Research Article

Association of ACE I/D, AT1R A1166C, CYP11B2 C344T polymorphism with essential hypertension in Asia: A meta-analysis

Received: April 22, 2018
Accepted: September 01, 2018
Published: November 05, 2018
Genet.Mol.Res. 17(4): http://dx.doi.org/gmr16039923
DOI: http://dx.doi.org/10.4238/gmr16039923

Abstract

Aim: To evaluate the association between ACE I/D, AT1R A11166C, CYP11B2 C344T gene polymorphisms and the risk of EH in Asia. Materials and Methods: Related case-control studies were collected, selected and screened; a meta-analysis was conducted to assess the association between polymorphism of target genes and essential hypertension. Results: 41 articles were included. Among them, 17 studies were about ACE I/D gene polymorphisms, and 13 studies were about AT1R A1166C. Besides, 11 studies were about CYP11B2 C344T. The study suggested that ACE I/D polymorphism was closely connected with EH risk under all models. After subgroup analysis there was no significant relationship between AT1R A1166C under all models in China and no evidence had been found that CYP11B2 C344T gene had connection with EH risk in China. Meanwhile was no relationship between C344T mutations and EH risk under (CC vs. TT) in other countries. Conclusion: The present evidence shows that it is of great guiding significant to identify ACE I/D mutation for preventing EH and screening high-risk groups rather than AT1R A1166C and CYP11B2 C344T polymorphism.

Introduction

Among all the diseases that lead to the increase of blood pressure, the essential hypertention (EH) accounts for 90% ~ 95% (Abdalla M, et al., 2016). It is a multifactorial disease which can be attributed to the interaction of genetic heterogeneity and various environmental factors. According to the epidemiological survey (Glorioso N, et al., 2013), 31% ~ 68% of the patients with high blood pressure have a family history. And there are also studies showing that the blood pressure variation caused by heredity account for 30% ~ 50% (Smith CJ, et al., 2016). Since Jeunemaitre (Jeunemaitre X, et al., 1992) first reported the close correlation between the susceptibility genes and high blood pressure in 1992, researches on the susceptibility genes of hypertension have become a heat spot. Candidate genes involved at least 200 kinds (Fowdar JY, et al., 2017), including sympathetic nervous system, endothelial function and signal transduction, of which the polymorphism of renin-angiotensin-aldosterone system also plays an important role in regulating blood pressure. Under physiological conditions the renin makes hemangiotensin convert into angiotensin I, which is further transformed into angiotensin II under the action of angiotensin converting enzyme (ACE) (Gonzalez-Villalobos RA, et al., 2013). The Angiotensin II has a strong contractile effect on blood vessels, and it can also act on angiotensin II type 1 receptor (AT1R) stimulating the secretion of aldosterone, which can induce water and sodium retention (Chen K, et al., 2014). Moreover the synthesis of aldosterone needs Aldosterone synthase (CYP11B2), a key rate-limiting enzyme in the process (Gu T, et al., 2016). The mechanisms above are involved in the occurrence and maintenance of EH. Therefore if the gene polymorphisms occur in the RAAS system, it can directly affect blood pressure and owing to its importance, a number of molecular epidemiological studies in different countries and regions have been conducted to study the correlation of the polymorphism in RASS systerm and EH over the last ten years, but the results remain inconsistent. This may be due to racial and regional differences, as well as the fact that the sample size is too small to truly reflect relevance. In order to compare different research results more scientifically and objectively, Meta-analysis on this issue is coming to be widely carried out but also generates conflicting results, Gu W, et al., (2011) Wang J, et al., (2016) Zhou T-B, et al., (2011) and most of the documents in the latest Meta-analysis are published in 10 years ago. Besides the content involves a very small number of countries and only focused on one or two gene locus Sun J, et al., (2016), which cannot comprehensively and objectively reflect the influence of RASS system gene polymorphism on EH. Therefore, on this basis, we carry out a meta-analysis including the genotype data from all eligible investigations in the latest years involving more extensive countries and regions in Asia, as well as covering three gene loci affiliated to RASS system to provide a more accurate evaluation of the connection between polymorphisms of ACE I/D, AT1R A1166C, CYP11B2 C344T and EH susceptibility.

