (which generates PGE2, an anti-inflammatory lipid mediator in asthma) and ORMDL3 (which promotes eosinophil trafficking to the airways). Overall, our findings suggest that crosstalk between AEC and EOSIE plays a key role in regulating airway inflammation in asthma, particularly following exposures that promote epithelial IL-33 release.

Rationale: Recruited, monocyte-derived macrophages are implicated in asthma and are present in the airways of individuals with asthma but their role in regulating inflammatory responses relevant to asthma remains incompletely understood. Human rhinovirus (RV) infections are key triggers for asthma exacerbations and are classically driven by primary infection of airway epithelial cells (AECs). Here we examine AEC responses to RV infection in the presence of peripheral blood monocytes. Methods: Primary AECs were obtained from children with asthma (n=11) and healthy children (n=10), differentiated at air-liquid interface, and cocultured with monocytes derived from the peripheral blood of a single healthy donor (Figure 1A). After infection with RV serogroup-A16 (RV16) for 48 hours, cells were harvested and RNA isolated for high-throughput transcriptomic analysis. Results: AECs infected with RV16 in the presence or absence of monocytes shared 3458 differentially expressed genes (DEGs) (Figure 1B). This shared response was positively enriched in pathways related to anti-viral response, response to type I and type II interferons, and T cell recruitment, and negatively enriched in pathways associated with ciliary function. RV16-infected AECs cocultured with monocytes showed 1047 distinct DEGs (462 upregulated, 585 downregulated), enriched in pathways related to monocyte trafficking, NK cell cytotoxicity, and regulation of IL-13 production. Finally, 1684 DEGs were distinct to RV16-infected cultured alone (727 upregulated, 957 downregulated) and were enriched in pathways related to IL-15-mediated signaling as well as eosinophil and neutrophil migration. The effects of AEC donor phenotype were small relative to the effects of viral infection and the presence of monocytes. There were no significant differences in RV16 counts in AECs based on the presence or absence of monocytes. Conclusion: There are considerable differences in the epithelial response to viral infection when monocytes are present, several of which are implicated as critical mechanisms of airway inflammation in asthma.

Rationale: The epithelial compartment of the airway wall is uniquely infiltrated by mast cells (MCs) in individuals with asthma, and the density of intraepithelial MCs (MCIE) is associated with airway dysfunction (Altman JCI 2019) and distinct type-2 (T2) and non-T2 mechanisms of inflammation (Murphy AJRCCM 2023). We have further modeled interactions between airway epithelial cells (AECs) and MCs using a coculture system with primary AECs in the apical chamber and MCs in the basolateral compartment, and have found that AECs promote sustained T2 gene expression in MCs. However, this model system has significant limitations in its ability to model the airway epithelial microenvironment, particularly the role of cell-cell contact in regulating intercellular communication. Here we aimed to utilize a novel ex vivo model system that better replicates the airway epithelial microenvironment in asthma. Methods: In the novel model system of MCIE (AEC-MCIE), Laboratory of Allergic Diseases-2 (LAD2) MCs were added to the apical chamber of the transwell system containing primary AECs from a healthy donor before and after transitioning to air-liquid interface (ALI). The AEC-MCIE system was cultured at ALI for 24 days and collected for single cell RNA-sequencing (scRNAseq) using the Chromium Fixed RNA Profiling platform. We simultaneously compared this to our conventional AEC-MC coculture system with AECs from the same donor in the apical chamber and LAD2 MCs in the basolateral compartment (AEC-MCBL, Figure 1A). Results: We were able to successfully identify MC and AEC subpopulations in both model systems (Figure 1B, 1C). We did not identify differences in AEC proportions between the models but did identify differential gene expression (FDR <0.05) within specific cell types between model systems (AEC-MCIE vs. AEC-MCBL). For example, MCs in the AEC-MCIE model demonstrated increased expression of the key inflammatory mediators (SOCS3, CCL4, AREG, CXCR4, and CCL18). Goblet cells from the AEC-MCIE model demonstrated increased expression of genes implicated in asthma, including cytokines (IL18), chemokines (CXCL1, CXCL8), eicosanoid metabolism (ALOX15, PLA2R1), and airway remodeling (TGFB2, TGFB3). Finally, a basal cell cluster in the AEC-MCIE model had lower expression of interferon-regulated genes (IFI6, IFIT1, RIGI, OAS1). Conclusions: We are successfully able to measure MC and AEC transcriptional patterns at single cell resolution in an ex vivo model system that better replicates the airway epithelial microenvironment. Preliminary results suggest that MCIE significantly alter epithelial transcriptional patterns in a manner relevant to asthma.

