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A functional polymorphism of the microRNA-146a gene is associated with susceptibility to drug-resistant epilepsy and seizures frequency
Seizure 27 (2015) 60–65
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A functional polymorphism of the microRNA-146a gene is associated with susceptibility to drug-resistant epilepsy and seizures frequency Lili Cui a,1, Hua Tao a,b,1, Yan Wang c,1, Zhou Liu a,b, Zhien Xu b, Haihong Zhou b, Yujie Cai a, Lifen Yao d, Beichu Chen b, Wandong Liang e, Yu Liu b, Wanwen Cheng b, Tingting Liu b, Guoda Ma a, You Li a, Bin Zhao a,**, Keshen Li a,* a
Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China Institute of Neurology, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China c Clinical Research Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China d Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China e Renji College, Wenzhou Medical University, Wenzhou, China b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 1 November 2014 Received in revised form 27 February 2015 Accepted 28 February 2015
Purpose: Epilepsy is the third most common chronic brain disorder and is characterized by an enduring predisposition for seizures. Recently, a growing body of evidence has suggested that microRNA-146a (miR-146a) is upregulated in the brains of epilepsy patients and of mouse models; furthermore, miR146a may be involved in the development and progression of seizures through the regulation of inflammation and immune responses. In this report, we performed a case–control study to analyze the relationship between the two potentially functional single nucleotide polymorphisms (SNPs) of the miR146a gene (rs2910464 and rs57095329) and the risk of epilepsy in a Chinese population comprising 249 cases and 249 healthy controls. Method: Our study comprised 249 epilepsy patients and 249 healthy controls in two regions of China. The DNA was genotyped using the ABI PRISM SNapShot method. The statistical analysis was estimated using the chi-square test or Fisher’s exact test. Results: Our results indicated a significant association between the rs57095329 SNP of the miR-146a gene and the risk of drug resistant epilepsy (DRE) (genotypes, p = 0.0258 and alleles, p = 0.0108). Moreover, the rs57095329 A allele was found to be associated with a reduced risk of seizures frequency in DRE patients (all p < 0.001). However, the rs2910164 variant was not associated with epilepsy. Conclusion: Our data indicate that the rs57095329 polymorphism in the promoter region of miR-146a is involved in the genetic susceptibility to DRE and the seizures frequency. ß 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Keywords: Polymorphism MicroRNA-146a Drug-resistant epilepsy Seizures frequency
1. Introduction Epilepsy is a common, serious neurological disorder characterized by recurring unprovoked seizures that result from the abnormal firing of populations of neurons in the brain [1]. Although
* Corresponding author at: Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Guangdong Medical College, 57 Ren-min Avenue, Xiashan District, Zhanjiang 524001, PR China. Tel.: +86 07592386772; fax: +86 07592386772. ** Corresponding author at: Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Guangdong Medical College, 57 Ren-min Avenue, Xiashan District, Zhanjiang 524001, PR China. Tel.: +86 07592387677; fax: +86 07592387677. E-mail addresses: [email protected] (B. Zhao), [email protected] (K. Li). 1 These authors contributed equally to this work.
the exact molecular pathogenic mechanism of epilepsy remains unclear, increasing evidence shows that the persistent upregulation of inflammatory gene expression contributes to the etiopathogenesis of epilepsy [2,3]. Additionally, inflammatory mediators such as interleukin (IL)-1b, Toll-like receptors (TLRs), and other factors are involved in the development of epilepsy in experimental animal models and in patients [4,5]. MicroRNAs (miRNAs) are a family of small, endogenous noncoding RNAs that post-transcriptionally regulate target gene expression to control most aspects of biological processes, including innate and adaptive immune responses [6–8]. Abnormal miRNA expression has also been observed in different diseases associated with inflammatory and immune processes [9–11]. One miRNA that attracted our attention was miRNA-146a (miR-146a),
http://dx.doi.org/10.1016/j.seizure.2015.02.032 1059-1311/ß 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
L. Cui et al. / Seizure 27 (2015) 60–65
which is well known for its important regulation of the TLR signaling pathway and of proinflammatory cytokines such as IL-1b and TNF-a [12–14]. Recently, increasing evidence has shown that miR-146a is upregulated in epilepsy mouse models and epilepsy patients [15–18], suggesting that miR-146a may operate as an important epigenetic regulator involved in the pathogenesis of epilepsy. Single nucleotide polymorphisms (SNPs) could influence the function or the expression of genes and be associated with the risk of disease. Two SNPs in the miR-146a gene, rs2910164 and rs57095329, have functional importance: they modify the expression level of mature miR-146a [19,20] and are associated with many inflammation-associated diseases such as systemic lupus erythematosus [19], Behc¸et’s disease [20] ulcerative colitis [21], sepsis [22] and asthma [23]. To the best of our knowledge, no studies have examined the association between the rs57095329 SNP and epilepsy, and only one study on the association between one SNP (rs2910164) and the risk of temporal lobe epilepsy (TLE) has been performed in a primarily Caucasian population [24]. Until now, no similar studies have been performed in Asian populations. In the present study, we conducted a case–control study to determine the association between these two functional SNPs of miR-146a (rs2910164 G>C and rs57095329 A>G) and epilepsy in an ethnically homogeneous Chinese population. Moreover, the potential associations between the miR-146a polymorphisms and clinical variables such as TLE/no-TLE, drugresponsiveness/resistance and seizure frequency were also examined. 