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International Journal of Molecular Epidemiology and Genetics logoLink to International Journal of Molecular Epidemiology and Genetics
. 2021 Oct 15;12(5):90–101.

Association of single nucleotide polymorphisms in ADIPOQ gene with risk of hypertension: a systematic review and meta-analysis

Jiegen Yu 1,*, Ling Liu 2,3,*, Zhipeng Li 4, Yanqiu Wang 2,3, Wanjun Zhang 2,3, Yuelong Jin 2,3, Liangping He 4, Yan Chen 2,3, Yingshui Yao 2,3,5
PMCID: PMC8611228  PMID: 34853633

Abstract

Background: Hypertension has been continuing to be a major contributor to the global burden of disease and to the global mortality, leading to over 10 million deaths each year. The purpose of this study was to investigate the association between Adiponectin gene polymorphism with Essential hypertension (EH). Methods: PubMed, EMbase, the Cochrane Library, and China National Knowledge Infrastructure (CNKI) were searched independently by two investigators. Pooled odds ratios and 95% confidence intervals were calculated to estimate the associations of Adiponectin polymorphism with EH. Results: Thirteen studies with 3198 cases and 3076 controls for meta-analysis (MA) were included in present study. Pooled results showed that rs2241766 polymorphism is associated with the risk of EH in the allelic model (G vs. T: OR=1.10; 95% CI, 1.01-1.21). In the <40 years subgroup, rs2241766 polymorphism is associated with the risk of EH in allele model (G vs. T: OR=1.43; 95% CI, 1.06-1.94), recessive model (GG vs. GT + TT: OR=5.26, 95% CI=1.47-18.76), homozygous model of GG (GG vs.TT: OR=5.27, 95% CI=1.47-18.95), and rs266729 in recessive model (GG vs. GT + TT: OR=2.33, 95% CI=1.33-4.08). Conclusions: Our meta-analysis results show that the rs2241766 polymorphism is associated with the risk of hypertension. There still need a larger sample with better design to verify.

Keywords: Adiponectin, polymorphisms, hypertension, meta-analysis

Introduction

Hypertension has been continuing to be a major contributor to the global burden of disease and to the global mortality, leading to over 10 million deaths each year [1,2]. The etiology of hypertension has not been fully elucidated , however, the interaction between genes and environmental factors is thought to play an important role in the pathological process of hypertension [3]. In recent years, researches have been focusing on the genetic susceptibility and genetic polymorphism of hypertension [4,5].

Adiponectin (ADIPOQ) is a recently discovered cytokine specifically secreted by adipocytes, with plasma concentrations range from 5 to 30 mg/L and accounting for approximately 0.05% of total plasma protein in healthy adults [6]. Studies have shown that adiponectin plays an vital role in improving insulin sensitivity, anti-inflammation and anti-atherosclerosis [7,8]. In recent years, there was a study have reported that the polymorphism of ADIPOQ gene is associated with plasma levels of adiponectin, and low adiponectin levels predispose essential hypertension [9]. Some studies have investigated the correlation between several polymorphisms in ADIPOQ gene and hypertension, including rs2241766 (+45T>G), rs1501299 (+276G>T), and rs266729 (-11377C>G). A study showed [10] that the association between polymorphisms of adiponectin and essential hypertension and found +45T/G and +276G/T were significantly associated with essential hypertension. Also reported by other scholars [11] that although -11377C>G in the promoter region of ADIPOQ gene was not yet suggested to be associated with essential hypertension, they confirmed that -11377C>G was associated with reduced plasma lipids. In addition, it is reported [12] that there was no significant association between rs2241766 and rs1501299 and hypertension. And other scholars reported [13,14] found that rs2241766 was associated with the risk of hypertension, but rs1501299 was not associated with the risk of hypertension. Therefore, results of these studies are inconsistent and the association between polymorphisms in ADIPOQ gene and hypertension remains to be determined. We performed this meta-analysis aimed at determining the associations of rs2241766, rs1501299, and rs266729 polymorphisms in the ADIPOQ gene with hypertension susceptibility.

