The Study of the Influence of IL5RA Variants on Chronic Obstructive Pulmonary Disease

Abstract

Chronic obstructive pulmonary disease (COPD) is a complex disease, and its pathogenesis is influenced by genetic factors. This study aimed to evaluate the role of IL5RA genetic variation in the risk of COPD. In this study, 498 patients with COPD and 498 normal controls were recruited. Subsequently, five SNPs (rs3804795, rs2290610, rs13097407, rs334782, and rs3856850) in the IL5RA gene were genotyped. Logistic analysis examined the association of five single nucleotide polymorphisms (SNPs) in IL5RA with the risk of COPD under various genetic models. Furthermore, the association between IL5RA and susceptibility to COPD was comprehensively analyzed with stratification based on age, sex, smoking, and alcohol consumption. Our study showed that IL5RA rs13097407 reduced susceptibility to COPD (OR = 0.43, p < 0.001, p (FDR)< 0.001). On the other hand, rs3856850 was associated with an increased risk of COPD (OR = 1.71, p = 0.002, p (FDR) = 0.002). Interestingly, the effect of IL5RA SNPs on susceptibility to COPD was found to be influenced by factors such as sex and smoking. IL5RA gene variants were significantly associated with susceptibility to COPD.

Keywords:

• A case-control study
• chronic obstructive pulmonary disease (COPD)
• IL5RA
• single nucleotide polymorphism (SNP)
• susceptibility
• genetic variation

Introduction

Chronic obstructive pulmonary disease (COPD) has emerged as a significant global health issue due to its high prevalence, increasing incidence, and substantial economic impact [1]. Typically, COPD is characterized by difficulty breathing, coughing, and/or sputum production, with acute exacerbations in some patients [2]. The diagnosis of COPD is based on clinical symptoms and a ratio of post-bronchodilator forced expiratory volume in 1 s to forced expiratory vital capacity (FEV1/FVC) that is less than 0.70 [3]. COPD is caused by inhaling harmful particles, so smoking is the most common risk factor for developing COPD [4, 5]. As a complex disease, COPD is also influenced by a combination of genetic and environmental factors [6]. Genome-wide association studies (GWAS) analysis revealed that sex was associated with specific genetic risk factors for susceptibility to COPD [7]. An unhealthy diet may increase oxidative and bronchial inflammation [8]. Nonsmoking-induced COPD may also be influenced by air pollution, asthma, and infectious diseases [9]. COPD consists of many different pathophysiological abnormalities and significant individual differences, resulting in heterogeneity in the effectiveness of drug therapy [10]. US Food and Drug Administration (FDA)-approved drugs are often supported by genetic associations [6]. Therefore, personalized treatments based on genetic markers of COPD may have high clinical efficacy.

The interleukin (IL)-5 receptor consists of an IL5-specific chain, and the β chain is shared with the IL-3 and granulocyte-macrophage colony-stimulating factor (GM-CSF) receptors [11]. It has been reported that IL-5/IL-5R is involved in the processes of eosinophil proliferation, differentiation, and recruitment [12]. Among them, transmembrane IL-5Rα is the rate-limiting component of the IL-5 signaling pathway [13]. Clinical studies have discovered that immune-related genes IL5RA, ALOX15, and PDE4D affect eosinophil levels in COPD patients [14]. In the late stages of COPD development, drugs that inhibit interleukin-5 or its receptors may hold the most promise for enhancing eosinophilic inflammation [15]. Benralizumab, a monoclonal antibody targeting the IL-5 receptor, improves airway inflammation in asthma caused by eosinophils [16]. We speculate that IL5RA may play a crucial role in the occurrence and development of COPD. Therefore, this study preliminarily explored its genetic value in susceptibility to COPD.

In this study, the Logistic regression method was applied to explore the correlation between five single nucleotide polymorphisms (SNPs) in IL5RA (rs3804795, rs2290610, rs13097407, rs334782 and rs3856850) and COPD. In correlation analysis, odds ratios (ORs) and 95% confidence intervals (95% CIs) were used as analysis indexes, along with p value for statistical significance. Associations between five SNPs in IL5RA and susceptibility to COPD, stratified by age, sex, smoking, and alcohol consumption, were assessed using the same method. Furthermore, bioinformatics analysis was applied to explore IL5RA-related targets and pathway mechanisms. The purpose of this study is to provide genetic data support for the clinical diagnosis and treatment biomarkers of COPD, which can contribute to personalized treatment of COPD.

