BACKGROUND:MUPPITS-2 was a randomized, placebo-controlled clinical trial that demonstrated mepolizumab (anti-IL-5) reduced exacerbations and blood and airway eosinophils in urban children with severe eosinophilic asthma. Despite this reduction in eosinophilia, exacerbation risk persisted in certain patients treated with mepolizumab. This raises the possibility that subpopulations of airway eosinophils exist that contribute to breakthrough exacerbations. OBJECTIVE:We aimed to determine the effect of mepolizumab on airway eosinophils in childhood asthma. METHODS:Sputum samples were obtained from 53 MUPPITS-2 participants. Airway eosinophils were characterized using mass cytometry and grouped into subpopulations using unsupervised clustering analyses of 38 surface and intracellular markers. Differences in frequency and immunophenotype of sputum eosinophil subpopulations were assessed based on treatment arm and frequency of exacerbations. RESULTS:Median sputum eosinophils were significantly lower among participants treated with mepolizumab compared with placebo (58% lower, 0.35% difference [95% CI 0.01, 0.74], P = .04). Clustering analysis identified 3 subpopulations of sputum eosinophils with varied expression of CD62L. CD62Lint and CD62Lhi eosinophils exhibited significantly elevated activation marker and eosinophil peroxidase expression, respectively. In mepolizumab-treated participants, CD62Lint and CD62Lhi eosinophils were more abundant in participants who experienced exacerbations than in those who did not (100% higher for CD62Lint, 0.04% difference [95% CI 0.0, 0.13], P = .04; 93% higher for CD62Lhi, 0.21% difference [95% CI 0.0, 0.77], P = .04). CONCLUSIONS:Children with eosinophilic asthma treated with mepolizumab had significantly lower sputum eosinophils. However, CD62Lint and CD62Lhi eosinophils were significantly elevated in children on mepolizumab who had exacerbations, suggesting that eosinophil subpopulations exist that contribute to exacerbations despite anti-IL-5 treatment.

