Association Between ADRB2 Genetic Polymorphisms and the Risk of Chronic Obstructive Pulmonary Disease: A Case-Control Study in a Chinese Population

Abstract

Objective:

This study was designed to investigate the association between single nucleotide polymorphisms (SNPs) of the β2-adrenergic receptor (ADRB2) gene and the risk of chronic obstructive pulmonary disease (COPD) in a Chinese population.

Methods:

From January 2010 to October 2014, 261 COPD patients were selected as the case group and 239 healthy subjects were selected as the control group. Pulmonary function tests were performed to detect forced vital capacity (FVC), 1-s forced expiratory volume (FEV₁), and FEV₁/FVC (%). rs1042711, rs1042714, and rs1042718 were selected as tagSNPs of the ADRB2 gene from the HapMap database in accordance with previous studies. The ADRB2 genotypes were established by real-time polymerase chain reaction assays using TaqMan-labeled probes. The relationships between the ADRB2 polymorphisms and COPD risk were estimated using logistic regression analyses.

Results:

The frequency of the genotypes and alleles of rs1042711 in ADRB2 showed a significant difference between the COPD and control groups (p < 0.05); compared with the CC genotype, the non-CC genotypes showed an increased COPD risk (p = 0.002). Compared with the CC haplotype, the TG haplotype increased COPD risk, while the CG haplotype reduced COPD risk for normal individuals. Compared with the CC genotype, the TT genotype showed significantly lower FEV₁ and FEV₁/FVC (p = 0.022, p = 0.0191, respectively). Both the TC and TG haplotypes showed lower FEV₁ and FEV₁/FVC in comparison with the CC haplotype (both p < 0.05). The results of logistic regression analysis showed that rs1042711 of ADRB2 and smoking history were associated with COPD risk (both p < 0.05).

Conclusion:

It is indicated that the TT genotype of rs1042711 and smoking pack years are both risk factors for COPD.

Introduction

Chronic obstructive pulmonary disease (COPD) is a prevalent disease caused by respiratory airflow limitation and characterized by airway inflammation (Ford et al., 2013).This disease may develop dyspnea and oxygenation impairment thus contributing great burden to patients worldwide (Landis et al., 2014).The mortality of COPD ranges from 3 to 111 deaths per 100,000 persons according to previous report (Rycroft et al., 2012). In recent years, mortality due to COPD has been elevating rapidly in women than that in men (Alfageme et al., 2010). Risk factors for COPD development include host factors and environmental factors (Brusselle et al., 2011). Environmental factors include air pollution and chemical exposure, while host factors include α-1antitrypsin, excess deposition of extracellular matrix, and metabolic imbalance (Foreman et al., 2012; Gan et al., 2013). As a polygenetic disease, the pathogenesis of COPD has been investigated by numerous researchers through a molecular mechanism containing adrenergic receptor (Kume et al., 2015).

According to its binding force to the epinephrine (EPI), norepinephrine (NE), and isoprenaline (ISP), adrenergic receptors are classified into α class and β subtypes (Lefkowitz and Caron, 1987). β2-adrenergic receptor (ADRB2) is a G protein-coupled transmembrane receptor that extensively exists in bronchial epithelium cells, bronchial smooth muscle cells, alveolar wall, as well as in immune cells such as macrophages and mast cells. The single nucleotide polymorphism (SNP) rs1042711 is located in the short open reading frame of ADRB2 gene, termed the 50 leader cistron; it causes missense mutation, which changes wild-type amino acid cysteine into arginine at the 19th position of the polypeptide, altering ADRB2 protein expressions and functions (Saadi et al., 2013). It is demonstrated that pharmacological targeting of the ADRB2 receptor such as β agonists and the ophylline could be used as a therapeutic approach to fight against the development of COPD (Thomsen et al., 2012; Hizawa, 2013). Several researches focusing on SNP rs1042713 and rs1042714 have discovered that polymorphism of ADRB2 was related to the progress of COPD (Bleecker et al., 2012; Wang et al., 2015). However, whether and how polymorphisms of ADRB2 are involved in the development of COPD remain controversial. Thus, this study was conducted to investigate the associations between three SNPs of ADRB2, namely rs1042711, rs1042714, and rs1042718, and the risk of COPD in a Chinese population.

Materials and Methods

Ethical statements

The study was approved by the Ethics Department of Linyi People's Hospital. Written informed consent was obtained from each participant.

