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Chronic obstructive pulmonary disease risk and smoking cessation changes induced by CHRNA5-A3 and CHRNB3-A6 variation in a Chinese male population


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Introduction

Investigating chronic obstructive pulmonary disease (COPD) and smoking cessation is a continuing concern within pulmonology. Its mortality i expected to be ranked fourth in the world by 2030 [1]. It is generally believed that smoking is the main risk factor for COPD development, however, only a fraction (~20.0%) of smokers develop COPD [2]. This suggests that individual susceptibility is caused by genetic factors. Previous genetic studies have shown that nicotine-dependence is a complex genetic disorder [3]. We believe that genes related to nicotine-dependence may affect the development of COPD. In addition, nicotine-dependence can be considered as the most significant factor for smoking cessation [4].

Nicotinic acetylcholine receptors, or nAChRs, are receptor polypeptides that respond to the neurotransmitter acetylcholine [5]. Nicotine, a major component of tobacco, is the main cause of tobacco addiction that acts through nAChRs. At present, genome-wide association studies have proved that several single nucleotide polymorphisms (SNPs) (rs1051730, rs16969968, rs8034191 and rs4950) in two nAChRs (CHRNA5-A3 and CHRNB3-A6) subunit coding gene clusters are associated with nicotine-dependence and lung cancer [6, 7, 8, 9, 10]. In addition, according to the HapMap database (https://www.ncbi.nlm.nih.gov/probe/docs/ projhapmap/) and a study by Wu et al. [11], there is no report that these three SNP variants have been found in Asian populations. These variants have little risk of lung cancer and nicotine-dependence in the Chinese population. Surprisingly, the results of two independent studies show that rs667282 and rs3743073 in CHRNA5-A3 will affect the risk of lung cancer in Chinese people [11,12]. Moreover, several independent studies have shown that rs4950 in CHRNB3-A6 is with smoking behavior, and this shows that they have a certain role in people who have difficulty in quitting smoking and people who are carcinogenic due to smoking [9,10]. Thus far, no research has reported if the three SNPs are also associated with smoking-related COPD and smoking cessation. Therefore, this study aimed to investigate the correlation between the three SNPs (rs667282, rs3743073 and rs4950) and smoking cessation in the Chinese male population.

Materials and methods

Research Participants. From January 2017 to May 2018, we recruited patients admitted to the Second Ward of Respiratory Department of Qingdao Municipal Hospital, Qingdao, Shandong Province, People’s Republic of China (PRC). The study consisting of 823 male smokers with COPD (407 patients with COPD who failed to quit smoking and 416 non smokers with COPD ≥1 year) and 435 healthy male smokers as control subjects. All subjects were recruited from the Smoking Cessation Clinic and the Medical Examination Department of Qingdao Municipal Hospital. Demographic information, including age, body mass index (BMI), and detailed circumstances of smoking, was collected in interviews conducted by trained medical doctors. Those smoking at least 20 packs in their life, or smoking at least one cigarette a day for more than 1 year were classified a smokers, non smokers were classified as having quit smoking ≥1 year. Smoking COPD subjects meet the following criteria: for those who still smoke or have quit smoking, physician-diagnosed COPD, pulmonary function test showing post-bronchodilator forced expiratory volume (FEV) in 1 second (FEV1)/forced vital capacity (FVC) of less than 70.0% and FEV1 of less than 80.0% predicted in the Global Initiative for COPD 2015 (GOLD 2015; https://glodcopd/org/) Subject exclusion criteria: definite diagnosis of lung cancer, asthma or smoking-related cancer. Cases were matched according to age, BMI and smoking history. The study was approved by Qingdao Municipal Hospital Ethics Committee (approval number: KYLL2010058). All patients participating in the program signed an informed consent form.