The present meta-analysis aimed to analyze the relationship between three widely evaluated genetic polymorphisms in ADIPOQ gene and the risk of hypertension. The ADIPOQ gene (OMIM: 605441, Gene ID: 9370) is located in human 3q27 and has a DNA length of approximately 16 kb and contains three exons and two introns. ADIPOQ is a specific hormone protein secreted by fat cells. It is a protective factor and plays a very important role in anti-atherosclerosis, insulin resistance and anti-inflammation [15].

Adamczak et al. [16] first analyzed and reported a negative correlation between plasma levelsof adiponectin and the systolic blood pressure, diastolic blood pressure, and mean arterial pressure and concluded that low levels of adiponectin may play a role in the pathogenesis of essential hypertension. Mangge et al. [17] reported that the polymorphism of ADPIOQ gene correlated with adiponectin concentration. Therefore, the polymorphism of ADPIOQ gene was considered associating with the risk of hypertension.

Materials and methods

The meta-analysis is conducted in accordance with the guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement [18].

Search strategy

To identify studies eligible for the systematic review and meta-analysis, we searched databases of PubMed, EMbase, the Cochrane Library, and China National Knowledge Infrastructure up to December 19, 2019, The following terms: “hypertension”, “adiponectin”, “ADIPOQ”, “intron”, “exon” and “polymorphism” was used for this searching. Additional potential relevant articles were identified by us through screened references of retrieved articles.

Inclusion and exclusion criteria

Inclusion criteria

Studies included must meet the following criteria: (1) Studies were case-control or cohort design; (2) Studies have evaluated the association between single nucleotide polymorphisms in ADIPOQ gene and susceptibility of hypertension; (3) Studies evaluated rs2241766, rs1501299, or/and rs266729; (4) Studies provided details of associations between genotypes and phenotypes and sufficient data for estimating odds ratios (ORs) with 95% confidence intervals (CIs).

Exclusion criteria

(1) Conference abstracts, case reports, comments, repeated researches, and systematic reviews were excluded; (2) Studies lacking data for genotype distribution; (3) Studies unable to determine whether the control population meets the Hardy-Weinberg equilibrium (HWE) balance.

Data extraction and quality assessment

Two reviewers independently screened the articles, extracted data, and performed quality evaluations. Data extracted from studies were as follows: first author, country, year of publication, average age, type of study, sample size, ethnicity, genotyping method, genotype distributions, and body mass index (BMI). Disagreements were resolved through discussion or consulting third-party experts. The quality of the included studies was assessed using the Newcastle-Ottawa (NOS) scale, with a rating of 0-9 and a maximum of 9 [19].

Statistical analysis

Stata version 12.0 (Stata Corp, College Station, TX) was used for statistical analyses. A chi-square test was performed to evaluate the HWE for the control group in each study group. Pooled ORs with corresponding 95% CIs were calculated to evaluate associations between the ADIPOQ gene and hypertension for the following genetic models: rs2241766 (allelic model: G vs. T, recessive models: GG vs. GT + TT, dominant models: GG + GT vs. TT, heterozygote model: GT vs. TT, homozygote model: GG vs. TT); rs1501299 (allelic model: T vs. G, recessive models: TT vs. TG + GG, dominant models: TT + TG vs. GG, heterozygote model: TG vs. GG, homozygote model: TT vs. GG); rs266729 (allelic model: G vs. C, recessive models: GG vs. GC + CC, dominant models: GG + GC vs. CC, heterozygote model: GC vs. CC, homozygote model: GG vs. CC). Q tests and I2 statistics were performed to assess heterogeneity between studies. If P Q<0.05 or I2>50%, a significant heterogeneity was existed among studies and then, a random effects model was used to calculate the pooled OR, otherwise (i.e., P Q>0.05 or I2<50%), a fixed effects model was performed.

For studies with significant heterogeneity, stratified analysis for samples may be performed by subgroup analysis to identify potential sources of heterogeneity. Gradually eliminating individual studies or studies deviating from HWE for sensitivity analysis were performed to assess the stability of results. Begg’s funnel plot and Egger’s test were used to justify potential publication bias.

Results

Literature screening

A total of 308 studies were retrieved in our work. After excluding duplicate publications, case reports, reviews, and studies that could not be combined, thirteen articles with 3198 cases and 3076 controls were included in this study. Studies by Zhang et al. [20], Leu et al. [21], Kang et al. [22], Jiang et al. [23], and Machado et al. [24] contained two studies, which were analyzed separately in the following meta-analysis. A flow chart summarizing the process of literature is depicted in Figure 1.

