# Variants in the 3′ End of SLC6A3 in Northwest Han Population with Parkinson’s

Authors: Peiye Chang; Yongwang Fu; Ping Zhao; Chunmei Wang; Mingfang Jiang; Rui Li; Yulin He
Journal: Parkinson’s Disease
 (2019)

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## Abstract

Parkinson’s disease (PD) is one of the most common neurodegenerative disorders in neurology. It is possible that multifactorial and genetic factors are related to its pathogenesis. Recently, there have been reports of SLC6A3 genetic variants leading to PD. However, the role of 3′ end of SLC6A3 in PD is less studied in different ethnic groups. To explore the roles of 3′ end of SLC6A3 in PD development, 17 SNP sites in 3′ end of SLC6A3 were analyzed in 360 PD patients and 392 normal controls of Han population residing in northwest of China. The significant difference of gene type and allele frequencies between the PD and control groups was detected only in rs40184 (P = 0.013 and 0.004, respectively; odds ratio 2.529, 95% confidence interval 1.325–4.827). The genotype and allele frequencies of the other 16 SNP sites were not found to be different between the PD group and the control group. rs2550936, rs3776510, and rs429699 were selected to construct the haplotypes; no significant difference was found in a frequency of 5 haplotypes between the PD group and the control group. These results suggest that the SLC6A3 variant in rs40184 A allele may increase the risk of PD in northwest Han population and may be a biomarker of PD.


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## Body

## 1. Introduction

Parkinson’s disease (PD) is a neurodegenerative disease; its prevalence increases with age, and PD influences 1% of the population over 60 years [1, 2]. Due to the high disability rate and long course of illness, PD has seriously impacted the quality of life of middle-aged and elderly people. Worldwide, the burden of medical expenses on Parkinson’s disease has risen from 2.5 million patients in 1990 to 6.1 million patients in 2016, almost doubled in 26 years [3]. The detail mechanism of the etiology and pathogenesis of PD is still unknown. The evidence from most studies showed that PD was a complex multifactor disease influenced by environmental and genetic factors [4, 5], in which genetic factors play a critical role [6–8]. Up to now, the genetic susceptibility of Parkinson’s disease is mainly focused on the screening of new genes in the PD family and the exploring of susceptible genes in patients. The genetic susceptibility genes in patients are mainly concentrated in the dopamine metabolic system genes, including the catecholamine oxymethyltransferase gene, the monoamine oxidase gene, the dopamine receptor gene, and the dopamine transporter (DAT) gene (gene symbol: SLC6A3), in which the DAT gene plays an essential role in the pathogenesis of PD. DAT is a transmembrane protein which is expressed by the presynaptic dopamine neuron. The main function of DAT is to reuptake dopamine released into the synaptic space and to stop the transmission of information among nerve cells [9, 10]. In addition, neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) enters into the synapse cell through DAT. Finally, MPTP destroys the black dopaminergic neurons by oxidative stress.Since PD is characterized by the selective loss of dopaminergic neurons, genes that affect the expression of dopaminergic neurons may become candidate genes for PD. The evidence from genetic studies revealed that variants in SLC6A3 were associated with PD [11–13]. The most extensively studied polymorphism was the variable number of tandem repeats (VNTR) in the 3′untranslated region (UTR) of SLC6A3 gene. However, the results from a number of related studies have not yet reached a consensus on its genetic correlation with PD. Moreover, there are few related studies on other polymorphisms at the 3′ end of SLC6A3 and PD. In order to further investigate the correlation between SLC6A3 and PD in northwest Han population, we performed a variants study in 3′ end of SLC6A3 in 360 PD patients and 392 healthy controls.


## 2. Materials and Methods

### 2.1. Patients

A cohort of 360 Chinese Han PD patients (63.5 ± 10.4 years) were enrolled. All the patients came from the Inner Mongolia Medical University Affiliated Hospital, Hohhot, China, and Bayannaoer City Hospital, Bayannaoer, China, between 2015 and 2018. All patients live in northwest of China and were not related to each other. All patients were examined by experienced neurologists, and the diagnosis of PD was based on clinical criteria [14]. The control group consisted of 392 age- and sex-matched healthy persons (63.7 ± 9.7 years) from the same geographic areas. This study was approved by the Institutional Review Board of the Inner Mongolia Medical University, Hohhot, China. The study obtained the informed consent of all participants.


### 2.2. Selection of Single-Nucleotide Polymorphisms (SNPs)

TagSNPs were selected from the Chinese HapMap database (http://www.hapmap.org), which is based on pairwise r2 ≥ 0.8 and minor allele frequency (MAF) ≥0.1. In this study, we chose 17 tagSNPs (rs2270913, rs27048, rs2270914, rs2550936, rs11133767, rs3776510, rs429699, rs11564759, rs27047, rs6347, rs40184, rs37022, rs10036478, rs2652514, rs2981359, rs365663 and rs11133770) from the 3′ end of SLC6A3.