Analysis. Blood samples of all participants were collected. Using the DNA extraction kit (Tiangen Biotech Co. Ltd., Beijing, PRC) to extract the genomic DNA of the subjects. Genotyping was carried out commercially using Sequenom MassARRAY® via Beijing Genomic Institute (BGI) (Shenzhen, PRC) [13]. In order to ensure the repeatability and consistency of the test, we randomly selected 5.0% of the samples for a second test. In addition, in order to further verify the accuracy of the BGI results, we also genotyped some samples by direct sequencing or restriction enzyme digestion.

Statistical Analysis. The t-test was used to confirm the difference in population characteristics and gene distribution between the experimental group and the control group. The χ2 test was used to compare the demographic characteristics of the case group and the control group. The correlation between each SNP and the risk of smoking and nicotine-dependence in COPD patients was evaluated by a logistic regression model, which adjusted the age, BMI, current smoking status and the number of packages per year for long-term smokers. Age, BMI, current smoking status and pack-years of the number of cigarettes smoked per year, including those who quit and those who are currently smoking, were analyzed in a hierarchical manner to assess whether there was any difference between these subgroups. All statistical analyses adopted a two-sided test, and a p value of <0.05 was considered to be statistically significant. The Statistical Package for the Social Sciences (SPSS) version 22 (IBM® SPSS; www.ibm.com/SPSS-Statistics/) was used for all statistical analysis.

Results

Demographic Characteristics. As shown in Table 1, the demographics and clinical feature distribution of the subjects show that there are significant differences in age, daily smoking volume and the years of smoking distribution between COPD smoking group, COPD absent smoking group, and smoking without COPD group (p 0.001, p <0.001 and p 0.001). For still smoking patients with COPD and non smoking patients with COPD, we discovered marked differences with respect to age and the years of smoking (both p 0.001). These differences were adjusted in subsequent logistic regression analyses. By comparing the ratios of FEV1 and FEV1/FVC, smoking COPD patients are significantly worse than the control group, and these findings are similar in still smoking patients with COPD and non smoking patients with COPD. In the COPD patients, pulmonary function was classified as mild, moderate, severe, and very severe (30.0, 31.4, 26.6 and 12.0%, respectively).

The demographic characteristics of the studied subjects. (Results are presented as mean±SD.)

Characteristics Male Smokers Male COPD Patients
COPD Patients (n=256) Healthy Controls (n=435) p Valuea Still Smoking (n=256) Non Smoking (n=410) p Valuea
Age (years) 67.6±11.1 57.1±13.2 <0.001 67.6±11.1 70.7±8.2 <0.001
BMI (years) 21.5±3.5 21.8±3.4 0.13 21.0±2.9 28.8±3.1 0.220
Smoking Cigarettes/variables: day 27.0±15.1 19.7±11.7 <0.001 27.0±15.1 21.2±9.7 <0.001
Years smoking 40.2±9.9 31.4±14.7 <0.001 40.2±9.9 34.9±13.4 <0.001
Post-FEV1 predicted 58.0±5.6 104.7±9.6 <0.001 58.0±5.6 59.1±16.2 0.0352
Post-FEV1/FVC ratio 52.7±8.7 78.5±5.6 <0.001 52.7±8.7 53.9±8.6 0.056
GOLD status:
Stage I (mild) 114 114 133
Stage II (moderate) 120 120 138
Stage III (severe) 98 98 121
Stage IV (very severe) 75 75 24

COPD: chronic obstructive pulmonary disease; FEV1: forced expiratory volume in 1 second; FVC: forced vital capacity.

a A p value of <0.05 was considered to be statistically significant.

Association Between Gene Polymorphisms and COPD Risk in Smokers. We observed all three SNPs were in Hardy-Weinberg equilibrium in the control group (p 0.05). We genotyped the three SNPs (rs3743073, rs667282 and rs4950) in cases and controls and the results are presented in Table 2. No significant associations were found between rs3743073, rs667282 and rs4950 genotypes and COPD risk after adjusting for age, BMI and smoking status.

Association of genotype distribution of three SNPs with COPD risk in the patients and controls.

