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Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate the clinical and imaging significance of increasing emphysema severity as graded by a deep learning algorithm on sequential CT scans in cigarette smokers. Materials and Methods A secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study participants was performed and included baseline and 5-year follow-up CT scans from 2007 to 2017. Emphysema was classified automatically according to the Fleischner emphysema grading system at baseline and 5-year follow-up using a deep learning model. Baseline and change in clinical and imaging parameters at 5-year follow-up were compared in participants whose emphysema progressed versus those who did not. Kaplan-Meier analysis and multivariable Cox regression were used to assess the relationship between emphysema score progression and mortality. Results A total of 5056 participants (mean age, 60 years ± 9 [SD]; 2566 men) were evaluated. At 5-year follow-up, 1293 of the 5056 participants (26%) had emphysema progression according to the Fleischner grading system. This group demonstrated progressive airflow obstruction (forced expiratory volume in 1 second [percent predicted]: -3.4 vs -1.8), a greater decline in 6-minute walk distance (-177 m vs -124 m), and greater progression in quantitative emphysema extent (adjusted lung density: -1.4 g/L vs 0.5 g/L; percentage of lung voxels with CT attenuation less than -950 HU: 0.6 vs 0.2) than those with nonprogressive emphysema (

BACKGROUND: Emerging data from longitudinal studies suggest that preserved ratio impaired spirometry (PRISm), defined by proportionate reductions in FEV(1) and FVC, is a heterogeneous population with frequent transitions to other lung function categories relative to individuals with normal and obstructive spirometry. Controversy regarding the clinical significance of these transitions exists (eg, whether transitions merely reflect measurement variability or noise). RESEARCH QUESTION: Are individuals with PRISm enriched for transitions associated with substantial changes in lung function? STUDY DESIGN AND METHODS: Current and former smokers enrolled in the Genetic Epidemiology of COPD (COPDGene) study with spirometry available in phases 1 through 3 (enrollment, 5-year follow-up, and 10-year follow-up) were analyzed. Postbronchodilator lung function categories were as follows: PRISm (FEV(1) < 80% predicted with FEV(1)/FVC ratio ≥ 0.7), Global Initiative for Chronic Obstructive Lung Disease grade 0 (FEV(1) ≥ 80% predicted and FEV(1)/FVC ≥ 0.7), and obstruction (FEV(1)/FVC < 0.7). Significant transition status was affirmative if a subject belonged to two or more spirometric categories and had > 10% change in FEV(1) % predicted and/or FVC % predicted between consecutive visits. Ever-PRISm was present if a subject had PRISm at any visit. Logistic regression examined the association between significant transitions and ever-PRISm status, adjusted for age, sex, race, FEV(1) % predicted, current smoking, pack-years, BMI, and ever-positive bronchodilator response. RESULTS: Among subjects with complete data (N = 1,775) over 10.1 ± 0.4 years of follow-up, the prevalence of PRISm remained consistent (10.4%-11.3%) between phases 1 through 3, but nearly one-half of subjects with PRISm transitioned into or out of PRISm at each visit. Among all subjects, 19.7% had a significant transition; ever-PRISm was a significant predictor of significant transitions (unadjusted OR, 10.3; 95% CI, 7.9-13.5; adjusted OR, 14.9; 95% CI, 10.9-20.7). Results were similar with additional adjustment for radiographic emphysema and gas trapping, when lower limit of normal criteria were used to define lung function categories, and when FEV(1) alone (regardless of change in FVC % predicted) was used to define significant transitions. INTERPRETATION: PRISm is an unstable group, with frequent significant transitions to both obstruction and normal spirometry over time. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT000608764; URL: www.clinicaltrials.gov