Methods

Study participants

A total of 996 adult subjects, consisting of 498 COPD patients and 498 normal controls, were recruited from the Hainan affiliated Hospital of Hainan Medical University. Among them, all participants belonged to the Han Chinese population in order to exclude the interference of ethnic factors [17]. Age, sex, smoking, alcohol consumption data, and other clinical characteristics of all patients were collected based on epidemiological questionnaires. The diagnosis of COPD is based on clinical examination and spirometry, using a fixed forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) ratio of less than 70% and an FEV1 of less than 80% as the index [18], according to the criteria set by the Global Initiative for Chronic Obstructive Lung Disease criteria [19]. Patients with lung diseases such as pneumonia, lung cancer, bronchial asthma, or severe endocrine organ damage were excluded from the case group [20]. The control group consisted of individuals with normal lung capacity who were selected from the health examination center of the same hospital [21]. Participants with respiratory diseases, respiratory disorders, and those unable to perform lung function tests were excluded [19]. The study was approved by the Ethics Committee of Hainan affiliated Hospital of Hainan Medical University before it began.

SNPs selection and genotyping

In this study, the five IL5RA SNPs (rs3804795, rs2290610, rs13097407, rs334782, and rs3856850) were selected for follow-up studies, and the selection criteria were as follow. First, we obtained the IL5RA’s physical position on chromosome 3 (location: 3:3066324-3126613) using the human e!GRCh37 database. In the VCF to PED Converter window, we entered the gene location, selected the Chinese Han in the Southern (CHS) population, and downloaded the ped and info files of IL5RA SNPs. Then, a total of 312 SNPs were obtained. Second, the tag-SNPs were further selected through the Haploview software with minor allele frequency (MAF) > 0.05, min genotype > 0.75, r² < 0.8, and Hardy-Weinberg equilibrium (HWE) > 0.05. Third, the call rate for each SNP was greater than 0.95. Finally, five SNPs including rs3804795, rs2290610, rs13097407, rs334782, and rs3856850 were selected for investigation. DNA was extracted and purified from blood samples of all recruiters. The detection and genotyping of the rs3804795 T > C, rs2290610 T > C, rs13097407 A > G, rs334782 T > C and rs3856850 A > G polymorphisms were performed using the Agena Mass Array and Agena Typer 4.0. Simultaneously, 5% of the DNA samples were randomly selected for repeat genotyping, which resulted in a genotyping agreement of greater than 99%. The primers for the candidate SNPs are listed in Supplementary Table 1.

Statistical analysis

The differences in epidemiological investigation data between the control and case groups were evaluated using the chi-square (χ²) test and Student’s t test. Prior to genetic association analysis, the values of Akaike information criterion (AIC) and Bayesian information criterion (BIC) were calculated to select the best one in all genetic models for each SNP by SNPStats online software (https://www.snpstats.net/start.htm?q=snpstats/start.htm). The best genetic model for each SNP was the model with a lowest AIC and BIC. Logistic regression was performed to analyze the association analysis between IL5RA SNPs with COPD, with adjusting for sex, age, smoking, and drinking. The associations were determined by calculating the odds ratio (OR), 95% confidence interval (CI), and statistical p value. The roles of IL5RA polymorphisms in COPD were further investigated after stratified by age, sex, smoking, and drinking status. Considering the age difference between the cases and controls, age was adjusted in the stratified models. The Benjamini and Hochberg’s false discovery rate (FDR) method was used to correct for multiple testing correction. In addition, the interaction between rs3804795, rs2290610, rs13097407, rs334782, and rs3856850 in IL5RA was analyzed using the multi-factor dimension reduction (MDR) software. The p < 0.05 was considered to indicate a significant difference. The possible functions of the five selected SNPs were predicted by using HaploReg v4.2 online software (https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php). In order to further explore the functions and mechanisms related to IL5RA in COPD, we utilized the STRING (https://cn.string-db.org/) and oebiotech (https://cloud.oebiotech.cn/task/) databases for analysis.

Results

Characteristics of the participants

The basic characteristics of the study participants are presented in Table 1. There were 996 adult subjects enrolled in this study, with 498 in the case group and 498 in the control group. The average age of COPD patients and healthy individuals was 70.89 ± 10.19 years and 65.86 ± 5.56 years, respectively. There was a significant difference in age between the case and control groups (p < 0.001). There were no significant differences in sex (p = 0.690) and drinking (p = 0.800) between the two groups.

Table 1. Characteristics of COPD patients and controls.