### 2.3. Genotyping

Genomic DNA was extracted from leukocytes in a peripheral blood sample using a blood DNA extraction kit (TIANamp Blood DNA kit; TIANGEN BIOTECH, Beijing, China), which was stored at −20°C. Gene typing was performed using the polymerase chain reaction (PCR)/ligase detection reaction assay. Primers were synthesized by HAYU Biological Engineering LTD in Shanghai; the information of the primers is shown in Table1. The probe for each group of ligase detection reactions consists of one common probe and two discriminating probes for the two types, as shown in Table 2.Table 1
Primer of single-nucleotide polymorphisms of SLC6A3.
Gene
Upstream primer
Downstream primer
PCR length
rs2270913
GGTTCCCCTACCTGTGCTAC
AACAGCTTCATCTCGTTTCCG
129
rs27048
AAAGGCGGAGGAGGTGTTC
CCAAACTGCGTTGACTTTTGG
135
rs2270914
GGTTCCCCTACCTGTGCTAC
AACAGCTTCATCTCGTTTCCG
129
rs2550936
CTCCCAAATAATCACGGGGC
GCAGTTGGGTTCCTTCCACC
124
rs11133767
GAGAGGGTGAGCTCCTGAAG
TGCTTTTTGTCACCTGCAGC
139
rs3776510
ACAGAGGAAGGGAGAAAGTGC
GAGAGGGGCGTGGATTTCTC
139
rs429699
CCTCACGGAGCCTTTTTCAG
TTTGGAGTGCTCATCGAAGC
126
rs11564759
AGCGCCCTTGGGAGTTCATG
CACCCAGGGCAGATCTTCC
131
rs27047
ACAAATCACACACGTCCACAC
CCACGTCTAACCTCACGGG
139
rs6347
GGGTTCTGTTTCAGGGCCAG
GATACCCAGGGTGAGCAGC
118
rs40184
TCTGATCAATACGCCCCAGAG
CCAACACACCCTTGACAGG
140
rs37022
TGCTTGCTTTGACCTTTATGG
CCAGCGCCCACTCTCAGTG
140
rs10036478
TCCCAGTTAGGAGCAGGGAG
GAGCTAAAAGGCCATCCAGC
134
rs2652514
CCAGAACCCAGCCACAGAG
ATAGAGGCCAATGAGGGAGG
138
rs2981359
CAGAGTTTAGGAAAGGGAGGC
CGCAGGCTGTTCTTTGGACC
140
rs365663
GTGAGACGCTGGCCATGTC
TTGCCAACCCTGAGGAACAC
138
rs11133770
ACACCTCTGACCACAGTGTG
AAGCCTGGGTTGTGGTCATC
125Table 2
Probe of single-nucleotide polymorphisms of SLC6A3.
Probe name
Sequence (5′–3′)
LDR length
rs2270913_modify
P-GGGGGTCTAGGGCAGCCGTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2270913_A
TTTTTTTTTTTTTTTTTTCTCCCTGAGCATGCTGGCCGGGT
81
rs2270913_G
TTTTTTTTTTTTTTTTTTTTCTCCCTGAGCATGCTGGCCGGGC
83
rs27048_modify
P-AGTCTGCCTGCTGGTAGCAGTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs27048_C
TTTTTTTTTTTTTTTTTTTTTTCTCGTCCCCTCCACCTCCATCCG
89
rs27048_T
TTTTTTTTTTTTTTTTTTTTTTTTCTCGTCCCCTCCACCTCCATCCA
91
rs2270914_modify
P-GACCCCCGCCCGGCCAGCATTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2270914_G
TTTTTTTTTTTTTTTTTTTTTTTTTTGCCTTGGCCCCGGCTGCCCCTAC
95
rs2550936_modify
P-ACGGCCCCCAGACCTCCTGTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2550936_A
TTTTTTTTTTTTTTTTTTTTTTTTTTAGGCAAGATCCCTGGGCTCACGT
97
rs2550936_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTAGGCAAGATCCCTGGGCTCACGG
99
rs11133767_modify
P-GCTGCGGCAGCTCCTGGGGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11133767_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTAACGTGCCTTCCTTCCACTGCCT
101
rs11133767_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAACGTGCCTTCCTTCCACTGCCC
103
rs3776510_modify
P-GCTTCTCCCCATCTCCCGTGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs3776510_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGTGCAGGTCGCCAGGGCCG
105
rs3776510_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGTGCAGGTCGCCAGGGCCA
107
rs429699_modify
P-CCCCCGGACTCACCATAGAATTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs429699_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGGTGCCGGCTTGGCTGCCTT
109
rs429699_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGGTGCCGGCTTGGCTGCCTC
111
rs11564759_modify
P-GGTCTCATGGGGTCTCGGGGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11564759_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAAGATGCAGATCCTGACTGGGCG
113
rs11564759_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAAGATGCAGATCCTGACTGGGCA
115
rs27047_modify
P-TGTGCCTGGAAGGCGGAGGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs27047_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTGGGAGGACCTCAGCTTCCTCG
117
rs27047_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTGGGAGGACCTCAGCTTCCTCA
119
rs6347_modify
P-GAGGACAGAGGGAGCGTGGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs6347_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGAAGACCACGGCCCAGGCT
121
rs6347_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGAAGACCACGGCCCAGGCC
123
rs2652514_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGGGATCACCAATGTTCTTGGACA
172
rs2981359_modify
P-AAACAGGAGGCAGAGCCAAGCTGCCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2981359_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCTTTCCAAAGCGAAGATAGCCTCTGG
175
rs2981359_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCTTTCCAAAGCGAAGATAGCCTCTGC
177
rs365663_modify
P-TTAGTGGGGCAGCTCAGCAGTCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs365663_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTATTCATGGCACATGGAGGAAGCACCG
180
rs365663_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTATTCATGGCACATGGAGGAAGCACCA
182
rs11133770_modify
P-TGATGGGATCAGTGAGGTGCTTAGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11133770_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGGGAGAGGCTTGGCACTGGTCCCTT
185
rs11133770_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGGGAGAGGCTTGGCACTGGTCCCTG
187The multiplex PCR methods were used to amplify the target DNA sequences. The final volume of PCRs for each subject was 20μl, which contained 1X PCR buffer, 3.0 mM/L·MgCl2, 2.0 mM/L deoxynucleotide triphosphate, 0.5 μmol/μl primer mix, 5 U/μl Qiagen HotStarTaq Polymerase (QIAGEN, Shenzhen, China), 1X Q-solution, and 50 ng/μl genomic DNA. The thermal cycle was carried out in GeneAmp PCR system 9600 (Norwalk, CT.06859, USA). The initial denaturation was 2 min at 95°C, followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 56°C for 90 s, and extension at 72°C for 1 min. The final extension of 72°C is 10 min.The total volume of the ligase detection reaction is 10μl for each subject, which contains 1X NEB Taq DNA ligase buffer 1 μl, 2 pmol of each probe mix 1 μl, 5 U/μl Taq DNA ligase 0.05 μl (BIOWING, Jiangsu, China), and 4 μl multi-PCR product. A total of 40 ligase detection reaction cycles were performed under conditions of 92°C for 2 min, 94°C for 15 s, and 50°C for 25 s. The fluorescent products of ligase detection reaction were identified by PRISM 3730 (ABI). The experimental methods are similar to Chang et al. [15].


