George R. Washko

Chronic obstructive pulmonary disease (COPD) was the third leading cause of global mortality in 2011 but receives limited attention and research funding. This Review describes the current knowledge on COPD risk factors, including genetic and epigenetic determinants and their interactions with the microbiome and environmental exposures. Preclinical models are being refined and single-cell transcriptomic, metabolomic, and proteomic technologies are being implemented to investigate the molecular mechanisms of disease progression. Patient cohorts to define biomarkers of early disease and the latest approaches to diagnose pre-COPD are essential to accelerate the development of novel and effective therapeutic interventions and translate new findings into clinical trials. This Review is a summary of topics covered by a symposium organized by the COPD-iNET consortium, an international network of researchers who have established a platform that facilitates collaboration of this multidisciplinary group of preclinical, translational, and clinical researchers.

Rationale: Expiratory central airway collapse is associated with respiratory morbidity independent of underlying lung disease. However, not all smokers develop expiratory central airway collapse, and the etiology of expiratory central airway collapse in adult smokers is unclear. Paraseptal emphysema in the paratracheal location, by untethering airway walls, may predispose smokers to developing expiratory central airway collapse. Objectives: To evaluate whether paratracheal paraseptal emphysema is associated with expiratory central airway collapse. Methods: We analyzed paired inspiratory and expiratory computed tomography scans from participants enrolled in a multicenter study (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) of smokers aged 45 to 80 years. Expiratory central airway collapse was defined as greater than or equal to 50% reduction in cross-sectional area of the trachea during expiration. In a nested case-control design, participants with and without expiratory central airway collapse were included in a 1:2 fashion, and inspiratory scans were further analyzed using the Fleischner Society criteria for presence of centrilobular emphysema, paraseptal emphysema, airway wall thickening, and paratracheal paraseptal emphysema (maximal diameter ≥ 0.5 cm). Results: A total of 1,320 patients were included, 440 with and 880 without expiratory central airway collapse. Those with expiratory central airway collapse were older, had higher body mass index, and were less likely to be men or current smokers. Paratracheal paraseptal emphysema was more frequent in those with expiratory central airway collapse than control subjects (16.6 vs. 11.8%; P = 0.016), and after adjustment for age, race, sex, body mass index, smoking pack-years, and forced expiratory volume in 1 second, paratracheal paraseptal emphysema was independently associated with expiratory central airway collapse (adjusted odds ratio, 1.53; 95% confidence interval, 1.18–1.98; P = 0.001). Furthermore, increasing size of paratracheal paraseptal emphysema (maximal diameter of at least 1 cm and 1.5 cm) was associated with greater odds of expiratory central airway collapse (adjusted odds ratio, 1.63; 95% confidence interval, 1.18–2.25; P = 0.003 and 1.77; 95% confidence interval, 1.19–2.64; P = 0.005, respectively). Conclusions: Paraseptal emphysema adjacent to the trachea is associated with expiratory central airway collapse. The identification of this risk factor on inspiratory scans should prompt further evaluation for expiratory central airway collapse. Clinical trial registered with ClinicalTrials.gov (NCT 00608764).

Rationale: Deep learning is a powerful tool that may allow for improved outcome prediction. Objectives: To determine if deep learning, specifically convolutional neural network (CNN) analysis, could detect and stage chronic obstructive pulmonary disease (COPD) and predict acute respiratory disease (ARD) events and mortality in smokers. Methods: A CNN was trained using computed tomography scans from 7,983 COPDGene participants and evaluated using 1,000 nonoverlapping COPDGene participants and 1,672 ECLIPSE participants. Logistic regression (C statistic and the Hosmer-Lemeshow test) was used to assess COPD diagnosis and ARD prediction. Cox regression (C index and the Greenwood-Nam-D’Agnostino test) was used to assess mortality. Measurements and Main Results: In COPDGene, the C statistic for the detection of COPD was 0.856. A total of 51.1% of participants in COPDGene were accurately staged and 74.95% were within one stage. In ECLIPSE, 29.4% were accurately staged and 74.6% were within one stage. In COPDGene and ECLIPSE, the C statistics for ARD events were 0.64 and 0.55, respectively, and the Hosmer-Lemeshow P values were 0.502 and 0.380, respectively, suggesting no evidence of poor calibration. In COPDGene and ECLIPSE, CNN predicted mortality with fair discrimination (C indices, 0.72 and 0.60, respectively), and without evidence of poor calibration (Greenwood-Nam-D’Agnostino P values, 0.307 and 0.331, respectively). Conclusions: A deep-learning approach that uses only computed tomography imaging data can identify those smokers who have COPD and predict who are most likely to have ARD events and those with the highest mortality. At a population level CNN analysis may be a powerful tool for risk assessment.

