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BACKGROUND: Race-specific spirometry reference equations are used globally to interpret lung function for clinical, research, and occupational purposes, but inclusion of race is under scrutiny. RESEARCH QUESTION: Does including self-identified race in spirometry reference equation formation improve the ability of predicted FEV1 values to explain quantitative chest CT abnormalities, dyspnea, or Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification? STUDY DESIGN AND METHODS: Using data from healthy adults who have never smoked in both the National Health and Nutrition Survey (2007-2012) and COPDGene study cohorts, race-neutral, race-free, and race-specific prediction equations were generated for FEV1. Using sensitivity/specificity, multivariable logistic regression, and random forest models, these equations were applied in a cross-sectional analysis to populations of individuals who currently smoke and individuals who formerly smoked to determine how they affected GOLD classification and the fit of models predicting quantitative chest CT phenotypes or dyspnea. RESULTS: Race-specific equations showed no advantage relative to race-neutral or race-free equations in models of quantitative chest CT phenotypes or dyspnea. Race-neutral reference equations reclassified up to 19% of Black participants into more severe GOLD classes, while race-neutral/race-free equations may improve model fit for dyspnea symptoms relative to race-specific equations. INTERPRETATION: Race-specific equations offered no advantage over race-neutral/race-free equations in three distinct explanatory models of dyspnea and chest CT scan abnormalities. Race-neutral/race-free reference equations may improve pulmonary disease diagnoses and treatment in populations highly vulnerable to lung disease.

The consequences of returning infectious pathogen test results identified incidentally in research studies have not been well-studied. Concerns include identification of an important health issue for individuals, accuracy of research test results, public health impact, potential emotional distress for participants, and need for IRB permissions. Blood RNA-sequencing analysis for non-human RNA in 3984 participants from the COPDGene study identified 228 participants with evidence suggestive for hepatitis C virus (HCV) infection. We hypothesized that incidentally discovered HCV results could be effectively returned to COPDGene participants with attention to the identified concerns. In conjunction with a COPDGene Participant Advisory Panel, we developed and obtained IRB approval for a process of returning HCV research results and an HCV Follow-Up Study questionnaire to capture information about previous HCV diagnosis and treatment information and participant reactions to return of HCV results. During phone calls following the initial HCV notification letter, 84 of 124 participants who could be contacted (67.7%) volunteered that they had been previously diagnosed with HCV infection. Thirty-one of these 124 COPDGene participants were enrolled in the HCV Follow-Up Study. Five of the 31 HCV Follow-Up Study participants did not report a previous diagnosis of HCV. For four of these participants, subsequent clinical HCV testing confirmed HCV infection. Thus, 30/31 Follow-Up Study participants had confirmed HCV diagnoses, supporting the accuracy of the HCV research test results. However, the limited number of participants in the Follow-Up Study precludes an accurate assessment of the false-positive and false-negative rates of the research RNA sequencing evidence for HCV. Most HCV Follow-Up Study participants (29/31) were supportive of returning HCV research results, and most participants found the process for returning HCV results to be informative and not upsetting. Newly diagnosed participants were more likely to be pleased to learn about a potentially curable infection (p = 0.027) and showed a trend toward being more frightened by the potential health risks of HCV (p = 0.11). We conclude that HCV results identified incidentally during transcriptomic research studies can be successfully returned to research study participants with a carefully designed process.

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.

BackgroundBronchodilator responsiveness (BDR) in obstructive lung disease varies over time and may be associated with distinct clinical features.Research questionIs consistent BDR over time (always present) differentially associated with obstructive lung disease features relative to inconsistent (sometimes present) or never (never present) BDR in tobacco-exposed people with or without COPD?Study design and methodsWe retrospectively analyzed data from 2,269 tobacco-exposed participants in the Subpopulations and Intermediate Outcome Measures in COPD Study with or without COPD. We used various BDR definitions: change of ≥ 200 mL and ≥ 12% in FEV1 (FEV1-BDR), change in FVC (FVC-BDR), and change in in FEV1, FVC or both (ATS-BDR). Using generalized linear models adjusted for demographics, smoking history, FEV1 % predicted after bronchodilator administration, and number of visits that the participant completed, we assessed the association of BDR group: (1) consistent BDR, (2) inconsistent BDR, and (3) never BDR with asthma, CT scan features, blood eosinophil levels, and FEV1 decline in participants without COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 0) and the entire cohort (participants with or without COPD).ResultsBoth consistent and inconsistent ATS-BDR were associated with asthma history and greater small airways disease (%parametric response mapping functional small airways disease) relative to never ATS-BDR in participants with GOLD stage 0 disease and the entire cohort. We observed similar findings using FEV1-BDR and FVC-BDR definitions. Eosinophils did not vary consistently among BDR groups. Consistent BDR was associated with FEV1 decline over time relative to never BDR in the entire cohort. In participants with GOLD stage 0 disease, both the inconsistent ATS-BDR group (OR, 3.20; 95% CI, 2.21-4.66; P < .001) and consistent ATS-BDR group (OR, 9.48; 95% CI, 3.77-29.12; P < .001) were associated with progression to COPD relative to the never ATS-BDR group.InterpretationDemonstration of BDR, even once, describes an obstructive lung disease phenotype with a history of asthma and greater small airways disease. Consistent demonstration of BDR indicated a high risk of lung function decline over time in the entire cohort and was associated with higher risk of progression to COPD in patients with GOLD stage 0 disease.