SNP ID Genotype COPD Patients Healthy Controls Logistics Regression
n (%) n (%) pa2) OR (95% CI) pa2)
rs3743073 GG 109 (26.8) 106 (24.4) 1 (reference)
GT 190 (46.7) 207 (47.6) 0.502 1.14 (0.69-1.88) 0.615
TT 108 (26.5) 122 (28.0) 0.430 1.24 (0.81-1.91) 0.322
rs667282 TT 118 (29.0) 108 (24.8) 1 (reference)
CT 162 (39.8) 197 (45.3) 0.095 0.77 (0.51-1.15) 0.196
CC 127 (31.2) 130 (29.9) 0.540 0.70 (0.48-1.02) 0.066
rs4950 AA 183 (45.0) 208 (47.8) 1 (reference)
AG 164 (40.3) 181 (41.6) 0.842 1.28 (0.78-2.07) 0.310
GG 60 (14.7) 46 (10.6) 0.073 0.90 (0.65-1.26) 0.549

SNPs ID: single nucleotide polymorphisms identification; COPD: chronic obstructive pulmonary disease; OR: odds ratio; 95% CI: 95% confidence interval.

a A p value of <0.05 was considered to be statistically significant.

Association Between Gene Polmorphisms and Smoking Cessation in COPD Patients. Associations between gene polymorphisms and smoking cessation in COPD are shown in Table 3. The genotypes of rs667282 and rs4950 showed significant difference between cases and controls without adjustment for potential confounding factors (age, BMI and smoking pack-years). We adjusted for potential confounding factors by means of logistic regression, and then calculated the odds ratios (ORs). The CT genotype of rs667282 demonstrated association with an increased rate of successful smoking cessation compared with the TT genotype [adjusted OR = 0.54, 95% confidence interval (95% CI) = 0.37-0.7, P = 0.001]. The rs4950 AG genotypes were distinctly associated with increased rates of successful smoking cessation (adjusted OR = 0.55, 95% CI = 0.40-0.76, p 0.001). The effect is significant under the assumption of an over dominant mode of inheritance (adjusted OR = 0.58, 95% CI = 0.43-0.79, p 0.001), while the similar significant differences in rs3743073 was not found (p 0.005).

Association of genotype distribution of three SNPs with smoking cessation in still smoking and non smoking subjects.

SNP ID Genotype Still Smoking Non Smoking Logistics Regression
n (%) n (%) pa2) OR (95% CI)b pa2)
rs3743073 GG 109 (26.8) 92 (22.1) 1 (reference)
GT 190 (46.7) 221 (53.1) 0.063 1.01 (0.66-1.53) 0.975
TT 108 (26.5) 103 (24.8) 0.093 0.73 (0.51-1.05) 0.731
rs667282 TT 118 (29.0) 92 (22.1) 1 (reference)
CT 162 (39.8) 205 (49.3) 0.005 0.54 (0.37-0.77) 0.001
CC 127 (31.2) 119 (28.6) 0.330 0.75 (0.50-1.10) 0.142
CT+CC 289 (71.0) 324 (77.9) 0.024 0.61 (0.44-0.86) 0.004
TT+CC 245 (60.2) 211 (50.7)
CT 162 (39.8) 205 (49.3) 0.006 0.61 (0.45-0.83) 0.001
rs4950 AA 183 (45.0) 143 (34.3) 1 (reference)
AG 164 (40.3) 217 (52.2) 0.001 0.55 (0.40-0.76) <0.001
GG 60 (14.7) 56 (13.5) 0.412 0.85 (0.54-1.32) 0.462
AG+GG 224 (55.0) 273 (65.7) 0.002 0.62 (0.46-0.83) 0.001
AA+GG 243 (59.7) 199 (47.8)
AG 164 (40.3) 217 (52.2) 0.001 0.58 (0.43-0.79) <0.001

SNPs ID: single nucleotide polymorphisms identification; COPD: chronic obstructive pulmonary disease; OR: odds ratio; 95% CI: 95% confidence interval.

a A p value of <0.05 was considered to be statistically significant.

