The association of plasma biomarkers with computed tomography-assessed emphysema phenotypes

Rationale: Chronic obstructive pulmonary disease (COPD) is a phenotypically heterogeneous disease. In COPD, the presence of emphysema is associated with increased mortality and risk of lung cancer. High resolution computed tomography (HRCT) scans are useful in quantifying emphysema but are associated with radiation exposure and high incidence of false positive findings (i.e., nodules). Using a comprehensive biomarker panel, we sought to determine if there was a peripheral blood biomarker signature of emphysema. Methods: 114 plasma biomarkers were measured using a custom assay in 588 individuals enrolled in the COPDGene study. Quantitative emphysema measurements included percent low lung attenuation (%LAA) ≤ −950 HU, ≤ − 910 HU and mean lung attenuation at the 15th percentile on lung attenuation curve (LP15A). Multiple regression analysis was performed to determine plasma biomarkers associated with emphysema independent of covariates age, gender, smoking status, body mass index and FEV1. The findings were subsequently validated using baseline blood samples from a separate cohort of 388 subjects enrolled in the Treatment of Emphysema with a Selective Retinoid Agonist (TESRA) study. Results: Regression analysis identified multiple biomarkers associated with CT-assessed emphysema in COPDGene, including advanced glycosylation end-products receptor (AGER or RAGE, p < 0.001), intercellular adhesion molecule 1 (ICAM, p < 0.001), and chemokine ligand 20 (CCL20, p < 0.001). Validation in the TESRA cohort revealed significant associations with RAGE, ICAM1, and CCL20 with radiologic emphysema (p < 0.001 after meta-analysis). Other biomarkers that were associated with emphysema include CDH1, CDH 13 and SERPINA7, but were not available for validation in the TESRA study. Receiver operating characteristics analysis demonstrated a benefit of adding a biomarker panel to clinical covariates for detecting emphysema, especially in those without severe airflow limitation (AUC 0.85). Conclusions: Our findings, suggest that a panel of blood biomarkers including sRAGE, ICAM1 and CCL20 may serve as a useful surrogate measure of emphysema, and when combined with clinical covariates, may be useful clinically in predicting the presence of emphysema compared to just using covariates alone, especially in those with less severe COPD. Ultimately biomarkers may shed light on disease pathogenesis, providing targets for new treatments. Electronic supplementary material The online version of this article (doi:10.1186/s12931-014-0127-9) contains supplementary material, which is available to authorized users

Design of the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) AIR Study.

IntroductionPopulation-based epidemiological evidence suggests that exposure to ambient air pollutants increases hospitalisations and mortality from chronic obstructive pulmonary disease (COPD), but less is known about the impact of exposure to air pollutants on patient-reported outcomes, morbidity and progression of COPD.Methods and analysisThe Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air Pollution Study (SPIROMICS AIR) was initiated in 2013 to investigate the relation between individual-level estimates of short-term and long-term air pollution exposures, day-to-day symptom variability and disease progression in individuals with COPD. SPIROMICS AIR builds on a multicentre study of smokers with COPD, supplementing it with state-of-the-art air pollution exposure assessments of fine particulate matter, oxides of nitrogen, ozone, sulfur dioxide and black carbon. In the parent study, approximately 3000 smokers with and without airflow obstruction are being followed for up to 3 years for the identification of intermediate biomarkers which predict disease progression. Subcohorts undergo daily symptom monitoring using comprehensive daily diaries. The air monitoring and modelling methods employed in SPIROMICS AIR will provide estimates of individual exposure that incorporate residence-specific infiltration characteristics and participant-specific time-activity patterns. The overarching study aim is to understand the health effects of short-term and long-term exposures to air pollution on COPD morbidity, including exacerbation risk, patient-reported outcomes and disease progression.Ethics and disseminationThe institutional review boards of all the participating institutions approved the study protocols. The results of the trial will be presented at national and international meetings and published in peer-reviewed journals

The association of plasma biomarkers with computed tomography-assessed emphysema phenotypes