2. Materials and methods 2.1. Clinical data of epilepsy patients and healthy controls Our study comprised 249 epilepsy patients (female 112; male 137; mean age: 26.5 15.2 years) and 249 healthy controls (female 94; male 155; mean age: 50.1 16.7 years). The epilepsy patients were recruited from two regions of China: the Department of Neurology of the Affiliated Hospital of Guangdong Medical College of southern China (134 patients and 137 controls) and the Department of Neurology of the first Affiliated Hospital of Harbin Medical University of northern China (115 patients and 112 controls). All of the patients were diagnosed and classified by experienced neurologists following the criteria of the International League Against Epilepsy [25]. Information such as the clinical history, electroencephalography (EEG) and magnetic resonance imaging (MRI) data was recorded for all patients. Patients and healthy controls with mental retardation were excluded as well as all of the healthy control subjects who had a history of seizures. The study was conducted in accordance with the Declaration of Helsinki, and written informed consent was obtained from all of the enrolled participants. This study was approved by the Ethics Committees of both the Affiliated Hospital of Guangdong Medical College and the first Affiliated Hospital of Harbin Medical University. Patients were divided into two groups, according to treatment, as drug responsive and drug resistant. Drug responsiveness was determined from clinical records. A drug response was defined as freedom from seizures or a 50% or greater reduction in the seizure frequency for at least one year during treatment with antiepileptic drugs (AEDs). Drug resistance was defined as no change or less a than 50% reduction in the seizure frequency for at least one year with two or more appropriate AEDs at maximally tolerated therapeutic doses. Patients who underwent epilepsy surgery for refractory epilepsy were classified as having drug-resistant epilepsy, regardless of their postoperative seizure control status. Moreover, the seizure frequencies of drug-resistant epilepsy (DRE) patients were followed up and recorded. Twenty-three patients
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were excluded because their seizure frequency data with follow up included less than 6 months or because the patients underwent epilepsy surgery within the previous 6 months. Finally, a total of 52 patients were included in these statistics and were divided into groups according to their seizure frequencies, as follows: less than 5 times/month, more than 5 times/month, more than 10 times/ month and more than 30 times/month. 2.2. Genotyping A 2-mL venous blood sample was taken for DNA extraction and genotyping. Genomic DNA was isolated from peripheral blood samples using a blood Genomic DNA Extraction Kit (Tiangen, China). DNA was genotyped using the ABI PRISM SNapShot method (Applied Biosystems, Foster, CA). The PCR primers used for the rs2910164 SNP were as follows: forward primer 5-GAACTGAATTCCATGGGTTG-3 and reverse primer 5-CACGATGACAGAGATATCCC3. The primers used for the rs57095329 SNP were as follows: forward primer 5-TCATTGGGCAGCCGATAAAG-3 and reverse primer 5-AGGAAGTTCTGGTCAGGCG-3. The assay conditions were in accordance with manufacturer’s protocols. Fluorescence outputs were quantified in real time by using a 7500HT Fast Real Time PCR System (Applied Biosystems, Carlsbad, CA). For quality control, random duplicate samples (5%) were run for each sequence analysis. 2.3. Statistical analysis All analyses were performed using SPSS version 19.0 (IBM, NY, USA). Genotype and allele frequencies distributions in the groups were counted and estimated using the chi-square test or Fisher’s exact test. Deviation of the genotype or allele frequency was assessed using Hardy–Weinberg equilibrium (HWE). The odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the correlation between the miR146a genotype and epilepsy. The data are presented as percentage frequencies or the means SD. Two-tailed p values <0.05 were considered to be statistically significant. 3. Results 3.1. Clinical characteristics The demographic characteristics of our subjects are shown in Table 1. In total, 249 epilepsy patients and 249 healthy controls, who were matched with case subjects according to sex, ethnicity and geographic location of origin, were recruited in our study. Among the cases, 174 patients were classified as TLE, and 75 patients were classified as non-TLE. No significant differences in the age and sex distributions between TLE patients and non-TLE patients were found. Additionally, the average seizure onset age was 19.42 14.38 years, and no statistically significant difference
Table 1 Clinical and demographic data of epileptic patients. Characteristics
Epilepsy patients (N = 249)
TLE patients (N = 174)
Non-TLE patients (N = 75)
Controls (N = 249)
Age (mean years SD) Gender (male/ female) Age at epilepsy onset (mean years SD)
26.5 15.2
26.33 14.29
27.07 16.79
50.1 16.7
137/112
95/79
42/33
155/94
19.42 14.38
19.68 13.31
18.87 16.55
–
L. Cui et al. / Seizure 27 (2015) 60–65
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Table 2 Distribution of miR146a gene polymorphisms between epilepsy patients and healthy controls. RS2910164
All
CC (%)
CG (%)
GG (%)
p-Value
C (%)
G (%)
p-Value
OR (95% CI)
CASE TLE No-TLE Control
249 174 75 249
98 66 32 97
120 85 35 106
31 23 8 46
0.1500 0.2649 0.2823 –
316 217 99 300
182 131 51 198
0.3279 0.5666 0.2144 –
1.146 (0.8872–1.480) 1.093 (0.8250–1.449) 1.281 (0.8738–1.878) –
(39.4) (37.9) (42.7) (39.0)
(48.2) (48.9) (46.7) (42.6)
(12.4) (13.2) (10.7) (18.5)
(63.5) (62.4) (66.0) (60.2)
(36.5) (37.6) (34.0) (39.8)
RS57095329
All
AA (%)
GA (%)
GG (%)
p-Value
A (%)
G (%)
p-Value
OR (95% CI)
CASE TLE No-TLE Control
249 174 75 249
163 110 53 155
79 59 20 86
7 5 2 8
0.7539 0.9677 0.4099 –
405 279 126 396
93 69 24 102
0.5230 0.8620 0.2413 –
1.122 (0.8199–1.535) 1.042 (0.7399–1.466) 1.352 (0.8302–2.203) –
(65.5) (63.2) (70.7) (62.2)
(31.7) (33.9) (26. 7) (34.5)
(2.8) (2.9) (2.7) (3.2)
was observed in the mean epilepsy onset age in patients in the TLE and non-TLE subgroups. 3.2. Genotype and allele frequency distributions in epilepsy patients and controls All of the enrolled subjects were successfully genotyped for the rs2910164 and rs57095329 SNPs, and the association between the genotype and the risk of epilepsy was analyzed using the chisquare test. The deviation from Hardy–Weinberg equilibrium for the polymorphisms examined was not found in the distributions of genotypes in the patients and controls (all p > 0.05, data not shown). The genotype and allele frequencies of miR-146a polymorphisms in the studies are shown in Table 2. For rs2910164, neither the genotype nor the allele showed significant differences between the epilepsy patients and the controls (genotypes p = 0.1500 and alleles p = 0.3279, respectively), and no significant difference was observed in the TLE group (genotypes p = 0.2649 and alleles p = 0.5666) or no-TLE groups (genotypes p = 0.2823 and alleles p = 0.2144) (Table 2). Similarly, we also did not observe a significant difference in the genotype or allele frequencies between the patients and controls for the rs57095329 SNP (epilepsy patients: genotypes p = 0.7539 and alleles p = 0.5230; TLE patients: genotypes p = 0.9677 and alleles p = 0.8612; no-TLE patients: genotypes p = 0.4099 and alleles p = 0.2413). Additionally, as shown in Table 3, there was no statistically significant difference in the mean age of onset of epilepsy in patients with an miR-146a polymorphism (genotype for rs2910164: p = 0.253; genotype for rs57095329: p = 0.196). We further performed haplotype-based association analyses of rs2910164 and rs57095329. However, no significant associations were observed between these haplotypes and epilepsy (Table 4).