INTRODUCTION: Recent evidence suggests a high prevalence of undiagnosed chronic obstructive pulmonary disease (COPD). These individuals are at risk of exacerbations and delayed treatment. We analyzed an at-risk population for the prevalence of abnormal spirometry to provide clarity into who should undergo early spirometry. METHODS: We analyzed data from the COPDGene study. Participants with ≥10 pack-years of smoking were included. Individuals with self-reported or physician-diagnosed COPD, asthma, chronic bronchitis, emphysema and/or were on inhalers were excluded. Parsimonious multivariable logistic regression models identified factors associated with abnormal spirometry, defined as either airflow obstruction (AFO) or preserved ratio impaired spirometry. Variables were selected for the final model using a stepwise backward variable elimination process which minimized Akaike information criterion (AIC). Similarly, during the 5-year follow-up period, we assessed factors associated with incident diagnosis of COPD. RESULTS: Of 5055 individuals, 1064 (21%) had undiagnosed AFO. Age, pack-years, current smoking and a history of acute bronchitis were associated with AFO while body mass index, female sex, and Black race were inversely associated. Among 2800 participants with 5-year follow-up, 532 (19%) had an incident diagnosis of COPD. Associated risk factors included mMRC ≥2, chronic productive cough, respiratory exacerbations during the follow-up period, and abnormal spirometry. Age was inversely associated. CONCLUSIONS: The prevalence of undiagnosed COPD is high in at-risk populations. We found multiple factors associated with undiagnosed COPD and incident diagnosis of COPD at follow up. These results can be used to identify those at risk for undiagnosed COPD to facilitate earlier diagnosis and treatment.

BackgroundPrior studies have found that human immunodeficiency virus (HIV) infection is associated with impaired lung function and increased risk of chronic lung disease, but few have included large numbers of women. In this study, we investigate whether HIV infection is associated with differences in lung function in women.MethodsThis was a cross-sectional analysis of participants in the Women's Interagency HIV Study, a racially and ethnically diverse multicenter cohort of women with and without HIV. In 2018-2019, participants at 9 clinical sites were invited to perform spirometry. Single-breath diffusing capacity for carbon monoxide (DLCO) was also measured at selected sites. The primary outcomes were the post-bronchodilator forced expiratory volume in 1 second (FEV1) and DLCO. Multivariable regression modeling was used to analyze the association of HIV infection and lung function outcomes after adjustment for confounding exposures.ResultsFEV1 measurements from 1489 women (1062 with HIV, 427 without HIV) and DLCO measurements from 671 women (463 with HIV, 208 without HIV) met standards for quality and reproducibility. There was no significant difference in FEV1 between women with and without HIV. Women with HIV had lower DLCO measurements (adjusted difference, -0.73 mL/min/mm Hg; 95% confidence interval, -1.33 to -.14). Among women with HIV, lower nadir CD4 + cell counts and hepatitis C virus infection were associated with lower DLCO measurements.ConclusionsHIV was associated with impaired respiratory gas exchange in women. Among women with HIV, lower nadir CD4 + cell counts and hepatitis C infection were associated with decreased respiratory gas exchange.

BACKGROUND: Studies have shown that COPD and smoking are associated with increased suicide risk. To date, there are no prospective studies examining suicide risk among individuals with smoking exposure along a spectrum of pulmonary diseases ranging from normal spirometry to severe COPD. RESEARCH QUESTION: Which clinical variables predict death by suicide or overdose of indeterminate intent in a large cohort of individuals with smoking exposure within the Genetic Epidemiology of COPD (COPDGene) study? STUDY DESIGN AND METHODS: We studied data from 9,930 participants involved in COPDGene, a multisite, prospective cohort study of individuals with smoking exposure. Primary cause of adjudicated deaths was identified by using death certificates, family reports, and medical records. Time to death by suicide/overdose was examined as the primary outcome in Cox regression models including age, sex, race, BMI, pack-years, current smoking status, airflow limitation (FEV1 % predicted), dyspnea (modified Medical Research Council scale score ≥ 2), 6-min walk distance, supplemental oxygen use, and severe exacerbations in the prior year with time-varying covariates and other causes of death as a competing risk. RESULTS: The cohort was 47% female and 33% Black (67% White); they had a mean ± SD age of 59.6 ± 9.0 years and a mean FEV1 % predicted of 76.1 ± 25.5. Sixty-three individuals died by suicide/overdose. Factors associated with risk of suicide/overdose were current smoking (hazard ratio [HR], 6.44; 95% CI, 2.64-15.67), use of sedative/hypnotics (HR, 2.33; 95% CI, 1.24-4.38), and dyspnea (HR, 2.23; 95% CI, 1.34-3.70). Lower risk was associated with older age (per-decade HR, 0.45; 95% CI, 0.31-0.67), higher BMI (HR, 0.95; 95% CI, 0.91-0.99), and African-American race (HR, 0.41; 95% CI, 0.23-0.74). Severity of airflow limitation (FEV % predicted) was not associated with suicide risk. INTERPRETATION: In this well-characterized cohort of individuals with smoking exposure with and without COPD, risk factors for suicide/overdose were identified that emphasize the subjective experience of illness over objective assessments of lung function.

BACKGROUND: Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations. METHODS: We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores. FINDINGS: Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088). INTERPRETATION: CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations. FUNDING: National Institutes of Health and the National Heart, Lung, and Blood Institute.

BackgroundThe association between HIV and asthma prevalence and manifestations remains unclear, with few studies including women.SettingA retrospective observational cohort study from the Multicenter AIDS Cohort Study and Women's Interagency HIV Study.MethodsAsthma was defined in 2 ways: (1) self-report and (2) robust criteria requiring all the following: lack of fixed airflow obstruction, presence of wheeze on the St. George's Respiratory Questionnaire (SGRQ), and report of asthma therapies. Estimates of asthma prevalence and asthma-related manifestations were compared by HIV serostatus.ResultsA total of 1815 men and 2122 women were included. Asthma prevalence did not differ between people with HIV (PWH) and people without HIV regardless of definition: self-report (men, 12.0% vs. 11.2%; women, 24.3% vs. 27.5%) and robust criteria (men, 5.0% vs. 3.4%; women, 12.8% vs. 13.2%). Among men with asthma, worse respiratory symptom burden was reported among those with HIV, regardless of asthma definition. Among women with self-reported asthma, those with HIV had less respiratory symptom burden. Regardless of serostatus, women with robust-defined asthma had similar respiratory symptoms across SGRQ domains and similar frequencies of phlegm, shortness of breath, and wheezing.ConclusionsAmong PWH and people without HIV, asthma prevalence was 2-fold to 3-fold higher using self-reported definition rather than robust definition. In men and women, HIV was not associated with increased asthma prevalence. In men, HIV was associated with more respiratory symptoms when asthma was self-reported; the relationship was attenuated with the robust criteria. Further studies are needed to explore asthma phenotypes among PWH.

