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The rs3756063 polymorphism is associated with SNCA methylation in the Chinese Han population
Journal of the Neurological Sciences 367 (2016) 11–14
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Journal of the Neurological Sciences journal homepage: www.elsevier.com/locate/jns
The rs3756063 polymorphism is associated with SNCA methylation in the Chinese Han population Yang Wei a,1, Nannan Yang a,1, Qian Xu a, Qiying Sun a, Jifeng Guo a,b,c,d, Kai Li a, Zhenhua Liu a, Xinxiang Yan a,b,d, Xiongwei Zhu e, Beisha Tang a,b,c,d,⁎ a
Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China State Key Laboratory of Medical Genetics, Changsha, 410008, Hunan, People's Republic of China Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, People's Republic of China d Neurodegenerative Disorders Research Center, Central South University, Changsha, 410008, Hunan, People's Republic of China e Institute of Pathology, Case Western Reserve University, Cleveland, OH 44106, USA b c
a r t i c l e
i n f o
Article history: Received 25 November 2015 Received in revised form 4 May 2016 Accepted 18 May 2016 Available online 19 May 2016 Keywords: Parkinson's disease SNCA Single nucleotide polymorphisms Methylation
a b s t r a c t Parkinson's disease (PD) is the second most common neurodegenerative disorder. Genome-wide association studies have confirmed the association of single nucleotide polymorphisms (SNPs) located in the SNCA gene with the risk of PD. While hypomethylation of the SNCA intron-1 was observed in patients with sporadic PD, an association between SNCA SNPs and SNCA methylation levels has been identified. To investigate whether these SNPs are associated with the level of SNCA methylation in the Chinese population, we genotyped SNCA SNPs and analyzed the relationship between SNCA SNPs and SNCA DNA methylation status from peripheral blood mononuclear cells of Chinese Han PD patients. Our results revealed that the rs3756063 polymorphism could contribute to the risk of PD in the Chinese Han population and confirmed the effect of this polymorphism on SNCA DNA methylation. Further studies will be needed to gain a better understanding of the mechanisms underlying the associations between SNPs, methylation and PD pathogenesis. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease (AD) and is characterized by the progressive loss of the dopaminergic neurons of the substantia nigra [1, 2]. It is generally considered that aging, genes and environmental factors influence the etiology of PD. Mutations in the alpha-synuclein gene (SNCA), encoding alpha-synuclein protein, the first to be identified in monogenic PD, account for approximately 2% of the autosomal dominant forms of early-onset PD [3,4]. Braak et al. later showed that the accumulation of alpha-synuclein protein in the brain is a hallmark of PD [5]. While most PD cases are sporadic, several case-control studies have reported that SNCA might be a susceptibility gene for sporadic PD and that its increased expression results in parkinsonian syndrome [6–9]. Genome-wide association studies have further confirmed that certain single nucleotide polymorphisms (SNPs) located in SNCA are associated with the risk of PD [10–17]. With the progress of study, researchers disproved the view that alpha-synuclein protein as a ‘neuron-specific’ protein in PD and indicated that high levels of alpha⁎ Corresponding author at: Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People's Republic of China. E-mail address: [email protected] (B. Tang). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.jns.2016.05.037 0022-510X/© 2016 Elsevier B.V. All rights reserved.
synuclein expression were found in peripheral [18,19]. Further studies showed that SNCA variants associated with alpha-synuclein levels in the blood as well as brain [20–23]. DNA methylation is the most intensely studied epigenetic mechanism and is characterized by the transfer of a methyl group from Sadenosylmethionine (SAM) to cytosine residues at the CpG dinucleotides on the DNA, which alters gene expression [24,25]. Because methylation status is related to the expression of gene transcripts, abnormal methylation patterns in the CpG islands of disease-associated genes might be involved in disease pathogenesis. Eliezer et al. identified that the level of genome-wide DNA methylation in brain and blood was consistent in PD patients [26]. The hypomethylation of SNCA intron-1 was observed in patients with sporadic PD, and the hypomethylation of this region could be associated with an increase in SNCA expression in vitro [27–29]. As we all known that SNCA variants associated with a-synuclein levels, and there was closely link between SNCA methylations level and SNCA expressions. We evaluated whether SNCA variants are associated with the SNCA methylation level, thus affecting the SNCA expression levels. In our previous study, we confirmed the hypomethylation of SNCA in the Chinese Han PD population and revealed the Rep1 polymorphism, which is located ~10 kb upstream of the translational start site of SNCA and was associated with SNCA DNA methylation [30]. Recently, Pihlstrøm et al. investigated the relationship between SNCA
12
Y. Wei et al. / Journal of the Neurological Sciences 367 (2016) 11–14
Table 1 Fundamental data, mean SNCA methylation levels and SNCA mRNA levels in PD patients and controls.