### 2.4. Statistical Analysis

Statistical analysis was carried out by the Statistical Program for Social Sciences (SPSS version 11.0). Hardy-Weinberg equilibrium of each group was determined by using the chi-squared test. Allele and genotype frequencies between groups were studied using SHEsis software [16]. We use SHEsis software to calculate the coefficient D′ of linkage disequilibrium (LD) and to build haplotypes. A haplotype with a frequency of less than 3% is considered rare and ignored. When D′ is more than 0.8, it is considered that there is a strong linkage disequilibrium. A P value of 0.05 was considered to have statistical significance.


## 2.1. Patients

A cohort of 360 Chinese Han PD patients (63.5 ± 10.4 years) were enrolled. All the patients came from the Inner Mongolia Medical University Affiliated Hospital, Hohhot, China, and Bayannaoer City Hospital, Bayannaoer, China, between 2015 and 2018. All patients live in northwest of China and were not related to each other. All patients were examined by experienced neurologists, and the diagnosis of PD was based on clinical criteria [14]. The control group consisted of 392 age- and sex-matched healthy persons (63.7 ± 9.7 years) from the same geographic areas. This study was approved by the Institutional Review Board of the Inner Mongolia Medical University, Hohhot, China. The study obtained the informed consent of all participants.


## 2.2. Selection of Single-Nucleotide Polymorphisms (SNPs)

TagSNPs were selected from the Chinese HapMap database (http://www.hapmap.org), which is based on pairwise r2 ≥ 0.8 and minor allele frequency (MAF) ≥0.1. In this study, we chose 17 tagSNPs (rs2270913, rs27048, rs2270914, rs2550936, rs11133767, rs3776510, rs429699, rs11564759, rs27047, rs6347, rs40184, rs37022, rs10036478, rs2652514, rs2981359, rs365663 and rs11133770) from the 3′ end of SLC6A3.


