Introduction

Epilepsy is one of the most common neurological disorders which affects over 70 million people globally and imposes a considerable socio-economic burden [1,2,3]. The etiology of epilepsy is diverse and remains elusive [4]. Among various factors, genetic mutations, such as single-nucleotide polymorphisms (SNPs), are a common cause of epilepsy and are generally associated with ion channels, neuronal receptors, transcription factors, and enzymes [5,6,7,8. Accumulating evidence has shown that purinergic signaling SNPs, including adenosine kinase SNPs, adenosine A1 receptor SNPs, and adenosine A2A receptor SNPs, are implicated in the pathogenesis mechanism of epilepsy [9,10,11]. However, purinergic signaling is a big family. It includes purines (ATP, ADP, AMP, adenosine), enzymes (CD39, CD73), and purinergic receptors (four P1 receptors, seven P2X receptors, and eight P2Y receptors). Moreover, purinergic signaling has been recognized as promising targets for the treatment of various central nervous system (CNS) diseases [12,13,14,15,Statistical analysis

All statistical analyses were conducted with SPSS v26.0 software (Chicago, IL, USA). Categorical variables of baseline characteristics were performed as proportions and continuous variables as medians with interquartile ranges. Differences in the demographic characteristics between the two groups were analyzed by the non-parametric independent-samples Wilcoxon signed-rank test for continuous variables and the chi-square test for categorical data. The chi-square test was used to assess the deviation from Hardy–Weinberg equilibrium. The chi-square statistics or Fisher’s exact test was used to compare the statistical differences in genotype distributions and allele frequencies between cases and controls. The odds ratio (OR) was calculated with 95% confidence intervals (CIs). Statistical significance was defined as two-tailed p < 0.05.

Results

Clinical characteristics of the study population

A total of 200 PWEs participated in the study, with 192 of them satisfactorily genotyped for both SNPs. A total of 16 participants were removed from the study due to a lack of clinical data. Therefore, our study included 176 PWEs (85 males, 91 females; median age: 29 years) and 50 healthy controls (22 males, 28 females; median age: 26 years). There was no statistically significant difference between epileptic patients and healthy controls in terms of gender. Table 1 demonstrates the demographic and clinical characteristics of the study population.

Table 1 Demographic and clinical characteristics of the study population
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Associations of the P2Y12R gene polymorphisms with epilepsy

Table 2 shows the genotypes or alleles of the two SNPs (rs1491974 and rs6798347) in PWEs and controls. Subsequently, we stratified the groups by gender, neuroimaging, epileptic seizure frequency, and treatment response (Tables 3, 4, 5, and 6). Our results demonstrated that the frequency of the rs1491974 G allele was significantly higher among all patients than in healthy controls (OR = 0.576, 95% CI = 0.368–0.901, p = 0.015 for A vs. G). We also found the distribution of the G allele of epileptic patients with negative intracranial imaging was significantly higher than that of the healthy individuals (OR = 0.600, 95% CI = 0.369–0.975, p = 0.038 for A vs. G). These results illustrated those individuals with the G allele of rs1491974 G>A might have higher risks for epilepsy. After separating the groups by gender, the differences appeared to be limited to healthy controls and female patients (p = 0.004 for genotype; p = 0.001 for allele). In female patients, we found the GG genotype frequency was markedly higher than that of the controls (OR = 3.450, 95% CI = 1.204–9.883, p = 0.017 for GG vs. AA/AG), indicating that the GG genotype of P2Y12R rs1491974 may be closely related to epilepsy susceptibility in females. Subgroup analyses were also conducted stratified for epileptic seizure frequency. We found the homozygous AA and GG genotypes were associated with a lower risk of frequent seizures for patients, while the heterozygous AG genotype was related to a higher risk (OR = 0.476, 95% CI = 0.255–0.890; p = 0.019 for AA/GG vs. GG). Additionally, we did not detect a significant association between rs1491974 and rs6798347 with the P2Y12R gene and treatment response.

Table 2 Genotypic and allelic distribution of the P2Y12R gene between all patients and controls
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Table 3 Genotypic and allelic distribution of the P2Y12R gene between patients with negative intracranial imaging and controls
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Table 4 Genotypic and allelic distribution of the P2Y12R gene between all patients and controls in different genders
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Table 5 Genotypic and allelic distribution of the P2Y12R gene between patients with epileptic seizure frequencies < 2 times/year and patients with epileptic seizure frequencies ≥ 2 times/year
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Table 6 Genotypic and allelic distribution of the P2Y12R gene between drug-resistant patients and drug-responsive patients
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For the P2Y12R rs6798347 G>A polymorphism, the frequency of the G allele was substantially greater in all patients than in the healthy controls (OR = 0.603, 95% CI = 0.367–0.988, p = 0.043 for A vs. G). Comparing PWEs with negative intracranial imaging and healthy controls, there were no variations in allelic or genotypic distribution. In addition, after grou** by gender, epileptic seizure frequency, and treatment response, we discovered that there were no significant differences between PWEs and controls.

Discussion

The results of the present study showed a significant difference in the G allele frequency of P2Y12R rs1491974 and rs6798347 polymorphisms between PWEs and healthy participants, indicating that P2Y12R genetic variability might be associated with epilepsy. Consistent with our result, animal studies have shown that P2Y12R-deficient mice had exacerbated behavioral seizures after intraperitoneal kainic acid injection and the percentage of mice showing seizures increased by inactivating the P2Y12R gene [24],[48,49]. Interestingly, our findings indicated the G allele or GG genotype of rs1491974 (G>A) was more predominant in female patients with epilepsy than in their control counterparts, whereas no significant differences were shown in males. A potential explanation for the disparity may involve the differences in endogenous sex hormones, such as androgen, estrogen, and progesterone, as well as their metabolites, which play a vital role in brain network construction and neuro-immune system activity [50]. This agrees with the findings of Wang et al. [51] and [52], who discovered that gender-specific incidence was higher for male partial seizures than for females in NLRP1 SNPs (rs878329, G>C) and NRG1 SNPs (rs35753505, T>C). We also observed an increased seizure frequency in individuals with the AG genotype of P2Y12R rs1491974. Overall, our findings suggest that P2Y12R gene variants influence some characteristics of expression in epilepsy patients. In addition, though our results suggest that P2Y12R gene polymorphisms do not correlate with the response to antiepileptic drugs, this still requires further investigation.

Our study is not without limitations. First, we only analyzed the population in southern China and lack representation from other regions of the country. Future studies should involve patients from the greater China region. Second, the SNPs of P2Y12R have not been reported in epilepsy. Hence, the discussion concerning the SNPs of P2Y12R is limited. Further validation and studies are necessary to confirm the relationship between P2Y12R and epilepsy. Third, this study was confined to the association of SNPs with epilepsy and lacked specific epileptic subtypes due to the limited sample size. Thus, more research is warranted to improve our understanding of the association between P2Y12R and the pathophysiology of epilepsy.