Figure 1.

Figure 1

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PRISMA flow diagram of studies included in the Meta-analysis.

Characteristics and quality evaluations for included studies

Table 1 summarizes characteristics of all included studies. Eleven studies were carried out in China, one in Brazil, and one in Turkey. The rs2241766 polymorphism was analyzed in 12 studies, the rs1501299 polymorphism was in 10, and the rs266729 polymorphism was in 8.

Table 1.

Principle characteristics of the studies included in the meta-analysis

Study Country Year Age Type of study Sample size Ethnicity Genotyping method Genotype distributions (case/control) P value of HWE Quality score BMI
Case Control Case Control Case Control
rs2241766 TT TG GG
    Yan [12] China 2006 49.0±9.0 48.0±10.0 Case control 482 497 Asian PCR 201/222 186/203 95/72 0.024 8 30.80±2.50 22.40±1.80
    Jeng [35] China 2007 51.6±14.7 50.7±12.1 Case control 212 356 Asian PCR 82/126 99/173 31/57 0.853 7 25.70±3.60 23.80±3.40
    Tang [13] China 2008 63.5±6.5 60.5±7.1 Case control 151 100 Asian PCR 99/63 32/28 20/9 0.036 8 NR NR
    Wang [14] China 2008 46.4±14.0 46.8±15.4 Case control 80 160 Asian PCR 41/87 34/60 5/13 0.561 6 26.82±2.44 22.43±3.99
    Youpeng [36] China 2010 30.9±6.0 30.0±4.5 Case control 107 81 Asian PCR 74/53 26/27 7/1 0.228 8 22.05±2.65 20.10±1.80
    Leu A [21] China 2011 41.4±0.7 46.7±0.8 Case control 159 446 Asian PCR 74/233 70/181 15/32 0.696 8 25.40±0.30 23.50±0.10
    Leu B [21] China 2011 41.7±0.6 57.5±1.0 Case control 192 165 Asian PCR 92/78 81/75 19/12 0.696 8 28.30±0.30 27.10±0.30
    Kang B [22] China 2013 52.3±9.6 49.8±8.7 Case control 153 126 Asian PCR 63/75 68/40 11/22 0.105 7 22.57±2.27 21.53±2.17
    Jiang A [23] China 2014 68.8±6.7 67.1±7.1 Case control 223 176 Asian PCR 102/91 86/65 10/14 0.72 9 24.50±4.30 23.10±3.30
    Jiang B [23] China 2014 68.2±6.1 67.1±7.2 Case control 181 176 Asian PCR 90/91 67/65 12/10 0.72 9 26.00±3.70 23.10±3.30
    Machado A [24] Brazil 2014 26.0±4.5 24.0±4.0 Case control 113 161 Caucasian PCR 81/139 29/29 3/1 0.697 8 27.53±5.15 22.80±2.70
    Machado B [24] Brazil 2014 27.0±4.5 24.0±5.0 Case control 127 161 Caucasian PCR 97/139 26/29 4/1 0.697 8 26.28±4.80 22.80±2.70
rs1501299 GG TG TT