(81.3) (80.2) (84.0) (79.5)
(18.7) (19.8) (16.0) (20.5)
p = 0.0258 and alleles p = 0.0108), and the patients carrying the miRNA-146a rs57095329 A allele had a lower risk of DRE, indicating that the rs57095329 SNP could be a risk factor for DRE. 3.4. Genotype and allele frequency distributions of miR-146a polymorphisms among DRE patients We collected the DRE patients with relatively stable seizure frequencies and with full clinical data with at least one year followup. A total of 52 DRE samples with relatively stable seizure frequency data were recruited for the association analysis between miR-146a polymorphisms and the seizure frequency. Among the 52 DRE patients, 31 patients had a seizure frequency of less than 5 times/month, 21 patients had a seizure frequency of more than 5 times/month, 16 patients had the seizure frequency of more than 10 times/month, and 7 patients had a seizure frequency of more than 30 times/month (Table 6). We analyzed the genotype and allele frequency distributions among DRE patients, and the results are shown in Fig. 1. The rs2910164 polymorphism showed no significant association with the seizure frequency of the DRE patients. However, the rs57095329 A allele was observed with a trend of reducing the seizure frequency in DRE patients (all p < 0.001), indicating that rs57095329 in the promoter region of miR-146a was a risk factor for the seizure frequency of DRE patients. 4. Discussion
The distribution of miR-146a genotypes was further analyzed in DRE patients and healthy controls. As shown in Table 5, the rs2910164 SNP showed no significant association with DRE patients. However, rs57095329 showed a significant association in the DRE group compared with the controls (genotypes
Despite extensive research, the mechanisms underlying the cause and progression of epilepsy remain unclear. In recent years, increasing evidence has supported the hypothesis that inflammatory processes within the epileptic brain might constitute a common and crucial mechanism in the pathology of seizures [26,27]. In the brain tissue of patients with DRE, several proinflammatory cytokines have been detected [28,29], and in animal models, the inflammatory mechanisms are also intimately connected with the generation of seizure onset [30]. Importantly, although controversial, several pieces of clinical evidence indicated that steroids and other anti-inflammatory treatments have anticonvulsant properties in DRE patients [31,32], supporting the view that the effects on neuroinflammation may influence the
Table 3 Distribution of miR146a gene polymorphisms of onset age in epilepsy patients.
Table 4 The haplotype of miR146a polymorphisms between cases and controls.
3.3. Genotype and allele frequency distributions of miR-146a polymorphisms between DRE patients and controls
rs2910164
CC
GC
GG
p-Value
Onset age
20.89 14.88
18.73 14.36
17.24 13.03
0.2531
rs57095329
AA
GA
GG
p-Value
Onset age
20.80 15.25
16.88 12.30
20.13 12.26
0.1968
rs2910164– rs57095329
Case
Control
OR (95% CI)
p-Value
CA AG GG
313 86 99
306 94 98
1 0.894 (0.6420–1.247) 0.988 (0.7166–1.361)
– 0.5100 0.9393
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Table 5 Distribution of miR146a gene polymorphisms between DRE patients and controls. rs2910164
CC (%)
GC (%)
GG (%)
p-Value
C (%)
G (%)
p-Value
OR (95% CI)
Drug-resistant Control
31 (41.3) 97 (40.0)
33 (44.0) 106 (42.6)
11 (14.7) 46 (18.5)
0.6501 –
95 (63.3) 300 (60.2)
55 (36.7) 198 (39.8)
0.5059 –
1.1400 (0.7815–1.663) –
rs57095329
AA (%)
GA (%)
GG (%)
p-Value
A (%)
G (%)
p-Value
OR (95% CI)
Drug-resistant Control
34 (45.3) 155 (62.2)
36 (48.0) 86 (34.5)
5 (6.7) 8 (3.2)
0.0258 –
104 (69.3) 396 (79.5)
46 (30.7) 102 (20.5)
0.0108 –
0.5823 (0.3866–0.8773) –
Table 6 Distribution of the seizure frequency in DRE patients. Seizure frequency rs2910164 CC GC GG p-Value C allele G allele p-Value OR (95% CI) rs57095329 AA GA GG p-Value A allele G allele p-Value OR (95% CI)
<5 times/month (N = 31)
>5 times/month (N = 21)
>10 times/month (N = 16)
>30 times/month (N = 7)
11 15 5
6 12 3 0.8206 24 18 0.8409 0.9009 (0.4070–1.994)
5 10 1 0.5333 20 12 0.8272 1.126 (0.4683–2.708)
2 5 0 0.4097 9 5 1 1.216 (0.3643–4.060)
10 5 6 0.0051 25 17 0.0008 0.1872 (0.06890–0.5085)
7 5 4 0.0072 19 13 0.0026 0.1860 (0.06465–0.5352)
2 2 3 0.0005 6 8 0.0006 0.0955 (0.02552–0.3570)
37 25 – –
24 7 0 55 7 – –
generation and exacerbation of epilepsy. MiR-146a is well known as a powerful innate immune- and pro-inflammatory-related regulator in immune and inflammatory responses. MiR-146a has been reported to be abnormally upregulated in several diseases [33–35]. Recently, miRNA expression profiling assays of samples under epilepsy conditions showed that miR-146a was significantly upregulated in the hippocampus both of a TLE rat model and of epilepsy patients [15,16], and miR-146a also interacts with IL-1b levels at different stages of epilepsy [14]. These findings inspired us to examine the relationship between miR-146a and epilepsy. In this case–control study, two functional SNPs in miR-146a (rs2910164 and rs57095329) were selected to evaluate the association between miR-146a polymorphisms and the risk of epilepsy. The rs2910164 G/C polymorphism, which is located in the stem region of precursor-miR146a and could disturb the
expression of mature miR-146a through mismatching with the stem structure, has been associated with several diseases [21,36,37]. The rs57095329 polymorphism, which is located in the miR-146a promoter, was recently found to influence mature miR-146a levels by altering the binding affinity of miR-146a for VEts oncogene homologue 1 (Ets-1), thereby possibly contribute to disease susceptibility [19]. Our previous study also confirmed that both of the 2 functional SNPs of miR-146a could influence the expression levels of miR-146a in vitro [11]. However, in the present study, only rs57095329 was associated with DRE susceptibility. Why these two functional SNPs of miR-146a, which can both influence miR-146a expression, show different correlations with epilepsy in our association study remains unknown. Because epilepsy is a complex disease that is associated with multiple genetic and environmental factors, we inferred that the
Fig. 1. Distribution of different seizures frequency in DRE patients with rs2910164 and rs57095329 allele of miR146a.
