Abstract
Background
Chronic obstructive pulmonary disease (COPD) is characterized by marked phenotypic heterogeneity. Most previous studies have focused on COPD subjects with FEV1 < 80% predicted. We investigated the clinical and genetic heterogeneity in subjects with mild airflow limitation in spirometry grade 1 defined by the Global Initiative for chronic Obstructive Lung Disease (GOLD 1).
Methods
Data from current and former smokers participating in the COPDGene Study (NCT00608764) were analyzed. K-means clustering was performed to explore subtypes within 794 GOLD 1 subjects. For all subjects with GOLD 1 and with each cluster, a genome-wide association study and candidate gene testing were performed using smokers with normal lung function as a control group. Combinations of COPD genome-wide significant single nucleotide polymorphisms (SNPs) were tested for association with FEV1 (% predicted) in GOLD 1 and in a combined group of GOLD1 and smoking control subjects.
Results
K-means clustering of GOLD 1 subjects identified putative “near-normal”, “airway-predominant”, “emphysema-predominant” and “lowest FEV1 % predicted” subtypes. In non-Hispanic whites, the only SNP nominally associated with GOLD 1 status relative to smoking controls was rs7671167 (FAM13A) in logistic regression models with adjustment for age, sex, pack-years of smoking, and genetic ancestry. The emphysema-predominant GOLD 1 cluster was nominally associated with rs7671167 (FAM13A) and rs161976 (BICD1). The lowest FEV1 % predicted cluster was nominally associated with rs1980057 (HHIP) and rs1051730 (CHRNA3). Combinations of COPD genome-wide significant SNPs were associated with FEV1 (% predicted) in a combined group of GOLD 1 and smoking control subjects.
Conclusions
Our results indicate that GOLD 1 subjects show substantial clinical heterogeneity, which is at least partially related to genetic heterogeneity.
Keywords: pulmonary disease, chronic obstructive, population characteristics, cluster analysis, genetic association
Introduction
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality worldwide, which is characterized by persistent and usually progressive airflow limitation. While cigarette smoking is a well-known risk factor, large variability in the response to cigarette smoke exists among individuals 1. Although chronic bronchitis and emphysema are two classic disease-related characteristics of COPD 2, many different COPD-related phenotypes have been suggested 3-9. COPD subjects with the same age, body mass index (BMI), and lung function exhibit different levels of dyspnea, exacerbation frequency, exercise capacity, severity of emphysema, and quality of life 10,11. There have been many reports investigating heterogeneity of COPD patients 3-11. However, most of them have focused on subjects with an FEV1 < 80% predicted 6,7,10-14. Studies of COPD patients with relatively preserved FEV1 are rare 15,16, yet these subjects make up a large proportion of subjects with COPD as defined by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) 17,18. The FEV1/FVC ratio normally falls with increasing age 19, so some fraction of individuals with reduced FEV1/FVC but normal FEV1 are likely healthy 20,21. However, some GOLD 1 subjects will likely progress to moderate and even severe COPD. Identification of the clinical, imaging, and genetic characteristics of GOLD 1 subjects with progressive disease could provide opportunities for early treatment interventions.
To begin to understand the epidemiology and genetics of COPD heterogeneity among individuals with mild airflow limitation, we investigated subjects with spirometry grade 1 defined by GOLD 17 in the COPDGene Study. Our hypothesis was that there is identifiable heterogeneity within GOLD 1 subjects, with some individuals having significant COPD and others being healthy. We also hypothesized that there will be an association of previously described single nucleotide polymorphisms (SNPs) 22-26 with COPD-related phenotypes in GOLD 1 subjects.
Methods
Study Population
COPDGene (clinicaltrials.gov Identifier NCT00608764) is a multicenter study designed to investigate the underlying genetic determinants of COPD. Study details have been described 27 and all protocols and questionnaires are available at http://www.copdgene.org. All subjects were self-identified non-Hispanic white (NHW) or African American (AA) between 45 and 80 years old and had at least 10 pack-years of cigarette smoking. Institutional review board approval was obtained at each of the 21 participating clinical centers; all subjects provided written informed consent. Subjects completed questionnaires, pre- and post-bronchodilator spirometry with quality control review, 6-minute walk test, and volumetric computed tomography (CT) of the chest at both inspiration and expiration.
Variable Definitions
Percent predicted values and lower limits of normal (LLN) were calculated using post-bronchodilator spirometric values 19. Subjects with GOLD spirometry grade 1 were defined as having post-bronchodilator FEV1 ≥ 80% predicted with FEV1/FVC < 0.7, and smoking controls were defined as smokers with normal lung function (post-bronchodilator FEV1 ≥ 80% with FEV1/FVC ≥ 0.7). Among GOLD 1 subjects, LLN-defined subgroups were defined as follows: LLN-COPD subjects had FEV1/FVC < LLN and LLN-normal subjects had FEV1/FVC ≥ LLN based on Hankinson prediction equations 19.
Quantitative CT lung density measurements were performed using Slicer (Version 2, www.slicer.org). Percent emphysema was calculated as the percentage of voxels within the lung with an attenuation < –950 Hounsfield units (HU) at full inspiration [% low attenuation area (LAA)–950insp] 28. For percent emphysema, we used <5% as a normal limit based on measurements from healthy non-smoking controls and ≥10% as a criteria of significant emphysema 29,30. Airway analysis was performed using the Pulmonary Workstation Plus (VIDA Diagnostics, Inc., Coralville, IA). In each segmental bronchus, the wall area (WA) and lumen area (LA) were measured. The segmental wall area % was defined as 100 × WA/ (WA + LA). The square root of the wall area of a hypothetical 10 mm internal perimeter airway (Pi10) was used as another measure of airway disease. Additional variable definitions are available in e-Appendix 1.
Epidemiological analysis
Comparisons of continuous variables between groups were made using a Wilcoxon rank sum test or Kruskal-Wallis test, as appropriate. Chi-square or Fisher’s exact tests were used for categorical variables. Statistical analyses were performed using R (2.15.1). A Venn diagram was generated using an automatic area-proportional Euler diagram drawing tool available at http://www.eulerdiagrams.org/eulerAPE/ (eulerAPE 2.0.3., University of Kent, Canterbury, UK).
Cluster Analysis
K-means clustering analyses were performed on a subset of GOLD 1 subjects with complete data for three key input variables which were selected to capture information related to airflow, emphysema, and airway disease: post-bronchodilator FEV1 % predicted, %LAA–950insp, and segmental wall area %. We used normalized mutual information 31 to determine the optimal number of clusters; clustering and candidate gene testing were performed separately in NHW and AA subjects using R (2.15.1).
