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Association of the interaction between interleukin-1β gene polymorphism and smoking status with the diabetic nephropathy risk in a Chinese Han population

Diabetology & Metabolic Syndrome volume 17, Article number: 101 (2025) Cite this article

Abstract

Objectives

we aimed to evaluate the association of interleukin-1β (IL-1β) gene single nucleotide polymorphisms (SNPs) and its interaction with smoking status on diabetic nephropathy (DN) risk in a Chinese Han population.

Methods

The Hardy-Weinberg equilibrium (HWE) was tested by using SNPStats (https://www.snpstats.net/start.htm), which was also used for testing the relationship between four SNPs and DN risk and haplotype analysis. The SNP- SNP and gene- smoking interaction were verified by using generalized multifactor dimensionality reduction (GMDR) model.

Results

Logistic regression suggested that the DN risks of participants with rs16944- G allele were significantly higher than those with AA genotype, adjusted OR (95%CI) = 1.62 (1.24–2.01) for AG versus AA, 1.41 (0.75–2.12) for GG versus AA. Additionally, we also found that participants with rs3917356- T allele had an obviously higher DN risk than those with CC genotype, adjusted OR (95%CI) = 1.75 (1.34–2.19) for CT versus CC, 1.87 (1.23–2.54) for TT versus CC. GMDR model found a significant two-locus model (P = 0.011) including rs16944 and smoking. Compared with non- smokers with rs16944- AA genotype, smokers with rs1225404 AG or GG genotype had the highest DN risk after covariates adjustment, OR (95%CI) was 3.04 (1.98–4.12). We also found a haplotype containing rs1143634- T and rs3917356- T was associated with higher DN risk.

Conclusions

we found that the rs16944- G and rs3917356- T allele, interaction between rs16944 and smoking, haplotype containing rs1143634- T and rs3917356- T were all associated with increased DN risk.

Introduction

Diabetes nephropathy (DN) is one of the major complications of type 2 diabetes (T2DM) and a major risk factor for end-stage renal disease (ESRD) or chronic kidney disease (CKD) [1, 2]. The main clinical features of DN include renal failure, hypertension, massive proteinuria and persistent proteinuria [3]. In the past decade, the prevalence and incidence rate of DN among Chinese residents have increased sharply, affecting the health of about 150 million people [4]. Importantly, with the increase of incidence rate of type 2 diabetes in the Chinese population, the incidence rate of diabetes nephropathy continues to increase [5]. There are many factors that affect the risk of DN, including age, gender, dyslipidemia, smoking, race, and genetic background [6]. Previous studies [7, 8] have reported that candidate genes have an obvious impact on the genetic susceptibility of DN. Some studies [9, 10] suggest that genetic variations encoding inflammatory cytokines may have a significant impact on susceptibility to DN.

The interleukin-1 (IL-1) gene family produces three cytokines, including IL-1α, IL-1β and IL-1Ra. These molecules play crucial roles in various inflammatory responses by influencing antigen recognition and the function of lymphocytes [11]. IL-1β could bind to IL-1 receptor 1, leading to fever and immune activation, and is therefore known as one of the most prominent mediators of inflammation [11]. Previously, several studies have reported that IL-1β gene single nucleotide polymorphisms (SNPs) were associated with diabetic retinopathy [12]. Studies also suggested a correlation between IL-1β gene SNPs and DN risk in different populations [13, 14]. However, to date, just one study [15] has been performed in Chinese population. In addition, smoking has been suggested as an important environmental risk factor for DN [16, 17]. Several studies [18, 19] also indicated that gene- smoking interaction could influence DN susceptibility. But to date, no study was performed focused on the interaction effect between IL-1β gene and smoking. Therefore, we performed this case- control study to evaluate the impact of IL-1β gene polymorphism, its interaction with smoking status and potential haplotype among four SNPs on the risk of DN based on a Chinese Han population.

Materials and methods

Study population

All participants were recruited continuously from the affiliated Hospital of Nantong University between July 2017 and March 2023. A total of 828 subjects were enrolled. The average age of all participants was 51.7 ± 11.7 years, involving 412 cases (T2DM patients with DN) and 416 controls (T2DM patients without DN). T2DM patients were diagnosed according to the criteria recommended by World Health Origination [20]. DN patients were diagnosed based on a consensus established by the American Diabetes Association and the National Kidney Foundation [21, 22]. Those T2DM patients with severe system diseases, including cardiovascular disease (CVD), cancer, renal disease and historical exposure to radiation were excluded. The controls were matched to cases by sex, age (± 3 years) and nationality. The affiliated Hospital of Nantong University’s ethics committee approved all study protocols for this research.