BackgroundImproved understanding of the pathways associated with airway pathophysiologic features in COPD will identify new predictive biomarkers and novel therapeutic targets.Research questionWhich physiologic pathways are altered in the airways of patients with COPD and will predict exacerbations?Study design and methodsWe applied a mass spectrometric panel of metabolomic biomarkers related to mucus hydration and inflammation to sputa from the multicenter Subpopulations and Intermediate Outcome Measures in COPD Study. Biomarkers elevated in sputa from patients with COPD were evaluated for relationships to measures of COPD disease severity and their ability to predict future exacerbations.ResultsSputum supernatants from 980 patients were analyzed: 77 healthy nonsmokers, 341 smokers with preserved spirometry, and 562 patients with COPD (178 with Global Initiative on Chronic Obstructive Lung Disease [GOLD] stage 1 disease, 303 with GOLD stage 2 disease, and 81 with GOLD stage 3 disease) were analyzed. Biomarkers from multiple pathways were elevated in COPD and correlated with sputum neutrophil counts. Among the most significant analytes (false discovery rate, 0.1) were sialic acid, hypoxanthine, xanthine, methylthioadenosine, adenine, and glutathione. Sialic acid and hypoxanthine were associated strongly with measures of disease severity, and elevation of these biomarkers was associated with shorter time to exacerbation and improved prediction models of future exacerbations.InterpretationBiomarker evaluation implicated pathways involved in mucus hydration, adenosine metabolism, methionine salvage, and oxidative stress in COPD airway pathophysiologic characteristics. Therapies that target these pathways may be of benefit in COPD, and a simple model adding sputum-soluble phase biomarkers improves prediction of pulmonary exacerbations.Trial registryClinicalTrials.gov; No.: NCT01969344; URL: www.Clinicaltrialsgov.

Chronic obstructive pulmonary disease (COPD) is a disease with marked metabolic disturbance. Previous studies have shown the association between single metabolites and lung function for COPD, but whether a combination of metabolites could predict phenotype is unknown. We developed metabolomic severity scores using plasma metabolomics from the Metabolon platform from two US cohorts of ever-smokers: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) (n = 648; training/testing cohort; 72% non-Hispanic, white; average age 63 years) and the COPDGene Study (n = 1120; validation cohort; 92% non-Hispanic, white; average age 67 years). Separate adaptive LASSO (adaLASSO) models were used to model forced expiratory volume at one second (FEV1) and MESA-adjusted lung density using 762 metabolites common between studies. Metabolite coefficients selected by the adaLASSO procedure were used to create a metabolomic severity score (metSS) for each outcome. A total of 132 metabolites were selected to create a metSS for FEV1. The metSS-only models explained 64.8% and 31.7% of the variability in FEV1 in the training and validation cohorts, respectively. For MESA-adjusted lung density, 129 metabolites were selected, and metSS-only models explained 59.0% of the variability in the training cohort and 17.4% in the validation cohort. Regression models including both clinical covariates and the metSS explained more variability than either the clinical covariate or metSS-only models (53.4% vs. 46.4% and 31.6%) in the validation dataset. The metabolomic pathways for arginine biosynthesis; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine pathway were enriched by adaLASSO metabolites for FEV1. This is the first demonstration of a respiratory metabolomic severity score, which shows how a metSS can add explanation of variance to clinical predictors of FEV1 and MESA-adjusted lung density. The advantage of a comprehensive metSS is that it explains more disease than individual metabolites and can account for substantial collinearity among classes of metabolites. Future studies should be performed to determine whether metSSs are similar in younger, and more racially and ethnically diverse populations as well as whether a metabolomic severity score can predict disease development in individuals who do not yet have COPD.

BackgroundLower heart rate (HR) increases during exercise and slower HR recovery (HRR) after exercise are markers of worse autonomic function that may be associated with risk of acute respiratory events (ARE).MethodsData from 6-min walk testing (6MWT) in COPDGene were used to calculate the chronotropic index (CI) [(HR immediately post 6MWT - resting HR)/((220 - age) - resting HR)] and HRR at 1 min after 6MWT completion. We used zero-inflated negative binomial regression to test associations of CI and HRR with rates of any ARE (requiring steroids and/or antibiotics) and severe ARE (requiring emergency department visit or hospitalization), among all participants and in spirometry subgroups (normal, chronic obstructive pulmonary disease [COPD], and preserved ratio with impaired spirometry).ResultsAmong 4,484 participants, mean follow-up time was 4.1 years, and 1,966 had COPD. Among all participants, CI-6MWT was not associated with rate of any ARE [adjusted incidence rate ratio (aIRR) 0.98 (0.95-1.01)], but higher CI-6MWT was associated with lower rate of severe ARE [0.95 (0.92-0.99)]. Higher HRR was associated with a lower rate of both any ARE [0.97 (0.95-0.99)] and severe ARE [0.95 (0.92-0.98)]. Results were similar in the COPD spirometry subgroup.ConclusionHeart rate measures derived from 6MWT tests may have utility in predicting risk of acute respiratory events and COPD exacerbations.