## 2.3. Genotyping

Genomic DNA was extracted from leukocytes in a peripheral blood sample using a blood DNA extraction kit (TIANamp Blood DNA kit; TIANGEN BIOTECH, Beijing, China), which was stored at −20°C. Gene typing was performed using the polymerase chain reaction (PCR)/ligase detection reaction assay. Primers were synthesized by HAYU Biological Engineering LTD in Shanghai; the information of the primers is shown in Table1. The probe for each group of ligase detection reactions consists of one common probe and two discriminating probes for the two types, as shown in Table 2.Table 1
Primer of single-nucleotide polymorphisms of SLC6A3.
Gene
Upstream primer
Downstream primer
PCR length
rs2270913
GGTTCCCCTACCTGTGCTAC
AACAGCTTCATCTCGTTTCCG
129
rs27048
AAAGGCGGAGGAGGTGTTC
CCAAACTGCGTTGACTTTTGG
135
rs2270914
GGTTCCCCTACCTGTGCTAC
AACAGCTTCATCTCGTTTCCG
129
rs2550936
CTCCCAAATAATCACGGGGC
GCAGTTGGGTTCCTTCCACC
124
rs11133767
GAGAGGGTGAGCTCCTGAAG
TGCTTTTTGTCACCTGCAGC
139
rs3776510
ACAGAGGAAGGGAGAAAGTGC
GAGAGGGGCGTGGATTTCTC
139
rs429699
CCTCACGGAGCCTTTTTCAG
TTTGGAGTGCTCATCGAAGC
126
rs11564759
AGCGCCCTTGGGAGTTCATG
CACCCAGGGCAGATCTTCC
131
rs27047
ACAAATCACACACGTCCACAC
CCACGTCTAACCTCACGGG
139
rs6347
GGGTTCTGTTTCAGGGCCAG
GATACCCAGGGTGAGCAGC
118
rs40184
TCTGATCAATACGCCCCAGAG
CCAACACACCCTTGACAGG
140
rs37022
TGCTTGCTTTGACCTTTATGG
CCAGCGCCCACTCTCAGTG
140
rs10036478
TCCCAGTTAGGAGCAGGGAG
GAGCTAAAAGGCCATCCAGC
134
rs2652514
CCAGAACCCAGCCACAGAG
ATAGAGGCCAATGAGGGAGG
138
rs2981359
CAGAGTTTAGGAAAGGGAGGC
CGCAGGCTGTTCTTTGGACC
140
rs365663
GTGAGACGCTGGCCATGTC
TTGCCAACCCTGAGGAACAC
138
rs11133770
ACACCTCTGACCACAGTGTG
AAGCCTGGGTTGTGGTCATC
125Table 2
Probe of single-nucleotide polymorphisms of SLC6A3.
Probe name
Sequence (5′–3′)
LDR length
rs2270913_modify
P-GGGGGTCTAGGGCAGCCGTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2270913_A
TTTTTTTTTTTTTTTTTTCTCCCTGAGCATGCTGGCCGGGT
81
rs2270913_G
TTTTTTTTTTTTTTTTTTTTCTCCCTGAGCATGCTGGCCGGGC
83
rs27048_modify
P-AGTCTGCCTGCTGGTAGCAGTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs27048_C
TTTTTTTTTTTTTTTTTTTTTTCTCGTCCCCTCCACCTCCATCCG
89
rs27048_T
TTTTTTTTTTTTTTTTTTTTTTTTCTCGTCCCCTCCACCTCCATCCA
91
rs2270914_modify
P-GACCCCCGCCCGGCCAGCATTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2270914_G
TTTTTTTTTTTTTTTTTTTTTTTTTTGCCTTGGCCCCGGCTGCCCCTAC
95
rs2550936_modify
P-ACGGCCCCCAGACCTCCTGTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2550936_A
TTTTTTTTTTTTTTTTTTTTTTTTTTAGGCAAGATCCCTGGGCTCACGT
97
rs2550936_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTAGGCAAGATCCCTGGGCTCACGG
99
rs11133767_modify
P-GCTGCGGCAGCTCCTGGGGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11133767_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTAACGTGCCTTCCTTCCACTGCCT
101
rs11133767_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAACGTGCCTTCCTTCCACTGCCC
103
rs3776510_modify
P-GCTTCTCCCCATCTCCCGTGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs3776510_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGTGCAGGTCGCCAGGGCCG
105
rs3776510_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGTGCAGGTCGCCAGGGCCA
107
rs429699_modify
P-CCCCCGGACTCACCATAGAATTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs429699_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGGTGCCGGCTTGGCTGCCTT
109
rs429699_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAGGGTGCCGGCTTGGCTGCCTC
111
rs11564759_modify
P-GGTCTCATGGGGTCTCGGGGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11564759_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAAGATGCAGATCCTGACTGGGCG
113
rs11564759_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTAAGATGCAGATCCTGACTGGGCA
115
rs27047_modify
P-TGTGCCTGGAAGGCGGAGGTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs27047_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTGGGAGGACCTCAGCTTCCTCG
117
rs27047_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGTGGGAGGACCTCAGCTTCCTCA
119
rs6347_modify
P-GAGGACAGAGGGAGCGTGGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs6347_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGAAGACCACGGCCCAGGCT
121
rs6347_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGAAGACCACGGCCCAGGCC
123
rs2652514_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGAAGGGATCACCAATGTTCTTGGACA
172
rs2981359_modify
P-AAACAGGAGGCAGAGCCAAGCTGCCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs2981359_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCTTTCCAAAGCGAAGATAGCCTCTGG
175
rs2981359_G
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCTTTCCAAAGCGAAGATAGCCTCTGC
177
rs365663_modify
P-TTAGTGGGGCAGCTCAGCAGTCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs365663_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTATTCATGGCACATGGAGGAAGCACCG
180
rs365663_T
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTATTCATGGCACATGGAGGAAGCACCA
182
rs11133770_modify
P-TGATGGGATCAGTGAGGTGCTTAGCTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT-FAM
rs11133770_A
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGGGAGAGGCTTGGCACTGGTCCCTT
185
rs11133770_C
TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGGGGAGAGGCTTGGCACTGGTCCCTG
187The multiplex PCR methods were used to amplify the target DNA sequences. The final volume of PCRs for each subject was 20μl, which contained 1X PCR buffer, 3.0 mM/L·MgCl2, 2.0 mM/L deoxynucleotide triphosphate, 0.5 μmol/μl primer mix, 5 U/μl Qiagen HotStarTaq Polymerase (QIAGEN, Shenzhen, China), 1X Q-solution, and 50 ng/μl genomic DNA. The thermal cycle was carried out in GeneAmp PCR system 9600 (Norwalk, CT.06859, USA). The initial denaturation was 2 min at 95°C, followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 56°C for 90 s, and extension at 72°C for 1 min. The final extension of 72°C is 10 min.The total volume of the ligase detection reaction is 10μl for each subject, which contains 1X NEB Taq DNA ligase buffer 1 μl, 2 pmol of each probe mix 1 μl, 5 U/μl Taq DNA ligase 0.05 μl (BIOWING, Jiangsu, China), and 4 μl multi-PCR product. A total of 40 ligase detection reaction cycles were performed under conditions of 92°C for 2 min, 94°C for 15 s, and 50°C for 25 s. The fluorescent products of ligase detection reaction were identified by PRISM 3730 (ABI). The experimental methods are similar to Chang et al. [15].


