Received: January 01, 1970
Published: January 01, 1970
Genet.Mol.Res. ():
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.
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.
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.
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.
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
References
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