Genetic Analysis
Genome-wide SNP genotyping data were obtained on the Illumina (San Diego, CA) OmniExpress platform with additional genotypes imputed using MaCH32 and minimac33 and 1000 Genomes 34 Phase I v3 using European (EUR) or cosmopolitan reference panels for the NHWs and AAs, respectively. Genome-wide association testing for binary GOLD 1 status under an additive model, adjusting for age, sex, pack-years of cigarette smoking, and principal components for genetic ancestry was performed separately in NHW and AA subjects using PLINK 35 with smokers with normal lung function as a control group. Fixed-effects meta-analysis 36 of these two racial groups was performed using METAL (version 2010-08-01) 37 and R 2.15.1 (www.r-project.org) with the meta-package. In addition to the genome-wide analysis, SNPs within genomic regions which have previously been identified to be associated with moderate-to-severe COPD or emphysema at genome-wide significance were further investigated. The single most significant previously reported SNP from the HHIP, FAM13A, RAB4B, and BICD1 regions was included; for the chromosome 15q25 region, which may contain multiple COPD susceptibility loci, two SNPs were selected. These COPD genome-wide significant SNPs were used in genetic association analysis comparing GOLD 1 subjects to smoking controls, and each GOLD 1 cluster to smoking controls; in addition, genetic association analysis with FEV1 (% predicted) was performed in GOLD 1 and combined subjects of GOLD 1 and smoking controls.
Results
Epidemiology
The number of GOLD 1 subjects enrolled in COPDGene was 794. Comparisons between GOLD 1 subjects with LLN-COPD and those with LLN-normal are summarized in Table 1. Subjects meeting both GOLD 1 and LLN-COPD criteria, as expected, were younger; however, we also found higher proportions of AAs and current smokers, decreased BMI and increased total lung capacity measured by CT, as well as an increased prevalence of chronic bronchitis, relative to LLN-normal subjects. While MMRC dyspnea score of LLN-COPD subjects was higher, their mean six-minute walk distance was longer than that of LLN-Normal. However, there were no differences in percentages of emphysema and gas trapping, segmental wall area %, Pi10, exacerbation frequency, history of severe exacerbations, and frequency of respiratory medication use between GOLD 1 LLN-COPD and LLN-Normal subjects. The prevalence of comorbidities in these two groups of GOLD 1 subjects was similar except for diabetes mellitus, hypertension and hyperlipidemia, which were more prevalent in LLN-normal subjects likely related to their older mean age. Physician-diagnosed asthma and COPD were reported in 13.5% and 31% of all GOLD 1 subjects, respectively, and 6.5% received a diagnosis of both asthma and COPD. There were no differences in the rates of physician-diagnosed asthma or physician-diagnosed COPD between the two LLN-defined GOLD 1 groups.
Table 1.
Characteristics of subjects with GOLD Stage 1 in the COPDGene cohort and comparison between two groups of GOLD 1 subjects according to lower limit of normal (LLN) values for FEV1/FVC
| GOLD 1 (All Subjects) | GOLD 1 with FEV1/FVC≥LLN | GOLD 1 with FEV1/FVC<LLN | p-value comparing subjects above and below LLN | |
|---|---|---|---|---|
|
| ||||
| N | 794 | 197 | 597 | |
|
| ||||
| Age, yrs | 61.7 (9.0) | 68.1 (6.4) | 59.7 (8.8) | <0.001 |
| Sex (% Male ) | 57.6 | 53.3 | 59.0 | NS |
| African American (%) | 22.7 | 14.2 | 25.5 | 0.002 |
| Current smoker (%) | 55.8 | 38.1 | 61.6 | <0.001 |
| Smoking pack-years | 45.0 (24.6) | 46.5 (24.3) | 44.5 (24.7) | NS |
| Body mass index, kg/m2 | 27.1 (5.1) | 27.9 (4.6) | 26.8 (5.3) | <0.001 |
|
| ||||
| FEV1 % predicted | 90.8 (9.0) | 92.2 (9.5) | 90.3 (8.8) | 0.011 |
| FVC % predicted | 107.6 (12.4) | 101.9 (10.6) | 109.5 (12.4) | <0.001 |
| FEV1/FVC | 0.65 (0.04) | 0.68 (0.01) | 0.64 (0.04) | <0.001 |
| Positive bronchodilator responsiveness (%) | 14.9 | 10.8 | 16.3 | NS |
|
| ||||
| Total lung capacityCT % predicted | 102.6 (15.0) | 100.4 (14.7) | 103.4 (15.1) | 0.015 |
| % emphysema (% LAA–950insp) | 5.2 (5.7) | 4.7 (4.7) | 5.4 (6.0) | NS |
| % gas trapping (%LAA–856exp) | 20.3 (12.3) | 20.2 (11.2) | 20.3 (12.6) | NS |
| Segmental wall area % | 60.3 (2.8) | 60.1 (2.4) | 60.4 (2.9) | NS |
| Pi10 | 3.62 (0.11) | 3.62 (0.10) | 3.62 (0.11) | NS |
|
| ||||
| 6 minute walk distance, m | 442 (105) | 443 (105) | 462 (105) | 0.029 |
| MMRC dyspnea score | 0.8 (1.2) | 0.6 (1.0) | 0.9 (1.2) | 0.025 |
| Resting O2 saturation, % | 96.7 (2.2) | 96.5 (2.3) | 96.8 (2.2) | 0.036 |
| Chronic bronchitis (% affirmative) | 15.7 | 9.6 | 17.8 | 0.009 |
| Exacerbation frequency, per year | 0.2 (0.7) | 0.1 (0.6) | 0.2 (0.7) | NS |
| Severe exacerbation (% affirmative) | 4.9 | 4.1 | 5.2 | NS |
Definition of abbreviations: LAA = low attenuation area; LLN = lower limit of normal for FEV1/FVC; MMRC = modified Medical Research Council; Pi10 = square root of wall area for a hypothetical airway with an internal perimeter of 10 mm.
Data are presented as mean (standard deviation) or percent.
Bronchodilator responsiveness was considered positive if the change in FEV1 was ≥200mL and ≥ 12% predicted following administration of short-acting inhaled beta-agonist.
For bronchodilator responsiveness, n = 783.
For TLCCT, % emphysema, and segmental wall area %, n = 760.
For % gas trapping, n = 678.
For Pi10, n= 750.
For respiratory medication use, n=782.
Table 2 shows comparisons according to the presence or absence of any respiratory exacerbation in the year prior to study participation among GOLD 1 subjects. Subjects with a history of any respiratory exacerbation were more likely to be female, and they had increased segmental wall area %, higher MMRC dyspnea score, and increased prevalence of chronic bronchitis and physician-diagnosed asthma compared to those without history of exacerbation. Except for oral corticosteroids, all respiratory medications were more frequently used in those with an exacerbation history. However, the prevalence of measured comorbidities did not show any differences between these two groups.