SNP selection and genotyping methods

Four SNPs of the IL-1β gene were searched in the SNP database of the National Center for Biotechnology Information (NCBI) (https://www.ncbi.nlm.nih.gov/snp/), according to the following criteria: first, those SNPs of the IL-1β gene which were not detailed studied previously; second, the minor allele frequency (MAF) of SNPs was greater than 2%. At last, 4 SNPs of IL-1β gene were selected, including: rs3917356, rs16944, rs1143634 and rs1143627. All collected EDTA-processed whole blood samples were stored in a cryogenic refrigerator. We then extracted DNA from a 2 ml whole blood sample using the Genomic DNA Extraction Kit (Tiangen, Beijing, China), adhering to the provided manufacturer’s guidelines. Polymerase chain reactions (PCRs) were performed for genotyping using specific primers for four SNPs of IL-1β gene (Table 1).

Table 1 Description and primer sequences used for genotyping for 4 SNPs of IL-1β gene
Full size table

Statistical analysis

This research utilized R4.4.1 software for all statistical evaluations. We computed the means and standard deviations of continuous variables that followed a normal distribution and compared them via the student t-test. For categorical variables, percentages were calculated and then compared using the χ2 test. The Hardy-Weinberg equilibrium (HWE) was tested by using SNPStats (https://www.snpstats.net/start.htm), which was also used for investigation the relationship between four SNPs and DN risk and haplotype analysis. The SNP-SNP and gene-smoking interactions were confirmed through the application of the generalized multifactor dimensionality reduction (GMDR) model [23].

Results

This research involved 828 participants, with an average age of 51.7 ± 11.7 years. The participants consist of 412 cases (T2DM patients with DN) and 416 controls (T2DM patients without DN). Table 2 displays the general and clinical data of all participants grouped by cases or controls. The distribution for gender, alcohol consumption and the means of age, BMI, duration of diabetes, TG, HDL-C, LDL-C was not significantly different between cases and controls. More smokers were found in the cases than in the controls. The means of FPG, SBP, DBP, TC, urea and eGFR were significantly higher in cases than controls.

Table 2 General characteristics of all participants in case and control group
Full size table

All genotypes in control group conformed to Hardy-Weinberg equilibrium (all P values > 0.05). The frequencies of rs16944- allele (G) and genotype (AG or/ and GG) and rs3917356 allele (T) and genotype (CT or/ and TT) in T2DM patients with DN group were significantly higher than that in T2DM patients without DN group. Logistic regression suggested that the DN risk of participants with rs16944- G allele was obviously higher than those with AA genotype, adjusted OR (95%CI) = 1.62 (1.24–2.01) for AG versus AA, 1.41 (0.75–2.12) for GG versus AA. In addition, we also found that DN risk was higher in participants with rs3917356- T allele than those participants with CC genotype, adjusted OR (95%CI) = 1.75 (1.34–2.19) for CT versus CC, 1.87 (1.23–2.54) for TT versus CC (Table 3).

Table 3 Genotype and allele frequencies for 4 SNPs of IL-1β gene in case and control group
Full size table

We employed the GMDR model to assess the effect of interactions between SNP-SNP and gene-smoking within four SNPs of the IL-1β gene, along with smoking status on the risk of DN (Table 4). No statistically significant SNP- SNP interaction was obtained among IL-1β gene SNPs. However, we found a significant two-locus model (p = 0.011) including rs16944 and smoking, which suggesting a potential gene–environment interaction between rs16944 and smoking on DN risk. After adjusting for covariates, smokers who possess the rs1225404 AG or GG genotype, in comparison to non-smokers with the rs16944-AA genotype, exhibited the greatest risk of DN, with an odds ratio (95% CI) of 3.04 (1.98–4.12) (Table 5).

Table 4 GMDR analysis on the best SNP–SNP and gene- smoking status interaction models
Full size table
Table 5 Logistic regression analysis for interaction between rs16944 and smoking on DN risk
Full size table

Pairwise LD method calculated the D’ values among four SNPs of the IL-1β gene. The results showed a heavy LD between rs1143634 and rs3917356. Therefore, we performed haplotype analysis for rs1143634 and rs3917356 by using SHEsis software. We found that rs1143634- C and rs3917356- C haplotype frequency was the highest in both cases and control groups (0.4811 for T2DM with DN patients, 0.5689 for T2DM without DN patients). The haplotype containing rs1143634- T and rs3917356- T allele was associated with higher DN risk after covariate adjustment (Table 6).