Gender (male/female) Age (years) Mean SNCA methylation levels (%) Mean SNCA-mRNA levels
PD (n = 91)
Controls (n = 92)
p
47/44 62.00 ± 9.72 14.27 ± 8.65 0.0015 ± 0.0007
49/43 62.27 ± 9.54 17.17 ± 8.89 0.0014 ± 0.0007
0.827 0.849 0.011 0.84
SNPs (including rs3756063, rs356165 and rs2245801) and determined that rs3756063 was associated with SNCA methylation levels [31]. However, it remains unknown whether these SNPs are associated with the SNCA methylation level in the Han population from mainland China. In this study, we genotyped SNCA SNPs and investigated the relationship between SNCA SNPs and SNCA DNA methylation status in Chinese Han PD patients. 2. Materials and methods 2.1. Subjects and SNCA transcript analysis A 30-ml sample of venous peripheral blood from 91 sporadic PD patients (mean ± SD age = 62.00 ± 9.72 years, female = 44, male = 47) and 92 controls (mean ± SD age = 62.27 ± 9.54 years, female = 49, male = 43) were collected in ethylenediamine tetra-acetate (EDTA) vacutainer tubes. The Department of Neurology, Xiangya Hospital, Central South University, the National Laboratory of Medical Genetics of China and the Neurodegenerative Disorders Research Center, Central South University approved the inclusion of the 91 sporadic PD patients, who were diagnosed by United Kingdom PD Brain Bank Criteria [32]. The Health Examine Center of Second Xiangya Hospital approved the inclusion of the 92 controls. All patients and controls signed an informed consent to participate in the project. The genomic DNA was prepared using the TIA Namp Genomic DNA blood kit (Tiangen Biotech, Beijing, China), total RNA was isolated using the standard Trizol method (Qiagen), and all of the samples were stored at −80 °C. The study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics committee of Central South University. 2.2. Sodium bisulfite sequencing Briefly, an Epitect Bisulfite Kit (Qiagen) was used for the bisulfite conversion. The converted product was purified and amplified by polymerase chain reaction (PCR) using primer sequences described previously [33]. The PCR products were then cloned into the pGEM-T easy vector (Promega, Madison, WI, U.S.A.), and for each subject, N10
independent clones were sequenced to study the CpG site methylation levels. A BiQ analyzer (quality control software for DNA methylation data from bisulfite sequencing) served as a control. 2.3. cDNA synthesis and real-time quantitative PCR (RT-PCR) The mRNA levels of SNCA determined by RT-PCR were used to analyze SNCA expression. First, cDNA was synthesized from total RNA using the RevertAid™ First Strand cDNA synthesis Kit (Fermentas, Burlington, Canada). We then performed RT-PCR using a ABI 7900 HT Fast Real-time PCR system (Applied Biosystems, Inc., Foster City, CA), and the SYBR Premix Ex Taq™ real-time PCR Kit (Takara Biotech, Co., Dalian, China); primer sequences have been described previously [26]. 2.4. SNCA rs356182/rs356165/rs2245801/rs3756063 genotyping Four SNCA SNPs (rs356182/rs356165/rs2245801/rs3756063) were reported in genome-wide association studies and were studied. All of the SNPs were genotyped by PCR. 2.5. Statistical analyses The Statistical Package for Social Sciences (SPSS, version 17.0) was used for all statistical analyses. A p b 0.05 was considered to be statistically significant. The frequencies and percentages of allelic genotypes and the mRNA and DNA methylation levels between patients and controls were compared by using a Chi-square test. The association between mRNA and DNA methylation levels was assessed by using a Pearson correlation. To compare the association of mRNA or DNA methylation levels with gender, age, disease status and SNP genotypes, a linear regression analysis was used. 3. Results There were no significant differences in gender or age distribution between the patients and controls. The mean DNA methylation level of SNCA intron-1 in PD patients was lower than that of controls (p =
Table 2 Allele frequencies of four SNPs in PD patients and controls. PD (na =182)
Controls (na =184)
Pb
OR
95% CI
rs3756063c G C
19 (10.4%) 163 (89.6%)
33 (17.9%) 151 (82.1%)
0.042
1.875
1.022–3.438
rs356182 G A
63 (34.6%) 119 (65.4%)
69 (37.5%) 115 (62.5%)
0.566
0.939
0.759–1.163
rs356165 G A
87 (47.8%) 95 (52.2%)
94 (51.1%) 90 (48.9%)
0.832
0.956
0.635–1.440
rs2245801 T C
20 (11.0%) 162 (89.0%)
32 (17.4%) 152 (62.6%)
0.082
1.705
0.935–3.110
a b c
n = 2 * case numbers. p values presented were corrected for by linear regression analysis, adjusting for gender, age and disease status. rs3756063 C allele had a significantly higher frequency among the patients.
