American Journal of Respiratory and Critical Care Medicine

Rationale: It is unclear whether airway wall thickening and emphysema make independent contributions to airflow limitation in chronic obstructive pulmonary disease (COPD) and whether these phenotypes cluster within families.

Objectives: To determine whether airway wall thickening and emphysema (1) make independent contributions to the severity of COPD and (2) show independent aggregation in families of individuals with COPD.

Methods: Index cases with COPD and their smoking siblings underwent spirometry and were offered high-resolution computed tomography scans of the thorax to assess the severity of airway wall thickening and emphysema.

Measurements and Main Results: A total of 3,096 individuals were recruited to the study, of whom 1,159 (519 probands and 640 siblings) had technically adequate high-resolution computed tomography scans without significant non–COPD-related thoracic disease. Airway wall thickness correlated with pack-years smoked (P ≤ 0.001) and symptoms of chronic bronchitis (P < 0.001). FEV1 (expressed as % predicted) was independently associated with airway wall thickness at a lumen perimeter of 10 mm (P = 0.0001) and 20 mm (P = 0.0013) and emphysema at −950 Hounsfield units (P < 0.0001). There was independent familial aggregation of both the emphysema (adjusted odds ratio, 2.1; 95% confidence interval, 1.1–4.0; P ≤ 0.02) and airway disease phenotypes (P < 0.0001) of COPD.

Conclusions: Airway wall thickening and emphysema make independent contributions to airflow obstruction in COPD. These phenotypes show independent aggregation within families of individuals with COPD, suggesting that different genetic factors influence these disease processes.

Scientific Knowledge on the Subject

It is unclear whether airway wall thickening and emphysema make independent contributions to airflow limitation in chronic obstructive pulmonary disease (COPD) and whether these phenotypes cluster within families.

What This Study Adds to the Field

Our data show that airway wall thickening and emphysema make independent contributions to airflow obstruction. These phenotypes also show independent aggregation within families of individuals with COPD.

Chronic obstructive pulmonary disease (COPD) is characterized by progressive and poorly reversible airflow limitation (1). It results from a combination of at least two pathologic processes: small airway remodeling and obstruction (2) and a loss of lung elastic recoil due to alveolar destruction (emphysema) (3). Their relative proportion can vary considerably between individuals with the same degree of airflow limitation (4, 5), and thus spirometry is inadequate to fully characterize COPD. However, imaging of the lung with high-resolution computed tomography (HRCT) provides a sensitive method to identify emphysema (68) and offers promise for quantifying airway remodeling (9, 10).

Tobacco smoking is the major risk factor for COPD (1114), but, for unknown reasons, only a proportion of smokers develop airflow obstruction (12, 15). The striking familial aggregation of COPD (16, 17) implies that shared genetic and/or environmental factors (18, 19) place some families at a much greater risk of COPD if they smoke. However, it is not known whether this familial aggregation of COPD is the result of a shared risk for small airway disease, emphysema, or both. We have established a multicenter International COPD Genetics Network (ICGN) that aims to identify genes that predispose cigarette smokers to COPD (20). This well-characterized cohort has been used to test the hypotheses that airway disease and emphysema (1) make independent contributions to the severity of COPD and (2) show independent aggregation in families of individuals with COPD. Some of the results of these studies have been reported previously in the form of abstracts (21, 22).

Population and Ethics

Inclusion criteria for index cases (probands) were airflow limitation (post-bronchodilator FEV1 < 60% predicted and FEV1/VC < 90% predicted, age 45 to 65 years, a smoking history of ≥5 pack-years, and at least one sibling with a smoking history of ≥5 pack-years. An FEV1/VC < 90% predicted approximates an FEV1/VC < 0.7 but corrects for age (23). Individuals with Pi ZZ, ZNull, Null-Null, or SZ α1-antitrypsin genotypes were excluded. All subjects gave written, informed consent, and the study was approved by the respective institutional review boards.

