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Association of SNPs in nAChRs genes, areca nut chewing and smoking, and their interaction with lung cancer in Hainan, China: a case control study

BMC Cancer volume 25, Article number: 626 (2025) Cite this article

Abstract

Background

Areca nut (AN) was classified as a carcinogen by the International Agency for Research on Cancer (IARC) of the WHO in 2003. AN has the same carcinogenic components as cigarettes, such as benzo[a]pyrene (B[a]P) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), but its effects on interactions with genetic factors related to lung cancer have rarely been investigated. 

Methods

Here, a propensity score-matched case‒control study was conducted in Hainan, which included 445 patients with lung cancer and 445 cancer-free controls. Then, the associations between single-nucleotide polymorphisms (SNPs) in the CHRNA5-CHRNA3-CHRNB4 gene cluster and their interaction effects with AN chewing and smoking on lung cancer were analyzed. In addition, we explored the associations among AN, cigarettes, and genes related to lung cancer using the Comparative Toxicogenomics Database (CTD).

Results

The results indicate that the CHRNA3 rs938682 (A > G) GG genotype (OR = 0.669, 95% CI = 0.454 ~ 0.984, P = 0.042) can decrease the risk of lung cancer. The CHRNB4 rs7178270 (C > G) GG genotype (OR = 1.729, 95% CI = 1.168 ~ 2.571, P = 0.006) can increase the risk of lung cancer. The CHRNA5 rs17486278 CC genotype was associated with a high risk in males, smokers, and drinkers. The CHRNA3 rs938682 GG genotype was associated with a low risk in AN chewers. The CHRNB4 rs7178270 GG genotype was associated with high risk in drinkers and AN chewers. CHRNB4 rs7178270 and AN chewing have an interaction effect on lung cancer in Hainan.

Conclusions

This study is the first to elucidate the hidden impacts of AN on lung cancer and provides a key evidence regarding the interactive effects of AN and cigarettes with SNPs in nAChRs genes on lung cancer.

Graphical Abstract

Highlights

• The CTD suggests that nicotine and B[a]P in areca nut and cigarettes can promote lung cancer by binding to nAChRs.

• The CHRNA3 rs938682 GG genotype was associated with a low risk of lung cancer in Hainan. The CHRNB4 rs7178270 GG genotype was associated with a high risk of lung cancer in Hainan.

• CHRNB4 rs7178270 and areca nut chewing have an interaction effect on lung cancer in Hainan.

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Introduction

Areca nut (AN), derived from the seeds of the tropical palm tree Areca catechu, is extensively chewed and consumed by approximately 600 million individuals globally, particularly in South Asia, Southeast Asia, and the Asia Pacific region [1]. AN is cultivated primarily in the eastern, central, and southern regions of Hainan, and AN chewing is commonly observed among the native population in Hainan [2]. AN was classified as a carcinogen by the International Agency for Research on Cancer (IARC) of the WHO in 2003. In 2020, the IARC assembled a panel of 20 scientists from 10 countries to evaluate the carcinogenic potential of arecoline, a constituent of AN. The assessment categorized arecoline as a Group 2B carcinogen, indicating limited evidence of potential carcinogenicity in humans, with insufficient evidence from animal studies [3, 4]. Prior studies have shown that long-term exposure to AN can increase the risk of cancer in the oral cavity, esophagus, and other locations [5, 6]. However, few studies have reported a relationship between AN and lung cancer.

Several studies indicate the presence of additive interactions between air pollutants and genetic susceptibility factors, and prolonged exposure to air pollution is associated with an increased risk of lung cancer, particularly among individuals with increased genetic susceptibility [7]. In mouse models, pancreatitis and Kras oncogene mutations synergize to accelerate the development of pancreatic cancer, indicating that gene-environment interactions can rapidly produce gene‒regulatory programs that dictate early neoplastic commitment [8]. A study on the interaction effects of smoking and genetic predisposition on lung cancer in the China Kadoorie Biobank (CKB) cohort revealed that individuals with high genetic risk and smoking habits had a 3.95-fold increased risk of developing lung cancer (HR = 4.95, 95% CI = 3.61 ~ 6.77) [9]. Epidemiological research has reported that approximately 75% and 37% of global lung cancer deaths in males and females, respectively, are related to smoking [10]. Interestingly, nicotine and two other carcinogens, benzo[a]pyrene (B[a]P) and 4-(methylnitrosamino)−1-(3-pyridyl)−1-butanone (NNK), can be ingested separately through by AN chewing and smoking [11, 12]. Prior studies revealed that nicotine can bind to nicotinic acetylcholine receptors (nAChRs) and activate the signaling pathway associated with lung cancer [13]. Several studies have proposed that single-nucleotide polymorphisms (SNPs) of the CHRNA5-CHRNA3-CHRNB4 gene cluster are associated with lung cancer, and rs1948 (C > T) and rs8040868 (T > C) have been identified as potential genetic markers indicative of susceptibility to lung cancer in the Chinese Han population [14]. However, relevant research regarding the interaction effects of SNPs and AN chewing and smoking on lung cancer is limited.