Y. Wei et al. / Journal of the Neurological Sciences 367 (2016) 11–14
13
Table 3 SNCA methylation levels and SNCA-mRNA levels among different SNPs alleles and genotypes in PD patients and controls. The mean SNCA methylation levels (%)
The mean SNCA -mRNA levels
PD
Controls
PD
Controls
rs3756063a GG + GC CC p
23.32 ± 8.91 12.04 ± 6.25 b0.001
19.30 ± 8.76 16.20 ± 8.34 0.094
0.0014 ± 0.0007 0.0016 ± 0.0009 0.833
0.0015 ± 0.0006 0.0015 ± 0.0007 0.891
rs356182 GG + GA AA p
14.21 ± 8.83 14.67 ± 7.74 0.864
16.88 ± 8.79 19.54 ± 9.12 0.290
0.0014 ± 0.0008 0.0016 ± 0.0009 0.715
0.0014 ± 0.0007 0.0016 ± 0.0007 0.743
rs356165 GG + GA AA p
13.67 ± 8.10 16.40 ± 10.35 0.285
15.97 ± 7.62 18.35 ± 11.03 0.180
0.0014 ± 0.0007 0.0014 ± 0.0009 0.810
0.0015 ± 0.0007 0.0014 ± 0.0008 0.792
rs2245801 TT + TC CC p
16.11 ± 9.56 14.79 ± 7.21 0.254
17.71 ± 10.28 15.49 ± 7.54 0.314
0.0015 ± 0.0009 0.0014 ± 0.0007 0.73
0.0016 ± 0.0008 0.0014 ± 0.0007 0.801
a
rs3756063 GG + GC/CC had a significantly difference DNA methylation levels among the patients.
0.011), and there was no significant difference in the mean SNCA mRNA levels between PD patients and controls (Table 1). SNCA SNP genotyping was performed, and the allelic distribution and frequencies are listed in Table 2. The results showed that the rs3756063 C allele was observed at a significantly higher frequency among the patients (p = 0.042, OR = 1.875, 95%CI = 1.022–3.438), while the other three SNPs (rs356182/rs356165/rs2245801) had no significant allelic distribution between PD patients and controls. We then analyzed the linkage disequilibrium between these four SNPs by using the program SHEsis (http://analysis.bio-x.cn/myAnalysis.php),the result showed no linkage disequilibrium between these four SNPs (r2 b 0.08). Further analysis showed that no linkage disequilibrium between rs3756063 and the common SNPs of southern Chinese Han population (including rs3822086, rs356220, rs2736990 and rs356219) (r2 b 0.2), analyzed the data provided by the program 1000 genomes (http://asia.ensembl.org/Homo_ sapiens/Variation/Population?db=core;r=4:89704460-89705460;v= rs356182;vdb=variation;vf=226270#373515_tablePanel) using the program SHEsis (http://analysis.bio-x.cn/myAnalysis.php). The results suggested that rs3756063 C allele might had independent effects with the risk of PD. We performed a linear regression analysis to investigate the association between DNA methylation levels of SNCA intron-1 and SNP genotype while adjusting for disease status, gender and age. The results showed that the DNA methylation levels of SNCA intron-1 were significant lower in the patients without the rs3756063 allele G compared to those patients carrying allele G (p b 0.001). Therefore, the CC genotype
Fig. 1. SNCA methylation levels in different alleles of rs3756063 (A) and different genotypes (B) in PD patients. SNCA intron-1 methylation levels were significant lower in the patients who did not carry rs3756063 allele G compared to those patients who carried allele G (p b 0.001), and the rs375606 genotype CC showed lower DNA methylation levels than the patients who carried GG and GC. (GC + GG vs.CC p b 0.001).
of rs375606 showed decreased DNA methylation levels compared to the patients harboring GG or GC genotypes (GC + GG vs.CC p b 0.001) (Table 3, Fig. 1). However, no significant differences in DNA methylation levels were found for the rs356182, rs356165 or rs2245801 SNPs. No significant differences were identified between the SNCA-mRNA level and allelic states or different genotypes of these four SNPs.
4. Discussion PD is a common neurodegenerative disorder affected by many complex factors. Since the first gene (SNCA) implicated in PD was found, many studies have focused on it. GWAS and large-scale meta-analysis have identified many risk loci or SNPs (including rs356165/rs356182/ rs2245801/rs3756063 located on SNCA) that are associated with the risk of PD, while the causal mechanisms remain unclear [10–17]. Subsequent studies confirmed the association between SNCA variants and alpha-synuclein levels, while the causal mechanisms remain unclear. With the progress of epigenetics, the hypomethylation of SNCA intron1 was observed in patients with sporadic PD, and the hypomethylation of this region could be associated with an increase in SNCA expression by promoting transcription of the gene [27–29]. Recently, Pihlstrøm et al. investigated the relationship between SNCA SNPs and determined that rs3756063 was associated with SNCA methylation levels [31]. In our study, we determined that rs3756063 was related to the risk of PD in the Chinese Han population. We further investigated the relationship between the four SNPs and the levels of DNA methylation in SNCA intron-1, and we found that rs3756063 was also associated with SNCA intron-1 methylation levels. To investigate the mechanism underlying the contribution of rs3756063 to the risk of PD and the association between that polymorphism and the methylation of SNCA intron-1, we searched for a potential transcription binding site in the sequences around this SNP using MatInspector 8.0 software (Genomatix, Oakland, CA, USA). Our analysis revealed many potential binding sites for transcription factors, and the binding sites with the highest score values (core similarity = 1; matrix similarity = 1) in the ±50 bp around the SNP were Myc interacting zinc finger protein 1 (Miz 1), transcription factor II B (TFIIB) and pleiomorphic adenoma gene (PLAG.). It is worth noting that the core binding sequence of a putative TFIIB binding site is contained within the SNP site. However, whether these potential transcription factor binding sites are functional remains unknown, and further investigation is needed to clarify whether the variant contributes to PD risk by altering transcription factor binding and DNA methylation.