Rationale: Individuals with chronic obstructive pulmonary disease (COPD) have a high prevalence of depression, which is associated with increased COPD hospitalizations and readmissions. Objectives: Examine the impact of depressive symptoms compared with FEV1% on COPD morbidity. Methods: Using longitudinal data from individuals with COPD in the Subpopulations and Intermediate Outcome Measures in COPD Study, longitudinal growth analysis was performed to assess COPD morbidity by assessing differences in baseline 6-minute walk distance and patient reported outcomes (PROs) and their rate of change over time explained by depressive symptoms or lung function, as measured by Hospital Anxiety and Depression Scale or FEV1% respectively. PROs consisted of in-person completion of St. George's Respiratory Questionnaire, COPD Assessment Test, Functional Assessment of Chronic Illness Therapy Fatigue, and Modified Medical Research Council Dyspnea Scale measures. Results: Of the individuals analyzed (n = 1,830), 43% were female, 81% Caucasian with mean ± SD age of 65.1 ± 8.1, and 52.7 ± 27.5 pack-years smoking. Mean ± SD FEV1% was 60.9 ± 23.0% and 20% had clinically significant depressive symptoms. Adjusted models showed higher Hospital Anxiety and Depression Scale scores and lower FEV1% each were associated with worse PROs at baseline (P ⩽ 0.001). Depression accounted for more baseline variance in St. George's Respiratory Questionnaire, COPD Assessment Test, and Functional Assessment of Chronic Illness Therapy Fatigue than FEV1%, explaining 30-67% of heterogeneity. FEV1% accounted for more baseline variance in Modified Medical Research Council Dyspnea Scale and 6-minute walk distance than depression, explaining 16-32% of heterogeneity. Depressive symptoms accounted for 3-17% variance in change over time in PROs. In contrast, FEV1% accounted for 1-4% variance over time in PROs. Conclusions: Depression is more strongly associated with many PROs at baseline and their change over time compared with FEV1%. Recognizing and incorporating the impact of depressive symptoms into individualized care may improve COPD outcomes.

Rationale: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. Objectives: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. Methods: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. Measurements and Main Results: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV1% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV1 was 3.9% lower (95% confidence interval [CI], -6.55% to -1.26%) and emphysema (the percentage of lung attenuation areas

BackgroundChronic obstructive pulmonary disease (COPD) is the third leading cause of death globally. COPD patients with cachexia or weight loss have increased risk of death independent of body mass index (BMI) and lung function. We tested the hypothesis genetic variation is associated with weight loss in COPD using a genome-wide association study approach.MethodsParticipants with COPD (N = 4308) from three studies (COPDGene, ECLIPSE, and SPIROMICS) were analysed. Discovery analyses were performed in COPDGene with replication in SPIROMICS and ECLIPSE. In COPDGene, weight loss was defined as self-reported unintentional weight loss > 5% in the past year or low BMI (BMI

BackgroundAttenuation of transforming growth factor β by blocking angiotensin II has been shown to reduce emphysema in a murine model. General population studies have demonstrated that the use of angiotensin converting enzyme inhibitors (ACEis) and angiotensin-receptor blockers (ARBs) is associated with reduction of emphysema progression in former smokers and that the use of ACEis is associated with reduction of FEV1 progression in current smokers.Research questionIs use of ACEi and ARB associated with less progression of emphysema and FEV1 decline among individuals with COPD or baseline emphysema?MethodsFormer and current smokers from the Genetic Epidemiology of COPD Study who attended baseline and 5-year follow-up visits, did not change smoking status, and underwent chest CT imaging were included. Adjusted linear mixed models were used to evaluate progression of adjusted lung density (ALD), percent emphysema (%total lung volume

BackgroundSmokers manifest varied phenotypes of pulmonary impairment.Research questionWhich pulmonary phenotypes are associated with coronary artery disease (CAD) in smokers?Study design and methodsWe analyzed data from the University of Pittsburgh COPD Specialized Center for Clinically Oriented Research (SCCOR) cohort (n = 481) and the Genetic Epidemiology of COPD (COPDGene) cohort (n = 2,580). Participants were current and former smokers with > 10 pack-years of tobacco exposure. Data from the two cohorts were analyzed separately because of methodologic differences. Lung hyperinflation was assessed by plethysmography in the SCCOR cohort and by inspiratory and expiratory CT scan lung volumes in the COPDGene cohort. Subclinical CAD was assessed as the coronary artery calcium score, whereas clinical CAD was defined as a self-reported history of CAD or myocardial infarction (MI). Analyses were performed in all smokers and then repeated in those with airflow obstruction (FEV1 to FVC ratio, < 0.70).ResultsPulmonary phenotypes, including airflow limitation, emphysema, lung hyperinflation, diffusion capacity, and radiographic measures of airway remodeling, showed weak to moderate correlations (r < 0.7) with each other. In multivariate models adjusted for pulmonary phenotypes and CAD risk factors, lung hyperinflation was the only phenotype associated with calcium score, history of clinical CAD, or history of MI (per 0.2 higher expiratory and inspiratory CT scan lung volume; coronary calcium: OR, 1.2; 95% CI, 1.1-1.5; P = .02; clinical CAD: OR, 1.6; 95% CI, 1.1-2.3; P = .01; and MI in COPDGene: OR, 1.7; 95% CI, 1.0-2.8; P = .05). FEV1 and emphysema were associated with increased risk of CAD (P < .05) in models adjusted for CAD risk factors; however, these associations were attenuated on adjusting for lung hyperinflation. Results were the same in those with airflow obstruction and were present in both cohorts.InterpretationLung hyperinflation is associated strongly with clinical and subclinical CAD in smokers, including those with airflow obstruction. After lung hyperinflation was accounted for, FEV1 and emphysema no longer were associated with CAD. Subsequent studies should consider measuring lung hyperinflation and examining its mechanistic role in CAD in current and former smokers.

