Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Association of genetic polymorphisms with chronic obstructive pulmonary disease in the Chinese Han population: a case–control study

  • Yi Guo1,
  • Yi Gong2,
  • Chunming Pan3,
  • Yanrong Qian1,
  • Guochao Shi1,
  • Qijian Cheng1,
  • Qingyun Li1,
  • Lei Ren4,
  • Qiuling Weng4,
  • Yi Chen5,
  • Ting Cheng1,
  • Liang Fan1,
  • Zhihong Jiang1 and
  • Huanying Wan1Email author
BMC Medical Genomics20125:64

DOI: 10.1186/1755-8794-5-64

Received: 22 August 2012

Accepted: 13 December 2012

Published: 26 December 2012

Abstract

Background

Chronic obstructive pulmonary disease (COPD) is influenced by both environmental and genetic factors. Few gene studies of the Chinese population have focused on COPD. We investigated candidate genes associated with susceptibility to COPD in the Chinese Han population.

Methods

A total of 331 COPD patients and 213 control subjects were recruited for this study. Nighty-seven single-nucleotide polymorphisms (SNPs) of 46 genes were selected for genotyping. Genotypes were determined using multiplex polymerase chain reaction (PCR).

Results

Significant differences between patients and healthy controls were observed in the allele frequencies of seven SNPs: rs1205 C, rs2353397 C, rs20541 T, rs2070600 G, rs10947233 G, rs1800629 G, and rs2241712 A. After Bonferroni correction, rs2353397 C was most strongly associated with susceptibility to COPD. Haplotype analysis showed that the frequencies of the GC, GT haplotypes of rs2241718 (TGF-β1 gene), and rs6957 (CDC97 gene) were significantly higher in the control group than in the COPD case group (p=1.88×10-9); the frequencies of the TT haplotype of rs1205 and rs2808630 (CRP gene) were significantly higher in the control group (p=0.0377).

Conclusion

Our study suggests some genetic variants associated with the susceptibility of COPD in the Chinese Han population.

Keywords

COPD Single-nucleotide polymorphisms Genotype Allele frequencies

Background

Chronic obstructive pulmonary disease (COPD) is characterized by progressive airflow limitation driven by an abnormal inflammatory response of the airways to inhaled particles and fumes [1]. The disease is predicted to become the third most common cause of death and the fifth most common cause of disability in the world by 2020 [2]. This disease remains under-recognized and under-diagnosed; the pathogenesis needs to be investigated.

Cigarette smoking is one of the most important risk factors for COPD, but the severity of the disease varies considerably, irrespective of the number of pack-years of smoking. Furthermore, only a minority of smokers (20%) develop the disease clinically, suggesting that in addition to smoking, COPD is partially genetically determined [3, 4]. COPD may be caused by a combination of genes and environmental influences. Genes have been associated with COPD in a family-based study, and some previous studies have demonstrated familial aggregation of COPD. The heritability of COPD is estimated to be 40–77% [5]. Some other twin studies have also indicated a genetic contribution to clinically relevant parameters of pulmonary function, such as forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) [6, 7].

Many studies of candidate genes for COPD and pulmonary function have been conducted over the past few years. Above all, genome-wide association studies (GWASs) have identified some loci associated with susceptibility to COPD [812] but with varying degrees of reproducibility. Conflicting results among these studies may be attributable to ethnic differences and sample sizes. In the past, candidate gene studies have focused on a single gene or on a few genes in combination; these genes were identified based on prior knowledge or suspected mechanisms of disease pathogenesis. Nonetheless, elucidating the genetics of respiratory disorders is severely hampered by genetic heterogeneity, the low penetrance of individual disease alleles, and the potential for gene–gene and gene–environment interactions. To date, the only proven genetic risk factor for COPD is the severe deficiency of alpha-1-antitrypsin (AAT), which is associated with a predisposition to early onset panacinar (panlobular) emphysema [13].

Furthermore, few gene studies performed on the Chinese population have focused on COPD. However, in China, the disease is increasingly prevalent. A 2007 survey of 20,245 participants in seven regions of China reported the occurrence of COPD in adults aged ≥40 years to be 8.2% [14]. Therefore, more gene-association studies are needed to identify genetic polymorphisms associated with the development of COPD in the Chinese population.

The aim of our current case–control study was to locate genes related to susceptibility to COPD in the Chinese Han population. We aimed to identify loci associated with COPD among 97 single-nucleotide polymorphisms (SNPs) of 46 genes (Table 1).
Table 1

Gene location and alleles of 97 single-nucleotide polymorphisms (SNPs)

SNP_ID

Gene

Chrom-osome

Alleles

SNP_ID

Gene

Chrom-osome

Alleles

rs1800610 [1]

TNF-α

6

C/T

rs673400 [14]

SERPINA2

2

C/G

rs1799964 [1]

TNF-α

6

C/T

rs7583463 [15]

SERPINA2

2

A/C

rs361525 [2]

TNF-α

6

A/G

rs2736100 [8]

TERT

5

G/T

rs1800629 [3]

TNF-α

6

A/G

rs10069690 [8]

TERT

5

C/T

rs2808630 [4]

CRP

1

C/T

rs34829399 [8]

TERT

5

C/T

rs1205 [5]

CRP

1

C/T

rs4246742 [8]

TERT

5

A/T

rs1130864 [4]

CRP

1

C/T

rs2736118 [8]

TERT

5

A/G

rs1059823 [6]

SLC11A1

2

A/G

rs2736122 [8]

TERT

5

C/T

rs1130866 [7]

SFTPB

2

C/T

rs2853677 [8]

TERT

5

C/T

rs2353397 [8]

HHIP

4

C/T

rs2853676 [8]

TERT

5

A/G

rs13147758 [8]

HHIP

4

A/G

rs1881457 [16]

IL-13

5

A/C

rs2035901 [8]

HHIP

4

A/G

rs1295685 [16]

IL-13

5

C/T

rs6537302 [8]

HHIP

4

A/T

rs1800925 [16]

IL-13

5

C/T

rs1032295 [8]

HHIP

4

T/G

rs2066960 [16]

IL-13

5

A/C

rs12504628 [8]

HHIP

4

C/T

rs20541 [16]

IL-13

5

C/T

rs17019336 [8]

HHIP

4

A/T

rs16909898 [8]

PTCH1

9

A/G

rs3749893 [8]

TSPYL-4

6

A/G

rs10512249 [8]

PTCH1

9

C/T

rs4987835 [9]

Bcl-2

18

A/G

rs35621 [17]

ABCC1

16

C/T

rs2292566 [10]

EPHX1

1

A/G

rs2241718 [18]

TGF-β1

19

C/T

rs1051740 [11]

EPHX1

1

C/T

rs56155294 [18]

TGF-β1

19

C/T

rs868966 [11]

EPHX1

1

A/G

rs1800469 [18]

TGF-β1

19

C/T

rs25882 [12]

CSF2

5

C/T

rs2241712 [18]

TGF-β1

19

A/G

rs829259 [13]

PDE4D

5

A/T

rs2277027 [8]

ADAM19

5

A/C

rs6712954 [14]

SERPINA2

2

A/G

rs2280090 [19]

ADAM33

20

A/G

rs2280091 [19]

ADAM33

20

A/G

rs4073 [12]

IL-8

4

A/T

rs1435867 [8]

PID1

2

C/T

rs8192288 [30]

SOD3

4

G/T

rs10498230 [8]

PID1

2

C/T

rs2571445 [20]

TNS1

2

C/T

rs3995090 [20]

HTR4

5

A/C

rs1003349 [31]

MMP14

14

G/T

rs6889822 [8]

HTR4

5

A/G

rs737693 [32]

MMP12

11

A/T

rs1531697 [9]

Bcl-2

18

A/T

rs2276109 [32]

MMP12

11

A/G

rs1042713 [21]

ARDB2

5

A/G

rs1052443 [8]

NT5DC1

6

A/C

rs3024791 [22]

SFTPB

2

A/G

rs10947233 [8]

PPT2

6

G/T

rs511898 [23]

ADAM33

20

C/T

rs1051730 [33]

CHRNA3

15

C/T

rs2853209 [23]

ADAM33

20

A/T

rs11106030 [20]

DCN

12

A/C

rs6555465 [8]

ADCY2

5

A/G

rs584367 [34]

sPLA2s

1

C/T

rs10075508 [13]

PDE4D

5

C/T

rs9904270 [26]

CDC6

17

C/T

rs12899618 [20]

THSD4

15

A/G

rs2395730 [8]

DAAM2

6

A/C

rs3091244 [8]

SFXN1

5

A/C/T

rs3817928 [8]

GPR126

6

A/G

rs8004738 [24]

SERPINA1

14

A/G

rs11155242 [8]

GRP126

6

A/C

rs709932 [24]

SERPINA1

14

A/G

rs7776375 [8]

GPR126

6

A/G

rs4934 [25]

SERPINA3

14

A/G

rs6937121 [8]

GPR126

6

G/T

rs13706 [26]

CDC6

17

A/G

rs1042714 [35]

ARDB2

5

C/G

rs7217852 [26]

CDC6

17

A/G

rs1800796 [36]

IL-6

7

C/G

rs2077464 [26]

CDC6

17

A/G

rs2236307 [31]

MMP14

14

C/T

rs2070600 [20]

AGER

6

A/G

rs2236302 [31]

MMP14

14

C/G

rs6957 [27]

CDC97

19

A/G

rs2230054 [37]

IL-8RB

2

C/T

rs1042522 [28]

P53

17

C/G

rs1422795 [8]

ADAM19

5

A/G

rs1695 [29]

GSTP1

11

A/G

rs6830970 [8]

FAM13A

4

A/G

rs2869967 [8]

FAM13A

4

C/T

 

References listed in supplemental document.