    Iwashima [9] Japan 2004 59.4±0.5 57.1±0.6 Case control 446 312 Asian PCR 225/165 180/124 41/23 0.964 8 24.40±0.10 23.10±0.20
    Yan [12] China 2006 49.0±9.0 48.0±10.0 Case control 482 497 Asian PCR 259/274 184/187 39/36 0.599 8 30.80±2.50 22.40±1.80
    Wang [14] China 2008 46.4±14.0 46.8±15.4 Case control 80 160 Asian PCR 41/74 28/73 11/13 0.392 6 26.82±2.44 22.43±3.99
    Youpeng [36] China 2010 30.9±6.0 30.0±4.5 Case control 107 81 Asian PCR 19/19 60/49 28/13 0.051 8 22.05±2.65 20.10±1.80
    Leu A [21] China 2011 41.4±0.7 46.7±0.8 Case control 159 446 Asian PCR 85/228 60/178 14/40 0.536 8 25.40±0.30 23.50±0.10
    Leu B [21] China 2011 41.7±0.6 57.5±1.0 Case control 192 165 Asian PCR 117/93 68/56 7/16 0.089 8 28.30±0.30 27.10±0.30
    Kang B [22] China 2013 52.3±9.6 49.8±8.7 Case control 153 126 Asian PCR 100/82 46/38 7/6 0.56 7 22.57±2.27 21.53±2.17
    Machado A [24] Brazil 2014 26.0±4.5 24.0±4.0 Case control 113 161 Caucasian PCR 59/68 46/74 8/19 0.868 8 27.53±5.15 22.80±2.70
    Machado B [24] Brazil 2014 27.0±4.5 24.0±5.0 Case control 127 161 Caucasian PCR 66/68 47/74 14/19 0.868 8 26.28±4.80 22.80±2.70
    Demir [30] Turkey 2016 63.6±7.1 64.6±7.3 Case control 170 170 Caucasian PCR 78/92 73/72 19/6 0.071 8 27.30±3.20 26.10±3.20
rs266729 CC CG GG
    Jia [37] China 2008 61.1 57.0 Case control 182 58 Asian PCR 96/37 77/19 9/2 0.817 8 NR NR
    Zhang A [20] China 2011 52.4±9.6 49.3±10.8 Case control 112 128 Asian PCR 72/78 33/46 7/4 0.368 7 NR NR
    Zhang B [20] China 2011 53.9±10.5 49.8±10.3 Case control 108 140 Asian PCR 66/85 37/38 5/17 <0.01 7 NR NR
    Leu A [21] China 2011 41.4±0.7 46.7±0.8 Case control 159 446 Asian PCR 85/84 90/64 23/11 0.8 8 25.40±0.30 23.50±0.10
    Leu B [21] China 2011 41.7±0.6 57.5±1.0 Case control 192 165 Asian PCR 93/84 68/64 12/11 0.8 8 28.30±0.30 27.10±0.30
    Kang A [22] China 2013 52.3±9.6 49.8±8.7 Case control 153 126 Asian PCR 95/70 48/46 10/10 0.532 7 22.57±2.27 21.53±2.17
    Machado A [24] Brazil 2014 26.0±4.5 24.0±4.0 Case control 113 161 Caucasian PCR 61/93 36/57 16/11 0.577 8 27.53±5.15 22.80±2.70
    Machado B [24] Brazil 2014 27.0±4.5 24.0±5.0 Case control 127 161 Caucasian PCR 81/93 27/57 19/11 0.577 8 26.28±4.80 22.80±2.70
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Abbreviations: PCR: polymerase chain reaction; BMI: body mass index.

