Analysis of ABCG2 gene rs2231142 single nucleotide polymorphism and risk factors in hyperuricemia (2025)

Uric acid (UA) represents the final product of purine metabolism. When UA excretion is reduced or when excessive purine-rich foods are ingested, the accumulation of UA can readily occur, resulting in hyperuricemia (HUA). HUA may be diagnosed when fasting blood UA levels exceed 7mg/dL in males or 6mg/dL in females on two separate occasions¹. A cross-sectional study involving non-obese populations in China revealed an overall prevalence of HUA at 9.4%, with rates of 16.3% in males and 4.6% in females². In Western countries, the prevalence varies from 11.4% to 20%^3,4. Historically, HUA has been more common among middle-aged and elderly men and postmenopausal women. However, recent trends indicate a shift towards younger demographics, although males continue to predominate^5,6. HUA not only serves as a significant risk factor for gout but is also closely linked to the onset of hypertension, diabetes, cardiovascular diseases, and renal disorders^7,8. Consequently, HUA has gradually emerged as a public health issue that poses serious threats to human life and safety.

The etiology of HUA may be ascribed to two principal factors: (1) genetic elements that lead to deficiencies or mutations in genes associated with purine metabolism pathways, and (2) acquired factors that result in suboptimal dietary and lifestyle practices. Epidemiological evidence indicates that body mass index (BMI), genetic polymorphisms, and the consumption of purine-rich foods (such as beer, meat, legumes, and seafood) affect serum UA levels⁸. Clinical diagnosis of HUA is typically achieved through the measurement of blood UA and renal function indicators. However, by the time the disease is diagnosed, certain pathophysiological changes have already manifested, markedly impacting the patient’s prognosis. The identification of biomarkers with diagnostic significance may provide early warning before the clinical phenotype of HUA emerges.

Adenosine triphosphate-binding cassette transporter G subfamily member 2 (ABCG2) functions as an adenosine triphosphate (ATP)-binding transporter protein, which is widely found in tissues with secretory and excretory roles. Dysfunction of ABCG2 may result in a diminished capacity for UA excretion⁹. Previous investigations have indicated that the T allele of ABCG2 rs2231142 is linked to increased serum UA levels, with its prevalence in Asian populations being approximately three times greater than that observed in European populations. Consequently, rs2231142 is regarded as the most significant genetic mutation site related to gout in Asian regions¹⁰. Nevertheless, the definitive relationship between this mutation and HUA has yet to be established.

Consequently, data were collected from individuals both with and without HUA, identified during physical examinations conducted at two tertiary hospitals. The relationship between ABCG2 rs2231142 and HUA was analyzed alongside the associated risk factors. The objective was to identify novel targets for the treatment of HUA and to offer early warnings for populations at high risk.

Research subject

The study comprised 1612 patients diagnosed with HUA at the First Affiliated Hospital of Xinjiang Medical University between February 2017 and June 2019. Simultaneously, 1770 individuals exhibiting normal UA levels were selected from the health examination center to serve as the control group. The age range for all participants was 20 to 70years. Diagnostic criteria for HUA were established based on the 1977 American College of Rheumatology guidelines for primary gout¹¹ and the findings from the Chinese serum urate survey¹²: fasting serum uric acid (SUA) levels exceeding 417μmol/L (7mg/dL) for males and SUA levels exceeding 357μmol/L (6mg/dL) for females. The control group consisted of individuals without a history of HUA and/or those not currently undergoing UA-lowering therapy, with SUA levels at or below 420μmol/L (7.0mg/dL) for males and SUA levels at or below 360μmol/L (6.0mg/dL) for females. Exclusion criteria included: (1) usage of UA-lowering medications within the previous week; (2) existence of severe malignant tumors, blood disorders, or liver and kidney dysfunction; and (3) history of acute gouty arthritis. This study received approval from the Ethics Committee of Xinjiang Medical University (No. K202105-08). All participants voluntarily participated in the study, provided informed consent, and signed consent forms. The research methods were carried out in accordance with relevant guidelines and regulations.