Methods

Subjects

In total, 331 COPD patients were recruited: 256 from the Department of Respiratory Diseases of Shanghai Rui Jin Hospital, 60 from the Shanghai Jing-an Geriatric Hospital, and 15 from the Shanghai Gong Hui Hospital. COPD was diagnosed according to the criteria established by the NHLBI/WHO Global Initiative for COPD (GOLD) [15]. The diagnoses were based on certain patient parameters (e.g., age≥40 years and smoking history of ≥20 pack-years) and on the presence of relentless and progressive symptoms: cough, productive sputum, and breathlessness over many years; airflow limitation as indicated by FEV1/ FVC≤70%; FEV1 reversibility after the inhalation of salbutamol <12% of the pre-bronchodilator FEV1 (MS-Body Diffusion, Germany). Patients were excluded if they had a comorbid diagnosis such as asthma or lung cancer, or had radiographic abnormalities suggestive of other significant respiratory diseases and any hereditary diseases.

Control subjects (n = 213) were selected from a pool of healthy people who visited the general health checkup center of Shanghai Rui Jin Hospital during the same period. The enrollment criteria for the controls were as follows: age≥40 years, smoker, no known disease, no history of any disease. Lung function was measured at baseline following the American Thoracic Society/European Respiratory Society standard procedure to confirm no evidence of airflow obstruction. All of the COPD patients and control subjects were ethnic Han Chinese. The study protocol was approved by the medical ethics committee of Shanghai Rui Jin Hospital, Shanghai Jiaotong University School of Medicine, and all participants gave written informed consent.

DNA extraction and genotyping

We chose 97 candidate SNPs identified in previously published GWASs and by searching the dbSNP database of NCBI (references in Additional file 1: Table S1). Their minor allele frequencies (MAFs) were >0.05 in the Han Chinese population we studied.

A 4-ml peripheral blood sample was obtained from each participant for DNA analysis. Plasma was separated by centrifuge and stored at −80°C until further use. We extracted genomic DNA using a QuickGene DNA whole blood kit, (Life Sciences, FUJIFILM, Japan). Any sample with DNA concentration <10 ng/ul was excluded, and another sample was acquired.

For genotyping, we first performed multiplex PCR, a variant of PCR that enables simultaneous amplification of many targets of interest in one reaction by using more than one pair of primers [16]. Mass-ARRAY™ Assay Design 2.0 software was used to design multiplex primers for each SNP: 1st PCR primer, 2nd PCR primer, and UEP primer. The primers of 97 SNPs are shown in Additional file 1: Table S1. Genotyping was achieved using the Mass-Array™ Technology platform of Sequenom, Inc. (San Diego, CA, USA). For quality control, two independent readers interpreted the results, and a random selection of 10% of all samples was retested. No discrepancies were discovered in the replicate tests. All genotyping analyses were blinded with respect to the case/control status, and all samples were analyzed in the same lab and under the same conditions. The results were 100% concordant. Several SNP samples were finally excluded because ≥10% of the genotyping data were missing.

Data analysis

Data analyses were performed using the Statistical Package for the Social Science 20.0 (SPSS, Inc., Chicago, IL, USA). Continuous variables (age, smoking history, and pulmonary function) were calculated as means (± standard deviation). The two-sided Student’s t-test was used to determine significant differences in clinical data between the COPD cases and the control subjects. The significance level for t tests of clinical information was 0.05. The χ2 test and unconditional logistic method were applied to compare genotype and allele frequencies between the two groups, logistic analysis was adjusted for age, gender and smoking. Frequencies were compared, respectively, using a p cutoff of 0.05 (like previous studies) and the Bonferroni correction method for multiple testing. The relative risk associated was estimated as an odds ratio (OR) with a 95% confidence interval (95% CI). Each of the SNPs in the control group was analyzed for Hardy-Weinberg equilibrium (HWE) using chi-square test and exact test, SNPs were excluded from the analysis if they were out of HWE (p≤0.05). Haplotype frequencies and linkage disequilibrium (LD) analyses were evaluated using PHASE and Haploview software.

Results

Study population characteristics

The study population characteristics are described in Table 2. They did not significantly differ in sex, age, or smoking history. FEV1 predictive (FEV1%) and FEV1/FVC of the case group were significantly decreased compared with the control group (p<0.05).
Table 2

Demographics of COPD patients and control subjects

 

COPD

Controls

P value

Number

331

213

 

Age

61±10

58±12

 

Male(%)

298(90%)

209(98%)

 

Female(%)

33(10%)

4(2%)

 

Pack-years(±SD)

41±34

38±17

 

FEV1/FVC

54±13.8*

85±7.6*

p<0.05

FEV1/predicted(%)

49±18.1#

88±17.0#

p<0.05

Data were presented as the means ± SD. FEV1, forced expiratory volume in 1 sec; FVC, forced vital capacity; *p<0.05 significant difference vs control.

#p<0.05 significant difference vs control.

Association analysis of each genotype

Eight SNPs (rs361525, rs1042713, rs34829399, rs2853677, rs2571445, rs8192288, rs2066960, and rs2230054) that deviated from HWE in the controls were removed from the association analysis. Thirteen SNPs (rs1130866, rs56155294, rs10498230, rs2035901, rs3091244, rs511898, rs2869967, rs7583463, rs2276109, rs737693, rs9904270, rs4934, and rs6830970) were also eliminated from the analysis due to lack of genotyping data in ≥10% of the sample. Finally, 76 of the 97 SNPs were included in the association analysis. The allele frequencies (Table 3) and the genotype distributions for these SNPs were analyzed in samples from 331 COPD patients and 213 control subjects. Seven SNPs tended to be associated with COPD: rs2353397, rs1800629, rs2241712, rs1205, rs20541, rs2070600, and rs10947233. Among these seven SNPs, after Bonferroni correction, rs2353397 was most strongly associated with susceptibility to COPD. The C allele (rs2353397) of the human hedgehog interacting protein (HHIP) gene occurred more frequently in COPD patients (58%) than in the control subjects (29%) (OR = 2.16, 95% CI 1.66–2.81, p<0.0001, p(Bonferroni) <0.0001). The G allele (rs1800629) of the TNF-α gene was more frequently detected in COPD patients (95%) versus control subjects (90%) (OR=1.97, 95% CI 1.21–3.21, p=0.0060, p(Bonferroni)=0.4560). The frequency of the A allele (rs2241712) of the TGF-β1 gene was significantly higher in COPD patients (52%) than in healthy controls (45%) (OR=1.24, 95% CI 0.96–1.59, p=0.0460, p(Bonferroni)=3.7848). The C allele (rs1205) of the CRP gene occurred more frequently in COPD patients (47%) compared with control subjects (40%) (OR=1.48, 95% CI 1.14–1.91, p=0.0030, p(Bonferroni)=0.2280). More COPD patients (35%) carried the T allele (rs20541) of the IL-13 gene than control subjects (28%) (OR=1.36, 95% CI 1.04–1.80, p=0.0280, p(Bonferroni)=2.1280). The G allele (rs2070600) of the AGER gene was found more frequently in COPD patients (81%) than in healthy controls (73%) (OR=1.47, 95% CI 1.08–1.98, p=0.0130, p(Bonferroni)=0.9880). The G allele (rs10947233) of the PPT2 gene occurred more frequently in COPD patients (79%) than in control subjects (72%) (OR=1.51, 95% CI 1.12–2.03, p=0.0060, p(Bonferroni)=0.4560).
Table 3

Allele frequencies in COPD and control subjects for SNPs

SNP

Allele

Control (n,%)

Case (n,%)

χ 2

P value

OR

OR(95%CI)

P (Bonferroni)

Adjusted P value

Adjusted OR

Adjusted OR(95%CI)

Adjusted P (Bonferroni)

rs1059823

G

139(33)

222(34)

0.0181

0.8929

1.01

0.79-1.32

67.8604

0.8290

0.97

0.74-1.27

63.0040

 

A

283(67)

440(66)

         

rs1205

C

168(40)

308(47)

5.2168

0.0223

1.34

1.04-1.71

1.6948

0.0030

1.48

1.14-1.91

0.2280

 

T

252(60)

346(53)

         

rs17019336

A

136(32)

242(37)

2.1770

0.1401

1.21

0.94-1.57

10.6476

0.0670

1.28

0.98-1.68

5.0920

 

T

284(68)

416(63)

         

rs1799964

T

333(79)

519(79)

0.0008

0.9772

1.00

0.74-1.36

74.2672

0.8140

0.96

0.71-1.31

61.8640

 

C

87(21)

135(21)

         

rs1800610

T

71(17)

112(17)

0.0117

0.9137

1.02

0.74-1.41

69.4412

0.9007

0.98

0.70-1.38

68.4532

 

C

355(83)

550(83)

         

rs2077464

T

271(65)

420(66)

0.1909

0.6621

1.06

0.82-1.37

50.3196

0.8230

1.03

0.79-1.35

62.5480

 

C

149(35)

218(34)

         

rs2236302

C

369(88)

584(89)

0.2011

0.6539

1.09

0.75-1.59

49.6964

0.4140

1.18

0.80-1.75

31.4640

 

G

51(12)

74(11)

         

rs2292566

A

125(30)

209(32)

0.4800

0.4884

1.10

0.84-1.43

37.1184

0.7630

1.04

0.79-1.38

57.9880

 

G

295(70)

449(68)

         

rs2353397

C

123(29)

382(58)

83.3798

6.8×10 -20

3.29

2.54-4.28

5.2×10 -18

<0.0001

2.16

1.66-2.81

<0.0001

 

T

297(71)

280(42)

         

rs25882

T

147(35)

240(36)

0.2421

0.6227

1.07

0.83-1.38

47.3252

0.4650

1.10

0.85-1.44

35.3400

 

C

273(65)

418(64)

         

rs2808630

C

66(16)

119(18)

1.0136

0.3140

1.18

0.85-1.65

23.8640

0.2120

0.86

0.69-1.09

16.1120

 

T

354(84)

539(82)

         

rs3749893

A

286(67)

454(69)

0.6232

0.4299

1.11

0.86-1.44

32.6724

0.4510

1.11

0.84-1.46

34.2760

 

G

140(33)

200(31)

         

rs4987835

A

236(56)

382(60)

1.7185

0.1899

1.19

0.92-1.51

14.4324

0.2950

1.15

0.88-1.49

22.4200

 

G

184(44)

252(40)

         

rs709932

A

73(17)

131(20)

1.2714

0.2595

1.20

0.87-1.65

19.7220

0.2860

1.19

0.86-1.65

21.7360

 

G

347(83)

519(80)

         

rs7217852

A

273(65)

434(66)