According to the Newcastle-Ottawa quality assessment scale, the quality of the included literature was evaluated. The scores are shown in Table 1 and 9 studies have a score of no less than 8.

Quantitative synthesis for MA

For a comprehensive evaluation, we calculated Ors with 95% CIs to estimate associations of the three polymorphisms in ADIPOQ with the risk of hypertension under the genetic models of alleles, recessive genotypes, dominant genotypes, heterozygote, and homozygote. The genetic polymorphisms of the three loci were not heterogeneous in general, so the combined effect model was used for the combined analysis (as shown in Table 2). According to ORs and 95% CIs, there were no statistical significances between the rs1501299 polymorphism and the rs266729 polymorphism and the risk of hypertension in all of the above mentioned genetic models. In the allelic model of the rs2241766 polymorphism, Figure 2 showed the allele of G was associated with an increased risk of hypertension (G vs. T: OR=1.10; 95% CI, 1.01-1.21). However, the difference was not statistically significant in the other four genetic models for the rs2241766 polymorphism (Table 2).

Table 2.

Pooled ORs and 95% CIs of the associations of ADIPOQ polymorphsims with hypertension

Genotype s.s Pooled estimate Heterogeneity P value for Begg’s test
OR, 95% CI P Z I 2 P Q
rs2241766
    G vs. T 12 1.10, 1.01-1.21 0.035 0.00% 0.563 0.304
    GG vs. GT + TT 12 1.17, 0.96-1.42 0.124 40.20% 0.073 0.537
    GG + GT vs. TT 12 1.12, 0.99-1.26 0.073 0.00% 0.567 0.837
    GT vs. TT 12 1.09, 0.96-1.23 0.206 25.00% 0.198 0.837
    GG vs. TT 12 1.19, 0.97-1.47 0.093 23.30% 0.215 0.537
rs1501299
    T vs. G 10 1.01, 0.92-1.11 0.824 45.90% 0.055 0.592
    TT vs. TG + GG 10 1.13, 0.91-1.41 0.257 49.00% 0.039 0.858
    TT + TG vs. GG 10 0.98, 0.86-1.11 0.720 15.30% 0.302 0.858
    TG vs. GG 10 0.96, 0.84-1.09 0.522 0.00% 0.633 0.474
    TT vs. GG 10 1.09, 0.87-1.37 0.455 53.70% 0.022 1.000
rs266729
    G vs. C 8 1.08, 0.94-1.24 0.263 25.90% 0.223 0.711
    GG vs. GC + CC 8 1.34, 0.98-1.84 0.063 45.20% 0.078 0.174
    GG + GC vs. CC 8 1.03, 0.87-1.22 0.708 17.40% 0.293 1.000
    GC vs. CC 8 0.98, 0.82-1.17 0.801 38.20% 0.125 0.902
    GG vs. CC 8 0.76, 0.55-1.05 0.095 2.70% 0.409 0.266
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Figure 2.

Figure 2

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Forest plot for the risk of hypertension with allele model of rs2241766.

We then performed analyses for associations of the three single nucleotide polymorphisms in ADIPOQ gene with the risk of hypertension in subgroups stratified by age, ethnicity, BMI, and whether the control group met the HWE (Hardy-Weinberg equilibrium) or not. The results of all subgroup analyses were listed in Table 3. We found that rs2241766 SNP was significantly associated with the risk of hypertension in individuals no more than 40 years old. Increased risk of hypertension was observed for the allele of G (G vs. T: OR=1.43; 95% CI, 1.06-1.94), for the recessive model (GG v GT + TT: OR=5.26, 95% CI=1.47-18.76), and for the homozygous model of GG (GG v TT: OR=5.27, 95% CI=1.47-18.95). In the Caucasian population, the risk of hypertension still increased significantly for the allele of G (G VS T: OR=1.67, 95% CI=1.16-2.40), for the recessive model (GG v GT + TT: OR=5.04, 95% CI=1.04-24.50), for the dominant models (GG + GT v TT: OR=1.62, 95% CI=1.08-2.42), and for the homozygous model of GG (GG v TT: OR=5.46, 95% CI=1.12-26.64). In the population with BMI of more than25, allele models (G VS T: OR=1.13, 95% CI=1.02-1.26), recessive models (GG v GT + TT: OR=1.27, 95% CI=1.02-1.59), and homozygous models (GG vs. TT: OR=1.28; 95% CI, 1.01-1.62) have significant associations with the risk of hypertension. The results of the stratified study showed that the polymorphism of rs1501299 was not associated with the risk of hypertension. Although there was no significant association between the rs266729 polymorphism and the risk of hypertension for the overall group without stratification, it was found that the recessive model of GG in individuals no more than40 years old (GG v GT + TT: OR=2.33, 95% CI=1.33-4.08) and in the Caucasian population (GG v GT + TT: OR=2.33, 95% CI=1.33-4.08) was significantly associated with an increased risk for the occurrence of hypertension (Table 3).

Table 3.

Hierarchical analysis results for the associations of three locis polymorphsims with hypertension