BackgroundPulmonary endothelial damage has been shown to precede the development of emphysema in animals, and vascular changes in humans have been observed in COPD and emphysema.Research questionIs intraparenchymal vascular pruning associated with longitudinal progression of emphysema on CT imaging or decline in lung function over 5 years?Study design and methodsThe Genetic Epidemiology of COPD Study enrolled ever smokers with and without COPD from 2008 through 2011. The percentage of emphysema-like lung, or "percent emphysema," was assessed at baseline and after 5 years on noncontrast CT imaging as the percentage of lung voxels < -950 Hounsfield units. An automated CT imaging-based tool assessed and classified intrapulmonary arteries and veins. Spirometry measures are postbronchodilator. Pulmonary arterial pruning was defined as a lower ratio of small artery volume (< 5 mm2 cross-sectional area) to total lung artery volume. Mixed linear models included demographics, anthropomorphics, smoking, and COPD, with emphysema models also adjusting for CT imaging scanner and lung function models adjusting for clinical center and baseline percent emphysema.ResultsAt baseline, the 4,227 participants were 60 ± 9 years of age, 50% were women, 28% were Black, 47% were current smokers, and 41% had COPD. Median percent emphysema was 2.1 (interquartile range, 0.6-6.3) and progressed 0.24 percentage points/y (95% CI, 0.22-0.26 percentage points/y) over 5.6 years. Mean FEV1 to FVC ratio was 68.5 ± 14.2% and declined 0.26%/y (95% CI, -0.30 to -0.23%/y). Greater pulmonary arterial pruning was associated with more rapid progression of percent emphysema (0.11 percentage points/y per 1-SD increase in arterial pruning; 95% CI, 0.09-0.16 percentage points/y), including after adjusting for baseline percent emphysema and FEV1. Arterial pruning also was associated with a faster decline in FEV1 to FVC ratio (-0.04%/y per 1-SD increase in arterial pruning; 95% CI, -0.008 to -0.001%/y).InterpretationPulmonary arterial pruning was associated with faster progression of percent emphysema and more rapid decline in FEV1 to FVC ratio over 5 years in ever smokers, suggesting that pulmonary vascular differences may be relevant in disease progression.Trial registryClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

BackgroundMild expiratory flow limitation may not be recognized using traditional spirometric criteria based on the ratio of FEV1/FVC.Research questionDoes slow vital capacity (SVC) instead of FVC increase the sensitivity of spirometry to identify patients with early or mild obstructive lung disease?Study design and methodsWe included 854 current and former smokers from the Subpopulations and Intermediate Outcome Measures in COPD Study cohort with a postbronchodilator FEV1/FVC ≥ 0.7 and FEV1 % predicted of ≥ 80% at enrollment. We compared baseline characteristics, chest CT scan features, exacerbations, and progression to COPD (postbronchodilator FEV1/FVC, < 0.7) during the follow-up period between 734 participants with postbronchodilator FEV1/SVC of ≥ 0.7 and 120 with postbronchodilator FEV1/SVC < 0.7 at the enrollment. We performed multivariate linear and logistic regression models and negative binomial and interval-censored proportion hazards regression models adjusted for demographics and smoking exposure to examine the association of FEV1/SVC < 0.7 with those characteristics and outcomes.ResultsParticipants with FEV1/SVC < 0.7 were older and had lower FEV1 and more emphysema than those with FEV1/SVC ≥ 0.7. In adjusted analysis, individuals with postbronchodilator FEV1/SVC < 0.7 showed a greater percentage of emphysema by 0.45% (95% CI, 0.09%-0.82%), percentage of gas trapping by 2.52% (95% CI, 0.59%-4.44%), and percentage of functional small airways disease based on parametric response mapping by 2.78% (95% CI, 0.72%-4.83%) at baseline than those with FEV1/SVC ≥ 0.7. During a median follow-up time of 1,500 days, an FEV1/SVC < 0.7 was not associated with total exacerbations (incident rate ratio [IRR], 1.61; 95% CI, 0.97-2.64), but was associated with severe exacerbations (IRR, 2.60; 95% CI, 1.04-4.89). An FEV1/SVC < 0.7 was associated with progression to COPD during a 3-year follow-up even after adjustment for demographics and smoking exposure (hazard ratio, 3.93; 95% CI, 2.71-5.72). We found similar results when we examined the association of prebronchodilator FEV1/SVC < 0.7 or FEV1/SVC less than the lower limit of normal with chest CT scan features and progression to COPD.InterpretationLow FEV1 to SVC in current and former smokers with normal spirometry results can identify individuals with CT scan features of COPD who are at risk for severe exacerbations and is associated with progression to COPD in the future.Trial registryClinicalTrials.gov; No.: NCT01969344T4; URL: www.clinicaltrials.gov.

Chronic obstructive pulmonary disease (COPD) is a common lung disease, and quantitative CT-based bronchial phenotypes are of increasing interest as a means of exploring COPD sub-phenotypes, establishing disease progression, and evaluating intervention outcomes. Reliable, fully automated, and accurate segmentation of pulmonary airway trees is critical to such exploration. We present a novel approach of multi-parametric freeze-and-grow (FG) propagation which starts with a conservative segmentation parameter and captures finer details through iterative parameter relaxation. First, a CT intensity-based FG algorithm is developed and applied for airway tree segmentation. A more efficient version is produced using deep learning methods generating airway lumen likelihood maps from CT images, which are input to the FG algorithm. Both CT intensity- and deep learning-based algorithms are fully automated, and their performance, in terms of repeat scan reproducibility, accuracy, and leakages, is evaluated and compared with results from several state-of-the-art methods including an industry-standard one, where segmentation results were manually reviewed and corrected. Both new algorithms show a reproducibility of 95% or higher for total lung capacity (TLC) repeat CT scans. Experiments on TLC CT scans from different imaging sites at standard and low radiation dosages show that both new algorithms outperform the other methods in terms of leakages and branch-level accuracy. Considering the performance and execution times, the deep learning-based FG algorithm is a fully automated option for large multi-site studies.