We further observed the suspicious influence factor of CHRNA5-A3 (rs 667282) and CHRNB3-A6 (rs4950) on smoking cessation, stratified by age, cigarettes per day (CPD) and initiation age smoking (Table 4 and Table 5, respectively). As show in Table 4, the success rate of quitting smoking increased for older subjects (>60 years) (OR = 0.66, 95% CI = 0.45-0.99, p = 0.042) and light smokers (CPD ≤20) (OR = 0.58, 95% CI = 0.39-0.86, p = 0.007), accompanied by rs667282 CT genotype. In Table 5, we show that the increased rate of successful smoking cessation with rs4950 AG genotypes was more notable in light smokers (CPD ≤20) (OR = 0.65, 95% CI = 0.45-0.92, p = 0.016). There was no significant difference in the stratification of age and initiation age smoking.

Stratification analysis of rs667282 genotypes by selected variables in still smoking and non smoking subjects.

Category Still Smoking Non Smoking
TT CT TT CT OR (9% CI) p Value
Age (years) <60 39 53 22 45 0.66 (0.35-1.28) 0.221
60 80 109 78 160 0.66 (0.45-0.99) 0.042
Cigarettes/Day <20 84 104 77 164 0.58 (0.39-0.86) 0.007
20 35 58 23 41 0.93 (0.48-1.80) 0.829
Initial age smoking <20 years 75 114 66 149 0.67 (0.45-1.02) 0.059
>20 years 44 48 34 56 0.66 (0.37-1.20) 0.171

OR: odds ratio; 95% CI: 95% confidence interval.

Stratification analysis of rs4950 genotypes by selected variables in still smoking and non smoking subjects.

Category Still Smoking Non Smoking
AA AG AA AG OR (9% CI) p Value
Age (years) <60 52 76 28 40 1.02 (0.56-1.86) 0.940
>60 128 106 118 174 1.22 (0.86-1.73) 0.260
Cigarettes/Day <20 116 114 106 161 0.65 (0.45-0.92) 0.016
>20 64 68 40 53 0.80 (0.47-1.37) 0.417
Initial age smoking <20 years 113 116 94 133 0.73 (0.50-1.05) 0.089
>20 years 67 66 52 81 0.63 (0.39-1.03) 0.064

OR: odds ratio; 95% CI: 95% confidence interval.

Association of CHRNA5-A3 and CHRNB3-A6 Poly-morphisms with the GOLD Stage of COPD Patients. The association of rs667282 and rs4950 polymorphisms with the GOLD stage of COPD patients are exhibited in Table 6. In our study, The CT genotype of rs667282 and the AG genotype of rs4950 showed a weak association with the GOLD stage of COPD patients.

Association of rs667282 and rs4950 polymorphisms with the GOLD stage of COPD patients.

Category Still Smoking OR (95% CI) p Value Non Smoking OR (95% CI) p Value
rs667292 TT CT TT CT
GOLD status: I and II 71 93 reference 55 126 reference
GOLD status: III and IV 48 70 0.90 (0.57-1.45) 0.661 45 79 1.31 (0.80-2.12) 0.281
rs4950 AA AG AA AG
GOLD status: I and II 102 110 reference 104 136 reference
GOLD status: III and IV 78 82 1.03 (0.68-1.55) 0.903 42 78 0.70 (0.45-0.11) 0.129

OR: odds ratio; 95% CI: 95% confidence interval.

Discussion

The purpose of our study was to investigate whether SNPs in the two gene clusters are related to COPD and smoking cessation in the Chinese population. We did not find a significant association between the SNPs and COPD risk in the smoking subjects. However, the SNP rs667282 in CHRNA3-A5 and rs4950 in CHRNB3-A6 showed a significant association with an increased rate of successful smoking cessation, in the Chinese COPD population, but the rs3743073 did not show an association with smoking cessation. These results suggest that the polymorphisms of CHRNA3-A5 and CHRNB3-A6 may play a key role in successful smoking cessation in Chinese COPD patients. As far as we know, this is the first study to reveal the relationship between SNP in CHRNA 3-A5 and CHRNB3-A6 genes and COPD and smoking cessation.

