Asthma control in the United States: relationships between short-acting ß2-agonist and systemic corticosteroid use.

BACKGROUND: Asthma control assessment is based on impairment (current symptoms) and risk (exacerbation history). OBJECTIVE: To understand the extent of uncontrolled asthma, we assessed relationships between prescription fills for systemic corticosteroids (SCS) and short-acting ß2-agonists (SABA) as risk and impairment markers, respectively. METHODS: Annual SCS and SABA fills among US patients with asthma were evaluated by a retrospective analysis of IQVIA Longitudinal Access and Adjudication Data. Patient severity was assigned based on GINA step-therapy level. Exacerbations were evaluated by SCS fills within 12 months of a first asthma prescription fill. Uncontrolled asthma was defined as ≥2 SCS and/or ≥3 SABA fills annually. Individual patient relationships between SCS and SABA fills were assessed by Pearson's correlation coefficient. RESULTS: 4,506,527 patients were included: 15% had ≥2 SCS fills, 29% had ≥3 SABA fills, 37% fulfilled either or both criteria. If only SCS were assessed, 22% treated as mild-to-moderate and 27% as severe asthma would have been misclassified as controlled. If only SABA use was evaluated, 8% treated as mild-to-moderate and 11% as severe asthma would have been misclassified. Overall, 81% of uncontrolled asthma occurred in patients treated for mild-to-moderate disease. Among patients with ≥2 SCS fills, mean SABA fills were 2.9; the correlation between SCS and SABA fills per patient was significant but weak (r=0.18; p<0.001). CONCLUSION: High symptom burden and SCS exposures are not limited to severe asthma but are also characteristic in patients treated for mild-to-moderate disease. Both impairment and risk assessments are required to understand the full extent of uncontrolled asthma across disease severities.

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.

Utility of eosinophil peroxidase as a biomarker of eosinophilic inflammation in asthma.

BACKGROUND: The relative utility of eosinophil peroxidase (EPX) and blood and sputum eosinophil counts as disease biomarkers in asthma is uncertain. OBJECTIVE: To determine the utility of EPX as a biomarker of systemic and airway eosinophilic inflammation in asthma. METHODS: EPX protein was measured by immunoassay in serum and sputum in 110 healthy controls to establish a normal reference range and in repeated samples of serum and sputum collected during three years of observation in 480 participants in the Severe Asthma Research Program (SARP)-3. RESULTS: Over three years, EPX levels in asthma patients were higher than normal in 27-31% of serum samples and 36-53% of sputum samples. Eosinophils and EPX correlated better in blood than in sputum (rs values of 0.74 and 0.43, respectively), and high sputum EPX levels occurred in 27% of participants with blood eosinophil counts < 150 cells/uL and 42% of participants with blood eosinophil counts 150-299 cells/uL. Patients with persistently high sputum EPX values for three years were characterized by severe airflow obstruction, frequent exacerbations, and high mucus plug scores. In 59 asthma patients who started mepolizumab during observation, serum EPX levels normalized in 96% but sputum EPX normalized in only 49%. Lung function remained abnormal even when sputum EPX normalized. CONCLUSION: Serum EPX is a valid protein biomarker of systemic eosinophilic inflammation in asthma, and sputum EPX levels are a more sensitive biomarker of airway eosinophilic inflammation than sputum eosinophil counts. Eosinophil measures in blood frequently miss airway eosinophilic inflammation, and mepolizumab frequently fails to normalize airway eosinophilic inflammation even though it invariably normalizes systemic eosinophilic inflammation.

A Novel DNase Assay Reveals Low DNase Activity in Severe Asthma.

Secreted deoxyribonucleases (DNases), such as DNase-1 and DNase-IL3, degrade extracellular DNA, and endogenous DNases have roles in resolving airway inflammation and guarding against autoimmune responses to nucleotides. Subsets of patients with asthma have high airway DNA levels, but information about DNase activity in health and in asthma is lacking. To characterize DNase activity in health and in asthma, we developed a novel kinetic assay using a Taqman probe sequence that is quickly cleaved by DNase-I to produce a large product signal. We used this kinetic assay to measure DNase activity in sputum from participants in the Severe Asthma Research Program (SARP)-3 (n=439) and from healthy controls (n=89). We found that DNase activity was lower than normal in asthma (78.7 RFU/min vs 120.4 RFU/min, p<0.0001). Compared to asthma patients with sputum DNase activity levels in the upper tertile activity levels, those in the lower tertile of sputum DNase activity were characterized clinically by more severe disease and pathologically by airway eosinophilia and airway mucus plugging. Carbamylation of DNase-I, a post translational modification that can be mediated by eosinophil peroxidase, inactivated DNase-I. In summary, a Taqman probe-based DNase activity assay uncovers low DNase activity in the asthma airway which is associated with more severe disease and airway mucus plugging and may be caused, at least in part, by eosinophil-mediated carbamylation.