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Y. Wei et al. / Journal of the Neurological Sciences 367 (2016) 11–14
We did not observe an association between SNCA mRNA levels and rs3756063, which is consistent with another previous study [31]. In our previous study, we also found that the Rep1 polymorphism was associated with SNCA DNA methylation but not with SNCA mRNA expression [30]. A recent study showed similar results with our research, the researchers considered it was probably because intracellular SNCA transcript levels reduced as a consequence of intracellular alpha-synuclein protein accumulation, leading a feedback repression of transcription [19]. Other studies have shown that levodopa increases SNCA methylation levels, lower levels of SNCA transcription in PD patients [23]. Because of the limited sample size, we did not compare the differences of SNCA transcript levels in patients taking levodopa and those patients who not taking in our study, this is our shortcomings. Other mechanisms may be involved in the regulation of SNCA mRNA, and a larger sample size is needed to further verify these results. PD is characterized by the progressive loss of the dopaminergic neurons of the substantia nigra and accumulation of alpha-synuclein protein in the brain, and the ideal experimental subject is human brain tissue. Due to the limitations of human brain tissue, researchers have focused on PD biomarkers. Many studies based on peripheral blood of patients with PD [19,20,23], and have shown that concordant methylation alterations in brain and blood in PD patients [21,26,31], suggesting that blood might hold promise as a surrogate for brain tissue and as a source for biomarker discovery. Considering these factors we used peripheral blood mononuclear cells (PBMC) for this study, and there were on similar studies in Chinese Han PD patients. However we must recognize that the situation in peripheral blood and brain tissue is not completely consistent, relevant research is needed to further validate by using brain, and larger multicenter sample study is required to be verify as the patients in our study were limited . Taken together, our results revealed that rs3756063 might contribute to the risk of PD in the Chinese Han population and confirmed the effect of this polymorphism on SNCA DNA methylation. Further studies are needed to better understand the mechanisms underlying the associations between SNPs, methylation and PD pathogenesis. Declaration of interest No conflict of interest exits in the submission of this manuscript. Acknowledgments The authors would like to thank all the patients and control subjects for participation in this study. This work was supported by grants from the NSFC-NIH joint program (81361120404), the key program of the National Natural Science Foundation of China(81430023) and the Major State Basic Research Development Program of China (973 Program) (2011CB510000). References [1] M.G. Spillantini, et al., Alpha-synuclein in Lewy bodies, Nature 388 (6645) (1997) 839–840. [2] M. Goedert, et al., 100 years of Lewy pathology, Nat. Rev. Neurol. 9 (1) (2013) 13–24.
[3] A.B. Singleton, M.J. Farrer, V. Bonifati, The genetics of Parkinson's disease: progress and therapeutic implications, Mov. Disord. 28 (1) (2013) 14–23. [4] E. Masliah, et al., Distinctive patterns of DNA methylation associated with Parkinson disease, Epigenetics 8 (10) (2014) 1030–1038. [5] H. Braak, et al., Staging of the intracerebral inclusion body pathology associated with idiopathic Parkinson's disease (preclinical and clinical stages), J. Neurol. 249 (Suppl. 3) (2002) 1–5. [6] I. Mizuta, Multiple candidate gene analysis identifies α-synuclein as a susceptibility gene for sporadic Parkinson's disease, Hum. Mol. Genet. 15 (7) (2006) 1151–1158. [7] J.C. Mueller, et al., Multiple regions of α-synuclein are associated with Parkinson's disease, Ann. Neurol. 57 (4) (2005) 535–541. [8] P. Pals, et al., α-Synuclein promoter confers susceptibility to Parkinson's disease, Ann. Neurol. 56 (4) (2004) 591–595. [9] L. Pihlstrom, M. Toft, Genetic variability in SNCA and Parkinson's disease, Neurogenetics 12 (4) (2011) 283–293. [10] W. Satake, et al., Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson's disease, Nat. Genet. 41 (12) (2009) 1303–1307. [11] J. Simon-Sanchez, et al., Genome-wide association study reveals genetic risk underlying Parkinson's disease, Nat. Genet. 41 (12) (2009) 1308–1312. [12] M.A. Nalls, et al., Imputation of Sequence Variants for Identification of Genetic Risks for Parkinson's Disease: A Meta-analysis of Genome-wide Association Studies, 3772011 641–649. [13] T.H. Hamza, et al., Common genetic variation in the HLA region is associated with late-onset sporadic Parkinson's disease, Nat. Genet. 42 (9) (2010) 781–785. [14] C.B. Do, et al., Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson's disease, PLoS Genet. 7 (6) (2011), e1002141. [15] T.L. Edwards, et al., Genome-wide association study confirms SNPs in SNCA and the MAPT region as common risk factors for Parkinson disease, Ann. Hum. Genet. 74 (2) (2010) 97–109. [16] E.M. Hill-Burns, et al., Identification of a novel Parkinson's disease locus via stratified genome-wide association study, BMC Genomics 15 (2014) 118. [17] M.A. Nalls, et al., Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease, Nat. Genet. 