CCL5
Materials and Methods
Study subjects
Among 274 patients with COPD recruited for the Hokkaido COPD cohort study
[17], a total of 267 patients, whose genetic samples were available, were examined in the current study. Patients with COPD were recruited from an outpatient setting from
Hokkaido University hospital at the Sapporo region in Japan, and the other 9 hospitals surrounding the region as a part of Hokkaido COPD cohort study. Details of patient

recruitment and phenotyping in Hokkaido COPD cohort study have been reported previously [17]. Inclusion criteria for patients were: as defined by GOLD guidelines [ 15 ]; aged 40 or older; current smoker or ex-smoker with a smoking history of at least 10 pack-years. Patients were excluded from study enrolment if they had a primary diagnosis of asthma or other relevant lung diseases including lung cancer and bronchiectasis.
Study approval was obtained from governing ethics committees for each study center, and all subjects provided written informed consent. All participants underwent a structured interview and physical examination; age, sex, smoking habits, and body-mass index (BMI) were recorded.
Pulmonary function test
Spirometry (FVC, FEV
1
, and FEV1%predicted) was performed before and 30 minutes after a bronchodilator (salbutamol 400  g) was given. The diagnosis of COPD is confirmed by spirometry according to the GOLD guideline [15]. Bronchial reversibility was expressed as the percent change in FEV
1
after salbutamol administration ([post-FEV
1
- pre-FEV
1
]/pre-FEV
1
×100). The carbon monoxide diffusing capacity (DLco) test were performed, and DLco adjusted with levels of hemoglobin over alveolar ventilation (V
A
) was calculated.

Lung computed tomography scans
The following commercially available scanners were used in 9 affiliate hospitals:
Somatom plus Volume Zoom (Siemens, Berlin); Aquilion Multi TSX-101A/2A,
TSX-101A/4E, TSX-101A/6A, X Force TSX-011A/6A, X Vigor SS TSX-012A/4B
(Toshiba Medical Systems, Japan); MX-8000/ID16 (Philips, Netherlands). Chest HRCT scans were performed under the supine position, holding their breaths at full inspiration.
No patient received intravenous contrast medium. Other technical parameters were as follows; 1 mm collimation, 120-140 kV, 75-350 mA, 0.75-1 s for scanning time, and 1-2 mm thickness. HRCT images were selected at 3 levels, including the aortic arch, carina, and
1-2 cm above the highest hemi-diaphragm. Image interpretations were performed under
-600 to -900 Hounsfield units (HU) window levels and 800 to 1500 HU window widths based on the best condition for detecting emphysema at each hospital. Severity of emphysema was visually assessed by three independent pulmonologists, who were blinded to any clinical information regarding the patient, according to the modified Goddard scoring system [17, 18]. We analyzed 6 images in 3 slices in the lungs and an average score of all images was considered as a representative value of severity of emphysema in each person. Each image was classified as normal (score 0), up to 5 percent affected (score 0.5),

up to 25 percent affected (score1), up to 50 percent affected (score 2), up to 75 percent affected (score 3), more than 75 percent affected (score 4) and the average score of 6 images, giving a minimum score of 0 to maximum score of 4, was considered as a representative value of the severity of emphysema in the lungs. When the three independent pulmonologists split in their evaluation, we took only the score assessed by the majority.
To confirm the accuracy and the reliability of our visual assessment, we compared the severity of emphysema assessed visually with that assessed by computerized analyses
[17, 1E-6E]. All CT row data sets were reconstructed to isometric voxel data using both soft-tissue and bone algorithms. The length of the 1 voxel side was 0.625 mm.
Reconstructed data were transferred to the workstation (AZE Ltd, Tokyo, Japan), and then reconstructed into three-dimensional chest images. On this workstation, using original software with volume rendering technique, three dimensional lung objects for analyses were obtained at 3 steps as follows; First, only trachea, bronchus and entire lung were extracted by using opacities under -740 HU. Second, trachea and central bronchus until second order bronchus were extracted from the object after the first step by using opacities from -740 to
-975 HU. Third, only the entire lung object was obtained by subtraction of the second object from the first object. In these steps, the software automatically removed central