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) ( 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR

BackgroundRisk factor identification is a proven strategy in advancing treatments and preventive therapy for many chronic conditions. Quantifying the impact of those risk factors on health outcomes can consolidate and focus efforts on individuals with specific high-risk profiles. Using multiple risk factors and longitudinal outcomes in 2 independent cohorts, we developed and validated a risk score model to predict mortality in current and former cigarette smokers.MethodsWe obtained extensive data on current and former smokers from the COPD Genetic Epidemiology (COPDGene®) study at enrollment. Based on physician input and model goodness-of-fit measures, a subset of variables was selected to fit final Weibull survival models separately for men and women. Coefficients and predictors were translated into a point system, allowing for easy computation of mortality risk scores and probabilities. We then used the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) cohort for external validation of our model.ResultsOf 9867 COPDGene participants with standard baseline data, 17.6% died over 10 years of follow-up, and 9074 of these participants had the full set of baseline predictors (standard plus 6-minute walk distance and computed tomography variables) available for full model fits. The average age of participants in the cohort was 60 for both men and women, and the average predicted 10-year mortality risk was 18% for women and 25% for men. Model time-integrated area under the receiver operating characteristic curve statistics demonstrated good predictive model accuracy (0.797 average), validated in the external cohort (0.756 average). Risk of mortality was impacted most by 6-minute walk distance, forced expiratory volume in 1 second and age, for both men and women.ConclusionsCurrent and former smokers exhibited a wide range of mortality risk over a 10- year period. Our models can identify higher risk individuals who can be targeted for interventions to reduce risk of mortality, for participants with or without chronic obstructive pulmonary disease (COPD) using current Global initiative for obstructive Lung Disease (GOLD) criteria.

BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to identify these structural phenotypes.METHODSParticipants enrolled in a large multicenter study (COPDGene) were included. The data points from expiratory flow-volume curves were trained using a deep-learning model to predict structural phenotypes of chronic obstructive pulmonary disease (COPD) on CT, and results were compared with traditional spirometry metrics and an optimized random forest classifier. Area under the receiver operating characteristic curve (AUC) and weighted F-score were used to measure the discriminative accuracy of a fully convolutional neural network, random forest, and traditional spirometry metrics to phenotype CT as normal, emphysema-predominant (>5% emphysema), airway-predominant (Pi10 > median), and mixed phenotypes. Similar comparisons were made for the detection of functional small airway disease phenotype (>20% on parametric response mapping).RESULTSAmong 8980 individuals, the neural network was more accurate in discriminating predominant emphysema/airway phenotypes (AUC 0.80, 95%CI 0.79-0.81) compared with traditional measures of spirometry, FEV1/FVC (AUC 0.71, 95%CI 0.69-0.71), FEV1% predicted (AUC 0.70, 95%CI 0.68-0.71), and random forest classifier (AUC 0.78, 95%CI 0.77-0.79). The neural network was also more accurate in discriminating predominant emphysema/small airway phenotypes (AUC 0.91, 95%CI 0.90-0.92) compared with FEV1/FVC (AUC 0.80, 95%CI 0.78-0.82), FEV1% predicted (AUC 0.83, 95%CI 0.80-0.84), and with comparable accuracy with random forest classifier (AUC 0.90, 95%CI 0.88-0.91).CONCLUSIONSStructural phenotypes of COPD can be identified from spirometry using deep-learning and machine-learning approaches, demonstrating their potential to identify individuals for targeted therapies.TRIAL REGISTRATIONClinicalTrials.gov NCT00608764.FUNDINGThis study was supported by NIH grants K23 HL133438 and R21EB027891 and an American Thoracic Foundation 2018 Unrestricted Research Grant. The COPDGene study is supported by NIH grants NHLBI U01 HL089897 and U01 HL089856. The COPDGene study (NCT00608764) is also supported by the COPD Foundation through contributions made to an Industry Advisory Committee comprising AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Novartis, and Sunovion.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.

Rationale: The role of PI (protease inhibitor) type Z heterozygotes and additional rare variant genotypes in the gene encoding alpha-1 antitrypsin, SERPINA1 (serpin peptidase inhibitor, clade A, member 1), in determining chronic obstructive pulmonary disease risk and severity is controversial.Objectives: To comprehensively evaluate the effects of rare SERPINA1 variants on lung function and emphysema phenotypes in subjects with significant tobacco smoke exposure using deep gene resequencing and alpha-1 antitrypsin concentrations.Methods: DNA samples from 1,693 non-Hispanic white individuals, 385 African Americans, and 90 Hispanics with ≥20 pack-years smoking were resequenced for the identification of rare variants (allele frequency

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains

Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P

[This corrects the article DOI: 10.2147/COPD.S220164.].

BackgroundObservational studies suggest that beta-blockers may reduce the risk of exacerbations and death in patients with moderate or severe chronic obstructive pulmonary disease (COPD), but these findings have not been confirmed in randomized trials.MethodsIn this prospective, randomized trial, we assigned patients between the ages of 40 and 85 years who had COPD to receive either a beta-blocker (extended-release metoprolol) or placebo. All the patients had a clinical history of COPD, along with moderate airflow limitation and an increased risk of exacerbations, as evidenced by a history of exacerbations during the previous year or the prescribed use of supplemental oxygen. We excluded patients who were already taking a beta-blocker or who had an established indication for the use of such drugs. The primary end point was the time until the first exacerbation of COPD during the treatment period, which ranged from 336 to 350 days, depending on the adjusted dose of metoprolol.ResultsA total of 532 patients underwent randomization. The mean (±SD) age of the patients was 65.0±7.8 years; the mean forced expiratory volume in 1 second (FEV1) was 41.1±16.3% of the predicted value. The trial was stopped early because of futility with respect to the primary end point and safety concerns. There was no significant between-group difference in the median time until the first exacerbation, which was 202 days in the metoprolol group and 222 days in the placebo group (hazard ratio for metoprolol vs. placebo, 1.05; 95% confidence interval [CI], 0.84 to 1.32; P = 0.66). Metoprolol was associated with a higher risk of exacerbation leading to hospitalization (hazard ratio, 1.91; 95% CI, 1.29 to 2.83). The frequency of side effects that were possibly related to metoprolol was similar in the two groups, as was the overall rate of nonrespiratory serious adverse events. During the treatment period, there were 11 deaths in the metoprolol group and 5 in the placebo group.ConclusionsAmong patients with moderate or severe COPD who did not have an established indication for beta-blocker use, the time until the first COPD exacerbation was similar in the metoprolol group and the placebo group. Hospitalization for exacerbation was more common among the patients treated with metoprolol. (Funded by the Department of Defense; BLOCK COPD ClinicalTrials.gov number, NCT02587351.).

BackgroundChronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.MethodsFour key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.ResultsUsing smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.ConclusionsA substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.

BackgroundPulmonary and systemic inflammation are central features of chronic obstructive pulmonary disease (COPD). Previous studies have demonstrated relationships between biologically active extracellular matrix components, or matrikines, and COPD pathogenesis. We studied the relationships between the matrikine acetyl-proline-glycine-proline (AcPGP) in sputum and plasma and clinical features of COPD.MethodsSputum and plasma samples were obtained from COPD participants in the SPIROMICS cohort at enrollment. AcPGP was isolated using solid phase extraction and measured by mass spectrometry. Demographics, spirometry, quality of life questionnaires, and quantitative computed tomography (CT) imaging with parametric response mapping (PRM) were obtained at baseline. Severe COPD exacerbations were recorded at 1-year of prospective follow-up. We used linear and logistic regression models to measure associations between AcPGP and features of COPD, and Kaplan-Meier analyses to measure time-to-first severe exacerbation.ResultsThe 182 COPD participants in the analysis were 66 ± 8 years old, 62% male, 84% White race, and 39% were current smokers. AcPGP concentrations were 0.61 ± 1.89 ng/mL (mean ± SD) in sputum and 0.60 ± 1.13 ng/mL in plasma. In adjusted linear regression models, sputum AcPGP was associated with FEV1/FVC, spirometric GOLD stage, PRM-small airways disease, and PRM-emphysema. Sputum AcPGP also correlated with severe AECOPD, and elevated sputum AcPGP was associated with shorter time-to-first severe COPD exacerbation. In contrast, plasma AcPGP was not associated with symptoms, pulmonary function, or severe exacerbation risk.ConclusionsIn COPD, sputum but not plasma AcPGP concentrations are associated with the severity of airflow limitation, small airways disease, emphysema, and risk for severe AECOPD at 1-year of follow-up.Trial registrationClinicalTrials.gov: NCT01969344 (SPIROMICS).

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation. Spirometry loops are not smooth curves and have undulations and peaks that likely reflect heterogeneity of airflow.Objectives: To assess whether the Peak Index, the number of peaks adjusted for lung size, is associated with clinical outcomes.Methods: We analyzed spirometry data of 9,584 participants enrolled in the COPDGene study and counted the number of peaks in the descending part of the expiratory flow-volume curve from the peak expiratory flow to end-expiration. We adjusted the peaks count for the volume of the lungs from peak expiratory flow to end-expiration to derive the Peak Index. Multivariable regression analyses were performed to test associations between the Peak Index and lung function, respiratory morbidity, structural lung disease on computed tomography (CT), forced expiratory volume in 1 second (FEV1) decline, and mortality.Results: The Peak Index progressively increased from Global Initiative for Chronic Obstructive Lung Disease stage 0 through 4 (P

COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes.

Rationale: The American Thoracic Society (ATS)/European Respiratory Society defines a positive bronchodilator response (BDR) by a composite of BDR in either forced expiratory volume in 1 second (FEV1) and/or forced vital capacity (FVC) greater than or equal to 12% and 200 ml (ATS-BDR). We hypothesized that ATS-BDR components would be differentially associated with important chronic obstructive pulmonary disease (COPD) outcomes. Objectives: To examine whether ATS-BDR components are differentially associated with clinical, functional, and radiographic features in COPD. Methods: We included subjects with COPD enrolled in the COPDGene study. In the main analysis, we excluded subjects with self-reported asthma. We categorized BDR into the following: 1) No-BDR, no BDR in either FEV1 or FVC; 2) FEV1-BDR, BDR in FEV1 but no BDR in FVC; 3) FVC-BDR, BDR in FVC but no BDR in FEV1; and 4) Combined-BDR, BDR in both FEV1 and FVC. We constructed multivariable logistic, linear, zero-inflated negative binomial, and Cox hazards models to examine the association of BDR categories with symptoms, computed tomography findings, change in FEV1 over time, respiratory exacerbations, and mortality. We also created models using the ATS BDR definition (ATS-BDR) as the main independent variable. Results: Of 3,340 COPD subjects included in the analysis, 1,083 (32.43%) had ATS-BDR, 182 (5.45%) had FEV1-BDR, 522 (15.63%) had FVC-BDR, and 379 (11.34%) had Combined-BDR. All BDR categories were associated with FEV1 decline compared with No-BDR. Compared with No-BDR, both ATS-BDR and Combined-BDR were associated with higher functional residual capacity %predicted, greater internal perimeter of 10 mm, and greater 6-minute-walk distance. In contrast to ATS-BDR, Combined-BDR was independently associated with less emphysema (adjusted beta regression coefficient, -1.67; 95% confidence interval [CI], -2.68 to -0.65; P = 0.001), more frequent respiratory exacerbations (incidence rate ratio, 1.25; 95% CI, 1.03-1.50; P = 0.02) and severe exacerbations (incidence rate ratio, 1.34; 95% CI, 1.05-1.71; P = 0.02), and lower mortality (adjusted hazards ratio, 0.76; 95% CI, 0.58-0.99; P = 0.046). Sensitivity analysis that included subjects with self-reported history of asthma showed similar findings. Conclusions: BDR in both FEV1 and FVC indicates a COPD phenotype with asthma-like characteristics, and provides clinically more meaningful information than current definitions of BDR.