Subjects

A total of 261 COPD patients (172 males and 89 females) undergoing treatment in Linyi People's Hospital from January 2010 to October 2014 were selected as the COPD group, aged between 36 and 93 years. No blood relationship was found in the COPD group. A total of 239 healthy smokers (146 males and 93 females) who had physical examination in Linyi People's Hospital were included as the control group, aged between 35 and 92 years. All healthy controls had no clinical history of chronic cough, expectoration, and shortness of breath. Besides, chest X-ray, computed tomography (CT), pulmonary function test, and forced expiratory volume in 1 s/forced vital capacity (FEV₁/FVC) >70% further confirmed that they did not have COPD.

Patients in the COPD group were diagnosed according to the guidelines of the Global Initiative for Chronic Obstructive Lung Disease (Vestbo et al., 2013): (1) history of exposure to risk factors: cigarette smoking (environmental cigarette smoke exposure included), occupational dust and chemical agent exposure, and air pollution; (2) history of chronic cough, expectoration, and shortness of breath; (3) presence of incomplete reversible airflow limitation: incomplete reversible airflow limitation could be confirmed with FEV₁/FVC <70% after usage of bronchodilator; and (4) signs of chronic bronchitis, emphysema, or pulmonary heart disease shown in chest X-ray or CT images.

Pulmonary function test

Pulmonary function detector (Yeager, Germany) was applied to detect the basal lung volume of the subjects. The FVC, FEV₁, and FEV₁/FVC (%) values were measured before and after usage of 200 μg salbutamol (Glaxo, United Kingdom) bronchodilators. All the detected values were used for further statistical analysis.

Blood sample collection and DNA extraction

Peripheral vein blood (5 mL) of the included subjects was collected, mixed with anticoagulant ethylenediaminetetraacetic acid, and then stored at −80°C for further use. DNA samples were extracted by using the DNA extraction kit (Promega Corporation, Madison, WI). Genotypes were detected by following the instructions of the manufacturer.

tgSNP selection

According to the data of minor allele frequency (≥0.03) of Han people in Beijing in public HapMap database and previous article, rs1042711, rs1042714, and rs1042718 ofADRB2 were selected as tagSNPs that may affect the development of ADRB2 gene.

TaqMan SNP genotyping assay

Genotypes were detected by a real-time polymerase chain reaction (PCR) assay using a TaqMan-labeled probe. The sequences of probes and primers are shown in Table 1 (Takara Holdings, Inc., Kyoto, Japan).

Table 1.

The Primers and Probes of Single Nucleotide Polymorphism rs1042711, rs1042714, and rs1042718 in ADRB2 Gene

SNP	Forward primer	Reverse primer	FAM	HEX
rs1042711	5′-ACCACAGCCGCTGAATGAG-3′	5′-CATTGGGTGCCAGCAAGAA-3′	TCCGCCCGCTGAG-GMB	TCCGCCTGCTGAGG-MGB
rs1042714	5′-GAACGGCAGCGCCTTCT-3′	5′-AGGACGATGAGAGACATGACGAT-3′	TCACGCAGGAAAG-MGB	TCACGCAGCAAAG-MGB
rs1042718	5′-TTCTTGCCCATTCAGATGCA-3′	5′-TCTCATTGGCATAGCAGTTGATG-3′	TGGTACCGGGCCAC-MGB	TGGTACAGGGCCAC-MGB

SNP, single nucleotide polymorphism.

Dilution of primers and probes: the samples were centrifuged for 5 min at 12,000 rpm. An appropriate amount of ddH₂O₂ was added to the samples and was shaken for 5 min. The probes were diluted to 10 pmol/μL and the primers were diluted to 20 pmol/μL. PCR system (10 μL) included 5 μL 2× HotTaq^@ PCR mix, 0.45 μL forward primer (20 pmol/μL), 0.45 μL reverse primer (20 pmol/μL), 0.25 μL FAM probe (10 pmol/μL), 0.25 μL HEX probe (10 pmol/μL), 1 μL DNA, and 6 μL ddH₂O₂. PCR conditions (ABI7500 PCR System) were as follows: (1) preamplification fluorescent signal reading (ADpre-read); (2) amplification conditions (40 cycles altogether): predegeneration at 95°C for 2 min, degeneration at 94°C for 15 s, annealing at 60°C for 45 s, and annealing at 72°C for 45 s; (3) postamplification fluorescent signal reading (AD postread); and (4) result analysis: ABISDS1.4 software was used to determine the genotype of the prepared samples (wild-type homozygote, mutation type, or heterozygote).