BACKGROUND:Mast cells (MCs) within the airway epithelium in asthma are closely related to airway dysfunction, but cross talk between airway epithelial cells (AECs) and MCs in asthma remains incompletely understood. Human rhinovirus (RV) infections are key triggers for asthma progression, and AECs from individuals with asthma may have dysregulated antiviral responses. OBJECTIVE:We utilized primary AECs in an ex vivo coculture model system to examine cross talk between AECs and MCs after epithelial rhinovirus infection. METHODS:Primary AECs were obtained from 11 children with asthma and 10 healthy children, differentiated at air-liquid interface, and cultured in the presence of laboratory of allergic diseases 2 (LAD2) MCs. AECs were infected with rhinovirus serogroup A 16 (RV16) for 48 hours. RNA isolated from both AECs and MCs underwent RNA sequencing. Direct effects of epithelial-derived interferons on LAD2 MCs were examined by real-time quantitative PCR. RESULTS:MCs increased expression of proinflammatory and antiviral genes in AECs. AECs demonstrated a robust antiviral response after RV16 infection that resulted in significant changes in MC gene expression, including upregulation of genes involved in antiviral responses, leukocyte activation, and type 2 inflammation. Subsequent ex vivo modeling demonstrated that IFN-β induces MC type 2 gene expression. The effects of AEC donor phenotype were small relative to the effects of viral infection and the presence of MCs. CONCLUSIONS:There is significant cross talk between AECs and MCs, which are present in the epithelium in asthma. Epithelial-derived interferons not only play a role in viral suppression but also further alter MC immune responses including specific type 2 genes.

RATIONALE Indirect airway hyperresponsiveness (AHR) is a highly specific feature of asthma but the underlying mechanisms responsible for driving indirect AHR remain incompletely understood. OBJECTIVES Identify differences in gene expression in epithelial brushings obtained from individuals with asthma who were characterized for indirect AHR in the form of exercise-induced bronchoconstriction (EIB). METHODS RNA-sequencing (RNA-seq) analysis was performed on epithelial brushings obtained from asthmatic individuals with (n=11) and without EIB (n = 9). Differentially expressed genes (DEGs) were correlated with measures of airway physiology, sputum inflammatory markers, and airway wall immunopathology. Based on these relationships, we examined the effects of primary airway epithelial cells (AECs) and specific epithelial-derived cytokines on both mast cells (MCs) and eosinophils (EOS). RESULTS We identified 120 DEGs between individuals with and without EIB. Network analyses suggested critical roles for IL-33-, IL-18-, and IFN--related signaling amongst these DEGs. IL1RL1 expression was positively correlated with the density of MCs in the epithelial compartment and IL1RL1, IL18R1, and IFNG were positively correlated with the density of intraepithelial EOS. Subsequent ex vivo modeling demonstrated that AECs promote sustained T2 inflammation in MCs and enhance IL-33-induced T2 gene expression. Further, EOS increase expression of IFNG and IL13 in response to both IL-18 and IL-33 as well as exposure to AECs. CONCLUSIONS Circuits involving epithelial interactions with MCs and EOS are closely associated with indirect AHR. Ex vivo modeling indicates that epithelial-dependent regulation of these innate cells may be critical in indirect AHR and modulating T2 and non-T2 inflammation in asthma.