46 (9) (2014) 989–993. [18] S. Kim, et al., Alpha-synuclein induces apoptosis by altered expression in human peripheral lymphocyte in Parkinson's disease, FASEB J. 18 (13) (2004) 1615–1617. [19] J.J. Locascio, et al., Association between alpha-synuclein blood transcripts and early, neuroimaging-supported Parkinson's disease, Brain 138 (Pt 9) (2015) 2659–2671. [20] I.F. Mata, et al., SNCA variant associated with Parkinson disease and plasma α-synuclein level, Arch. Neurol. (2010) 67(11). [21] J. Fuchs, et al., Genetic variability in the SNCA gene influences α-synuclein levels in the blood and brain, FASEB J. 22 (5) (2007) 1327–1334. [22] L.F. Cardo, et al., Alpha-synuclein transcript isoforms in three different brain regions from Parkinson's disease and healthy subjects in relation to the SNCA rs356165/ rs11931074 polymorphisms, Neurosci. Lett. 562 (2014) 45–49. [23] I. Schmitt, et al., L-dopa increases α-synuclein DNA methylation in Parkinson's disease patients in vivo and in vitro, Mov. Disord. 30 (13) (2015) 1794–1801. [24] W. Reik, W. Dean, et al., Epigenetic reprogramming in mammalian development, Science 293 (5532) (2001) 1089–1093. [25] A. Bird, DNA methylation patterns and epigenetic memory, Genes Dev. 16 (1) (2002) 6–21. [26] E. Masliah, et al., Distinctive patterns of DNA methylation associated with Parkinson disease: identification of concordant epigenetic changes in brain and peripheral blood leukocytes, Epi. 8 (10) (2013) 1030–1038. [27] L. Matsumoto, et al., CpG demethylation enhances alpha-synuclein expression and affects the pathogenesis of Parkinson's disease, PLoS One 5 (11) (2010) 15522. [28] A. Jowaed, et al., Methylation regulates alpha-synuclein expression and is decreased in Parkinson's disease patients' brains, J. Neurosci. 30 (18) (2010) 6355–6359. [29] Y. Tan, et al., Methylation of α-synuclein and leucine-rich repeat kinase 2 in leukocyte DNA of Parkinson's disease patients, Parkinsonism Relat. Disord. 20 (3) (2014) 308–313. [30] S.X. Ai, et al., Hypomethylation of SNCA in blood of patients with sporadic Parkinson's disease, J. Neurol. Sci. 337 (1–2) (2014) 123–128. [31] L. Pihlstrøm, et al., Parkinson's disease correlates with promoter methylation in the α-synuclein gene, Mov. Disord. 30 (4) (2015) 577–580. [32] A.J. Hughes, et al., Accuracy of clinical diagnosis of idiopathic Parkinson's disease: a clinico-pathological study of 100 cases, J. Neurol. Neurosurg. Psychiatry 55 (3) (1992) 181–184. [33] P. 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Journal of the Neurological Sciences journal homepage: www.elsevier.com/locate/jns
The rs3756063 polymorphism is associated with SNCA methylation in the Chinese Han population Yang Wei a,1, Nannan Yang a,1, Qian Xu a, Qiying Sun a, Jifeng Guo a,b,c,d, Kai Li a, Zhenhua Liu a, Xinxiang Yan a,b,d, Xiongwei Zhu e, Beisha Tang a,b,c,d,⁎ a
Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China State Key Laboratory of Medical Genetics, Changsha, 410008, Hunan, People's Republic of China Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, 410008, Hunan, People's Republic of China d Neurodegenerative Disorders Research Center, Central South University, Changsha, 410008, Hunan, People's Republic of China e Institute of Pathology, Case Western Reserve University, Cleveland, OH 44106, USA b c
a r t i c l e
i n f o
Article history: Received 25 November 2015 Received in revised form 4 May 2016 Accepted 18 May 2016 Available online 19 May 2016 Keywords: Parkinson's disease SNCA Single nucleotide polymorphisms Methylation
a b s t r a c t Parkinson's disease (PD) is the second most common neurodegenerative disorder. Genome-wide association studies have confirmed the association of single nucleotide polymorphisms (SNPs) located in the SNCA gene with the risk of PD. While hypomethylation of the SNCA intron-1 was observed in patients with sporadic PD, an association between SNCA SNPs and SNCA methylation levels has been identified. To investigate whether these SNPs are associated with the level of SNCA methylation in the Chinese population, we genotyped SNCA SNPs and analyzed the relationship between SNCA SNPs and SNCA DNA methylation status from peripheral blood mononuclear cells of Chinese Han PD patients. Our results revealed that the rs3756063 polymorphism could contribute to the risk of PD in the Chinese Han population and confirmed the effect of this polymorphism on SNCA DNA methylation. Further studies will be needed to gain a better understanding of the mechanisms underlying the associations between SNPs, methylation and PD pathogenesis. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease (AD) and is characterized by the progressive loss of the dopaminergic neurons of the substantia nigra [1, 2]. It is generally considered that aging, genes and environmental factors influence the etiology of PD. Mutations in the alpha-synuclein gene (SNCA), encoding alpha-synuclein protein, the first to be identified in monogenic PD, account for approximately 2% of the autosomal dominant forms of early-onset PD [3,4]. Braak et al. later showed that the accumulation of alpha-synuclein protein in the brain is a hallmark of PD [5]. While most PD cases are sporadic, several case-control studies have reported that SNCA might be a susceptibility gene for sporadic PD and that its increased expression results in parkinsonian syndrome [6–9]. Genome-wide association studies have further confirmed that certain single nucleotide polymorphisms (SNPs) located in SNCA are associated with the risk of PD [10–17]. With the progress of study, researchers disproved the view that alpha-synuclein protein as a ‘neuron-specific’ protein in PD and indicated that high levels of alpha⁎ Corresponding author at: Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People's Republic of China. E-mail address: [email protected] (B. Tang). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.jns.2016.05.037 0022-510X/© 2016 Elsevier B.V. All rights reserved.