Here, we first explored the interactions among AN, cigarettes, and genes related to lung cancer via the Comparative Toxicogenomics Database (CTD) and analyzed the association between AN, cigarettes, and lung cancer-related genes, as well as the expression of CHRNA5, CHRNA3, and CHRNB4 genes in lung cancer tissues and normal tissues and their impact on overall survival (OS) by Gene Expression Profiling Interactive Analysis 2 (GEPIA 2). Then we conducted a case–control study in Hainan that included 445 patients with lung cancer and 445 cancer-free controls. We focused on investigating the AN chewing and smoking behaviors of the study individuals, and SNPs in the CHRNA5-CHRNA3-CHRNB4 gene cluster were detected via mass spectrometry. This study revealed a link between AN and lung cancer and provided key evidence regarding the interactive effects of AN and cigarettes with SNPs in nAChRs genes on lung cancer.

Materials and methods

Two databases used to analyze the correlation of nAChRs in lung cancer

The CTD database (http://ctdbase.org/) could provide information on the relationships between chemicals, human genes, and diseases [15]. The compounds that interact with lung cancer were queried in the CTD, search queries were specifically configured with four chemicals—nicotine, B[a]P, arecoline, and NNK to analyze chemical-gene interactions associated with lung cancer. The GEPIA 2 database (http://gepia2.cancer-pku.cn/) was constructed by integrating RNA-seq-derived gene expression profiles from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects, enabling systematic comparative analyses of transcriptional patterns across malignancies and normal tissues [16]. The expression of the CHRNA5-CHRNA3-CHRNB4 gene cluster in normal and cancer tissues, as well as the OS of lung cancer patients, were analyzed using data retrieved from the GEPIA 2 database.

Case‒control studies of lung cancer patients and cancer-free controls

A total of 890 subjects enrolled in this study were recruited from Hainan General Hospital and the First Affiliated Hospital of Hainan Medical University from November 2021 to June 2023. The research subjects included 445 patients with lung cancer and 445 cancer-free controls from the same period. Propensity score matching (PSM) was applied for 1:1 matching by sex and age between the patient group and the cancer-free group. This study was conducted in accordance with the Declaration of Helsinki principles and approved by the Ethics Committee of Hainan Medical University (HYLL-2021–187). All participants in this study provided written informed consent. Subjects with limited physical activity, difficulty in language expression, severe psychological disorders, and mental illness resulting in unconsciousness were excluded from the study. The participants answered a questionnaire containing questions about age, sex, and exposure factors such as smoking and AN chewing. The questionnaire for the case group included information on the prevalence of chronic obstructive pulmonary disease (COPD).

Smoking was defined as having smoked at least one cigarette daily for at least six consecutive months at any time during the person's life. Alcohol consumption was defined as consuming an alcoholic drink at least once per week for at least twelve consecutive months at any time during a person's life. AN chewing was defined as having chewed at least one petal daily for at least six consecutive months at any time during a person's life.