Clinical Data and Spirometric Measurements

Clinical symptoms, demographic data, and details of smoking exposure were obtained in a structured interview using a modified version of the American Thoracic Society/Division of Lung Diseases Respiratory Epidemiology Questionnaire (24). Spirometry was performed pre- and post-bronchodilator (salbutamol 180 μg administered via an Aerochamber spacer) using a Survey Tach portable spirometer (W.E. Collins, Braintree, MA). All measurements were taken by trained operators using a standardized protocol in accordance with American Thoracic Society standards (25). At least three recordings were made and the higher of the slow and forced vital capacity (FVC) was used as the VC. This overcomes the possibility of the FVC underestimating VC in some individuals with COPD. The resulting values were compared with predicted values of FEV1 and FVC (26). COPD in siblings was defined by a post-bronchodilator FEV1 of less than 80% predicted and an FEV1/VC of less than 90% predicted.

HRCT

All probands, as well as their siblings with a smoking history of greater than 5 pack-years, were invited for an HRCT of the thorax (1-mm sections at 20-mm intervals, 120 kilovolts [peak] [kVp], 200 mA·s) to assess the presence of emphysema and airway remodeling. All of the images were transferred to the study radiology center in Vancouver where the extent of emphysema was independently scored by two radiologists (see the online supplement Methods and Table E1 of the online supplement). The extent of emphysema was categorized by visual inspection as none or trivial (<5% of lung involved), mild (5–25%), moderate (25–50%), or severe (>50%). Quantitative assessment of emphysema was performed by density mask analysis using a threshold of −950 Hounsfield units (HU) (27, 28). Airways were assessed by plotting lumen perimeter (Pi) against the square root of wall area for all airways with a Pi > 6 mm and calculating the square root of the wall area at a Pi of 10 mm and 20 mm for each subject (29).

Statistical Analysis

Post-bronchodilator values of FEV1 and VC were used in the analysis. The means of continuous variables were compared using Student's t test, Kruskal-Wallis test, or analysis of variance as appropriate. Differences in proportions were compared using a χ2 test. Pairwise Pearson correlation coefficients were calculated between seven variables: FEV1, FEV1/VC, emphysema at −950 HU, emphysema at −910 HU, Pi10, Pi20, and pack-years of smoking. Generalized estimating equations and random effects mixed linear models were used to adjust for confounding variables and familial correlations as described previously (16). Statistical analyses were performed using the software packages SAS (SAS Institute, Cary, NC) and STATA (Stata Corp., College Station, TX).

Demographics of the Cohort

A total of 3,505 individuals were recruited to the study between June 2000 and April 2003. Of these individuals, 401 were subsequently found to be ineligible because they failed to meet the inclusion criteria; eight half-siblings were also excluded. The characteristics of the remaining 3,096 individuals (1,156 probands and 1,940 siblings) are summarized in Table E2. A total of 104 of the 1,156 probands were singletons (i.e., no siblings agreed to join the study); the remaining probands had between one and nine siblings (median, 2 interquartile range, 1). Post-bronchodilator spirometry results were available for 1,887 (97.3%) of the siblings with 723 (38.3%) meeting the criteria for COPD.

COPD Phenotypes as Determined by HRCT

Qualitative HRCT data were available for 1,224 individuals (561 probands [48.5%] and 663 siblings [34.2%]; Table E3). Thirty-one individuals with HRCT data (24 probands and 7 siblings) were considered to have moderate or severe bronchiectasis on HRCT and were excluded from all subsequent analyses. A further 34 individuals were excluded because the HRCT scan was of insufficient quality. Of the remaining 1,159 individuals, 519 (44.8%) were probands, whereas 640 (55.2%) were siblings (Table 1). The radiologists' assessment identified emphysema (>5% of lung involved) in 429 (82.7%) of the probands and 250 (39.1%) of the siblings (Table 2).

