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RATIONALE: Bronchiectasis is common among those with heavy smoking histories, but risk factors for bronchiectasis, including alpha-1 antitrypsin deficiency, and its implications for COPD severity are uncharacterized in such individuals. OBJECTIVES: To characterize the impact of bronchiectasis on COPD and explore alpha-1antitrypsin as a risk factor for bronchiectasis. METHODS: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) participants (N=914; ages 40-80 years; ≥20-pack-year smoking) had high-resolution computed tomography (CT) scans interpreted visually for bronchiectasis, based on airway dilation without fibrosis or cicatrization. We performed regression-based models of bronchiectasis with clinical outcomes and quantitative CT measures. We deeply sequenced the gene encoding -alpha-1 antitrypsin, SERPINA1, in 835 participants to test for rare variants, focusing on the PiZ genotype (Glu366Lys, rs28929474). MEASUREMENTS AND MAIN RESULTS: We identified bronchiectasis in 365 (40%) participants, more frequently in women (45% versus 36%, p=0.0045), older participants (mean age=66[standard deviation (SD)=8.3] versus 64[SD=9.1] years, p=0.0083), and those with lower lung function (forced expiratory volume in 1 second [FEV1 ] percentage predicted=66%[SD=27] versus 77%[SD=25], p

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.

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.

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.

Background Airway mucus plugs in asthma are associated with exacerbation frequency, increased eosinophilia, and reduced lung function. The relationship between mucus plugs and spatially overlapping ventilation abnormalities observed at hyperpolarized gas MRI has not been assessed quantitatively. Purpose To assess regional associations between CT mucus plugs scored by individual bronchopulmonary segment and corresponding measurements of segmental ventilation defect percentage (VDP) at hyperpolarized helium 3 (3He) MRI. Materials and Methods In this secondary analysis of a Health Insurance Portability and Accountability Act-compliant prospective observational cohort, participants in the Severe Asthma Research Program (SARP) III (NCT01760915) between December 2012 and August 2015 underwent hyperpolarized 3He MRI to determine segmental VDP. Segmental mucus plugs at CT were scored by two readers, with segments scored as plugged only if both readers agreed independently. A linear mixed-effects model controlling for interpatient variability was then used to assess differences in VDP in plugged versus plug-free segments. Results Forty-four participants with asthma were assessed (mean age ± standard deviation, 47 years ± 15; 29 women): 19 with mild-to-moderate asthma and 25 with severe asthma. Mucus plugs were observed in 49 total bronchopulmonary segments across eight of 44 patients. Segments containing mucus plugs had a median segmental VDP of 25.9% (25th-75th percentile, 7.3%-38.3%) versus 1.4% (25th-75th percentile, 0.1%-5.2%; P < .001) in plug-free segments. Similarly, the model estimated a segmental VDP of 18.9% (95% CI: 15.7, 22.2) for mucus-plugged segments versus 5.1% (95% CI: 3.3, 7.0) for plug-free segments (P < .001). Participants with one or more mucus plugs had a median whole-lung VDP of 11.1% (25th-75th percentile, 7.1%-18.9%) versus 3.1% (25th-75th percentile, 1.1%-4.4%) in those without plugs (P < .001). Conclusion Airway mucus plugging at CT was associated with reduced ventilation in the same bronchopulmonary segment at hyperpolarized helium 3 MRI, suggesting that mucus plugging may be an important cause of ventilation defects in asthma. © RSNA, 2021 Online supplemental material is available for this article.

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

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.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes.

PurposeQuantitative computed tomography (qCT) imaging-based cluster analysis identified clinically meaningful COPD former-smoker subgroups (clusters) based on cross-sectional data. We aimed to identify progression clusters for former smokers using longitudinal data.Patients and methodsWe selected 472 former smokers from SPIROMICS with a baseline visit and a one-year follow-up visit. A total of 150 qCT imaging-based variables, comprising 75 variables at baseline and their corresponding progression rates, were derived from the respective inspiration and expiration scans of the two visits. The COPD progression clusters identified were then associated with subject demography, clinical variables and biomarkers.ResultsCOPD severities at baseline increased with increasing cluster number. Cluster 1 patients were an obese subgroup with rapid progression of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%). Cluster 2 exhibited a decrease of fSAD% and Emph%, an increase of tissue fraction at total lung capacity and airway narrowing over one year. Cluster 3 showed rapid expansion of Emph% and an attenuation of fSAD%. Cluster 4 demonstrated severe emphysema and fSAD and significant structural alterations at baseline with rapid progression of fSAD% over one year. Subjects with different progression patterns in the same cross-sectional cluster were identified by longitudinal clustering.ConclusionqCT imaging-based metrics at two visits for former smokers allow for the derivation of four statistically stable clusters associated with unique progression patterns and clinical characteristics. Use of baseline variables and their progression rates enables identification of longitudinal clusters, resulting in a refinement of cross-sectional clusters.