DNA extraction and SNPs genotyping

Two millilitres of peripheral blood was collected from each study subject using ethylenediamine tetraacetic acid (EDTA) vacuum blood collection tubes and stored at 4 °C. After cold chain transportation to the laboratory, the plasma, leukocytes, and erythrocytes were separated by centrifugation at 4000 rpm for 10 min and dispensed into 1.5 ml freezing tubes. The plasma was stored at −80 °C, and the leukocytes and erythrocytes were stored at −40 °C until laboratory detection. The whole blood was mixed with sodium dodecyl sulfate (SDS), buffer, and proteinase K and incubated at 37 °C with shaking for 20 h. After centrifugation, phenol equilibration was performed, the mixture was centrifuged, the supernatant was collected, an equal volume of 24:1 chloroform-isoamyl alcohol was added, and the mixture was shaken for 10 min. This step was repeated twice, and the supernatant was transferred to an EP tube. A total of 10 μl of 4 mol/L NaCl solution and twice the volume of anhydrous ethanol was added, mixed by inversion, and centrifuged, and the supernatant was discarded. Two hundred microlitres of 70% ethanol was added, the mixture was mixed by inversion and then centrifuged, the supernatant was discarded, and the mixture was air dried. Finally, the DNA was dissolved in 200 µl of TE buffer, the DNA concentration was measured via a UV spectrophotometer to ensure that the OD260/OD280 ratio was between 1.8 and 2.0, and the samples were stored in a −20 °C freezer for later use. SNPs genotyping using the MassARRAY System. MassARRAY SNPs genotyping technology, developed by Agena Bioscience, Inc., in the US, is a state-of-the-art genotyping methodology based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI‒TOF MS). This innovative technique enables the simultaneous analysis of SNPs loci within a sample. The gene positions are shown in (Fig. 1). The sequences of the primers used for PCR are shown in Table 1.

Table 1 Primer information
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Fig. 1
figure 1

Simplified illustration of the human CHRNA5–CHRNA3–CHRNB4 gene cluster. (Each gene is not drawn to scale. The colored arrows indicate the direction of transcription. The locations of each gene are marked, and the genes highlighted in color are the ones we prioritized for further study after quality control.)

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Quality control

To obtain high-quality genotyping data, SNPs quality control was conducted using PLINK v1.9. The SNPs were included if they met the following criteria: (1) Call rate > 90%, (2) MAF > 5%, (3) HWE > 1 × 10–6. The snp_fastImpute function in the bigsnpr package was used to fill in the missing genotypes. The quality control of the questionnaire included verifying the accuracy of the survey questions and survey content and combining the answers to the closed questions with the answers to the open questions. Doctors were trained uniformly, thus improving the reliability and validity of the questionnaire results. A face-to-face paper questionnaire survey was used to collect data on demographic characteristics, living environment, dietary behavior, and lifestyle. After the questionnaires were received, timely checks and codes were performed, invalid questionnaires were eliminated, and valid questionnaires were subsequently input into the data analysis results. After quality control, 7 SNPs and 890 subjects were included for further analysis.

Statistical analysis

Epidata software (version 3.1) was used to input questionnaires, and SPSS 20.0 statistical software was used for data analysis, excluding invalid questionnaires. Propensity score matching (PSM) was applied for 1:1 matching between the case group and the cancer-free group. Conditional logistic regression analysis and PSM were performed using R software (version 4.2.1). Adjusted P values, odd ratio (OR), and 95% CI, with and without adjustment for potential confounding factors, including sex, age, smoking status, and alcohol consumption, were obtained. Haploview software (version 4.2) was used to conduct the haplotype analysis and linkage disequilibrium. The log-likelihood ratio test and logistic regression analysis were used to test SNPs and smoking and AN multiplicative interaction. The additive interaction term was assessed with the relative excess risk due to the interaction (RERI), the attributable proportion (AP), and the synergy index (SI) due to the interaction by the additive interaction model of Tomas Andersson [17], and when 0 was within the 95% CI of the RERI and AP, 1 was within the 95% CI of the SI, it meant that there was no additive interaction. A two-sided P < 0.05 was considered to indicate statistical significance.

Results

Correlation analysis of nAChRs in lung cancer via the CTD and GEPIA 2 databases

We retrieved the four components of nicotine, B[a]P, arecoline, and NNK in tobacco and AN from the CTD. Nicotine has been identified as the main psychoactive and addictive component of tobacco and is a potent agonist of nAChRs [18]. AN chewing is considered the fourth most common psychoactive and addictive habit worldwide (after alcohol consumption, tobacco smoking, and caffeine consumption). The carcinogenic substances B[a]P and NNK are present in the smoke of cigarettes as well as during tobacco and AN chewing [19]. These four substances are associated with genes related to lung cancer: nicotine (86 genes), NNK (46 genes), arecoline (20 genes), and B[a]P (260 genes). Through analysis using a Venn diagram, we identified 12 genes that are collectively impacted by the four substances present in tobacco and AN, namely, AKT1, CASP8, CCND1, CTNNB1, CYP1A2, CYP2E1, EGFR, FOS, IL6, MAPK1, MAPK3, and TP53. A total of 85 genes were collectively impacted by nicotine and B[a]P, including some common cancer-related genes, as well as genes associated with nAChRs, namely, CHRNA2, CHRNA3, CHRNA5, CHRNA7, and CHRNB4 (Fig. 2). In particular, a significant overlap was present between nicotine and B[a]P, including nAChRs.