RATIONALE: The course of lung function, respiratory symptoms, and functional status over time in people who smoke cigarettes is still incompletely understood. The COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]) study provides a unique cohort to examine these trajectories, and now 10-year follow-up data are available. OBJECTIVES: This study aims to provide insight into the progression of spirometric parameters, respiratory symptoms, and functional capacity over 10 years in current and former cigarette smokers. METHODS: We analyzed available longitudinal data for COPDGene participants who did not change smoking status over three visits spanning approximately 10 years of follow-up. Change in postbronchodilator forced expiratory volume in 1 second (FEV(1)), St. George’s Respiratory Questionnaire (SGRQ), and 6-minute walk distance (6MWD) from Phase 1 to Phase 3 were examined using linear mixed models. Terms were included in the models to estimate mean progression separately for current and former cigarette smokers. Models were stratified by baseline Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometry stages as well as by new 2019 COPDGene classification. RESULTS: The mean age at enrollment of the 9,103 participants in this analysis was 59.8 years (SD = 9.2 yr); 46.4% were women, and 32.6% were African American. In all GOLD COPD groups, including participants with normal spirometry, and all groups categorized by 2019 COPDGene classification, FEV(1) decreased, SGRQ increased (indicating higher symptom burden), and 6MWD decreased over the 10-year follow-up period. Current smokers exhibited a greater mean loss of FEV(1) over the study period than former smokers for all groups except those with preserved ratio impaired spirometry. For both SGRQ and 6MWD, rates of progression tended to be similar for former and current smokers except for 6MWD in the highest severity groups, in which former smokers had greater progression. However, this could be impacted by some current smokers with faster progression who had quit smoking and were dropped from analyses. CONCLUSIONS: Progression in FEV(1), SGRQ, and 6MWD overall appears to be slow, and the change over time in groups traditionally characterized as not having disease closely mirrors that of the groups with COPD at all GOLD stages. Current cigarette smokers had greater loss of FEV(1) than former smokers, whereas SGRQ and 6MWD changes were more similar between current and former cigarette smokers.

While variation in emphysema between COPD patients is well-recognized, clinically applicable definitions of emphysema-predominant (EPD) and non-emphysema-predominant (NEPD) subtypes have not been established. To study the clinical relevance of EPD and NEPD subtypes, we tested the association of these subtypes to prospective FEV1 decline and mortality in 3,427 subjects with GOLD spirometric grade 2-4 COPD at baseline in the COPDGene Study, an ongoing national multicenter study that started in 2007. NEPD was defined as airflow obstruction with =10% CT emphysema. Mixed effects models for FEV1 demonstrated larger average annual FEV1 loss in EPD versus NEPD subjects (-10.2 ml/yr, p 0.9. NEPD and EPD COPD subtypes capture important aspects of COPD heterogeneity and are associated with different rates of disease progression and mortality.

Supplementary Figure 1 from Increased Manganese Superoxide Dismutase Expression or Treatment with Manganese Porphyrin Potentiates Dexamethasone-Induced Apoptosis in Lymphoma Cells

Supplementary Figure Legend from Increased Manganese Superoxide Dismutase Expression or Treatment with Manganese Porphyrin Potentiates Dexamethasone-Induced Apoptosis in Lymphoma Cells

Rationale: The ability of peripheral blood biomarkers to assess COPD risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict...

Understanding baseline characteristics that can predict the progression of lung disease such as chronic obstructive pulmonary disease (COPD) for current or former smokers may allow for therapeutic intervention, particularly for individuals at high risk of rapid disease progression or transition from non-COPD to COPD. Classic diagnostic criteria for COPD and disease severity such as the Global Initiative for Chronic Obstructive Lung Disease document are based on forced expiratory volume in 1 second (FEV(1)) and FEV(1) to forced vital capacity (FVC) ratio. Modeling changes in these outcomes jointly is beneficial given that they are correlated, and they are both required for specific disease classifications. Here, linear mixed models were used to model changes in FEV(1) and FEV(1)/FVC jointly for 5- and 10-year intervals, using important baseline predictors to better understand the factors that affect disease progression. Participants with predicted loss of FEV(1) and/or FEV(1)/FVC of at least 5% tended to have more emphysema, higher functional residual capacity, higher airway wall thickness as measured by Pi10, lower FVC to total lung capacity ratio and a lower body mass index at baseline, all relative to overall cohort averages. The model developed can be used to predict progression for any potential COPD individual, based on demographic, symptom, computed tomography, and comorbidity variables.