0.0652

0.7985

1.03

0.80-1.34

60.6860

0.8460

1.03

0.79-1.34

64.2960

 

G

147(35)

226(34)

         

rs7776375

A

270(63)

438(66)

0.8832

0.3473

1.13

0.88-1.46

26.3948

0.2570

1.17

0.89-1.52

19.5320

 

G

156(37)

224(34)

         

rs10069690

C

331(80)

520(81)

0.0264

0.8709

1.03

0.75-1.40

66.1884

0.6480

1.08

0.78-1.48

49.2480

 

T

81(20)

124(19)

         

rs1051740

T

247(60)

403(61)

0.0424

0.8369

1.03

0.79-1.32

63.6044

0.8910

1.02

0.79-1.32

67.7160

 

C

163(40)

259(39)

         

rs11155242

A

372(90)

604(91)

0.5784

0.4469

1.18

0.77-1.79

33.9644

0.2560

1.28

0.83-1.94

19.4560

 

C

42(10)

58(9)

         

rs1295685

T

118(29)

221(33)

2.8124

0.0935

1.26

0.96-1.64

7.1060

0.1730

1.21

0.92-1.60

13.1480

 

C

296(71)

441(67)

         

rs1435867

C

55(13)

90(14)

0.0200

0.8877

1.03

0.72-1.47

67.4652

0.5300

0.89

0.62-1.29

40.5080

 

T

355(87)

566(86)

         

rs16909898

G

33(8)

54(8)

0.0101

0.9200

1.02

0.65-1.61

69.9200

0.3140

0.79

0.50-1.25

23.8640

 

A

379(92)

606(92)

         

rs1881457

A

308(74)

495(75)

0.0726

0.7876

1.04

0.78-1.38

59.8576

0.9120

1.02

0.76-1.36

69.3120

 

C

108(26)

167(25)

         

rs2241718

T

114(28)

206(31)

1.4433

0.2296

1.18

0.90-1.55

17.4496

0.2930

1.16

0.88-1.53

22.2680

 

C

298(72)

456(69)

         

rs2277027

C

64(15)

106(16)

0.0586

0.8088

1.04

0.74-1.46

61.4688

0.8350

0.96

0.68-1.36

63.4600

 

A

350(85)

556(84)

         

rs2736100

T

231(57)

368(58)

0.1539

0.6948

1.05

0.82-1.35

52.8048

0.6340

1.06

0.82-1.38

48.1840

 

G

173(43)

262(42)

         

rs35621

C

305(74)

499(75)

0.1317

0.7167

1.05

0.79-1.40

54.4692

0.3480

1.15

0.86-1.54

26.4480

 

T

105(26)

163(25)

         

rs3995090

C

288(70)

461(71)

0.1521

0.6965

1.06

0.80-1.39

52.9340

0.4200

1.12

0.84-1.48

31.9200

 

A

122(30)

185(29)

         

rs4246742

A

244(60)

429(65)

3.0339

0.0815

1.25

0.97-1.61

6.1940

0.0510

1.32

1.01-1.71

3.8760

 

T

166(40)

233(35)

         

rs6712954

G

321(78)

545(82)

3.1679

0.0751

1.32

0.97-1.79

5.7076

0.0560

1.38

1.01-1.89

4.2560

 

A

91(22)

117(18)

         

rs829259

A

137(33)

233(35)

0.4250

0.5145

1.09

0.84-1.41

39.1020

0.9300

1.01

0.77-1.32

70.6800

 

T

275(67)

429(65)

         

rs10075508

T

69(16)

108(17)

0.0253

0.8736

1.03

0.74-1.43

66.3936

0.9070

1.02

0.72-1.44

68.9320

 

C

357(84)

544(83)

         

rs10512249

T

33(8)

52(8)

0.0606

0.8056

1.06

0.67-1.67

61.2256

0.4950

1.16

0.75-1.80

37.6200

 

C

383(92)

570(92)

         

rs12899618

G

370(89)

579(89)

0.0806

0.7765

1.06

0.72-1.56

59.0140

0.6010

1.11

0.75-1.65

45.6760

 

A

48(11)

71(11)

         

rs13706

G

272(65)

427(65)

0.0598

0.8068

1.03

0.80-1.34

61.3168

0.8300

0.97

0.75-1.27

63.0800

 

A

148(35)

225(35)

         

rs1531697

A

255(61)

411(63)

0.5370

0.4637

1.10

0.85-1.41

35.2412

0.4750

1.10

0.85-1.43

36.1000

 

T

163(39)

239(37)

         

rs1800925

T

62(15)

105(17)

0.8620

0.3531

1.18

0.84-1.66

26.8356

0.1000

1.32

0.94-1.85

7.6000

 

C

352(85)

507(83)

         

rs3024791

G

388(93)

616(95)

1.5299

0.2161

1.39

0.82-2.34

16.4236

0.3820

1.25

0.76-2.06

29.0320

 

A

28(7)

32(5)

         

rs6537302

A

310(75)

480(77)

0.7206

0.3959

1.13

0.85-1.51

30.0884

0.9110

1.10

0.76-1.36

69.2360

 

T

104(25)

142(23)

         

rs6555465

G

195(46)

310(48)

0.4399

0.5072

1.09

0.85-1.39

38.5472

0.5010

1.09

0.85-1.41

38.0760

 

A

231(54)

338(52)

         

rs673400

C

178(43)

278(43)

0.0062

0.9371

1.01

0.79-1.30

71.2196

0.9280

0.99

0.76-1.28

70.5280

 

G

238(57)

368(57)

         

rs6889822

G

268(64)

417(65)

0.0594

0.8073

1.03

0.80-1.34

61.3548

0.5000

1.10

0.84-1.43

38.0000

 

A

148(36)

223(35)

         

rs8004738

G

184(44)

275(44)

0.0092

0.9236

1.01

0.79-1.30

70.1936

0.6650

1.01

0.82-1.37

50.5400

 

A

232(56)

351(56)

         

rs1003349

G

238(57)

392(60)

0.8897

0.3456

1.13

0.88-1.45

26.2656

0.2340

1.17

0.90-1.51

17.7840

 

T

178(43)

260(40)

         

rs1032295

T

320(75)

523(80)

3.1870

0.0742

1.30

0.97-1.74

5.6392

0.1130

1.28

0.94-1.73

8.5880

 

G

106(25)

133(20)

         

rs1042522

C

184(44)

304(47)

0.8170

0.3660

1.12

0.88-1.43

27.8160

0.4090

1.11

0.86-1.44

31.0840

 

G

236(56)

348(53)

         

rs1052443

C

281(67)

457(71)

1.7602

0.1846

1.20

0.92-1.56

14.0296

0.1610

1.22

0.93-1.60

12.2360

 

A

139(33)

189(29)

         

rs12504628

T

305(72)

475(72)

0.0847

0.7710

1.04

0.79-1.37

58.5960

0.9810

1.04

0.76-1.33

74.5560

 

C

121(28)

181(28)

         

rs1695

G

72(17)

126(19)

0.6673

0.4140

1.14

0.83-1.57

31.4640

0.4650

1.13

0.82-1.57

35.3400

 

A

346(83)

530(81)

         

rs1800469

C

182(44)

315(48)

2.1252

0.1449

1.20

0.94-1.54

11.0124

0.2010

1.74

1.35-2.27

15.2760

 

T

234(56)

337(52)

         

rs20541

T

118(28)

228(35)

5.3633

0.0206

1.37

1.05-1.79

1.5656

0.0280

1.36

1.04-1.80

2.1280

 

C

302(72)

426(65)

         

rs2070600

G

312(73)

529(81)

8.1712

0.0043

1.52

1.14-2.03

0.3268

0.0130

1.47

1.08-1.98

0.9880

 

A

114(27)

127(19)

         

rs2853209

A

191(45)

305(47)

0.1953

0.6586

1.06

0.83-1.35

50.0536

0.9890

0.10

0.77-1.29

75.1640

 

T

231(55)

349(53)

         

rs4073

A

185(44)

300(46)

0.5198

0.4709

1.10

0.86-1.40

35.7884

0.2530

1.16

0.90-1.50

19.2280

 

T

235(56)

348(54)

         

rs6937121

T

254(60)

423(65)

2.1263

0.1448

1.21

0.94-1.56

11.0048

0.1720

1.20

0.92-1.56

13.0720

 

G

166(40)

229(35)

         

rs6957

G

150(36)

241(37)

0.0802

0.7771

1.04

0.80-1.34

59.0596

0.6830

1.06

0.81-1.38

51.9080

 

A

268(64)

415(63)

         

rs1051730

C

403(97)

641(97)

0.2343

0.6284

1.20

0.57-2.52

47.3252

0.6480

1.17

0.60-2.29

49.2480

 

T

11(3)

21(3)

         

rs10947233

G

299(72)

526(79)

7.4524

0.0063

1.49

1.12-1.98

0.4788

0.0060

1.51

1.12-2.03

0.4560

 

T

115(28)

136(21)

         

rs11106030

C

355(85)

560(85)

0.0013

0.9716

1.01

0.71-1.42

73.8416

0.7030

1.07

0.75-1.52

53.4280

 

A

63(15)

100(15)

         

rs1130864

T

23(6)

43(7)

0.6081

0.4355

1.23

0.73-2.07

33.0980

0.3890

1.24

0.77-2.00

29.5640

 

C

389(94)

591(93)

         

rs1800629

G

379(90)

627(95)

7.8793

0.0050

1.94

1.21-3.10

0.3800

0.0060

1.97

1.21-3.21

0.4560

 

A

41(10)

35(5)

         

rs2241712

A

188(45)

342(52)

3.9820

0.0460

1.28

1.00-1.64

3.4960

0.0498

1.24

0.96-1.59

3.7848

 

G

226(55)

320(48)

         

rs2280090

G

395(94)

629(95)

0.9844

0.3211

1.30

0.77-2.20

24.4036

0.4640

1.22

0.72-2.06

35.2640

 

A

27(6)

33(5)

         

rs2395730

A

119(28)

209(32)

1.3886

0.2386

1.17

0.90-1.54

18.1336

0.0850

1.28

0.97-1.69

6.4600

 

C

303(72)

453(68)

         

rs2736118

A

397(94)

630(95)