Accurate phenotypic and endotypic characterization of asthma is critical to inform treatment decisions, particularly for patients with eosinophilic or type-2 (T2) high asthma who are more responsive to inhaled corticosteroids and are candidates for biologic therapies targeting T2 inflammation.1 Current biomarkers of T2 inflammation, including blood and sputum eosinophilia, and fractional exhaled nitric oxide (FENO), have limitations. Thus there is an unmet need for additional, more accurate biomarkers and to understand the relationship between such biomarkers and airway immunopathology.1 Periostin, a matrix protein secreted by epithelial and stromal cells and a biomarker of T2 inflammation in clinical research, can be measured in sputum and has been associated with the T2-high endotype and persistent airflow obstruction in patients with severe asthma.2 The relationship of sputum periostin to airway dysfunction in the form of airway hyperresponsiveness (AHR) and airway inflammation was examined in individuals with mild-to-moderate asthma who were not using controller therapies. In this cross-sectional assessment, individuals with and without asthma were recruited based on rigorous diagnostic testing, with further characterization of participants for endogenous AHR in the form of exercise-induced bronchoconstriction (EIB).3, 4 Briefly, individuals underwent methacholine challenge testing, dry air exercise challenge, induced sputum collection and research bronchoscopy. Periostin levels in induced sputum supernatant were measured at a 1:2 dilution using a sandwich ELISA assay (Genentech, Inc., South San Francisco, CA; lower limit of quantitation [LLOQ]: 37 pg/mL).5 We assessed induced sputum cell differentials and expression of selected genes (IL4, IL5, IL13, ARG2, INFG, TPSAB1, CMA1, and CPA3) by qPCR. Individuals were categorized for T2 inflammation using the sputum Type-2 Gene Mean (T2GM), with T2-high asthma defined by a T2GM ≥2 standard deviations above that of healthy controls within the study population.3, 4, 6 Endobronchial biopsies were assessed by immunohistochemistry and quantified by design-based stereology, to precisely quantify the numerical density of mast cells and eosinophils per reference volume within different compartments of the airway wall.3, 4 Nonparametric statistics were used. Correlations between continuous variables were assessed using Spearman's rho (r). Forty-three study participants had sputum periostin measured, and all but two had periostin levels above the LLOQ including 10 healthy controls (median age [IQR], 24.5 [23–34.3]; % females, 80%) and 33 individuals with asthma (median [IQR] for age, 23 [21–28.5]; FEV1% predicted, 92 [83–95] and FEV1/FVC ratio, 0.77 [0.71–0.84]; % females, 72.7%). There was no difference in sputum periostin concentration between healthy controls and subjects with asthma (median [IQR], 0.30 [0.09–0.69] vs. 0.18 [0.06–0.45]; p = 0.51) and there was no significant association between sputum periostin levels and baseline lung function or the severity of AHR to methacholine (Table 1). There was also no association between sputum periostin concentration and baseline lung function amongst individuals with asthma (Table 1). Amongst individuals with asthma, 20 (60.6%) had a positive exercise challenge test (EIB+). Sputum periostin concentration was similar between EIB− and EIB+ asthmatics (median [IQR], 0.14 [0.06 to 0.23] vs. 0.20 [0.12 to 0.74]; p = 0.16) and did not correlate with the severity of endogenous AHR (Table 1). Airway T2 gene expression was available from 31 individuals, with 14/31 classified as T2-high according to their T2GM. Our prior analysis of this cohort found that the T2GM and individual T2 cytokines correlate with the severity of AHR.3, 4 Here, sputum periostin was non-significantly higher amongst T2-high individuals, across the full study population (median [IQR], 0.36 [0.18–0.68] vs. 0.19 [0.06–0.59], p = 0.14) and after restricting analysis to individuals with asthma (median [IQR], 0.36 [0.18–0.68] vs. 0.15 [0.05–0.38], p = 0.08). Further correlation analyses revealed a significant association between sputum periostin and the sputum T2GM (Table 1). Of the genes included in the T2GM, sputum periostin was most strongly correlated with the expression of IL4 and IL5, and to a lesser extent with IL13 in induced sputum cells (Table 1). Conversely, neither the expression of ARG2 nor INFG in sputum correlated with sputum periostin concentration (Table 1). Subjects with ‘eosinophilic asthma’, defined by sputum eosinophil percentage ≥3%, had a higher sputum periostin concentration compared to non-eosinophilic asthma (median [IQR], 0.50 [0.20–1.09] vs. 0.16 [0.06–0.37], p = 0.03). Sputum periostin differentiated eosinophilic from non-eosinophilic asthma with an area under the ROC curve of 0.8 (95% CI, 0.63–0.97; p = 0.04). Across the full study population and amongst the individuals with asthma, sputum periostin correlated significantly with sputum eosinophil concentration (Table 1). We also further refined the relationship between sputum periostin and the