A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma.

By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma.

Multivariate Cluster Analyses to Characterize Asthma Heterogeneity and Benralizumab Responsiveness.

BACKGROUND: An improved understanding of how severe asthma heterogeneity affects response could inform treatment decisions. OBJECTIVES: Characterize heterogeneity and benralizumab responsiveness in patients grouped by predefined Severe Asthma Research Program clusters using a multivariate approach. METHODS: In post-hoc analyses of the randomized, double-blind, placebo-controlled phase III SIROCCO (NCT01928771) and CALIMA (NCT01914757) studies, patients with severe asthma who received benralizumab or placebo were assigned to clusters using an established discriminant function to simultaneously analyze 11 clinical characteristics. Annualized asthma exacerbation rate, exacerbation incidence, and lung function were analyzed across clusters. RESULTS: Patients (N = 2,281) met criteria for 4 of 5 clusters: Cluster 2 (early-onset moderate asthma, n = 393), Cluster 4 (early-onset severe, n = 386), Cluster 3 (late-onset severe, n = 641), and Cluster 5 (late-onset severe, obstructed, n = 861); no patients met Cluster 1 criteria. Exacerbation rate reductions were significant in late-onset severe (-48% [95% CI: -61%, -31%], P<.0001) and late-onset severe, obstructed asthma (-50% [95% CI: -59%, -38%], P<.0001), with non-significant reductions in early-onset clusters. These differences could not be fully explained by blood eosinophil count differences. Forced expiratory volume in 1 second improvements were significant in late-onset severe (+133 mL [95% CI: 66 mL, 200 mL], P=.0001) and late-onset severe, obstructed asthma (+160 mL [95% CI: 85 mL, 235 mL], P<.0001) while maintaining acute bronchodilator responsiveness. CONCLUSIONS: Benralizumab reduced exacerbations and improved lung function, primarily in late-onset asthma clusters. This multivariate approach to identify subphenotypes, potentially reflecting pathobiological mechanisms, can guide therapy beyond univariate approaches.

Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.

BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes. OBJECTIVES: To further explore asthma heterogeneity through determination of multiple patient groups by using novel machine learning (ML) approaches and large-scale real-world data. METHODS: We used electronic health records of patients with asthma followed at the Cleveland Clinic between 2010 and 2021. We used k-prototype unsupervised ML to develop a clustering model where predictors were age, sex, race, body mass index, prebronchodilator and postbronchodilator spirometry measurements, and the usage of inhaled/systemic steroids. We applied elbow and silhouette plots to select the optimal number of clusters. These clusters were then evaluated through LightGBM's supervised ML approach on their cross-validated F1 score to support their distinctiveness. RESULTS: Data from 13,498 patients with asthma with available postbronchodilator spirometry measurements were extracted to identify 5 stable clusters. Cluster 1 included a young nonsevere asthma population with normal lung function and higher frequency of acute exacerbation (0.8 /patient-year). Cluster 2 had the highest body mass index (mean ± SD, 44.44 ± 7.83 kg/m2), and the highest proportion of females (77.5%) and Blacks (28.9%). Cluster 3 comprised patients with normal lung function. Cluster 4 included patients with lower percent of predicted FEV1 of 77.03 (12.79) and poor response to bronchodilators. Cluster 5 had the lowest percent of predicted FEV1 of 68.08 (15.02), the highest postbronchodilator reversibility, and the highest proportion of severe asthma (44.9%) and blood eosinophilia (>300 cells/µL) (34.8%). CONCLUSIONS: Using real-world data and unsupervised ML, we classified asthma into 5 clinically important subphenotypes where group-specific asthma treatment and management strategies can be designed and deployed.

Protein-Protein interactive networks identified in bronchoalveolar lavage of severe compared to nonsevere asthma.