Table 6 Haplotype analysis on association between IL-1β gene and DN risk
Full size table

Discussion

In this study, we evaluated the effect of IL-1β gene SNPs on DN risk. We found that increased DN risk was associated with both rs16944- G and rs3917356- T allele. Nevertheless, we did not find any significant correlation of rs1143634 and rs1143627 with DN susceptibility, after covariates adjustment. The polymorphism rs16944 in the IL-1β gene is linked to changes in both the transcription [24] of this gene and the production levels of the IL-1β protein [25]. Previously, an animal study [26] found a significant upregulation of IL-1β levels in diabetic animals in comparison with normal rats. Yuan et al. [15] conducted a study observing a cohort in China, which indicated that IL-1β is significantly implicated in the advancement of T2DM. They also found that its concentration escalates as DN worsens. Therefore, the level of IL-1β in human plasma can serve as an important indicator for determining the occurrence and development of DN, provide reference for early diagnosis and precise treatment of DN. Bi et al. [27] suggested that IL-1β was positively correlated with insulin resistance (IR) in non-diabetic hemodialysis patients, which means that IL-1β may be involved in the pathogenesis of IR. The previous case-control study in South Korean diabetes population suggested that there was a significant correlation between the T allele of rs16944 and the risk of DN [28]. However, the other two studies performed in white patients with diabetes have contradictory results with this study, they found no significant association between rs16944 and DN risk [29, 30]. Stefanidis et al. [14] conducted a case-control study at the University Hospital of Aachen and demonstrated that the rs16944 polymorphism in the IL1β gene was statistically associated with the onset of type 2 diabetic nephropathy and resulted in increased IL-1β synthesis. Hameed et al. [31] confirmed that there was a statistical correlation between the promoter polymorphism of cytokine IL-1 β gene and the regulation of transcription level and the susceptibility to nephropathy in diabetic patients. Wu et al. [32] performed a comprehensive meta-analysis and revealed a significant relationship between rs16944 polymorphism and the increased risk of developing DN. Previously, no study focused on relationship between rs3917356 and DN risk was performed. This study firstly verified the impact of rs3917356 and DN risk in Chinese population. We also found that rs1143634- T and rs3917356- T haplotype was associated with increased DN risk. The exact mechanism of IL-1β gene SNPs mediated progression of DN is still unclear. However, IL-1β gene polymorphisms could influence IL-1β levels, IR and which was associated with DN susceptibility [15, 27].

Numerous factors, including genetics, environmental influences and the interaction between them can influence susceptibility to DN. It is widely recognized that smoking significantly elevates the risk of developing DN [18, 19]. The exact mechanism of smoking mediated progression of DN is still unclear. Potential mechanisms include persistent sympathetic overactivity, atherosclerosis, oxidative stress and hyperlipidemia [33]. There may be a synergistic effect between smoking and hyperglycemia, which aggravates kidney deterioration through continuous sympathetic nerve activity, atherosclerosis, oxidative stress and hyperlipidemia. Our research revealed a higher prevalence of smoking among patients with diabetic nephropathy. Additionally, a notable interaction between the genetic marker rs16944 and tobacco use was observed. Maybe rs16944 and smoking can affect the risk of DN through different mechanisms. When both exist, they will significantly increase the risk of individual DN.

Although we obtained some novel results, several certain limitations existed in this study. Firstly, only four SNPs of IL-1 β gene were included in this study and more SNPs should be included in future research to explore the synergistic effect of multiple SNPs on the risk of DN. Secondly, this study was conducted in a single hospital of Nantong city, Jiangsu province in southeast of China, selection bias may be present to some extent. Thirdly, smoking status was self-reported, which may lead to misclassification and bias. Lastly, this study was a case-control study, which did not allow for causal inferences. So, the results obtained from this study should be verified by future studies explored the functional mechanisms underlying the observed genetic effects.

In conclusion, our research table confirms that there is a significant statistical correlation between IL-1 β gene rs16944-G and rs3917356-T alleles and DN risk in the Chinese population. In addition, there is a significant synergistic effect between rs16944 and smoking on the risk of DN. Although this study did not find an association between rs1143634 and DN risk, we found that the haplotype rs1143634-T and rs3917556-T was associated with increased DN risk.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

OR:

Odds ratios

CI:

Confidence interval

IL-1β:

Interleukin-1β

DN:

Diabetic nephropathy

GMDR:

Generalized multifactor dimensionality reduction

HWE:

Hardy-weinberg equilibrium

T2DM:

Type 2 diabetes mellitus

SNPs:

Single nucleotide polymorphism

ESRD:

End-stage renal disease

CKD:

Chronic kidney disease

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Authors and Affiliations

  1. Department of Endocrinology, Affiliated Hospital of Nantong University, No.20 Xisi Road, Chongchuan District, Nantong city, 226001, Jiangsu, China

    Tianyue Xie & Zhuqi Tang

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Contributions

All authors have read and approved the manuscript; TX performed data curation, formal analysis, methodology, writing and editing the manuscript. ZT: performed methodology and review the manuscript.

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Correspondence to Zhuqi Tang.

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Each participant understood the process of the study and signed a written informed consent before the start of the study. All study protocols of the current study were approved by the ethics committee of affiliated Hospital of Nantong University. All methods were performed in accordance with the Declaration of Helsinki.

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The authors declare no competing interests.

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Xie, T., Tang, Z. Association of the interaction between interleukin-1β gene polymorphism and smoking status with the diabetic nephropathy risk in a Chinese Han population. Diabetol Metab Syndr 17, 101 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-025-01667-y

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Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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