AllergyVolume 78, Issue 12 p. 3274-3277 LETTER Sputum alarmins delineate distinct T2 cytokine pathways and unique subtypes of patients with asthma Samir Gautam, Samir Gautam Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorJen-Hwa Chu, Jen-Hwa Chu Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USASearch for more papers by this authorAvi J. Cohen, Avi J. Cohen orcid.org/0000-0001-8909-5365 Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorRavdeep Kaur, Ravdeep Kaur Department of Internal Medicine, Division of Rheumatology, Allergy and Clinical Immunology, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorSeohyuk Lee, Seohyuk Lee Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorGabriella Wilson, Gabriella Wilson Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorQing Liu, Qing Liu Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorJose Gomez, Jose Gomez Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorHaseena Rajaveen, Haseena Rajaveen Yale Center for Medical Informatics, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorXiting Yan, Xiting Yan Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USASearch for more papers by this authorLauren Cohn, Lauren Cohn Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorBrian J. Clark, Brian J. Clark Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorGeoffrey L. Chupp, Corresponding Author Geoffrey L. Chupp [email protected] Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Correspondence Geoffrey L. Chupp, Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, P.O. Box 208057, New Haven, CT 06520, USA. Email: [email protected]Search for more papers by this author Samir Gautam, Samir Gautam Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorJen-Hwa Chu, Jen-Hwa Chu Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USASearch for more papers by this authorAvi J. Cohen, Avi J. Cohen orcid.org/0000-0001-8909-5365 Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorRavdeep Kaur, Ravdeep Kaur Department of Internal Medicine, Division of Rheumatology, Allergy and Clinical Immunology, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorSeohyuk Lee, Seohyuk Lee Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorGabriella Wilson, Gabriella Wilson Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorQing Liu, Qing Liu Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorJose Gomez, Jose Gomez Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorHaseena Rajaveen, Haseena Rajaveen Yale Center for Medical Informatics, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorXiting Yan, Xiting Yan Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USASearch for more papers by this authorLauren Cohn, Lauren Cohn Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorBrian J. Clark, Brian J. Clark Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USASearch for more papers by this authorGeoffrey L. Chupp, Corresponding Author Geoffrey L. Chupp [email protected] Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut, USA Correspondence Geoffrey L. Chupp, Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, P.O. Box 208057, New Haven, CT 06520, USA. Email: [email protected]Search for more papers by this author First published: 24 October 2023 https://doi.org/10.1111/all.15915 Samir Gautam, Jen-Hwa Chu and Avi J. Cohen contributed equally to this work. Read 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 onEmailFacebookTwitterLinkedInRedditWechat Open Research DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. Supporting Information Filename Description all15915-sup-0001-supinfo.docxWord 2007 document , 5.7 MB Data S1: 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. REFERENCES 1Fahy JV. Type 2 inflammation in asthma-present in most, absent in many. Nat Rev Immunol. 2015; 15: 57-65. 10.1038/nri3786 CASPubMedWeb of Science®Google Scholar 2Kaur R, Chupp G. Phenotypes and endotypes of adult asthma: moving toward precision medicine. J Allergy Clin Immunol. 2019; 144: 1-12. 10.1016/j.jaci.2019.05.031 PubMedWeb of Science®Google Scholar 3Brasier AR, Victor S, Boetticher G, et al. Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage-derived cytokines. J Allergy Clin Immunol. 2008; 121: 30-37.e6. doi:10.1016/j.jaci.2007.10.015 10.1016/j.jaci.2007.10.015 CASPubMedWeb of Science®Google Scholar 4Osei ET, Brandsma CA, Timens W, Heijink IH, Hackett TL. Current perspectives on the role of interleukin-1 signalling in the pathogenesis of asthma and COPD. Eur Respir J. 2020; 55:1900563. doi:10.1183/13993003.00563-2019 10.1183/13993003.00563-2019 CASPubMedWeb of Science®Google Scholar 5Peters MC, Ringel L, Dyjack N, et al. A transcriptomic method to determine airway immune dysfunction in T2-high and T2-low asthma. Am J Respir Crit Care Med. 2019; 199: 465-477. 10.1164/rccm.201807-1291OC CASPubMedWeb of Science®Google Scholar 6Couillard S, Shrimanker R, Chaudhuri R, et al. Fractional exhaled nitric oxide nonsuppression identifies corticosteroid-resistant type 2 signaling in severe asthma. Am J Respir Crit Care Med. 2021; 204: 731-734. 10.1164/rccm.202104-1040LE PubMedWeb of Science®Google Scholar Volume78, Issue12December 2023Pages 3274-3277 ReferencesRelatedInformation