INTRODUCTION: Previous bronchoalveolar lavage fluid (BALF) proteomic analysis has evaluated limited numbers of subjects for only a few proteins of interest, which may differ between asthma and normal controls. Our objective was to examine a more comprehensive inflammatory biomarker panel in quantitative proteomic analysis for a large asthma cohort to identify molecular phenotypes distinguishing severe from nonsevere asthma. METHODS: Bronchoalveolar lavage fluid from 48 severe and 77 nonsevere adult asthma subjects were assessed for 75 inflammatory proteins, normalized to BALF total protein concentration. Validation of BALF differences was sought through equivalent protein analysis of autologous sputum. Subjects' data, stratified by asthma severity, were analysed by standard statistical tests, principal component analysis and 5 machine learning algorithms. RESULTS: The severe group had lower lung function and greater health care utilization. Significantly increased BALF proteins for severe asthma compared to nonsevere asthma were fibroblast growth factor 2 (FGF2), TGFα, IL1Ra, IL2, IL4, CCL8, CCL13 and CXCL7 and significantly decreased were platelet-derived growth factor a-a dimer (PDGFaa), vascular endothelial growth factor (VEGF), interleukin 5 (IL5), CCL17, CCL22, CXCL9 and CXCL10. Four protein differences were replicated in sputum. FGF2, PDGFaa and CXCL7 were independently identified by 5 machine learning algorithms as the most important variables for discriminating severe and nonsevere asthma. Increased and decreased proteins identified for the severe cluster showed significant protein-protein interactions for chemokine and cytokine signalling, growth factor activity, and eosinophil and neutrophil chemotaxis differing between subjects with severe and nonsevere asthma. CONCLUSION: These inflammatory protein results confirm altered airway remodelling and cytokine/chemokine activity recruiting leukocytes into the airways of severe compared to nonsevere asthma as important processes even in stable status.

Genetic and T2 biomarkers linked to the efficacy of HDM sublingual immunotherapy in asthma.

BACKGROUND: Hypersensitivity to house dust mite (HDM) allergens is a common cause of allergic asthma symptoms and can be effectively treated with allergy immunotherapy (AIT). OBJECTIVE: To investigate whether genetic and type 2 (T2) inflammatory biomarkers correlate with disease severity in subjects with allergic asthma, and whether this can be modified by AIT. METHODS: MITRA (NCT01433523) was a phase III, randomised, double-blind, placebo-controlled trial of HDM sublingual immunotherapy (SLIT)-tablets in adults with HDM allergic asthma. Post hoc analyses of the study population (N=742) evaluated associations between T2 inflammatory (blood eosinophils, eosinophil cationic protein (ECP), total IgE and tryptase) and genetic (single-nucleotide polymorphisms, SNP) biomarkers (n=582) for the primary study endpoint (time to first moderate/severe asthma exacerbation). SNP associations were verified in HDM-positive subgroup from an independent 3-year Severe Asthma Research Programme (SARP3) subject cohort. RESULTS: An increased asthma exacerbation risk in subjects homozygous for SNP rs7216389 (chromosomal locus 17q12-21) was reduced (p=0.037) by treatment with HDM SLIT (HR=0.37 (95% CI 0.22 to 0.64), p<0.001). The associations between exacerbation risk and 17q12-21 SNPs were replicated in the SARP3 HDM-positive subgroup. High levels of T2 biomarkers were associated with increased risk of asthma exacerbations in the placebo group. HDM SLIT-tablet treatment reduced this risk (blood eosinophils: HR=0.50 (95% CI 0.30 to 0.85); ECP: HR=0.45 (95% CI 0.29 to 0.87); tryptase: HR=0.45 (95% CI 0.25 to 0.80)). The treatment effect was higher (p=0.006) for subjects with a higher number of elevated T2 biomarkers. CONCLUSIONS: HDM SLIT-tablet AIT is efficacious in HDM-sensitised asthma subjects with a genetic asthma predisposition and/or an underlying T2 endotype. TRIAL REGISTRATION NUMBER: NCT01433523.

Mitochondrial DNA Copy Number Variation in Asthma Risk, Severity, and Exacerbations.