Beta-blockers are commonly prescribed for patients with cardiovascular disease. Providers have been wary of treating chronic obstructive pulmonary disease (COPD) patients with beta-blockers due to concern for bronchospasm, but retrospective studies have shown that cardio-selective beta-blockers are safe in COPD and possibly beneficial. However, these benefits may reflect symptom improvements due to the cardiac effects of the medication. The purpose of this study is to evaluate associations between beta-blocker use and both exacerbation rates and longitudinal measures of lung function in two well-characterized COPD cohorts. We retrospectively analyzed 1219 participants with over 180 days of follow up from the STATCOPE trial, which excluded most cardiac comorbidities, and from the placebo arm of the MACRO trial. Primary endpoints were exacerbation rates per person-year and change in spirometry over time in association with beta blocker use. Overall 13.9% (170/1219) of participants reported taking beta-blockers at enrollment. We found no statistically significant differences in exacerbation rates with respect to beta-blocker use regardless of the prevalence of cardiac comorbidities. In the MACRO cohort, patients taking beta-blockers had an exacerbation rate of 1.72/person-year versus a rate of 1.71/person-year in patients not taking beta-blockers. In the STATCOPE cohort, patients taking beta-blockers had an exacerbation rate of 1.14/person-year. Patients without beta-blockers had an exacerbation rate of 1.34/person-year. We found no detrimental effect of beta blockers with respect to change in lung function over time. We found no evidence that beta-blocker use was unsafe or associated with worse pulmonary outcomes in study participants with moderate to severe COPD.

Rationale: Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe–predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. Objectives: To identify the genetic influences of emphysema distribution in non–alpha-1 antitrypsin–deficient smokers. Methods: A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism–, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. Measurements and Main Results: We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. Conclusions: This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic approaches in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and local histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women’s Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient’s lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the local histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.

Rationale: Acute exacerbations of chronic obstructive pulmonary disease (COPD) increase the risk of death and drive healthcare costs, but whether they accelerate loss of lung function remains controversial. Whether exacerbations in subjects with mild COPD or similar acute respiratory events in smokers without airflow obstruction affect lung function decline is unknown. Objectives: To determine the association between acute exacerbations of COPD (and acute respiratory events in smokers without COPD) and the change in lung function over 5 years of follow-up. Methods: We examined data on the first 2,000 subjects who returned for a second COPDGene visit 5 years after enrollment. Baseline data included demographics, smoking history, and computed tomography emphysema. We defined exacerbations (and acute respiratory events in those without established COPD) as acute respiratory symptoms requiring either antibiotics or systemic steroids, and severe events by the need for hospitalization. Throughout the 5-year follow-up period, we collected self-reported acute respiratory event data at 6-month intervals. We used linear mixed models to fit FEV1 decline based on reported exacerbations or acute respiratory events. Measurements and Main Results: In subjects with COPD, exacerbations were associated with excess FEV1 decline, with the greatest effect in Global Initiative for Chronic Obstructive Lung Disease stage 1, where each exacerbation was associated with an additional 23 ml/yr decline (95% confidence interval, 2–44; P = 0.03), and each severe exacerbation with an additional 87 ml/yr decline (95% confidence interval, 23–151; P = 0.008); statistically significant but smaller effects were observed in Global Initiative for Chronic Obstructive Lung Disease stage 2 and 3 subjects. In subjects without airflow obstruction, acute respiratory events were not associated with additional FEV1 decline. Conclusions: Exacerbations are associated with accelerated lung function loss in subjects with established COPD, particularly those with mild disease. Trials are needed to test existing and novel therapies in subjects with early/mild COPD to potentially reduce the risk of progressing to more advanced lung disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Hypoxemia is a major complication of COPD and is a strong predictor of mortality. We previously identified independent risk factors for the presence of resting hypoxemia in the COPDGene cohort. However, little is known about characteristics that predict onset of resting hypoxemia in patients who are normoxic at baseline. We hypothesized that a combination of clinical, physiologic, and radiographic characteristics would predict development of resting hypoxemia after 5-years of follow-up in participants with moderate to severe COPD We analyzed 678 participants with moderate-to-severe COPD recruited into the COPDGene cohort who completed baseline and 5-year follow-up visits and who were normoxic by pulse oximetry at baseline. Development of resting hypoxemia was defined as an oxygen saturation ≤88% on ambient air at rest during follow-up. Demographic and clinical characteristics, lung function, and radiographic indices were analyzed with logistic regression models to identify predictors of the development of hypoxemia. Forty-six participants (7%) developed resting hypoxemia at follow-up. Enrollment at Denver (OR 8.30, 95%CI 3.05–22.6), lower baseline oxygen saturation (OR 0.70, 95%CI 0.58–0.85), self-reported heart failure (OR 6.92, 95%CI 1.56–30.6), pulmonary artery (PA) enlargement on computed tomography (OR 2.81, 95%CI 1.17–6.74), and prior severe COPD exacerbation (OR 3.31, 95%CI 1.38–7.90) were independently associated with development of resting hypoxemia. Participants who developed hypoxemia had greater decline in 6-min walk distance and greater 5-year decline in quality of life compared to those who remained normoxic at follow-up. Development of clinically significant hypoxemia over a 5-year span is associated with comorbid heart failure, PA enlargement and severe COPD exacerbation. Further studies are needed to determine if treatments targeting these factors can prevent new onset hypoxemia. COPDGene is registered at ClinicalTrials.gov: NCT00608764 (Registration Date: January 28, 2008)