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functional rs2910164 SNP may have a limited capacity to alter the susceptibility to epilepsy because it could only disturb miR-146a expression by influencing the stem structure of precursor miR146a. Nevertheless, rs57095329 is located in the promoter region of miR-146a. Thus, the effect of this SNP on the miR-146a expression level relies mainly on Ets-1. Notably, Ets-1 is widely expressed in the cortex and hippocampus and is upregulated in Alzheimer’s disease, in which the inflammatory response is one of the important pathological features [38], suggesting that rs57095329 may have a potential function on the miR-146a expression due to the high level of Ets-1 in the brain when inflammation occurs such as in epilepsy. However, the effects of rs57095329 and rs2910164 on miR-146a expression in the epileptic brain require further study. Another novel finding was that our statistical data showed a connection between the rs57095329 A allele and the reduced seizure frequency. Recently, increasing evidence suggested that miR-146a may play a more important role before the onset of seizures. E. Aronica and coworkers observed a prominent upregulation of miR-146a in a mouse model at 1 week after status epilepticus; furthermore, this upregulation persisted into the chronic phase [15]. This finding was supported by another study, which confirmed that miR-146a expression was highest in the latent stage and lowest in the acute stage in an MTLE rat model; during the latent stage of seizures, a state of chronic inflammation was also observed in epileptic patients [16]. Moreover, miR-146a is a potential powerful regulator and acts as a regulating mechanism to prevent an excessive inflammatory response [12,39–41]. Thus, we infer that miR-146a may serve as a negative regulator of chronic inflammation in the latent stage in epilepsy patients. Additionally, the rs57095329 A allele may weaken the chronic inflammation in the latent stage of epilepsy via increased miR-146a expression, thereby potentially reducing the seizure frequency. DRE patients were chosen for this analysis based on the following considerations: first, obtaining accurate data regarding seizure frequencies among epilepsy patients who have not used AEDs in several months is difficult, and the drug-responsive patients who utilized AEDs in our study lacked stable seizure frequencies; second, in contrast, the DRE patients had a relatively homogeneous background and stable seizure frequencies during the drug treatment. Thus, our results do not exclude the possibility that this polymorphism may be associated with the seizure frequency of the other subtypes of epilepsy patients. However, because epilepsy is a multifactorial disorder in which genetic susceptibility and environmental factors may both be implicated, larger samples of epilepsy patients, more clinical data and further study of the molecular mechanism underlying this association are needed to confirm this association. Our study has some potential limitations. Although we recruited from two regions in China, the sample sizes of the case and control groups in this study were still not large enough. Moreover, the data regarding the seizure frequency of the DRE patients were mainly collected by questionnaires and by continuously recording clinical observations; thus, we cannot exclude the existence of bias from the physician. Moreover, although associations between the miR-146a polymorphisms and DRE were observed, the molecular mechanism of these associations is not reflected in this case–control study. Our future studies will focus on exploring the mechanisms underlying the connection between miR-146a and epilepsy. In summary, our study identified for the first time a significant association between the rs57095329 polymorphism in the promoter of miR-146a and the risk of DRE. The rs57095329 A allele was associated with a reduced seizure frequency in DRE patients.
Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements This work was supported by funding from the National Nature Science Foundation of China (81471326), the Natural Science Foundation of Guangdong Province (S2013040013740), the Medical Scientific Research Foundation of Guangdong Province (B2013306) and the PhD Start-up Fund of Guangdong Medical College (B2012020). We thank Dr. Lifen Yao and Dr. Zhien Xu for providing the case resources and clinical data.
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[33] Wang Q, Bozack SN, Yan Y, Boulton ME, Grant MB, Busik JV. Regulation of retinal inflammation by rhythmic expression of MiR-146a in diabetic retina. Invest Ophthalmol Vis Sci 2014;55:3986–94. [34] Ichii O, Otsuka S, Sasaki N, Namiki Y, Hashimoto Y, Kon Y. Altered expression of microRNA miR-146a correlates with the development of chronic renal inflammation. Kidney Int 2012;81:280–92. [35] Hung PS, Liu CJ, Chou CS, Kao SY, Yang CC, Chang KW, et al. miR-146a enhances the oncogenicity of oral carcinoma by concomitant targeting of the IRAK1 TRAF6 and NUMB genes. PLOS ONE 2013;8:e79926. [36] Jazdzewski K, Murray EL, Franssila K, Jarzab B, Schoenberg DR, de la Chapelle A. Common SNP in pre-miR-146a decreases mature miR expression and predisposes to papillary thyroid carcinoma. Proc Natl Acad Sci U S A 2008;105:7269–74. [37] Permuth-Wey J, Thompson RC, Burton Nabors L, Olson JJ, Browning JE, Madden MH, et al. A functional polymorphism in the pre-miR-146a gene is associated with risk and prognosis in adult glioma. J Neurooncol 2011;105:639–46. [38] Jantaratnotai N, Ling A, Cheng J, Schwab C, McGeer PL, McLarnon JG. Upregulation and expression patterns of the angiogenic transcription factor ets-1 in Alzheimer’s disease brain. J Alzheimers Dis 2013;37:367–77. [39] Rebane A, Runnel T, Aab A, Maslovskaja J, Ruckert B, Zimmermann M, et al. MicroRNA-146a alleviates chronic skin inflammation in atopic dermatitis through suppression of innate immune responses in keratinocytes. J Allergy Clin Immunol 2014;134:836–47. [40] Li K, Du Y, Jiang BL, He JF. Increased microRNA-155 and decreased microRNA146a may promote ocular inflammation and proliferation in Graves’ ophthalmopathy. Med Sci Monit 2014;20:639–43. [41] Rusca N, Monticelli S. MiR-146a in immunity and disease. Mol Biol Int 2011;2011:437301.