Rationale: Although airway oxidative stress and inflammation are central to asthma pathogenesis, there is limited knowledge of the relationship of asthma risk, severity, or exacerbations to mitochondrial dysfunction, which is pivotal to oxidant generation and inflammation. Objectives: We investigated whether mitochondrial DNA copy number (mtDNA-CN) as a measure of mitochondrial function is associated with asthma diagnosis, severity, oxidative stress, and exacerbations. Methods: We measured mtDNA-CN in blood in two cohorts. In the UK Biobank (UKB), we compared mtDNA-CN in mild and moderate-severe asthmatics to non-asthmatics. In the Severe Asthma Research Program (SARP), we evaluated mtDNA-CN in relation to asthma severity, biomarkers of oxidative stress and inflammation, and exacerbations. Measures and Main Results: In UK Biobank, asthmatics (n = 29,768) have lower mtDNA-CN compared to non-asthmatics (n = 239,158) (beta, -0.026 [95% CI, -0.038 to -0.014], P = 2.46×10-5). While lower mtDNA-CN is associated with asthma, mtDNA-CN did not differ by asthma severity in either UKB or SARP. Biomarkers of inflammation show that asthmatics have higher white blood cells (WBC), neutrophils, eosinophils, fraction exhaled nitric oxide (FENO), and lower superoxide dismutase (SOD) than non-asthmatics, confirming greater oxidative stress in asthma. In one year follow-up in SARP, higher mtDNA-CN is associated with reduced risk of three or more exacerbations in the subsequent year (OR 0.352 [95% CI, 0.164 to 0.753], P = 0.007). Conclusions: Asthma is characterized by mitochondrial dysfunction. Higher mtDNA-CN identifies an exacerbation-resistant asthma phenotype, suggesting mitochondrial function is important in exacerbation risk.

A Polygenic Risk Score for Idiopathic Pulmonary Fibrosis and Interstitial Lung Abnormalities.

Rationale: In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives: We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods: We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results: We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case-control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10-95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10-87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions: A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

Large scale proteomic studies create novel privacy considerations.

Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90-95% of proteomes to their correct genome and for 95-99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Impact of Bronchiectasis on COPD Severity and Alpha-1 Antitrypsin Deficiency as a Risk Factor in Individuals with a Heavy Smoking History.

Rationale: Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including alpha-1 antitrypsin deficiency, and its implications for COPD severity are uncharacterized in such individuals. Objectives: To characterize the impact of bronchiectasis on COPD and explore alpha-1antitrypsin as a risk factor for bronchiectasis. Methods: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) participants (N=914; ages 40-80 years; ≥20-pack-year smoking) had high-resolution computed tomography (CT) scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding -alpha-1 antitrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on the PiZ genotype (Glu366Lys, rs28929474). Measurements and Main Results: We identified bronchiectasis in 365 (40%) participants, more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[standard deviation (SD)=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (forced expiratory volume in 1 second [FEV1 ] percentage predicted=66%[SD=27] versus 77%[SD=25], p<0.0001; FEV1 to forced vital capacity [FVC] ratio=0.54[0.17] versus 0.63[SD=0.16], p<0.0001). Participants with bronchiectasis had greater emphysema (%voxels ≤-950 Hounsfield units, 11%[SD=12] versus 6.3%[SD=9], p<0.0001) and parametric response mapping functional small airways disease (26[SD=15] versus 19[SD=15], p<0.0001). Bronchiectasis was more frequent in the combined PiZZ and PiMZ genotype groups compared to those without PiZ, PiS, or other rare pathogenic variants (N=21 of 40 [52%] versus N=283 of 707[40%], odds ratio [OR]=1.97; 95% confidence interval [CI]=1.002, 3.90, p=0.049), an association attributed to White individuals (OR=1.98; 95%CI = 0.9956, 3.9; p=0.051). Conclusions: Bronchiectasis was common in those with heavy smoking histories and was associated with detrimental clinical and radiographic outcomes. Our findings support alpha-1antitrypsin guideline recommendations to screen for alpha-1 antitrypsin deficiency in an appropriate bronchiectasis subgroup with a significant smoking history.