TABLE 1. COMPARISON OF THE CHARACTERISTICS OF PROBANDS AND SIBLINGS WITH VALID HIGH-RESOLUTION COMPUTED TOMOGRAPHY DATA




Probands

Siblings

P
Number519640
Male, % (n)51.0 (301)51.9 (332)<0.05
Age, yr (SD)58.0 (5.3)57.2 (9.0)NS
Current smokers, % (n)35.7 (185)52.5 (336)<0.001
Age started smoking, yr (SD)15.7 (3.7)16.0 (3.9)NS
Pack-years smoked, median (IQR)45 (31.1)34.5 (26.4)≤0.0001
FEV1% predicted (SD)36.3 (13.0)81.9 (25.6)<0.001
FEV1/VC, % predicted (SD)
45.5 (14.3)
79.3 (18.1)
<0.001

Definition of abbreviations: IQR = interquartile range; NS = not significant.

TABLE 2. CHARACTERISTICS OF INDIVIDUALS (PROBANDS AND SIBLINGS) BY EXTENT OF EMPHYSEMA BASED ON RADIOLOGISTS' QUALITATIVE ASSESSMENT OF THE HIGH-RESOLUTION COMPUTED TOMOGRAPHY SCAN



Extent of Emphysema


None/Trivial*
Mild
Moderate
Severe
P
Number480228185266
Men, % (n)52.7 (253)59.7 (136)56.8 (105)52.3 (139)NS
Age, yr (SD)56.5 (8.8)57.8 (7.1)58.3 (6.9)58.7 (5.5)NS
Current smokers, % (n)47.1 (226)61.8 (141)41.6 (77)28.9 (77)≤0.001
Age started smoking, yr (SD)16.3 (4.3)15.3 (3.7)15.2 (3.5)16.0 (3.7)0.04
Pack-years smoked, median (IQR)31.7 (27.9)43.0 (32.0)44.9 (32.3)43.0 (27.8)≤0.0001
FEV1% predicted (SD)80.8 (28.5)65.2 (25.8)46.8 (21.1)33.6 (13.6)≤0.0001
FEV1/VC, % predicted (SD)
81.5 (18.2)
66.4 (17.6)
50.9 (15.5)
40.1 (12.1)
≤0.0001

Definition of abbreviations: IQR = interquartile range; NS = not significant.

*Defined as less than 5% of lung affected.

Quantitative HRCT data were available for 1,032 individuals. The mean number of airways analyzed per subject was 27 (SD, 16; minimum, 4; maximum, 101). The mean number of airways per subject that had an internal perimeter (Pi) greater than 6 mm was 14 (SD, 9; minimum, 3; maximum, 80). Those subjects who did not have three or more airways with a Pi greater than 6 mm were excluded from the calculation of Pi10 (square root of the airway wall area at Pi of 10 mm) and Pi20. Pi10 was significantly greater in individuals with, as opposed to without, chronic cough (0.489 [SD, 0.044] vs. 0.476 [0.043] cm), chronic expectoration of sputum (0.491 [SD, 0.043] vs. 0.475 [SD, 0.043] cm), and chronic bronchitis (defined as a daily cough productive of sputum for 3 mo for 2 consecutive years) (0.492 [SD, 0.045] vs. 0.477 [SD, 0.043] cm) (P < 0.001 for each comparison). Similar results were observed with Pi20. For example, subjects with chronic bronchitis had a larger airway wall area at Pi20 (0.728 [SD, 0.095] cm) compared with subjects without chronic bronchitis (0.699 [SD, 0.088] cm) (P < 0.001).