Table 2.
Comparisons according to the presence or absence of any respiratory exacerbations in the one year period before COPDGene study enrollment among subjects with GOLD stage 1*
| No exacerbation | Exacerbation | p-value | |
|---|---|---|---|
|
| |||
| N | 684 | 110 | |
|
| |||
| Age, yrs | 61.8 (8.9) | 61.3 (9.6) | NS |
| Sex (% male ) | 59.4 | 46.4 | 0.014 |
| African American (%) | 22.8 | 21.8 | NS |
| Current smoker (%) | 56.4 | 51.8 | NS |
| Smoking pack-years | 44.7 (23.5) | 46.9 (30.6) | NS |
| Body mass index, kg/m2 | 27.0 (5.0) | 27.7 (5.8) | NS |
|
| |||
| FEV1 % predicted | 90.9 (9.0) | 90.1 (9.2) | NS |
| FVC % predicted | 107.4 (12.1) | 108.8 (14.2) | NS |
| FEV1/FVC | 0.65 (0.04) | 0.64 (0.05) | NS |
| Positive bronchodilator responsiveness (%) | 14.3 | 18.7 | NS |
|
| |||
| Total Lung CapacityCT % predicted | 102.3 (14.8) | 104.5 (16.2) | NS |
| % emphysema (% LAA–950insp) | 5.1 (5.2) | 6.1 (7.8) | NS |
| % gas trapping (%LAA–856exp) | 20.4 (12.2) | 19.8 (13.1) | NS |
| Segmental wall area % | 60.2 (2.7) | 60.8 (3.1) | 0.04 |
| Pi10 | 3.62 (0.11) | 3.64 (0.11) | NS |
|
| |||
| 6 minute walk distance, m | 459 (106) | 442 (102) | NS |
| MMRC dyspnea score | 0.7 (1.1) | 1.6 (1.3) | <0.001 |
| Resting O2 saturation, % | 96.8 (2.2) | 96.2 (2.7) | NS |
| Chronic bronchitis (% affirmative) | 13.9 | 27.3 | 0.001 |
| Exacerbation frequency, per year | 0 | 1.6 (1.2) | <0.001 |
| Physician-diagnosed asthma (% affirmative) | 10.7 | 30.9 | <0.001 |
|
| |||
| Short-acting beta-agonist use (% affirmative) | 12.1 | 54.1 | <0.001 |
| Long-acting beta-agonist use (% affirmative) | 0.6 | 6.4 | <0.001 |
| Ipratropium use (% affirmative) | 0.7 | 4.6 | 0.007 |
| Tiotropium use (% affirmative) | 4.6 | 18.3 | <0.001 |
| Inhaled corticosteroid use (% affirmative) | 2.8 | 12.8 | <0.001 |
| Oral corticosteroid use (% affirmative) | 0.6 | 1.9 | NS |
Thirteen subjects who indicated that they had an ER visit or hospitalization in the past year but who did not respond affirmatively to the question “Have you had a flare-up of your chest trouble in the last 12 months” were included in the exacerbation group.
Definition of abbreviations: LAA = low attenuation area; MMRC = modified Medical Research Council; Pi10 = square root of wall area for a hypothetical airway with an internal perimeter of 10 mm.
Data are presented as mean (standard deviation) or percent.
Bronchodilator responsiveness was considered positive if the change in FEV1 was ≥200mL and ≥ 12% predicted following administration of short acting inhaled beta-agonist.
For bronchodilator responsiveness, n = 783.
For TLCCT, % emphysema, and segmental wall area %, n = 760.
For % gas trapping, n = 678.
For Pi10, n= 750.
For respiratory medication use, n=782.
Table 3 compares GOLD 1 subjects with and without significant emphysema. Among subjects with significant emphysema, there were more males, fewer current smokers, higher pack-years of smoking, lower BMI, lower segmental wall area %, and lower Pi10 compared with those without significant emphysema. Tiotropium was more frequently used in subjects with higher % emphysema. There were no differences in frequency of exacerbation and prevalence of comorbidities between these groups except for coronary artery disease. These epidemiological analyses suggest substantial heterogeneity within the GOLD 1 group, which is illustrated in Figure 1.
Table 3.
Comparisons according to percent emphysema among subjects with GOLD stage 1
| % LAA-950insp <5% | %LAA-950insp≥10% | p-value | |
|---|---|---|---|
|
| |||
| N | 487 | 121 | |
|
| |||
| Age, yrs | 60.7 (9.0) | 65.2 (7.7) | <0.001 |
| Sex (% Male ) | 52.4 | 68.6 | 0.002 |
| African American (%) | 24.6 | 16.5 | NS |
| Current smoker (%) | 64.5 | 30.6 | <0.001 |
| Smoking pack-years | 43.5 (23.7) | 52.2 (27.9) | 0.002 |
| Body mass index, kg/m2 | 27.3 (5.1) | 26.2 (5.1) | 0.016 |
|
| |||
| FEV1 % predicted | 90.6 (8.7) | 92.5 (10.9) | NS |
| FVC % predicted | 106.5 (12.3) | 112.7 (13.9) | <0.001 |
| FEV1/FVC | 0.66 (0.04) | 0.62 (0.06) | <0.001 |
| Positive bronchodilator responsiveness (%) | 16.3 | 13.4 | NS |
|
| |||
| Total lung capacityCT % predicted | 99.8 (14.8) | 107.6 (14.6) | <0.001 |
| % emphysema (% LAA-950insp) | 2.0 (1.4) | 15.8 (5.8) | <0.001 |
| % gas trapping (%LAA-856exp) | 16.3 (11.1) | 32.3 (11.0) | <0.001 |
| Segmental wall area % | 60.7 (2.9) | 59.3 (2.4) | <0.001 |
| Pi10 | 3.64 (0.11) | 3.58 (0.10) | <0.001 |
|
| |||
| 6 minute walk distance, m | 456 (97) | 465 (123) | NS |
| MMRC dyspnea score | 0.75 (1.16) | 0.96 (1.28) | NS |
| Resting O2 saturation, % | 96.9 (2.1) | 96.0 (2.6) | <0.001 |
| Chronic bronchitis (% affirmative) | 16.0 | 15.7 | NS |
| Exacerbation frequency, per year | 0.2 (0.7) | 0.2 (0.5) | NS |
| Severe exacerbation (% affirmative) | 4.5 | 5.8 | NS |
|
| |||
| Short-acting beta-agonist use (% affirmative) | 16.4 | 23.3 | NS |
| Long-acting beta-agonist use (% affirmative) | 1.0 | 3.3 | NS |
| Ipratropium use (% affirmative) | 0.8 | 2.5 | NS |
| Tiotropium use (% affirmative) | 3.5 | 19.2 | <0.001 |
| Inhaled corticosteroid use (% affirmative) | 4.2 | 5.8 | NS |
| Oral corticosteroid use (% affirmative) | 0.6 | 0.8 | NS |
Definition of abbreviations: LAA = low attenuation area; MMRC = modified Medical Research Council; Pi10 = square root of wall area for a hypothetical airway with an internal perimeter of 10 mm.