Study selection

Our study followed the Meta-analysis of Observational Studies in Epidemiology guidelines Simonyte S, et al., (2017) and the researches were investigated in the following databases since the establishment of the library to April 2018: the China National Knowledge Infrastructure (CNKI), China Wanfang Database, China Weipu Database, Chinese biomedical literature database and PubMed, EMBASE, Cochrane library, Web of Science, ScieNce direct. The following search words were used: Angiotensin converting enzyme, ACE, Angiotensin II type 1 receptor, AT1R, A1166C, aldosterone synthase, CYP11B2, 344C/T, and combined together with essential hypertension, primary hypertension. In addition, we searched the references in detail for further research.

Studies that met the following criteria would be adopted: (1) the literature must be a case–control study published both at home and abroad, with good balance and comparability. (2)Languages were limited to Chinese or English. (3)The research should involve gene polymorphisms of ACE I/D, AT1R A11166C or CYP11B2 344C/T and EH. (4) Systolic pressure of EH patients should be greater than 140 mmHg and (or) with diastolic pressure greater than 90 mmHg. And secondary hypertension should be excluded. (5)Each genotype distribution and individual number in the case and control groups should be listed in the literature, or the corresponding number can be calculated by the frequency of each genotype given.

Studies with the following characteristics would be excluded: (1) the literature was not associated with ACE I/D, AT1R A11166C or CYP11B2 344C/T polymorphism and EH; (2) it was not a case–control study; (3) The case group did not exclude the secondary hypertension; (4) The data of genotype frequency and allele frequency in the literature were incomplete or unclear.

If the information provided in this article was not comprehensive and uncertain, contact the original author by phone, email and other means to obtain relevant information. We used the 9 - star Newcastle - Ottawa scale to evaluate the quality of the studies. Han Y, et al., (2017) It includes three aspects: study object selection, group comparability and exposure factor measurement. In brief, a maximum of 9 points was assigned to each study: 4 for selection, 2 for comparability, and 3 for outcomes. A final score of >6 was regarded as high quality. Organize each article that are included in and extract relevant data: The first author's name, years of publication, country and region, genotype frequencies in the observation group and control group. Minimum number of abortions, H ardy–W e inberg equilibrium and Quality score of case-control study were showed in Figure 1.

geneticsmr-association-polymorphism-essential-hypertension-asia-screening

Figure 1: Article screening flowchart.

Statistical analysis

All the data were analyzed by Stata 12.0 software and the related charts were drawn below. Based on the odds ratio (OR) with a corresponding 95% confidence interval (CI), we counted the pooled odds to analyze the effect on the association. While crossing these studies, Q test and I2 were used to test the heterogeneity of the included literature firstly. When I2>50%, it was proved that heterogeneity exists between the studies, the random effect model was used, and if not, the fixed effect model was used instead. In order to Search for the sources of heterogeneity, we mainly conducted subgroup analysis on the nations. In order to evaluate the stability of the combined results, a sensitivity analysis was conducted for the meta-analysis results after each removal of a case-control study. The Begg funnel plot was used as a criterion for assessing publication bias.

Results

Characteristics of the included studies

Overall, a total of 41 out of 1346 articles were selected for the final meta-analysis (Gong HT, et al., Vamsi UM, et al., (2016)) Among the included articles, 17 studies reported the association between ACE I/D gene mutation and EH with 2816 cases and 3727 controls involving 5 countries.13 articles demonstrated the relationship between AT1R A11166C and EH with 2869 cases and 3063 controls touching on 5 countries.11 studies described the connection between CYP11B2 C344T and EH with 4476 cases and 4237 controls concerning 3 countries. The baseline characteristics of the studies related to mutation of ACE I/D, AT1R A11166C and CYP11B2C344T are respectively shown in Tables 1, 2 and 3. All of the 41 articles were published before Jan. 2018. In addition, 16 manuscripts were published in English, and 21 manuscripts were published in Chinese.