precise location of eosinophils in the airway wall, revealing that sputum periostin concentration correlated with the density of subepithelial eosinophils, but not intraepithelial eosinophils (Table 1). Prior analysis of this cohort revealed that intraepithelial mast cell density and the expression of TPSAB1 and CPA3 in induced sputum were associated with the severity of EIB.4 No association was identified between sputum periostin and the density of mast cells in different compartments of the airway wall. However, expression of genes encoding key mast cell proteases implicated in T2 inflammation (TPSAB1, CPA3) correlated with sputum periostin concentration across the full study population (Table 1). From this pilot assessment, we show that sputum periostin is positively correlated with airway T2 gene expression and airway eosinophilia, but did not differ between individuals with and without asthma and was not associated with reduced lung function or with non-specific AHR to methacholine challenge. As the precise location of eosinophils and mast cells in the airway wall was characterized in this cohort, we demonstrated that sputum periostin correlated with the overall eosinophil density in the airway wall and eosinophils in the subepithelial compartment, the eosinophil location that is most closely associated with T2 airway inflammation.3 However, sputum periostin was not related to mast cells or eosinophils within the epithelial compartment, which are increased in subjects with asthma and tightly associated with airway dysfunction in the form of endogenous AHR, the most specific form of AHR in asthma.3, 4 Periostin has been proposed as a potential biomarker for asthma and for identifying individuals with T2 inflammation. However, serum periostin levels do not reliably differentiate adults with asthma from healthy controls7 but are consistently associated with classic peripheral T2 biomarkers2 and may predict responsiveness to T2-directed biologic therapies.1 Studies evaluating airway periostin levels in induced sputum have been limited with mixed results. One study found similar levels between individuals with mild-to-moderate asthma and healthy controls8 and another identified significantly higher sputum periostin levels in individuals with severe asthma.9 No prior studies have evaluated the details of the components of airway dysfunction with airway periostin levels, but serum periostin levels have been associated with AHR in children, particularly endogenous AHR.10 In children, asthma tends to be T2 predominant, so there may be less discordance between T2 inflammation and AHR, and periostin levels vary widely with age in children.11 We used a direct assessment of T2 gene expression in the airways (rather than peripheral biomarkers such as blood eosinophils or FENO) to demonstrate an association between the level of periostin in induced sputum and the T2 endotype in a well-defined cohort of individuals with mild-to-moderate asthma who were not using controller therapy at the time of assessment. We present evidence that sputum periostin is more closely associated with the T2 endotype and less of a marker of asthma or airway dysfunction, with additional details shown about the relationship of periostin to the precise location of mast cells and eosinophils in the airway wall. As few studies have characterized airway physiology and tissue infiltration with immune cells in relation to airway levels of periostin amongst individuals with asthma, these results add to the growing body of evidence of discordance between T2 biomarkers and airway dysfunction in the form of AHR in asthma. Taha Al-Shaikhly: Data curation (equal); formal analysis (lead); investigation (equal); writing – original draft (lead); writing – review and editing (equal). Ryan C. Murphy: Data curation (equal); formal analysis (equal); validation (equal); writing – original draft (equal); writing – review and editing (equal). Ying Lai: Investigation (equal); writing – review and editing (equal). Charles W. Frevert: Conceptualization (equal); formal analysis (equal); investigation (equal); methodology (equal); writing – review and editing (equal). Jason S. Debley: Formal analysis (equal); investigation (equal); validation (equal); writing – review and editing (equal). Steven F. Ziegler: Funding acquisition (equal); writing – review and editing (equal). Kit Wong: Formal analysis (equal); writing – review and editing (equal). Guiquan Jia: Formal analysis (equal); investigation (equal); writing – review and editing (equal). Cecile T. J. Holweg: Formal analysis (equal); writing – review and editing (equal). Michael C. Peters: Formal analysis (equal); investigation (equal); writing – review and editing (equal). Teal S. Hallstrand: Conceptualization (lead); data curation (equal); formal analysis (equal); funding acquisition (lead); investigation (lead); methodology (lead); project administration (lead); resources (lead); supervision (lead); validation (lead); writing – original draft (equal); writing – review and editing (equal). The work was supported by the