Fig. 2
figure 2

Venn diagram showing genes that are collectively impacted by the four substances (nicotine, benzopyrene, arecoline, and NNK) present in cigarettes and AN

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Furthermore, we used the GEPIA 2 database to explore CHRNA5-CHRNA3-CHRNB4 gene cluster expression and OS in patients with lung cancer. The GEPIA 2 database revealed that CHRNA5 was upregulated in both lung adenocarcinoma (LUAD) (Fig. 3A) and lung squamous cell carcinoma (LUSC) (Fig. 3B), whereas CHRNA3 showed no significant changes in gene expression in lung tumours. Additionally, CHRNB4 was found to be upregulated specifically in LUSC (Fig. 3C). Studies have shown that nicotine regulates the expression of PLEK2 in lung cancer cells by activating α5-nAChR. CHRNA5 has been confirmed to be involved in mediating nicotine-induced metastasis and invasion of LUAD through PLEK2, but similar conclusions have not been reached regarding lung squamous cell carcinoma [20]. Survival analysis revealed that elevated CHRNA5 expression was correlated with poor prognosis in patients with LUAD (P = 0.001) (Fig. 3D), but this association was not detected in patients with LUSC (P = 0.580) (Fig. 3E). Furthermore, no notable effect was observed on survival associated with the upregulation of CHRNB4 expression in patients with LUSC (P = 0.920) (Fig. 3F). Other studies have shown that CHRNB4 is specifically overexpressed in squamous cell carcinoma but not significantly expressed in adenocarcinoma. Additionally, it has been suggested that CHRNB4 is significantly associated with the survival rate of squamous cell carcinoma patients [21].

Fig. 3
figure 3

Box plot and Kaplan‒Meier survival curve of lung cancer patients whose nAChR expression was analyzed via the GEPIA 2 database. A Differences in CHRNA5 expression between cancer tissues and normal tissues in LUAD. B Differences in CHRNA5 expression between cancer tissues and normal tissues in LUSC. C Differences in the expression of CHRNB4 between cancer tissues and adjacent normal tissues in LUSC. D Survival curves of the high- and low-CHRNA5 expression groups in LUAD. E Survival curves of the high- and low-CHRNA5 expression groups in LUSC. F Survival curves of the high- and low-CHRNB4 expression groups in LUSC

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Comparison of baseline characteristics between the case and cancer-free groups

Propensity score matching was applied to achieve a balanced baseline. The covariates were age and sex, which were matched at a 1:1 ratio on the basis of propensity score with a standard caliper width of 0.05. Before matching, the total number of cases and the distribution of males and females in the case and cancer-free groups differed; however, after matching, the total number of cases was the same, and approximately twice as many males as females were present in each group (296 males and 149 females). After matching, the ages of the participants in the case and control groups were 61.51 ± 10.31 years and 58.11 ± 10.19 years, respectively, which were balanced and comparable. In the case group, smokers made up the majority of participants (59.78%). In the cancer-free group, the majority of the participants (64.27%) were non-smokers. There was a significant difference in the number of smoking individuals between the two groups' statuses (P < 0.001). However, we did not observe a significant difference between the two groups regarding drinking (P = 0.879) and AN chewing (P = 0.253). After PSM, in the case group, the prevalence of COPD was 10.56%, the smoking rate was 59.78%, and the AN chewing rate was 6.74%. According to the "International Expert Consensus on Diagnosis and Treatment of Lung Cancer Complicated by Chronic Obstructive Pulmonary Disease", the prevalence of COPD among lung cancer patients in China is approximately 40% to 70% [22], which is significantly different from the prevalence of COPD in the case group in our study.

According to global estimates, approximately 600 million people, which is approximately 10% ~ 20% of the world’s population, consume AN worldwide [23]. The smoking rate among lung cancer patients varies depending on the region and study sample, but generally, the majority of lung cancer patients have a history of smoking, as smoking is one of the primary risk factors for lung cancer. Adenocarcinoma was the most common pathological type, accounting for 66.3%, followed by squamous cell carcinoma, small cell carcinoma, and other types. The specific baseline information is shown in Table 2. In addition, we observed that there were a total of 52 cases in the two groups; 30 cases (6.74%) reported a history of AN chewing in the case group, which was slightly greater than the 22 cases (4.94%) reported in the control group. Among the male lung cancer patients, 25 had a history of AN exposure, accounting for 8.45% of the total male lung cancer patients, which was greater than the 20 participants in the control group (6.76%). Among the female lung cancer patients, 5 had a history of AN exposure, accounting for 3.36% of the total female lung cancer patients, which was greater than the 2 participants in the control group (1.34%) (Table 3).