Subgroups (rs2241766) s.s G vs. T GG v GT + TT GG + GT v TT GT v TT GG v TT
OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q
Age
    ≤40 years 3 1.43, 1.06-1.94 7.5%, 0.339 5.26, 1.47-18.76 0.0%, 0.991 1.33, 0.95-1.86 40.8%, 0.185 1.18, 0.84-1.67 53.9%, 0.114 5.27, 1.47-18.95 0.0%, 0.996
    >40 years 9 1.07, 0.98-1.18 0.0%, 0.836 1.11, 0.91-1.35 37.6%, 0.118 1.09, 0.96-1.24 0.0%, 0.758 1.07, 0.93-1.23 20.3%, 0.262 1.13, 0.91-1.39 9.4%, 0.356
Ethnicity
    Asian 10 1.07, 0.98-1.18 0.0%, 0.895 1.13, 0.93-1.38 40.2%, 0.090 1.08, 0.95-1.22 0.0%, 0.777 1.05, 0.92-1.20 23.4%, 0.227 1.15, 0.94-1.42 15.9%, 0.297
    Caucasian 2 1.67, 1.16-2.40 0.0%, 0.648 5.04, 1.04-24.50 0.0%, 0.913 1.62, 1.08-2.42 0.0%, 0.551 1.49, 0.98-2.25 0.0%, 0.494 5.46, 1.12-26.64 0.0%, 0.947
BMI
    ≤25 3 1.01, 0.81-1.26 0.0%, 0.940 0.65, 0.39-1.09 60.4%, 0.080 1.16, 0.88-1.52 15.7%, 0.306 1.26, 0.94-1.68 70.2%, 0.035 0.77, 0.45-1.32 44.1%, 0.167
    >25 8 1.13, 1.02-1.26 19.3%, 0.277 1.27, 1.02-1.59 0.0%, 0.474 1.12, 0.98-1.29 0.0%, 0.486 1.07, 0.93-1.24 0.0%, 0.632 1.28, 1.01-1.62 2.1%, 0.413
HWE
    P H<0.05 2 1.17, 0.99-1.38 0.0%, 0.583 1.46, 1.07-2.00 0.0%, 0.890 1.08, 0.86-1.36 0.0%, 0.435 0.96, 0.74-1.23 0.0%, 0.325 1.45, 1.04-2.02 0.0%, 0.949
    P H>0.05 10 1.08, 0.97-1.20 0.0%, 0.461 1.00, 0.78-1.29 38.8%, 0.100 1.13, 0.98-1.30 0.0%, 0.449 1.14, 0.98-1.32 27.1%, 0.195 1.05, 0.80-1.37 24.3%, 0.219
Subgroups (rs1501299) T v G TT v TG + GG TT + TG v GG TG v GG TT v GG
OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q
Age
    ≤40 years 3 0.89, 0.71-1.10 67.9%, 0.044 1.05, 0.68-1.61 54.0%, 0.114 1.03, 0.90-1.17 0.0%, 0.628 0.76, 0.55-1.05 0.0%, 0.369 0.89, 0.55-1.44 63.7%, 0.064
    >40 years 7 1.04, 0.94-1.16 30.8%, 0.193 1.16, 0.91-1.50 54.4%, 0.041 0.77, 0.57-1.04 41.8%, 0.179 1.00, 0.87-1.16 0.0%, 0.844 1.16, 0.89-1.50 54.4%, 0.041
Ethnicity
    Asian 7 1.03, 0.92-1.15 2.6%, 0.405 1.13, 0.88-1.44 37.6%, 0.142 1.00, 0.87-1.16 0.0%, 0.795 0.99, 0.85-1.15 0.0%, 0.883 1.10, 0.85-1.43 34.7%, 0.163
    Caucasian 3 0.96, 0.79-1.18 80.3%, 0.006 1.16, 0.74-1.83 75.2%, 0.018 0.89, 0.68-1.16 70.9%, 0.032 0.85, 0.65-1.12 46.9%, 0.152 1.06, 0.66-1.69 80.3%, 0.006
BMI
    ≤25 3 1.13, 0.95-1.35 0.0%, 0.522 1.38, 0.92-2.06 0.0%, 0.571 1.11, 0.87-1.40 0.0%, 0.715 1.06, 0.83-1.36 0.0%, 0.902 1.40, 0.90-2.15 0.0%, 0.510
    >25 7 0.97, 0.86-1.08 54.5%, 0.040 1.04, 0.80-1.35 60.7%, 0.018 0.93, 0.81-1.08 29.5%, 0.203 0.92, 0.79-1.07 0.0%, 0.436 0.99, 0.76-1.29 63.2%, 0.012
Subgroups (rs266729) G v C GG v GC + CC GG + GC v CC GC v CC GG v CC
OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q OR, 95% CI I 2, P Q
Age
    ≤40 years 2 1.18, 0.9-1.55 0.0%, 0.414 2.33, 1.33-4.08 0.0%, 0.911 0.95, 0.68-1.33 26.9%, 0.242 0.73, 0.50-1.06 54.0%, 0.140 0.82, 0.46-1.47 0.0%, 0.440
    >40 years 6 1.05, 0.89-1.23 38.8%, 0.147 1.04, 0.71-1.53 35.9%, 0.168 1.06, 0.87-1.29 26.4%, 0.236 1.07, 0.87-1.32 19.4%, 0.287 0.73, 0.49-1.08 22.9%, 0.262
Ethnicity
    Asian 6 1.05, 0.89-1.23 38.8%, 0.147 1.04, 0.71-1.53 35.9%, 0.168 1.06, 0.87-1.29 26.4%, 0.236 1.07, 0.87-1.32 19.4%, 0.287 0.73, 0.49-1.08 22.9%, 0.262
    Caucasian 2 1.18, 0.9-1.55 0.0%, 0.414 2.33, 1.33-4.08 0.0%, 0.911 0.95, 0.68-1.33 26.9%, 0.242 0.73, 0.50-1.06 54.0%, 0.140 0.82, 0.46-1.47 0.0%, 0.440
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Sensitivity analysis and publication bias