Rationale Asthma is a chronic airway disease driven by multiple immunologic pathways that determine the clinical response to therapy. Current diagnostic methods are incapable of discriminating subtypes of asthma and guiding targeted treatment. We hypothesized that sputum cytokine profiles could help to identify immunologically-defined disease subtypes and individualize therapy in patients with severe asthma. Objectives Define asthma subtypes associated with sputum alarmin and cytokine levels. Methods Cross-sectional analysis of clinical features and sputum from 200 asthmatic patients was performed. 10 cytokines belonging to alarmin, T2, and non-T2 pathways were measured. Pearson correlation was used to identify cytokine modules. Latent class analysis was used to cluster patients by cytokine expression. Measurements and Main Results Three modules of highly correlated cytokines were identified including a non-T2 module, the IL-1βmod (IL-1β, IL-6, GCSF), and two distinct T2 modules: TSLPmod (TSLP, IL-4, IL-5, IL-9) and IL-33mod (IL-33, IL-13, IL-21). The TSLPmod was associated with asthma severity, airway obstruction, eosinophilia, and elevated FeNO. Patient clustering revealed three subgroups; two different subgroups showed expression of T2 modules. Conclusions Analysis of sputum cytokines revealed three discrete signaling modules in patients with asthma. Unexpectedly, the inclusion of alarmins led to separation of canonical T2 cytokines into two unique modules; IL-5 grouped with TSLP, while IL-13 grouped with IL-33. In addition, patient clustering revealed two distinct endotypes associated with T2 immune signaling. These findings indicate a new layer of immunologic heterogeneity within the T2 paradigm, and suggest that sputum cytokine profiling may hold diagnostic utility for patients with asthma. ### Competing Interest Statement All authors have completed the ICMJE uniform disclosure form at [www.icmje.org/coi_disclosure.pdf][1] and declare: no support from any organization for the submitted work; SG has received payment for his Advisory Board role for AstraZeneca, GLC has received payments for his Speakers Bureau / Advisory Board roles for AstraZeneca, Glaxo Smith-Kline, Boehringer Ingelheim, Sanofi, Regeneron, Genentech. ### Funding Statement This study was funded by: F32 (HL154641), K08 (HL159422), CFF Fellowship (GAUTAM20D0), PBF Fellowship, Patterson Award, YCCI Scholar Award, and Doris Duke FRCS at Yale Award (#2021266) to SG. R01 (HL153604) to JG. R21 (LM012884) to XY. UM1 (AI114271), U23 (HL138998), and R01 (HL153604) to GLC. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Institutional Review Board of Yale University gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors. * ACT : Asthma control test BDR : Bronchodilator response BMI – : Body mass index FeNO : Fractional exhaled nitric oxide IgE : Immunoglobulin E LCA : Latent class analysis PFT : Pulmonary function test T2 : Type 2 TSLP : Thymic stromal lymphopoietin YCAAD : Yale Center for Asthma and Airway Diseases [1]: http://www.icmje.org/coi_disclosure.pdf

TOPIC: Genetic and Developmental Disorders TYPE: Original Investigations PURPOSE: Cystic Fibrosis (CF) is a multisystem autosomal recessive disease caused by mutations in the CFTR (CF transmembrane conductance regulator) gene. Airway inflammation and infection in CF leads to tissue injury, worsening lung function, and disease progression. Increased cytokine levels reflect the exaggerated inflammation characteristic of the CF airway environment and contribute to pathogenesis even in the absence of respiratory symptoms. We sought to define individual CF-specific cytokine variations as a means to characterize the difference between healthy and CF airways, and to identify patients at risk of clinical deterioration. METHODS: Sputum samples were obtained from Forty-four adult patients with confirmed CF diagnosis from the Yale Adult CF Program. Patients were classified as CF stable at each visit if they did not meet predefined criteria for an acute exacerbation. Ten healthy controls (HC) were recruited to undergo sputum induction. Sputum samples were assayed for twelve cytokines using a multiplexed indirect ELISA. Differences in cytokine levels between CF stable and healthy controls were analyzed using the Mann-Whitney Test with Bonferroni correction. RESULTS: Twelve inflammatory cytokine levels were measured. Six cytokines were significantly increased in the sputum of stable CF patients compared to healthy controls (median values, pg/mL). These cytokines included: IL-1beta (CF 1720; HC 39.7), IL-8 (CF 28173; HC 3468), TNF-alpha (CF 98.65; HC 10.70), and IFN-alpha (CF 38.90; HC 5.60) [p < 0.0001] as well as IFN-gamma (CF 68.45; HC 17.10) and IL-13 (20.10; 0.00) [p < 0.01]. Cytokines tested without significant difference between groups included: CXCL10, G-CSF, IFNI, IL-6, MCP1, and MIP-alpha. CONCLUSIONS: Inflammatory cytokine levels of IL-1beta, IL-8, TNF-alpha, IFN-a, IFN-gamma and IL-13 are significantly increased in the sputum of stable CF patients compared to the sputum of healthy controls. CLINICAL IMPLICATIONS: Monitoring basal sputum cytokine levels may help identify patients with worsening inflammation before symptoms develop and thus prevent irreversible lung damage and disease progression. Additionally, further understanding of inflammatory cytokine dysregulation in stable CF airways may serve as the basis for a sputum inflammation marker panel that guides future therapeutic interventions. DISCLOSURES: No relevant relationships by Clemente Britto, source=Web Response Consultant relationship with AstraZeneca Please note: >$100000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Genentech Please note: $20001 - $100000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Genzyme Corporation Please note: $5001 - $20000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Novartis Please note: $5001 - $20000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Circassia Please note: $1001 - $5000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Boehringer Ingelheim Please note: $1001 - $5000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with GlaxoSmithKline Please note: $1-$1000 by Geoffrey Chupp, source=Web Response, value=Consulting fee Consultant relationship with Regeneron Please note: 5/2019-present Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Speaker/Speaker's Bureau relationship with Genentech Please note: 5/2019-11/2019 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Honoraria Advisory Committee Member relationship with novartis Please note: 10/2019 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Advisory Committee Member relationship with glaxosmithkline Please note: 12/2019 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Advisory Committee Member relationship with sanofi Please note: 5/2020 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Advisory Committee Member relationship with Pieris Please note: 5/2019 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Advisory Committee Member relationship with AstraZeneca Please note: 5/2019-7/2020 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee Consultant relationship with Biohaven Please note: 6/23/2020 Added 04/26/2021 by Lauren Cohn, source=Web Response, value=Consulting fee No relevant relationships by Sara Khanal, source=Web Response No relevant relationships by qing liu, source=Web Response No relevant relationships by Jana Zielonka, source=Web Response

BackgroundAsthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods.MethodsTwo complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study.ResultsPBMCs (n=9414) from five SA (n=6099) and three HC (n=3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4+T cells, CD8+T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4+T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n=160,000) from the same individuals (SA=5; HC=3) demonstrated higher CD8+and CD8+effector T cells in SA at baseline, followed by a decrease of CD8+effector T cells after poly I:C stimulation.ConclusionsSingle-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8+effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.

BACKGROUND:Airway eosinophilia is a prominent feature of asthma and chronic rhinosinusitis (CRS), and the endothelium plays a key role in eosinophil trafficking. To date, microRNA-1 (miR-1) is the only microRNA known to be regulated in the lung endothelium in asthma models.OBJECTIVE:We sought to determine the role of endothelial miR-1 in allergic airway inflammation.METHODS:We measured microRNA and mRNA expression using quantitative RT-PCR. We used ovalbumin and house dust mite models of asthma. Endothelium-specific overexpression of miR-1 was achieved through lentiviral vector delivery or induction of a transgene. Tissue eosinophilia was quantified by using Congo red and anti-eosinophil peroxidase staining. We measured eosinophil binding with a Sykes-Moore adhesion chamber. Target recruitment to RNA-induced silencing complex was assessed by using anti-Argonaute2 RNA immunoprecipitation. Surface P-selectin levels were measured by using flow cytometry.RESULTS:Serum miR-1 levels had inverse correlations with sputum eosinophilia, airway obstruction, and number of hospitalizations in asthmatic patients and sinonasal tissue eosinophilia in patients with CRS. IL-13 stimulation decreased miR-1 levels in human lung endothelium. Endothelium-specific overexpression of miR-1 reduced airway eosinophilia and asthma phenotypes in murine models and inhibited IL-13-induced eosinophil binding to endothelial cells. miR-1 recruited P-selectin, thymic stromal lymphopoietin, eotaxin-3, and thrombopoietin receptor to the RNA-induced silencing complex; downregulated these genes in the lung endothelium; and reduced surface P-selectin levels in IL-13-stimulated endothelial cells. In our asthma and CRS cohorts, miR-1 levels correlated inversely with its target genes.CONCLUSION:Endothelial miR-1 regulates eosinophil trafficking in the setting of allergic airway inflammation. miR-1 has therapeutic potential in asthmatic patients and patients with CRS.