Data are presented as mean (standard deviation) or percent.
Bronchodilator responsiveness was considered positive if the change in FEV1 was ≥200mL and ≥ 12% predicted following administration of short-acting inhaled beta-agonist.
For bronchodilator responsiveness, n = 598.
For % gas trapping, n = 549.
For Pi10, n= 600.
For respiratory medication use, n=599.
Figure 1.
Venn diagram for clinical heterogeneity of GOLD 1*
*The area for each group and the area of overlap are proportional to the number of subjects. LLN: lower limit of normal for FEV1/FVC. LLN-Normal subjects have FEV1/FVC values greater than or equal to this threshold, while LLN-COPD subjects have FEV1/FVC below this threshold. Exacerbation: the presence of any respiratory exacerbations in the one year period before COPDGene study enrollment.
% emphysema: the percentage of voxels within the lung with an attenuation < –950 Hounsfield units (HU) from volumetric chest CT measurements at full inspiration [% low attenuation area (LAA)–950insp].
Cluster Analysis
To further explore heterogeneity in GOLD 1 subjects, we performed cluster analysis. The subset of GOLD 1 subjects with complete data for FEV1 % predicted, % emphysema, and segmental wall area % included in the cluster analysis (n = 760) did not differ from the full cohort of GOLD 1 subjects with respect to mean age, pack-years of cigarette smoking, BMI, or distribution by gender or current smoking status. Normalized mutual information analysis demonstrated high cluster reproducibility for k = 4 clusters (Table E1). The results of k-means clustering in NHW subjects with GOLD 1 are summarized in Table 4. Members of cluster 1 demonstrated the highest post-bronchodilator FEV1 % predicted; we refer to this cluster as a putative “near-normal subtype”. Members of cluster 2 have the youngest age, the highest BMI and segmental wall area %, the highest proportion of chronic bronchitis and bronchodilator responsiveness, and the shortest 6 minute walk distance; we refer to this cluster as a putative “airway-predominant subtype”. Members of cluster 3 have the oldest age, the lowest BMI, the highest % emphysema, % gas trapping, and MMRC dyspnea score, the lowest rate of current smoking but the highest pack-years, and the lowest resting O2 saturation; we refer to this cluster as the “emphysema-predominant subtype”. Finally, members of cluster 4 show the lowest post-bronchodilator FEV1 % predicted and rate of bronchodilator responsiveness; we refer to this as the “lowest FEV1 % predicted subtype”.
Table 4.
Results of k-means clustering for k = 4 clusters in non-Hispanic white subjects with GOLD 1 (N=594)
| Feature | Near-normal | Airway-predominant | Emphysema-predominant | Lowest FEV1 % predicted | p-value* |
|---|---|---|---|---|---|
|
| |||||
| N | 104 | 201 | 68 | 221 | |
|
| |||||
| Variables used to classify | |||||
| FEV1 % predicted | 105.9 (8.1) | 88.3 (5.5) | 88.9 (6.9) | 87.0 (4.6) | <0.001 |
| % emphysema | 5.8 (4.7) | 2.9 (2.6) | 17.3 (5.6) | 4.2 (2.9) | <0.001 |
| Segmental wall area % | 58.6 (2.0) | 62.8 (1.8) | 59.1 (2.1) | 58.6 (1.6) | <0.001 |
|
| |||||
| Variables used to assess clusters | |||||
| Age, yrs | 64.5 (8.7) | 61.9 (9.5) | 65.6 (6.8) | 63.4 (8.3) | 0.012 |
| Sex (% male) | 66.3 | 55.2 | 69.1 | 55.2 | NS |
| Body mass index, kg/m2 | 26.5 (5.1) | 28.1 (5.2) | 26.1 (4.3) | 26.5 (4.2) | 0.001 |
| Current smoker (%) | 52.9 | 54.7 | 20.6 | 43.0 | <0.001 |
| Smoking pack-years | 43.0 (20.8) | 46.4 (25.1) | 55.1 (27.4) | 44.9 (23.7) | 0.01 |
|
| |||||
| FVC % predicted | 122.4 (13.0) | 103.2 (8.8) | 110.1 (11.2) | 102.2 (8.2) | <0.001 |
| FEV1/FVC | 0.65 (0.04) | 0.65 (0.04) | 0.61 (0.06) | 0.65 (0.04) | <0.001 |
| FEF 25-75% | 1.58 (0.57) | 1.32 (0.48) | 1.21 (0.48) | 1.25 (0.45) | <0.001 |
| Positive bronchodilator responsiveness (%) | 12.6 | 18.7 | 16.4 | 10.5 | NS |
|
| |||||
| Total lung capacityCT % predicted | 111.2 (14.4) | 100.6 (15.3) | 109.2 (13.3) | 103.0 (13.3) | <0.001 |
| % emphysema upper third | 5.9 (6.1) | 3.0 (3.7) | 21.1 (9.3) | 4.9 (4.7) | <0.001 |
| % emphysema lower third | 6.1 (4.8) | 3.1 (2.9) | 14.1 (7.2) | 4.1 (3.1) | <0.001 |
| % emphysema upper 3rd/lower 3rd ratio | 1.2 (1.5) | 1.9 (4.8) | 2.6 (4.5) | 2.1 (3.8) | <0.001 |
| % gas trapping | 21.7 (10.4) | 16.7 (10.9) | 34.7 (8.9) | 19.5 (9.9) | <0.001 |
|
| |||||
| 6 minute walk distance, m | 495 (99) | 457 (97) | 485 (98) | 469 (93) | 0.015 |
| MMRC dyspnea score | 0.40 (0.81) | 0.78 (1.16) | 0.91 (1.28) | 0.73 (1.12) | 0.027 |
| Resting O2 saturation, % | 96.8(2.0) | 96.7 (2.1) | 95.8 (2.4) | 96.5 (2.4) | 0.023 |
| Chronic bronchitis (% affirmative) | 11.5 | 21.9 | 16.2 | 13.1 | 0.046 |
| Exacerbation frequency, per year | 0.1 (0.4) | 0.3 (0.9) | 0.2 (0.6) | 0.2 (0.7) | 0.036 |
|
| |||||
| SGRQ score symptoms | 21.2 (20.0) | 30.3 (24.1) | 27.0 (25.6) | 23.6 (23.0) | 0.003 |
| SGRQ score active | 16.6 (17.6) | 26.9 (24.0) | 28.1 (26.0) | 23.9 (23.1) | 0.004 |
| SGRQ score impact | 6.1 (10.7) | 12.7 (16.3) | 13.5 (16.6) | 9.8 (14.3) | <0.001 |
| SGRQ score total | 11.6 (12.4) | 19.8 (18.1) | 20.1 (19.4) | 16.3 (16.8) | <0.001 |
Definition of abbreviations: MMRC = Modified Medical Research Council; SGRQ = St. George Respiratory Questionnaire.