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Seizure journal homepage: www.elsevier.com/locate/yseiz
A functional polymorphism of the microRNA-146a gene is associated with susceptibility to drug-resistant epilepsy and seizures frequency Lili Cui a,1, Hua Tao a,b,1, Yan Wang c,1, Zhou Liu a,b, Zhien Xu b, Haihong Zhou b, Yujie Cai a, Lifen Yao d, Beichu Chen b, Wandong Liang e, Yu Liu b, Wanwen Cheng b, Tingting Liu b, Guoda Ma a, You Li a, Bin Zhao a,**, Keshen Li a,* a
Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China Institute of Neurology, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China c Clinical Research Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, PR China d Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, PR China e Renji College, Wenzhou Medical University, Wenzhou, China b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 1 November 2014 Received in revised form 27 February 2015 Accepted 28 February 2015
Purpose: Epilepsy is the third most common chronic brain disorder and is characterized by an enduring predisposition for seizures. Recently, a growing body of evidence has suggested that microRNA-146a (miR-146a) is upregulated in the brains of epilepsy patients and of mouse models; furthermore, miR146a may be involved in the development and progression of seizures through the regulation of inflammation and immune responses. In this report, we performed a case–control study to analyze the relationship between the two potentially functional single nucleotide polymorphisms (SNPs) of the miR146a gene (rs2910464 and rs57095329) and the risk of epilepsy in a Chinese population comprising 249 cases and 249 healthy controls. Method: Our study comprised 249 epilepsy patients and 249 healthy controls in two regions of China. The DNA was genotyped using the ABI PRISM SNapShot method. The statistical analysis was estimated using the chi-square test or Fisher’s exact test. Results: Our results indicated a significant association between the rs57095329 SNP of the miR-146a gene and the risk of drug resistant epilepsy (DRE) (genotypes, p = 0.0258 and alleles, p = 0.0108). Moreover, the rs57095329 A allele was found to be associated with a reduced risk of seizures frequency in DRE patients (all p < 0.001). However, the rs2910164 variant was not associated with epilepsy. Conclusion: Our data indicate that the rs57095329 polymorphism in the promoter region of miR-146a is involved in the genetic susceptibility to DRE and the seizures frequency. ß 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Keywords: Polymorphism MicroRNA-146a Drug-resistant epilepsy Seizures frequency
1. Introduction Epilepsy is a common, serious neurological disorder characterized by recurring unprovoked seizures that result from the abnormal firing of populations of neurons in the brain [1]. Although
* Corresponding author at: Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Guangdong Medical College, 57 Ren-min Avenue, Xiashan District, Zhanjiang 524001, PR China. Tel.: +86 07592386772; fax: +86 07592386772. ** Corresponding author at: Guangdong Key Laboratory of Age-related Cardiac and Cerebral Diseases, Guangdong Medical College, 57 Ren-min Avenue, Xiashan District, Zhanjiang 524001, PR China. Tel.: +86 07592387677; fax: +86 07592387677. E-mail addresses: [email protected] (B. Zhao), [email protected] (K. Li). 1 These authors contributed equally to this work.
the exact molecular pathogenic mechanism of epilepsy remains unclear, increasing evidence shows that the persistent upregulation of inflammatory gene expression contributes to the etiopathogenesis of epilepsy [2,3]. Additionally, inflammatory mediators such as interleukin (IL)-1b, Toll-like receptors (TLRs), and other factors are involved in the development of epilepsy in experimental animal models and in patients [4,5]. MicroRNAs (miRNAs) are a family of small, endogenous noncoding RNAs that post-transcriptionally regulate target gene expression to control most aspects of biological processes, including innate and adaptive immune responses [6–8]. Abnormal miRNA expression has also been observed in different diseases associated with inflammatory and immune processes [9–11]. One miRNA that attracted our attention was miRNA-146a (miR-146a),
http://dx.doi.org/10.1016/j.seizure.2015.02.032 1059-1311/ß 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
L. Cui et al. / Seizure 27 (2015) 60–65
which is well known for its important regulation of the TLR signaling pathway and of proinflammatory cytokines such as IL-1b and TNF-a [12–14]. Recently, increasing evidence has shown that miR-146a is upregulated in epilepsy mouse models and epilepsy patients [15–18], suggesting that miR-146a may operate as an important epigenetic regulator involved in the pathogenesis of epilepsy. Single nucleotide polymorphisms (SNPs) could influence the function or the expression of genes and be associated with the risk of disease. Two SNPs in the miR-146a gene, rs2910164 and rs57095329, have functional importance: they modify the expression level of mature miR-146a [19,20] and are associated with many inflammation-associated diseases such as systemic lupus erythematosus [19], Behc¸et’s disease [20] ulcerative colitis [21], sepsis [22] and asthma [23]. To the best of our knowledge, no studies have examined the association between the rs57095329 SNP and epilepsy, and only one study on the association between one SNP (rs2910164) and the risk of temporal lobe epilepsy (TLE) has been performed in a primarily Caucasian population [24]. Until now, no similar studies have been performed in Asian populations. In the present study, we conducted a case–control study to determine the association between these two functional SNPs of miR-146a (rs2910164 G>C and rs57095329 A>G) and epilepsy in an ethnically homogeneous Chinese population. Moreover, the potential associations between the miR-146a polymorphisms and clinical variables such as TLE/no-TLE, drugresponsiveness/resistance and seizure frequency were also examined. 