## 2.4. Statistical Analysis

Statistical analysis was carried out by the Statistical Program for Social Sciences (SPSS version 11.0). Hardy-Weinberg equilibrium of each group was determined by using the chi-squared test. Allele and genotype frequencies between groups were studied using SHEsis software [16]. We use SHEsis software to calculate the coefficient D′ of linkage disequilibrium (LD) and to build haplotypes. A haplotype with a frequency of less than 3% is considered rare and ignored. When D′ is more than 0.8, it is considered that there is a strong linkage disequilibrium. A P value of 0.05 was considered to have statistical significance.


## 3. Results

### 3.1. Association Study of TagSNPs and PD

The genotype and allele frequencies of the 3′ end of SLC6A3 are summarized in Table3. No deviation from Hardy–Weinberg equilibrium was evident in the PD and control groups (P>0.05). Statistically significant differences in genotype and allele frequencies were found in the SLC6A3 variant rs40184 between PD (AA 5.6%, AG 47.2%, and GG 47.2%) and controls (AA 2.0%, AG 24.0%, and GG 74.0%). The frequency of the minor A allele was 29.2% in patients and 14.0% in controls. There was no significant difference in genotype and allele frequencies for other 16 SNP polymorphism sites in the 3′ end of SLC6A3.Table 3
Frequency distribution of SLC6A3 genotypes and alleles.
Gene
Allele/genotype
PD (n)
Control (n)
χ
2
P
OR
95% CI
rs2270913
C
698 (1.000)
768 (1.000)
C/C
349 (1.000)
384 (1.000)
rs27048
C
620 (0.912)
652 (0.867)
0.939
0.332
0.585
0.620–4.0483
T
60 (0.088)
100 (0.133)
C/C
280 (0.824)
276 (0.734)
C/T
60 (0.176)
100 (0.266)
1.089
0.297
1.691
0.626–4.566
rs2270914
G
700 (1.000)
768 (1.000)
G/G
350 (1.000)
384 (1.000)
rs2550936
A
651 (0.930)
712 (0.908)
C
49 (0.070)
72 (0.092)
0.271
0.602
1.315
0.469–3.685
A/A
301 (0.860)
320 (0.816)
A/C
49 (0.140)
72 (0.184)
0.301
0.584
0.350
0.460–3.960
rs11133767
A
31 (0.043)
36 (0.046)
G
669 (0.956)
748 (0.954)
0.011
0.914
0.930
0.245–3.539
A/G
31 (0.089)
36 (0.092)
G/G
319 (0.911)
356 (0.908)
0.012
0.914
0.927
0.236–3.640
rs3776510
C
668 (0.954)
744 (0.949)
T
32 (0.046)
40 (0.051)
0.074
0.786
1.201
0.321–4.495
C/C
318 (0.909)
352 (0.898)
C/T
32 (0.091)
40 (0.102)
0.078
0.780
1.212
0.314–4.686
rs429699
C
500 (0.714)
592 (0.755)
T
200 (0.286)
192 (0.245)
0.452
0.502
0.811
0.440–1.495
C/C
190 (0.543)
220 (0.561)
C/T
120 (0.343)
152 (0.388)
T/T
40 (0.114)
20 (0.051)
1.679
0.43
rs11564759
C
403 (0.576)
443 (0.589)
T
297 (0.424)
309 (0.411)
0.076
0.783
0.924
0.531–1.611
C/C
131 (0.374)
116 (0.309)
C/T
141 (0.403)
211 (0.561)
T/T
78 (0.223)
49 (0.130)
3.303
0.192
rs27047
C
450 (0.643)
488 (0.622)
T
250 (0.357)
296 (0.378)
0.092
0.762
1.092
0.619–1.926
C/C
150 (0.429)
160 (0.408)