National Institutes of Health (grant numbers: U19AI125378, K24AI130263 and R01HL153979). Taha Al-Shaikhly has a patent MicroRNAs as Predictors of Response to Anti-IgE Therapies in Chronic Spontaneous Urticaria pending. Charles W. Frevert, Jason S. Debley, Steven F. Ziegler, and Teal S. Hallstrand report grants from the National Institute of Health during the conduct of the study. Michael C. Peters reports grants from National Institute of Health-NHLBI, Boeringer-Ingelheim, Astrazeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi-Genzyme-Regeneron, and Teva, outside the submitted work. Kit Wong, Guiquan Jia, and Cecile T. J. Holweg are employees of Genentech. All other authors declared no conflict of interest. This study was performed in accordance with the Declaration of Helsinki. This human study was approved by Institutional Review Board at the University of Washington (Seattle, Washington). All adult participants provided written informed consent to participate in this study. Data available on request from the authors. Visual Abstract Sputum periostin is a biomarker of type 2 inflammation but not airway dysfunction in asthma Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Innate immune cell populations are critical in asthma with different functional characteristics based on tissue location, which has amplified the importance of characterizing the precise number and location of innate immune populations in murine models of asthma. In this study, we performed premortem intravascular (IV) labeling of leukocytes in mice in two models of asthma to differentiate innate immune cell populations within the IV compartment versus those residing in the lung tissue or airway lumen. We performed spectral flow cytometry analysis of the blood, suspensions of digested lung tissue, and bronchoalveolar lavage fluid. We discovered that IV labeled leukocytes do not contaminate analysis of bronchoalveolar lavage fluid but represent a significant proportion of cells in digested lung tissue. Exclusion of IV leukocytes significantly improved the accuracy of the assessments of myeloid cells in the lung tissue and provided important insights into ongoing trafficking in both eosinophilic and neutrophilic asthma models.

AllergyVolume 78, Issue 2 p. 547-549 LETTER Identification of mast cell progenitor cells in the airways of individuals with allergic asthma Ryan C. Murphy, Ryan C. Murphy orcid.org/0000-0003-0094-0003 Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorYu-Hua Chow, Yu-Hua Chow Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorYing Lai, Ying Lai Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorTaha Al-Shaikhly, Taha Al-Shaikhly Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USA Division of Allergy and Infectious Disease, University of Washington, Seattle, Washington, USASearch for more papers by this authorDaniel H. Petroni, Daniel H. Petroni Division of Allergy and Infectious Disease, University of Washington, Seattle, Washington, USA Seattle Allergy and Asthma Research Institute, Seattle, Washington, USASearch for more papers by this authorMichele Black, Michele Black orcid.org/0000-0003-2330-1140 Department of Immunology, University of Washington, Seattle, Washington, USASearch for more papers by this authorJessica A. Hamerman, Jessica A. Hamerman Department of Immunology, University of Washington, Seattle, Washington, USA Immunology Program, Benaroya Research Institute, Seattle, Washington, USASearch for more papers by this authorAdam Lacy-Hulbert, Adam Lacy-Hulbert Department of Immunology, University of Washington, Seattle, Washington, USA Immunology Program, Benaroya Research Institute, Seattle, Washington, USASearch for more papers by this authorAdrian M. Piliponsky, Adrian M. Piliponsky Seattle Children's Research Institute, Seattle, Washington, USASearch for more papers by this authorTeal S. Hallstrand, Corresponding Author Teal S. Hallstrand [email protected] orcid.org/0000-0002-5059-6872 Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USA Correspondence Teal S. Hallstrand, Division of Pulmonary, Critical Care, and Sleep Medicine, Center for Lung Biology, University of Washington, Box 358052, 850 Republican Street, Seattle, WA 98109-4714, USA. Email: [email protected]Search for more papers by this author Ryan C. Murphy, Ryan C. Murphy orcid.org/0000-0003-0094-0003 Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorYu-Hua Chow, Yu-Hua Chow Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorYing Lai, Ying Lai Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USASearch for more papers by this authorTaha Al-Shaikhly, Taha Al-Shaikhly Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USA Division of Allergy and Infectious Disease, University of Washington, Seattle, Washington, USASearch for more papers by this authorDaniel H. Petroni, Daniel H. Petroni Division of Allergy and Infectious Disease, University of Washington, Seattle, Washington, USA Seattle Allergy and Asthma Research Institute, Seattle, Washington, USASearch for more papers by this authorMichele Black, Michele Black