The first author Publicati-on date Country/city Total of cases  
II    ID    DD    I    D
Total of controls 
II    ID    DD    I    D
HWE
inspec-tion
Quality score
Gong H,et al.[14] 2011 Beijing.China 160
58   46    56    202   198
192
74   94     24    242    142
0.053 9
Wang B,etal.[15] 2014 Heilongjiang.
China
486
167  181   138   515    457
457
159  227    71    545    369
<0.05 5
Simonyte S,et al.[16] 2017 Lithuanian 269
59   149   61   267    271
430
123   205   102   451   409
0.077 9
Singh KhD,et al.[17] 2014 India 211
40   88    83   168    254
211
51    93    67     195   227
0.059 8
Xue T,et al.[18] 2015 Heilongjiang.
China
64
18   25    21    62    68
43
19    19     5      57    29
0.083 7
Dong N[19] 2011 Qinghai.China 116
45   50    21   140     92
97
57    24    16     138    56
0.28 7
Guo S,et al.[20] 2010 Xinjiang.China 220
48   76    96   172    268
220
61   107    52     229   211
0.057 7
Fu Y,et al.[21] 2013 Hainan.China 38
17   13    8     47     29
63
34    21     8      89    37
0.089 6
Zhang C,et al.[22] 2007 Neimenggu.China 98
43   37    18    123    73
108
45    35     28     125   91
0.057 8
Jia S[23] 2010 Neimenggu.China 68
27   30    11    84     52
67
26    34     7      86    48
0.586 8
Hu R,et al.[24] 2007 Neimenggu.China 98
43   37    18    123    73
108
45    35     28     125   91
0.057 6
Han X,et al.[25] 2010 Hebei.China 220
67   97    56    231    209
1004
403   388   213   1194   814
0.085 7
Li D,et al.[26] 2012 Shandong.China 235
64   116   55    244    226
240
92    118   30    302    178
0.862 7
Fang J,et al.[27] 2007 Gansu.China 115
22   72   21     116    114
102
21    57    24    99     105
0.084 7
Akra-Ismail M,et al.[28] 2010  Lebanese 115
13   52   50     78     152
77
10    40    27    60     94  
0.925 9
Nakhjavani M,et al.[29] 2007 Iran 82
22   33   27     77     87
87
25    51    11    101     73
0.082 9
He Q,et al.[30] 2013 Zhejiang.China 221
73   97   51     243    199
221
87    95    39    269    173
0.092 7
Characteristics of studies between AT1R A1166C and EH risk
The first author Publicati-on date Country/city Total of cases  
AA   AC   CC   A   C
Total of controls 
AA   AC   CC   A   C
HWE
inspec-tion
Quality score
Luo J[31] 2010 Hunan.China 100
66   31    3     163   37
100
85   14    1    184    16
0.779 9
Zheng F,etal.[32] 2014 Beijing.China 101
85   15   1     185   17
100
88   12     0    188   12
0.713 9
Ding Y,et al.[33] 2008 Xinjiang.China 201
157   43   1   357    45
220
179   41    0    399    41
0.281 8
Zhong Z,et al.[34] 2016 Guizhou.China 75
65    9    1    139    11
78
76    2     0    154     2
0.31 8
Chen L[35] 2012 Ningxia.China 147
129   17   1    275   19
112
105   7     0     217    7
0.598 7
Li N,et al.[36] 2005 Xinjiang.China 198
153   44    1   350    46
130
99    31    0     229    31
0.247 6
Simonyte S,et al.[37] 2017 Lithuanian 271
146   106   19    311   144 
425
208   184    33   600   250
0.968 9
Dhanachandra SinghKh,et al.[38] 2014 India 211
88    84   39     260   162
211
85    83    43    253   169
0.021 7
Yang CH,etal.[39] 2015 Taiwan.China 313
287   25    1    599     27
130
115   14   1     244     16
0.567 8
Tong J,et al.[40] 2017 Hebei.China 312
278   33    1     589    35
623
580   42   1   1202      44
0.984 8
Shahin DS,et al.[41] 2014 Jordan 108
67   37     4     171   45
102
64    32    6     160    44
0.688 8
Guo S,et al.[20] 2010 Xinjiang.China 221
173   47    1     393    49
220
179   41    0     399    41
0.242 7
Kooffreh ME,et al.[42] 2013 Nigeria 611
605   7    1     1217    9
612
606    6    0     1218    6
0.012 9
Characteristics of studies between CYP11B2 C344T and EH risk
The first author Publicati-on date Country/city Total of cases  
CC   CT   TT   C    T
Total of controls 
CC   CT   TT   C    T
HWE
inspec-tion
Quality score
Luo J[31] 2010 Hunan.China 100
17    40   43   74    126
100
18    36   46    72   128
0.156 7
Tao X[43] 2010 Neimenggu.China 925
139   368  418   646   1204
1199
134   495  570   763   1635
0.000 8
Mi D[44] 2011 Neimenggu.China 201
24   85   92     133   269
202
22   93    87    137   267
0.524 7
Li J[45] 2008 Xinjiang.China 233
36   107   90    179    287
252
42   109   101    193    311
0.581 6
Hlubocká Z,et al.[46] 2009 Czech 213
23   122    68    168   258
156
35   81   40     151   161
0.653 9
Rajan S,et al.[47] 2010 India 406
43   185   178    271   541
424
56   226   142   338   510
0.62 7
Zhang H,et al.[48] 2017 Heilongjiang.China 1023
482   454  87   1418   628
956
462   420   74   1348   568
0.168 9
Sia SK,et al.[49] 2012 Taiwan.China 514
37   209   268   283   745
192
16   85    91     117    267
0.666 9
Vamsi UM,et al.[50] 2016 India 279
47   130   102   224   334
200
26   116    58    168   232
0.611 7
Wang B,et al.[15] 2014 Heilongjiang.China 486
66   228   192   360   612
457
76   200   181    352   562
0.897 8
Hu R,et al.[24] 2007 Neimenggu.China 96
45   42    9     132    60
99
37    53    9     127    71
0.859 6