Anthropometry and blood pressure measurement

Height, weight, waist circumference, and hip circumference were recorded using calibrated instruments. BMI was computed as weight (kg) divided by height squared (m²). The waist-to-hip ratio (WHR) was established by dividing waist circumference (cm) by hip circumference (cm). Blood pressure measurements were conducted after participants rested for 5 to 10min in a calm and comfortable environment. Measurements were obtained in a seated position, utilizing either a mercury sphygmomanometer or an electronic blood pressure monitor. Readings were alternated between the left and right arms, and the mean value was documented.

Detection of blood indicators

Fasting blood samples were routinely collected from all participants across two distinct days. The samples were analyzed within four hours of collection utilizing a Hitachi 7060 automatic biochemical analyzer. The following parameters were assessed: UA, serum creatinine (CREA), blood urea nitrogen (BUN), total triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C).

Extraction of total deoxyribonucleic acid (DNA) from blood and determination of concentration and purity

Fasting venous blood samples (2mL) were collected from both groups in the morning. Following a 30-min rest, 2mL of ethylenediaminetetraacetic acid (EDTA)-anticoagulated blood was utilized for DNA extraction with the BioTeke AU1001 nucleic acid extraction instrument. The extracted DNA was stored at −20°C for subsequent use. The purity and concentration of genomic DNA were evaluated using an ultraviolet spectrophotometer. DNA purity was deemed acceptable when the OD260/OD280 ratio ranged from 1.6 to 1.9.

Genotyping of ABCG2 gene rs2231142 locus in the whole blood samples from both groups

The target gene was amplified utilizing the polymerase chain reaction (PCR) technique. The upstream primer for ABCG2 mRNA was 5′-GAAAGCAACCATTTTTGACCATACACA-3′, while the downstream primer was 5′-GTGATGGGCACTCTGACGGTGA-3′, both synthesized by Genesky Biotechnology Inc. (Shanghai). The PCR reaction mixture comprised 1 μL DNA template, 5 μL PCR mix, 3 μL DNase-free water, and 1 μL Taqman probe, resulting in a total volume of 10 μL. The reaction conditions included an initial denaturation at 95°C for 3min, followed by 40 cycles of denaturation at 95°C for 15s, annealing at 65°C for 30s, and extension at 60°C for 1min. The quality of the amplification products was assessed via 2.0% agarose gel electrophoresis. Subsequent to purification, the PCR products were dispatched to Genesky Biotechnology Inc. (Shanghai) for genotyping of the ABCG2 gene rs2231142 locus employing the enhanced multiplex ligation detection reaction method.

Statistical methods

Statistical analyses were conducted utilizing R software version 4.2.1. Normally distributed quantitative data were represented as \(\overline{X}\) ± s, with group comparisons performed using t-tests. Categorical data were analyzed using X² tests. LASSO regression was employed to identify independent risk factors associated with HUA. Following this, multivariate logistic regression analysis (MLRA) was employed to investigate the relationship between HUA and the ABCG2 gene rs2231142 polymorphism, as well as the identified independent risk factors. Receiver operating characteristic (ROC) curves were subsequently utilized to evaluate the predictive accuracy of the risk factors for HUA. A p-value of < 0.05 was deemed statistically significant.

Baseline characteristics of the study population

A total of 3,382 cases were incorporated into this investigation. The HUA group demonstrated markedly elevated levels of BMI, WHR, systolic blood pressure, and diastolic blood pressure in comparison to the control group (P < 0.01). Furthermore, no statistically significant difference in age was detected between the two groups (P > 0.05). Nonetheless, the gender distribution across the groups was statistically significant (P < 0.001), with a greater proportion of males observed in the HUA group as opposed to females (62.3% > 37.7%). These findings are illustrated in Table 1.

Comparison of biochemical indicators

The SUA levels in the HUA group and the control group were recorded at 468.861 ± 81.726 and 239.239 ± 64.515μmol/L, respectively, indicating a statistically significant difference (P < 0.05). Additionally, other biochemical indicators, including glucose, BUN, CREA, TG, and LDL-C, were found to be markedly elevated in the HUA group when contrasted with the control group (P < 0.001). Conversely, TC and high-density lipoprotein cholesterol levels were observed to be lower in the HUA group (P = 0.01 and P < 0.01, respectively), as presented in Table 2. A comparison of the distribution of biochemical indicators between males and females within both groups revealed that BUN levels in males with HUA were lower than those in the control group, whereas TC levels were higher, although these differences did not reach statistical significance. This trend was reversed in females, as illustrated in Table 3.