orcid.org/0000-0003-2330-1140 Department of Immunology, University of Washington, Seattle, Washington, USASearch for more papers by this authorJessica A. Hamerman, Jessica A. Hamerman Department of Immunology, University of Washington, Seattle, Washington, USA Immunology Program, Benaroya Research Institute, Seattle, Washington, USASearch for more papers by this authorAdam Lacy-Hulbert, Adam Lacy-Hulbert Department of Immunology, University of Washington, Seattle, Washington, USA Immunology Program, Benaroya Research Institute, Seattle, Washington, USASearch for more papers by this authorAdrian M. Piliponsky, Adrian M. Piliponsky Seattle Children's Research Institute, Seattle, Washington, USASearch for more papers by this authorTeal S. Hallstrand, Corresponding Author Teal S. Hallstrand [email protected] orcid.org/0000-0002-5059-6872 Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington, USA Center for Lung Biology, Department of Medicine, University of Washington, Seattle, Washington, USA Correspondence Teal S. Hallstrand, Division of Pulmonary, Critical Care, and Sleep Medicine, Center for Lung Biology, University of Washington, Box 358052, 850 Republican Street, Seattle, WA 98109-4714, USA. Email: [email protected]Search for more papers by this author First published: 29 August 2022 https://doi.org/10.1111/all.15498Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Supporting Information Filename Description all15498-sup-0001-AppendixS1.docxWord 2007 document , 31.8 KB AppendixS1 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. Volume78, Issue2February 2023Pages 547-549 RelatedInformation

BACKGROUND:Eosinophils are implicated as effector cells in asthma, but the functional implications of the precise location of eosinophils in the airway wall is poorly understood. We aimed to quantify eosinophils in the different compartments of the airway wall and associate these findings with clinical features of asthma and markers of airway inflammation.METHODS:In this cross-sectional study, we utilised design-based stereology to accurately partition the numerical density of eosinophils in both the epithelial compartment and the subepithelial space (airway wall area below the basal lamina including the submucosa) in individuals with and without asthma and related these findings to airway hyperresponsiveness (AHR) and features of airway inflammation.RESULTS:Intraepithelial eosinophils were linked to the presence of asthma and endogenous AHR, the type that is most specific for asthma. In contrast, both intraepithelial and subepithelial eosinophils were associated with type 2 (T2) inflammation, with the strongest association between IL5 expression and intraepithelial eosinophils. Eosinophil infiltration of the airway wall was linked to a specific mast cell phenotype that has been described in asthma. We found that interleukin (IL)-33 and IL-5 additively increased cysteinyl leukotriene (CysLT) production by eosinophils and that the CysLT LTC4 along with IL-33 increased IL13 expression in mast cells and altered their protease profile.CONCLUSIONS:We conclude that intraepithelial eosinophils are associated with endogenous AHR and T2 inflammation and may interact with intraepithelial mast cells via CysLTs to regulate airway inflammation.

The mechanisms responsible for driving endogenous airway hyperresponsiveness (AHR) in the form of exercise-induced bronchoconstriction (EIB) are not fully understood. We examined alterations in airway phospholipid hydrolysis, surfactant degradation, and lipid mediator release in relation to AHR severity and changes induced by exercise challenge. Paired induced sputum ( n = 18) and bronchoalveolar lavage (BAL) fluid ( n = 11) were obtained before and after exercise challenge in asthmatic subjects. Samples were analyzed for phospholipid structure, surfactant function, and levels of eicosanoids and secreted phospholipase A2group 10 (sPLA2-X). A primary epithelial cell culture model was used to model effects of osmotic stress on sPLA2-X. Exercise challenge resulted in increased surfactant degradation, phospholipase activity, and eicosanoid production in sputum samples of all patients. Subjects with EIB had higher levels of surfactant degradation and phospholipase activity in BAL fluid. Higher basal sputum levels of cysteinyl leukotrienes (CysLTs) and prostaglandin D2(PGD2) were associated with direct AHR, and both the postexercise and absolute change in CysLTs and PGD2levels were associated with EIB severity. Surfactant function either was abnormal at baseline or became abnormal after exercise challenge. Baseline levels of sPLA2-X in sputum and the absolute change in amount of sPLA2-X with exercise were positively correlated with EIB severity. Osmotic stress ex vivo resulted in movement of water and release of sPLA2-X to the apical surface. In summary, exercise challenge promotes changes in phospholipid structure and eicosanoid release in asthma, providing two mechanisms that promote bronchoconstriction, particularly in individuals with EIB who have higher basal levels of phospholipid turnover.