Association between Cigarette Smoking, Emphysema, and Airway Wall Thickness

The risk for the presence of more than 5% lung involvement of emphysema on the radiologist's scoring of the CT scans increased with each pack-year smoked (odds ratio [OR], 1.023; 95% confidence interval [CI], 1.018–1.029; P ≤ 0.001). The quantitative emphysema data confirmed the significant association between pack-years smoked and emphysema at both −950 (P < 0.0001) and −910 (P = 0.0001) HU when adjusted for age, sex, weight, and center effects. The cumulative pack-years smoked was significantly associated with airway wall thickness at Pi10 and Pi20 (r = 0.26 and r = 0.19, P ≤ 0.001). Multivariate analysis, which included adjustment for age, sex, weight, current smoking status, study center, and familial clustering, confirmed a significant relationship between pack-years smoked and airway wall thickness at Pi10 (P = 0.0001) and Pi20 (P = 0.016). Weak negative correlations were observed between quantitative measures of emphysema and airway wall thickness. For emphysema at −950 HU, the correlations with Pi10 (r = −0.11, P < 0.01) and Pi20 (r = −0.12, P < 0.01) were both statistically significant. The negative correlations between these phenotypes (more emphysema is correlated with thinner airways) suggest that emphysema and airway wall thickening are independent processes.

Contribution of Emphysema and Airway Wall Thickness to Airflow Obstruction

Qualitatively assessed emphysema severity (mild, moderate, severe) was related to impairment in FEV1 and FEV1/VC (Table 2; P for trend ≤ 0.001), even after the exclusion of probands (Figure 1). The quantitative extent of emphysema, as determined by the density mask analysis at −950 HU, was also inversely associated with FEV1% predicted (r = −0.31, P < 0.001) and FEV1/VC% predicted (r = −0.41, P < 0.001). Multivariate analysis with random effects mixed linear models was used to determine if airway wall thickness and emphysema made independent contributions to airflow obstruction. After adjustment for pack-years smoked, current smoking status, study center, and weight, there were highly significant independent associations between airway wall thickness at 10 mm (P = 0.0001) and emphysema at −950 HU (P < 0.0001) with FEV1% predicted. Similarly, a multivariate model with the same covariates demonstrated significant and independent effects of airway wall thickness at 20 mm (P = 0.0013) and emphysema (P < 0.0001) with FEV1% predicted. These results demonstrate an independent contribution of emphysema and airway wall thickening to airflow obstruction in COPD.

Familial Clustering of Emphysema and Airway Wall Thickness

To assess whether there is a genetic predisposition to the development of emphysema, the risk of emphysema in the sibling group was assessed in relation to the presence of emphysema in the family proband. There were 285 families in which qualitative HRCT data were available for both the proband and at least one sibling. This analysis was therefore restricted to the 476 siblings from these families. Of these 476 siblings, 404 (84.9%) were from a family in which the proband had more than 5% lung involvement of emphysema as scored by the radiologist and 72 (15.1%) were from families where the proband had no or trivial emphysema. The prevalence and severity of COPD (as assessed by FEV1) were not significantly different between siblings of probands with significant emphysema (44.9% affected) and siblings of probands without emphysema (40.9%). However, emphysema was more prevalent in the siblings of probands with significant emphysema (44.8%) than in siblings of probands without emphysema (26.4%; OR, 2.3; 95% CI, 1.3–4.0; P ≤ 0.004). To assess for confounding by cigarette smoking, generalized estimating equations were used to adjust for cumulative pack-years smoked and age and to allow for the inclusion of variable numbers of siblings within a family. Even after adjustment for these variables, siblings from families in which the proband had emphysema were more likely to have emphysema than siblings from families in which the proband did not have emphysema (adjusted OR, 2.1; 95% CI, 1.1–4.0; P < 0.02).

The effect of proband phenotype on sibling phenotype was further assessed using the quantitative scores from the density mask analysis and measurements of airway wall thickness. Random effects mixed linear models were used to adjust for age, sex, pack-years smoked, current smoking status, study center, weight, and the inclusion of sibling clusters. In these analyses, summarized in Table 3, sibling emphysema was significantly associated with proband emphysema (P = 0.0005). Moreover, sibling airway wall thickness at Pi10 was significantly associated with proband airway wall thickness at Pi10 (P < 0.0001).