Background The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations. Methods Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case–control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses. Results Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV1/FVC ($$\beta$$ β 0.020, SE 0.004, p 4.97 × 10–08), with suggestive evidence of association with FEV1 ($$\beta$$ β 0.092, SE 0.018, p 3.40 × 10–07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions. Conclusions This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease.

Background Parameters from maximal expiratory flow-volume curves (MEFVC) have been linked to CT-based parameters of COPD. However, the association between MEFVC shape and phenotypes like emphysema, small airways disease (SAD) and bronchial wall thickening (BWT) has not been investigated. Research question We analyzed if the shape of MEFVC can be linked to CT-determined emphysema, SAD and BWT in a large cohort of COPDGene participants. Study design and methods In the COPDGene cohort, we used principal component analysis (PCA) to extract patterns from MEFVC shape and performed multiple linear regression to assess the association of these patterns with CT parameters over the COPD spectrum, in mild and moderate-severe COPD. Results Over the entire spectrum, in mild and moderate-severe COPD, principal components of MEFVC were important predictors for the continuous CT parameters. Their contribution to the prediction of emphysema diminished when classical pulmonary function test parameters were added. For SAD, the components remained very strong predictors. The adjusted R2 was higher in moderate-severe COPD, while in mild COPD, the adjusted R2 for all CT outcomes was low; 0.28 for emphysema, 0.21 for SAD and 0.19 for BWT. Interpretation The shape of the maximal expiratory flow-volume curve as analyzed with PCA is not an appropriate screening tool for early disease phenotypes identified by CT scan. However, it contributes to assessing emphysema and SAD in moderate-severe COPD.

World COPD Day raises awareness about chronic obstructive pulmonary disease (COPD). COPD accounts for over 150,000 US deaths per year. A major challenge is that COPD receives only a fraction of the research funding provided to other major diseases. Control of COPD is dependent on developing new approaches to diagnose the disease earlier with a recognition of either pre-COPD or established COPD based on symptoms, lung structural change and/or loss of lung function that occurs before meeting long established criteria for a population-based definition of obstruction. Optimization of current therapies improves lung function, exercise capacity, quality of life, and survival. New pathways of disease progression are being identified creating new opportunities for development of therapies that could stop or cure this disease.

BACKGROUND: Smokers manifest varied phenotypes of pulmonary impairment. RESEARCH QUESTION: Which pulmonary phenotypes are associated with coronary artery disease (CAD) in smokers? STUDY DESIGN AND METHODS: We 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 (FEV(1) to FVC ratio, < 0.70). RESULTS: Pulmonary 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). FEV(1) 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. INTERPRETATION: Lung hyperinflation is associated strongly with clinical and subclinical CAD in smokers, including those with airflow obstruction. After lung hyperinflation was accounted for, FEV(1) 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.

Chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA) are both independently associated with increased cardiovascular disease (CVD) risk and impaired cognitive function. It is unknown if individuals with both COPD and OSA (i.e., overlap syndrome) have greater common carotid artery (CCA) stiffness, an independent predictor of CVD risk, and lower cognitive performance than either COPD or OSA alone. Elevated CCA stiffness is associated with cognitive impairment in former smokers with and without COPD in past studies. We compared CCA stiffness and cognitive performance between former smokers with overlap syndrome, COPD only, OSA only and former smoker controls using analysis of covariance (ANCOVA) tests to adjust for age, sex, body mass index (BMI), pack years, and postbronchodilator FEV(1)/FVC. We also examined the association between CCA stiffness and cognitive performance among each group separately. Individuals with overlap syndrome (n = 12) had greater CCA β-stiffness index (P = 0.015) and lower executive function-processing speed (P = 0.019) than individuals with COPD alone (n = 47), OSA alone (n = 9), and former smoker controls (n = 21), differences that remained significant after adjusting for age, BMI, sex, pack years, and FEV(1)/FVC. Higher CCA β-stiffness index was associated with lower executive function-processing speed in individuals with overlap syndrome (r = −0.58, P = 0.047). These data suggest that CCA stiffness is greater and cognitive performance is lower among individuals with overlap syndrome compared with individuals with COPD or OSA alone and that CCA stiffening may be an underlying mechanism contributing to the lower cognitive performance observed in patients with overlap syndrome. NEW & NOTEWORTHY Previous studies have demonstrated greater carotid artery stiffness and lower cognitive function among individuals with COPD alone and OSA alone. However, the present study is the first to demonstrate that individuals that have both COPD and OSA (i.e., overlap syndrome) have greater carotid artery stiffness and lower executive function-processing speed than individuals with either disorder alone. Furthermore, among individuals with overlap syndrome greater carotid artery stiffness is associated with lower executive function-processing speed.

Background: The heterogeneous nature of chronic obstructive pulmonary disease (COPD) complicates the identification of the predictors of disease progression. We aimed to improve the prediction of disease progression in COPD by using machine learning and incorporating a rich dataset of phenotypic features. Methods: We included 4496 smokers with available data from their enrollment and 5-year follow-up visits in the COPD Genetic Epidemiology (COPDGene(®)) study. We constructed linear regression (LR) and supervised random forest models to predict 5-year progression in forced expiratory in 1 second (FEV(1)) from 46 baseline features. Using cross-validation, we randomly partitioned participants into training and testing samples. We also validated the results in the COPDGene 10-year follow-up visit. Results: Predicting the change in FEV(1) over time is more challenging than simply predicting the future absolute FEV(1) level. For random forest, R-squared was 0.15 and the area under the receiver operator characteristic (ROC) curves for the prediction of participants in the top quartile of observed progression was 0.71 (testing) and respectively, 0.10 and 0.70 (validation). Random forest provided slightly better performance than LR. The accuracy was best for Global initiative for chronic Obstructive Lung Disease (GOLD) grades 1–2 participants, and it was harder to achieve accurate prediction in advanced stages of the disease. Predictive variables differed in their relative importance as well as for the predictions by GOLD. Conclusion: Random forest, along with deep phenotyping, predicts FEV(1) progression with reasonable accuracy. There is significant room for improvement in future models. This prediction model facilitates the identification of smokers at increased risk for rapid disease progression. Such findings may be useful in the selection of patient populations for targeted clinical trials.

Background: Little is known about factors associated with emphysema progression in cigarette smokers. We evaluated factors associated with change in emphysema and forced expiratory volume in 1 second (FEV(1)) in participants with and without chronic obstructive pulmonary disease (COPD). Methods: This retrospective study included individuals participating in the COPD Genetic Epidemiology study who completed the 5-year follow-up, including inspiratory and expiratory computed tomography (CT) and spirometry. All paired CT scans were analyzed using micro-mapping, which classifies individual voxels as emphysema or functional small airway disease (fSAD). Presence and progression of emphysema and FEV(1) were determined based on comparison to nonsmoker values. Logistic regression analyses were used to identify clinical parameters associated with disease progression. Results: A total of 3088 participants were included with a mean ± SD age of 60.7±8.9 years, including 72 nonsmokers. In all Global initiative for chronic Obstructive Lung Disease (GOLD) stages, the presence of emphysema at baseline was associated with emphysema progression (odds ratio [OR]: GOLD 0: 4.32; preserved ratio-impaired spirometry [PRISm]; 5.73; GOLD 1: 5.16; GOLD 2: 5.69; GOLD 3/4: 5.55; all p ≤0.01). If there was no emphysema at baseline, the amount of fSAD at baseline was associated with emphysema progression (OR for 1% increase: GOLD 0: 1.06; PRISm: 1.20; GOLD 1: 1.7; GOLD 3/4: 1.08; all p ≤ 0.03).In 1735 participants without spirometric COPD, progression in emphysema occurred in 105 (6.1%) participants and only 21 (1.2%) had progression in both emphysema and FEV(1). Conclusions: The presence of emphysema is an important predictor of emphysema progression. In patients without emphysema, fSAD is associated with the development of emphysema. In participants without spirometric COPD, emphysema progression occurred independently of FEV(1) decline.