Table 1: Characteristics of studies on the association between ACE I/D, AT1R A1166C, CYP11B2 C344T gene polymorphisms and EH risk.

  I2 Model OR           95%CL p z
DD vs. II 35.8% FEM  1.478       1.288     1.695 <0.05 5.58
ID vs. II 30.5% FEM 1.213       1.078     1.364 <0.05 3.21
(DD + ID) vs. II 0.2% FEM  1.289       1.154     1.439 <0.05 4.50
DD vs. (II + ID) 58.8% REM  1.367       1.213     1.541 <0.05 5.12
D vs. I 32.3% FEM 1.260       1.169     1.359 <0.05 6.00

Table 2:Meta-analysis of ACE I/D polymorphism and EH risk

  I2 Model OR           95%CL p z
DD vs. (II + ID) 49.2% FEM        1.265       1.111     1.440 <0.05 3.55

Table 3: Meta-analysis of (DD vs. II + ID) gene polymorphism and EH risk without Wang [15].

Results of the overall meta-analysis

Meta-analysis of ACE I/D polymorphism and EH risk

17 articles were related to I/D and the risk of EH. The results showed that the polymorphism of ACE I/D gene was significantly correlated with the risk of EH under dominant model (DD+ID vs. II; OR 1.289, 95% CI 1.1544-1.439), recessive model (DD vs. II+ID); OR 1.367, 95% CI 1.213, 1.541), heterozygote model (ID vs. II; OR 1.213, 95% CI 1.078-1.364), homozygote model (DD vs. II; OR 1.478, 95% CI 1.288-1.695), and additive model (D vs. I; OR 1.260, 95% CI 1.169-1.359). (Table 2)

Test for heterogeneity

In the heterogeneity test for the I/D genotypes of each model, I2 of recessive group (DD vs. (II + ID)) were >50%, indicating that the included studies have heterogeneity. Sub-group analysis was needed to explore the source of heterogeneity.

Sub-group analysis

Of the 17 articles included, one of the articles conducted by Wang was judged to be of low quality and high heterogeneity in accordance with the standard, and therefore, to prevent errors in data analysis, this article was rejected. After it was eliminated, meta-analysis was conducted again, and the results showed that besides other models, the recessive model (DD vs. II + ID) was also had relationship with EH susceptivity [OR=1.265, 95% CI= (1.111, 1.440)]. The results were shown in Table 3.

Meta-analysis of AT1R A1166C polymorphism and EH risk

13 articles were associated with A1166C and the EH emotivity. The results showed that the polymorphism of AT1R A1166C gene was not significantly associated with EH riskunder dominant model (CC+AC vs. AA; OR 1.132, 95% CI 0.978-1.310), recessive model (CC vs. AA+AC; OR0.993, 95% CI 0.715-1.379), heterozygote model (AC vs. AA; OR1.134, 95% CI 0.975-1.318) homozygote model (CC vs. AA; OR 0.984, 95% CI 0.698-1.387), and heterozygote model (AC vs. AA; OR 1.134, 95% CI 0.975-1.318) (p>0.05).The results were shown in Table 4.