0.6150

0.4329

1.24

0.72-2.12

32.9004

0.2850

1.36

0.78-2.37

21.6600

 

G

25(6)

32(5)

         

rs2736122

C

388(94)

632(95)

1.5783

0.2090

1.41

0.82-2.42

15.884

0.0510

1.77

1.02-3.07

3.8760

 

T

26(6)

30(5)

         

rs3817928

A

370(89)

596(90)

0.1202

0.7288

1.07

0.72-1.61

55.3888

0.4410

1.17

0.78-1.76

33.5160

 

G

44(11)

66(10)

         

rs584367

T

91(22)

152(23)

0.1399

0.7083

1.06

0.79-1.42

53.8308

0.8590

1.03

0.76-1.39

65.2840

 

C

323(78)

510(77)

         

rs1042714

C

374(90)

607(92)

1.1947

0.2744

1.27

0.83-1.96

20.8544

0.1440

1.39

0.90-2.14

10.9440

 

G

40(10)

374(90)

         

rs13147758

A

283(69)

464(71)

0.8780

0.3487

1.14

0.87-1.49

26.5012

0.3840

1.13

0.86-1.49

29.1840

 

G

129(31)

186(29)

         

rs1422795

G

61(15)

108(16)

0.5395

0.4626

1.14

0.81-1.60

35.1576

0.8690

1.03

0.73-1.46

66.0440

 

A

353(85)

550(84)

         

rs1800796

C

293(71)

473(72)

0.1539

0.6948

1.06

0.80-1.39

52.8048

0.8250

1.03

0.78-1.36

62.7000

 

G

121(29)

185(28)

         

rs2236307

C

169(41)

286(43)

0.7270

0.3938

1.11

0.87-1.43

29.9288

0.4150

1.11

0.86-1.44

31.5400

 

T

245(59)

372(57)

         

rs2280091

A

383(93)

611(93)

0.1518

0.6968

1.10

0.68-1.77

52.9568

0.5020

1.17

0.74-1.87

38.1520

 

G

31(7)

45(7)

         

rs2853676

G

335(81)

544(83)

0.4538

0.5005

1.12

0.81-1.54

38.0380

0.2770

1.20

0.86-1.67

21.0520

 

A

77(19)

112(17)

         

rs868966

A

205(50)

337(51)

0.2934

0.5880

1.07

0.84-1.37

44.6880

0.7890

1.04

0.80-1.34

59.9640

 

G

209(50)

321(49)

         

Chi-square test and logistic analysis were used.

Logistic analysis was adjusted by potential confounders including age, gender, smoking history.

The p value with bold letters indicate those allele frequencies with significant differences between COPD and controls.

For analysis of genotypic association of these seven SNPs under certain genotype models (Table 4), rs2353397 TT protected subjects from the disease; CC, CT carriers were more susceptible to COPD (OR=1.01, 95% CI 0.79–1.32, p<0.0001). The rs1800629 GG homozygous carriers exhibited an increased susceptibility to the disease compared with AA, GA carriers (OR=1.90, 95% CI 1.12–3.21, p=0.0170). The rs1205 CC, CT genotype increased risk for COPD compared with the TT homozygous genotype (OR=1.82, 95% CI 1.21–2.73, p=0.0040). Individuals carrying the rs20541 TT, CT genotype were at a significantly higher risk for COPD than were healthy subjects carrying the CC genotype (OR=1.47, 95% CI 1.01–2.13, p=0.0450). The rs2070600 GG homozygous carriers tended to develop COPD more frequently that AA, GA carriers (OR=1.55, 95% CI 1.06–2.26, p=0.0240). rs10947233 GG, GT carriers were associated with susceptibility to COPD compared with TT carriers (OR=3.30, 95% CI 1.47–7.44, p=0.0040).GG carriers versus GT, TT carriers (OR=1.56, 95% CI 1.07–2.27, p=0.0200).
Table 4

Analysis of Genotypic Association of SNPs identified under Genetic Models

SNP

Genotype model

Control (n,%)

Case (n,%)

P value*

OR*

OR(95%CI) *

rs2353397

CC+CT

104(50)

261(79)

<0.0001

1.01

0.79-1.32

 

TT

106(50)

70(21)

   

rs2070600

GG

100(47)

213(65)

0.0240

1.55

1.06-2.26

 

GA+AA

113(53)

115(35)

   

rs10947233

GG+GT

191(92)

319(96)

0.0040

3.30

1.47-7.44

 

TT

16(8)

12(4)

   

rs10947233

GG

108(52)

207(63)

0.0200

1.56

1.07-2.27

 

GT+TT

99(48)

124(37)

   

rs1800629

GG

171(81)

296(89)

0.0170

1.90

1.12-3.21

 

GA+AA

39(19)

35(11)

   

rs1205

CC+CT

134(64)

238(73)

0.0040

1.82

1.21-2.73

 

TT

76(36)

89(27)

   

rs20541

TT+CT

99(47)

189(58)

0.0450

1.47

1.01-2.13

 

CC

111(53)

138(42)

   

* Logistic regression analysis was adjusted by potential confounders including age, gender, smoking history.

The complete genotype distributions of the other SNPs are listed in Table 5. Frequencies under different genotypic models of each SNP were compared between the COPD group and the control group.
Table 5

Genotype frequencies of each SNP in COPD and control subjects for SNPs

SNP

Allele

Control (n,%)

Case (n,%)

Adjusted P value

Adjusted OR

Adjusted OR(95%CI)

Adjusted P (Bonferroni)

rs1059823

GG

24(11)

39(11)

0.8120

0.93

0.52-1.67

61.7120

 

GA+AA

187(89)

292(89)

    
 

GG+GA

115(55)

183(55)

0.8760

0.97

0.68-1.39

66.5760

 

AA

96(45)

148(45)

    

rs17019336

AA

26(12)

35(11)

0.0100

0.14

0.09-0.22

0.7600

 

TA+TT

184(88)

294(89)

    
 

AA+AT

110(52)

207(63)

0.0210

1.54

1.07-2.21

1.5960

 

TT

100(48)

122(37)

    

rs1799964

TT

130(62)

206(63)

0.8010

0.95

0.66-1.38

60.8760

 

TC+CC

80(38)

121(37)

    
 

TT+TC

203(97)

313(96)

0.9180

0.96

0.41-2.23

69.7680

 

CC

7(3)

14(4)

    

rs1800610

TT

9(4)

13(4)

0.9940

1.00

0.41-2.44

75.5440

 

TC+CC

204(96)

318(96)

    
 

TT+TC

62(29)

99(30)

0.7350

1.07

0.72-1.59

55.8600

 

CC

151(71)

232(70)

    

rs2077464

TT

85(40)

138(43)

0.6620

1.09

0.75-1.57

50.3120

 

TC+CC

125(60)

181(57)

    
 

TT+TC

186(89)

282(88)

0.8190

0.94

0.53-1.64

62.2440

 

CC

24(11)

37(12)

    

rs2236302

CC+GC

208(99)

327(99)

0.8210

1.26

0.18-8.99

62.3960

 

GG

2(1)

2(1)

    
 

CC

161(77)

257(78)

0.4060

1.20

0.78-1.84

30.8560

 

GG+GC

49(23)

72(22)

    

rs2292566

AA

21(10)

36(11)

0.7410

1.11

0.61-2.0

56.3160

 

GG+AG

189(90)

293(89)

    
 

AA+AG

106(50)

156(47)

0.8610

1.03

0.72-1.48

65.4360

 

GG

      

rs2353397

CC

19(9)

121(37)

0.4850

1.24

0.68-2.28

36.8600

 

CT+TT

191(91)

210(63)

    
 

CC+CT

104(50)

261(79)

0.3740

1.18

0.82-1.69

28.4240

 

TT

106(50)

70(21)

    

rs25882

TT

30(14)

46(14)

0.9400

1.02

0.61-1.71

71.4400

 

CT+CC

180(86)

283(86)

    
 

TT+CT

117(56)

194(59)

0.3490

1.19

0.83-1.72

26.5240

 

CC

93(44)

135(41)

    

rs2808630

CC

4(2)

10(3)

0.4820

0.90

0.66-1.22

36.6320

 

CT+TT

206(98)

319(97)

    
 

CC+CT

62(30)

109(33)

0.2200

0.80

0.55-1.15

16.7200

 

TT

148(70)

220(67)

    

rs3749893

AA

100(47)

161(50)

0.4510

1.11

0.85-1.46

34.2760

 

AG+GG

113(53)

166(50)

    
 

AA+AG

186(87)

293(90)

0.6830

1.08

0.75-1.55

51.9080

 

GG

27(13)

34(10)

    

rs4987835

AA

65(31)

121(38)

0.2280

1.27

0.86-1.86

17.3280

 

AG+GG

145(69)

196(62)

    
 

AA+AG

171(81)

261(80)

0.6900

1.10

0.69-1.76

52.4400

 

GG

39(19)

56(20)

    

rs709932

AA

8(4)

16(5)

0.7950

1.13

0.45-2.84

60.4200

 

AG+GG

202(96)

309(95)

    
 

AG+AA

65(31)

115(35)

0.2570

1.25

0.85-1.82

19.5320

 

GG

145(69)

210(65)

    

rs7217852

AA

86(41)

141(43)

0.6180

1.01

0.76-1.58

46.9680

 

AG+GG

124(59)

189(57)

    
 

AA+AG

187(89)

293(89)

0.7000

0.89

0.51-1.57

53.2000

 

GG

23(11)

37(11)

    

rs7776375

AA

83(39)

148(45)

0.0900

1.37

0.95-1.98

6.8400

 

AG+GG

130(61)

183(55)

    
 

AA+AG

187(39)

290(45)

0.7940

0.93

0.54-1.6

60.3440

 

GG

26(12)

41(12)

    

rs10069690

TT

12(6)

7(2)

0.7100

0.93

0.64-1.35

53.9600

 

CT+CC

194(94)

315(98)

    
 

TT+CT

69(33)

117(36)

0.0240

3.14

1.17-9.92

1.8240

 

CC

137(67)

205(64)

    

rs1051740

TT

72(35)

123(37)

0.5730

1.12

0.76-1.63

43.5480

 

TC+CC

133(65)

208(63)

    
 

TT+TC

175(85)