Table 2 Baseline characteristics before and after propensity score matching
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Table 3 Associations of AN chewing with lung cancer
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Association of CHRNA3 rs938682 (A > G) and CHRNB4 rs7178270 (C > G) with lung cancer risk

Associations between the SNPs and the risk of lung cancer

In this study, we found that CHRNA3 rs938682 GG carriers had a lower risk of lung cancer than AA carriers (OR = 0.669, 95% CI = 0.454 ~ 0.984, P = 0.042), GG carriers had a lower risk of lung cancer than AG and AA carriers in the recessive model (OR = 0.668, 95% CI = 0.477 ~ 0.933, P = 0.018). The GG carriers of the CHRNB4 rs7178270 had a greater risk of lung cancer than CC carriers (OR = 1.729, 95% CI = 1.168 ~ 2.571, P = 0.006). In the dominant model, CG and GG carriers had a greater risk of lung cancer than CC carriers (OR = 1.353, 95% CI = 1.029 ~ 1.781, P = 0.031). In the recessive model, the risk of lung cancer was significantly increased compared with the CG and CC genotypes (OR = 1.530, 95%CI = 1.072 ~ 2.195, P = 0.020). Carriers of the G allele had a greater risk of lung cancer than carriers of the C allele in the allelic model (OR = 1.306, 95% CI = 1.080 ~ 1.580, P = 0.006) (Fig. 4).

Fig. 4
figure 4

Associations between the SNPs and the risk of lung cancer. a Adjusted by smoking and drinking

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Compared with the AG haplotype, the CG haplotypes of CHRNA5 rs17486278 and rs692780 were associated with an increased risk of lung cancer

In the haplotype analysis, the CHRNA5 rs17486278 locus allelic variation and the CHRNA5 rs692780 locus allelic variation were identified (Fig. 5). These two loci presented genotypes comprising AG, CG and AC alleles. Researchers have identified multiple genetic variant loci in the chromosome 15q25.1 region associated with nAChRs function. Li reported that individuals carrying the CC genotype of CHRNA5 rs17486278 had a positive interaction with lung cancer when they smoked 1–15 cigarettes per day [24]. Similarly, allelic variation in the CHRNA5 rs555018 locus and allelic variation in the CHRNA3 rs3743078 locus were detected. The genotypes at these two loci included AC, AG and GG alleles. The CG haplotype in CHRNA5 rs17486278 and CHRNA5 rs692780 was significantly associated with lung cancer, indicating that the CG haplotype increases the risk of lung cancer by 1.250-fold compared with the AG haplotype (95% CI = 1.014 ~ 1.542, P = 0.036) (Table 4).

Table 4 Association of haplotypes and the risk of lung cancer
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Fig. 5
figure 5

Haplotype plot for the LD block constructed from 7 SNPs

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Stratified analysis of CHRNA5 rs17486278, CHRNA3 rs938682 and CHRNB4 rs7178270 by age, sex, alcohol consumption, smoking status, and AN chewing status

The detailed results of the stratified analysis can be found in Supplementary Tables 1–5. In stratified analyses, the CC genotype of CHRNA5 rs17486278 was associated with a significantly higher risk of lung cancer among males, smokers, and alcohol drinkers. The GG genotype of CHRNA3 rs938682 showed a significantly reduced risk of lung cancer in AN chewers. Furthermore, the GG genotype of CHRNB4 rs7178270 was associated with a significantly higher risk of lung cancer among AN chewers and alcohol drinkers.

In the males and smoking population, the CHRNA5 rs17486278 carriers the CC genotype had a significantly higher risk of lung cancer (ORadj = 2.192, 95%CI = 1.036 ~ 4.719, P = 0.042; ORadj = 2.621, 95%CI = 1.211 ~ 6.120, P = 0.019). A meta-analysis study showed that carrying the C allele at the CHRNA3 rs938682 locus is a protective factor for lung cancer in smokers and Caucasians [25]. This was different from the results in our study population. Considering the potential for ethnic differences, it also suggests that this could be a factor influencing the incidence of lung cancer in the population. In the AN chewing population, the CHRNA3 rs938682 locus carriers either the AG or GG genotype had a significantly lower risk of lung cancer (ORadj = 0.082, 95%CI = 0.009 ~ 0.481, P = 0.011; ORadj = 0.073, 95%CI = 0.008 ~ 0.490, P = 0.012). In the AN chewing and drinking population, the CHRNB4 rs7178270 locus carriers the GG genotype had a significantly higher risk of lung cancer (ORadj = 20.378, 95%CI = 2.288 ~ 491.562, P = 0.018; ORadj = 2.051, 95%CI = 1.065 ~ 4.101, P = 0.036).