pulmonary arteries and veins until the second order branch, which had similar opacities of lung, using original algorithm recognizing morphology. The percent volume of low attenuation being defined as < -960 Hounsfield density units against total lung volume represents % lung attenuation volume (% LAV) [3E-6E]. We found a strong correlation between subjective visual score and %LAV, an objective quantification based on three dimensional CT (3D-CT) findings (n=137, r=0.835, p<0.0001) (Figure 3E).
In this study, we carefully withdrew any class of bronchodilators for 1-2 days prior to pulmonary function measurements including reversibility testing after inhaling a short-acting beta-agonist and lung CT scans. As these measurements were conducted on the same day, we took CT imaging only a couple of hours after pulmonary function measurements [17].
Allele-Specific PCR and Detection of Fluorescence-Labeled PCR Fragments
Genomic DNA is available for 267 patients, and three SNPs (-403G>A
[rs2107538], -28C>G [rs2280788], and +375T>C [rs2280789]) at the regulatory region were genotyped using an assay that combines kinetic (real-time quantitative) PCR with allele-specific amplification, as described previously [2]. The alleles -403G, –403A –28C,
-28G, +375T and +375C were identified by allele-specific PCR, in which primers were

designed (Primer Express  software, PE Applied Biosystems, Foster City, CA) to specifically amplify either the common allele or its alternative in separate PCR reactions.
Genotyping assays were performed by real-time quantitative PCR, and the PCR products were detected using the ABI 7700 Sequence Detection System with the dsDNA-specific fluorescent dye SYBR Green I (PE Applied Biosystems, Foster City, CA). The incorporation of SYBR Green I into a real-time PCR reaction allows discrimination between specific and non-specific products. We used the hot-start enzyme “AmpliTaq
Gold” DNA polymerase (included in SYBR Green I reagent kits [PE Applied Biosystems,
Foster City, CA]), which allows the highest performance available by minimizing non-specific product formation. The following primers were used: -403G forward primer,
5’-CAT GGA TGA GGG AAA GGA GG-3’; -403A forward primer, 5’-CAT GGA TGA
GGG AAA GGA GA-3’; -403 common reverse oligonucleotide primer, 5’-CAG TTA
GGA CAG GAT CAG AAG TCA CT-3’; -28C forward primer, 5’-CTT AGG GGA TGC
CCC TCA A-3’; -28G forward primer, 5’-CTT AGG GGA TGC CCC TGA A-3’; -28 common reverse oligonucleotide primer, 5’-CGA GGT CCA CGT GCT GTC TT-3’;
+375T forward primer, 5’-AGG CCT TGA GGG TGT AGA CCT AA-3’; +375C forward primer, 5’-GCC TTG AGG GTG TAG ACC TAG-3’; +375 common reverse oligonucleotide primer, 5’-CAT GGC AGG GAT CTC CTG AT-3’. The accuracy of

genotyping data obtained by allele-specific PCR was confirmed by DNA sequencing.
We failed to obtain genotypes of the -28C>G SNP for 4 patients with COPD, and failed to obtain genotypes of the -403 G>A SNP for 3 patients with COPD.
Statistical analysis
The linkage disequilibrium (LD) between 3 SNPs was analyzed, and all SNPs were tested for conformation with Hardy-Weinberg expectations in patients with COPD using
Haploview software version 3.2 [19]. Haploview uses expectation maximum (EM) algorithm to find maximum likelihood estimates of the four gamete frequencies, from which the D’ calculation derives.
We made comparisons of COPD-related phenotypes according to the genotypes of 3 CCL5 SNPs in patients with COPD; the chi-square test was used for discrete variables
(sex, smoking status [ex. or current], frequency of atopy), and one-way analysis of variance was used for continuous variables (age, BMI, pack-years of smoking, FEV
1
%predicted, bronchial reversibility, DLco/V
A
, and CT score). We examined the genetic impact of 3 regulatory SNPs on the CT score using a multivariate stepwise linear regression model. The model included sex, age, smoking status (current or ex), pack-years of smoking, BMI,
DLco/V
A
, FEV
1
(%predicted), levels of total serum IgE and peripheral blood eosinophil