Data are presented as mean (standard deviation) or percent. Bronchodilator responsiveness was considered positive if the change in FEV1 was ≥200mL and ≥ 12% predicted following administration of short-acting inhaled beta-agonist.
Kruskal-Wallis test comparing four clusters
Table E2 shows the results of k-means clustering in AA GOLD 1 subjects on the left and the results of clustering AA GOLD 1 subjects by using clustering centers of NHW subjects on the right. The reproducibility rate of assigning AA subjects using these two methods was 75%.
Genetics
After genotyping and quality control, 587 subjects with GOLD 1 and 2,534 smoking controls were included for genetic analysis of NHWs, and 161 GOLD 1 subjects and 1,749 smoking controls were included for genetic analysis of AAs. GWAS of all GOLD 1 subjects relative to smoking controls for each of NHWs and AAs did not include any SNPs that reached the genome-wide significance threshold (p<5×10-8) (Table E3 and E4, Fig. E1 and E2). The most significantly associated SNPs for all GOLD 1 subjects relative to smoking controls were: rs6084592 on chromosome 20p13 (RNF24, p=1.06×10-7) in NHW and rs114095670 on 9p13.3 (RECK, p=5.92×10-8) in AA. Neither a meta-analysis of NHWs and AAs nor additional analyses with adding current/former smoking status as an adjustment variable led to any SNPs meeting genome-wide significance.
GWAS of each GOLD 1 cluster relative to smoking controls was performed separately in NHW and AA subjects; only SNPs with minor allele frequencies (MAFs) above 5% were analyzed. There were only two genome-wide significant SNPs, rs7268680 near to KIF16B on 20p12.1 with MAF of 0.09 (p=1.67×10-8) in the lowest FEV1 GOLD 1 cluster of NHWs (n=219) and rs17669292 near to TAF13 on 1p13.3 with MAF of 0.1 (p=3.35×10-8) in the lowest FEV1 GOLD 1 cluster of AAs (n=66). Further replication of these cluster-specific findings will be required, since the sample sizes are quite small for a GWAS.
Since the GWAS results in our relatively small sample size of GOLD 1 subjects were not genome-wide significant, we assessed genetic variants associated with COPD or emphysema previously reported to be genome-wide significant in the literature including rs7671167 (4q22, FAM13A); rs1980057 (4q31, HHIP); rs13180 and rs1051730 (15q25, IREB2/CHRNA3); rs161976 (12p11, BICD1); and rs7937 (19q13, RAB4B) 22-26. These SNPs were examined for associations with GOLD 1 relative to smoking controls, GOLD 1 cluster relative to smoking controls, and post-bronchodilator FEV1 % predicted among combined subjects with GOLD 1 and smoking controls or only GOLD 1 subjects.
In NHWs, the only SNP nominally associated with GOLD 1 status relative to smoking controls was rs7671167 (FAM13A) in both univariate and multiple logistic regression models with adjustment for age, sex, pack-years of cigarette smoking and genetic ancestry principal components (Table 5). In the analysis of GOLD 1 clusters, we noted a general lack of genetic associations in the near-normal and airway-predominant clusters; however, nominally significant associations were found between the emphysema-predominant GOLD 1 cluster and SNPs near FAM13A (rs7671167) and BICD1 (rs161976). The lowest FEV1 % predicted cluster was associated with rs1980057 (HHIP) and rs1051730 (CHRNA3) (Table 6). While two SNPs, rs1051730 (CHRNA3) and rs7937 (RAB4B), were associated with post-bronchodilator FEV1 % predicted in the combined group of GOLD 1 and smoking control subjects in both univariate and multiple linear regression models with adjustment for pack-years of cigarette smoking and the genetic ancestry principal components, rs1980057 (HHIP) was associated with FEV1 % predicted in subjects with GOLD 1 in only univariate linear regression analysis (Table 7).
Table 5.
Logistic regression analyses of previously identified COPD GWAS SNPs with GOLD 1 (n=587) relative to smokers with normal lung function (n=2,534) among non-Hispanic white subjects in the COPDGene cohort*
| Locus | Nearest gene | SNP | Risk/non-risk allele | Odds ratio | 95% CI | p-value† |
|---|---|---|---|---|---|---|
| 4q22 | FAM13A | rs7671167 | T/C | 1.15 | 1.01-1.32 | 0.035 |
| 4q31 | HHIP | rs1980057 | C/T | 1.13 | 0.99-1.29 | 0.064 |
| 15q25 | IREB2 | rs13180 | T/C | 1.12 | 0.98-1.29 | 0.091 |
| 15q25 | CHRNA3 | rs1051730 | A/G | 1.15 | 1.00-1.32 | 0.050 |
| 12p11 | BICD1 | rs161976 | G/A | 1.05 | 0.93-1.20 | NS |
| 19q13 | RAB4B | rs7937 | T/C | 1.03 | 0.90-1.17 | NS |
Adjusted for age, sex, pack-years of cigarette smoking and genetic ancestry as summarized in the principal components.
p-values <0.1 are expressed.
Table 6.
Logistic regression analyses of previously identified COPD GWAS SNPs with each GOLD 1 cluster relative to smokers with normal lung function (n=2,534) in non-Hispanic white subjects*
| Locus | Nearest gene | SNP | Risk/non-risk allele | Airway-predominant† vs. smoking controls | Emphysema-predominant‡ vs. smoking controls | Lowest FEV1 % predicted§ vs. smoking controls | |||
|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p¶ | OR (95% CI) | p¶ | OR (95% CI) | p¶ | ||||
| 4q22 | FAM13A | rs7671167 | T/C | 1.15 (0.93-1.42) | NS | 1.57 (1.10-2.25) | 0.014 | 1.11 (0.91-1.36) | NS |
| 4q31 | HHIP | rs1980057 | C/T | 1.09 (0.89-1.34) | NS | 1.32 (0.93-1.90) | NS | 1.26 (1.03-1.55) | 0.024 |
| 15q25 | IREB2 | rs13180 | T/C | 1.08 (0.87-1.34) | NS | 0.94 (0.65-1.37) | NS | 1.20 (0.97-1.48) | 0.092 |
| 15q25 | CHRNA3 | rs1051730 | A/G | 0.99 (0.79-1.23) | NS | 0.92 (0.62-1.34) | NS | 1.34 (1.09-1.65) | 0.006 |
| 12p11 | BICD1 | rs161976 | G/A | 1.07 (0.87-1.32) | NS | 1.54 (1.08-2.22) | 0.020 | 0.98 (0.81-1.20) | NS |
| 19q13 | RAB4B | rs7937 | T/C | 0.99 (0.80-1.22) | NS | 1.33 (0.94-1.93) | NS | 0.95 (0.78-1.16) | NS |
Adjusted for age, sex, pack-years of cigarette smoking and genetic ancestry as summarized in the principal components.