Variables	Cases (N = 498)	Controls (N = 498)	p value
Age, year	70.89 ± 10.19	65.86 ± 5.56	< 0.001^a
≤68	187(37.55%)	372(74.70%)	< 0.001^b
>68	311(62.45%)	126(25.30%)
Sex			0.690^b
Male	328(65.86%)	322(64.66%)
Female	170(34.14%)	176(35.34%)
Smoking
Current	106(21.3%)	221(44.4%)
Former	134(26.9%)	0
Never	258(51.8%)	277(55.6%)
Smoking pack year	33.44 ± 15.56
Drinking			0.800^b
Yes	251(50.40%)	255(51.20%)
No	247(49.60%)	243(48.80%)
BMI (kg/m^2)	23.1 ± 3.12	25.2 ± 3.21	< 0.001^a
≥24	438(87.95%)	152(30.52%)
<24	47(9.44%)	152(30.52%)
missing	13(2.61%)	194(38.96%)
The history of exacerbation (yes/no/unavailable), n	171/310/17
COPD with cough (yes/no/unavailable), n	475/12/11
COPD with expectoration (yes/no/unavailable), n	437/50/11
COPD with wheezing (yes/no/unavailable), n	153/334/11
COPD with dyspnea (yes/no/unavailable), n	65/422/11
COPD with chest distress (yes/no/unavailable), n	146/341/11
History of asthma (yes/no/unavailable), n	142/336/20
FVC (L)	2.18 ± 0.69
FEV1 (L)	1.35 ± 0.45
FEV1/FVC	62.21 ± 7.41
Gold Group, n (%)
A	73(14.7%)
B	172(34.5%)
C	200(40.2%)
D	53(10.6%)

COPD: Chronic obstructive pulmonary disease; BMI: body mass index; FVC: forced vital capacity; FEV1: forced the first second of expiratory volume.

^a p value were calculated from an independent sample t-test.

^b p value were calculated from a two-sided χ² test.

p < 0.05 indicates statistical significance.

Candidate SNPs information

The chromosome, physical position, function, MAF of cases and controls, and HWE pvalue of the five SNPs (rs3804795, rs2290610, rs13097407, rs334782, and rs3856850) in IL5RA are presented in Table 2. These five SNPs in IL5RA are located on chromosome 3, with MAF greater than 0.05, and all SNPs in the case group follow HWE (p > 0.05). Among them, rs3804795, rs13097407, rs334782 and rs3856850 are intron variations, while rs2290610 is a missense variation. the five selected SNPs (rs3804795, rs2290610, rs13097407, rs334782, and rs3856850) in IL5RA can be used for correlation analysis.

Table 2. Basic information of SNPs in IL5RA gene.

SNP	Chromosome position	Function	Allele (A/B)	MAF		HWE p	HaploReg v4.2
				Case	Control
rs3804795	3: 3088961	Intron Variant	C/T	0.761	0.772	0.899	Promoter histone marks, Enhancer histone marks, DNAse, Motifs changed, NHGRI/EBI GWAS hits, GRASP QTL hits
rs2290610	3: 3098273	Missense Variant	C/T	0.543	0.577	0.233	Enhancer histone marks, Motifs changed, GRASP QTL hits
rs13097407	3: 3102835	Intron Variant	G/A	0.968	0.928	0.999	Promoter histone marks, Enhancer histone marks, Proteins bound, Motifs changed
rs334782	3: 3106774	Intron Variant	C/T	0.776	0.784	0.691	Enhancer histone marks, Motifs changed
rs3856850	3: 3109662	Intron Variant	G/A	0.542	0.590	0.064	Promoter histone marks, Enhancer histone marks, DNAse, Proteins bound, Motifs changed

NP: single nucleotide polymorphism; A: minor; B: major; MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium.

Overall susceptibility

Logistic analysis was employed to demonstrate the correlation between IL5RA genetic variants and the risk of COPD (Table 3), with significant findings depicted in Figure 1A. Rs13097407 in IL5RA was associated to a decreased susceptibility to COPD under allele (OR = 0.43, 95% CI 0.28–0.65, p < 0.001, p (FDR)< 0.001), and dominant (OR = 0.40, 95% CI 0.25–0.64, p < 0.001, p (FDR)< 0.001) models. Conversely, rs3856850 significantly increased the risk of COPD under allele (OR = 1.22, 95% CI 1.02–1.45, p = 0.034, p (FDR) = 0.075), and recessive (OR = 1.71, 95% CI 1.22–2.41, p = 0.002, p (FDR) = 0.006) models. In summary, rs13097407 decreased the risk of developing COPD, whereas rs3856850 increased the risk of COPD.

Figure 1. Association of five SNPs in IL5RA with COPD risk. A: Significant overall analysis results. B: SNP-SNP interaction dendrogram of MDR analysis. C: Fruchterman-reingold of MDR analysis (The closer to red the stronger the synergy, the closer to blue the more redundancy.).