A blood and bronchoalveolar lavage protein signature of rapid FEV1 decline in smoking-associated COPD.

Accelerated progression of chronic obstructive pulmonary disease (COPD) is associated with increased risks of hospitalization and death. Prognostic insights into mechanisms and markers of progression could facilitate development of disease-modifying therapies. Although individual biomarkers exhibit some predictive value, performance is modest and their univariate nature limits network-level insights. To overcome these limitations and gain insights into early pathways associated with rapid progression, we measured 1305 peripheral blood and 48 bronchoalveolar lavage proteins in individuals with COPD [n = 45, mean initial forced expiratory volume in one second (FEV1) 75.6 ± 17.4% predicted]. We applied a data-driven analysis pipeline, which enabled identification of protein signatures that predicted individuals at-risk for accelerated lung function decline (FEV1 decline ≥ 70 mL/year) ~ 6 years later, with high accuracy. Progression signatures suggested that early dysregulation in elements of the complement cascade is associated with accelerated decline. Our results propose potential biomarkers and early aberrant signaling mechanisms driving rapid progression in COPD.

Clinical Implications of Longitudinal Blood Eosinophil Counts in Patients With Severe Asthma.

BACKGROUND: The stability and variability of blood eosinophil counts (BECs) to phenotype patients with severe asthma is not fully understood. OBJECTIVE: This post hoc, longitudinal, pooled analysis of placebo-arm patients from 2 phase 3 studies evaluated the clinical implications of BEC stability and variability in moderate-to-severe asthma. METHODS: This analysis included patients from SIROCCO and CALIMA who received maintenance medium- to high-dosage inhaled corticosteroids plus long-acting ß2-agonists; 2:1 patients with BECs of 300 cells/µL or higher and less than 300 cells/µL were enrolled. The BECs were measured 6 times over 1 year in a centralized laboratory. Exacerbations, lung function, and Asthma Control Questionnaire 6 scores were documented across patients grouped by BEC (<300 cells/µL or ≥300 cells/µL) and variability (<80% or ≥80% BECs less than or greater than 300 cells/µL). RESULTS: Among 718 patients, 42.2% (n = 303) had predominantly high, 30.9% (n = 222) had predominantly low, and 26.9% (n = 193) had variable BECs. Prospective exacerbation rates (mean ± SD) were significantly greater in patients with predominantly high (1.39 ± 2.20) and variable (1.41 ± 2.09) BECs versus predominantly low (1.05 ± 1.66) BECs. Similar results were observed for the number of exacerbations while on placebo. CONCLUSIONS: Although patients with variable BECs had intermittently high and low BECs, they experienced similar exacerbation rates to the predominantly high group, which were greater than those in the predominantly low group. A high BEC supports an eosinophilic phenotype in clinical settings without additional measurements, whereas a low BEC requires repeated measurements because it could reflect intermittently high or predominantly low BECs.

Genetic analyses of chr11p15.5 region identify MUC5AC-MUC5B associated with asthma-related phenotypes.