280(85)

0.6070

0.88

0.53-1.45

46.1320

 

CC

30(15)

51(15)

    

rs11155242

AA

169(82)

276(83)

0.3060

1.27

0.80-2.01

23.2560

 

AC+CC

38(18)

55(17)

    
 

AA+AC

203(98)

328(99)

0.5030

1.68

0.37-7.56

38.2280

 

CC

4(2)

3(1)

    

rs1295685

TT

19(9)

37(12)

0.4470

1.27

0.69-2.32

33.9720

 

TC+CC

188(91)

294(88)

    
 

TT+CT

99(48)

184(56)

0.1880

1.27

0.89-1.83

14.2880

 

CC

108(52)

147(44)

    

rs1435867

CC

5(2)

7(2)

0.7660

0.83

0.24-2.85

58.2160

 

CT+TT

200(98)

321(98)

    
 

CC+CT

50(24)

83(25)

0.5380

0.88

0.58-1.33

40.8880

 

TT

155(76)

245(75)

    

rs16909898

GG

2(1)

1(0.3)

0.4560

0.40

0.03-4.45

34.6560

 

GA+AA

204(99)

329(99.7)

    
 

GG+GA

31(15)

53(16)

0.3580

0.80

0.49-1.30

27.2080

 

AA

175(85)

277(84)

    

rs1881457

AA

117(56)

187(56)

0.9540

0.99

0.69-1.42

72.5040

 

AC+CC

91(44)

144(44)

    
 

AA+AC

191(92)

308(93)

0.7340

1.13

0.57-2.22

55.7840

 

CC

17(8)

23(7)

    

rs2241718

TT

10(5)

26(8)

0.1380

1.80

0.83-3.88

10.4880

 

TC+CC

196(95)

305(92)

    
 

TT+TC

104(50)

180(54)

0.5480

1.12

0.78-1.60

41.6480

 

CC

102(50)

151(46)

    

rs2277027

CC

5(2)

10(3)

0.4990

1.47

0.49-4.44

37.9240

 

CA+AA

202(98)

321(97)

    
 

CC+CA

59(29)

96(29)

0.6170

0.90

0.61-1.34

46.8920

 

AA

148(71)

235(71)

    

rs2736100

TT

72(36)

108(34)

0.7840

0.95

0.65-1.39

59.5840

 

TG+GG

130(64)

207(66)

    
 

TT+TG

159(79)

260(83)

0.2490

1.32

0.83-2.10

18.9240

 

GG

43(21)

55(17)

    

rs35621

CC

114(56)

185(56)

0.3820

1.18

0.82-1.69

29.0320

 

CT+TT

91(44)

146(44)

    
 

CC+CT

191(93)

314(95)

0.5710

1.25

0.58-2.67

43.3960

 

TT

14(7)

17(5)

    

rs3995090

CC

98(48)

163(50)

0.2110

1.26

0.88-1.80

16.0360

 

CA+AA

107(52)

160(50)

    
 

CC+CA

190(93)

298(92)

0.6630

0.86

0.43-1.70

50.3880

 

AA

15(7)

25(8)

    

rs4246742

AA

71(35)

136(41)

0.0550

1.44

0.99-2.10

4.1800

 

AT+TT

134(65)

195(59)

    
 

AA+AT

173(84)

293(89)

0.1700

1.44

0.86-2.42

12.9200

 

TT

32(16)

38(11)

    

rs6712954

GG

128(62)

218(66)

0.1940

1.28

0.88-1.86

14.7440

 

GA+AA

78(38)

113(34)

    
 

GG+GA

193(94)

327(99)

0.0130

4.25

1.37-13.24

0.9880

 

AA

13(6)

4(1)

    

rs829259

AA

24(12)

35(11)

0.4770

0.81

0.45-1.46

36.2520

 

AT+TT

182(88)

296(89)

    
 

AA+AT

113(55)

198(60)

0.5920

1.11

0.77-1.59

44.9920

 

TT

93(45)

133(40)

    

rs10075508

TT

4(2)

6(2)

0.3660

0.49

0.10-2.30

27.8160

 

TC+CC

209(98)

320(98)

    
 

TT+TC

65(31)

102(31)

0.7280

1.07

0.73-1.58

55.3280

 

CC

148(69)

224(69)

    

rs10512249

TT

2(1)

1(0.3)

0.4560

0.40

0.04-4.45

34.6560

 

TC+CC

206(99)

310(99.7)

    
 

TT+TC

31(15)

51(16)

0.4150

1.27

0.71-2.27

31.5400

 

CC

177(85)

260(84)

    

rs12899618

GG

162(78)

259(79)

0.3010

1.26

0.82-1.94

22.8760

 

GA+AA

47(32)

66(21)

    
 

GG+GA

208(99)

320(98)

0.1430

0.20

0.02-1.71

10.8680

 

AA

1(1)

5(2)

    

rs13706

GG

85(40)

138(42)

0.7230

1.07

0.74-1.54

54.9480

 

GA+AA

125(60)

188(58)

    
 

GG+GA

187(89)

289(89)

0.3210

0.76

0.43-1.31

24.3960

 

AA

23(11)

37(11)

    

rs1531697

AA

75(36)

134(41)

0.2920

1.22

0.84-1.77

22.1920

 

AT+TT

134(64)

191(59)

    
 

AA+AT

180(86)

277(85)

0.9290

0.98

0.58-1.645

70.6040

 

TT

29(14)

48(15)

    

rs1800925

TT

6(3)

12(4)

0.7160

1.22

0.43-3.47

54.4160

 

TC+CC

201(97)

294(96)

    
 

TT+TC

56(27)

93(31)

0.0790

1.41

0.96-2.08

6.0040

 

CC

151(73)

213(69)

    

rs3024791

GG

181(87)

293(90)

0.3770

1.27

0.75-2.14

28.6520

 

GA+AA

27(13)

31(10)

    
 

GG+GA

207(99.5)

323(99.7)

0.8760

1.25

0.08-20.07

66.5760

 

AA

1(0.5)

1(0.3)

    

rs6537302

AA

115(55)

194(62)

0.5150

1.13

0.79-1.62

39.1400

 

AT+TT

92(45)

117(38)

    
 

AA+AT

195(94)

286(92)

0.3070

0.68

0.33-1.41

23.3320

 

TT

12(6)

25(8)

    

rs6555465

GG

40(19)

83(26)

0.1920

1.34

0.86-2.10

14.5920

 

GA+AA

173(81)

241(74)

    
 

GG+GA

155(73)

227(70)

0.8710

0.97

0.65-1.45

66.1960

 

AA

58(27)

97(30)

    

rs673400

CC

0(0)

0(0)

NA

NA

NA

NA

 

CG+GG

208(100)

323(100)

    
 

CC+CG

178(86)

278(86)

0.8190

0.94

0.56-1.57

62.2440

 

GG

30(14)

45(14)

    

rs6889822

GG

84(40)

133(42)

0.4800

1.14

0.79-1.65

36.4800

 

GA+AA

124(60)

187(58)

    
 

GG+GA

184(88)

284(89)

0.7550

1.10

0.62-1.95

57.3800

 

AA

24(12)

36(11)

    

rs8004738

GG

45(22)

68(22)

0.7910

1.06

0.69-1.64

60.1160

 

GA+AA

163(78)

245(78)

    
 

GG+GA

139(67)

207(66)

0.6880

1.08

0.74-1.60

52.2880

 

AA

69(33)

106(34)

    

rs1003349

GG

68(33)

122(37)

0.1880

1.29

0.88-1.89

14.2880

 

GT+TT

140(67)

204(63)

    
 

GG+GT

170(82)

270(83)

0.6130

1.13

0.70-1.83

46.5880

 

TT

38(18)

56(17)

    

rs1032295

TT

119(56)

206(63)

0.1570

1.30

0.90-1.88

11.9320

 

TG+GG

94(44)

122(37)

    
 

TT+TG

201(94)

317(97)

0.2380

1.70

0.70-4.12

18.0880

 

GG

12(6)

11(3)

    

rs1042522

CC

37(18)

60(18)

0.8050

1.06

0.66-1.70

61.1800

 

GC+GG

173(82)

266(82)

    
 

CC+CG

147(70)

244(75)

0.2860

1.25

0.83-1.86

21.7360

 

GG

63(30)

82(25)

    

rs1052443

CC

96(46)

163(50)

0.2950

1.21

0.85-1.74

22.4200

 

CA+AA

114(54)

160(50)

    
 

CC+CA

185(88)

294(91)

0.1970

1.49

0.81-2.71

14.9720

 

AA

25(12)

29(9)

    

rs12504628

TT

107(50)

166(50)

0.9000

0.98

0.68-1.40

68.4000

 

TC+CC

106(50)

162(50)

    
 

TT+TC

198(93)

309(94)

0.7810

1.11

0.54-2.27

59.3560

 

CC

15(7)

19(6)

    

rs1695

GG

5(2)

10(3)

0.4990

1.47

0.48-4.44

37.9240

 

GA+AA

204(98)

318(97)

    
 

GG+GA

67(32)

116(35)

0.5520

1.12

0.77-1.64

41.9520

 

AA

142(68)

212(65)

    

rs1800469

CC

39(19)

74(23)

0.9960

1.34

0.98-1.95

75.6960

 

TC+TT

169(81)

252(77)

    
 

CC+TC

143(69)

241(74)

0.2530

1.26

0.85-1.88

19.2280

 

TT

65(31)

85(26)

    

rs2853209

AA

42(20)

68(21)

0.4560

1.18

0.76-1.84

34.6560

 

AT+TT

169(80)

251(79)

    
 

AA+AT

149(71)

232(72)

0.4850

0.87

0.59-1.28

36.8600

 

TT

62(29)

92(28)

    

rs4073

AA

36(17)

68(21)

0.2460

1.32

0.83-2.09

18.6960

 

AT+TT

174(83)

256(79)

    
 

AA+AT

149(71)

232(72)

0.3260

1.22

0.82-1.83

24.7760

 

TT

61(29)

92(28)

    

rs6937121

TT

72(34)

141(43)

0.0280

1.52

1.05-2.20

2.1280

 

TG+GG

138(66)

185(57)

    
 

TT+TG

182(87)

282(86)

