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Abstract Rationale Corticosteroids (CSs) are the most effective asthma therapy, but responses are heterogeneous and systemic CSs lead to long-term side effects. Therefore, an improved understanding of the contributing factors in CS responses could enhance precision management. Although several factors have been associated with CS responsiveness, no integrated/cluster approach has yet been undertaken to identify differential CS responses. Objectives To identify asthma subphenotypes with differential responses to CS treatment using an unsupervised multiview learning approach. Methods Multiple-kernel k-means clustering was applied to 100 clinical, physiological, inflammatory, and demographic variables from 346 adult participants with asthma in the Severe Asthma Research Program with paired (before and 2–3 weeks after triamcinolone administration) sputum data. Machine-learning techniques were used to select the top baseline variables that predicted cluster assignment for a new patient. Measurements and Main Results Multiple-kernel clustering revealed four clusters of individuals with asthma and different CS responses. Clusters 1 and 2 consisted of young, modestly CS-responsive individuals with allergic asthma and relatively normal lung function, separated by contrasting sputum neutrophil and macrophage percentages after CS treatment. The subjects in cluster 3 had late-onset asthma and low lung function, high baseline eosinophilia, and the greatest CS responsiveness. Cluster 4 consisted primarily of young, obese females with severe airflow limitation, little eosinophilic inflammation, and the least CS responsiveness. The top 12 baseline variables were identified, and the clusters were validated using an independent Severe Asthma Research Program test set. Conclusions Our machine learning–based approaches provide new insights into the mechanisms of CS responsiveness in asthma, with the potential to improve disease treatment.

Summary Background New evidence has suggested that people with asthma who are homozygous for arginine at aminoacid 16 of the β2 -adrenergic receptor (ADRB2) might not benefit from longacting β2 -agonist therapy. We, therefore, investigated whether ADRB2 polymorphisms affect response to longacting β2 -agonists in combination with inhaled corticosteroids. Methods Asthmatics were stratified by ADRB2 genotype in two studies to assess the effects of inhaled corticosteroids plus longacting β2 -agonists on asthma exacerbations. In study 1 (double-blind), 2250 asthmatics were randomly assigned to budesonide plus formoterol maintenance and reliever therapy, fixed-dose budesonide plus formoterol, or fixed-dose fluticasone plus salmeterol for 6 months. Study 2 (open-label) consisted of 405 asthmatics and compared an adjustable regimen of budesonide plus formoterol with fixed-dose budesonide plus formoterol and fixed-dose fluticasone plus salmeterol for 7 months. The relation between ADRB2 polymorphism, severe asthma exacerbations, and other asthma outcomes was analysed. Primary endpoints for studies 1 and 2 were severe asthma exacerbation and asthma control as assessed by measures of exacerbations, respectively. Findings In study 1, Gly16Arg genotype had no effect on the percentage of participants with severe exacerbations across all treatment groups (99 [12%] of 833 Gly/Gly, 110 [11%] of 1028 Gly/Arg, and 32 [9%] of 361 Arg/Arg participants). Secondary endpoints, including forced expiratory volume in 1 s, peak expiratory flow, use of as-needed medication, and number of nights with awakenings were similar between genotype groups. No relation was recorded between ADRB2 haplotype and primary and secondary endpoints. In study 2, the frequency of asthma exacerbations (15 [9%] of 168 Gly/Gly, 13 [8%] of 169 Gly/Arg, and 6 [9%] of 67 Arg/Arg participants) and other study endpoints were closely similar for all ADRB2 genotypes. Interpretation Since we showed no pharmacogenetic effect of ADRB2 variation on therapeutic response in asthma, patients, irrespective of their genotype, can continue to receive inhaled corticosteroids plus longacting β2 -agonists.

The National Heart, Lung, and Blood Institute has sponsored several asthma clinical networks, but the Severe Asthma Research Program (SARP) is unique, because it is not a clinical trials network, and it includes both adults and children. Investigators in SARP have comprehensively characterized 1,644 patients with asthma over the past 10 years, including 583 individuals with severe asthma and 300 children below the age of 18 years. The diversity in clinical characteristics, physiologic measures, and biomarkers in a large number of subjects across the ages provides an ideal cohort in which to investigate asthma heterogeneity. Using both biased and unbiased approaches, multiple asthma phenotypes have been described in SARP. These phenotypic analyses have improved our understanding of heterogeneity in asthma, and may provide a starting point to transform clinical practice through the evidence-based classification of disease severity. Although these new phenotypes strive to make order out of a heterogeneous group of patients, they are limited by that heterogeneity. There may be large groups of patients, especially those with milder asthma, that can be grouped into a clinical phenotype to guide therapy, but there will always be patients on the “edge” of a phenotype who will not fit into these groupings. In the SARP cluster analysis, subjects on the “edge” of a phenotype frequently had lung function that was better or worse than other subjects in the same cluster, despite similar clinical characteristics. This suggests that different pathophysiologic mechanisms may be responsible for decrements in lung function in some subjects. This is extremely important for subjects with severe asthma who may be on the “edge” of two phenotypes that may be driven by different pathobiologic mechanisms that warrant different therapeutic approaches.