2. Materials and methods 2.1. Clinical data of epilepsy patients and healthy controls Our study comprised 249 epilepsy patients (female 112; male 137; mean age: 26.5 15.2 years) and 249 healthy controls (female 94; male 155; mean age: 50.1 16.7 years). The epilepsy patients were recruited from two regions of China: the Department of Neurology of the Affiliated Hospital of Guangdong Medical College of southern China (134 patients and 137 controls) and the Department of Neurology of the first Affiliated Hospital of Harbin Medical University of northern China (115 patients and 112 controls). All of the patients were diagnosed and classified by experienced neurologists following the criteria of the International League Against Epilepsy [25]. Information such as the clinical history, electroencephalography (EEG) and magnetic resonance imaging (MRI) data was recorded for all patients. Patients and healthy controls with mental retardation were excluded as well as all of the healthy control subjects who had a history of seizures. The study was conducted in accordance with the Declaration of Helsinki, and written informed consent was obtained from all of the enrolled participants. This study was approved by the Ethics Committees of both the Affiliated Hospital of Guangdong Medical College and the first Affiliated Hospital of Harbin Medical University. Patients were divided into two groups, according to treatment, as drug responsive and drug resistant. Drug responsiveness was determined from clinical records. A drug response was defined as freedom from seizures or a 50% or greater reduction in the seizure frequency for at least one year during treatment with antiepileptic drugs (AEDs). Drug resistance was defined as no change or less a than 50% reduction in the seizure frequency for at least one year with two or more appropriate AEDs at maximally tolerated therapeutic doses. Patients who underwent epilepsy surgery for refractory epilepsy were classified as having drug-resistant epilepsy, regardless of their postoperative seizure control status. Moreover, the seizure frequencies of drug-resistant epilepsy (DRE) patients were followed up and recorded. Twenty-three patients
61
were excluded because their seizure frequency data with follow up included less than 6 months or because the patients underwent epilepsy surgery within the previous 6 months. Finally, a total of 52 patients were included in these statistics and were divided into groups according to their seizure frequencies, as follows: less than 5 times/month, more than 5 times/month, more than 10 times/ month and more than 30 times/month. 2.2. Genotyping A 2-mL venous blood sample was taken for DNA extraction and genotyping. Genomic DNA was isolated from peripheral blood samples using a blood Genomic DNA Extraction Kit (Tiangen, China). DNA was genotyped using the ABI PRISM SNapShot method (Applied Biosystems, Foster, CA). The PCR primers used for the rs2910164 SNP were as follows: forward primer 5-GAACTGAATTCCATGGGTTG-3 and reverse primer 5-CACGATGACAGAGATATCCC3. The primers used for the rs57095329 SNP were as follows: forward primer 5-TCATTGGGCAGCCGATAAAG-3 and reverse primer 5-AGGAAGTTCTGGTCAGGCG-3. The assay conditions were in accordance with manufacturer’s protocols. Fluorescence outputs were quantified in real time by using a 7500HT Fast Real Time PCR System (Applied Biosystems, Carlsbad, CA). For quality control, random duplicate samples (5%) were run for each sequence analysis. 2.3. Statistical analysis All analyses were performed using SPSS version 19.0 (IBM, NY, USA). Genotype and allele frequencies distributions in the groups were counted and estimated using the chi-square test or Fisher’s exact test. Deviation of the genotype or allele frequency was assessed using Hardy–Weinberg equilibrium (HWE). The odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the correlation between the miR146a genotype and epilepsy. The data are presented as percentage frequencies or the means SD. Two-tailed p values <0.05 were considered to be statistically significant. 3. Results 3.1. Clinical characteristics The demographic characteristics of our subjects are shown in Table 1. In total, 249 epilepsy patients and 249 healthy controls, who were matched with case subjects according to sex, ethnicity and geographic location of origin, were recruited in our study. Among the cases, 174 patients were classified as TLE, and 75 patients were classified as non-TLE. No significant differences in the age and sex distributions between TLE patients and non-TLE patients were found. Additionally, the average seizure onset age was 19.42 14.38 years, and no statistically significant difference
Table 1 Clinical and demographic data of epileptic patients. Characteristics
Epilepsy patients (N = 249)
TLE patients (N = 174)
Non-TLE patients (N = 75)
Controls (N = 249)
Age (mean years SD) Gender (male/ female) Age at epilepsy onset (mean years SD)
26.5 15.2
26.33 14.29
27.07 16.79