Rationale: MicroRNAs are potent regulators of biologic systems that are critical to tissue homeostasis. Individual microRNAs have been identified in airway samples. However, a systems analysis of the microRNA-mRNA networks present in the sputum that contribute to airway inflammation in asthma has not been published. Objectives: Identify microRNA and mRNA networks in the sputum of patients with asthma. Methods: We conducted a genome-wide analysis of microRNA and mRNA in the sputum from patients with asthma and correlated expression with clinical phenotypes. Weighted gene correlation network analysis was implemented to identify microRNA networks (modules) that significantly correlate with clinical features of asthma and mRNA expression networks. MicroRNA expression in peripheral blood neutrophils and lymphocytes and in situ hybridization of the sputum were used to identify the cellular sources of microRNAs. MicroRNA expression obtained before and after ozone exposure was also used to identify changes associated with neutrophil counts in the airway. Measurements and Main Results: Six microRNA modules were associated with clinical features of asthma. A single module (nely) was associated with a history of hospitalizations, lung function impairment, and numbers of neutrophils and lymphocytes in the sputum. Of the 12 microRNAs in the nely module, hsa-miR-223-3p was the highest expressed microRNA in neutrophils and was associated with increased neutrophil counts in the sputum in response to ozone exposure. Multiple microRNAs in the nely module correlated with two mRNA modules enriched for TLR (Toll-like receptor) and T-helper cell type 17 (Th17) signaling and endoplasmic reticulum stress. hsa-miR-223-3p was a key regulator of the TLR and Th17 pathways in the sputum of subjects with asthma. Conclusions: This study of sputummicro RNA and mRNA expression from patients with asthma demonstrates the existence of microRNA networks and genes that are associated with features of asthma severity. Among these, hsa-miR-223-3p, a neutrophil-derived microRNA, regulates TLR/Th17 signaling and endoplasmic reticulum stress.

Chitinases are the enzymes that cleave chitin. Even in the absence of chitin, mammalians have significant amounts of chitinases present in the body including at baseline. The precise role of chitinase is not known, however it was believed to play important role in digestion and host defense against chitin-containing food and pathogens, respectively. Recent work, including ours, has shown an important role of chitinase and chitinase-like proteins in host immunity and allergic diseases. Importantly, chitinase activities serve as important biomarkers of disease severity in a wide-range of diseases including type 2 inflammatory diseases such as asthma and pulmonary fibrosis. Similarly, patients with genetic disorders like Gaucher disease have significantly elevated chitinase levels, which not only correlate with disease severity but also serve as a reliable biomarker for therapeutic effectiveness. The protocol outlined here describes a simple, quick, and straightforward way to measure chitinase activity in BAL or serum samples of mice and can be widely adapted to human subjects and other model organisms due to the highly conserved nature of the enzymes.

Oxidative stress is important in the pathogenesis of allergic asthma. Extracellular superoxide dismutase (EC-SOD; SOD3) is the major antioxidant in lungs, but its role in allergic asthma is unknown. Here we report that asthmatics have increased SOD3 transcript levels in sputum and that a single nucleotide polymorphism (SNP) in SOD3 (R213G; rs1799895) changes lung distribution of EC-SOD, and decreases likelihood of asthma-related symptoms. Knockin mice analogous to the human R213G SNP had lower airway hyperresponsiveness, inflammation, and mucus hypersecretion with decreased interleukin-33 (IL-33) in bronchoalveolar lavage fluid and reduced type II innate lymphoid cells (ILC2s) in lungs. SOD mimetic (Mn (III) tetrakis (N-ethylpyridinium-2-yl) porphyrin) attenuated Alternaria-induced expression of IL-33 and IL-8 release in BEAS-2B cells. These results suggest that R213G SNP potentially benefits its carriers by resulting in high EC-SOD in airway-lining fluid, which ameliorates allergic airway inflammation by dampening the innate immune response, including IL-33/ST2-mediated changes in ILC2s.