counts. We specified the F-to-remove value as 3.99, and the F-to-entry value as 4.00 in the model. As total serum IgE levels, peripheral blood eosinophil counts and pack-years exhibited a skewed distribution with a long right-hand tail, these variables were log transformed to approximate a normal distribution. All clinical and genotype data were managed with the statistical package SYSTAT for Windows (Version 10.2 Systat Inc.). We also examined the genetic effect of the regulatory SNPs on CT score using only 180 patients whose bronchial reversibility was less than 15% (model 2), because airflow limitation tends to be fixed, by definition, in COPD rather than demonstrate significant reversibility and a possibility might remain that the presence of bronchodilator reversibility indicates the presence of coexisting asthma, although patients with physician-diagnosed asthma were carefully excluded from the study [17]. We also examined an association between the severity of emphysema as judged by a low attenuation volume (LAV) assessed by 3D-CT and the 3 SNPs (model 3; n = 105).
The association between common haplotypes with a frequency of >1% and CT score was tested using global and haplotype-specific statistics using the Haplo.Score program, which adjusts for covariates and calculates simulation p values for each haplotype
[20]. The Haplo.Score program was implemented in the haplo.stats software developed using the R language. Global haplotype p values and empirical p value for each haplotype

were derived from a minimum of 10 000 simulations.

References
1E.
Park KJ, Bergin CJ, Clausen JL. Quantitation of emphysema with three-dimensional CT densitometry: comparison with two-dimensional analysis, visual emphysema scores, and pulmonary function test results. Radiology 1999; 211:
541-547.
2E. Zaporozhan J, Ley S, Eberhardt R, et al. Paired inspiratory/expiratory volumetric thin-slice CT scan for emphysema analysis: comparison of different quantitative evaluations and pulmonary function test. Chest 2005; 128: 3212-3220.
3E. Madani A, Zanen J, de Maertelaer V, et al. Pulmonary emphysema: objective quantification at multi-detector row CT--comparison with macroscopic and microscopic morphometry. Radiology 2006; 238: 1036-1043.
4E. Nakano Y, Muro S, Sakai H, et al. Computed tomographic measurements of airway dimensions and emphysema in smokers. Correlation with lung function.
Am J Respir Crit Care Med 2000; 162(3 Pt 1): 1102-1108.
5E. Mishima M, Hirai T, Itoh H, et al. Complexity of terminal airspace geometry assessed by lung computed tomography in normal subjects and patients with chronic obstructive pulmonary disease. Proc Natl Acad Sci U S A 1999; 96(16):
8829-8834.

6E. Nakano Y, Sakai H, Muro S, et al. Comparison of low attenuation areas on computed tomographic scans between inner and outer segments of the lung in patients with chronic obstructive pulmonary disease: incidence and contribution to lung function. Thorax 1999; 54(5): 384-389.

Figure legends
Figure 1E
The severity of emphysema according to the -28C>G CCL5 promoter SNP in the 3 models
The severity of emphysema was assessed by visual scoring (A, B) and computerized analysis (C).
In all models, genetic effects of the -28C>G SNPs were co-dominant with heterozygotes showing intermediate levels of the severity of emphysema when compared with both the
CC and GG homozygote genotypes.
Figure 2E
Correlation between CT score and carbon monoxide diffusing capacity (DL/V
A
)
CT score and DL/V
A were significantly correlated in the population, as shown (Pearson correlation matrix=-0.573, p<0.0001); wide variations of CT scores were noted even in patients who had the same levels of DL/V
A
.

Figure 3E
Correlation between CT score and % lung attenuation volume (%LAV)
Visual assessment of emphysema was compared with computerized volume-based assessment in patients with COPD. The percent volume of low attenuation being defined as < -960 Hounsfield density units against total lung volume represents % LAV. We found a strong correlation between subjective visual score and %LAV, an objective quantification based on three dimensional CT (3D-CT) findings (n=137, r=0.835, p<0.0001)