  I2 Model OR            95%CL p z
CC VS AA 0.0% FEM 0.984       0.698     1.387 0.926 0.09
AC VS AA 42.4% FEM  1.134       0.975     1.318  0.104 1.63
CC+AC VS AA 50.0% FEM  1.132       0.978     1.310 0.096 1.66
CC VS AA+AC 0.0% FEM  0.993       0.715     1.379 0.966 0.04
C VS A 54.2% REM  1.093       0.966     1.238 0.159 1.41

Table 4: Results of AT1R A1166C polymorphism and EH risk

Test for heterogeneity

In the heterogeneity test for the AT1R A1166C genotypes of each model, I2 of additive model (C vs. A) were>50%, indicating that the included studies have heterogeneity. Sub group analysis was needed to explore the source of heterogeneity.

Sub-group analysis

Of the 13 articles included, 9 studies were from China, of which 3 were carried out in the Han nationality and 6 were from national minorities. And we conducted subgroup analysis on C vs. A genotype and EH risk according to the population of ethnic groups. The I2 of (C vs. A) in Chinese Han nationality and minorities were <50%, indicating that ethnic differences had an impact on heterogeneity. And there is no significantly associated with EH risk under additive (C vs. A)model in Chinese people (p>0.05). The results were shown in Figure 2.

geneticsmr-association-polymorphism-essential-hypertension-asia-subgroup

Figure 2: Results of AT1R A1166C mutation and EH risk in subgroup analysis

Meta-analysis of CYP11B2 C344T polymorphism and EH risk

The contents of the 11 articles involved C344T and EH risk.The results elucidated that the polymorphism o f CYP11B2 C344T gene was not significantly associated with EH risk under additive model (C vs. T; OR 1.204, 95% CI1.044-1.390, p=0.011<0.05), dominant model (CC+TC vs. TT), heterozygote model (CT vs. TT); OR1.0 75, 95% CI 0.874 -1.322) and homozygote model (CC vs. TT; OR1.343, 95% CI 0.966-1.867). (p>0.05), except for recessive model (CC vs. TT+TC; OR 1.290, 95% CI 0.956-1.740) and homozygote model (CC vs. TT).The r esults were shown in Table 5.

  I2 Model OR           95%CL p z
CT VS.TT 19.9% FEM 0.915       0.827     1.013 0.087 1.71
CC VS.TT 51.0% REM  0.978       0.923     1.037 0.464 0.73
(CC+TC) vs.TT 32.5% FEM 0.926       0.842     1.019 0.115 1.58
CC vs. (TT+TC) 55.8% REM  0.995       0.924     1.072 0.895 0.13
C VS.T 50.0% FEM 0.961       0.902     1.024 0.220 1.23

Table 5: Results of CYP11B2 C344T polymorphism and EH risk.

Test for heterogeneity

In the heterogeneity test for the C344T genotypes of each model, I2 of recessive group (CC vs. TT+TC) and homozygote group (CC vs. TT) were>50%, indicating that the studies included have heterogeneity. Subgroup analysis was needed to explore the source of heterogeneity.

Sub-group analysis

Of the 11 articles included, 7 were from China and 4 was from other countries.Therefore, the subgroup analys is of recessive model (CC vs. TT+TC) and homozygote model (CC vs. TT)were conducted according to the sour ce of the countries.The meta-analysis of 7 Chinese articles showed that I2 of the two models were both <50%, in dicating that different countries had an impact on heterogeneity.And the subgroup analysis showed that there wa s no significant association between C344T mutation and EH risk under (CCvs. TT+TC) [OR=1.0421 95%CI= (0.923, 1.177)] and (CC vs. TT) [OR=1.069, 95%CI=(0.909, 1.256)]in China (p>0.05).There was no relat ionship between C344T mutation and EH risk under (CC vs. TT) [OR=0.87,95%CI=(0.51, 1.09)] in other c ountries.The results were shown in Table 6 and Figure 3.

geneticsmr-association-polymorphism-essential-hypertension-asia-mutation

Figure 3: Results of CYP11B2 C344T mutation and EH risk in subgroup analysis.