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

BACKGROUND: Asthma classification into different sub-phenotypes is important to guide personalized therapy and improve outcomes. OBJECTIVES: This study sought 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 employed k-prototype unsupervised ML to develop a clustering model where predictors were age, gender, race, body mass index (BMI), pre- and post-bronchodilator (BD) 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 post-BD spirometry measurements were extracted to identify 5 stable clusters. Cluster 1 included a young non-severe asthma population with normal lung function and higher frequency of acute exacerbation (0.8 /patient-year). Cluster 2 had the highest BMI (mean (SD): 44.44 (7.83) kg/m2), and the highest proportion of female (77.5%) and African Americans (28.9%). Cluster 3 comprised patients with normal lung function. Cluster 4 included patients with lower FEV1% of 77.03 (12.79) and poor response to bronchodilators. Cluster 5 had the lowest FEV1% of 68.08 (15.02), the highest post-BD reversibility, and the highest proportion of severe asthma (44.9%) and blood eosinophilia (>300 cells/µL) (34.8%). CONCLUSION: Using real-world data and unsupervised ML, we classified asthma into 5 clinically important sub-phenotypes 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.

Loss of Airway Phylogenetic Diversity Is Associated with Clinical and Pathobiological Markers of Disease Development in COPD.

RATIONALE: The airway microbiome has the potential to shape COPD pathogenesis, but its relationship to outcomes in milder disease is unestablished. OBJECTIVES: Identify sputum microbiome characteristics associated with markers of COPD in participants of the SubPopulations and InteRmediate Outcome Measures of COPD Study (SPIROMICS). METHODS: Sputum DNA from 877 participants were analyzed using 16S rRNA gene sequencing. Relationships between baseline airway microbiota composition and clinical, radiographic and muco-inflammatory markers, including longitudinal lung function trajectory, were examined. MEASUREMENTS AND MAIN RESULTS: Participant data represented predominantly milder disease (GOLD 0-2: N=732/877). Phylogenetic diversity (range of different species within a sample) correlated positively with baseline lung function, declined with higher GOLD stage, and correlated negatively with symptom burden, radiographic markers of airway disease, and total mucin concentrations (p<0.001). In co-variate adjusted regression models, organisms robustly associated with better lung function included members of Alloprevotella, Oribacterium, and Veillonella. Conversely, lower lung function, greater symptoms and radiographic measures of small airway disease associated with enrichment in members of Streptococcus, Actinobacillus, Actinomyces, and other genera. Baseline sputum microbiota features also associated with lung function trajectory during SPIROMICS follow up (stable/improved, decliner, or rapid decliner). The 'stable/improved' group (slope of FEV1 regression ≥ 66th percentile) had higher bacterial diversity at baseline, associated with enrichment in Prevotella, Leptotrichia, and Neisseria. In contrast, the 'rapid decliner' group (FEV1 slope ≤ 33rd percentile) had significantly lower baseline diversity, associated with enrichment in Streptococcus. CONCLUSIONS: In SPIROMICS baseline airway microbiota features demonstrate divergent associations with better or worse COPD-related outcomes.

Real-world effectiveness of dupilumab in patients with asthma: Findings from the US ADVANTAGE study.

