Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Haghighi B

PROVIDER: S-EPMC6631615 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

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

Haghighi Babak B Choi Sanghun S Choi Jiwoong J Hoffman Eric A EA Comellas Alejandro P AP Newell John D JD Lee Chang Hyun CH Barr R Graham RG Bleecker Eugene E Cooper Christopher B CB Couper David D Han Mei Lan ML Hansel Nadia N NN Kanner Richard E RE Kazerooni Ella A EA Kleerup Eric A C EAC Martinez Fernando J FJ O'Neal Wanda W Paine Robert R Rennard Stephen I SI Smith Benjamin M BM Woodruff Prescott G PG Lin Ching-Long CL

Respiratory research 20190715 1

<h4>Background</h4>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.<h4>Methods</h4>An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 7 ...[more]

PMID: 31307479

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Project description:Background: Marijuana is often smoked via a filterless cigarette and contains similar chemical makeup as smoked tobacco. There are few publications describing usage patterns and respiratory risks in older adults or in those with chronic obstructive pulmonary disease (COPD). Methods: A cross-sectional analysis of current and former tobacco smokers from the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) study assessed associations between marijuana use and pulmonary outcomes. Marijuana use was defined as never, former (use over 30 days ago), or current (use within 30 days). Respiratory health was assessed using quantitative high-resolution computed tomography (HRCT) scans, pulmonary function tests and questionnaire responses about respiratory symptoms. Results: Of the total 2304 participants, 1130 (49%) never, 982 (43%) former, and 192 (8%) current marijuana users were included. Neither current nor former marijuana use was associated with increased odds of wheeze (odds ratio [OR] 0.87, OR 0.97), cough (OR 1.22; OR 0.93) or chronic bronchitis (OR 0.87; OR 1.00) when compared to never users. Current and former marijuana users had lower quantitative emphysema (P=0.004, P=0.03), higher percent predicted forced expiratory volume in 1 second (FEV1%) (P<0.001, P<0.001), and percent predicted forced vital capacity (FVC%) (p<0.001, P<0.001). Current marijuana users exhibited higher total tissue volume (P=0.003) while former users had higher air trapping (P<0.001) when compared to never marijuana users. Conclusions: Marijuana use was found to have little to no association with poor pulmonary health in older current and former tobacco smokers after adjusting for covariates. Higher forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) was observed among current marijuana users. However, higher joint years was associated with more chronic bronchitis symptoms (e.g., wheeze), and this study cannot determine if long-term heavy marijuana smoking in the absence of tobacco smoking is associated with lung symptoms, airflow obstruction, or emphysema, particularly in those who have never smoked tobacco cigarettes.

Project description:Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) is a multi-center longitudinal, observational study to identify novel phenotypes and biomarkers of chronic obstructive pulmonary disease (COPD). In a subset of 300 subjects enrolled at six clinical centers, we are performing flow cytometric analyses of leukocytes from induced sputum, bronchoalveolar lavage (BAL) and peripheral blood. To minimize several sources of variability, we use a "just-in-time" design that permits immediate staining without pre-fixation of samples, followed by centralized analysis on a single instrument.The Immunophenotyping Core prepares 12-color antibody panels, which are shipped to the six Clinical Centers shortly before study visits. Sputum induction occurs at least two weeks before a bronchoscopy visit, at which time peripheral blood and bronchoalveolar lavage are collected. Immunostaining is performed at each clinical site on the day that the samples are collected. Samples are fixed and express shipped to the Immunophenotyping Core for data acquisition on a single modified LSR II flow cytometer. Results are analyzed using FACS Diva and FloJo software and cross-checked by Core scientists who are blinded to subject data.Thus far, a total of 152 sputum samples and 117 samples of blood and BAL have been returned to the Immunophenotyping Core. Initial quality checks indicate useable data from 126 sputum samples (83%), 106 blood samples (91%) and 91 BAL samples (78%). In all three sample types, we are able to identify and characterize the activation state or subset of multiple leukocyte cell populations (including CD4+ and CD8+ T cells, B cells, monocytes, macrophages, neutrophils and eosinophils), thereby demonstrating the validity of the antibody panel.Our study design, which relies on bi-directional communication between clinical centers and the Core according to a pre-specified protocol, appears to reduce several sources of variability often seen in flow cytometric studies involving multiple clinical sites. Because leukocytes contribute to lung pathology in COPD, these analyses will help achieve SPIROMICS aims of identifying subgroups of patients with specific COPD phenotypes. Future analyses will correlate cell-surface markers on a given cell type with smoking history, spirometry, airway measurements, and other parameters.This study was registered with ClinicalTrials.gov as NCT01969344 .

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Dataset Information

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

Methods

Results

Conclusions

Publications

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

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