0.6680

0.89

0.53-1.50

50.7680

 

GG

28(13)

44(14)

    

rs6957

GG

21(10)

40(12)

0.2810

1.37

0.77-2.43

21.3560

 

GA+AA

188(90)

288(88)

    
 

GG+GA

129(62)

201(61)

0.8730

0.97

0.67-1.41

66.3480

 

AA

80(38)

127(39)

    

rs1051730

CC

196(95)

311(94)

0.5330

1.25

0.62-2.50

40.5080

 

CT+TT

11(5)

20(6)

    
 

CC+CT

207(100)

330(99.7)

NA

NA

NA

NA

 

TT

0(0)

1(0.3)

    

rs11106030

CC

153(73)

237(72)

0.9350

1.02

0.68-1.52

71.0600

 

CA+AA

56(27)

93(28)

    
 

CC+CA

202(96)

323(98)

0.3350

1.77

0.55-5.66

25.4600

 

AA

7(4)

7(2)

    

rs1130864

TT

0(0)

0(0)

NA

NA

NA

NA

 

TC+CC

206(100)

317(100)

    
 

TT+TC

23(11)

43(14)

0.3720

1.26

0.76-2.07

28.2720

 

CC

183(89)

274(86)

    

rs2241712

AA

44(21)

92(28)

0.1560

1.37

0.89-2.10

11.8560

 

AG+GG

163(79)

239(72)

    
 

AA+AG

144(69)

250(76)

0.2290

1.28

0.86-1.92

17.4040

 

GG

63(31)

81(24)

    

rs2280090

GG

185(88)

299(90)

0.4650

1.23

0.71-2.14

35.3400

 

GA+AA

26(12)

32(10)

    
 

GG+GA

210(99.5)

330(99.4)

0.8760

1.25

0.08-20.07

66.5760

 

AA

1(0.5)

1(0.6)

    

rs2395730

AA

20(9)

48(15)

0.0490

1.77

1.00-3.13

3.7240

 

AC+CC

191(91)

283(85)

    
 

AA+AC

99(9)

161(49)

0.3610

1.18

0.82-1.70

27.4360

 

CC

112(53)

170(51)

    

rs2736118

AA

186(88)

299(90)

0.2740

1.38

0.78-2.45

20.8240

 

AG+GG

25(12)

32(10)

    
 

AA+AG

211(100)

331(100)

NA

NA

NA

NA

 

GG

0(0)

0(0)

    

rs2736122

CC

181(87)

301(90)

0.035

1.84

1.04-3.24

2.6600

 

CT+TT

26(13)

30(10)

    
 

CC+CT

181(100)

331(100)

NA

NA

NA

NA

 

TT

0(0)

0(0)

    

rs3817928

AA

166(81)

268(81)

0.4490

1.19

0.76-1.85

34.1240

 

AG+GG

41(19)

63(19)

    
 

AA+AG

204(99)

328(99)

0.7860

1.25

0.25-6.26

59.7360

 

GG

3(1)

3(1)

    

rs584367

TT

10(5)

14(4)

0.5010

0.73

0.30-1.82

38.0760

 

TC+CC

197(95)

317(96)

    
 

TT+TC

81(39)

138(42)

0.6410

1.10

0.76-1.57

48.7160

 

CC

126(61)

193(58)

    

rs1042714

CC

168(81)

280(85)

0.1020

1.48

0.93-2.36

7.7520

 

GC+GG

39(19)

49(15)

    
 

CC+GC

206(99)

327(99)

0.6990

0.62

0.06-6.90

53.1240

 

GG

1(1)

2(1)

    

rs13147758

AA

102(50)

168(52)

0.6310

1.09

0.76-1.57

47.9560

 

AG+GG

104(50)

157(48)

    
 

AA+AG

181(88)

296(91)

0.2920

1.38

0.76-2.49

22.1920

 

GG

25(12)

29(9)

    

rs1422795

GG

5(2)

11(3)

0.4990

1.47

0.48-4.44

37.9240

 

GA+AA

202(98)

313(97)

    
 

GG+GA

56(27)

97(29)

0.9400

0.99

0.66-1.46

71.4400

 

AA

151(73)

232(71)

    

rs1800796

CC

110(53)

168(51)

0.5080

0.89

0.62-1.27

38.6080

 

CG+GG

97(47)

161(49)

    
 

CC+CG

183(88)

305(97)

0.1060

1.68

0.90-3.16

8.0560

 

GG

24(12)

24(3)

    

rs2236307

CC

41(20)

62(19)

0.9460

0.98

0.62-1.55

71.8960

 

CT+TT

166(80)

267(81)

    
 

CC+CT

128(62)

224(68)

0.2150

1.27

0.87-1.86

16.3400

 

TT

79(38)

105(32)

    

rs2280091

AA

178(86)

283(86)

0.6730

1.11

0.68-1.82

51.1480

 

AG+GG

29(14)

45(14)

    
 

AA+AG

205(99)

328(100)

NA

NA

NA

NA

 

GG

2(1)

0(0)

    

rs2853676

GG

137(67)

225(69)

0.3510

1.20

0.82-1.75

26.6760

 

GA+AA

69(33)

103(31)

    
 

GG+GA

198(97)

319(98)

0.3930

1.58

0.56-4.46

29.8680

 

AA

8(3)

9(2)

    

rs868966

AA

56(27)

84(26)

0.6620

0.91

0.60-1.38

50.3120

 

AG+GG

151(73)

245(74)

    
 

AA+AG

149(72)

253(77)

0.3970

1.20

0.79-1.80

30.1720

 

GG

58(28)

76(23)

    

Haplotype analysis

Using Haploview software, CRP gene polymorphisms were determined to be in linkage disequilibrium (D’=1.0). Using PHASE software, haplotype frequencies for the polymorphisms rs1205 and rs2808630 of CRP at chromosome 1 were compared with respect to frequency between COPD patients and healthy controls. These two SNPs formed three haplotypes: CC, CT, and TT (Table 6 and Figure 1). Among them, only the TT haplotype was more frequently detected in controls (61%) compared with COPD patients (52%) (OR=0.69, 95% CI 0.49–0.98, p=0.0377). TGF-β1 rs2241718 and CDC97 rs6957 were in linkage disequilibrium (D’=0.98); they formed two haplotypes, GC and GT. These two haplotypes were respectively more frequent in healthy controls compared with COPD patients (OR=0.33, 95% CI 0.23–0.48, p=1.88×10-9) (Table 6 and Figure 2). TGF-β1 rs1800469 and rs2241712 were also in linkage disequilibrium (D’=0.98); they formed TG and CA haplotypes. However, no significant differences between the two groups were detected (Table 6 and Figure 2).
Table 6

Haplotypes of the CRP and TGF-β1 gene

SNPs(gene)

Haplotype

Control (n,%)

Case (n,%)

χ2

P value

OR

OR(95%CI)

rs2241718(TGF-β1)

GC

107(50)

83(25)

36.0947

1.88×10 -9

0.33

0.23-0.48

rs6957(CDC97)

Non-GC

106(50)

248(75)

    
 

GT

107(50)

83(25)

36.0947

1.88×10 -9

0.33

0.23-0.48

 

Non-GT

106(50)

248(75)

    

rs1800469(TGF-β1)

TG

111(52)

159(48)

0.8615

0.3533

0.85

0.60-1.20

rs2241712(TGF-β1)

Non-TG

102(48)

172(52)

    
 

CA

94(44)

162(49)

1.2041

0.2725

1.21

0.86-1.71

 

Non-CA

119(56)

169(51)

    

rs1205(CRP)

TT

130(61)

172(52)

4.3163

0.0377

0.69

0.49-0.98

rs2808630(CRP)

Non-TT

83(39)

159(48)

    
 

CC

32(15)

60(18)

0.8883

0.3459

1.25

0.78-2.0

 

Non-CC

181(85)

271(82)

    
 

CT

51(24)

96(29)

1.6822

0.1946

1.30

0.87-1.92

 

Non-CT

162(76)

235(71)

    

The p value with bold letters indicate those allele frequencies with significant differences between COPD and controls.

https://static-content.springer.com/image/art%3A10.1186%2F1755-8794-5-64/MediaObjects/12920_2012_Article_367_Fig1_HTML.jpg
Figure 1

Linkage disequilibrium of SNPs in the CRP gene using Haploview software. The red color indicates the higher linkage disequilibrium (D’=1.0) between rs2808630 and rs1205.

https://static-content.springer.com/image/art%3A10.1186%2F1755-8794-5-64/MediaObjects/12920_2012_Article_367_Fig2_HTML.jpg
Figure 2

Linkage disequilibrium of SNPs in the TGF-β1 and CDC97 genes using Haploview software. The red color indicates the higher linkage disequilibrium (D’=0.98) between the rs2241718 and rs6957; between the rs1800469 and rs2241712.

Discussion

In this study, we sought to determine which of 76 SNPs we chose were associated with the development of COPD. Our case–control study verified that the following SNPs were associated with COPD: rs2353397 C, rs1800629 G, rs2241712 A, rs1205 C, rs20541 T, rs2070600 G, and rs10947233 G. The rs2353397 C allele was most strongly associated with COPD.

rs2353397 CC, CT genotypes of the HHIP gene were associated with susceptibility to COPD in the Chinese Han population. The HHIP gene is located at chromosome 4q31.21–31.3, position 145517578; it encodes the HHIP protein [17]. This protein is a critical regulator of the hedgehog (Hh) signalling pathway, which has been implicated in cell development, cell repair, and cancer development in multiple tissues [18]. The idea that COPD could be associated with inappropriate growth or structural defects in small airways makes HHIP an attractive candidate developmental gene. Several GWASs have also demonstrated that the 4q31 locus, which contains the HHIP gene, is associated with COPD and lung function [912]. A GWA meta-analysis for pulmonary function in 20,890 participants of European white ancestry revealed eight genes associated with COPD and concluded that HHIP is associated with FEV1/FVC [10]. Few studies prior to our current study have reported the SNPs of the HHIP gene related to COPD in an Asian population. Polymorphisms may lead to changes in gene expression, resulting in functional alteration and, subsequently, to COPD. According to Zhou et al. (2012) [19], significant decreases in expression of the HHIP gene at the mRNA and protein levels were observed in COPD lungs compared with lungs of smokers with normal lung function. The risk-associated haplotype confers decreased activity on the HHIP promoter, indicating that lower HHIP expression may exacerbate smoking-induced COPD pathogenesis. Lemjabbar-Alaoui et al. (2006) [20] demonstrated that hedgehog signaling proteins are critical mediators of cigarette smoke-induced disease, such as lung cancer and chronic airway inflammatory disease, and the expression levels of hedgehog signaling proteins are modulated by HHIP. Based on our current study of HHIP polymorphisms and the Hh signaling pathway, we need to further our mechanistic research in the context of smoking.