Distributions of rs2231142 zygotes in different genders

The distribution frequency of rs2231142 heterozygotes(G/T) in the HUA group was found to be higher than that in the control group, whereas the distribution of homozygotes(G/G and T/T) exhibited an opposing trend, with statistically significant differences observed (P < 0.05), as presented in Table 4. In the male groups, the distribution frequencies of rs2231142 heterozygotes were recorded at 54.9% and 45.1% for the HUA and control groups, respectively, while homozygotes exhibited frequencies of 47.8% and 52.2%, respectively, with markedly higher distribution frequency of heterozygotes in the HUA group. In the female HUA group, the distribution frequency of rs2231142 heterozygotes was noted as 49.3%, which surpassed the frequency of homozygotes (41.6%) within the same group, yet was lower than the heterozygote distribution frequency in the control group (50.7%). It can be inferred that irrespective of gender, the distribution frequencies of rs2231142 heterozygotes and homozygotes between the HUA and control groups were statistically significant (P < 0.01).

Distribution of rs2231142 in HUA populations of different genders

Based on the differences in zygote types, further analysis was conducted for each genotype in different genders. The Hardy–Weinberg equilibrium test confirmed that the genotype distribution adhered to Hardy–Weinberg equilibrium (P > 0.05), indicating that the study participants were representative of the population and appropriate for genetic marker analysis. The distribution of single nucleotide polymorphism (SNP) genotypes and allele frequencies in HUA populations across different genders is illustrated in Table 5. In the male group, the frequencies of ABCG2 rs2231142 genotypes G/G, G/T, and T/T in the HUA group were recorded as 60.3%, 35.5%, and 4.3%, respectively, revealing significant differences when compared to the control group (P < 0.05). In the female group, the distribution of ABCG2 rs2231142 genotypes also displayed statistically significant differences between the HUA and control groups (P < 0.001), with the frequency of the T/T genotype in the HUA group (5.8%) being markedly higher than that in the control group.

The frequencies of G and T alleles exhibited variations between the disease and control groups for both genders. The distribution frequency of the T allele in the HUA population was found to be markedly higher than that in the control group, recorded at 22% and 23.8% for males and females, respectively, compared to 19.2% and 16.9% in the control group. Conversely, the distribution frequency of the G allele in the HUA population was observed to be lower than in the normal population, with frequencies of 78% and 76.2% for males and females, respectively, compared to 80.8% and 83.1% in the normal male and female groups.

Comparison of serum BUN and CREA levels among different genotypes at rs2231142 locus

Among HUA patients, male homozygous T/T carriers exhibited an average CREA level of 87.051 ± 36.378μmol/L, which was markedly higher than that of homozygous G/G and heterozygous G/T carriers. In females, the highest CREA levels were observed in heterozygous G/T carriers. Nevertheless, these differences were not statistically significant (P = 0.673 and 0.122, respectively) (Table 6). In the population with normal SUA levels, both male and female heterozygous G/T carriers demonstrated elevated average CREA levels compared to other genotypes, while BUN levels remained relatively stable. This finding suggests that the T allele mutation at the rs2231142 locus may be linked to increased CREA levels.

Risk factor analysis for HUA

Based on the baseline characteristics, biochemical indicators, and rs2231142 genotypes of the studied population, seven independent risk factors for HUA were identified through multiple logistic regression analysis (MLRA). These factors encompass WHR, BUN, TG, TC, LDL-C, and the rs2231142 G/T and T/T genotypes (Table 7). The findings reveal that for each unit increase in WHR, BUN, TG, and LDL-C, the likelihood of developing HUA increases by 1.794, 1.166, 1.421, and 1.286 times, respectively. Furthermore, the risk of HUA is markedly associated with the rs2231142 G/T and T/T genotypes. Individuals carrying the rs2231142 G/T mutation demonstrate a 1.192-fold higher probability of developing HUA compared to those lacking the mutation, whereas individuals with the rs2231142 T/T mutation face an even greater risk, 2.557 times that of the non-mutated population. A diagnostic model for HUA was developed utilizing these risk factors, and its performance was assessed through the ROC curve. The area under the curve (AUC) was determined to be 74.8% (Fig.1), suggesting that the model incorporating the rs2231142 locus can effectively differentiate between affected and healthy populations.