Table 3. Associations between SNPs in IL5RA and chronic obstructive pulmonary disease (COPD).

SNP	Model	Genotype	Without adjusted			With adjusted
			OR (95% CI)	p^1	p (FDR)	OR (95% CI)	p^2	p (FDR)
rs3804795	Allele	T				1.00
		C				1.06 (0.86–1.31)	0.596	0.721
	Recessive	TT-CT	1.00			1.00
		CC	1.25 (0.73–2.16)	0.414	0.414	1.45 (0.82–2.56)	0.197	0.197
rs2290610	Allele	T				1.00
		C				1.15 (0.96–1.37)	0.136	0.219
	Recessive	TT-CT	1.00			1.00
		CC	1.41 (1.03–1.94)	0.034*	0.051	1.39 (0.99–1.94)	0.053	0.079
rs13097407	Allele	A				1.00
		G				0.43 (0.28–0.65)	<0.001**	<0.001**
	Dominant	AA	1.00			1.00
		AG-GG	0.39 (0.25–0.61)	<0.001**	<0.001**	0.40 (0.25–0.64)	<0.001**	<0.001**
rs334782	Allele	T				1.00
		C				1.05 (0.85–1.30)	0.705	0.705
	Log-additive	/	1.05 (0.85–1.30)	0.661	0.397	1.12 (0.90–1.41)	0.312	0.234
rs3856850	Allele	A				1.000
		G				1.22 (1.02–1.45)	0.034*	0.075
	Recessive	AA-AG	1.00			1.00
		GG	1.73 (1.25–2.39)	<0.001**	0.003	1.71 (1.22–2.41)	0.002**	0.006

SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval; FDR: false discovery rate.

p value were calculated by logistic regression analysis. p¹ was without adjustment. p² was adjusted by age, sex, smoking, and drinking status.

Bold text and *p < 0.05 or **p < 0.01 represent statistical significance.

Stratified susceptibility

The association of IL5RA rs13097407 and COPD susceptibility under age-, sex-, smoking-, and alcohol consumption-based stratification is shown in Table 4. The average age of the participants is 68 years old in our study, thus we stratified by 68 years. IL5RA rs13097407 significantly decreased the risk of COPD in various genetic models among different subgroups, including individuals aged> 68 years (dominant: OR = 0.44, 95% CI 0.20–0.96, p = 0.038, p (FDR) = 0.115), participants aged≤ 68 years (allele: OR = 0.40, 95% CI 0.21–0.75, p = 0.003, p (FDR) = 0.018; dominant: OR = 0.35, 95% CI 0.17–0.70, p = 0.003, p (FDR) = 0.009), in males (allele: OR = 0.54, 95% CI 0.33–0.88, p = 0.015, p (FDR) = 0.061; dominant: OR = 0.49, 95% CI 0.28–0.84, p = 0.010, p (FDR) = 0.030) and females (allele: OR = 0.23, 95% CI 0.09–0.55, p < 0.001, p (FDR) = 0.002; dominant: OR = 0.23, 95% CI 0.09–0.59, p = 0.002, p (FDR) = 0.007), individual with smoking (allele: OR = 0.54, 95% CI 0.31–0.95, p = 0.038, p (FDR) = 0.155; dominant: OR = 0.41, 95% CI 0.22–0.79, p = 0.008, p (FDR) = 0.023) and nonsmoking (allele: OR = 0.32, 95% CI 0.16–0.61, p < 0.001, p (FDR) = 0.002; dominant: OR = 0.31, 95% CI 0.15–0.63, p = 0.001, p (FDR) = 0.004), drinkers (allele: OR = 0.43, 95% CI 0.23–0.80, p = 0.008, p (FDR) = 0.032; dominant: OR = 0.41, 95% CI 0.21–0.82, p = 0.012, p (FDR) = 0.036), and nondrinkers (allele: OR = 0.42, 95% CI 0.23–0.76, p = 0.003, p (FDR) = 0.015; dominant: OR = 0.39, 95% CI 0.21–0.74, p = 0.004, p (FDR) = 0.012). All in all, rs13097407 can decrease the susceptibility to COPD.

Table 4. Relationship between rs13097407 in IL5RA and COPD under stratification analyses.