synuclein expression were found in peripheral [18,19]. Further studies showed that SNCA variants associated with alpha-synuclein levels in the blood as well as brain [20–23]. DNA methylation is the most intensely studied epigenetic mechanism and is characterized by the transfer of a methyl group from Sadenosylmethionine (SAM) to cytosine residues at the CpG dinucleotides on the DNA, which alters gene expression [24,25]. Because methylation status is related to the expression of gene transcripts, abnormal methylation patterns in the CpG islands of disease-associated genes might be involved in disease pathogenesis. Eliezer et al. identified that the level of genome-wide DNA methylation in brain and blood was consistent in PD patients [26]. The hypomethylation of SNCA intron-1 was observed in patients with sporadic PD, and the hypomethylation of this region could be associated with an increase in SNCA expression in vitro [27–29]. As we all known that SNCA variants associated with a-synuclein levels, and there was closely link between SNCA methylations level and SNCA expressions. We evaluated whether SNCA variants are associated with the SNCA methylation level, thus affecting the SNCA expression levels. In our previous study, we confirmed the hypomethylation of SNCA in the Chinese Han PD population and revealed the Rep1 polymorphism, which is located ~10 kb upstream of the translational start site of SNCA and was associated with SNCA DNA methylation [30]. Recently, Pihlstrøm et al. investigated the relationship between SNCA
12
Y. Wei et al. / Journal of the Neurological Sciences 367 (2016) 11–14
Table 1 Fundamental data, mean SNCA methylation levels and SNCA mRNA levels in PD patients and controls.
Gender (male/female) Age (years) Mean SNCA methylation levels (%) Mean SNCA-mRNA levels
PD (n = 91)
Controls (n = 92)
p
47/44 62.00 ± 9.72 14.27 ± 8.65 0.0015 ± 0.0007
49/43 62.27 ± 9.54 17.17 ± 8.89 0.0014 ± 0.0007
0.827 0.849 0.011 0.84
SNPs (including rs3756063, rs356165 and rs2245801) and determined that rs3756063 was associated with SNCA methylation levels [31]. However, it remains unknown whether these SNPs are associated with the SNCA methylation level in the Han population from mainland China. In this study, we genotyped SNCA SNPs and investigated the relationship between SNCA SNPs and SNCA DNA methylation status in Chinese Han PD patients. 2. Materials and methods 2.1. Subjects and SNCA transcript analysis A 30-ml sample of venous peripheral blood from 91 sporadic PD patients (mean ± SD age = 62.00 ± 9.72 years, female = 44, male = 47) and 92 controls (mean ± SD age = 62.27 ± 9.54 years, female = 49, male = 43) were collected in ethylenediamine tetra-acetate (EDTA) vacutainer tubes. The Department of Neurology, Xiangya Hospital, Central South University, the National Laboratory of Medical Genetics of China and the Neurodegenerative Disorders Research Center, Central South University approved the inclusion of the 91 sporadic PD patients, who were diagnosed by United Kingdom PD Brain Bank Criteria [32]. The Health Examine Center of Second Xiangya Hospital approved the inclusion of the 92 controls. All patients and controls signed an informed consent to participate in the project. The genomic DNA was prepared using the TIA Namp Genomic DNA blood kit (Tiangen Biotech, Beijing, China), total RNA was isolated using the standard Trizol method (Qiagen), and all of the samples were stored at −80 °C. The study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics committee of Central South University. 2.2. Sodium bisulfite sequencing Briefly, an Epitect Bisulfite Kit (Qiagen) was used for the bisulfite conversion. The converted product was purified and amplified by polymerase chain reaction (PCR) using primer sequences described previously [33]. The PCR products were then cloned into the pGEM-T easy vector (Promega, Madison, WI, U.S.A.), and for each subject, N10
independent clones were sequenced to study the CpG site methylation levels. A BiQ analyzer (quality control software for DNA methylation data from bisulfite sequencing) served as a control. 2.3. cDNA synthesis and real-time quantitative PCR (RT-PCR) The mRNA levels of SNCA determined by RT-PCR were used to analyze SNCA expression. First, cDNA was synthesized from total RNA using the RevertAid™ First Strand cDNA synthesis Kit (Fermentas, Burlington, Canada). We then performed RT-PCR using a ABI 7900 HT Fast Real-time PCR system (Applied Biosystems, Inc., Foster City, CA), and the SYBR Premix Ex Taq™ real-time PCR Kit (Takara Biotech, Co., Dalian, China); primer sequences have been described previously [26]. 2.4. SNCA rs356182/rs356165/rs2245801/rs3756063 genotyping Four SNCA SNPs (rs356182/rs356165/rs2245801/rs3756063) were reported in genome-wide association studies and were studied. All of the SNPs were genotyped by PCR. 2.5. Statistical analyses The Statistical Package for Social Sciences (SPSS, version 17.0) was used for all statistical analyses. A p b 0.05 was considered to be statistically significant. The frequencies and percentages of allelic genotypes and the mRNA and DNA methylation levels between patients and controls were compared by using a Chi-square test. The association between mRNA and DNA methylation levels was assessed by using a Pearson correlation. To compare the association of mRNA or DNA methylation levels with gender, age, disease status and SNP genotypes, a linear regression analysis was used. 3. Results There were no significant differences in gender or age distribution between the patients and controls. The mean DNA methylation level of SNCA intron-1 in PD patients was lower than that of controls (p =