Airway diseases affect over 7% of the U.S. population and millions of patients worldwide. Asthmatic patients have wide variation in clinical severity with different clinical and physiologic manifestations of disease that may be driven by distinct biologic mechanisms. Further, the immunologic underpinnings of this complex trait disease are heterogeneous and treatment success depends on defining subgroups of asthmatics. Because of the limited availability and number of cells from the lung, the active site, in‐depth investigation has been challenging. Recent advances in technology support transcriptional analysis of cells from induced sputum. Flow cytometry studies have described cells present in the sputum but a detailed analysis of these subsets is lacking. Mass cytometry or CyTOF (Cytometry by Time‐Of‐Flight) offers tremendous opportunities for multiparameter single cell analysis. Experiments can now allow detection of up to ∼40 markers to facilitate unprecedented multidimensional cellular analyses. Here we demonstrate the use of CyTOF on primary airway samples obtained from well‐characterized patients with asthma and cystic fibrosis. Using this technology, we quantify cellular frequency and functional status of defined cell subsets. Our studies provide a blueprint to define the heterogeneity among subjects and underscore the power of this single cell method to characterize airway immune status. © 2016 International Clinical Cytometry Society

BACKGROUND BRP-39/YKL-40 is a chitinase-like protein that plays a critical role in IL-13-induced inflammation. It correlates positively with asthma severity and airway remodeling ( 1 ) via binding to IL-13 receptor α2 chain (IL-13Rα2). Because the relationship of IL-13Rα2 to human asthma has never been evaluated previously, we sought to determine the relationship between IL-13Rα2, YKL-40, and asthma. METHODS We evaluated 112 patients (69% women) with a mean age of 46.7 years. Subjects completed an asthma phenotyping protocol that included analysis of sputum gene expression by Affymetrix 1.0 ST gene array (Affymetrix, Santa Clara, CA) and YKL-40 protein levels. MEASUREMENTS AND MAIN RESULTS IL-13Rα2 gene expression was readily detectable in the sputum and correlated negatively with prebronchodilator (BD) FEV1 (rs = -0.282, P < 0.01), post-BD FEV1 (rs = -0.268, P < 0.01), pre-BD FEV1/FVC ratio (rs = -0.228, P < 0.05), and post-BD FEV1/FVC ratio (rs = -0.242, P < 0.01). IL-13Rα2 gene expression correlated positively with gene expression of IL-13 (rs = 0.484, P < 0.001), IL-5 (rs = 0.237, P < 0.05), and IL-8 (rs = 0.218, P < 0.05). Regression analysis showed that the post-BD FEV1/FVC ratio is significantly associated with IL-13Rα2 expression and CHI3L1 expression in sputum after controlling for IL-4, IL-5, IL-13, and transforming growth factor-β1 gene expression (all P < 0.01). Sputum YKL-40 gene expression positively correlated with IL-8 expression (rs = 0.357, P < 0.001) and negatively correlated with pre- and post-BD FEV1/FVC ratios (rs = -0.299, P < 0.001 and rs = -0.305, P < 0.01, respectively). Sputum and serum YKL-40 protein levels were not associated with IL-13Rα2 expression. CONCLUSIONS This analysis demonstrates that IL-13Rα2 is associated with reduced lung function, helper T-cell type 2 gene expression, and airflow obstruction in the airway of individuals with asthma, which might in turn be driven by airway remodeling. Future studies will be required to define the proinflammatory and remodeling effects of this receptor that up to now has been considered solely a modulator of IL-13-induced inflammation.

BACKGROUND: Analysis of inflammatory cell populations in induced sputum has been used to identify subgroups of asthma, but the associated cytokine/chemokine profiles of these subgroups have not been defined. METHODS: Questionnaires, blood collection, spirometry, and sputum induction were completed by 299 asthmatics. Subgroups were determined using the method defined by Simpson et al (Respirology 2006). Sputum eosinophil and neutrophil cutoffs were 5.4% and 45.4%, respectively. Cytokine levels in mucus supernatants were measured by Luminex and analyzed using non-parametric tests. RESULTS: The paucigranulocytic subgroup was the largest followed by the eosinophilic, neutrophilic, and mixed. The neutrophilic, eosinophilic, and mixed subgroups had more moderate and severe asthmatics with equal risks of severe and near fatal exacerbations. The neutrophilic subgroup had the youngest median age of disease onset and lowest FENO overall, and higher levels of IL-8 (2746 vs. 654, pg/mL, p=0.002) and IP-10 (8448 vs. 2390, pg/mL, p=0.008) compared to the eosinophilic subgroup. A trend was seen for higher IL-6 levels in the neutrophilic subgroup compared to the other subgroups. CONCLUSIONS: The neutrophilic, eosinophilic, and mixed subgroups displayed nearly identical sputum cytokine/chemokine profiles. The distinguishing characteristics of the neutrophilic subgroup were the higher levels of proinflammatory cytokines IL-8, IL-6 and the antimicrobial protein IP-10. IP-10 has been associated with refractory upper airway inflammation and rhinovirus-induced asthma exacerbations. This suggests the neutrophilic subgroup may be more susceptible to viral-mediated asthma exacerbations.