Statistical analysis

Statistical analysis was performed using SPSS 21.0 (SPSS Company, Chicago IL). Hardy-Weinberg equilibrium was used to test whether SNPs of ADRB2 would reach genetic equilibrium by equating allele frequencies of control and COPD groups. Comparison of allele frequency distribution between the COPD and control groups was conducted using χ² test. The measurement of data was presented using mean ± standard deviation. Differences between two groups were compared by t-test. Association with genotypes was expressed as an odds ratio (OR) and 95% credibility interval (CI). Haplotype was analyzed using SHEsis software. The relationship between ADRB2 polymorphisms and COPD risk was compared using logistic regression analysis. p < 0.05 was considered significant.

Results

Baseline characteristics of the COPD group and control group

The baseline characteristics and pulmonary function indices are shown in Table 2. FEV₁%Pred and FEV₁/FVC in the COPD group were significantly lower than those in the control group (both p < 0.05), while smoking amount was higher in the COPD group than in the control group (p < 0.05). No significant difference was found in age, gender, and body mass index between the COPD and control groups (all p > 0.05).

Table 2.

Baseline Characteristics of Chronic Obstructive Pulmonary Disease and the Control Group

Characteristic	COPD group (n = 261)	Control group (n = 239)	p
Age (years)	63.17 ± 7.95	61.77 ± 8.07	0.051
Gender			0.266
Male	172	146
Female	89	93
BMI	24.23 ± 2.80	24.09 ± 3.34	0.611
Smoking amount (package/year)	27.15 ± 12.89	22.90 ± 12.26	<0.001
FEV₁/FVC%	51.86 ± 11.63	83.54 ± 8.68	<0.001
FEV₁/Pre%	52.99 ± 15.48	91.22 ± 10.90	<0.001

BMI, body mass index; COPD, chronic obstructive pulmonary disease; FEV₁/FVC, forced expiratory volume in 1 s/forced vital capacity.

Genotype distribution of ADRB2 and COPD risk in the COPD group and control group

The genotype frequencies and allele distributions of SNPs rs1042711, rs1042714, and rs1042718 in ADRB2 of COPD and control groups were accorded with the Hardy-Weinberg equilibrium (all p > 0.05), indicating that the cases are representative. The distributions of rs1042711 genotype and allele in the COPD and control groups were significantly different (both p < 0.05). Compared with allele C, allele T of rs1042711 showed increased COPD risk (OR = 2.259, 95% CI = 1.552-3.290, p = 0.000). Compared with CC genotype, non-CC genotypes of rs1042711 elevated COPD risk (OR = 7.449, 95% CI = 1.663-33.380, p = 0.002). However, genotype and allele frequency of rs1042714 and rs1042718 was not significantly different between the two groups (both p > 0.05) (Table 3).

Table 3.

Genotype Distribution of rs1042711, rs1042714, rs1042718 in Chronic Obstructive Pulmonary Disease and the Control Group

SNP	Genotype	COPD group (n = 261) (%)	Control group (n = 239) (%)	p	OR (95% CI)
rs1042711	CC	2 (0.77)	13 (5.44)
	CT	44 (16.86)	63 (26.36)	0.047	3.084 (0.832-11.430)
	TT	215 (82.37)	163 (68.20)	0.001	4.266 (1.170-15.550)
	CT + TT	46 (99.23)	226 (94.56)	0.002	7.449 (1.663-33.380)
	C	474 (9.20)	89 (18.62)
	T	48 (90.820)	389 (81.38)	<0.001	2.259 (1.552-3.290)
rs1042714	CC	204 (78.16)	192 (80.33)		1.00 (Ref)
	CG	53 (20.31)	44 (18.41)	0.581	1.134 (0.726-1.770)
	GG	4 (1.53)	3 (1.26)	0.768	1.255 (0.277-5.682)
	CG + GG	57 (21.84)	47 (19.67)	0.549	1.141 (0.740-1.761)
	C	461 (88.31)	428 (89.54)
	G	61 (11.69)	50 (10.46)	0.538	1.133 (0.762-1.684)
rs1042718	CC	126 (48.28)	109 (45.61)		1.00 (Ref)
	CA	108 (41.38)	107 (44.77)	0.473	0.873 (0.603-1.265)
	AA	27 (10.34)	23 (9.62)	0.961	1.016 (0.550-1.874)
	CA + AA	135 (51.72)	130 (54.39)	0.550	0.898 (0.632-1.277)
	C	360 (68.97)	325 (67.99)		1.00 (Ref)
	A	162 (31.03)	153 (32.01)	0.741	0.956 (0.732-1.249)

CI, credibility interval; OR, odds ratio.