Abstract Rationale Chronic obstructive pulmonary disease (COPD) is a phenotypically heterogeneous disease. In COPD, the presence of emphysema is associated with increased mortality and risk of lung cancer. High resolution computed tomography (HRCT) scans are useful in quantifying emphysema but are associated with radiation exposure and high incidence of false positive findings (i.e., nodules). Using a comprehensive biomarker panel, we sought to determine if there was a peripheral blood biomarker signature of emphysema. Methods 114 plasma biomarkers were measured using a custom assay in 588 individuals enrolled in the COPDGene study. Quantitative emphysema measurements included percent low lung attenuation (%LAA)≤ - 950 HU, ≤ -910 HU and mean lung attenuation at the 15th percentile on lung attenuation curve (LP15A). Multiple regression analysis was performed to determine plasma biomarkers associated with emphysema independent of covariates age, gender, smoking status, body mass index and FEV1. The findings were subsequently validated using baseline blood samples from a separate cohort of 388 subjects enrolled in the Treatment of Emphysema with a Selective Retinoid Agonist (TESRA) study. Results Regression analysis identified multiple biomarkers associated with CT-assessed emphysema in COPDGene, including advanced glycosylation end-products receptor (AGER or RAGE, p < 0.001), intercellular adhesion molecule 1 (ICAM, p < 0.001), and chemokine ligand 20 (CCL20, p < 0.001). Validation in the TESRA cohort revealed significant associations with RAGE, ICAM1, and CCL20 with radiologic emphysema (p < 0.001 after meta-analysis). Other biomarkers that were associated with emphysema include CDH1, CDH 13 and SERPINA7, but were not available for validation in the TESRA study. Receiver operating characteristics analysis demonstrated a benefit of adding a biomarker panel to clinical covariates for detecting emphysema, especially in those without severe airflow limitation (AUC 0.85). Conclusions Our findings, suggest that a panel of blood biomarkers including sRAGE, ICAM1 and CCL20 may serve as a useful surrogate measure of emphysema, and when combined with clinical covariates, may be useful clinically in predicting the presence of emphysema compared to just using covariates alone, especially in those with less severe COPD. Ultimately biomarkers may shed light on disease pathogenesis, providing targets for new treatments.http://deepblue.lib.umich.edu/bitstream/2027.42/134591/1/12931_2014_Article_127.pd

Genetic susceptibility for chronic bronchitis in chronic obstructive pulmonary disease

Background: Chronic bronchitis (CB) is one of the classic phenotypes of COPD. The aims of our study were to investigate genetic variants associated with COPD subjects with CB relative to smokers with normal spirometry, and to assess for genetic differences between subjects with CB and without CB within the COPD population. Methods: We analyzed data from current and former smokers from three cohorts: the COPDGene Study; GenKOLS (Bergen, Norway); and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). CB was defined as having a cough productive of phlegm on most days for at least 3 consecutive months per year for at least 2 consecutive years. CB COPD cases were defined as having both CB and at least moderate COPD based on spirometry. Our primary analysis used smokers with normal spirometry as controls; secondary analysis was performed using COPD subjects without CB as controls. Genotyping was performed on Illumina platforms; results were summarized using fixed-effect meta-analysis. Results: For CB COPD relative to smoking controls, we identified a new genome-wide significant locus on chromosome 11p15.5 (rs34391416, OR = 1.93, P=4.99× 10-8) as well as significant associations of known COPD SNPs within FAM13A. In addition, a GWAS of CB relative to those without CB within COPD subjects showed suggestive evidence for association on 1q23.3 (rs114931935, OR = 1.88, P= 4.99 ×10-7). Conclusions: We found genome-wide significant associations with CB COPD on 4q22.1 (FAM13A) and 11p15.5 (EFCAB4A, CHID1 and AP2A2), and a locus associated with CB within COPD subjects on 1q23.3 (RPL31P11 and ATF6). This study provides further evidence that genetic variants may contribute to phenotypic heterogeneity of COPD.publishedVersio

Respiratory Symptoms Items from the COPD Assessment Test Identify Ever-Smokers with Preserved Lung Function at Higher Risk for Poor Respiratory Outcomes