Age			>68					≤68
SNP	Model	Genotype	Case	Control	OR (95% CI)	p	p (FDR)	Case	Control	OR (95% CI)	p	p (FDR)
rs13097407	Allele	A	602	237	1.00			362	687	1.00
		G	20	15	0.52 (0.26–1.04)	0.084	0.308	12	57	0.40 (0.21–0.75)	0.003**	0.018
	Dominant	AA	292	111	1.00			176	317	1.00
		AG-GG	19	15	0.44 (0.20–0.96)	0.038*	0.115	11	55	0.35 (0.17–0.70)	0.003**	0.009
Sex			Male					Female
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs13097407	Allele	A	630	598	1.00			334	326	1.00
		G	26	46	0.54 (0.33–0.88)	0.015*	0.061	6	26	0.23 (0.09–0.55)	<0.001**	0.002
	Dominant	AA	304	277	1.00			164	151	1.00
		AG-GG	24	45	0.49 (0.28–0.84)	0.010*	0.030	6	25	0.23 (0.09–0.59)	0.002**	0.007
Smoking			Smoking					Nonsmoking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs13097407	Allele	A	371	396	1.00			548	518	1.00
		G	20	36	0.54 (0.31–0.95)	0.038*	0.155	12	36	0.32 (0.16–0.61)	<0.001**	0.002
	Dominant	AA	200	186	1.00			268	242	1.00
		AG-GG	18	35	0.41 (0.22–0.79)	0.008**	0.023	12	35	0.31 (0.15–0.63)	0.001**	0.004
Drinking			Drinking					Non-drinking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs13097407	Allele	A	487	476	1.00			477	448	1.00
		G	15	34	0.43 (0.23–0.80)	0.008**	0.032	17	38	0.42 (0.23–0.76)	0.003**	0.015
	Dominant	AA	237	223	1.00			231	205	1.00
		AG-GG	14	32	0.41 (0.21–0.82)	0.012*	0.036	16	38	0.39 (0.21–0.74)	0.004**	0.012

SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval; FDR: false discovery rate.

p value were calculated by logistic regression analysis with adjustment for age, sex, smoking, and drinking status.

Bold text and *p < 0.05 or **p < 0.01 represent statistical significance.

Interestingly, rs3856850 was found to be associated with an increased risk of COPD across various stratifications (Table 5). In the recessive model, the risk of COPD was significantly higher in individuals with rs3856850 who were older than 68 years (OR = 1.93, 95% CI 1.06–3.53, p = 0.032, p (FDR) = 0.097) and those aged≤ 68 years (OR = 1.61, 95% CI 1.01–2.56, p = 0.045, p (FDR) = 0.136). This study explored the significant association between rs3856850 and COPD risk in males under recessive model (OR = 1.64, 95% CI 1.08–2.50, p = 0.022, p (FDR) = 0.065). Among nonsmokers, rs3856850 was found to be a risk factor for COPD under allele (OR = 1.36, 95% CI 1.08–1.73, p = 0.010, p (FDR) = 0.026) and recessive (OR = 2.26, 95% CI 1.39–3.69, p = 0.001, p (FDR) = 0.003) models. In addition, rs3856850 was identified as a risk locus for COPD susceptibility in participants with drinking, under recessive (OR = 1.98, 95% CI 1.20–3.27, p = 0.008, p (FDR) = 0.023) model. In short, rs3856850 was significantly associated with an increased risk of COPD among males, nonsmokers, and drinkers.

Table 5. Relationship between rs3856850 in IL5RA and COPD under stratification analyses.

Age			> 68					≤ 68
SNP	Model	Genotype	Case	Control	OR (95% CI)	p	p (FDR)	Case	Control	OR (95% CI)	p	p (FDR)
rs3856850	Allele	A	336	152	1.00			204	436	1.00
		G	286	100	1.29 (0.96–1.74)	0.089	0.224	170	308	1.18 (0.92–1.52)	0.196	0.326
	Recessive	AA-AG	238	109	1.00			146	316	1.00
		GG	73	17	1.93 (1.06–3.53)	0.032*	0.097	41	56	1.61 (1.01–2.56)	0.045*	0.136
Sex			Male					Female
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs3856850	Allele	A	351	376	1.00			189	212	1.00
		G	305	286	1.22 (0.98–1.52)	0.076	0.191	151	140	1.21 (0.89–1.64)	0.217	0.361
	Recessive	AA-AG	249	273	1.00			135	152	1.00
		GG	79	49	1.64 (1.08–2.50)	0.022*	0.065	35	24	1.78 (0.99–3.18)	0.053	0.159
Smoking			Smoking					Nonsmoking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs3856850	Allele	A	242	251	1.00			298	337	1.00
		G	194	191	1.05 (0.81–1.38)	0.702	0.877	262	217	1.36 (1.08–1.73)	0.010*	0.026
	Recessive	AA-AG	165	180	1.00			219	245	1.00
		GG	53	41	1.33 (0.80–2.21)	0.274	0.411	61	32	2.26 (1.39–3.69)	0.001**	0.003
Drinking			Drinking					Non-drinking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs3856850	Allele	A	277	310	1.00			263	278	1.00
		G	225	200	1.26 (0.98–1.62)	0.071	0.177	231	208	1.17 (0.91–1.51)	0.212	0.531
	Recessive	AA-AG	196	221	1.00			188	204	1.00
		GG	55	34	1.98 (1.20–3.27)	0.008**	0.023	59	39	1.53 (0.96–2.43)	0.075	0.226

SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval; FDR: false discovery rate.

pvalue were calculated by logistic regression analysis with adjustment for age, sex, smoking, and drinking status.