Linkage disequilibrium analysis of SNPs of ADRB2 gene

Linkage disequilibrium analysis of SNPs rs1042711, rs1042714, and rs1042718 in ADRB2 was performed using Haploview. As shown in Figure 1, both rs1042711 and rs1042714 presented linkage disequilibrium to some extent (r² = 0.47), while neither rs1042718 and rs1042711 nor rs1042718 and rs1042714 showed linkage disequilibrium.

FIG. 1.

Linkage disequilibrium analysis of SNPs in ADRB2 gene. SNP, single nucleotide polymorphism.

Haplotype analysis of ADRB2 polymorphisms in the COPD group and control group

Haplotype analysis of SNPs rs1042711 and rs1042714 was performed using SHEsis software. Four haplotypes of rs1042711 and rs1042714, CC, TC, TG, and CG were analyzed. As shown in Table 4, compared with CC haplotype, TG haplotype increased COPD risk (OR = 2.096, 95% CI = 1.172-3.747), while CG haplotype reduced COPD risk (OR = 0.313, 95% CI = 0.097-1.002) for healthy individuals.

Table 4.

Distributions of Haplotypes of rs1042711 and rs1042714 in ADRB2 Gene in Chronic Obstructive Pulmonary Disease and the Control Group

Haplotype	COPD group (%)	Control group (%)	χ²	p	OR (95% CI)
CC	44 (8.43)	55 (11.51)			1.00 (Ref)
TC	417 (79.89)	373 (78.03)	2.451	0.117	1.40 (0.9187-2.128)
TG	57 (10.92)	34 (7.11)	6.303	0.012	2.10 (1.172-3.747)
CG	4 (0.77)	16 (3.35)	1.033	0.042	0.31 (0.097-1.002)

Relationship between genotypes and haplotypes of ADRB2 and lung function

A significant difference was found in rs1042711 genotype frequency and pulmonary function of COPD patients (p < 0.05). Compared with patients carrying CC genotype, those with TT genotype showed significantly lower values of FEV₁ and FEV₁/FVC (p = 0.022, p = 0.0191, respectively), suggesting that COPD patients with TT genotype had a reduced pulmonary function. Also, COPD patients with TC or TG haplotype of rs1042711 showed lower FEV₁ and FEV₁/FVC when compared with those carrying CC haplotype of rs1042711 (both p < 0.05). Frequency of rs1042714 and rs1042718 genotypes was not associated with pulmonary function of COPD patients (both p > 0.05) (Table 5).

Table 5.

Relationship Between Genotypes and Haplotypes in ADRB2 and Pulmonary Function Indices

Genotype/haplotype	Cases (%)	FEV₁/pre%	p	FEV₁/FVC%	p
rs1042711
CC	2 (0.77)	67.85 ± 13.22		74.35 ± 4.35
CT	44 (16.86)	60.90 ± 10.25	0.357	66.17 ± 10.25	0.379
TT	215 (82.38)	49.86 ± 10.92	0.022	50.09 ± 0.097	0.019
rs1042714
CC	204 (78.16)	2.52 ± 11.46		53.78 ± 11.466
CG	53 (20.31)	49.21 ± 11.85	0.064	50.47 ± 0.475	0.064
GG	4 (1.53)	53.40 ± 15.49	0.880	45.90 ± 15.49	0.192
rs1042718
CC	126 (48.28)	53.07 ± 11.73		53.95 ± 11.73
CA	108 (41.38)	50.99 ± 11.63	0.176	53.06 ± 3.063	0.664
AA	27 (10.34)	49.69 ± 10.91	0.171	48.19 ± 10.91	0.075
Haplotype
CC	44 (8.43)	69.30 ± 10.91		69.82 ± 11.34
TC	417 (79.89)	59.73 ± 8.13	<0.001	58.47 ± 9.26	<0.001
TG	57 (10.92)	50.11 ± 8.00	<0.001	46.65 ± 8.96	<0.001
CG	4 (0.77)	66.83 ± 10.67	0.649	67.03 ± 9.89	0.675

FEV₁/FVC, forced expiratory volume in 1 s/forced vital capacity.

Logistic regression analysis of risk factors for COPD patients

With COPD as dependent variable, logistic regression analysis revealed that SNP rs1042711 in ADRB2 and smoking history were associated with COPD risk (both p < 0.05). rs1042714, rs1042718, and age were not associated with COPD risk (all p > 0.05) (Table 6).

Table 6.