C/T
150 (0.429)
168 (0.429)
T/T
50 (0.143)
64 (0.163)
0.094
0.954
rs6347
A
641 (0.914)
771 (0.920)
G
59 (0.086)
67 (0.080)
0.001
0.979
1.013
0.383–2.682
A/A
291 (0.831)
325 (0.829)
A/G
59 (0.169)
67 (0.171)
0.001
0.978
1.014
0.365–2.821
rs40184
A
210 (0.292)
112 (0.140)
G
510 (0.708)
688 (0.860)
8.245
0.004∗
2.529
1.325–4.827
A/A
20 (0.056)
8 (0.020)
A/G
170 (0.472)
96 (0.240)
G/G
170 (0.472)
296 (0.740)
8.760
0.013∗
rs37022
A
314 (0.431)
402 (0.502)
T
406 (0.569)
398 (0.498)
1.337
0.246
0.726
0.422–1.250
A/A
73 (0.194)
93 (0.232)
A/T
168 (0.472)
216 (0.540)
T/T
119 (0.333)
91 (0.228)
1.83
0.340
rs10036478
C
614 (0.853)
704 (0.880)
T
106 (0.147)
96 (0.120)
0.507
0.476
0.756
0.3499–1.634
C/C
262 (0.728)
309 (0.773)
C/T
90 (0.250)
86 (0.215)
T/T
8 (0.028)
5 (0.012)
0.753
0.686
rs2652514
C
577 (0.824)
693 (0.866)
T
123 (0.176)
107 (0.134)
0.736
0.392
0.722
0.343–1.523
C/C
238 (0.680)
299 (0.748)
C/T
101 (0.289)
95 (0.238)
T/T
11 (0.031)
6 (0.015)
0.965
0.617
rs2981359
C
383 (0.532)
388 (0.485)
G
337 (0.468)
412 (0.515)
0.680
0.410
1.255
0.731–2.154
C/C
96 (0.267)
104 (0.260)
C/G
191 (0.530)
180 (0.450)
G/G
73 (0.203)
116 (0.290)
1.285
0.526
rs365663
C
420 (0.583)
517 (0.646)
T
300 (0.417)
283 (0.354)
0.862
0.353
0.771
0.444–1.337
C/C
110 (0.306)
165 (0.412)
C/T
200 (0.556)
187 (0.468)
T/T
50 (0.139)
48 (0.120)
1.224
0.542
rs11133770
A
658 (0.914)
737 (0.921)
C
62 (0.086)
63 (0.079)
0.052
0.820
0.892
0.332–2.395
A/A
298 (0.828)
337 (0.843)
A/C
62 (0.172)
63 (0.157)
0.056
0.812
0.882
0.314–2.482
OR = odds ratio; CI = confidence interval;χ2 = Pearson chi-square. ∗P<0.05.


### 3.2. Haplotypes of TagSNPs

LD plots of the SLC6A3 in the study are shown in Figure1. The LD was measured among the tagSNPs by the Lewontin standardized disequilibrium coefficient D′ [17]. Adjacent SNPs in strong LD (D′ > 0.8), rs2550936, rs3776510, and rs429699 have strong LD (D′ > 0.99), which were chosen to build the haplotypes for subsequent analyses. A total of 5 haplotypes were formed, and the frequencies of haplotypes are shown in Table 4. No significant difference was found in frequencies of 5 haplotypes between PD and control groups in the Han population.Figure 1
Linkage disequilibrium plots for the 3′ end of SLC6A3.Table 4
SLC6A3 haplotype frequency distribution in the Han population.
Haplotype
PD (N%)
Control (N%)
χ
2
P
OR
95% CI
A C C
450.10 (0.643)
519.79 (0.663)
0.094
0.759
0.914
0.516∼1.620
A C T
200.20 (0.286)
192.08 (0.245)
0.450
0.502
1.233
0.668∼2.275
C C C
19.59 (0.028)
32.14 (0.041)
0.214
0.644
0.691
0.143∼3.336
C T C
30.10 (0.043)
39.98 (0.051)
0.075
0.784
0.831
0.222∼3.117
C T T
0.01 (0.000)
0.01 (0.000)
Globeχ2
0.64
Fisher P
0.89
OR = odds ratio; CI = confidence interval;χ2 = Pearson chi-square. ∗P<0.05.


