New Spirometry Indices for Detecting Mild Airflow Obstruction.
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ABSTRACT:
SUBMITTER: Bhatt SP
PROVIDER: S-EPMC6269456 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature
Publications
New Spirometry Indices for Detecting Mild Airflow Obstruction.
Bhatt Surya P SP Bhakta Nirav R NR Wilson Carla G CG Cooper Christopher B CB Barjaktarevic Igor I Bodduluri Sandeep S Kim Young-Il YI Eberlein Michael M Woodruff Prescott G PG Sciurba Frank C FC Castaldi Peter J PJ Han MeiLan K MK Dransfield Mark T MT Nakhmani Arie A
Scientific reports 20181130 1
The diagnosis of chronic obstructive pulmonary disease (COPD) relies on demonstration of airflow obstruction. Traditional spirometric indices miss a number of subjects with respiratory symptoms or structural lung disease on imaging. We hypothesized that utilizing all data points on the expiratory spirometry curves to assess their shape will improve detection of mild airflow obstruction and structural lung disease. We analyzed spirometry data of 8307 participants enrolled in the COPDGene study, a ...[more]
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Project description:Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation. Spirometry loops are not smooth curves and have undulations and peaks that likely reflect heterogeneity of airflow.Objectives: To assess whether the Peak Index, the number of peaks adjusted for lung size, is associated with clinical outcomes.Methods: We analyzed spirometry data of 9,584 participants enrolled in the COPDGene study and counted the number of peaks in the descending part of the expiratory flow-volume curve from the peak expiratory flow to end-expiration. We adjusted the peaks count for the volume of the lungs from peak expiratory flow to end-expiration to derive the Peak Index. Multivariable regression analyses were performed to test associations between the Peak Index and lung function, respiratory morbidity, structural lung disease on computed tomography (CT), forced expiratory volume in 1 second (FEV1) decline, and mortality.Results: The Peak Index progressively increased from Global Initiative for Chronic Obstructive Lung Disease stage 0 through 4 (P < 0.001). On multivariable analysis, the Peak Index was significantly associated with CT emphysema (adjusted β = 0.906; 95% confidence interval [CI], 0.789 to 1.023; P < 0.001) and small airways disease (adjusted β = 1.367; 95% CI, 1.188 to 1.545; P < 0.001), St. George's Respiratory Questionnaire score (adjusted β = 1.075; 95% CI, 0.807 to 1.342; P < 0.001), 6-minute-walk distance (adjusted β = -1.993; 95% CI, -3.481 to -0.506; P < 0.001), and FEV1 change over time (adjusted β = -1.604; 95% CI, -2.691 to -0.516; P = 0.004), after adjustment for age, sex, race, body mass index, current smoking status, pack-years of smoking, and FEV1. The Peak Index was also associated with the BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index and mortality (P < 0.001).Conclusions: The Peak Index is a spirometry metric that is associated with CT measures of lung disease, respiratory morbidity, lung function decline, and mortality.Clinical trial registered with www.clinicaltrials.gov (NCT00608764).
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Project description: Not available
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Project description:Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10's role in influencing lung's susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.
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