50.1 16.7
137/112
95/79
42/33
155/94
19.42 14.38
19.68 13.31
18.87 16.55
–
L. Cui et al. / Seizure 27 (2015) 60–65
62
Table 2 Distribution of miR146a gene polymorphisms between epilepsy patients and healthy controls. RS2910164
All
CC (%)
CG (%)
GG (%)
p-Value
C (%)
G (%)
p-Value
OR (95% CI)
CASE TLE No-TLE Control
249 174 75 249
98 66 32 97
120 85 35 106
31 23 8 46
0.1500 0.2649 0.2823 –
316 217 99 300
182 131 51 198
0.3279 0.5666 0.2144 –
1.146 (0.8872–1.480) 1.093 (0.8250–1.449) 1.281 (0.8738–1.878) –
(39.4) (37.9) (42.7) (39.0)
(48.2) (48.9) (46.7) (42.6)
(12.4) (13.2) (10.7) (18.5)
(63.5) (62.4) (66.0) (60.2)
(36.5) (37.6) (34.0) (39.8)
RS57095329
All
AA (%)
GA (%)
GG (%)
p-Value
A (%)
G (%)
p-Value
OR (95% CI)
CASE TLE No-TLE Control
249 174 75 249
163 110 53 155
79 59 20 86
7 5 2 8
0.7539 0.9677 0.4099 –
405 279 126 396
93 69 24 102
0.5230 0.8620 0.2413 –
1.122 (0.8199–1.535) 1.042 (0.7399–1.466) 1.352 (0.8302–2.203) –
(65.5) (63.2) (70.7) (62.2)
(31.7) (33.9) (26. 7) (34.5)
(2.8) (2.9) (2.7) (3.2)
was observed in the mean epilepsy onset age in patients in the TLE and non-TLE subgroups. 3.2. Genotype and allele frequency distributions in epilepsy patients and controls All of the enrolled subjects were successfully genotyped for the rs2910164 and rs57095329 SNPs, and the association between the genotype and the risk of epilepsy was analyzed using the chisquare test. The deviation from Hardy–Weinberg equilibrium for the polymorphisms examined was not found in the distributions of genotypes in the patients and controls (all p > 0.05, data not shown). The genotype and allele frequencies of miR-146a polymorphisms in the studies are shown in Table 2. For rs2910164, neither the genotype nor the allele showed significant differences between the epilepsy patients and the controls (genotypes p = 0.1500 and alleles p = 0.3279, respectively), and no significant difference was observed in the TLE group (genotypes p = 0.2649 and alleles p = 0.5666) or no-TLE groups (genotypes p = 0.2823 and alleles p = 0.2144) (Table 2). Similarly, we also did not observe a significant difference in the genotype or allele frequencies between the patients and controls for the rs57095329 SNP (epilepsy patients: genotypes p = 0.7539 and alleles p = 0.5230; TLE patients: genotypes p = 0.9677 and alleles p = 0.8612; no-TLE patients: genotypes p = 0.4099 and alleles p = 0.2413). Additionally, as shown in Table 3, there was no statistically significant difference in the mean age of onset of epilepsy in patients with an miR-146a polymorphism (genotype for rs2910164: p = 0.253; genotype for rs57095329: p = 0.196). We further performed haplotype-based association analyses of rs2910164 and rs57095329. However, no significant associations were observed between these haplotypes and epilepsy (Table 4).
(81.3) (80.2) (84.0) (79.5)
(18.7) (19.8) (16.0) (20.5)
p = 0.0258 and alleles p = 0.0108), and the patients carrying the miRNA-146a rs57095329 A allele had a lower risk of DRE, indicating that the rs57095329 SNP could be a risk factor for DRE. 3.4. Genotype and allele frequency distributions of miR-146a polymorphisms among DRE patients We collected the DRE patients with relatively stable seizure frequencies and with full clinical data with at least one year followup. A total of 52 DRE samples with relatively stable seizure frequency data were recruited for the association analysis between miR-146a polymorphisms and the seizure frequency. Among the 52 DRE patients, 31 patients had a seizure frequency of less than 5 times/month, 21 patients had a seizure frequency of more than 5 times/month, 16 patients had the seizure frequency of more than 10 times/month, and 7 patients had a seizure frequency of more than 30 times/month (Table 6). We analyzed the genotype and allele frequency distributions among DRE patients, and the results are shown in Fig. 1. The rs2910164 polymorphism showed no significant association with the seizure frequency of the DRE patients. However, the rs57095329 A allele was observed with a trend of reducing the seizure frequency in DRE patients (all p < 0.001), indicating that rs57095329 in the promoter region of miR-146a was a risk factor for the seizure frequency of DRE patients. 4. Discussion
The distribution of miR-146a genotypes was further analyzed in DRE patients and healthy controls. As shown in Table 5, the rs2910164 SNP showed no significant association with DRE patients. However, rs57095329 showed a significant association in the DRE group compared with the controls (genotypes
Despite extensive research, the mechanisms underlying the cause and progression of epilepsy remain unclear. In recent years, increasing evidence has supported the hypothesis that inflammatory processes within the epileptic brain might constitute a common and crucial mechanism in the pathology of seizures [26,27]. In the brain tissue of patients with DRE, several proinflammatory cytokines have been detected [28,29], and in animal models, the inflammatory mechanisms are also intimately connected with the generation of seizure onset [30]. Importantly, although controversial, several pieces of clinical evidence indicated that steroids and other anti-inflammatory treatments have anticonvulsant properties in DRE patients [31,32], supporting the view that the effects on neuroinflammation may influence the
Table 3 Distribution of miR146a gene polymorphisms of onset age in epilepsy patients.
Table 4 The haplotype of miR146a polymorphisms between cases and controls.
