BackgroundChronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterized by multiple subtypes and variable disease progression. Blood biomarkers have been variably associated with subtype, severity, and disease progression. Just as combined clinical variables are more highly predictive of outcomes than individual clinical variables, we hypothesized that multiple biomarkers may be more informative than individual biomarkers to predict subtypes, disease severity, disease progression, and mortality.MethodsFibrinogen, C-Reactive Protein (CRP), surfactant protein D (SP-D), soluble Receptor for Advanced Glycation Endproducts (sRAGE), and Club Cell Secretory Protein (CC16) were measured in the plasma of 1465 subjects from the COPDGene cohort and 2746 subjects from the ECLIPSE cohort. Regression analysis was performed to determine whether these biomarkers, individually or in combination, were predictive of subtypes, disease severity, disease progression, or mortality, after adjustment for clinical covariates.ResultsIn COPDGene, the best combinations of biomarkers were: CC16, sRAGE, fibrinogen, CRP, and SP-D for airflow limitation (p < 10−4), SP-D, CRP, sRAGE and fibrinogen for emphysema (p < 10−3), CC16, fibrinogen, and sRAGE for decline in FEV1 (p < 0.05) and progression of emphysema (p < 10−3), and all five biomarkers together for mortality (p < 0.05). All associations except mortality were validated in ECLIPSE. The combination of SP-D, CRP, and fibrinogen was the best model for mortality in ECLIPSE (p < 0.05), and this combination was also significant in COPDGene.ConclusionThis comprehensive analysis of two large cohorts revealed that combinations of biomarkers improve predictive value compared with clinical variables and individual biomarkers for relevant cross-sectional and longitudinal COPD outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-017-0597-7) contains supplementary material, which is available to authorized users.

Blood biomarkers were significantly associated with the occurrence of exacerbations but were not robust between cohorts and added little to the predictive value of clinical covariates for exacerbations.

IntroductionExposure to secondhand smoke (SHS) is associated with occult obstructive lung disease as evident by abnormal airflow indices representing small airway disease despite having preserved spirometry (normal forced expiratory volume in 1 s-to-forced vital capacity ratio, FEV1/FVC). The significance of lung volumes that reflect air trapping in the presence of preserved spirometry is unclear.MethodsTo investigate whether lung volumes representing air trapping could determine susceptibility to respiratory morbidity in people with SHS exposure but without spirometric chronic obstructive pulmonary disease, we examined a cohort of 256 subjects with prolonged occupational SHS exposure and preserved spirometry. We elicited symptom prevalence by structured questionnaires, examined functional capacity (maximum oxygen uptake, VO2max) by exercise testing, and estimated associations of those outcomes with air trapping (plethysmography-measured residual volume-to-total lung capacity ratio, RV/TLC), and progressive air trapping with exertion (increase in fraction of tidal breathing that is flow limited on expiration during exercise (per cent of expiratory flow limitation, %EFL)).ResultsRV/TLC was within the predicted normal limits, but was highly variable spanning 22%±13% and 16%±8% across the increments of FEV1/FVC and FEV1, respectively. Respiratory complaints were prevalent (50.4%) with the most common symptom being ≥2 episodes of cough per year (44.5%). Higher RV/TLC was associated with higher OR of reporting respiratory symptoms (n=256; r2=0.03; p=0.011) and lower VO2max (n=179; r2=0.47; p=0.013), and %EFL was negatively associated with VO2max (n=32; r2=0.40; p=0.017).ConclusionsIn those at risk for obstruction due to SHS exposure but with preserved spirometry, higher RV/TLC identifies a subgroup with increased respiratory symptoms and lower exercise capacity.

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Rationale: Chronic obstructive pulmonary disease exacerbations are associated with disease progression, higher healthcare cost, and increased mortality. Published predictors of future exacerbations include previous exacerbation, airflow obstruction, poor overall health, home oxygen use, and gastroesophageal reflux. Objectives: To determine the value of adding blood biomarkers to clinical variables to predict exacerbations. Methods: Subjects from the SPIROMICS (Subpopulations and Intermediate Outcomes Measures in COPD Study) (n = 1,544) and COPDGene (Genetic Epidemiology of COPD) (n = 602) cohorts had 90 plasma or serum candidate proteins measured on study entry using Myriad-RBM multiplex panels. We defined total exacerbations as subject-reported worsening in respiratory health requiring therapy with corticosteroids and/or antibiotics, and severe exacerbations as those leading to hospitalizations or emergency room visits. We assessed retrospective exacerbations during the 12 months before enrollment and then documented prospective exacerbations in each cohort. Exacerbations were modeled for biomarker associations with negative binomial regression including clinical covariates (age, sex, percent predicted FEV 1 , self-reported gastroesophageal reflux, St. George's Respiratory Questionnaire score, smoking status). We used the Stouffer-Liptak test to combine P values for metaanalysis. Measurements and Main Results: Between the two cohorts, 3,471 total exacerbations (1,044 severe) were reported. We identified biomarkers within each cohort that were significantly associated with a history of exacerbation and with a future exacerbation, but there was minimal replication between the cohorts. Although established clinical features were predictive of exacerbations, of the blood biomarkers only decorin and a 2-macroglobulin increased predictive value for future severe exacerbations. Conclusions: Blood biomarkers were significantly associated with the occurrence of exacerbations but were not robust between cohorts and added little to the predictive value of clinical covariates for exacerbations.

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