For the airway-predominant GOLD 1 cluster, n = 198.
For the emphysema-predominant GOLD 1 cluster, n=68.
For the lowest FEV1 % predicted GOLD 1 cluster, n=219.
p-values <0.1 are expressed.
Table 7.
Linear regression analyses of previously identified COPD GWAS SNPs with post-bronchodilator FEV1 % predicted among non-Hispanic white subjects with GOLD 1 and smoking controls or only GOLD 1 subjects*
| Locus | Nearest gene | SNP | Risk/non-risk allele | GOLD 1 and smoking controls | GOLD 1 | ||||
|---|---|---|---|---|---|---|---|---|---|
|
|
|||||||||
| Risk allele frequency | β | p-value† | Risk allele frequency | β | p-value† | ||||
| 4q22 | FAM13A | rs7671167 | T/C | 0.49 | −0.25 | NS | 0.52 | 0.54 | NS |
| 4q31 | HHIP | rs1980057 | C/T | 0.58 | −0.42 | NS | 0.60 | −1.23 | 0.026 |
| 15q25 | IREB2 | rs13180 | T/C | 0.61 | −0.06 | NS | 0.63 | −0.09 | NS |
| 15q25 | CHRNA3 | rs1051730 | A/G | 0.35 | −0.67 | 0.023 | 0.37 | −0.25 | NS |
| 12p11 | BICD1 | rs161976 | G/A | 0.56 | 0.15 | NS | 0.57 | −0.32 | NS |
| 19q13 | RAB4B | rs7937 | T/C | 0.55 | −0.75 | 0.006 | 0.56 | −0.13 | NS |
Adjusted for pack-years of cigarette smoking and genetic ancestry as summarized in the principal components.
p-values <0.1 are expressed.
In AAs, the only SNP nominally associated with GOLD 1 status relative to smoking controls was rs1051730 (CHRNA3) in both univariate and multiple logistic regression models (Table E5). In the analysis of AA GOLD 1 clusters compared to AA smoking controls, nominally significant association was found between the near-normal GOLD 1 cluster and rs1051730 (CHRNA3) (Table E6). In AAs, there were no SNPs associated with post-bronchodilator FEV1 % predicted in the combined group of GOLD 1 and smoking control subjects or in only GOLD 1 subjects.
In NHWs but not in AAs, the number of COPD risk alleles based on four previously reported COPD genome-wide significant associations, consisting of rs7671167 (FAM13A), rs1980057 (HHIP), rs1051730 (CHRNA3), and rs7937 (RAB4B), were negatively associated with post-bronchodilator FEV1 % predicted (p<0.001) and positively associated with % emphysema among combined subjects with GOLD 1 and smoking controls (p=0.022, Fig. 2), but not in only GOLD 1 subjects.
Figure 2.
Mean (A) post-bronchodilator FEV1 % predicted (N=3,121) and (B) percent emphysema (N=2,984) according to the number* of known COPD risk allele for rs7671167 (FAM13A), rs1980057 (HHIP), rs1051730 (CHRNA3) and rs7937 (RAB4B) in non-Hispanic white subjects with GOLD 1 or normal lung function
Discussion
This study demonstrates that substantial phenotypic heterogeneity of COPD exists even in individuals with mild airflow limitation. We also found that genetic variants previously associated with moderate-to-severe COPD demonstrate evidence for genetic associations with reduced lung function and clustering-derived clinical subtypes of GOLD 1 subjects. Our findings provide suggestive evidence that at least part of the observed phenotypic heterogeneity in GOLD 1 subjects is related to genetic variants.
Previous studies that have focused on subjects with mild airflow obstruction are rare. Recently, a physiological study showed that the respiratory system reached its physiologic limit in mild COPD at a lower peak work rate and ventilation than in healthy participants 16. Although most of the GOLD 1 subjects in our study did not have severe emphysema or functional limitations, a small number of GOLD 1 subjects had severe emphysema (>20%) and even resting hypoxemia. We found clinical heterogeneity of GOLD 1 population in various aspects. Firstly, we compared GOLD 1 subjects with LLN-COPD to those with LLN-normal. Those with LLN-COPD had some evidence for increased respiratory symptoms compared to LLN-normal subjects, based on their higher mean MMRC score and increased prevalence of chronic bronchitis, but they had better exercise performance—which may relate to their younger mean age. We found that GOLD 1 subjects with a history of respiratory exacerbations had increased respiratory symptoms (chronic bronchitis and dyspnea) and increased respiratory medication use. The GOLD 1 subjects with a history of respiratory exacerbations exhibited thicker airway walls and increased prevalence of chronic bronchitis compared to those without an exacerbation in the year before study enrollment. Previously, many studies have reported increased risk of COPD exacerbations in patients with chronic bronchitis 7,38,39. Also, GOLD 1 subjects with a history of respiratory exacerbations reported physician-diagnosed asthma more frequently compared to those without, which is consistent with a previous study demonstrating increased frequency of exacerbations in patients with moderate-to-severe COPD and a history of physician-diagnosed asthma compared to those without a history of physician-diagnosed asthma 40.
In order to provide insights into the substantial clinical heterogeneity which we observed, we selected post-bronchodilator FEV1 % predicted, % emphysema, and segmental wall area % for cluster analysis; these variables were chosen based on many previous studies demonstrating that these phenotypes represent key components of COPD, including airflow limitation, parenchymal destruction, and airway disease, respectively 5,28,30,41,41,42. K-means clustering showed four discrete subgroups, which were similar in NHW and AA subjects. The airway-predominant cluster is characterized by poor exercise performance and quality of life in spite of relatively young age, low percentages of emphysema and gas trapping, and high rate of post-bronchodilator response, which may be related to their high prevalence of chronic bronchitis and increased airway wall thickness. While airway- and emphysema-predominant GOLD 1 clusters represent two classic phenotypes 2, the near-normal cluster may represent individuals who have a reduced FEV1/FVC but are otherwise well. Of interest, their mean FVC % predicted value exceeds the normal upper limit (122.4%) in contrast with a normal mean FEV1 % predicted (105.9%).