TABLE 3. MULTIVARIATE ANALYSIS OF FAMILIAL AGGREGATION OF EMPHYSEMA AND AIRWAY WALL THICKNESS


Predictor of Sibling Pi10

Regression Coefficient (95% CI)

P Value

Predictor of Sibling Emphysema at −950 HU

Regression Coefficient (95% CI)

P Value
Proband Pi100.41 (0.28 to 0.53)<0.0001Proband emphysema0.15 (0.07 to 0.24)0.0005
Pack-years0.00027 (0.000078 to 0.00045)0.006Pack-years0.0002 (−0.0001 to 0.0006)0.2
Sex0.016 (0.0078 to 0.025)0.0003Sex0.033 (0.016 to 0.051)0.0002
Current smoking0.01 (0.0019 to 0.020)0.02Current smoking−0.028 (−0.046 to −0.0097)0.003
Weight (kg)0.0007 (0.0004 to 0.001)<0.0001Weight (kg)−0.0005 (−0.001 to 0.000)0.05
Age0.00035 (−0.0002 to 0.0009)0.2Age0.0018 (0.00077 to 0.0028)0.0007
Center
NA
0.049
Center
NA
<0.0001

Definition of abbreviations: CI = confidence interval; HU = Hounsfield units; NA = not applicable; Pi10 = calculated square root of wall area at internal perimeter of 10 mm.

The recruitment of a large, well-characterized cohort of probands with COPD and their smoking siblings has allowed us to explore the relationship between airway remodeling, emphysema, and airflow obstruction in siblings with and without COPD. Our data show that airway wall thickening and emphysema make independent contributions to airflow obstruction. It is well known that within a population of cigarette smokers there is variation in susceptibility to developing airflow obstruction (1114), with previous studies suggesting that some of this variation may be genetic (16, 17). In this study, we again demonstrate a high prevalence of airflow obstruction in the siblings of probands with COPD and, by precise phenotyping, we were able to demonstrate independent familial aggregation of both airway remodeling and emphysema. This suggests that the development of airflow obstruction in a susceptible cigarette smoker may be the result of genetic predisposition to airway remodeling or emphysema. The familial aggregation of emphysema in this cohort was striking, with siblings of an affected proband having a greater than twofold increased risk of emphysema than siblings of a proband without emphysema, despite a similar overall prevalence of airflow obstruction. Moreover, this effect was independent of pack-years smoked. These findings suggest that precise phenotyping of individuals with COPD will be required if we are to identify genes that render smokers susceptible to the different components of COPD. The identification of at least two distinct pathophysiologic processes in COPD may also have important implications for the design of new therapies to treat this disorder.

The results reported in this study are critically dependent on the use of HRCT imaging. A standard algorithm was used for the 16 different CT scanners (listed in Table E1) in the 10 clinical centers that participated in this study. There was a significant “center effect” in the measurement of emphysema (Table 3). However, there was also a significant center effect in FEV1, suggesting that the subjects being enrolled were different in each center. This is perhaps best exemplified by the site in Denver, which is a quaternary care center for lung volume reduction surgery. The subjects from Denver had the lowest mean FEV1 of all the centers in the ICGN. The issue of center effect was also addressed by repeating the analysis with data acquired on only the GE (Milwaukee, WI) and Siemens (Erlangen, Germany) CT scanners (which have a similar noise profile). There was no difference in the findings—for example, the results in Table E4 are comparable to those in Table 3. Thus, the data are likely to be comparable despite being acquired from different centers with a range of CT scanners.