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 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 music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

BackgroundObesity is associated with an increased risk of primary graft dysfunction (PGD) after lung transplantation. The contribution of specific adipose tissue depots is unknown.MethodsWe performed a prospective cohort study of adult lung transplant recipients at 4 U.S. transplant centers. We measured cross-sectional areas of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) on chest and abdominal computed tomography (CT) scans and indexed each measurement to height.2 We used logistic regression to examine the associations of adipose indices and adipose classes with grade 3 PGD at 48 or 72 hours, and Cox proportional hazards models to examine survival. We used latent class analyses to identify the patterns of adipose distribution. We examined the associations of adipose indices with plasma biomarkers of obesity and PGD.ResultsA total of 262 and 117 subjects had available chest CT scans and underwent protocol abdominal CT scans, respectively. In the adjusted models, a greater abdominal SAT index was associated with an increased risk of PGD (odds ratio 1.9, 95% CI 1.02-3.4, p = 0.04) but not with survival time. VAT indices were not associated with PGD risk or survival time. A greater abdominal SAT index correlated with greater pre- and post-transplant leptin (r = 0.61, p < 0.001, and r = 0.44, p < 0.001), pre-transplant IL-1RA (r = 0.25, p = 0.04), and post-transplant ICAM-1 (r = 0.25, p = 0.04). We identified 3 latent patterns of adiposity. The class defined by high thoracic and abdominal SAT had the greatest risk of PGD.ConclusionsSubcutaneous, but not visceral, adiposity is associated with an increased risk of PGD after lung transplantation.

Rationale: Interstitial lung abnormalities (ILAs) are associated with the highest genetic risk locus for idiopathic pulmonary fibrosis (IPF); however, the extent to which there are unique associations among individuals with ILAs or additional overlap with IPF is not known.Objectives: To perform a genome-wide association study (GWAS) of ILAs.Methods: ILAs and a subpleural-predominant subtype were assessed on chest computed tomography (CT) scans in the AGES (Age Gene/Environment Susceptibility), COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]), Framingham Heart, ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), MESA (Multi-Ethnic Study of Atherosclerosis), and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) studies. We performed a GWAS of ILAs in each cohort and combined the results using a meta-analysis. We assessed for overlapping associations in independent GWASs of IPF.Measurements and Main Results: Genome-wide genotyping data were available for 1,699 individuals with ILAs and 10,274 control subjects. The MUC5B (mucin 5B) promoter variant rs35705950 was significantly associated with both ILAs (P = 2.6 × 10-27) and subpleural ILAs (P = 1.6 × 10-29). We discovered novel genome-wide associations near IPO11 (rs6886640, P = 3.8 × 10-8) and FCF1P3 (rs73199442, P = 4.8 × 10-8) with ILAs, and near HTRE1 (rs7744971, P = 4.2 × 10-8) with subpleural-predominant ILAs. These novel associations were not associated with IPF. Among 12 previously reported IPF GWAS loci, five (DPP9, DSP, FAM13A, IVD, and MUC5B) were significantly associated (P

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.

The purpose of this study was to test the feasibility and acceptability of a staff-delivered physical exercise program embedded into the daily lives of older adults living in nursing homes. A randomized controlled pilot feasibility study was carried out, which included quantitative, qualitative, and economic assessments at baseline, 12 weeks, and 12 months. Two nursing homes (one intervention and one control) took part. The exercise program was carried out on 3 days per week for 12 weeks and consisted of a program of Morning Movement (walking and sit-to-stand exercises) and Activity Bursts. The results confirm that the intervention and study processes are largely acceptable and feasible to implement in the nursing home setting. Potential short-term improvements in physical mobility and quality of life were noticed as positive mean changes and supported by qualitative assessment. Future randomized controlled trials should consider using the 6-meter walk test and refining nursing home and participant eligibility criteria. [ABSTRACT FROM AUTHOR]