To rule out the impact of low-quality literature on meta-analysis results, we performed a sensitivity analysis by omitting individual studies one by one. Results showed that no individual studies on the polymorphisms of the three loci affected the value of the combined OR, which proved that the MA has good stability.

The publication bias was analyzed using the Stata 12.0 software. We found that the funnel plot was basically symmetrical with respect to the central axis, and P values of Begg’s test were all more than 0.05 (Table 2), indicating that there was no publication bias in each genetic model.

Discussion

Our results of the present study indicate that there is a significant association between the polymorphism of rs2241766 and the risk of hypertension. The T→G mutation was observed in the allelic model and increased the risk of hypertension by 10% (OR=1.10, 95% CI=1.01-1.21), meanwhile, no statistical significances were found in other genetic models nor in any genetic models for the polymorphisms of rs1501299 and rs266729. Although no heterogeneity was identified between studies and considering the asymmetry of factors such as race, age, and BMI in the study, we performed analyses for subgroups stratified by these factors. Subgroup analysis showed that significant associations of the rs2241766 polymorphism with the risk of hypertension were observed not only in the allelic model, recessive model, dominant model, and homozygous model in the subgroup of the Caucasian population, but also in the allelic model, recessive model, and homozygous model in individuals with BMI more than 25. In subgroups stratified by age, we found that the allelic model, recessive model, and homozygous models was significantly associated with an increased risk of hypertension in individuals no more than 40 years old. In order to prevent the impact of the HWE study on the analysis, we analyzed the test value based on the control group P, and found that the recessive and homozygous models were significantly associated with the risk of onset in the group at P<0.05. The association between the rs2241766 polymorphism in ADIPOQ gene and the susceptibility to hypertension has also been discussed by Xi et al. [25] Zhaoet al. [26]. In their study, the rs2241766 was not associated with the hypertension susceptibility, whichis inconsistent with our findings. However, the rs2241766 in ADIPOQ gene is associated with risks of obesity, coronary heart disease, and type 2 diabetes. Therefore, no association between the rs2241766 polymorphism and the risk of hypertension that reported by Zhao et al. [26] and Xi et al. [25] may be related to environmental factors such as diet-induced obesity which were not considered in their studies. The level of adiponectin in the plasma of patients with hypertension is low, and low levels of adiponectin are associated with single nucleotide polymorphisms of ADIPOQ [27]. Mousavinasab et al. [28] found that the GG genotype of the rs2241766 had a higher prevalence in individuals with hypertension than TT genotype. Tang et al. [5,28] reported that GG + GT genotype rather than TT genotype was significantly associated with the low level of adiponectin. Therefore, we speculate that the association between hypertension susceptibility and rs2241766 polymorphism may be affected by environmental factors such as obesity. The rs2241766 polymorphism in the exon 2 of the ADIPOQ gene may affect the expression of ADIPOQ genein adipose tissues and thereby associate with a reduced plasma concentration of adiponectin, which may increase the probability of developing hypertension. In the present study, the significance of association identified in the subgroup of the Caucasian may indicate the genetic heterogeneity. We speculate that the linkage disequilibrium structure of human ADIPOQ gene may be different in different ethnicities, i.e., the rs2241766 polymorphism is not consistently associated with the risk of hypertension in different races. Further exploration of the genetic structure of ADIPOQ gene may improve our understanding of mechanisms by which genetic factors work in hypertension.