Both single- and multislice CT scanners were used in this study. The images were reconstructed using a high spatial frequency reconstruction algorithm, and a threshold cutoff value of −950 HU was used to define emphysema. This protocol for the detection of emphysema has shown good correlation with histologic emphysema when assessed on either single-slice (30) or multislice CT scanners (31). Multislice CT scanners are better at lung volume and density resolution than single-slice CT scanners (32), but they were not in widespread use at the start of the study. Nevertheless, the densitometry results produced by single-slice CT scanners are comparable between sites (33, 34). Indeed, when the analysis was repeated after the removal of the sites at which part of the data was collected with multislice scanners (Holland, Harvard, and Vancouver), the familial clustering of the airway and emphysema phenotypes remained unchanged. There was only modest agreement between the radiologist (quantitative) and qualitative scores of emphysema (Figure E1), but in both cases there was a poor correlation between smoking history and the severity of emphysema. The correlation was stronger between cumulative pack-years smoked and airway wall thickening and this remained robust after adjustment for relevant covariates. The association between airway wall thickening and chronic cough and sputum production provides support for this being a marker of the mucus hypersecretion that defines chronic bronchitis.

A potential limitation of our study is that qualitative HRCT data were only available for 33% of the sibling group. However, in siblings with HRCT data, there was not a significant difference in either the FEV1% predicted or in the proportion of siblings with COPD, by proband phenotype. Therefore, the greater prevalence of emphysema in siblings of probands with emphysema when compared with probands without emphysema cannot be explained by a difference in airflow limitation between the sibling groups. Another potential limitation is that we only assessed airway wall dimensions in airways with an internal perimeter of more than 6 mm (this conforms to airways with an internal diameter >2 mm) when it is known that the major site of airflow obstruction is in bronchioles smaller than 2 to 3 mm in diameter (35). However airway dimensions in larger airways have been shown to be a reasonable surrogate for those in bronchioles (29). If we had been able to assess the dimensions in smaller airways, we may have found even better correlations with pulmonary function as reported recently (10).

Our results have identified a strong familial risk for the development of airway wall thickening and emphysema within families, which we attribute to genetic susceptibility. This may also result from shared environmental exposures. However, no environmental exposure has been identified that can confer this level of risk other than cigarette smoking. Moreover, the nonsmoking siblings of probands with severe, early-onset COPD have normal values for FEV1 (17). Thus, our results provide strong support for the two major components of COPD being the result of independent interactions between cigarette smoking and genetic susceptibility. Although these findings have obvious implications for the identification of genes that render smokers susceptible to COPD, they also have implications for prognosis and therapy. Individuals with a greater degree of emphysema have more symptoms for a given reduction in FEV1 (5). Thus, those families with the “emphysema” phenotype will be at more risk of symptomatic COPD if they smoke than those with an “airway phenotype.” Moreover, any future therapeutic intervention that is effective at preventing or reversing a component of COPD (airway disease or emphysema) may be most beneficial for siblings because they are likely to share the same disease phenotype and will therefore be predicted to have a similar therapeutic response.

The authors thank the clinical fellows, field workers, radiologists, and data managers who made this study possible: Boston, MA: James Keary, An Ly Church, Kim LaDouceur, Deborah Russ; Cambridge, UK: Sean McCloskey, Tina Audley, Judy Ryan, Angela Tasker, Pamela DeClive-Lowe; Copenhagen, Denmark: Oli Dalsgaard; Liverpool, UK: Paul Walker, Deirdre Frost; Maastricht, The Netherlands: Herman-Jan Pennings, Miriam Groenen; Omaha, Nebraska: Mary Carlson; Spain: Jaume Sauleda (Hospital Universitario Son Dureta), Marc Miravitlles (Barcelona), Jose Luis Alvarez-Sala (Madrid), Victor Sobradillo (Bilbao); Vancouver, Canada: Ramon Sheehan, Stephen Melsom, David Wong, Winnie Zhao, Dianna Louie, Clea Amundsen, Anh-Toan Tran, Joanne Carmen, Roxanne Rousseau, Georgina Lopez; Veruno, Italy: Silvestro D'Anna; GlaxoSmithKline: Rachel Taylor, Mark Hall, Sara Alalouf, and Sandra Hammond.

1. Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, Fukuchi Y, Jenkins C, Rodriguez-Roisin R, van Weel C, et al.; Global Initiative for Chronic Obstructive Lung Disease. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2007;176:532–555.
2. Hogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, Cherniack RM, Rogers RM, Sciurba FC, Coxson HO, et al. The nature of small-airway obstruction in chronic obstructive pulmonary disease. N Engl J Med 2004;350:2645–2653.
3. Hogg JC. Pathophysiology of airflow limitation in chronic obstructive pulmonary disease. Lancet 2004;364:709–721.
4. Hogg JC, Wright JL, Wiggs BR, Coxson HO, Opazo Saez A, Paré PD. Lung structure and function in cigarette smokers. Thorax 1994;49:473–478.
5. Makita H, Nasuhara Y, Nagai K, Ito Y, Hasegawa M, Betsuyaku T, Onodera Y, Hizawa N, Nishimura M; Hokkaido COPD Cohort Study Group. Characterisation of phenotypes based on severity of emphysema in chronic obstructive pulmonary disease. Thorax 2007;62:932–937.
6. Thurlbeck WM, Müller NL. Emphysema: definition, imaging, and quantification. Am J Roentgenol 1994;163:1017–1025.
7. Foster WL Jr, Pratt PC, Roggli VL, Godwin JD, Halvorsen RA Jr, Putman CE. Centrilobular emphysema: CT–pathologic correlation. Radiology 1986;159:27–32.
8. Bergin C, Müller N, Nichols DM, Lillington G, Hogg JC, Mullen B, Grymaloski MR, Osborne S, Paré PD. The diagnosis of emphysema: a computed tomographic–pathologic correlation. Am Rev Respir Dis 1986;133:541–546.
9. Nakano Y, Muro S, Sakai H, Hirai T, Chin K, Tsukino M, Nishimura K, Itoh H, Paré PD, Hogg JC, et al. Computed tomographic measurements of airway dimensions and emphysema in smokers: correlation with lung function. Am J Respir Crit Care Med 2000;162:1102–1108.
10. Hasegawa M, Nasuhara Y, Onodera Y, Makita H, Nagai K, Fuke S, Ito Y, Betsuyaku T, Nishimura M. Airflow limitation and airway dimensions in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2006;173:1309–1315.
11. Fletcher C, Peto R. The natural history of chronic airflow obstruction. BMJ 1977;1:1645–1648.
12. Burrows B, Knudson RJ, Cline MG, Lebowitz MD. Quantitative relationships between cigarette smoking and ventilatory function. Am Rev Respir Dis 1977;115:195–205.
13. Dockery DW, Speizer FE, Ferris BG Jr, Ware JH, Louis TA, Spiro A III. Cumulative and reversible effects of lifetime smoking on simple tests of lung function in adults. Am Rev Respir Dis 1988;137:286–292.
14. Peat JK, Woolcock AJ, Cullen K. Decline of lung function and development of chronic airflow limitation: a longitudinal study of non-smokers and smokers in Busselton, Western Australia. Thorax 1989;45:32–37.
15. Rennard SI, Vestbo J. COPD: the dangerous underestimate of 15%. Lancet 2006;367:1216–1219.
16. Silverman EK, Chapman HA, Drazen JM, Weiss ST, Rosner B, Campbell EJ, O'Donnell WJ, Reilly JJ, Ginns L, Mentzer S, et al. Genetic epidemiology of severe, early-onset chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1998;157:1770–1778.
17. McCloskey SC, Patel BD, Hinchliffe SJ, Reid ED, Wareham NJ, Lomas DA. Siblings of patients with severe chronic obstructive pulmonary disease have a significant risk of airflow obstruction. Am J Respir Crit Care Med 2001;164:1419–1424.
18. Silverman EK, Speizer FE. Risk factors for the development of chronic obstructive pulmonary disease. Med Clin North Am 1996;80:501–522.
19. Lomas DA, Silverman EK. Genetics of chronic obstructive pulmonary disease. Respir Res 2001;2:20–36.