HUA is a condition defined by elevated SUA levels, which arise from disorders in purine metabolism that result in a supersaturated state of urate within the extracellular fluid. This state can precipitate gout and UA nephropathy¹³. With advancements in the Human Genome Project and comprehensive investigations into gene polymorphisms, it has become increasingly apparent that specific genetic backgrounds may be linked to various human diseases. SNPs, representing variations in gene sequences and lengths, serve as significant determinants of disease susceptibility, phenotypic expression, and variations in treatment responses¹⁴. The development of HUA is influenced by multiple factors, including genetic interactions, environmental conditions, and lifestyle choices^15,16, with genetic components contributing approximately 40% to 70% to the overall risk¹⁷. Consequently, the identification of primary susceptibility genes associated with HUA could provide valuable insights for early molecular diagnosis and targeted interventions for patients with HUA and gout in the future.

As more UA transport proteins and genes are identified, their significant roles have become increasingly evident. Abnormal expression of these proteins and genes may result in heightened UA reabsorption or diminished excretion, thereby precipitating HUA¹⁰. ABCG2 serves as a transport protein that serves a vital function in UA excretion and is extensively distributed in the brush border membrane of renal proximal tubules, the apical membrane of intestinal epithelial cells, and hepatic cells. Mutations in this gene markedly influence SUA levels in humans and exhibit a strong association with HUA and gout^18,19. Dysfunction of ABCG2 is known to elevate the risk of developing gout and HUA^20,21. Compared to other urate transporters, the ABCG2 gene harbors the highest number of SNP sites, with over 40 having been identified thus far. Notably, the mutation at the rs2231142 site is particularly significant regarding its effect on HUA^21,22.

The findings of this study demonstrate that, for both male and female participants, the allele frequency distribution of the ABCG2 gene rs2231142 genotypes G/G, G/T, and T/T in the HUA group exhibited statistically significant differences compared to the control group. Importantly, the frequencies of the G/T and T/T genotypes were substantially elevated in the disease group relative to the control group. Furthermore, the distribution frequency of the T allele was higher in the HUA population than in the control group. This observation implies that the mutations at the ABCG2 gene rs2231142 (G/T and T/T) loci are linked to HUA, with the T allele potentially acting as a risk factor for its development. To further substantiate this hypothesis, MLRA was utilized to identify the primary risk factors associated with HUA. The results indicated that individuals possessing rs2231142 G/T and T/T mutations faced an increased risk of developing HUA, quantified at 1.192 and 2.557 times, respectively, compared to those without mutations. The current data reinforce the notion that carrying the rs2231142 T allele elevates the risk of HUA among both genders, aligning with findings from other studies conducted within Asian populations^23,24,25. Li et al.²³ reported that elevated UA in the Liangshan population of China was related to the T allele at the rs2231142 locus, and people carrying the rs2231142 T allele were more likely to develop hyperuricemia. This had also been confirmed in another study, where populations with G/T and T/T genotypes had a higher risk than those with G/G genotype, and the interaction between BMI and ABCG2 rs2231142 T allele increased the risk of HUA²⁵. Nevertheless, BMI was not a high-risk factor for hyperuricemia in our study, so no interaction study was conducted between the both.

In contrast to previous studies, the present research incorporated seven independent risk factors: rs2231142 G/T and T/T, WHR, BUN, TG, TC, and LDL-C to establish a diagnostic model for HUA. The model’s efficacy was assessed utilizing the ROC curve, which indicated an AUC of 74.8%. This finding suggests that the model, which includes the rs2231142 T allele, exhibits a notable diagnostic capability for the early prediction of HUA. Additionally, it was noted that the frequencies of T/T genotype within the female HUA and control population were 5.8% and 2.3%, respectively, the difference between both surpassing observed in the male HUA and control group (4.3% and 4.6%). This observation implies that the mutation of the rs2231142 T allele may exert a more pronounced influence on the female group compared to their male counterparts.

