A novel spirometric measure identifies mild COPD unidentified by standard criteria

BACKGROUND: In chronic obstructive pulmonary disease, both smaller and larger airways are affected. FEV1 mainly reflects large airways obstruction, while the later fraction of forced exhalation reflects reduction in terminal expiratory flow. In this study, the objective was to evaluate the relationship between spirometric ratios, including the ratio of forced expiratory volume in 3 and 6 seconds (FEV3/FEV6), and small airways measures and gas trapping at quantitative chest CT scanning, and clinical outcomes in the Genetic Epidemiology of COPD (COPDGene) cohort. METHODS: Seven thousand eight hundred fifty-three current and ex-smokers were evaluated for airflow obstruction by using recently defined linear iteratively derived equations of Hansen et al to determine lower limit of normal (LLN) equations for prebronchodilator FEV1/FVC, FEV1/FEV6, FEV3/FEV6, and FEV3/FVC. General linear and ordinal regression models were applied to the relationship between prebronchodilator spirometric and radiologic and clinical data. RESULTS: Of the 10,311 participants included in the COPDGene phase I study, participants with incomplete quantitative CT scanning or relevant spirometric data were excluded, resulting in 7,853 participants in the present study. Of 4,386 participants with FEV1/FVC greater than or equal to the LLN, 15.4% had abnormal FEV3/FEV6. Compared with normal FEV3/FEV6 and FEV1/FVC, abnormal FEV3/FEV6 was associated with significantly greater gas trapping; St. George's Respiratory Questionnaire score; modified Medical Research Council dyspnea score; and BMI, airflow obstruction, dyspnea, and exercise index and with shorter 6-min walking distance (all P < .0001) but not with CT scanning evidence of emphysema. CONCLUSIONS: Current and ex-smokers with prebronchodilator FEV3/FEV6 less than the LLN as the sole abnormality identifies a distinct population with evidence of small airways disease in quantitative CT scanning, impaired indexes of physical function and quality of life otherwise deemed normal by using the current spirometric definition.United States Department of Health & Human Services - R01 HL 08 9856 - R01 HL 08 9897National Institutes of Health (NIH) - USA - 1KL2TR001419NIH National Heart Lung & Blood Institute (NHLBI) - UL1TR001417 - KL2TR001419 - UL1TR001881NIH National Center for Advancing Translational Sciences (NCATS) - U01HL089897 - U01HL089856 - R01HL124233 - R01HL089856 - R01HL08989

Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10−8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD

Quantitative Computed Tomography in COPD: Possibilities and Limitations

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that is characterized by chronic airflow limitation. Unraveling of this heterogeneity is challenging but important, because it might enable more accurate diagnosis and treatment. Because spirometry cannot distinguish between the different contributing pathways of airflow limitation, and visual scoring is time-consuming and prone to observer variability, other techniques are sought to start this phenotyping process. Quantitative computed tomography (CT) is a promising technique, because current CT technology is able to quantify emphysema, air trapping, and large airway wall dimensions. This review focuses on CT quantification techniques of COPD disease components and their current status and role in phenotyping COPD