Inducible nitric oxide synthase (iNOS) and arginase-2 (ARG2) share a common substrate, arginine. Higher expression of iNOS and exhaled NO are linked to airway inflammation in patients. iNOS deletion in animal models suggests that eosinophilic inflammation is regulated by arginine metabolism. Moreover, ARG2 is a regulator of Th2 response, as shown by the development of severe eosinophilic inflammation in ARG2 –/– mice. However, potential synergistic roles of iNOS and ARG2 in asthma have not been explored. Here, we hypothesized that arginine metabolic fate via iNOS and ARG2 may govern airway inflammation. In an asthma cohort, ARG2 variant genotypes were associated with arginase activity. ARG2 variants with lower arginase activity, combined with levels of exhaled NO, identified a severe asthma phenotype. Airway inflammation was present in WT, ARG2 –/– , iNOS –/– , and ARG2 –/– / iNOS –/– mice but was greatest in ARG2 –/– . Eosinophilic and neutrophilic infiltration in the ARG2 –/– mice was abrogated in ARG2 –/– / iNOS –/– animals. Similarly, angiogenic airway remodeling was greatest in ARG2 –/– mice. Cytokines driving inflammation and remodeling were highest in lungs of asthmatic ARG2 –/– mice and lowest in the iNOS –/– . ARG2 metabolism of arginine suppresses inflammation, while iNOS metabolism promotes airway inflammation, supporting a central role for arginine metabolic control of inflammation.

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 (FEV 1 ) 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 (FEV 1 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.

Background Transcriptomic analysis is common in large cohort studies but is generally restricted to cells in blood, which limits inferences about organs of interest, and direct organ sampling is mostly infeasible in large cohorts. New techniques for RNA-seq from noninvasive biosamples may provide the opportunity to profile transcriptomes of additional tissues for more organ-relevant insights at scale. We investigated the feasibility and utility of hair follicle gene expression profiling in a multi-center study of chronic obstructive pulmonary disease (COPD). Methods Bulk RNA-seq was performed on hair follicles collected in the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS), a multi-center longitudinal study of COPD ( n  = 97). The resulting hair follicle gene expression data were characterized and compared both to gene expression in whole blood and bronchial epithelium previously measured in SPIROMICS and to Genotype-Tissue Expression (GTEx) project tissue gene expression by principal component analysis and single-sample gene enrichment analysis, used to estimate hair follicle cell type proportions, and tested for association with disease-relevant lung phenotypes. eQTL discovery was also performed and colocalization with a genome-wide association study for lung function was tested. Results Hair follicles reliably produced transcriptomic data of sufficient quality and number for cell type composition, which revealed mostly epithelial and fibroblast cells. Comparison to other tissues previously profiled in SPIROMICS and GTEx project demonstrated transcriptomes from hair follicles were much more similar to those from lung parenchyma than blood. Combining these data with rich clinical, imaging, and genomic profiling in SPIROMICS, we found that they provided an attractive approach for discovery of associations with complex lung phenotypes, particularly of the airways. Finally, we investigated hair follicle genetic architecture through expression quantitative trait locus (eQTL) discovery and demonstrated better colocalization with lung-related genetic associations than blood. Conclusion Here, we demonstrated that RNA-seq applied to hair follicle transcriptomic profiling can be scaled up successfully in a multi-center study to yield inferences not available from blood transcriptomics.

Background The aim of this study is to identify genetic loci associated with post-bronchodilator FEV 1 /FVC and FEV 1 , and develop a multi-gene predictive model for lung function in COPD. Methods Genome-wide association study (GWAS) of post-bronchodilator FEV 1 /FVC and FEV 1 was performed in 1645 non-Hispanic White European descent smokers. Results A functional rare variant in SERPINA1 (rs28929474: Glu342Lys) was significantly associated with post-bronchodilator FEV 1 /FVC ( p  = 1.2 × 10 − 8 ) and FEV 1 ( p  = 2.1 × 10 − 9 ). In addition, this variant was associated with COPD (OR = 2.3; p  = 7.8 × 10 − 4 ) and severity (OR = 4.1; p  = 0.0036). Heterozygous subjects (CT genotype) had significantly lower lung function and higher percentage of COPD and more severe COPD than subjects with the CC genotype. 8.6% of the variance of post-bronchodilator FEV 1 /FVC can be explained by SNPs in 10 genes with age, sex, and pack-years of cigarette smoking ( P  <  2.2 × 10 − 16 ). Conclusions This study is the first to show genome-wide significant association of rs28929474 in SERPINA1 with lung function. Of clinical importance, heterozygotes of rs28929474 (4.7% of subjects) have significantly reduced pulmonary function, demonstrating a major impact in smokers. The multi-gene model is significantly associated with CT-based emphysema and clinical outcome measures of severity. Combining genetic information with demographic and environmental factors will further increase the predictive power for assessing reduced lung function and COPD severity.