Introduction: Smoking cessation counseling is a central part of the Medicare guidelines for lung cancer screening. With increasing age, many heavy smokers eventually stop smoking, however, factors influencing the decision to stop smoking are poorly understood. We postulated that declining health or physician-diagnosis of a medical condition may be associated with successful smoking cessation. Methods: A total of 4448 current and former smokers in Phase 2 of the COPD Genetic Epidemiology (COPDGene®) study answered a question about reasons for stopping smoking. Participants were classified as successful quitters (n=3345), and unsuccessful quitters (n=1003). Reasons cited for quitting were grouped as: medical diagnoses, social factors, symptoms. Logistic modeling of factors associated with successful quitting were adjusted for age, gender, race, and education. Results: The most common factors cited for a quit attempt by all respondents were medical diagnoses (48%), followed by social factors (47%), and respiratory symptoms (36%). Successful quitters were more likely to be older, male, and non-Hispanic White. An adjusted model found increased age, White race, education beyond high school, and male sex favored successful quitting while the cited medical diagnoses, social factors, and “other” reasons were associated with unsuccessful quitting. Fagerstrom Nicotine Dependence scores were ³ 5 in 54% of the unsuccessful group compared to 45% for successful quitters(p

Objective Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation; however, pulmonary function does not fully account for patients’ functional difficulties. The primary aim of the study was to determine the association between several domains of cognition and daily activity among those with COPD. Method Eighty-nine former smokers completed a neuropsychological battery including measures across multiple domains of cognition, pulmonary function measures, and daily activity questionnaires. Using a cross-sectional design, we compared daily activity between former smokers with and without COPD using two measures (St. George’s Respiratory Questionnaire [SGRQ] Activity Subscale and Lawton Instrumental Activities of Daily Living [IADL] Scale) and examined the association between cognition and daily activity among those with COPD. Results As expected, former smokers with COPD reported more difficulty than those without COPD on both activity measures (SGRQ Activity Subscale p Conclusion The findings suggest that cognition is associated with daily activity in patients with COPD. Future research should examine whether cognitive interventions may help to maximize patients’ engagement in daily activities.

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: 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 FEV(1)% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV(1) was 3.9% lower (95% confidence interval [CI], −6.55% to −1.26%) and emphysema (the percentage of lung attenuation areas