Logistic Regression Analysis of Risk Factors for Chronic Obstructive Pulmonary Disease Patients

							95% CI
Factor	B	SE	Wals	df	Significance	Exp (B)	Low limit	Upper limit
rs1042711 T/T	0.612	0.247	6.123	1	0.013	1.845	1.136	2.997
rs1042714 C/C	−0.524	0.282	3.457	1	0.063	0.592	0.341	1.029
rs1042718 C/C	0.068	0.218	0.096	1	0.756	1.07	0.698	1.641
Smoking amount	0.029	0.01	8.106	1	0.004	1.029	1.009	1.05
Age	−0.001	0.015	0.009	1	0.923	0.999	0.97	1.028
BMI	−0.032	0.035	0.824	1	0.364	0.969	0.905	1.037

Exp, exponent; SE, standard error.

Discussion

This study investigated the relationship between SNPs of ADRB2, rs1042711, rs1042714, and rs1042718, and COPD risk. Interestingly, our findings provided evidence that TT genotype and haplotypes of TG and TC of rs1042711 in ADRB2 may be related to pulmonary function in COPD patients.

COPD, an incurable disease, is generally considered as the fourth leading cause of death around the world, mainly featured as abnormal tissue repair, thus causing small airway fibrosis or emphysema (Brandsma et al., 2015). ADRB2 is located in chromosome 5q31-q33, with a length about 1.8 kb, containing nine SNP sites at 5′ initiation codon. ADRB2 gene polymorphism participates in the regulation of cilia wave, mucous secretion, and inflammatory factor release in the respiratory tract, thus affecting bronchial expansion, secretion clearance, and airway protection, directly influences COPD development (Munakata et al., 2006). The role of ADRB2 gene polymorphisms in COPD has been repeatedly explored with varied findings. ADRB2 Gly16Arg (rs1042713) and Gln27Glu (rs1042714) were found to have no meaningful effect on COPD in a case-control study, which is further supported by another proving that rs1042713 is not associated with therapeutic response in COPD patients (Brogger et al., 2006; Bleecker et al., 2012). However, another study showed evidence that Gly16 allele of ADRB2 predisposes to COPD development (Vacca. et al., 2009).

Results of this study revealed that the distribution of genotypes and alleles of SNP rs1042711 in ADRB2 was significantly different between the COPD and control groups. Moreover, it was discovered that in SNP rs1042711 of ADRB2, T allele may increase the risk of COPD compared with C allele. Mutation of SNP rs1042711 is believed to affect protein structure and functions by altering amino acid cysteine (Saadi et al., 2013). Similar to our findings, Fu et al. (2011) compared the gene alterations of COPD patients and healthy controls in the southwest of China, and found that rs1042711 in ADRB2 was an independent risk factor for asthma.

Logistic regression analysis further confirmed that TT genotype of rs1042711 in ADRB2 and smoking amount are risk factors for COPD. The 5′-SNP sites in ADRB2 could combine with transcription factors and regulate the activity of ADRB2 promoter, thus affecting the expression and function of ADRB2 (Saadi et al., 2013). Also, rs1042711 polymorphism in ADRB2 has been reported to play an important part in regulating the expression of ADRB2, and rs1042711 is an independent factor for decreasing FEV₁% and FEV₁/FVC in Chinese asthma patients (Fu et al., 2011). Tian et al. (2015) reported that variations of ADRB2 significantly affect the susceptibility to childhood asthma. This was supported by Martinez-Aguilar et al. (2015) who verified that ADRB2 haplotypes are risk factors for asthma in pediatric patients. Despite studies exploring the relationship between ADRB2 polymorphism and COPD development, no evidence has shown the function of rs1042711 TT genotype in COPD development. Based on previous evidences and our results, it is hypothesized that TT genotype of rs1042711 could change amino acid sequence and protein function, thus indirectly affecting the progress of COPD. At the same time, cigarette smoking has been well established to be the single most important risk factor for COPD (Cunningham et al., 2015), which strongly supported our result that smoking amount increases the possibility of COPD development.

In conclusion, the current study provides strong evidence that TT genotype and TG and TC haplotypes of rs1042711 in ADRB2 are related to pulmonary function in COPD patients. Furthermore, this study ascertained that TT genotype of rs1042711 in ADRB2 and smoking amount are risk factors for COPD development, providing a theoretical foundation for molecular mechanisms of COPD risk. However, the sample size in this study is relatively small, coupling with the heterogeneity of selected patients, which may influence our results. Further evidence is needed to confirm our findings.

Footnotes

Acknowledgment

We are grateful for the helpful comments on this article received from our reviewers.

Author Disclosure Statement

No competing financial interests exist.

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