Bold text and *p < 0.05 or **p < 0.01 represent statistical significance.

In terms of smoking stratification, nonsmokers with rs3804795 had a higher risk in allele (OR = 1.30, 95% CI 1.02–1.65, p = 0.031, p (FDR) = 0.052) and recessive (OR = 1.85, 95% CI 1.16–2.96, p = 0.010, p (FDR) = 0.015) models (Table 6). There was no apparent correlation of rs334782 and rs3804795 with various COPD stratifications, as indicated in Supplementary Table 2 and Table 3.

Table 6. Relationship between rs2290610 in IL5RA and COPD under stratification analyses.

Age			>68					≤68
SNP	Model	Genotype	Case	Control	OR (95% CI)	p	p (FDR)	Case	Control	OR (95% CI)	p	p (FDR)
rs2290610	Allele	T	337	147	1.00			204	424	1.00
		C	285	105	1.18 (0.88–1.59)	0.263	0.439	170	314	1.13 (0.88–1.45)	0.356	0.356
	Recessive	TT-CT	241	105	1.00			148	308	1.00
		CC	70	21	1.40 (0.80–2.47)	0.240	0.240	39	61	1.36 (0.86–2.17)	0.193	0.290
Sex			Male					Female
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs2290610	Allele	T	353	360	1.00			188	211	1.00
		C	303	280	1.10 (0.89–1.37)	0.378	0.629	152	139	1.23 (0.91–1.66)	0.184	0.461
	Recessive	TT-CT	252	263	1.00			137	150	1.00
		CC	76	57	1.34 (0.89–2.02)	0.159	0.239	33	25	1.46 (0.82–2.61)	0.199	0.199
Smoking			Smoking					Nonsmoking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs2290610	Allele	T	243	243	1.00			298	328	1.00
		C	193	197	0.98 (0.75–1.28)	0.880	0.880	262	222	1.30 (1.02–1.65)	0.031*	0.052
	Recessive	TT-CT	171	176	1.00			218	237	1.00
		CC	47	44	1.11 (0.66–1.84)	0.698	0.523	62	38	1.85 (1.16–2.96)	0.010*	0.015
Drinking			Drinking					Non-drinking
SNP	Model	Genotype	Case	Control	OR (95% CI)	p		Case	Control	OR (95% CI)	p
rs2290610	Allele	T	273	293	1.00			268	278	1.00
		C	229	215	1.14 (0.89–1.47)	0.292	0.364	226	204	1.149 (0.89–1.48)	0.281	0.469
	Recessive	TT-CT	197	213	1.00			192	200	1.00
		CC	54	41	1.50 (0.93–2.41)	0.099	0.149	55	41	1.28 (0.80–2.05)	0.297	0.297

SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval; FDR: false discovery rate.

pvalue were calculated by logistic regression analysis with adjustment for age, sex, smoking, and drinking status.

Bold text and *p < 0.05 represent statistical significance.

MDR analysis of IL5RA SNPs

As shown in Table 7, the results of the MDR analysis indicated that rs3856850 was a single-locus predictive model for COPD (CVC = 6/10). The two-locus model was rs3804795 and rs3856850 (CVC = 5/10). The three-locus model included rs13097407, rs334782, and rs3856850 (CVC = 5/10). The four-locus model consisted in rs3804795, rs2290610, rs334782, and rs3856850 (CVC = 6/10). The combination of rs3804795, rs2290610, rs13097407, rs334782, and rs3856850 was the five-locus model for predicting COPD (CVC = 10/10). Therefore, the five-locus model was the best predictive model for COPD, with the perfect CVC and highest testing accuracy (0.5592). Besides, Figure 1B, C indicates that rs3804795 and rs3856850 have a positive synergistic interaction (0.39%).

Table 7. SNP–SNP interaction in IL5RA models analyzed by the MDR method.