Even though GWASs of GOLD 1 relative to smoking controls revealed no genome-wide significant associations in both NHWs and AAs, the top SNP in AA subjects, rs114095670, was nearly genome-wide significant and is located within RECK, a negative regulator of MMP9 43,44, which was previously reported by our group to be regulated by HHIP in human bronchial epithelial cells 45. In both NHWs and AAs, the airway-predominant GOLD 1 cluster did not show any significant associations with previously identified COPD risk alleles. Interestingly, SNPs nominally associated (p<0.05) with the emphysema-predominant NHW GOLD 1 cluster relative to smoking controls were different from those associated with the lowest FEV1 % predicted cluster. These results support the concept that clinical heterogeneity of COPD may be closely related to genetic heterogeneity. A SNP associated with the emphysema-predominant NHW GOLD 1 cluster, rs161976 (BICD1), was previously demonstrated in GWAS for emphysema in COPD patients with FEV1 <80% predicted 24. The lowest FEV1 % predicted subgroup had the lowest rate of post-bronchodilator response, suggesting fixed airway obstruction. Each subtype may have, at least in part, a different set of genetic susceptibility determinants. Even though the known COPD genome-wide significant SNPs do not provide a complete explanation for COPD, the number of risk alleles at four previously reported COPD GWAS loci correlated with post-bronchodilator FEV1 % predicted in the group of COPDGene subjects with normal FEV1 values (smoking controls and GOLD 1). Thus, we reconfirmed that these COPD risk alleles, identified in GWAS of moderate-to-severe COPD 22,23,25,26, likely play a role in mild COPD as well.
Our study is the largest detailed description of GOLD 1 reported to date and demonstrates a relationship between genetic variation and clinical heterogeneity. However, our study did have several important limitations. Despite the size of our study, the number of subjects is still small in the context of GWAS and likely limits our ability to detect novel genetic variants. It is not yet clear whether known predictors of lung function decline or future respiratory exacerbations in moderate-to-severe COPD will be applicable for GOLD 1. Whether our four clusters will demonstrate stability or progression to advanced COPD stages will need to be addressed with longitudinal studies.
Clinically useful subtypes in subjects with mild airflow limitation should be helpful for individualized treatment and/or risk prediction. The currently available evidence is not adequate to create such a clinically useful set of GOLD 1 subtypes with certainty; replication of our proposed subtypes in other study populations will be necessary. In addition, genetic markers may be useful to define GOLD 1 subtypes; for example, our results suggest that an NHW subject with risk alleles for both FAM13A and BICD1 might have an increased risk of emphysema, while an NHW subject with risk alleles for HHIP and CHRNA3 might experience accelerated decline of FEV1. These conjectures will also need to be validated in other study populations.
In summary, we have reported epidemiological and radiographic characteristics of GOLD 1 subjects, explored clinically relevant putative subtypes, and analyzed genetic associations with these subtypes. The current study has clearly shown substantial clinical heterogeneity of GOLD 1 subjects; our results also suggest that different genetic determinants may influence different GOLD 1 subtypes. Future work including larger numbers of GOLD 1 subjects for genetic association studies as well as longitudinal follow-up of GOLD 1 subjects may provide new insights into COPD progression and therapeutic approaches.
Supplementary Material
Highlights.
This study is the largest detailed description of GOLD 1 subjects reported to date.
Substantial phenotypic heterogeneity of GOLD 1 subjects exists.
Cluster analysis identified clinically relevant subtypes of GOLD 1 subjects.
Some of these GOLD1 subtypes were associated with known COPD genetic risk variants.
Acknowledgments
This study was funded by NIH R01 HL089856 (E.K.S.) and R01 HL089897 (J.D.C.) and P01 HL105339 (E.K.S.).
We acknowledge and thank the COPDGene Core Teams:
Administrative Core: James D. Crapo, MD (PI); Edwin K. Silverman, MD, PhD (PI); Barry J. Make, MD; Elizabeth A. Regan, MD, PhD; Stephanie Bratschie, MPH; Rochelle Lantz; Sandra Melanson, MSW, LCSW; Lori Stepp
Executive Committee: Terri Beaty, PhD; Russell P. Bowler, MD, PhD; James D. Crapo, MD; Jeffrey L. Curtis, MD; Douglas Everett, PhD; MeiLan K. Han, MD, MS; John E. Hokanson, MPH, PhD; David Lynch, MB; Barry J. Make, MD; Elizabeth A. Regan, MD, PhD; Edwin K. Silverman, MD, PhD; E. Rand Sutherland, MD
External Advisory Committee: Eugene R. Bleecker, MD; Harvey O. Coxson, PhD; Ronald G. Crystal, MD; James C. Hogg, MD; Michael A. Province, PhD; Stephen I. Rennard, MD; Duncan C. Thomas, PhD
NHLBI: Thomas Croxton, MD, PhD; Weiniu Gan, PhD; Lisa Postow, PhD
COPD Foundation: John W. Walsh; Randel Plant; Delia Prieto
Biorepository Visit 1 (Baltimore): Homayoon Farzadegan, PhD; Samantha Bragan; Stacey Cayetano
Biorepository Visit 2 (Boston): Daniel Cossette; Roxanne K. Kelly, MBA
Data Coordinating Center: Douglas Everett, PhD; Andre Williams, PhD; Ruthie Knowles; Carla Wilson, MS
Epidemiology Core: John Hokanson, MPH, PhD; Jennifer Black-Shinn, MPH; Gregory Kinney, MPH
