Imaging approaches to understand disease complexity: chronic obstructive pulmonary disease as a clinical model

Update on the Etiology, Assessment, and Management of COPD Cachexia: Considerations for the Clinician

Cachexia is a commonly observed but frequently neglected extra-pulmonary manifestation in patients with chronic obstructive pulmonary disease (COPD). Cachexia is a multifactorial syndrome characterized by severe loss of body weight, muscle, and fat, as well as increased protein catabolism. COPD cachexia places a high burden on patients (eg, increased mortality risk and disease burden, reduced exercise capacity and quality of life) and the healthcare system (eg, increased number, length, and cost of hospitalizations). The etiology of COPD cachexia involves a complex interplay of non-modifiable and modifiable factors (eg, smoking, hypoxemia, hypercapnia, physical inactivity, energy imbalance, and exacerbations). Addressing these modifiable factors is needed to prevent and treat COPD cachexia. Oral nutritional supplementation combined with exercise training should be the primary multimodal treatment approach. Adding a pharmacological agent might be considered in some, but not all, patients with COPD cachexia. Clinicians and researchers should use longitudinal measures (eg, weight loss, muscle mass loss) instead of cross-sectional measures (eg, low body mass index or fat-free mass index) where possible to evaluate patients with COPD cachexia. Lastly, in future research, more detailed phenotyping of cachectic patients to enable a better comparison of included patients between studies, prospective longitudinal studies, and more focus on the impact of exacerbations and the role of biomarkers in COPD cachexia, are highly recommended.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Distinguishing Smoking-Related Lung Disease Phenotypes Via Imaging and Molecular Features

BACKGROUND

Chronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates.

RESEARCH QUESTION

Can CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis?

STUDY DESIGN AND METHODS

Using K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression.

RESULTS

Three clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-β) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes.

INTERPRETATION

Using quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-β pathways.

CLINICAL TRIAL REGISTRATION

COPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697).

Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.