OBJECTIVE: Genome-wide association studies (GWASs) have identified single nucleotide polymorphisms (SNPs) in chr11p15.5 region associated with asthma and idiopathic interstitial pneumonias (IIPs). We sought to identify functional genes for asthma by combining SNPs and mRNA expression in bronchial epithelial cells (BEC) in the Severe Asthma Research Program (SARP). METHODS: Correlation analyses of mRNA expression of six candidate genes (AP2A2, MUC6, MUC2, MUC5AC, MUC5B, and TOLLIP) and asthma phenotypes were performed in the longitudinal cohort (n = 156) with RNAseq in BEC, and replicated in the cross-sectional cohort (n = 155). eQTL (n = 114) and genetic association analysis of asthma severity (426 severe vs. 531 non-severe asthma) were performed, and compared with previously published GWASs of IIPs and asthma. RESULTS: Higher expression of AP2A2 and MUC5AC and lower expression of MUC5B in BEC were correlated with asthma, asthma exacerbations, and T2 biomarkers (P < 0.01). SNPs associated with asthma and IIPs in previous GWASs were eQTL SNPs for MUC5AC, MUC5B, or TOLLIP, however, they were not in strong linkage disequilibrium. The risk alleles for asthma or protective alleles for IIPs were associated with higher expression of MUC5AC and lower expression of MUC5B. rs11603634, rs12788104, and rs28415845 associated with moderate-to-severe asthma or adult onset asthma in previous GWASs were not associated with asthma severity (P > 0.8). CONCLUSIONS: SNPs associated with asthma in chr11p15.5 region are not associated with asthma severity neither with IIPs. Higher expression of MUC5AC and lower expression of MUC5B are risk for asthma but protective for IIPs.

Investigations of a combination of atopic status and age of asthma onset identify asthma subphenotypes.

OBJECTIVE: Subphenotypes of asthma may be determined by age onset and atopic status. We sought to characterize early or late onset atopic asthma with fungal or non-fungal sensitization (AAFS or AANFS) and non-atopic asthma (NAA) in children and adults in the Severe Asthma Research Program (SARP). SARP is an ongoing project involving well-phenotyped patients with mild to severe asthma. METHODS: Phenotypic comparisons were performed using Kruskal-Wallis or chi-square test. Genetic association analyses were performed using logistic or linear regression. RESULTS: Airway hyper-responsiveness, total serum IgE levels, and T2 biomarkers showed an increasing trend from NAA to AANFS and then to AAFS. Children and adults with early onset asthma had greater % of AAFS than adults with late onset asthma (46% and 40% vs. 32%; P < 0.00001). In children, AAFS and AANFS had lower % predicted FEV1 (86% and 91% vs. 97%) and greater % of patients with severe asthma than NAA (61% and 59% vs. 43%). In adults with early or late onset asthma, NAA had greater % of patients with severe asthma than AANFS and AAFS (61% vs. 40% and 37% or 56% vs. 44% and 49%). The G allele of rs2872507 in GSDMB had higher frequency in AAFS than AANFS and NAA (0.63 vs. 0.55 and 0.55), and associated with earlier age onset and asthma severity. CONCLUSIONS: Early or late onset AAFS, AANFS, and NAA have shared and distinct phenotypic characteristics in children and adults. AAFS is a complex disorder involving genetic susceptibility and environmental factors.

CCL5 is a potential bridge between type 1 and type 2 inflammation in asthma.

BACKGROUND: Type 1 (T1) inflammation (marked by IFN-γ expression) is now consistently identified in subsets of asthma cohorts, but how it contributes to disease remains unclear. OBJECTIVE: We sought to understand the role of CCL5 in asthmatic T1 inflammation and how it interacts with both T1 and type 2 (T2) inflammation. METHODS: CCL5, CXCL9, and CXCL10 messenger RNA expression from sputum bulk RNA sequencing, as well as clinical and inflammatory data were obtained from the Severe Asthma Research Program III (SARP III). CCL5 and IFNG expression from bronchoalveolar lavage cell bulk RNA sequencing was obtained from the Immune Mechanisms in Severe Asthma (IMSA) cohort and expression related to previously identified immune cell profiles. The role of CCL5 in tissue-resident memory T-cell (TRM) reactivation was evaluated in a T1high murine severe asthma model. RESULTS: Sputum CCL5 expression strongly correlated with T1 chemokines (P < .001 for CXCL9 and CXCL10), consistent with a role in T1 inflammation. CCL5high participants had greater fractional exhaled nitric oxide (P = .009), blood eosinophils (P < .001), and sputum eosinophils (P = .001) in addition to sputum neutrophils (P = .001). Increased CCL5 bronchoalveolar lavage expression was unique to a previously described T1high/T2variable/lymphocytic patient group in the IMSA cohort, with IFNG trending with worsening lung obstruction only in this group (P = .083). In a murine model, high expression of the CCL5 receptor CCR5 was observed in TRMs and was consistent with a T1 signature. A role for CCL5 in TRM activation was supported by the ability of the CCR5 inhibitor maraviroc to blunt reactivation. CONCLUSION: CCL5 appears to contribute to TRM-related T1 neutrophilic inflammation in asthma while paradoxically also correlating with T2 inflammation and with sputum eosinophilia.

Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.

Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants.

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Bronchial epithelial cell transcriptional responses to inhaled corticosteroids dictate severe asthmatic outcomes.

BACKGROUND: Inhaled corticosteroids (CSs) are the backbone of asthma treatment, improving quality of life, exacerbation rates, and mortality. Although effective for most, a subset of patients with asthma experience CS-resistant disease despite receiving high-dose medication. OBJECTIVE: We sought to investigate the transcriptomic response of bronchial epithelial cells (BECs) to inhaled CSs. METHODS: Independent component analysis was performed on datasets, detailing the transcriptional response of BECs to CS treatment. The expression of these CS-response components was examined in 2 patient cohorts and investigated in relation to clinical parameters. Supervised learning was used to predict BEC CS responses using peripheral blood gene expression. RESULTS: We identified a signature of CS response that was closely correlated with CS use in patients with asthma. Participants could be separated on the basis of CS-response genes into groups with high and low signature expression. Patients with low expression of CS-response genes, particularly those with a severe asthma diagnosis, showed worse lung function and quality of life. These individuals demonstrated enrichment for T-lymphocyte infiltration in endobronchial brushings. Supervised machine learning identified a 7-gene signature from peripheral blood that reliably identified patients with poor CS-response expression in BECs. CONCLUSIONS: Loss of CS transcriptional responses within bronchial epithelium was related to impaired lung function and poor quality of life, particularly in patients with severe asthma. These individuals were identified using minimally invasive blood sampling, suggesting these findings may enable earlier triage to alternative treatments.

Low CC16 mRNA Expression Levels in Bronchial Epithelial Cells Are Associated with Asthma Severity.

Rationale: CC16 is a protein mainly produced by nonciliated bronchial epithelial cells (BECs) that participates in host defense. Reduced CC16 protein concentrations in BAL and serum are associated with asthma susceptibility. Objectives: Few studies have investigated the relationship between CC16 and asthma progression, and none has focused on BECs. In this study, we sought to determine if CC16 mRNA expression levels in BECs are associated with asthma severity. Methods: Association analyses between CC16 mRNA expression levels in BECs (242 asthmatics and 69 control subjects) and asthma-related phenotypes in Severe Asthma Research Program were performed using a generalized linear model. Measurements and Main Results: Low CC16 mRNA expression levels in BECs were significantly associated with asthma susceptibility and asthma severity, high systemic corticosteroids use, high retrospective and prospective asthma exacerbations, and low pulmonary function. Low CC16 mRNA expression levels were significantly associated with high T2 inflammation biomarkers (fractional exhaled nitric oxide and sputum eosinophils). CC16 mRNA expression levels were negatively correlated with expression levels of Th2 genes (IL1RL1, POSTN, SERPINB2, CLCA1, NOS2, and MUC5AC) and positively correlated with expression levels of Th1 and inflammation genes (IL12A and MUC5B). A combination of two nontraditional T2 biomarkers (CC16 and IL-6) revealed four asthma endotypes with different characteristics of T2 inflammation, obesity, and asthma severity. Conclusions: Our findings indicate that low CC16 mRNA expression levels in BECs are associated with asthma susceptibility, severity, and exacerbations, partially through immunomodulation of T2 inflammation. CC16 is a potential nontraditional T2 biomarker for asthma development and progression.