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. 2019 Mar 24;8(1):137–143. doi: 10.1080/21623945.2019.1595270

Effects of ADIPOQ polymorphisms on individual susceptibility to coronary artery disease: a meta-analysis

Zhiyuan Wang a, Jinglan Diao a, Xin Yue b, Jingquan Zhong b,✉
PMCID: PMC6768194  PMID: 30879388

ABSTRACT

Whether adiponectin (ADIPOQ) polymorphisms affect individual susceptibility to coronary artery disease (CAD) remains controversial. Therefore, we performed this meta-analysis to better analyse associations between ADIPOQ polymorphisms and CAD. PubMed, Web of Science, Embase and CNKI were searched for eligible studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Totally, 51 studies were eligible for analyses. In overall analyses, significant associations with the susceptibility to CAD were detected for rs266729 (overdominant model: p= 0.03, OR = 1.11, 95% CI 1.01–1.22), rs822395 (recessive model: p= 0.007, OR = 1.21, 95% CI 1.05–1.40) and rs2241766 (dominant model: p= 0.0009, OR = 0.82, 95% CI 0.73–0.92; recessive model: p= 0.04, OR = 1.29, 95% CI 1.02–1.64; allele model: p< 0.0001, OR = 0.80, 95% CI 0.73–0.88) polymorphisms. Further subgroup analyses by ethnicity revealed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, while rs2241766 polymorphism was significantly associated with the susceptibility to CAD in Caucasians, East Asians and South Asians. In summary, our findings indicated that rs266729, rs822395, rs1501299 and rs2241766 polymorphisms were all significantly associated with the susceptibility to CAD in certain populations.

KEYWORDS: Adiponectin (ADIPOQ), genetic polymorphisms, coronary artery disease (CAD), meta-analysis

Introduction

Coronary artery disease (CAD) is the leading cause of death and disability worldwide [1,2]. So far, the exact pathogenesis of CAD is still unclear. Nevertheless, plenty of evidence supported that genetic factors may play a crucial part in its development. First, family clustering of CAD was observed extensively, and past twin studies proved that the heredity grade of CAD was over 50% [3,4]. Second, numerous genetic variants were found to be associated with an increased susceptibility to CAD by previous genetic association studies, and screening of common causal variants was also proved to be an efficient way to predict the individual risk of developing CAD [5,6]. Overall, these findings jointly supported that genetic predisposition to CAD is important for its occurrence and development.

Adiponectin (ADIPOQ), a multifunctional adipocytokine that is predominantly secreted by adipocytes, plays a central role in regulating energy and material metabolism [7]. Previous studies showed that adiponectin has both anti-atherogenic and anti-inflammatory properties [8,9]. Furthermore, the expression level of adiponectin was also significantly decreased in patients with CAD [10,11]. In summary, these pieces of evidence jointly suggested that adiponectin might exert favourable protection effects against CAD. Therefore, functional ADIPOQ genetic polymorphisms, which may alter the expression level of adiponectin, may also affect individual susceptibility to CAD. So far, several studies already tried to investigate associations between ADIPOQ polymorphisms and CAD, but the results of these studies were controversial, especially when they were conducted in different populations [12–19]. Previous studies failed to reach a consensus regarding associations between ADIPOQ polymorphisms and CAD partially because of their relatively small sample sizes. Thus, we performed the present meta-analysis to explore the relationship between ADIPOQ polymorphisms and CAD in a larger pooled sample size. Additionally, we also aimed to elucidate the potential effects of ethnic background on associations between ADIPOQ polymorphisms and CAD.

Materials and methods

Literature search and inclusion criteria

The current meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist [20]. PubMed, Web of Science, Embase and China National Knowledge Infrastructure (CNKI) were searched for potentially eligible articles using the combination of following terms: (adiponectin OR ADIPOQ) AND (polymorphism OR variant OR mutation OR genotype OR allele) AND (coronary heart disease OR coronary artery disease OR angina pectoris OR acute coronary syndrome OR myocardial infarction). We also reviewed the reference lists of all retrieved articles to identify other potentially eligible studies. The initial search was conducted in July 2018 and the latest update was performed in December 2018.

To test the research hypothesis of this meta-analysis, included studies must satisfy the following criteria: (1) case–control study on associations between ADIPOQ polymorphisms and CAD; (2) provide genotypic and/or allelic frequency of investigated ADIPOQ polymorphisms; and (3) full text in English or Chinese available. Studies were excluded if one of the following criteria was fulfilled: (1) not relevant to ADIPOQ polymorphisms and CAD; (2) case reports or case series; and (3) abstracts, reviews, comments, letters and conference presentations. In the case of duplicate reports by the same authors, we only included the most recent study for analyses.

Data extraction and quality assessment

We extracted the following information from eligible studies: (a) name of the first author; (b) year of publication; (c) country and ethnicity of participants; (d) sample size; and (e) genotypic distributions of ADIPOQ polymorphisms in cases and controls. The probability value (p value) of Hardy–Weinberg equilibrium (HWE) was also calculated.

We used the Newcastle–Ottawa scale (NOS) to evaluate the quality of eligible studies [21]. The NOS has a score range of 0 to 9, and studies with a score of more than 7 were thought to be of high quality.

Two reviewers conducted data extraction and quality assessment independently. When necessary, we wrote to the corresponding authors for extra information. Any disagreement between two reviewers was solved by discussion until a consensus was reached.