Rationale: Ever-smokers without airflow obstruction scores greater than or equal to 10 on the COPD Assessment Test (CAT) still have frequent acute respiratory disease events (exacerbation-like), impaired exercise capacity, and imaging abnormalities. Identification of these subjects could provide new opportunities for targeted interventions. Objectives: We hypothesized that the four respiratory-related items of the CAT might be useful for identifying such individuals, with discriminative ability similar to CAT, which is an eight-item questionnaire used to assess chronic obstructive pulmonary disease impact, including nonrespiratory questions, with scores ranging from 0 to 40. Methods: We evaluated ever-smoker participants in the Subpopulations and Intermediate Outcomes in COPD Study without airflow obstruction (FEV1/FVC≥0.70; FVC above the lower limit of normal). Using the area under the receiver operating characteristic curve, we compared responses to both CAT and the respiratory symptom–related CAT items (cough, phlegm, chest tightness, and breathlessness) and their associations with longitudinal exacerbations. We tested agreement between the two strategies (k statistic), and we compared demographics, lung function, and symptoms among subjects identified as having high symptoms by each strategy. Results: Among 880 ever-smokers with normal lung function (mean age, 61 yr; 52% women) and using a CAT cutpoint greater than or equal to 10, we classified 51.8% of individuals as having high symptoms, 15.3% of whom experienced at least one exacerbation during 1-year follow-up. After testing sensitivity and specificity of different scores for the first four questions to predict any 1-year followup exacerbation, we selected cutpoints of 0–6 as representing a low burden of symptoms versus scores of 7 or higher as representing a high burden of symptoms for all subsequent comparisons. The four respiratory-related items with cutpoint greater than or equal to 7 selected 45.8% participants, 15.6% of whom experienced at least one exacerbation during follow-up. The two strategies largely identified the same individuals (agreement, 88.5%; k = 0.77; P \u3c 0.001), and the proportions of high-symptoms subjects who had severe dyspnea were similar between CAT and the first four CAT questions (25.9% and 26.8%, respectively), as were the proportions reporting impaired quality of life (66.9% and 70.5%, respectively) and short walking distance (22.4% and 23.1%, respectively). There was no difference in area under the receiver operating characteristic curve to predict 1-year follow-up exacerbations (CAT score ≥10, 0.66; vs. four respiratory items from CAT ≥ 7 score, 0.65; P = 0.69). Subjects identified by either method also hadmore depression/anxiety symptoms, poor sleep quality, and greater fatigue. Conclusions: Four CAT items on respiratory symptoms identified high-risk symptomatic ever-smokers with preserved spirometry as well as the CAT did. These data suggest that simpler strategies can be developed to identify these high-risk individuals in primary care

Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Background Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD. Methods Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering. Results Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters. Conclusions Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations

Lower serum IgA is associated with COPD exacerbation risk in SPIROMICS

Background Decreased but measurable serum IgA levels (≤70 mg/dL) have been associated with risk for infections in some populations, but are unstudied in COPD. This study tested the hypothesis that subnormal serum IgA levels would be associated with exacerbation risk in COPD. Methods Data were analyzed from 1,049 COPD participants from the observational cohort study SPIROMICS (535 (51%) women; mean age 66.1 (SD 7.8), 338 (32%) current smokers) who had baseline serum IgA measured using the Myriad RBM biomarker discovery platform. Exacerbation data was collected prospectively (mean 944.3 (SD 281.3) days), and adjusted linear, logistic and zero-inflated negative binomial regressions were performed. Results Mean IgA was 269.1 mg/dL (SD 150.9). One individual had deficient levels of serum IgA (<7 mg/dL) and 25 (2.4%) had IgA level ≤70 mg/dL. Participants with IgA ≤70 mg/dL were younger (62 vs. 66 years, p = 0.01) but otherwise similar to those with higher IgA. In adjusted models, IgA ≤70 mg/dL was associated with higher exacerbation incidence rates (IRR 1.71, 95% CI 1.01–2.87, p = 0.044) and greater risk for any severe exacerbation (OR 2.99, 95% CI 1.30–6.94, p = 0.010). In adjusted models among those in the lowest decile (<120 mg/dL), each 10 mg/dL decrement in IgA (analyzed continuously) was associated with more exacerbations during follow-up (β 0.24, 95% CI 0.017–0.46, p = 0.035). Conclusions Subnormal serum IgA levels were associated with increased risk for acute exacerbations, supporting mildly impaired IgA levels as a contributing factor in COPD morbidity. Additionally, a dose-response relationship between lower serum IgA and number of exacerbations was found among individuals with serum IgA in the lowest decile, further supporting the link between serum IgA and exacerbation risk. Future COPD studies should more comprehensively characterize immune status to define the clinical relevance of these findings and their potential for therapeutic correction

Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS)

Background: Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. Methods: An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. Results: We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. Conclusions: QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.NIH [U01-HL114494, R01-HL112986, S10-RR022421]; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1D1A1B03034157]; Korea Ministry of Environment (MOE) [RE201806039]; NIH/NHLBI [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]