Rationale: We recently used quantitative morphometry to precisely partition the quantity of mast cells (MCs) and eosinophils (EOS) to the airway epithelium and submucosa in individuals with and without asthma who were extensively characterized for direct and endogenous airway hyperresponsiveness (AHR) in the form of exercise-induced bronchoconstriction (EIB) and were not using controller therapies at the time of sample collection or phenotypic characterization.These innate immune cells are implicated as effector cells in asthma but their function and communication with the airway epithelium is incompletely understood.Here we perform RNA-sequencing (RNA-seq) analysis of epithelial brushings from this same cohort and correlate epithelial gene expression with intra-epithelial MCs and EOS.Methods: The location and density of MCs and EOS were correlated with AHR and airway type 2 (T2) gene expression.RNA was isolated from epithelial brushings for RNA-seq analysis.Differential gene expression analysis was performed using the Bioconductor package DESeq2.Differentially expressed genes (DEGs) were correlated with the quantity of intra-epithelial MCs and EOS using simple linear regression analysis.Gene interaction network analysis was performed using Ingenuity Pathway Analysis.Results: Intra-epithelial MCs and EOS are correlated with T2 inflammation and endogenous AHR, which is the most specific form of AHR in asthma.We identified 67 DEGs between EIB+ asthmatics and EIB-asthmatics using a false discovery rate of <0.05.18 DEGs were associated with intra-epithelial MCs and 19 DEGs were associated with intra-epithelial EOS (Table 1).A gene interaction network analysis identified the involvement of both IL-18 and IFN-γ as central regulators of T2 gene expression in the airways, most notably via IL-13.Conclusions: Intra-epithelial MCs and EOS are correlated with AHR and T2 inflammation.Using a transcriptomics approach, we identified associations between IL-18 receptor 1 and IFN-γ with endogenous AHR and EOS infiltration of the epithelium.

Secreted phospholipase A2 (sPLA2) enzymes release free fatty acids, including arachidonic acid, and generate lysophospholipids from phospholipids, including membrane phospholipids from cells and bacteria and surfactant phospholipids. We have shown that an endogenous enzyme sPLA2 group X (sPLA2-X) is elevated in the airways of asthmatics and that mice lacking the sPLA2-X gene (Pla2g10) display attenuated airway hyperresponsiveness, innate and adaptive immune responses, and type 2 cytokine production in a model of airway sensitization and challenge using a complete allergen that induces endogenous adjuvant activity. This complete allergen also induces the expression of sPLA2-X/Pla2g10 In the periphery, an sPLA2 found in bee venom (bee venom PLA2) administered with the incomplete Ag OVA leads to an Ag-specific immune response. In this study, we demonstrate that both bee venom PLA2 and murine sPLA2-X have adjuvant activity, leading to a type 2 immune response in the lung with features of airway hyperresponsiveness and Ag-specific type 2 airway inflammation following peripheral sensitization and subsequent airway challenge with OVA. Further, the adjuvant effects of sPLA2-X that result in the type 2-biased OVA-specific adaptive immune response in the lung were dependent upon the catalytic activity of the enzyme, as a catalytically inactive mutant form of sPLA2-X does not elicit the adaptive component of the immune response, although other components of the immune response were induced by the inactive enzyme, suggesting receptor-mediated effects. Our results demonstrate that exogenous and endogenous sPLA2s play an important role in peripheral sensitization, resulting in airway responses to inhaled Ags.