BACKGROUND: Pattern of emphysema at chest CT, scored visually by using the Fleischner Society system, is associated with physiologic impairment and mortality risk. PURPOSE: To determine whether participant-level emphysema pattern could predict impairment and mortality when classified by using a deep learning method. MATERIALS AND METHODS: This retrospective analysis of Genetic Epidemiology of COPD (COPDGene) study participants enrolled between 2007 and 2011 included those with baseline CT, visual emphysema scores, and survival data through 2018. Participants were partitioned into nonoverlapping sets of 2407 for algorithm training, 100 for validation and parameter tuning, and 7143 for testing. A deep learning algorithm using convolutional neural network and long short-term memory architectures was trained to classify pattern of emphysema according to Fleischner criteria. Deep learning scores were compared with visual scores and clinical parameters including pulmonary function tests. Cox proportional hazard models were used to evaluate relationships between emphysema scores and survival. The algorithm was also tested by using CT and clinical data in 1962 participants enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE) study. RESULTS: A total of 7143 COPDGene participants (mean age ± standard deviation, 59.8 years ± 8.9; 3734 men and 3409 women) were evaluated. Deep learning emphysema classifications were associated with impaired pulmonary function tests, 6-minute walk distance, and St George’s Respiratory Questionnaire at univariate analysis (P < .001 for each). Testing in the ECLIPSE cohort showed similar associations (P < .001). In the COPDGene test cohort, deep learning emphysema classification improved the fit of linear mixed models in the prediction of these clinical parameters compared with visual scoring (P < .001). Compared with participants without emphysema, mortality was greater in participants classified by the deep learning algorithm as having any grade of emphysema (adjusted hazard ratios were 1.5, 1.7, 2.9, 5.3, and 9.7, respectively, for trace, mild, moderate, confluent, and advanced destructive emphysema; P < .05). CONCLUSION: Deep learning automation of the Fleischner grade of emphysema at chest CT is associated with clinical measures of pulmonary insufficiency and the risk of mortality. © RSNA, 2019 Online supplemental material is available for this article.

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC 1

BACKGROUND: Attention difficulties are often reported by patients with chronic obstructive pulmonary disease (COPD); however, limited research exists using objective tests designed specifically to measure attention in this population. This study aimed to: 1) identify specific attention deficits in COPD, and 2) determine which demographic/clinical characteristics are associated with reduced attention. METHODS: 84 former smokers (53 COPD, 31 no COPD) completed questionnaires, pulmonary function testing, and the Conner’s Continuous Performance Test II (CPT-II). Participants with and without COPD were compared on CPT-II measures of inattention, impulsivity, and vigilance. CPT-II measures that differed significantly between the two groups were further examined using hierarchical regression modeling. Demographic/clinical characteristics were entered into models with attention as the dependent variable. RESULTS: Participants with COPD performed worse than those without COPD on CPT measures of inattention and impulsivity (i.e., detectability [discrimination of target from non-target stimuli], perseverations [reaction time under 100 ms], omissions [target stimuli response failures], and commissions [responses to non-target stimuli]). More severe COPD (measured by greater airflow limitation) was associated with poorer ability to detect targets vs. foils and perseverative responding after adjusting for age and other covariates in the model. CONCLUSION: Former smokers with COPD experience problems with attention that go beyond slowed processing speed, including aspects of inattention and impulsivity. Clinicians should be aware that greater airflow limitation and older age are associated with attention difficulties, as this may impact functioning.

Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors. For many years, knowledge of the genetic basis of COPD was limited to Mendelian syndromes, such as alpha-1 antitrypsin deficiency and cutis laxa, caused by rare genetic variants. Over the past decade, the proliferation of genome-wide association studies, the accessibility of whole-genome sequencing, and the development of novel methods for analyzing genetic variation data have led to a substantial increase in the understanding of genetic variants that play a role in COPD susceptibility and COPD-related phenotypes. COPDGene (Genetic Epidemiology of COPD), a multicenter, longitudinal study of over 10,000 current and former cigarette smokers, has been pivotal to these breakthroughs in understanding the genetic basis of COPD. To date, over 20 genetic loci have been convincingly associated with COPD affection status, with additional loci demonstrating association with COPD-related phenotypes such as emphysema, chronic bronchitis, and hypoxemia. In this review, we discuss the contributions of the COPDGene study to the discovery of these genetic associations as well as the ongoing genetic investigations of COPD subtypes, protein biomarkers, and post–genome-wide association study analysis.