CHRNB4 rs7178270 has an interaction with AN chewing

Nearly 40% of diseases have genetic origins, whereas environmental factors, including socioeconomic status, air pollution, and climate change, contribute to at least 25% of diseases [26]. Previous studies have extensively explored the influence of known genetic variations on cellular signaling pathways, DNA repair mechanisms, and the functionality of tumor regulatory genes, such as those that modulate MGMT expression by interfering with cell signaling pathways [27, 28]. Moreover, studies have investigated the interplay between gene mutations in MSH5, MMP9, and CYP2D6 and smoking, which results in an increased risk of lung adenocarcinoma development [29].

In this study, a significant interaction was found that CHRNA5 rs17486278, CHRNA5 rs555018, CHRNA5 rs692780, CHRNA3 rs3743078, CHRNA3 rs1317286, CHRNA3 rs938682 and CHRNB4 rs7178270 all of these loci had an increased risk of lung cancer when exposure to smoking (P < 0.05) (Table 5). However, the additive model found no interaction between SNPs and smoking (Table 6). The multiplicative interaction model for SNPs and AN chewing showed that CHRNB4 rs7178270 has a multiplicative interaction with AN chewing (ORadj = 3.095, 95%CI = 1.210 ~ 9.164, P = 0.027). A significant interaction was subsequently found that CHRNA5 rs555018 GG genotype, CHRNA5 rs692780 CC genotype, CHRNA3 rs938682 AA genotype, CHRNB4 rs7178270 CG and GG genotypes had an increased risk of lung cancer when exposure to AN chewing (Table 7). However, the additive model found no interaction between SNPs and AN chewing (Table 8). In addition, our results showed that no significant multiplicative interaction between the seven loci with smoking and AN chewing (Table 9).

Table 5 The multiplicative interaction between SNPs and smoking
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Table 6 The additive interaction between SNPs and smoking
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Table 7 The multiplicative interaction between SNPs and AN chewing
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Table 8 The additive interaction between SNPs and AN chewing
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Table 9 The multiplicative interaction between SNPs, smoking and AN chewing
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Discussion

In 2022, lung cancer was the most prevalent cancer in China, with 1,060,600 cases [30]. In Hainan, tracheal, bronchial, and lung cancer (TBL) has the highest mortality rate among all cancers, according to data from the National Mortality Surveillance System 2005 to 2020 in China [31]. Our study revealed that CHRNB4 rs7178270 (C > G) can increase the risk of lung cancer in individuals living in Hainan. CHRNA3 rs938682 (A > G) can decrease the risk of lung cancer in Hainan. Our study suggested that the CHRNA5 rs17486278 C and rs692780 G variants conferred a 1.250-fold increase in lung cancer risk compared with the AG genotype. The correlation between specific genotypes and the risk of lung cancer varied in different populations in this study. The CC genotype at the CHRNA5 rs17486278 locus was associated with a high risk in males, smokers, drinkers and the GG genotype at the CHRNA3 rs938682 locus was associated with a low risk in AN chewers. The GG genotype at CHRNB4 rs7178270 was associated with high risk in drinkers and AN chewers. In our study population, the rate of AN chewing was 6.74%, the current stratified analyses should be interpreted with caution due to the limited representation of AN chewers in our cohort, necessitating validation through larger-scale population studies. We hope to assess additive interaction since it is of greater public health relevance than multiplicative interaction. However, we did not find evidence of additive interaction in this study. Thus, we considered that among these seven loci, CHRNB4 rs7178270 and AN chewing have an interaction effect on lung cancer.

In one cohort study spanning from 1994 to 2006 and comprising 177,271 male participants, AN chewing was associated with a 2.43-fold increase in the risk of lung cancer development. A different study indicated that a synergistic relationship between AN chewing and smoking was evident, as individuals who practiced both behaviors accounted for half of all cancer-related fatalities within the cohort [32]. Previous studies have suggested a potential link between AN chewing and increased lung cancer risk, with evidence suggesting that arecoline, a compound found in AN, may enhance the migration of A549 cells through the activation of the EGFR/Src/FAK pathway [33]. Furthermore, the combined habit of smoking and AN chewing may synergistically impact the elevation of serum triglyceride levels [34]. Consistent with findings regarding the association of smoking with lung cancer, smoking is indeed a risk factor for lung cancer. Additionally, findings from other studies on the synergistic effect of smoking and AN in causing lung cancer further support our hypothesis.