Approximately two-thirds of UA within the human body is eliminated through the kidneys, whereas the remaining one-third is excreted via the intestinal tract, thereby establishing the kidneys as an essential organ for UA excretion²⁶. Persistent elevations in UA levels may result in kidney damage due to the inflammatory characteristics of UA and the formation of urate crystals. These mechanisms can activate the renin–angiotensin–aldosterone system and decrease E-cadherin expression, leading to renal vascular endothelial injury and renal fibrosis^27,28, ultimately compromising kidney function. In the current study, it was noted that individuals diagnosed with HUA exhibited markedly elevated levels of CREA and BUN, which are indicators of renal function, in comparison to the normal population (Table 2). Female patients with HUA presented statistically significant differences in CREA and BUN levels relative to the normal population (Table 3), while male patients displayed a significant difference only in CREA levels (Table 3). These findings indicate that heightened SUA levels may influence kidney function in individuals with early-stage HUA. Moreover, it was found that male HUA patients possessing the rs2231142 T/T genotype exhibited the highest CREA levels. This observation can be ascribed to the expression of the ABCG2 gene within the apical membrane of proximal tubular epithelial cells in the kidney, where it serves a function in UA secretion and transport. Consequently, dysfunction of ABCG2 may diminish tubular UA excretion, resulting in an increased relative risk of HUA and a concurrent decline in CREA clearance.

This study further examined the potential etiologies and risk factors that influence HUA. An association was identified between the rs2231142 T allele polymorphism of the ABCG2 gene and susceptibility to HUA. Individuals possessing the rs2231142 T allele demonstrated a higher likelihood of developing HUA, with this tendency appearing to be more pronounced among female populations. A model integrating the rs2231142 T allele with relevant clinical risk factors may serve for the early prediction of HUA occurrence, indicating notable diagnostic efficacy. Furthermore, the mutation at the rs2231142 locus of the ABCG2 gene could contribute to the reduction of CREA clearance.

Author notes

1. Meiting Liang and Xingxing Liu contributed equally to this work.

Authors and Affiliations

1. Department of Pathology, School of Basic Medical Sciences, XinJiang Second Medical College, Karamay, 834000, China

   Meiting Liang,Meng Sun,Jun Zhu,FuRong Jing&Jingyi Shen

2. Department of Preventive Medicine, Medical College, Tarim University, Alar, 843300, China

   Meiting Liang&Yongsheng Li

3. Laboratory and Equipment Management Center of Xinjiang Second Medical College, Karamay, 834000, China

   Xingxing Liu

4. Department of Laboratory Medicine, Fifth Affiliated Hospital of Xinjiang Medical University, Ürümqi, 830011, China

   Shanshan Yang

5. Department of Cell and Genetics, Xinjiang Second Medical College, Karamay, 834000, China

   Yi He

6. Department of Morphological Center, School of Basic Medical Sciences, Xinjiang Medical University, Ürümqi, 830017, China

   Wujin Chen

7. Departent of Microbiology, School of Basic Medical Sciences, Xinjiang Medical University, Ürümqi, 830017, China

   Yuping Sun

8. Key Laboratory of Xinjiang Uygur Autonomous Region, Laboratory of Molecular Biology of Endemic Diseases, Ürümqi, 830017, China

   Yuping Sun

9. State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Ürümqi, 830017, China

   Yuping Sun

Contributions

(I) Conception and design: ML, YS. (II) Administrative support: XL, WC. (III) Provision of study materials or patients: SY, FJ. (IV) Collection and assembly of data: MS, JZ, JS. (V) Data analysis and interpretation: YH, YL. (VI)Manuscript writing: all authors. (VII) Final approval of manuscript: all authors. All authors contributed to the article and approved the submitted version.

Corresponding authors

Correspondence to Yuping Sun or Yongsheng Li.

Competing interests

The authors declare no competing interests.

Ethics statement

The human participants involved in the research have been reviewed and approved by the Medical Ethics Committee of the First Affiliated Hospital of Xinjiang Medical University (No. K202105-08).

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