Our results also demonstrated that rs1800629 GG carriers of the TNF-α gene were at several times the risk for COPD compared with GA, AA carriers. TNF-α is critical in the regulation of inflammation; it induces a cascade of other inflammatory cytokines, chemokines, and other growth factors; it is important in the pathogenesis of many diseases. Several gene studies have also determined that the promoter polymorphism of TNF-α is associated with chronic bronchitis or the extent of emphysematous changes. Two of these studies were performed with Caucasian subjects, two with Japanese subjects [2124]. The promoter polymorphism may have caused varied concentrations of serum TNF-α, which have been associated with induced sputum in bronchial biopsies and with bronchoalveolar lavage fluid in stable COPD patients and during exacerbations, compared with that of control subjects [25]. Some investigators have shown that TNF-α genotypes do influence the severity of infectious diseases, while others have concluded that polymorphisms of this gene promoter are of no functional consequence [26, 27].

A polymorphism of the TGF-β1 gene, rs2241712 A, tended to be a risk-associated allele in our study. TGF-β1 is one of the important cytokines involved in the inflammatory process of COPD. TGF-β1 expression is usually increased in the airways of patients. Su et al. (2005) [28] found that more carriers of the -800A allele, or fewer carriers of the -509T allele were detected among the COPD patients, but only 84 COPD cases and 97 healthy controls participated in their research. In addition, we used a Chinese Han population, while Su et al. recruited people in a general Chinese population. Van Diemen et al. (2010) [29] showed that the TGF-β1 rs6957 SNP haplotype with the major allele of rs6957 and minor alleles of rs1800469 and rs1982073 were associated with COPD. The differences in study populations may explain these dissimilarities between our studies. Various studies have indicated that certain SNPs of the TGF-β1 gene are functional and result in higher levels of circulating TGF-β1 [30, 31].

The SNP rs20541 at IL-13 gene exon 4 tended to be associated with COPD in our study. Genotype TT, CT carriers were at risk. IL-13 is a Th2 cytokine implicated in the recruitment of inflammatory cells from the blood to the lung, which may be involved in the pathogenesis of COPD. In experimental studies, the overexpression of IL-13 in the adult murine lung caused emphysema [32]. The number of IL-13+ cells was elevated in the bronchial submucosa of smokers with chronic bronchitis compared to asymptomatic smokers [33]. rs2066960, rs20541, and rs1295685 in the IL-13 gene were associated with COPD risk and lower baseline lung function in the study by Beghé et al. (2010) [34], which used a Caucasian study population. We chose the same SNPs located in the IL-13 gene, but our results showed that only rs20541 is of significance in susceptibility to COPD in the Chinese Han population. In addition, another study revealed the role of rs20541 in another chronic airway inflammatory disease (asthma), which indicates that the polymorphism in the coding region might contribute to airflow limitation [35].

The polymorphism of another inflammatory marker in the CRP gene, rs1205 C, was also a risk-associated allele according to our current study. Sunyer et al. (2008) [36] assessed the association between rs1205 and lung function; they demonstrated that the TT homozygous genotype in the CRP gene is associated with better lung function. Our result that the TT genotype protects people against COPD is similar to theirs because COPD is characterized by airflow limitation according to lung function. This polymorphism has been previously reported associated with varied levels of CRP in several studies [37]. Higher levels of CRP in peripheral blood may cause impaired lung function [38].

Two other SNPs, AGER rs2070600 and PPT2 rs10947233, tended to be associated with COPD in our current study. rs2070600 GG and rs10947233 GG, GT carriers tended to develop COPD. An occidental GWAS demonstrated a role for the chromosome 6p21 locus including the AGER and PPT2 genes in COPD development in smokers [39]. Repapi et al. (2010) [12] reported a meta-analysis of GWAS results from 20,288 participants and follow-up analyses in 54,276 participants; they identified five novel, genome-wide, significant loci for pulmonary function containing AGER rs2070600, but their analysis subject group did not include Asians. In addition, rs2070600 was associated with severe COPD in a study of Caucasian smokers from Poland [40]. The two SNPs of AGER and PPT2 were also identified associated with FEV1/FVC in the 2009 work of Hancock et al. [10].

In addition, our study revealed some haplotypes composed of rs1205 and rs 2808630 in the CRP gene, rs2241718 and rs 6957 at the TGF-β1 and CDC97 genes. In our future research, we will further analyze our data with regard to lung function.

Our research had some limitations. First, a larger sample size would have improved quality of the results. Second, although we selected 97 SNPs for the study and found some loci related to the disease, further GWASs of COPD are needed in the Chinese Han population to identify more associated polymorphisms. It is likely that more genetic risk factors than those identified in this study contribute to the development of COPD. In our future work, we will further our investigation on gene function of the genetic factors related to the development of COPD.

Conclusion

Our findings identified some genetic variants associated with COPD. This study has provided important information regarding the association of these polymorphisms to the susceptibility to COPD in the Chinese Han population. However, these findings need to be verified. These data emphasize the need for further research regarding gene function in COPD that will ultimately contribute to future gene therapies for this significant and costly disease in the Chinese Han population.

Abbreviations

COPD: 

Chronic obstructive pulmonary disease

FEV1: 

Forced expiratory volume in 1s

FVC: 

Forced vital capacity

GWAS: 

Genome-wide association study

SNP: 

Single-nucleotide polymorphisms

MAF: 

Minor allele frequency

HHIP: 

Human hedgehog interacting protein.

Declarations

Acknowledgements

We acknowledge the 11th Chinese National Five-year Development Plan for support of this work.

Authors’ Affiliations

(1)
Department of Pulmonary Medicine, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University
(2)
Department of Respiratory Medicine, Hua Shan Hospital, Fu Dan University
(3)
State Key Laboratory of Medical Genomics, Molecular Medicine Center, Shanghai Rui Jin Hospital
(4)
Department of Respiratory Medicine, Shanghai Jing-an geriatric Hospital
(5)
Department of Respiratory Medicine, Shanghai Gong Hui Hospital