We found that the rs266729 polymorphism was not significantly associated with the risk of hypertension risk at an overall level for included subjects. However, after stratification, in individuals no more than 40 years old and those who were Caucasians, the recessive genetic model of GG of the rs266729 were associated with an increased probability of developing hypertension (GG v GT + TT: OR=2.33, 95% CI=1.33-4.08). Studies on rs266729 and hypertension risk included subjects from different regions. A study of the British population found that the rs266729 polymorphism was associated with the levels of systolic and diastolic blood pressure [29]. The -11377C>G mutation in the proximal promoter region is associated with lower levels ofadiponectin and with an increased risk of hypertension in Hong Kong and the mainland of China. Although our results were also statistically significant, considering the limited number of the included studies, the interpretation of our results needs to be cautious. The association between the rs266729 polymorphism and the risk of hypertension and the underlying mechanism deserve further study.

In our present study, the polymorphism of rs1501299 was not significantly associated with the risk of hypertension in either overall or subgroup analyses. In our included studies, it was reported that the rs1501299 polymorphism is a protective factor for hypertension or a risk factor for hypertension [24,30], which is inconsistent to our null conclusions. Hara et al. [31] found association between the rs1501299 polymorphism and adiponectin concentration in obese individuals with a BMI of no less than 26.7. We considered that the inconsistency may be due to differences in stratification and assumed that rs1501299 might be less able to regulate adiponectin levels than other polymorphism loci, all of which may be unrelated. Therefore, more research is needed to explore the effect of rs1501299 polymorphism on hypertension.

Nowadays, it has been proved that adiponectin can decrease blood pressure through central and peripheral mechanisms. However, experiments for these findings are performed in environment that were strictly controlled and had well designed controls, which may not directly and accurately reflect the occurrence and development of human hypertension in the real world. Hypertension is affected by a combination of environmental and genetic factors. Adiponectin levels are also affected by both the ADIPOQ polymorphism and the environment. Risk factors relating to lifestyle such as obesity may often play a more decisive role than genetic factors. Some studies have shown that after adjustment of some adipokines such as resistin and leptin, adiponectin levels are no longer associated with the risk of hypertension, meanwhile, adipocytokines secreted by perivascular adipose tissue still cause contractions of adjacent small arteries [32,33]. Under this circumstance, the level of adiponectin may not be sufficient to affect blood pressure, and other fat factors may do. However, a genome-wide association study showed that the ADIPOQ polymorphism was identified as an important genetic factor affecting blood pressure, and the ADIPOQ gene affects blood pressure by regulating adiponectin levels, rather than by regulating adipokines or other acquired risk factors identified [34].

Our research has some limitations: ① the literature we included is either in Chinese or in English and may have some bias in the results; ② when we conducted subgroup analysis, limited studies were available for certain subgroup analyses and the results need to be treated with caution; ③ there were two control group in the literature that does not meet the HWE balance, which mightdue to genotyping errors or other biases in the original study; ④ our analysis was based primarily on unadjusted effect estimates, while confounding factors were not controlled and gene-environment interactions with disease were not considered; ⑤ only Asians and Caucasians were included, and the conclusions may not be suitable for all races.

In summary, our meta-analysis results show that the rs2241766 polymorphism is associated with the risk of hypertension. The polymorphism of rs1501299 is not significantly associated with the risk of hypertension. The rs266729 polymorphism is only found to be associated with the risk of hypertension in subgroups of individuals no more than 40 years old and in Caucasian population. Whether these polymorphisms may have a clinical significance in patients with hypertension remains to be determined, and further research is needed to confirm our finding in the future.

Acknowledgements

This work was supported by: (1) The new era comprehensively and thoroughly promote the study of healthy Anhui construction, Anhui Province philosophy and social science planning general project (No. AHSKY2018D55); (2) Molecular epidemiological study of cZNF609/mir-615-5p/target gene signaling pathway involved in hypertension and stroke mechanism, National Natural Science Foundation of China (No. 81874280).

Disclosure of conflict of interest

None.

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