BackgroundCOPD is associated with cardiovascular disease (CVD), and coronary artery calcification (CAC) provides additional prognostic information. With increasing use of nongated CT scans in clinical practice, this study hypothesized that the visual Weston CAC score would perform as well as the Agatston score in predicting prevalent and incident coronary artery disease (CAD) and CVD in COPD.MethodsCAC was measured by using Agatston and Weston scores on baseline CT scans in 1,875 current and former smokers enrolled in the Genetic Epidemiology of COPD (COPDGene) study. Baseline cardiovascular disease and incident cardiac events on longitudinal follow-up were recorded. Accuracy of the CAC scores was measured by using receiver-operating characteristic analysis, and Cox proportional hazards analyses were used to estimate the risk of incident cardiac events.ResultsCAD was reported by 133 (7.1%) subjects at baseline. A total of 413 (22.0%) and 241 (12.9%) patients had significant CAC according to the Weston (≥ 7) and Agatston (≥ 400) scores, respectively; the two methods were significantly correlated (r = 0.84; P < .001). Over 5 years of follow-up, 127 patients (6.8%) developed incident CVD. For predicting prevalent CAD, c-indices for the Weston and Agatston scores were 0.78 and 0.74 and for predicting incident CVD, they were 0.62 and 0.61. After adjustment for age, race, sex, smoking pack-years, FEV1, percent emphysema, and CT scanner type, a Weston score ≥ 7 was associated with time to first acute coronary event (hazard ratio, 2.16 [95% CI, 1.32 to 3.53]; P = .002), but a Agatston score ≥ 400 was not (hazard ratio, 1.75 [95% CI, 0.99-3.09]; P = .053).ConclusionsA simple visual score for CAC performed well in predicting incident CAD in smokers with and without COPD.Trial registryClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.

Rationale: Rural residence is associated with poor outcomes in several chronic diseases. The association between rural residence and chronic obstructive pulmonary disease (COPD) exacerbations remains unclear.Objectives: In this work, we sought to determine the independent association between rural residence and COPD-related outcomes, including COPD exacerbations, airflow obstruction, and symptom burden.Methods: A total of 1,684 SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) participants with forced expiratory volume in 1 second/forced vital capacity < 0.70 had geocoding-defined rural-urban residence status determined (N = 204 rural and N = 1,480 urban). Univariate and multivariate logistic and negative binomial regressions were performed to assess the independent association between rurality and COPD outcomes, including exacerbations, lung function, and symptom burden. The primary exposure of interest was rural residence, determined by geocoding of the home address to the block level at the time of study enrollment. Additional covariates of interest included demographic and clinical characteristics, occupation, and occupational exposures. The primary outcome measures were exacerbations determined over a 1-year course after enrollment by quarterly telephone calls and at an annual research clinic visit. The odds ratio (OR) and incidence rate ratio (IRR) of exacerbations that required treatment with medications, including steroids or antibiotics (total exacerbations), and exacerbations leading to hospitalization (severe exacerbations) were determined after adjusting for relevant covariates.Results: Rural residence was independently associated with a 70% increase in the odds of total exacerbations (OR, 1.70 [95% confidence interval (CI), 1.13-2.56]; P = 0.012) and a 46% higher incidence rate of total exacerbations (IRR 1.46 [95% CI, 1.02-2.10]; P = 0.039). There was no association between rural residence and severe exacerbations. Agricultural occupation was independently associated with increased odds and incidence of total and severe exacerbations. Inclusion of agricultural occupation in the analysis attenuated the association between rural residence and the odds and incidence rate of total exacerbations (OR, 1.52 [95% CI, 1.00-2.32]; P = 0.05 and IRR 1.39 [95% CI, 0.97-1.99]; P = 0.07). There was no difference in symptoms or airflow obstruction between rural and urban participants.Conclusions: Rural residence is independently associated with increased odds and incidence of total, but not severe, COPD exacerbations. These associations are not fully explained by agriculture-related exposures, highlighting the need for future research into potential mechanisms of the increased risk of COPD exacerbations in the rural population.

BACKGROUND:Eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) is associated with exacerbations and responsivity to steroids, suggesting potential shared mechanisms with eosinophilic asthma. However, there is no consistent blood eosinophil count that has been used to define the increased exacerbation risk. OBJECTIVE:We sought to investigate blood eosinophil counts associated with exacerbation risk in patients with COPD. METHODS:Blood eosinophil counts and exacerbation risk were analyzed in patients with moderate-to-severe COPD by using 2 independent studies of former and current smokers with longitudinal data. The Genetic Epidemiology of COPD (COPDGene) study was analyzed for discovery (n = 1,553), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study was analyzed for validation (n = 1,895). A subset of the ECLIPSE study subjects were used to assess the stability of blood eosinophil counts over time. RESULTS:COPD exacerbation risk increased with higher eosinophil counts. An eosinophil count threshold of 300 cells/μL or greater showed adjusted incidence rate ratios for exacerbations of 1.32 in the COPDGene study (95% CI, 1.10-1.63). The cutoff of 300 cells/μL or greater was validated for prospective risk of exacerbation in the ECLIPSE study, with adjusted incidence rate ratios of 1.22 (95% CI, 1.06-1.41) using 3-year follow-up data. Stratified analysis confirmed that the increased exacerbation risk associated with an eosinophil count of 300 cells/μL or greater was driven by subjects with a history of frequent exacerbations in both the COPDGene and ECLIPSE studies. CONCLUSIONS:Patients with moderate-to-severe COPD and blood eosinophil counts of 300 cells/μL or greater had an increased risk exacerbations in the COPDGene study, which was prospectively validated in the ECLIPSE study.