## 3.1. Association Study of TagSNPs and PD

The genotype and allele frequencies of the 3′ end of SLC6A3 are summarized in Table3. No deviation from Hardy–Weinberg equilibrium was evident in the PD and control groups (P>0.05). Statistically significant differences in genotype and allele frequencies were found in the SLC6A3 variant rs40184 between PD (AA 5.6%, AG 47.2%, and GG 47.2%) and controls (AA 2.0%, AG 24.0%, and GG 74.0%). The frequency of the minor A allele was 29.2% in patients and 14.0% in controls. There was no significant difference in genotype and allele frequencies for other 16 SNP polymorphism sites in the 3′ end of SLC6A3.Table 3
Frequency distribution of SLC6A3 genotypes and alleles.
Gene
Allele/genotype
PD (n)
Control (n)
χ
2
P
OR
95% CI
rs2270913
C
698 (1.000)
768 (1.000)
C/C
349 (1.000)
384 (1.000)
rs27048
C
620 (0.912)
652 (0.867)
0.939
0.332
0.585
0.620–4.0483
T
60 (0.088)
100 (0.133)
C/C
280 (0.824)
276 (0.734)
C/T
60 (0.176)
100 (0.266)
1.089
0.297
1.691
0.626–4.566
rs2270914
G
700 (1.000)
768 (1.000)
G/G
350 (1.000)
384 (1.000)
rs2550936
A
651 (0.930)
712 (0.908)
C
49 (0.070)
72 (0.092)
0.271
0.602
1.315
0.469–3.685
A/A
301 (0.860)
320 (0.816)
A/C
49 (0.140)
72 (0.184)
0.301
0.584
0.350
0.460–3.960
rs11133767
A
31 (0.043)
36 (0.046)
G
669 (0.956)
748 (0.954)
0.011
0.914
0.930
0.245–3.539
A/G
31 (0.089)
36 (0.092)
G/G
319 (0.911)
356 (0.908)
0.012
0.914
0.927
0.236–3.640
rs3776510
C
668 (0.954)
744 (0.949)
T
32 (0.046)
40 (0.051)
0.074
0.786
1.201
0.321–4.495
C/C
318 (0.909)
352 (0.898)
C/T
32 (0.091)
40 (0.102)
0.078
0.780
1.212
0.314–4.686
rs429699
C
500 (0.714)
592 (0.755)
T
200 (0.286)
192 (0.245)
0.452
0.502
0.811
0.440–1.495
C/C
190 (0.543)
220 (0.561)
C/T
120 (0.343)
152 (0.388)
T/T
40 (0.114)
20 (0.051)
1.679
0.43
rs11564759
C
403 (0.576)
443 (0.589)
T
297 (0.424)
309 (0.411)
0.076
0.783
0.924
0.531–1.611
C/C
131 (0.374)
116 (0.309)
C/T
141 (0.403)
211 (0.561)
T/T
78 (0.223)
49 (0.130)
3.303
0.192
rs27047
C
450 (0.643)
488 (0.622)
T
250 (0.357)
296 (0.378)
0.092
0.762
1.092
0.619–1.926
C/C
150 (0.429)
160 (0.408)
C/T
150 (0.429)
168 (0.429)
T/T
50 (0.143)
64 (0.163)
0.094
0.954
rs6347
A
641 (0.914)
771 (0.920)
G
59 (0.086)
67 (0.080)
0.001
0.979
1.013
0.383–2.682
A/A
291 (0.831)
325 (0.829)
A/G
59 (0.169)
67 (0.171)
0.001
0.978
1.014
0.365–2.821
rs40184
A
210 (0.292)
112 (0.140)
G
510 (0.708)
688 (0.860)
8.245
0.004∗
2.529
1.325–4.827
A/A
20 (0.056)
8 (0.020)
A/G
170 (0.472)
96 (0.240)
G/G
170 (0.472)
296 (0.740)
8.760
0.013∗
rs37022
A
314 (0.431)
402 (0.502)
T
406 (0.569)
398 (0.498)
1.337
0.246
0.726
0.422–1.250
A/A
73 (0.194)
93 (0.232)
A/T
168 (0.472)
216 (0.540)
T/T
119 (0.333)
91 (0.228)
1.83
0.340
rs10036478
C
614 (0.853)
704 (0.880)
T
106 (0.147)
96 (0.120)
0.507
0.476
0.756
0.3499–1.634
C/C
262 (0.728)
309 (0.773)
C/T
90 (0.250)
86 (0.215)
T/T
8 (0.028)
5 (0.012)
0.753
0.686
rs2652514
C
577 (0.824)
693 (0.866)
T
123 (0.176)
107 (0.134)
0.736
0.392
0.722
0.343–1.523
C/C
238 (0.680)
299 (0.748)
C/T
101 (0.289)
95 (0.238)
T/T
11 (0.031)
6 (0.015)
0.965
0.617
rs2981359
C
383 (0.532)
388 (0.485)
G
337 (0.468)
412 (0.515)
0.680
0.410
1.255
0.731–2.154
C/C
96 (0.267)
104 (0.260)
C/G
191 (0.530)
180 (0.450)
G/G
73 (0.203)
116 (0.290)
1.285
0.526
rs365663
C
420 (0.583)
517 (0.646)
T
300 (0.417)
283 (0.354)
0.862
0.353
0.771
0.444–1.337
C/C
110 (0.306)
165 (0.412)
C/T
200 (0.556)
187 (0.468)
T/T
50 (0.139)
48 (0.120)
1.224
0.542
rs11133770
A
658 (0.914)
737 (0.921)
C
62 (0.086)
63 (0.079)
0.052
0.820
0.892
0.332–2.395
A/A
298 (0.828)
337 (0.843)
A/C
62 (0.172)
63 (0.157)
0.056
0.812
0.882
0.314–2.482
OR = odds ratio; CI = confidence interval;χ2 = Pearson chi-square. ∗P<0.05.