3.3. Genotype and allele frequency distributions of miR-146a polymorphisms between DRE patients and controls
rs2910164
CC
GC
GG
p-Value
Onset age
20.89 14.88
18.73 14.36
17.24 13.03
0.2531
rs57095329
AA
GA
GG
p-Value
Onset age
20.80 15.25
16.88 12.30
20.13 12.26
0.1968
rs2910164– rs57095329
Case
Control
OR (95% CI)
p-Value
CA AG GG
313 86 99
306 94 98
1 0.894 (0.6420–1.247) 0.988 (0.7166–1.361)
– 0.5100 0.9393
L. Cui et al. / Seizure 27 (2015) 60–65
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Table 5 Distribution of miR146a gene polymorphisms between DRE patients and controls. rs2910164
CC (%)
GC (%)
GG (%)
p-Value
C (%)
G (%)
p-Value
OR (95% CI)
Drug-resistant Control
31 (41.3) 97 (40.0)
33 (44.0) 106 (42.6)
11 (14.7) 46 (18.5)
0.6501 –
95 (63.3) 300 (60.2)
55 (36.7) 198 (39.8)
0.5059 –
1.1400 (0.7815–1.663) –
rs57095329
AA (%)
GA (%)
GG (%)
p-Value
A (%)
G (%)
p-Value
OR (95% CI)
Drug-resistant Control
34 (45.3) 155 (62.2)
36 (48.0) 86 (34.5)
5 (6.7) 8 (3.2)
0.0258 –
104 (69.3) 396 (79.5)
46 (30.7) 102 (20.5)
0.0108 –
0.5823 (0.3866–0.8773) –
Table 6 Distribution of the seizure frequency in DRE patients. Seizure frequency rs2910164 CC GC GG p-Value C allele G allele p-Value OR (95% CI) rs57095329 AA GA GG p-Value A allele G allele p-Value OR (95% CI)
<5 times/month (N = 31)
>5 times/month (N = 21)
>10 times/month (N = 16)
>30 times/month (N = 7)
11 15 5
6 12 3 0.8206 24 18 0.8409 0.9009 (0.4070–1.994)
5 10 1 0.5333 20 12 0.8272 1.126 (0.4683–2.708)
2 5 0 0.4097 9 5 1 1.216 (0.3643–4.060)
10 5 6 0.0051 25 17 0.0008 0.1872 (0.06890–0.5085)
7 5 4 0.0072 19 13 0.0026 0.1860 (0.06465–0.5352)
2 2 3 0.0005 6 8 0.0006 0.0955 (0.02552–0.3570)
37 25 – –
24 7 0 55 7 – –
generation and exacerbation of epilepsy. MiR-146a is well known as a powerful innate immune- and pro-inflammatory-related regulator in immune and inflammatory responses. MiR-146a has been reported to be abnormally upregulated in several diseases [33–35]. Recently, miRNA expression profiling assays of samples under epilepsy conditions showed that miR-146a was significantly upregulated in the hippocampus both of a TLE rat model and of epilepsy patients [15,16], and miR-146a also interacts with IL-1b levels at different stages of epilepsy [14]. These findings inspired us to examine the relationship between miR-146a and epilepsy. In this case–control study, two functional SNPs in miR-146a (rs2910164 and rs57095329) were selected to evaluate the association between miR-146a polymorphisms and the risk of epilepsy. The rs2910164 G/C polymorphism, which is located in the stem region of precursor-miR146a and could disturb the
expression of mature miR-146a through mismatching with the stem structure, has been associated with several diseases [21,36,37]. The rs57095329 polymorphism, which is located in the miR-146a promoter, was recently found to influence mature miR-146a levels by altering the binding affinity of miR-146a for VEts oncogene homologue 1 (Ets-1), thereby possibly contribute to disease susceptibility [19]. Our previous study also confirmed that both of the 2 functional SNPs of miR-146a could influence the expression levels of miR-146a in vitro [11]. However, in the present study, only rs57095329 was associated with DRE susceptibility. Why these two functional SNPs of miR-146a, which can both influence miR-146a expression, show different correlations with epilepsy in our association study remains unknown. Because epilepsy is a complex disease that is associated with multiple genetic and environmental factors, we inferred that the
Fig. 1. Distribution of different seizures frequency in DRE patients with rs2910164 and rs57095329 allele of miR146a.
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functional rs2910164 SNP may have a limited capacity to alter the susceptibility to epilepsy because it could only disturb miR-146a expression by influencing the stem structure of precursor miR146a. Nevertheless, rs57095329 is located in the promoter region of miR-146a. Thus, the effect of this SNP on the miR-146a expression level relies mainly on Ets-1. Notably, Ets-1 is widely expressed in the cortex and hippocampus and is upregulated in Alzheimer’s disease, in which the inflammatory response is one of the important pathological features [38], suggesting that rs57095329 may have a potential function on the miR-146a expression due to the high level of Ets-1 in the brain when inflammation occurs such as in epilepsy. However, the effects of rs57095329 and rs2910164 on miR-146a expression in the epileptic brain require further study. Another novel finding was that our statistical data showed a connection between the rs57095329 A allele and the reduced seizure frequency. Recently, increasing evidence suggested that miR-146a may play a more important role before the onset of seizures. E. Aronica and coworkers observed a prominent upregulation of miR-146a in a mouse model at 1 week after status epilepticus; furthermore, this upregulation persisted into the chronic phase [15]. This finding was supported by another study, which confirmed that miR-146a expression was highest in the latent stage and lowest in the acute stage in an MTLE rat model; during the latent stage of seizures, a state of chronic inflammation was also observed in epileptic patients [16]. Moreover, miR-146a is a potential powerful regulator and acts as a regulating mechanism to prevent an excessive inflammatory response [12,39–41]. Thus, we infer that miR-146a may serve as a negative regulator of chronic inflammation in the latent stage in epilepsy patients. Additionally, the rs57095329 A allele may weaken the chronic inflammation in the latent stage of epilepsy via increased miR-146a expression, thereby potentially reducing the seizure frequency. DRE patients were chosen for this analysis based on the following considerations: first, obtaining accurate data regarding seizure frequencies among epilepsy patients who have not used AEDs in several months is difficult, and the drug-responsive patients who utilized AEDs in our study lacked stable seizure frequencies; second, in contrast, the DRE patients had a relatively homogeneous background and stable seizure frequencies during the drug treatment. Thus, our results do not exclude the possibility that this polymorphism may be associated with the seizure frequency of the other subtypes of epilepsy patients. However, because epilepsy is a multifactorial disorder in which genetic susceptibility and environmental factors may both be implicated, larger samples of epilepsy patients, more clinical data and further study of the molecular mechanism underlying this association are needed to confirm this association. Our study has some potential limitations. Although we recruited from two regions in China, the sample sizes of the case and control groups in this study were still not large enough. Moreover, the data regarding the seizure frequency of the DRE patients were mainly collected by questionnaires and by continuously recording clinical observations; thus, we cannot exclude the existence of bias from the physician. Moreover, although associations between the miR-146a polymorphisms and DRE were observed, the molecular mechanism of these associations is not reflected in this case–control study. Our future studies will focus on exploring the mechanisms underlying the connection between miR-146a and epilepsy. In summary, our study identified for the first time a significant association between the rs57095329 polymorphism in the promoter of miR-146a and the risk of DRE. The rs57095329 A allele was associated with a reduced seizure frequency in DRE patients.
Conflict of interest The authors declare that they have no conflict of interest. Acknowledgements This work was supported by funding from the National Nature Science Foundation of China (81471326), the Natural Science Foundation of Guangdong Province (S2013040013740), the Medical Scientific Research Foundation of Guangdong Province (B2013306) and the PhD Start-up Fund of Guangdong Medical College (B2012020). We thank Dr. Lifen Yao and Dr. Zhien Xu for providing the case resources and clinical data.
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