Model	Training Bal. Acc.	Testing Bal. Acc.	CVC	OR (95% CI)	p
rs3856850	0.5435	0.5090	6/10	1.73 (1.25–2.39)	0.0009
rs3804795,rs3856850	0.5593	0.5161	5/10	1.96 (1.45–2.67)	<0.0001
rs13097407,rs334782,rs3856850	0.5775	0.5090	5/10	1.82 (1.41–2.36)	<0.0001
rs3804795,rs2290610,rs334782,rs3856850	0.5975	0.5151	6/10	2.15 (1.67–2.78)	<0.0001
rs3804795,rs2290610,rs13097407,rs334782,rs3856850	0.6199	0.5592	10/10	2.61 (2.02–3.36)	<0.0001

MDR, multifactor dimensionality reduction; Bal. Acc., balanced accuracy; CVC, cross-validation consistency; OR, odds ratio; 95% CI, 95% confidence interval.

p values were calculated using χ² tests.

Bioinformatics analysis of IL5RA

The analysis results of IL5RA-related targets and pathways are shown in Figure 2. Protein–protein interaction (Figure 2A) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis (Figure 2B, C) demonstrate that IL5RA regulates IL5 and Cytokine receptor common subunit beta (CSF2RB), which are involved in the regulation of the Janus kinase 2 (JAK2)/Signal transducer and activator of transcription 5 (STAT5A/B) pathway. What’s more, IL5RA can also regulate the tyrosine-protein phosphatase non-receptor type 11 (PTPN11)/growth factor receptor-bound protein 2 (GRB2) to activate mitogen-activated protein kinase (MAPK) pathway and phosphoinositide 3-kinase regulatory subunit 1 (PIK3R1)/protein kinase B alpha (AKT)/mammalian target of rapamycin (mTOR) pathway. It is suggested that IL5R and its related proteins may play a vital role in cell proliferation, inflammation, and apoptosis.

Figure 2. Biological function of IL5RA and its related proteins. A: Interaction diagram of IL5RA and its related proteins. B: KEGG enrichment of IL5RA and its related proteins. C: IL5RA and its related proteins are involved in the JAK/STAT signaling pathway.

Discussion

According to a report, IL5RA polymorphism affects the occurrence and development of many diseases, including asthma, leukemia, and allergic diseases. For example, genetic polymorphisms in IL5RA increase the genetic risk of asthma, which can subsequently lead to COPD [22]. IL5RA SNPs were also associated with peripheral blood eosinophil counts and tissue invasion in patients with FIP1L1-PDGFRA-positive chronic eosinophilic leukemia [23]. Moreover, a case-control study of eczema in Japanese women demonstrated that the IL5RA SNPs significantly reduced the occurrence of eczema [24]. However, the roles of IL5RA genetic polymorphisms in COPD is still unclear. Thus, our study was the first to determine the association between IL5RA polymorphisms and COPD risk. We found that IL5RA rs13097407 reduces susceptibility to COPD, while rs3856850 is a risk factor for COPD. Besides, IL5RA could regulate eosinophil counts and function, which played a role in disease development.

Rs3804795, rs13097407, rs334782, and rs3856850 are located on the intron region of IL5RA, and rs2290610 is a missense variant. Our study showed that there were no significant associations of rs3804795 and rs2290610 with COPD risk. On the contrary, a GWAS study indicated that rs3804795 was significant associated with humoral immune responses [25]. Besides, rs2290610 was a genetic risk factor for schizophrenia [26]. These differences may be influenced by the disease itself. Furthermore, we found that rs13097407 and rs3856850 were significantly associated with COPD risk. Even though the association of rs13097407 and rs3856850 with COPD risk has not been reported. FDR analysis indicated that the significant findings were worthy of observation.

Sex is an import risk factors for COPD, and males can increase risk for COPD than females [27]. When stratified by sex, we found that rs3856850 was significantly associated with an increased risk of COPD in males, but not in females, which suggested that there were sex differences in the influence of rs3856850 on COPD risk. Similarity, Jing et al. revealed that rs4731420 had strong association with an increased susceptibility to COPD in males, but not in females [28]. Besides, rs298207 could enhance COPD risk among males, but not in females [29]. Based on these findings, we can infer that the effect of suggest genetic susceptibility to COPD may be related to sex, which emphasizes the importance of considering heterogeneity when studying the relationship between genetic factors and COPD risk. Smoking is also the primary risk factor for COPD. When stratified by smoking status, it was found that rs3856850 and rs2290610 were related to an increased susceptibility to COPD among nonsmokers, but not in smokers. Similar to our results, Tang et al. showed that rs15783 and rs1800517 had a reduced risk in COPD with nonsmokers, but not in smokers [30]. Another study indicated that rs2227481 had a protective role in COPD with smokers, but not in nonsmokers [21]. Additionally, the CHRNA3/5 locus was associated with lung function in individuals who smoke heavily [31]. There was a significant association between SMAD3 rs36221701 and SREK1 rs74794265 with the risk of COPD among the nonsmoking population, but not in smokers [19, 32]. In addition, rs4719841 and rs7934083 were identified as protective factors against COPD susceptibility among nonsmokers [18]. The present study revealed that the effect of IL5RA SNPs on COPD susceptibility may associated with smoking status. To sum up, our data suggests that the roles of IL5RA SNPs in COPD may affected by sex and smoking consumption.