20. Zhu G, Warren L, Aponte J, Gulsvik A, Bakke P, Anderson WH, Lomas DA, Silverman EK, Pillai SG; ICGN Investigators. The SERPINE2 gene is associated with chronic obstructive pulmonary disease in two large populations. Am J Respir Crit Care Med 2007;176:167–173.
21. Patel BD, Coxson H, Pillai S, Anderson W, Pare P, Muller N, Silverman EK, Lomas DA. The role of smoking and familial factors in the development of emphysematous and non-emphysematous COPD [abstract]. Am J Respir Crit Care Med 2004;169:A507.
22. Patel B, Make BJ, Coxson HO, Muller NL, Pillai S, Anderson W, Silverman E, Lomas DA; for the GSK COPD International Genetics Network. Airway and parenchymal disease in chronic obstructive pulmonary disease are distinct phenotypes. Proc Am Thorac Soc 2006;3:533.
23. Hardie JA, Buist AS, Vollmer WM, Ellingsen I, Bakke PS, Mørkve O. Risk of over-diagnosis of COPD in asymptomatic elderly never-smokers. Eur Respir J 2002;20:1117–1122.
24. Ferris BG. Epidemiology standardization project. Am Rev Respir Dis 1978;118(Suppl):1–120.
25. American Thoracic Society. Standardization of spirometry. Am J Respir Crit Care Med 1994;152:1107–1136.
26. Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis 1981;123:659–664.
27. Coxson HO, Rogers RM, Whittall KP, D'Yachkova Y, Paré PD, Sciurba FC, Hogg JC. A quantification of the lung surface area in emphysema using computed tomography. Am J Respir Crit Care Med 1999;159:851–856.
28. Gevenois PA, de Maertelaer V, De Vuyst P, Zanen J, Yernault JC. Comparison of computed density and macroscopic morphometry in pulmonary emphysema. Am J Respir Crit Care Med 1995;152:653–657.
29. Nakano Y, Wong JC, de Jong PA, Buzatu L, Nagao T, Coxson HO, Elliott WM, Hogg JC, Paré PD. The prediction of small airway dimensions using computed tomography. Am J Respir Crit Care Med 2005;171:142–146.
30. Gevenois PA, De Vuyst P, de Maertelaer V, Zanen J, Jacobovitz D, Cosio MG, Yernault J-C. Comparison of computed density and microscopic morphometry in pulmonary emphysema. Am J Respir Crit Care Med 1996;154:187–192.
31. Madani A, Zanen J, de Maertelaer V, Gevenois PA. Pulmonary emphysema: objective quantification at multi-detector row CT: comparison with macroscopic and microscopic morphometry. Radiology 2006;238:1036–1043.
32. Stoel BC, Bakker ME, Stolk J, Dirksen A, Stockley RA, Piitulainen E, Russi EW, Reiber JH. Comparison of the sensitivities of 5 different computed tomography scanners for the assessment of the progression of pulmonary emphysema: a phantom study. Invest Radiol 2004;39:1–7.
33. Kemerink GJ, Lamers RJS, Thelissen GRP, van Engelshoven JMA. Scanner conformity in CT densitometry of the lungs. Radiology 1995;197:749–752.
34. Kemerink GJ, Lamers RJ, Thelissen GR, van Engelshoven JM. CT densitometry of the lungs: scanner performance. J Comput Assist Tomogr 1996;20:24–33.
35. Hogg JC, Macklem PT, Thurlbeck WM. Site and nature of airway obstruction in chronic obstructive lung disease. N Engl J Med 1968;278:1355–1360.
Correspondence and requests for reprints should be addressed to Prof. David Lomas, Ph.D., F.R.C.P., Department of Medicine, University of Cambridge, Cambridge Institute for Medical Research, Wellcome Trust/MRC Building, Hills Road, Cambridge, CB2 0XY, UK. E-mail:

Related

No related items
American Journal of Respiratory and Critical Care Medicine
178
5

Click to see any corrections or updates and to confirm this is the authentic version of record