  I2 Model OR          95%CL p
CCvs. (TT+TC)in China 42.86% FEM  1.042     0.923     1.177 0.105
CCvs. (TT+TC)in other countries 66.5% REM 0.80      0.62      1.03 0.03
CCVS.TT in China 19.2% FEM  1.069     0.909     1.256 0.422
CCVS.TT in other countries 42.4% FEM 0.67      0.51      0.88 0.157

Table 6: Results of CYP11B2 C344T mutation and EH risk in subgroup analysis

Publication bias evaluation

We analyzed the publication bias of articles on the relationship between ACE I/D, AT1R A1166C, C344T and EH risk. The two groups of gene funnel plot analysis showed asymmetry, indicating the possibility of publication bias. The results were shown in Figure 4.

geneticsmr-association-polymorphism-essential-hypertension-asia-funnel

Figure 4: The publication bias of articles on the relationship between ACE I/D, AT1R A1166C, CYP11B2 C344T and EH risk was shown in the Funnel figure.

Discussion

Among all the the gene polymorphisms associated with RASS system, mutation of ACE I/D, AT1R A11166C, CYP11B2 C344T are paid intensive attention at home and abroad.Insertions and deletions of Alu sequence are the most common mutation in ACE gene, namely I/D which can affect the expression of ACE gene so as to participate in the regulation of blood pressure Singh A, et al., (2018). At present, researches show that I/D polymorphisms are more than 50%.Besides, A1166C, as the closest gene polymorphism to AT1R, situates at the 5' end of 3'untranlated region which will not impact the open reading frame and functional change, but involve in regulating transcription and translation and affect the role of AT1R in turn Wang HB, et al., (2015).Transcriptional regulatory zone -334T/C, one of the four major genetic variants of CYP11B2 is the most studied, which can influence the binding of CYP11B2 gene promoter and sf-1 factor, influencing the synthesis and secretion of aldosterone synthase mRNA and aldosterone Munshi A, et al., (2010).

The results of the studies on the correlation between gene polymorphism above and EH are not consistent. In our current meta-analysis, a total of 41 studies (17 studies for the ACE I/D polymorphism, 13 studies for the A1166C polymorphism and 11 studies for the C344T polymorphism) are accepted to review the relationship between ACE, AT1R as well as CYP11B2 gene polymorphism and EH risk. The results show that the presence of the ACE gene I/D mutation is related to the susceptibility to EH under all models, which is consistent with Wang's research results Wang ZG, et al., (2010). For A1166C, 13 articles are associated with A1166C and the EH risk. The results show that the polymorphism of A1166C gene has no connection with EH risk under dominant model (CC+AC vs. AA), recessive model (CC vs. AA+AC, heterozygote model (AC vs. AA) homozygote model (CC vs. AA) and heterozygote model (AC vs. AA).Besides, we also find that ethnic differences have an impact on heterogeneity.I2 of (C vs. A) is changed from greater than 50% to less than 50% when the minority is not considered in subgroup analysis. And there is no significantly association between A1166C mutation and EH risk under additive model (C vs. A) in China. When it comes to C344T, 11 articles showed that there is no relationship with EH risk in the polymorphism of CYP11B2 C344T under additive model (C vs. T), dominant model (CC+TC vs. TT), recessive model (CC vs. TT+TC), heterozygote model (CT vs. TT) and homozygote model (CC vs. TT) (p>0.05). Moreover, besides above models, no significantly relationship has been found between CYP11B2 C344T mutation and EH in Chinese people when compared with other countries under recessive model (CC vs. TT+TC)and homozygote model (CC vs. TT) (p>0.05).’Our finding is different from Li WX's results Li WX, et al., (2014) The length and quality of the included literature may be the result of different results.

Conclusion

In a nutshell, to identify ACE I/D mutation has certain clinical significance for the prevention of EH and there is not enough evidence to suggest that gene polymorphism of AT1R A1166C, CYP11B2 C344T are associated with EH.

Acknowledgments

The authors thank all patients for their participation. Special thanks are also extended to colleagues at the First Affiliated Hospital of Heilongjiang University Of Chinese Medicine.

Conflicts of interest

On behalf of all authors, the corresponding author states that there are no conflicts of interest.

Disclosure

No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication.

About the Authors

Corresponding Author

Liu Li

P.R. China

Email:
[email protected]

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