Nicotinic acetylcholine receptor (CHRN) genes code nAChRs, which bind to nicotinic that cause nicotinic dependence and smoking-related diseases. Recently, the associations of rs3743073 and rs667282 in CHRNA3-A5 and rs4950 in CHRNB3-A6 with tobacco consumption and lung cancer risk have been discovered [11,12,14,15]. Chronic smoking and environmental factors contribute to the development of lung cancer. Some studies show that COPD is a risk factor for lung cancer, even in early stage COPD [16, 17, 18]. The association between CHRNs and COPD and lung cancer has been confirmed [11,19]. We speculate that rs3743073, rs667282 and rs4950 may be associated with COPD in smokers, but we did not study the role of CHRN genetic variants with lung cancer. In addition, consistency with the conclusions of the study of Budulac et al. [20], CHRN gene variants are closely correlated with smoking habits, but do not directly cause COPD.

The main reason that smokers are unable to quit is nicotine dependence, and nicotine dependence has a relationship with a series of diseases, especially COPD [21]. Smoking cessation is the only evidence-based intervention, which can reduce the risk of developing COPD and slow down the accelerated decline of lung function in patients with COPD [21]. Nicotine dependence and smoking cessation are influenced by genetic factors [14,15,22,23]. The study of Pérez-Rubio et al. [24] demonstrated that rs6313 in HTR2A increased the risk for the early onset of smoking. Nicotine dependence is strongly associated with the decreased rate of initial abstinence and the high risk of transition from lapse to relapse [25]. Gold and Lerman [26] found that nicotine dependence and smoking cessation have their respectively unique regulatory genes. Although these phenotypes may share some genetic effects, it cannot be considered that the genetic association of nicotine dependence will translate into smoking cessation or vice versa [26]. Studies have shown that CHRNs are strongly associated with nicotine dependence [14,15,21,27]. Given the limited genetic contributions in nicotine dependence and smoking cessation, more research of the genetic study of smoking cessation is needed.

We observed a significant association between the SNPs rs667282, and rs4950 and smoking status (still smoking vs. non smoking: n = 823), indicating CHRNs variants are associated with smoking cessation. Our results agree with previous studies which show CHRNs were significantly related to smoking cessation in different populations [28,29]. Moreover, a number of other studies concluded that association of CHRNs and smoking cessation is limited [30,31]. For instance, Freathy et al. [31] found that among Caucasian smokers, there was no significant relationship between CHRNA5-A3-B4 gene variation and smoking cessation treatment results. These different conclusions may come from different groups of people for each study, but further investigation is needed.

In the stratified study, the relationship between the rs667282 genotype and successful smoking cessation was more obvious in older subjects and lighter smokers. It is remarkable that the successful smoking cessation was more likely in older smokers than in younger smokers. The result agrees with study of Chen et al. [32], which reported on the CHRNA5-CHRNA3-CHRNB4 haplotypes. Compared with low-risk haplotype (H1), high-risk haplotype (H3) is associated with a later quitting age [30]. Knowing that there is a genetic role in smoking cessation, individualized treatment is particularly important. Doctors can adapt a precise program for the smokers, especially for those who have failed several attempts at cessation, based to the genotypes of CHRNA5-A3-B4.

Our study also has its limitations. First, this was a hospital-based case control study with limited numbers of samples, and selection bias or recall bias may exist that might affect the results. Secondly, COPD and smoking cessation are influenced by complex factors. In terms of genetic factors, there are multiple gene interaction, and other unobserved variables could alter the results. Finally, our results are only applicable to male smokers; a further study of female smokers is needed.

In conclusion, this study reveals that CHRNA3-A5 and CHRNB3-A6 are associated with increased successful smoking cessation in COPD smokers, and this could provide a basis for formulation of a specific smoking cessation program. As this study is a hospital-based case control study, a larger multi-center study is needed to confirm the conclusions, and more studies are needed to establish data for different ethnic populations.

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Medicine, Basic Medical Science, other