Table 2 Allele frequencies of four SNPs in PD patients and controls. PD (na =182)
Controls (na =184)
Pb
OR
95% CI
rs3756063c G C
19 (10.4%) 163 (89.6%)
33 (17.9%) 151 (82.1%)
0.042
1.875
1.022–3.438
rs356182 G A
63 (34.6%) 119 (65.4%)
69 (37.5%) 115 (62.5%)
0.566
0.939
0.759–1.163
rs356165 G A
87 (47.8%) 95 (52.2%)
94 (51.1%) 90 (48.9%)
0.832
0.956
0.635–1.440
rs2245801 T C
20 (11.0%) 162 (89.0%)
32 (17.4%) 152 (62.6%)
0.082
1.705
0.935–3.110
a b c
n = 2 * case numbers. p values presented were corrected for by linear regression analysis, adjusting for gender, age and disease status. rs3756063 C allele had a significantly higher frequency among the patients.
Y. Wei et al. / Journal of the Neurological Sciences 367 (2016) 11–14
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Table 3 SNCA methylation levels and SNCA-mRNA levels among different SNPs alleles and genotypes in PD patients and controls. The mean SNCA methylation levels (%)
The mean SNCA -mRNA levels
PD
Controls
PD
Controls
rs3756063a GG + GC CC p
23.32 ± 8.91 12.04 ± 6.25 b0.001
19.30 ± 8.76 16.20 ± 8.34 0.094
0.0014 ± 0.0007 0.0016 ± 0.0009 0.833
0.0015 ± 0.0006 0.0015 ± 0.0007 0.891
rs356182 GG + GA AA p
14.21 ± 8.83 14.67 ± 7.74 0.864
16.88 ± 8.79 19.54 ± 9.12 0.290
0.0014 ± 0.0008 0.0016 ± 0.0009 0.715
0.0014 ± 0.0007 0.0016 ± 0.0007 0.743
rs356165 GG + GA AA p
13.67 ± 8.10 16.40 ± 10.35 0.285
15.97 ± 7.62 18.35 ± 11.03 0.180
0.0014 ± 0.0007 0.0014 ± 0.0009 0.810
0.0015 ± 0.0007 0.0014 ± 0.0008 0.792
rs2245801 TT + TC CC p
16.11 ± 9.56 14.79 ± 7.21 0.254
17.71 ± 10.28 15.49 ± 7.54 0.314
0.0015 ± 0.0009 0.0014 ± 0.0007 0.73
0.0016 ± 0.0008 0.0014 ± 0.0007 0.801
a
rs3756063 GG + GC/CC had a significantly difference DNA methylation levels among the patients.
0.011), and there was no significant difference in the mean SNCA mRNA levels between PD patients and controls (Table 1). SNCA SNP genotyping was performed, and the allelic distribution and frequencies are listed in Table 2. The results showed that the rs3756063 C allele was observed at a significantly higher frequency among the patients (p = 0.042, OR = 1.875, 95%CI = 1.022–3.438), while the other three SNPs (rs356182/rs356165/rs2245801) had no significant allelic distribution between PD patients and controls. We then analyzed the linkage disequilibrium between these four SNPs by using the program SHEsis (http://analysis.bio-x.cn/myAnalysis.php),the result showed no linkage disequilibrium between these four SNPs (r2 b 0.08). Further analysis showed that no linkage disequilibrium between rs3756063 and the common SNPs of southern Chinese Han population (including rs3822086, rs356220, rs2736990 and rs356219) (r2 b 0.2), analyzed the data provided by the program 1000 genomes (http://asia.ensembl.org/Homo_ sapiens/Variation/Population?db=core;r=4:89704460-89705460;v= rs356182;vdb=variation;vf=226270#373515_tablePanel) using the program SHEsis (http://analysis.bio-x.cn/myAnalysis.php). The results suggested that rs3756063 C allele might had independent effects with the risk of PD. We performed a linear regression analysis to investigate the association between DNA methylation levels of SNCA intron-1 and SNP genotype while adjusting for disease status, gender and age. The results showed that the DNA methylation levels of SNCA intron-1 were significant lower in the patients without the rs3756063 allele G compared to those patients carrying allele G (p b 0.001). Therefore, the CC genotype
Fig. 1. SNCA methylation levels in different alleles of rs3756063 (A) and different genotypes (B) in PD patients. SNCA intron-1 methylation levels were significant lower in the patients who did not carry rs3756063 allele G compared to those patients who carried allele G (p b 0.001), and the rs375606 genotype CC showed lower DNA methylation levels than the patients who carried GG and GC. (GC + GG vs.CC p b 0.001).
of rs375606 showed decreased DNA methylation levels compared to the patients harboring GG or GC genotypes (GC + GG vs.CC p b 0.001) (Table 3, Fig. 1). However, no significant differences in DNA methylation levels were found for the rs356182, rs356165 or rs2245801 SNPs. No significant differences were identified between the SNCA-mRNA level and allelic states or different genotypes of these four SNPs.