Owing to the common components shared by tobacco and AN, it is reasonable to speculate that their associations with lung cancer might be similar. In this study, we identified common genes linked to B[a]P, arecoline, and NNK in lung cancer from the CTD, notably the nAChRs linked to both nicotine and B[a]P. Nicotine and benzopyrene collectively influence 85 genes, including several implicated in cancer, such as BRAF, EGFR, PIK3CA, PTEN, and TP53. Notably, BRAF mutations at the V600 position have been linked to carcinogenesis in melanoma, colorectal cancer, and NSCLC. The overexpression of EGFR, which is observed in more than 60% of NSCLC cases, has emerged as a crucial therapeutic target in NSCLC treatment [35]. Mutations in PIK3CA, a common oncogenic alteration, combined with EGFR and TP53 mutations, have prognostic value for predicting survival in patients with NSCLC [36, 37]. A familial study conducted in the southeastern United States revealed that carriers of the EGFR T790M variant have an increased risk of developing lung nodules, and the occurrence of lung nodules may be consistent with the development of in situ adenocarcinoma [38]. Decreased PTEN expression in tumors may be correlated with lower overall survival rates in NSCLC patients [39]. Small-cell lung cancer is strongly associated with exposure to tobacco carcinogens, and genomic analysis often reveals TP53 tumor suppressor gene inactivation [40].

To identify the nicotinic acetylcholine receptor as a promising avenue of study, we focused on the CHRNA5-CHRNA3-CHRNB4 gene cluster, which is located at 15q2.5, for further investigation [41]. Subsequent comparison of gene expression in lung cancer and adjacent tissues was performed using the GEPIA 2 database. These findings suggest that CHRNA5-CHRNA3-CHRNB4 is intricately involved in lung cancer occurrence and progression, with genetic polymorphisms at these loci potentially modulating individual lung cancer risk. Human genetic studies, particularly genome-wide association studies (GWASs), have identified several lung cancer susceptibility loci [42]. While findings derived from the GEPIA 2 database primarily reflect European populations and may present ethnic differences compared to Chinese cohorts, the established associations between variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster and lung carcinogenesis still provide valuable clues for our investigation. Complementary evidence from the CTD database further underscores the critical role of gene-environment interactions in lung cancer pathogenesis, particularly through its systematic documentation of chemical-gene relationship networks. These collective findings reinforce the biological plausibility of tobacco exposure-related genetic susceptibility in driving pulmonary malignancies [43, 44].

Gene-environment interactions play an important role in population genetics, such as the impact of smoking and environmental exposure on gene effects. Genes may show different disease association strengths in smokers and non-smokers, suggesting that environmental factors may significantly modulate gene effects [45]. The heterogeneity of gene effects suggests that, when studying complex diseases, it is important to fully consider the influence of environmental factors and population stratification in order to more accurately identify disease risk factors and potential intervention targets. Previous meta-analyses have associated CHRNA3 rs938682 with lung cancer [46]. Another study reported that the GG genotype carrying the CHRNB4 rs7178270 locus was associated with a low risk of non-small cell lung cancer in a Chinese non-smoking population (OR = 0.553, 95%CI = 0.309 ~ 0.989, P = 0.0437) [47]. CHRNB4 is recognized as a pivotal gene within the CHRNA5-CHRNA3-CHRNB4 cluster [48]. In this study, we only find that CHRNB4 rs7178270 and AN chewing have an interaction effect on lung cancer in Hainan.