Additionally, the possible functions of IL5RA SNPs were predicted and we found that rs3804795 was related to the regulation of Promoter histone marks, Enhancer histone marks, DNAse, Motifs changed, NHGRI/EBI GWAS hits, and GRASP QTL hits. Rs2290610 could influence the regulation of Enhancer histone marks, Motifs changed, and GRASP QTL hits. Rs13097407 was associated with the regulation of Promoter histone marks, Enhancer histone marks, Proteins bound, and Motifs changed. Rs334782 might be involved in the regulation of Enhancer histone marks, and Motifs changed. Rs3856850 was related to the regulation of Promoter histone marks, Enhancer histone marks, DNAse, Proteins bound, and Motifs changed. What’s more, much evidence has shown that SNPs contribute to the development of human diseases through changing gene expression and its function [33–35]. Taken above, we speculated that IL5RA gene polymorphisms, especially rs13097407 and rs3856850 might affect the expression and functions of the IL5RA gene and could lead to COPD, and further study is needed to confirm this hypothesis.

COPD can be classified into four types based on cellular inflammatory substrates: neutrophilic, eosinophilic, mixed (a combination of neutrophils and eosinophils), and paucigranulocytic [36]. In an environment that triggers anaphylaxis, Th2 cell immune responses are activated to produce IL-5 and IL-13, which induce eosinophilic airway inflammation, leading to the development of COPD [15]. Mepolizumab, an antibody that inhibits the binding of IL-5 to the α chain of the IL-5 receptor, has been used in the treatment of severe eosinophilic asthma [37]. Clinical case studies have indicated that mepolizumab can not only regulate blood eosinophil levels but also improve lung function, inhibit disease progression, and enhance the quality of life for patients [38]. IL-5 induces rapid tyrosine phosphorylation and activation of cellular proteins, including JAK1/JAK2 and STAT1/STAT5, by binding to IL-5R on target cells [39]. The GM-CSF/interleukin (IL)-3/IL-5 receptor family regulates the function of myeloid cells [40]. These factors activate the overlapping α and βc signaling pathways, the JAK/STAT, PI3K/AKT, and ERK/MAPK pathways [41, 42]. In this study, bioinformatics analysis also suggested that IL5RA regulates IL5/CSF2RB to activate JAK2/STAT5, PTPN11/GRB2/MAPK and PI3K/AKT/mTOR pathways. In short, IL5RA regulates the participation of IL5 in eosinophils and multiple pathways.

Inevitably, this study has some limitations. Only the Chinese population was recruited for this study, so it is necessary to collect data from different ethnic groups for a comprehensive exploration. Secondly, cell and animal experiments are still needed to further elucidate the regulatory mechanism of IL5RA in COPD.

Conclusion

This study explored the association between genetic variants of IL5RA with COPD risk. The rs13097407 decreased susceptibility to COPD overall, whereas rs3856850 was identified as a risk factor for COPD. Interestingly, the effect of IL5RA SNPs on susceptibility to COPD was found to be influenced by factors such as sex and smoking. This research provides data support for the clinical risk assessment and personalized treatment of COPD.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Hainan affiliated Hospital of Hainan Medical University (Hainan General Hospital Hospital).

Authors’ contributions

Siguang Li and Linsang Lin completed genotyping and performed the manuscript. Jie Zhao and Zehua Yang took part in genotyping. Yi Zhong and Linhui Huang participated in the statistical analysis of the data. Jie Chen and Lei Zhang modified the manuscript. Yipeng Ding and Tian Xie designed the study, co-supervised the work and finalized the manuscript. All the authors have read and approved the final manuscript.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Acknowledgement

We are grateful to all contributors to this research.

Declaration of interest

The authors declare there is no Complete of Interest at this study.

Disclosure Statement

The authors have declared that they have no conflict of interest.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This paper was supported by the Key Research and Development Plan of Hainan Province (No. ZDYF2023SHFZ103), Hainan Provincial Natural Science Foundation of China (No. 819QN354), and National Natural Science Foundation of China (No. 81860015 and No. 82160011).