Asthma, the prototypic Th2-mediated inflammatory disorder of the lung, is an emergent disease worldwide. Vascular endothelial growth factor (VEGF) is a critical regulator of pulmonary Th2 inflammation, but the underlying mechanism and the roles of microRNAs (miRNAs) in this process have not been defined. Here we show that lung-specific overexpression of VEGF decreases miR-1 expression in the lung, most prominently in the endothelium, and a similar down-regulation occurs in lung endothelium in Th2 inflammation models. Intranasal delivery of miR-1 inhibited inflammatory responses to ovalbumin, house dust mite, and IL-13 overexpression. Blocking VEGF inhibited Th2-mediated lung inflammation, and this was restored by antagonizing miR-1. Using mRNA arrays, Argonaute pull-down assays, luciferase expression assays, and mutational analysis, we identified Mpl as a direct target of miR-1 and showed that VEGF controls the expression of endothelial Mpl during Th2 inflammation via the regulation of miR-1. In vivo knockdown of Mpl inhibited Th2 inflammation and indirectly inhibited the expression of P-selectin in lung endothelium. These experiments define a novel VEGF-miR-1-Mpl-P-selectin effector pathway in lung Th2 inflammation and herald the utility of miR-1 and Mpl as potential therapeutic targets for asthma.

Short palate, lung, and nasal epithelial clone-1 (SPLUNC1) is a protein abundantly expressed by the respiratory epithelium of the proximal lower respiratory tract, a site of great environmental exposure. Previous studies showed that SPLUNC1 exerts antimicrobial effects, regulates airway surface liquid and mucociliary clearance, and suppresses allergic airway inflammation. We studied SPLUNC1 to gain insights into its role in host defense. In the lower respiratory tract, concentrations of SPLUNC1 are high under basal conditions. In models of pneumonia caused by common respiratory pathogens, and in Th1-induced and Th2-induced airway inflammation, SPLUNC1 secretion is markedly reduced. Pathogen-associated molecular patterns and IFN-γ act directly on airway epithelial cells to inhibit SPLUNC1 mRNA expression. Thus, SPLUNC1 is quickly suppressed during infection, in response to an insult on the epithelial surface. These experiments highlight the finely tuned fluctuations of SPLUNC1 in response to exposures in the respiratory tract, and suggest that the loss of SPLUNC1 is a crucial feature of host defense across air-breathing animal species.

Aspartic proteases are important virulence factors in pathogens like HIV, Candida albicans or Plasmodium falciparum. We report here the identification of seven putative aspartic proteases, TgASP1 to TgASP7, in the apicomplexan parasite Toxoplasma gondii. Bioinformatic and phylogenetic analysis of the TgASPs and other aspartic proteases from related Apicomplexa suggests the existence of five distinct groups of aspartic proteases with different evolutionary lineages. The members of each group share predicted biological features that validate the phylogeny. TgASP1 is expressed in tachyzoites, the rapidly dividing asexual stage of T. gondii. We present the proteolytic maturation and subcellular localization of this protease through the cell cycle. TgASP1 shows a novel punctate localization associated with the secretory system in non‐dividing cells, and relocalizes dramatically and unambiguously to the nascent inner membrane complex of daughter cells at replication, before coalescing again at the end of division.