Background The objective of the study was to assess the diagnostic process, access to care and treatment adequacy for primary adrenal insufficiency (PAI) patients from a US-based online registry. Methods The National Adrenal Diseases Foundation (NADF) patient registry from 2015 to 2016 was used for a cross-sectional assessment of PAI patients. Five hundred and forty-one adults met the study inclusion criteria (US residents, age >20, self-reported physician diagnosis of PAI and replacement dosing for cortisol). Issues in diagnosis, comorbid conditions, symptoms, with demographic and socioeconomic characteristics were determined. Disease management assessment included medication dose, patient satisfaction with function, and education. Factors associated with adrenal crisis were noted. Results The cohort was predominantly female (83%), non-Hispanic White (97%), and well-educated (94% > high school education). A majority (57%) of patients reported difficulty with initial diagnosis, while 27% felt that their current steroid replacement was not adequate. Comorbid thyroid disease and other autoimmune conditions were common among PAI patients in the registry. More than three-quarters (78%) of patients used hydrocortisone for glucocorticoid replacement with a mean dose of 24.4 (standard deviation [SD]: 8.7) mg. Mean dose of hydrocortisone has declined over time following current treatment recommendations. Conclusions Timely, accurate diagnosis remains a problem for patients with primary adrenal insufficiency in an affluent, well-educated US cohort. Episodes of adrenal crisis are common and replacement steroid treatment is not always effective for patient function. Comprehensive information about outcomes of care for PAI in the US remains limited and the establishment of a research-specific registry to foster future research may be desirable. Patient registry data is a valuable source of information on diagnostic error and outcomes of care in rare diseases.

Genome-wide association studies (GWAS) have identified multiple associations with emphysema apicobasal distribution (EABD), but the biological functions of these variants are unknown. To characterize the functions of EABD-associated variants, we integrated GWAS results with 1) expression quantitative trait loci (eQTL) from the Genotype Tissue Expression (GTEx) project and subjects in the COPDGene (Genetic Epidemiology of COPD) study and 2) cell type epigenomic marks from the Roadmap Epigenomics project. On the basis of these analyses, we selected a variant near ACVR1B (activin A receptor type 1B) for functional validation. SNPs from 168 loci with P values less than 5 × 10(−5) in the largest GWAS meta-analysis of EABD were analyzed. Eighty-four loci overlapped eQTL, with 12 of these loci showing greater than 80% likelihood of harboring a single, shared GWAS and eQTL causal variant. Seventeen cell types were enriched for overlap between EABD loci and Roadmap Epigenomics marks (permutation P

BackgroundBody composition measures, specifically low weight or reduced muscle mass, are associated with mortality in COPD, but the effect of longitudinal body composition changes is undefined.Research questionIs the longitudinal loss of fat-free mass (FFM) associated with increased mortality, including in those with initially normal or elevated body composition metrics?Study design and methodsParticipants with complete data for at least one visit in the COPDGene study (n= 9,268) and the ECLIPSE study (n= 1,760) were included and monitored for 12 and 8 years, respectively. Pectoralis muscle area (PMA) was derived from thoracic CT scans and used as a proxy for FFM. A longitudinal mixed submodel for PMA and a Cox proportional hazards submodel for survival were fitted on a joint distribution, using a shared random intercept parameter and Markov chain Monte Carlo parameter estimation.ResultsBoth cohorts demonstrated a left-shifted distribution of baseline FFM, not reflected in BMI, and an increase in all-cause mortality risk associated with longitudinal loss of PMA. For each 1-cm2 PMA loss, mortality increased 3.1%(95%CI, 2.4%-3.7%; P< .001) in COPDGene, and 2.4%(95%CI, 0.9%-4.0%; P< .001) in ECLIPSE. Increased mortality risk was independent of enrollment values for BMI and disease severity [BODE (body mass, airflow obstruction, dyspnea, and exercise capacity) index quartiles] and was significant even in participants with initially greater than average PMA.InterpretationLongitudinal loss of PMA is associated with increased all-cause mortality, regardless of BMI or initial muscle mass. Consideration of novel screening tests and further research into mechanisms contributing to muscle decline may improve risk stratification and identify novel therapeutic targets in ever smokers.