RATIONALE: There is an unmet need to investigate the lower airways in chronic obstructive pulmonary disease (COPD) to define pathogenesis and to identify potential markers to accelerate therapeutic development. Although bronchoscopy is well established to sample airways in various conditions, a comprehensive COPD research protocol has yet to be published. OBJECTIVES: To evaluate the safety and tolerability of a comprehensive research bronchoscopy procedure suitable for multicenter trials and to identify factors associated with adverse events. METHODS: We report the detailed methodology used to conduct the bronchoscopy used in SPIROMICS (the Subpopulations and Intermediate Outcome Measures in COPD Study). The protocol entailed collection of tongue scrapings and oral rinses as well as bronchoscopy with airway inspection, bronchoalveolar lavage (BAL), protected brushings, and endobronchial biopsies. Visual airway characteristics were graded on a scale of 0 (normal appearance) to 3 (severe abnormality) in four domains: erythema, edema, secretions, and friability. Adverse events were defined as events requiring intervention. Logistic regression modeling assessed associations between adverse event occurrence and key variables. RESULTS: We enrolled 215 participants. They were 61 ± 9 years old, 71% were white, 53% were male, and post-bronchodilator forced expiratory volume in 1 second was 89 ± 19% predicted. Self-reported asthma was present in 22% of bronchoscopy participants. Oral samples were obtained in greater than or equal to 99% of participants. Airway characteristics were recorded in 99% and were most often characterized as free of edema (61.9%). Less than 50% reported secretions, friability, or erythema. BAL yielded 111 ± 57 ml (50%) of the 223 ± 65 ml of infusate, brushes were completed in 98%, and endobronchial biopsies were performed in 82% of procedures. Adverse events requiring intervention occurred in 14 (6.7%) of 208 bronchoscopies. In logistic regression models, female sex (risk ratio [RR], 1.10; 95% confidence interval [CI], 1.02-1.19), self-reported asthma (RR, 1.17; 95% CI, 1.02-1.34), bronchodilator reversibility (RR, 1.17; 95% CI, 1.04-1.32), COPD (RR, 1.10; 95% CI, 1.02-1.20), forced expiratory volume in 1 second (RR, 0.97; 95% CI, 0.95-0.99), and secretions (RR, 1.85; 1.08-3.16) or friability (RR, 1.64; 95% CI, 1.04-2.57) observed during bronchoscopy were associated with adverse events. CONCLUSIONS: A research bronchoscopy procedure that includes oral sampling, BAL, endobronchial biopsy, and brushing can be safely performed. Airway characteristics during bronchoscopy, demographics, asthma or COPD, and lung function may convey increased risk for procedure-related events necessitating intervention.

ObjectiveBronchodilator responsiveness (BDR) is prevalent in COPD, but its clinical implications remain unclear. We explored the significance of BDR, defined by post-bronchodilator change in FEV1 (BDRFEV1) as a measure reflecting the change in flow and in FVC (BDRFVC) reflecting the change in volume.MethodsWe analyzed 2974 participants from a multicenter observational study designed to identify varying COPD phenotypes (SPIROMICS). We evaluated the association of BDR with baseline clinical characteristics, rate of prospective exacerbations and mortality using negative binomial regression and Cox proportional hazards models.ResultsA majority of COPD participants exhibited BDR (52.7%). BDRFEV1 occurred more often in earlier stages of COPD, while BDRFVC occurred more frequently in more advanced disease. When defined by increases in either FEV1 or FVC, BDR was associated with a self-reported history of asthma, but not with blood eosinophil counts. BDRFVC was more prevalent in subjects with greater emphysema and small airway disease on CT. In a univariate analysis, BDRFVC was associated with increased exacerbations and mortality, although no significance was found in a model adjusted for post-bronchodilator FEV1.ConclusionWith advanced airflow obstruction in COPD, BDRFVC is more prevalent in comparison to BDRFEV1 and correlates with the extent of emphysema and degree of small airway disease. Since these associations appear to be related to the impairment of FEV1, BDRFVC itself does not define a distinct phenotype nor can it be more predictive of outcomes, but it can offer additional insights into the pathophysiologic mechanism in advanced COPD.Clinical trials registrationClinicalTrials.gov: NCT01969344T4.

BACKGROUND:Chronic obstructive pulmonary disease (COPD) is associated with a two-to-five fold increase in the risk of coronary artery disease independent of shared risk factors. This association is hypothesized to be mediated by systemic inflammation but this link has not been established. METHODS:We included 300 participants enrolled in the SPIROMICS cohort, 75 each of lifetime non-smokers, smokers without airflow obstruction, mild-moderate COPD, and severe-very severe COPD. We quantified emphysema and airway disease on computed tomography, characterized visual emphysema subtypes (centrilobular and paraseptal) and airway disease, and used the Weston visual score to quantify coronary artery calcification (CAC). We used the Sobel test to determine whether markers of systemic inflammation mediated a link between spirometric and radiographic features of COPD and CAC. RESULTS:FEV1/FVC but not quantitative emphysema or airway wall thickening was associated with CAC (p = 0.036), after adjustment for demographics, diabetes mellitus, hypertension, statin use, and CT scanner type. To explain this discordance, we examined visual subtypes of emphysema and airway disease, and found that centrilobular emphysema but not paraseptal emphysema or bronchial thickening was independently associated with CAC (p = 0.019). MMP3, VCAM1, CXCL5 and CXCL9 mediated 8, 8, 7 and 16% of the association between FEV1/FVC and CAC, respectively. Similar biomarkers partially mediated the association between centrilobular emphysema and CAC. CONCLUSIONS:The association between airflow obstruction and coronary calcification is driven primarily by the centrilobular subtype of emphysema, and is linked through bioactive molecules implicated in the pathogenesis of atherosclerosis. TRIAL REGISTRATION:ClinicalTrials.gov: Identifier: NCT01969344 .