Genetic Analysis Core: Terri Beaty, PhD; Peter J. Castaldi, MD, MSc; Michael Cho, MD; Dawn L. DeMeo, MD, MPH; Marilyn G. Foreman, MD, MS; Nadia N. Hansel, MD, MPH; Megan E. Hardin, MD; Craig Hersh, MD, MPH; Jacqueline Hetmanski, MS; John E. Hokanson, MPH, PhD; Nan Laird, PhD; Christoph Lange, PhD; Sharon M. Lutz, MPH, PhD; Manuel Mattheisen, MD; Merry-Lynn McDonald, MSc, PhD; Margaret M. Parker, MHS; Elizabeth A. Regan, MD, PhD; Stephanie Santorico, PhD; Edwin K. Silverman, MD, PhD; Emily S. Wan, MD; Jin Zhou, PhD
Genotyping Cores: Genome-Wide Core: Terri Beaty, PhD; Candidate Genotyping Core: Craig P. Hersh, MD, MPH; Edwin K. Silverman, MD, PhD
Imaging Core: David Lynch, MB; Mustafa Al Qaisi, MD; Jaleh Akhavan; Christian W. Cox, MD; Harvey O. Coxson, PhD; Deanna Cusick; Jennifer G. Dy, PhD; Shoshana Ginsburg, MS; Eric A. Hoffman, PhD; Philip F. Judy, PhD; Alex Kluiber; Alexander McKenzie; John D. Newell, Jr., MD; John J. Reilly, Jr., MD; James Ross, MSc; Raul San Jose Estepar, PhD; Joyce D. Schroeder, MD; Jered Sieren; Arkadiusz Sitek, PhD; Douglas Stinson; Edwin van Beek, MD, PhD, MEd; George R. Washko, MD; Jordan Zach
PFT QA Core: Robert Jensen, PhD; E. Rand Sutherland, MD
Biological Repository, Johns Hopkins University, Baltimore, MD: Homayoon Farzadegan, PhD: Samantha Bragan; Stacey Cayetano
We further wish to acknowledge the COPDGene Investigators from the participating Clinical Centers:
Ann Arbor VA: Jeffrey Curtis, MD, Ella Kazerooni, MD
Baylor College of Medicine, Houston, TX: Nicola Hanania, MD, MS, Philip Alapat, MD, Venkata Bandi, MD, Kalpalatha Guntupalli, MD, Elizabeth Guy, MD, Antara Mallampalli, MD, Charles Trinh, MD, Mustafa Atik, MD, Hasan Al-Azzawi, MD, Marc Willis, DO, Susan Pinero, MD, Linda Fahr, MD, Arun Nachiappan, MD, Collin Bray, MD, L. Alexander Frigini, MD, Carlos Farinas, MD, David Katz, MD, Jose Freytes, MD, Anne Marie Marciel, MD
Brigham and Women’s Hospital, Boston, MA: Dawn DeMeo, MD, MPH, Craig Hersh, MD, MPH, George Washko, MD, Francine Jacobson, MD, MPH, Hiroto Hatabu, MD, PhD, Peter Clarke, MD, Ritu Gill, MD, Andetta Hunsaker, MD, Beatrice Trotman-Dickenson, MBBS, Rachna Madan, MD
Columbia University, New York, NY: R. Graham Barr, MD, DrPH, Byron Thomashow, MD, John Austin, MD, Belinda D’Souza, MD
Duke University Medical Center, Durham, NC: Neil MacIntyre, Jr., MD, Lacey Washington, MD, H Page McAdams, MD
Fallon Clinic, Worcester, MA: Richard Rosiello, MD, Timothy Bresnahan, MD, Joseph Bradley, MD, Sharon Kuong, MD, Steven Meller, MD, Suzanne Roland, MD
Health Partners Research Foundation, Minneapolis, MN: Charlene McEvoy, MD, MPH, Joseph Tashjian, MD
Johns Hopkins University, Baltimore, MD: Robert Wise, MD, Nadia Hansel, MD, MPH, Robert Brown, MD, Gregory Diette, MD, Karen Horton, MD
Los Angeles Biomedical Research Institute at Harbor UCLA Medical Center, Los Angeles, CA: Richard Casaburi, MD, Janos Porszasz, MD, PhD, Hans Fischer, MD, PhD, Matt Budoff, MD, Mehdi Rambod, MD
Michael E. DeBakey VAMC, Houston, TX: Amir Sharafkhaneh, MD, Charles Trinh, MD, Hirani Kamal, MD, Roham Darvishi, MD, Marc Willis, DO, Susan Pinero, MD, Linda Fahr, MD, Arun Nachiappan, MD, Collin Bray, MD, L. Alexander Frigini, MD, Carlos Farinas, MD, David Katz, MD, Jose Freytes, MD, Anne Marie Marciel, MD
Minneapolis VA: Dennis Niewoehner, MD, Quentin Anderson, MD, Kathryn Rice, MD, Audrey Caine, MD
Morehouse School of Medicine, Atlanta, GA: Marilyn Foreman, MD, MS, Gloria Westney, MD, MS, Eugene Berkowitz, MD, PhD
National Jewish Health, Denver, CO: Russell Bowler, MD, PhD, David Lynch, MB, Joyce Schroeder, MD, Valerie Hale, MD, John Armstrong, II, MD, Debra Dyer, MD, Jonathan Chung, MD, Christian Cox, MD
Temple University, Philadelphia, PA: Gerard Criner, MD, Victor Kim, MD, Nathaniel Marchetti, DO, Aditi Satti, MD, A. James Mamary, MD, Robert Steiner, MD, Chandra Dass, MD, Libby Cone, MD
University of Alabama, Birmingham, AL: William Bailey, MD, Mark Dransfield, MD, Michael Wells, MD, Surya Bhatt, MD, Hrudaya Nath, MD, Satinder Singh, MD
University of California, San Diego, CA: Joe Ramsdell, MD, Paul Friedman, MD
University of Iowa, Iowa City, IA: Alejandro Cornellas, MD, John Newell, Jr., MD, Edwin JR van Beek, MD, PhD
University of Michigan, Ann Arbor, MI: Fernando Martinez, MD, MeiLan Han, MD, Ella Kazerooni, MD
University of Minnesota, Minneapolis, MN: Christine Wendt, MD, Tadashi Allen, MD
University of Pittsburgh, Pittsburgh, PA: Frank Sciurba, MD, Joel Weissfeld, MD, MPH, Carl Fuhrman, MD, Jessica Bon, MD, Danielle Hooper, MD
University of Texas Health Science Center at San Antonio, San Antonio, TX: Antonio Anzueto, MD, Sandra Adams, MD, Carlos Orozco, MD, Mario Ruiz, MD, Amy Mumbower, MD, Ariel Kruger, MD, Carlos Restrepo, MD, Michael Lane, MD
The COPDGene project is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, Novartis, Pfizer, Siemens and Sunovion. The sponsor had no role in the design of the study, the collection and analysis of the data, or in the preparation of the manuscript.
Footnotes
Conflicts of interest: In the past 3 years, Drs Lee, McDonald, Castaldi, Crapo, Wan, Dy, Regan, Hardin and Mr Chang have no competing interests. In the past 3 years, Dr. Silverman reports grants from NIH, grants and other support from COPD Foundation, grants and personal fees from GlaxoSmithKline, during the conduct of the study; personal fees from Merck and travel support from Novartis, outside the submitted work. In the past 3 years, Dr. Cho reports grants from NIH / NHLBI, grants from Alpha-1 Foundation, during the conduct of the study; personal fees from Merck, outside the submitted work. In the past 3 years, Dr. Hersh reports grants from National Institutes of Health, during the conduct of the study; personal fees from Novartis, personal fees from CSL Behring, outside the submitted work. In the past 3 years, Dr DeMeo has received NIH grant (outside the submitted work).
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