4. Discussion PD is a common neurodegenerative disorder affected by many complex factors. Since the first gene (SNCA) implicated in PD was found, many studies have focused on it. GWAS and large-scale meta-analysis have identified many risk loci or SNPs (including rs356165/rs356182/ rs2245801/rs3756063 located on SNCA) that are associated with the risk of PD, while the causal mechanisms remain unclear [10–17]. Subsequent studies confirmed the association between SNCA variants and alpha-synuclein levels, while the causal mechanisms remain unclear. With the progress of epigenetics, the hypomethylation of SNCA intron1 was observed in patients with sporadic PD, and the hypomethylation of this region could be associated with an increase in SNCA expression by promoting transcription of the gene [27–29]. Recently, Pihlstrøm et al. investigated the relationship between SNCA SNPs and determined that rs3756063 was associated with SNCA methylation levels [31]. In our study, we determined that rs3756063 was related to the risk of PD in the Chinese Han population. We further investigated the relationship between the four SNPs and the levels of DNA methylation in SNCA intron-1, and we found that rs3756063 was also associated with SNCA intron-1 methylation levels. To investigate the mechanism underlying the contribution of rs3756063 to the risk of PD and the association between that polymorphism and the methylation of SNCA intron-1, we searched for a potential transcription binding site in the sequences around this SNP using MatInspector 8.0 software (Genomatix, Oakland, CA, USA). Our analysis revealed many potential binding sites for transcription factors, and the binding sites with the highest score values (core similarity = 1; matrix similarity = 1) in the ±50 bp around the SNP were Myc interacting zinc finger protein 1 (Miz 1), transcription factor II B (TFIIB) and pleiomorphic adenoma gene (PLAG.). It is worth noting that the core binding sequence of a putative TFIIB binding site is contained within the SNP site. However, whether these potential transcription factor binding sites are functional remains unknown, and further investigation is needed to clarify whether the variant contributes to PD risk by altering transcription factor binding and DNA methylation.
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We did not observe an association between SNCA mRNA levels and rs3756063, which is consistent with another previous study [31]. In our previous study, we also found that the Rep1 polymorphism was associated with SNCA DNA methylation but not with SNCA mRNA expression [30]. A recent study showed similar results with our research, the researchers considered it was probably because intracellular SNCA transcript levels reduced as a consequence of intracellular alpha-synuclein protein accumulation, leading a feedback repression of transcription [19]. Other studies have shown that levodopa increases SNCA methylation levels, lower levels of SNCA transcription in PD patients [23]. Because of the limited sample size, we did not compare the differences of SNCA transcript levels in patients taking levodopa and those patients who not taking in our study, this is our shortcomings. Other mechanisms may be involved in the regulation of SNCA mRNA, and a larger sample size is needed to further verify these results. PD is characterized by the progressive loss of the dopaminergic neurons of the substantia nigra and accumulation of alpha-synuclein protein in the brain, and the ideal experimental subject is human brain tissue. Due to the limitations of human brain tissue, researchers have focused on PD biomarkers. Many studies based on peripheral blood of patients with PD [19,20,23], and have shown that concordant methylation alterations in brain and blood in PD patients [21,26,31], suggesting that blood might hold promise as a surrogate for brain tissue and as a source for biomarker discovery. Considering these factors we used peripheral blood mononuclear cells (PBMC) for this study, and there were on similar studies in Chinese Han PD patients. However we must recognize that the situation in peripheral blood and brain tissue is not completely consistent, relevant research is needed to further validate by using brain, and larger multicenter sample study is required to be verify as the patients in our study were limited . Taken together, our results revealed that rs3756063 might contribute to the risk of PD in the Chinese Han population and confirmed the effect of this polymorphism on SNCA DNA methylation. Further studies are needed to better understand the mechanisms underlying the associations between SNPs, methylation and PD pathogenesis. Declaration of interest No conflict of interest exits in the submission of this manuscript. Acknowledgments The authors would like to thank all the patients and control subjects for participation in this study. This work was supported by grants from the NSFC-NIH joint program (81361120404), the key program of the National Natural Science Foundation of China(81430023) and the Major State Basic Research Development Program of China (973 Program) (2011CB510000). References [1] M.G. Spillantini, et al., Alpha-synuclein in Lewy bodies, Nature 388 (6645) (1997) 839–840. [2] M. Goedert, et al., 100 years of Lewy pathology, Nat. Rev. Neurol. 9 (1) (2013) 13–24.
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