References

  1. Rabe KF, Beghé B, Luppi F, Fabbri LM: Update in chronic obstructive pulmonary disease 2006. Am J Respir Crit Care Med. 2007, 175 (12): 1222-1232. 10.1164/rccm.200704-586UP.View ArticlePubMedGoogle Scholar
  2. Murray CJL, Lopez AD: Evidence-based health policy: lessons from the global burden of disease study. Science. 1996, 274 (5288): 740-743. 10.1126/science.274.5288.740.View ArticlePubMedGoogle Scholar
  3. Silverman EK: Progress in chronic obstructive pulmonary disease genetics. Proc Am Thorac Soc. 2006, 3 (5): 405-408. 10.1513/pats.200603-092AW.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Lokke A, Lange P, Scharling H, Fabricius P, Vestbo J: Developing COPD: a 25-year follow up study of the general population. Thorax. 2006, 61 (11): 935-939. 10.1136/thx.2006.062802.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, Pukkala E, Skytthe A, Hemminki K: Environmental and heritable factors in the causation of cancer: analyses of cohorts of twins from Sweden, Denmark and Finland. N Eng J Med. 2000, 343 (2): 78-85. 10.1056/NEJM200007133430201.View ArticleGoogle Scholar
  6. 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 (8): 1419-1424.View ArticlePubMedGoogle Scholar
  7. Chen Y: Genetics and pulmonary medicine.10: Genetic epidemiology of pulmonary function. Thorax. 1999, 54 (9): 818-824. 10.1136/thx.54.9.818.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Wilk JB, Chen TH, Gottlieb DJ, Walter RE, Nagle MW, Brandler BJ, Myers RH, Borecki IB, Silverman EK, Weiss ST, O’Connor GT: A genome-wide association study of pulmonary function measures in the Framingham Heart Study. PLoS Genet. 2009, 5 (3): e1000429-10.1371/journal.pgen.1000429.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Pillai SG, Ge DL, Zhu GH, Kong XY, Shianna KV, Need AC, Feng S, Hersh CP, Bakke P, Gulsvik A, Ruppert A, Lødrup Carlsen KC, Roses A, Anderson W, Investigators ICGN, Rennard SI, Lomas DA, Silverman EK, Goldstein DB: A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci. PLoS Genet. 2009, 5 (3): e1000421-10.1371/journal.pgen.1000421.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Hancock DB, Eijgelsheim M, Wilk JB, Gharib SA, Loehr LR, Marciante KD, Franceschini N, van Durme YMTA, Chen TH, Barr RG, Schabath MB, Couper DJ, Brusselle GG, Psaty BM, van Duijn CM, Rotter JI, Uitterlinden AG, Hofman A, Punjabi NM, Rivadeneira F, Morrison AC, Enright PL, North KE, Heckbert SR, Lumley T, Stricker BHC, O’Connor GT, London SJ: Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet. 2010, 42 (1): 45-52. 10.1038/ng.500.View ArticlePubMedGoogle Scholar
  11. Cho MH, Boutaoui N, Klanderman BJ, Sylvia JS, Ziniti JP, Hersh CP, et al: Variants in FAM13A are associated with chronic obstructive pulmonary disease. Nat Genet. 2010, 42 (3): 200-202. 10.1038/ng.535.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Repapi E, Sayers I, Wain LV, Burton PR, Johnson T, Obeidat M, et al: Genome-wide association study indentifies five loci associated with lung function. Nat Genet. 2010, 42 (1): 36-44. 10.1038/ng.501.View ArticlePubMedGoogle Scholar
  13. Tomashefski JF, Crystal RG, Wiedemann HP, Mascha E, Stoller JK: The bronchopulmonary pathology of alpha-1 antitrypsin (AAT) deficiency: findings of the Death Review Committee of the national registry for individuals with Severe Deficiency of Alpha-1 Antitrypsin. Hum Pathol. 2004, 35 (12): 1452-1461. 10.1016/j.humpath.2004.08.013.View ArticlePubMedGoogle Scholar
  14. Wang XY, Li L, Xiao JL, Jin CZ, Huang K, Kang XW, Wu XM, Lv FZ: Association of ADAM33 gene polymorphisms with COPD in a northeastern Chinese population. BMC Medical Genetics. 2009, 10: 132-138. 10.1186/1471-2350-10-132.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, Fukuchi Y, Jenkins C, Rodriguez-Roisin R, Weel CV, Zielinski J: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2007, 176 (6): 532-555. 10.1164/rccm.200703-456SO.View ArticlePubMedGoogle Scholar
  16. Edwards MC, Gibbs RA: Multiplex PCR: advantages, development, and applications. Genome Res. 1994, 3 (5): S65-75.View ArticleGoogle Scholar
  17. Kayed H, Kleeff J, Keleg S, Guo J, Ketterer K, Berberat PO, Giese N, Esposito I, Giese T, Büchler MW, Friess H: Indian hedgehog signaling pathway:expression and regulation in pancreatic cancer. Int J Cancer. 2004, 110 (5): 668-676. 10.1002/ijc.20194.View ArticlePubMedGoogle Scholar
  18. Villavicencio EH, Walterhouse DO, Iannaccone PM: The sonic hedgehog-patched-gli pathway in human development and disease. Am J Hum Genet. 2000, 67 (5): 1047-1054.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Zhou XB, Baron RM, Hardin M, Cho MH, Zielinski J, Hawrylkiewicz I, Sliwinski P, Hersh CP, Mancini JD, Lu K, Thibault D, Donahue AL, Klanderman BJ, Rosner B, Raby BA, Lu Q, Geldart AM, Layne MD, Perrella MA, Weiss ST, Choi AMK, Silverman EK: Identification of a chronic obstructive pulmonary disease genetic determinant that regulates HHIP. Hum Mol Genet. 2012, 21 (6): 1325-1335. 10.1093/hmg/ddr569.View ArticlePubMedGoogle Scholar
  20. Lemjabbar-Alaoui H, Dasari V, Sidhu SS, Mengistab A, Finkbeiner W, Gallup M, Basbaum C: Wnt and hedgehog are critical mediators of cigarette smoke-induced lung cancer. PLoS One. 2006, 1: e93-10.1371/journal.pone.0000093.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Sakao S, Tatsumi K, Igari H, Watanabe R, Shino Y, Shirasawa H, Kuriyama T: FCCP Association of tumor necrosis factor gene promoter polymorphism with low attenuation areas on high-resolution CT in patients with COPD. Chest. 2002, 122 (2): 416-420. 10.1378/chest.122.2.416.View ArticlePubMedGoogle Scholar
  22. Keicho N, Emi M, Nakata K, Taguchi Y, Azuma A, Tokunaga K, Ohishi N, Kudoh S: Promoter variation of tumour necrosis factor-alpha gene:possible high risk for chronic bronchitis but not diffuse panbronchiolitis. Respir Med. 1999, 93 (10): 752-753. 10.1016/S0954-6111(99)90044-6.View ArticlePubMedGoogle Scholar
  23. Stankovic MM, Nestorovic AR, Tomovic AM, Petrovic-Stanojevic ND, Andjelicjelic A, Dopudja-Pantic VB, Nagorni-Obradovic LM, Mitic-Milikic MM, Radojkovic DP: TNF-alpha-308 promotor polymorphism in patients with chronic obstructive pulmonary disease and lung cancer. Neoplasma. 2009, 56 (4): 348-352. 10.4149/neo_2009_04_348.View ArticlePubMedGoogle Scholar
  24. Papatheodorou A, Latsi P, Vrettou C, Dimakou A, Chroneou A, Makrythanasis P, Kaliakatsos M, Orfanidou D, Roussos C, Kanavakis E, Tzetis M: Development of a novel microarray methodology for the study of SNPs in the promoter region of the TNF-alpha gene:their association with obstructive pulmonary disease in Greek patients. Clin Biochem. 2007, 40 (12): 843-850. 10.1016/j.clinbiochem.2007.03.024.View ArticlePubMedGoogle Scholar
  25. Chung KF: Cytokines in chronic obstructive pulmonary disease. Eur Respir J. 2001, 18 (Suppl 34): 50s-59s.View ArticleGoogle Scholar
  26. Bouma G, Crusius JBA, Pool MO, Kolkman JJ, von Blomberg BME, Kostense PJ, Giphart MJ, Schreuder GMTH, Meuwissen SGM, Peña AS: Secretion of tumor necrosis factor α and lymphotoxin in relation to polymorphisms in TNF genes and HLA-DR alleles: relevance for inflammatory bowel disease. Scand J Immunol. 1996, 43 (4): 456-463. 10.1046/j.1365-3083.1996.d01-65.x.View ArticlePubMedGoogle Scholar
  27. Moffatt MF, Cookson OCM: Tumor necrosis factor haplotypes and asthma. Hum Mol Genet. 1997, 6 (4): 551-554. 10.1093/hmg/6.4.551.View ArticlePubMedGoogle Scholar
  28. Su ZG, Wen FQ, Feng YL, Xiao M, Wu XL: Transforming growth factor-beta1 gene polymorphisms associated with chronic obstructive pulmonary disease in Chinese population. Acta pharmacol sin. 2005, 26 (6): 714-720.PubMedGoogle Scholar
  29. Van Diemen CC, Postma DS, Aulchenko YS, Snijders PJLM, Oostra BA, van Duijin CM, Boezen M: Novel strategy to identify genetic risk factors for COPD severity: a genetic isolate. Eur Respir J. 2010, 35 (4): 768-775. 10.1183/09031936.00054408.View ArticlePubMedGoogle Scholar
  30. Silverman ES, Palmer LJ, Subramaniam V, Hallock A, Mathew S, Vallone J, Faffe DS, Shikanai T, Raby BA, Weiss ST, Shore SA: Transforming Growth Factor-β1 promoter polymorphism C-509T is associated with asthma. AM J Respir Crit Care Med. 2004, 169 (2): 214-219.View ArticlePubMedGoogle Scholar
  31. Grainger DJ, Heathcote K, Chiano M, Snieder H, Kemp PR, Metcalfe JC, Carter ND, Spector TD: Genetic control of the circulating concentration of transforming growth factor type beta1. Hum Mol Genet. 1999, 8 (1): 93-97. 10.1093/hmg/8.1.93.View ArticlePubMedGoogle Scholar
  32. Zheng T, Zhu Z, Wang Z, Homer RJ, Ma B, Riese RJ, Chapman HA, Shapiro SD, Elias JA: Inducible targeting of IL-13 to the adult lung causes matrix metalloproteinase- and cathepsin-dependent emphysema. J Clin Invest. 2000, 106 (9): 1081-1093. 10.1172/JCI10458.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Miotto D, Ruggieri MP, Boschetto P, Cavallesco G, Papi A, Bononi I, Piola C, Murer B, Fabbri LM, Mapp CE: Interleukin-13 and −4 expression in the central airways of smokers with chronic bronchitis. Eur Respir J. 2003, 22 (4): 602-608. 10.1183/09031936.03.00046402.View ArticlePubMedGoogle Scholar
  34. Beghé B, Hall IP, Parker SG, Moffatt MF, Wardlaw A, Connolly MJ, Fabbri LM, Ruse C, Sayers I: Polymorphisms in IL13 pathway genes in asthma and chronic obstructive pulmonary disease. Allergy. 2010, 65 (4): 474-481. 10.1111/j.1398-9995.2009.02167.x.View ArticlePubMedGoogle Scholar
  35. Black S, Teixeira AS, Loh AXW, Vinall L, Holloway JW, Hardy R, Swallow DM: Contribution of functional variation in the IL13 gene to allergy, hay fever and asthma in the NSHD longitudinal 1946 birth cohort. Allergy. 2009, 64 (8): 1172-1178. 10.1111/j.1398-9995.2009.01988.x.View ArticlePubMedGoogle Scholar
  36. Sunyer J, Pistelli R, Plana E, Andreani M, Baldari F, Kolz M, Koenig W, Pekkanen J, Peters A, Forastiere F: Systemic inflammation, genetic susceptibility and lung function. Eur Respir J. 2008, 32 (1): 92-97. 10.1183/09031936.00052507.View ArticlePubMedGoogle Scholar
  37. Kardys I, de Maat MP, Uitterlinden AG, Hofman A, Witteman JC: C-reactive protein gene haplotypes and risk of coronary heart disease: the Rotterdam Study. Eur Heart J. 2006, 27 (11): 1331-1337. 10.1093/eurheartj/ehl018.View ArticlePubMedGoogle Scholar
  38. Pinto-Plata VM, Müllerova H, Toso JF, Feudjo-Tepie M, Soriano JB, Vessey RS, Celli BR: C-reactive protein in patients with COPD, control smokers and nonsmokers. Thorax. 2006, 61 (1): 23-28.View ArticlePubMedGoogle Scholar
  39. Castaldi PJ, Cho MH, Litonjua AA, Bakke P, Gulsvik A, Lomas DA, Anderson W, Beaty TH, Hokanson JE, Crapo JD, Laird N, Silverman EK, COPD Gene and Eclipse investigators: The association of genome-wide significant spirometric loci with chronic obstructive pulmonary disease susceptibility. AM J Respir Cell Mol Biol. 2011, 45 (6): 1147-1153. 10.1165/rcmb.2011-0055OC.View ArticlePubMedPubMed CentralGoogle Scholar
  40. Hardin M, Zielinski J, Wan ES, Hersh CP, Castaldi PJ, Schwinder E, Hawrylkiewicz I, Sliwinski P, Cho MH, Silverman EK: CHRNA3/5, IREB2, and ADCY2 are associated with severe COPD in Poland. Am J Respir Cell Mol Biol. 2012, 47 (2): 203-208. 10.1165/rcmb.2012-0011OC.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1755-8794/5/64/prepub

Copyright

© Guo et al.; licensee BioMed Central Ltd. 2012

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.