## 3.2. Haplotypes of TagSNPs

LD plots of the SLC6A3 in the study are shown in Figure1. The LD was measured among the tagSNPs by the Lewontin standardized disequilibrium coefficient D′ [17]. Adjacent SNPs in strong LD (D′ > 0.8), rs2550936, rs3776510, and rs429699 have strong LD (D′ > 0.99), which were chosen to build the haplotypes for subsequent analyses. A total of 5 haplotypes were formed, and the frequencies of haplotypes are shown in Table 4. No significant difference was found in frequencies of 5 haplotypes between PD and control groups in the Han population.Figure 1
Linkage disequilibrium plots for the 3′ end of SLC6A3.Table 4
SLC6A3 haplotype frequency distribution in the Han population.
Haplotype
PD (N%)
Control (N%)
χ
2
P
OR
95% CI
A C C
450.10 (0.643)
519.79 (0.663)
0.094
0.759
0.914
0.516∼1.620
A C T
200.20 (0.286)
192.08 (0.245)
0.450
0.502
1.233
0.668∼2.275
C C C
19.59 (0.028)
32.14 (0.041)
0.214
0.644
0.691
0.143∼3.336
C T C
30.10 (0.043)
39.98 (0.051)
0.075
0.784
0.831
0.222∼3.117
C T T
0.01 (0.000)
0.01 (0.000)
Globeχ2
0.64
Fisher P
0.89
OR = odds ratio; CI = confidence interval;χ2 = Pearson chi-square. ∗P<0.05.


## 4. Discussion

PD is a complex disease caused by age and environmental and genetic factors. Finding the genetic susceptibility factors for PD may help identify the individuals at risk and design more specific prevention or treatment options for them. SLC6A3 gene encodes DAT, which comprises 15 exons spanning 60 kb on chromosome 5p15.32 [18]. The studies of the coding region of SLC6A3 have shown that the gene was highly conservative [19]; therefore, the researchers turned the perspective to the noncoding area. The correlation between 40-bp VNTR polymorphisms in the 3′ UTR of SLC6A3 and PD has been studied extensively because VNTR polymorphisms may regulate gene transcription and affect the reuptake of dopamine in the synaptic cleft [20]. The variable numbers of the 40-bp repeat range from 3 to 13 copies; the most common alleles in human beings are the 9- and 10-repeat allele. A lot of studies have shown the association between VNTR polymorphisms of the SLC6A3 and PD in different populations, but the results are inconsistent [21–24]. Two variants, rs28363170 and rs3836790 in SLC6A3, were found to be significantly correlated with PD patients in French population [25], while the variation of these two sites were not related to PD in Han population [26].Here, we conducted a case-control study of 752 participants in the northwest Han population to further investigate the role of the 3′ end of SLC6A3 in the development of PD. We found that only the SLC6A3 variant rs40184 had statistically significant differences in genotypes and alleles, which may be related to PD. The minor A allele of rs40184 may lead to an increased risk of PD in northwest Han Chinese, and it may be a marker of PD. However, the other 16 polymorphic sites were not found to be related to PD. The reason why the other 16 sites had negative results may be the insufficient number of samples in this study and that these 16 sites may be rare genotypes or alleles in the Han population. Haplotype analysis is thought to be much more powerful than single-nucleotide polymorphism sites in correlation studies [27]. Haplotype analysis greatly reduces the number of test samples and control type I errors although this method will increase the incidence of unavoidable type II errors [28, 29]. Few studies have reported associations between haplotypes of the 3′ end of SLC6A3 and PD; we built the haplotypes among 3 strong LD tagSNPs, while no difference was found between the PD and the control group.At present, more than 1,500 genes are known to be closely related to the occurrence of diseases. For a long time, coding areas have been a major research direction of genetic diseases and only a small part of noncoding area has been proved to be a useful component that can help genes to be turned on and off to regulate gene expression. The normal expression of genes cannot be separated from the participation of regulatory elements. Abnormalities in certain regulatory components can also lead to mutations in the corresponding gene-coding regions. Therefore, we can assume that the variant rs40184 in the noncoding area of SLC6A3 may lead to differences in susceptibility to PD in our study.In summary, our findings showed a link between the 3′ end of SLC6A3 gene variant rs40184 and PD in northwest Han population. Given that different populations are genetically heterogeneous and mutations have a specific population frequency, larger sample size studies are needed to confirm the correlation between the 3′ end of SLC6A3 variant and PD in independent larger cohorts and in different geographical origins. Moreover, functional studies of the 3′ end of SLC6A3 need to be carried out to further understand the role of SLC6A3 in PD. Further research is likely to find genetic variations that are risky or protective of PD, which is important for the prevention and treatment of PD.



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*Source: 6452471-2019-09-03.xml*