BACKGROUND: Dupilumab is approved as an add-on maintenance therapy for patients (≥6 years) with moderate-to-severe asthma. Better understanding of real-world effectiveness is needed. OBJECTIVE: To characterize the real-world effectiveness of dupilumab in asthma management. METHODS: This retrospective study included patients (≥12 years of age) diagnosed with asthma, initiating dupilumab between November 2018 and September 2020. The study used a US electronic medical record database (TriNetX Dataworks, Cambridge, Massachusetts). Asthma exacerbation rates before and after the initiation of dupilumab were analyzed using generalized estimating equations models with Poisson probabilistic link to estimate incidence rate ratios (IRRs). Sensitivity analyses were conducted based on previous exacerbation data, eosinophil levels, history of atopic dermatitis or chronic rhinosinusitis with nasal polyps, previous use of biologics, and presence of SARS-CoV-2 (COVID-19). RESULTS: A total of 2400 patients initiating dupilumab met all study criteria. After initiation of dupilumab, risk of asthma exacerbation was reduced by 44% (IRR, 0.56; 95% CI, 0.47-0.57; P = <0.0001) and systemic corticosteroid prescriptions by 48% (IRR, 0.52; 95% CI, 0.48, 0.56; P = <0.0001) compared with those before initiation of dupilumab. Adjustment for COVID-19 showed a greater reduction in asthma exacerbations (IRR, 0.50; 95% CI, 0.45-0.55; P = <0.0001). CONCLUSION: Current real-world efficacy evidence indicates that dupilumab reduces asthma exacerbations and total systemic corticosteroid prescriptions in clinical practice. The effectiveness of dupilumab was observed independent of exacerbation history, eosinophil levels, or COVID-19 impact.

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.

Dupilumab Efficacy in Patients with Type 2 Asthma with and without Elevated Blood Neutrophils.

Introduction: Elevated neutrophil counts in blood, sputum, or lung have been associated with poor clinical outcomes and more severe disease in patients with type 2 asthma. In the phase 3 LIBERTY ASTHMA QUEST (NCT02414854), add-on dupilumab 200 and 300 mg every 2 weeks compared with matched placebo significantly reduced severe asthma exacerbations and improved forced expiratory volume in 1 s (FEV1) in patients with uncontrolled, moderate-to-severe asthma. This post hoc analysis explored the efficacy of dupilumab in patients with type 2 asthma enrolled in QUEST with or without elevated blood neutrophil counts. Methods: Annualized severe exacerbation rates during the 52-week treatment period and least-squares mean change from baseline in FEV1 over time were evaluated for patients with elevated type 2 biomarkers at baseline (blood eosinophils ≥ 150 cells/µL or fractional exhaled nitric oxide (FeNO) ≥ 20 ppb; and eosinophils ≥ 300 cells/µL or FeNO ≥ 50 ppb) and low (<4,000 cells/µL) or high (≥4,000 cells/µL) neutrophil counts. Results: Dupilumab significantly reduced annualized severe exacerbation rates compared with placebo during the 52-week treatment period in patients with elevated type 2 biomarkers, irrespective of baseline neutrophil count (P < 0.0001 for all comparisons). Significant improvements in FEV1 versus placebo were observed as early as Week 2 and over the 52-week treatment period, irrespective of baseline neutrophil count (P < 0.001 for all comparisons). Safety findings were similar across all subgroups, regardless of neutrophil counts at baseline. Conclusions: Dupilumab treatment significantly reduced annualized severe exacerbation rates and improved lung function in patients with uncontrolled, moderate-to-severe, type 2 asthma, irrespective of baseline blood neutrophil count. This trial is registered with NCT02414854.

Longitudinal Follow-Up of Participants With Tobacco Exposure and Preserved Spirometry.