Background Optimism is the general belief that good things will occur in the future; optimism is modifiable by cognitive behavioral therapy (CBT). Previous studies have associated higher optimism with improved health outcomes and lower all-cause mortality. Research question Investigate association between optimism and disease-related characteristics in chronic obstructive pulmonary disease (COPD). Study design and methods Current and former smokers with/without COPD and Preserved Ratio Impaired Spirometry (PRISm) from the 10-year follow-up visit for the Genetic Epidemiology of COPD (COPDGene) study were included. Optimism was assessed at the 10-year visit using the Life Orientation Test-Revised. Models of optimism as a predictor of lung function, COPD-associated phenotypes including exacerbations, and functional assessments, were adjusted for demographic confounders, smoking status, and comorbidities. Results Among 1967 subjects, higher optimism was significantly associated with older age, non-Hispanic white race, marital status, quitting smoking status, absence of COPD, and absence of depression. In multivariable analysis, higher optimism was independently associated with fewer prior exacerbations of COPD (coef = − 0.037, P 1 (%) or FVC (%) with optimism score. Interpretation Fewer exacerbations and less severe respiratory symptoms and higher functional capacity were associated with higher optimism, which may impact health outcomes in current and former smokers with and without COPD. Optimism is a modifiable trait and these results may further support a role for CBT to improve outcomes in COPD.

Background Attenuation 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 Question Is use of ACEi and ARB associated with less progression of emphysema and FEV1 decline among individuals with COPD or baseline emphysema? Methods Former 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 Results Over 5 years of follow-up, compared with nonusers, ACEi and ARB users with COPD showed slower ALD progression (adjusted mean difference [aMD], 1.6; 95% CI, 0.34-2.9). Slowed lung function decline was not observed based on phase 1 medication (aMD of FEV1 % predicted, 0.83; 95% CI, –0.62 to 2.3), but was when analysis was limited to consistent ACEi and ARB users (aMD of FEV1 % predicted, 1.9; 95% CI, 0.14-3.6). No effect modification by smoking status was found for radiographic outcomes, and the lung function effect was more pronounced in former smokers. Results were similar among participants with baseline emphysema. Interpretation Among participants with spirometry-confirmed COPD or baseline emphysema, ACEi and ARB use was associated with slower progression of emphysema and lung function decline. Trial Registry ClinicalTrials.gov ; No.: NCT00608764; URL: www.clinicaltrials.gov

Background: Risk 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. Methods: We 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. Results: Of 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. Conclusions: Current 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 chronic Obstructive Lung Disease (GOLD) criteria.

Background COPD is a leading cause of mortality. Research Question We hypothesized that applying machine learning to clinical and quantitative CT imaging features would improve mortality prediction in COPD. Study Design and Methods We selected 30 clinical, spirometric, and imaging features as inputs for a random survival forest. We used top features in a Cox regression to create a machine learning mortality prediction (MLMP) in COPD model and also assessed the performance of other statistical and machine learning models. We trained the models in subjects with moderate to severe COPD from a subset of subjects in Genetic Epidemiology of COPD (COPDGene) and tested prediction performance in the remainder of individuals with moderate to severe COPD in COPDGene and Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). We compared our model with the BMI, airflow obstruction, dyspnea, exercise capacity (BODE) index; BODE modifications; and the age, dyspnea, and airflow obstruction index. Results We included 2,632 participants from COPDGene and 1,268 participants from ECLIPSE. The top predictors of mortality were 6-min walk distance, FEV1 % predicted, and age. The top imaging predictor was pulmonary artery-to-aorta ratio. The MLMP-COPD model resulted in a C index ≥ 0.7 in both COPDGene and ECLIPSE (6.4- and 7.2-year median follow-ups, respectively), significantly better than all tested mortality indexes (P Interpretation An MLMP-COPD model outperformed four existing models for predicting all-cause mortality across two COPD cohorts. Performance of machine learning was similar to that of traditional statistical methods. The model is available online at: https://cdnm.shinyapps.io/cgmortalityapp/.