A notable strength of our study lies in its exploration of the relationship between SNPs linked to the targeted receptor and AN chewing within the cultural context of Hainan. Despite prior associations of this receptor with smoking behavior, our investigation yielded affirmative outcomes, shedding light on the potential influence of AN chewing on genetic susceptibility in the Hainan population. However, it is imperative to acknowledge certain limitations inherent in our study. Firstly, the modest sample size, coupled with the fact that only participants from Hainan were included, in China, represents a notable constraint. Secondly, other potential confounding variables should also be considered, including socioeconomic status, comorbidities, occupational carcinogen exposures, air pollution, and dietary habits. Consequently, the generalizability of our research findings may be limited to populations of similar ethnic backgrounds and geographical regions. Nevertheless, our study has contributed novel insights into the relationship between lung cancer and AN chewing, augmenting existing evidence in this domain. Future endeavours will focus on expanding the sample size and encompassing diverse demographic cohorts to validate and extend the observed associations, thereby fostering a more comprehensive understanding of the intricate interplay between genetic predisposition and environmental exposure in lung cancer pathogenesis. Genetic screening for CHRNA5-CHRNA3-CHRNB4 polymorphisms in high-risk populations is scientifically justified and holds potential preventive significance. However, it should be implemented cautiously, with full consideration of ethical and social issues. Future research should further explore the specific mechanisms of these polymorphisms in different populations and develop targeted prevention and intervention strategies.

Conclusion

In conclusion, the CHRNA3 rs938682 and the CHRNB4 rs7178270 were associated with lung cancer in Hainan. CHRNB4 rs7178270 and AN chewing have an interaction effect on lung cancer in Hainan. Our findings not only underscore the association between polymorphisms in the CHRNA5-CHRNA3-CHRNB4 gene region and AN chewing with an elevated risk of lung cancer in the Hainan population but also implicate the potential adverse impact of these factors on lung cancer susceptibility in this geographic region. Notably, this locus has not been previously implicated in the context of AN chewing, warranting further investigation to elucidate its functional significance.

Data availability

The data in this study are available by reasonable request from the corresponding author.

Abbreviations

AN:

Areca nut

nAChRs:

Nicotinic acetylcholine receptors

IARC:

International Agency for Research on Cancer

SNPs:

Single-nucleotide polymorphisms

CTD:

Comparative Toxicogenomics Database

CKB:

China Kadoorie Biobank

B[a]P:

Benzo[a]pyrene

NNK:

4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone

GEPIA 2:

Gene Expression Profiling Interactive Analysis 2

OS:

Overall survival

PSM:

Propensity score matching

COPD:

Chronic obstructive pulmonary disease

MAF:

Minor Allele Frequency

HWE:

Hardy–weinberg equilibrium

LUAD:

Lung adenocarcinoma

LUSC:

Lung squamous cell carcinoma

TBL:

Tracheal, bronchial, and lung cancer

GWASs:

Genome-wide association studies

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Acknowledgements

We sincerely thank the staff of the Hainan Medical University and those involved in data collection in particular, including Hainan General Hospital and the First Affiliated Hospital of Hainan Medical University.

Funding

This study was supported by Hainan Province Science and Technology Special Fund (ZDYF2025SHFZ046, ZDYF2021SHFZ086) and Hainan Provincial Natural Science Foundation of China (820QN268).

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Author notes

  1. Yixuan Li, Jing Zhou and Lirong Liu were co-first authors and contributed equally to this work.

Authors and Affiliations

  1. School of Public Health, Key Laboratory of Tropical Translational Medicine of Ministry of Education, Heinz Mehlhorn Academician Workstation, Hainan Medical University, Haikou, Hainan, 571199, People’s Republic of China

    Yixuan Li, Jing Zhou, Ziyue Luo, Na Li, Jing Zhang & Sha Xiao

  2. Department of Respiratory and Critical Care Medicine, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, 570311, People’s Republic of China

    Lirong Liu, Tian Xie & Yipeng Ding

  3. Medical Examination Center of Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, 570311, People’s Republic of China

    Chaoyong Zhu

  4. Department of Breast Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, 570102, People’s Republic of China

    Pengfei Lyu

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Contributions

Yixuan Li: Collected and analysis of the data –writing. Jing Zhou: Investigation and analysis of the data. Lirong Liu: Investigation. Chaoyong Zhu: Investigation. Ziyue Luo: Investigation. Na Li: Investigation. Pengfei Lyu: Investigation. Jing Zhang: Investigation. Tian Xie: Investigation. Yipeng Ding: Writing – review & editing. Sha Xiao: Supervision, writing – review & editing.

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Correspondence to Yipeng Ding or Sha Xiao.

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The study protocol was reviewed and approved by the Ethics Committees of Hainan Medical University (HYLL-2021–187). Participants provided written informed consent prior to taking part in the study. All experiments were performed in accordance with relevant guidelines and regulations.

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Li, Y., Zhou, J., Liu, L. et al. Association of SNPs in nAChRs genes, areca nut chewing and smoking, and their interaction with lung cancer in Hainan, China: a case control study. BMC Cancer 25, 626 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-14020-3

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BMC Cancer

ISSN: 1471-2407

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