John Novembre and colleagues present a new approach for constructing recombination maps based on ancestry switch points among individuals. They construct a high-resolution genome-wide recombination map based on admixed African-American and African-Caribbean individuals and compare this to previous recombination maps. Studies of recombination and how it varies depend crucially on accurate recombination maps. We propose a new approach for constructing high-resolution maps of relative recombination rates based on the observation of ancestry switch points among admixed individuals. We show the utility of this approach using simulations and by applying it to SNP genotype data from a sample of 2,565 African Americans and 299 African Caribbeans and detecting several hundred thousand recombination events. Comparison of the inferred map with high-resolution maps from non-admixed populations provides evidence of fine-scale differentiation in recombination rates between populations. Overall, the admixed map is well predicted by the average proportion of admixture and the recombination rate estimates from the source populations. The exceptions to this are in areas surrounding known large chromosomal structural variants, specifically inversions. These results suggest that outside of structurally variable regions, admixture does not substantially disrupt the factors controlling recombination rates in humans.

We used a deeply sequenced dataset of 910 individuals, all of African descent, to construct a set of DNA sequences that is present in these individuals but missing from the reference human genome. We aligned 1.19 trillion reads from the 910 individuals to the reference genome (GRCh38), collected all reads that failed to align, and assembled these reads into contiguous sequences (contigs). We then compared all contigs to one another to identify a set of unique sequences representing regions of the African pan-genome missing from the reference genome. Our analysis revealed 296,485,284 bp in 125,715 distinct contigs present in the populations of African descent, demonstrating that the African pan-genome contains ~10% more DNA than the current human reference genome. Although the functional significance of nearly all of this sequence is unknown, 387 of the novel contigs fall within 315 distinct protein-coding genes, and the rest appear to be intergenic. Assembly of a pan-genome from 910 humans of African descent identifies 296.5 Mb of novel DNA mapping to 125,715 distinct contigs. This African pan-genome contains ~10% more DNA than the current human reference genome.

The link between mucus plugs and airflow obstruction has not been established in chronic severe asthma, and the role of eosinophils and their products in mucus plug formation is unknown. In clinical studies, we developed and applied a bronchopulmonary segment-based scoring system to quantify mucus plugs on multidetector computed tomography (MDCT) lung scans from 146 subjects with asthma and 22 controls, and analyzed relationships among mucus plug scores, forced expiratory volume in 1 second (FEV1), and airway eosinophils. Additionally, we used airway mucus gel models to explore whether oxidants generated by eosinophil peroxidase (EPO) oxidize cysteine thiol groups to promote mucus plug formation. Mucus plugs occurred in at least 1 of 20 lung segments in 58% of subjects with asthma and in only 4.5% of controls, and the plugs in subjects with asthma persisted in the same segment for years. A high mucus score (plugs in ≥ 4 segments) occurred in 67% of subjects with asthma with FEV1 of less than 60% of predicted volume, 19% with FEV1 of 60%-80%, and 6% with FEV1 greater than 80% (P < 0.001) and was associated with marked increases in sputum eosinophils and EPO. EPO catalyzed oxidation of thiocyanate and bromide by H2O2 to generate oxidants that crosslink cysteine thiol groups and stiffen thiolated hydrogels. Mucus plugs are a plausible mechanism of chronic airflow obstruction in severe asthma, and EPO-generated oxidants may mediate mucus plug formation. We propose an approach for quantifying airway mucus plugging using MDCT lung scans and suggest that treating mucus plugs may improve airflow in chronic severe asthma. Clinicaltrials.gov NCT01718197, NCT01606826, NCT01750411, NCT01761058, NCT01761630, NCT01759186, NCT01716494, and NCT01760915. NIH grants P01 HL107201, R01 HL080414, U10 HL109146, U10 HL109164, U10 HL109172, U10 HL109086, U10 HL109250, U10 HL109168, U10 HL109257, U10 HL109152, and P01 HL107202 and National Center for Advancing Translational Sciences grants UL1TR0000427, UL1TR000448, and KL2TR000428.