Importance: People who smoked cigarettes may experience respiratory symptoms without spirometric airflow obstruction. These individuals are typically excluded from chronic obstructive pulmonary disease (COPD) trials and lack evidence-based therapies. Objective: To define the natural history of persons with tobacco exposure and preserved spirometry (TEPS) and symptoms (symptomatic TEPS). Design, Setting, and Participants: SPIROMICS II was an extension of SPIROMICS I, a multicenter study of persons aged 40 to 80 years who smoked cigarettes (>20 pack-years) with or without COPD and controls without tobacco exposure or airflow obstruction. Participants were enrolled in SPIROMICS I and II from November 10, 2010, through July 31, 2015, and followed up through July 31, 2021. Exposures: Participants in SPIROMICS I underwent spirometry, 6-minute walk distance testing, assessment of respiratory symptoms, and computed tomography of the chest at yearly visits for 3 to 4 years. Participants in SPIROMICS II had 1 additional in-person visit 5 to 7 years after enrollment in SPIROMICS I. Respiratory symptoms were assessed with the COPD Assessment Test (range, 0 to 40; higher scores indicate more severe symptoms). Participants with symptomatic TEPS had normal spirometry (postbronchodilator ratio of forced expiratory volume in the first second [FEV1] to forced vital capacity >0.70) and COPD Assessment Test scores of 10 or greater. Participants with asymptomatic TEPS had normal spirometry and COPD Assessment Test scores of less than 10. Patient-reported respiratory symptoms and exacerbations were assessed every 4 months via phone calls. Main Outcomes and Measures: The primary outcome was assessment for accelerated decline in lung function (FEV1) in participants with symptomatic TEPS vs asymptomatic TEPS. Secondary outcomes included development of COPD defined by spirometry, respiratory symptoms, rates of respiratory exacerbations, and progression of computed tomographic-defined airway wall thickening or emphysema. Results: Of 1397 study participants, 226 had symptomatic TEPS (mean age, 60.1 [SD, 9.8] years; 134 were women [59%]) and 269 had asymptomatic TEPS (mean age, 63.1 [SD, 9.1] years; 134 were women [50%]). At a median follow-up of 5.76 years, the decline in FEV1 was -31.3 mL/y for participants with symptomatic TEPS vs -38.8 mL/y for those with asymptomatic TEPS (between-group difference, -7.5 mL/y [95% CI, -16.6 to 1.6 mL/y]). The cumulative incidence of COPD was 33.0% among participants with symptomatic TEPS vs 31.6% among those with asymptomatic TEPS (hazard ratio, 1.05 [95% CI, 0.76 to 1.46]). Participants with symptomatic TEPS had significantly more respiratory exacerbations than those with asymptomatic TEPS (0.23 vs 0.08 exacerbations per person-year, respectively; rate ratio, 2.38 [95% CI, 1.71 to 3.31], P < .001). Conclusions and Relevance: Participants with symptomatic TEPS did not have accelerated rates of decline in FEV1 or increased incidence of COPD vs those with asymptomatic TEPS, but participants with symptomatic TEPS did experience significantly more respiratory exacerbations over a median follow-up of 5.8 years.

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.

Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans.

BACKGROUND: Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations. METHODS: New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined. RESULTS: The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome. CONCLUSION: Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

Changes in Lung Volumes with Spirometric Disease Progression in COPD.

Background: Abnormal lung volumes representing air trapping identify the subset of smokers with preserved spirometry who develop spirometric chronic obstructive pulmonary disease (COPD) and adverse outcomes. However, how lung volumes evolve in early COPD as airflow obstruction develops remains unclear. Methods: To establish how lung volumes change with the development of spirometric COPD, we examined lung volumes from the pulmonary function data (seated posture) available in the U.S. Department of Veterans Affairs electronic health records (n=71,356) and lung volumes measured by computed tomography (supine posture) available from the COPD Genetic Epidemiology (COPDGene®) study (n=7969) and the SubPopulations and InterMediate Outcome Measures In COPD Study (SPIROMICS) (n=2552) cohorts, and studied their cross-sectional distributions and longitudinal changes across the airflow obstruction spectrum. Patients with preserved ratio-impaired spirometry (PRISm) were excluded from this analysis. Results: Lung volumes from all 3 cohorts showed similar patterns of distributions and longitudinal changes with worsening airflow obstruction. The distributions for total lung capacity (TLC), vital capacity (VC), and inspiratory capacity (IC) and their patterns of change were nonlinear and included different phases. When stratified by airflow obstruction using Global initiative for chronic Obstructive Lung Disease (GOLD) stages, patients with GOLD 1 (mild) COPD had larger lung volumes (TLC, VC, IC) compared to patients with GOLD 0 (smokers with preserved spirometry) or GOLD 2 (moderate) disease. In longitudinal follow-up of baseline GOLD 0 patients who progressed to spirometric COPD, those with an initially higher TLC and VC developed mild obstruction (GOLD 1) while those with an initially lower TLC and VC developed moderate obstruction (GOLD 2). Conclusions: In COPD, TLC, and VC have biphasic distributions, change in nonlinear fashions as obstruction worsens, and could differentiate those GOLD 0 patients at risk for more rapid spirometric disease progression.