Statistical analyses

In the current study, we performed statistical analyses by using Review Manager Version 5.3.3. We calculated ORs and 95% CIs to estimate potential associations between ADIPOQ polymorphisms and CAD in dominant, recessive, overdominant and allele models, and statistical significances of pooled analyses were determined by the Z test, with a p value of 0.05 or less was defined as statistically significant. All investigated ADIPOQ polymorphisms contain a major allele (M) and a minor allele (m), and the definitions of all genetic comparisons were as follows: dominant comparison is defined as MM versus Mm + mm, recessive comparison is defined as mm vs. MM +Mm, overdominant comparison is defined as Mm versus MM + mm, and the allele comparison is defined as M versus m. Between-study heterogeneities were evaluated by I2 statistic. Random-effect models would be used for analyses if I2 was greater than 50% (Der Simonian–Laird method). Otherwise, analyses would be conducted with fixed-effect models (Mantel–Haenszel method). Subgroup analyses were subsequently carried out by ethnicity and type of disease. Stabilities of synthetic results were tested in sensitivity analyses. Publication biases were assessed by funnel plots.

Results

Characteristics of included studies

We found 434 potentially relevant articles. Among these articles, totally 51 eligible studies were finally included for synthetic analyses (see Figure 1). The NOS score of eligible articles ranged from 7 to 8, which indicated that all the included studies were of high quality. Baseline characteristics of the included studies are summarized in Table 1.

Figure 1.

Figure 1.

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Flowchart of study selection for the present study.

Table 1.

The characteristics of included studies.

First author, y Country Ethnicity Type of disease Sample size Genotype distribution
 p-Value for HWE NOS score
Case–controls
rs266729 G/C         CC/CG/GG    
Cheung 2014 Hong Kong East Asian CAD 184/2007 111/65/8 1148/729/130 0.327 7
Chiodini 2010 Italy Caucasian MI 1002/503 583/353/66 321/160/22 0.717 7
De Caterina 2011 Italy Caucasian MI 1855/1855 1076/671/108 1063/684/108 0.883 7
Du 2016 China East Asian CAD 493/304 278/175/40 219/73/12 0.069 8
Gable 2007 UK Caucasian MI 530/564 278/217/35 329/197/38 0.254 8
Hegener 2006 USA Mixed MI 340/342 197/123/20 188/134/20 0.543 8
Lacquemant 2004 UK Caucasian CAD 161/313 89/65/7 174/118/21 0.870 7
Oguri 2009 Japan East Asian MI 773/1114 397/336/40 675/379/60 0.478 7
Persson 2010 Sweden Caucasian MI 244/244 127/100/17 130/101/13 0.241 8
Prior 2009 UK Caucasian CAD 155/609 89/56/10 335/242/32 0.165 8
Prior 2011 UK Caucasian CAD 85/298 46/38/1 158/114/26 0.406 8
Rodr´ıguez-Rodr´ıguez 2011 Spain Caucasian CAD 119/555 67/46/6 327/188/40 0.076 7
Zhang 2015 China East Asian CAD 561/412 305/228/28 212/172/28 0.383 8
Zhang 2018 China East Asian CAD 717/612 345/306/66 301/253/58 0.648 8
Zhao 2018 China East Asian CAD 1044/1349 590/385/69 774/498/77 0.791 8
Zhong 2010 China East Asian CAD 198/237 110/72/16 146/76/15 0.239 8
rs822395 A/C         AA/AC/CC    
Cheung 2014 Hong Kong East Asian CAD 184/2009 130/53/1 1441/527/41 0.371 7
De Caterina 2011 Italy Caucasian MI 1855/1854 848/811/196 867/806/181 0.750 7
Lacquemant 2004 UK Caucasian CAD 162/311 75/69/18 138/141/32 0.647 7
Pischon 200 USA Mixed CAD 496/989 223/208/65 450/467/72 0.001 7
Qi 2005 USA Mixed CAD 234/626 104/101/29 270/280/76 0.795 7
Zhang 2015 China East Asian CAD 535/396 408/119/8 274/114/8 0.328 8
Zhang 2018 China East Asian CAD 717/612 295/307/115 252/281/79 0.962 8
Zhong 2010 China East Asian CAD 198/237 143/48/7 175/59/3 0.424 8
rs1501299 G/T         GG/GT/TT    
Al-Daghri 2011 Saudi Arabia South Asian CAD 123/297 47/57/19 111/142/44 0.897 7
Ambroziak 2018 Poland Caucasian MI 188/153 88/72/28 84/59/10 0.933 7
Antonopoulos 2013 Greece Caucasian CAD 462/132 220/212/30 66/50/16 0.184 8
Bacci 2004 Italy Caucasian CAD 142/234 70/65/7 118/88/28 0.073 7
Boumaiza 2011 Tunisia Caucasian CAD 213/108 105/84/23 45/41/18 0.115 8
Chen 2011 China East Asian CAD 93/102 54/33/6 61/38/3 0.307 7
Cheung 2014 Hong Kong East Asian CAD 182/2010 88/75/19 1103/759/148 0.270 7
Chiodini 2010 Italy Caucasian MI 1002/503 530/392/80 239/198/66 0.016 7
De Caterina 2011 Italy Caucasian MI 1833/1821 926/746/161 906/767/148 0.419 7
Esteghamati 2012 Iran South Asian CAD 114/127 76/30/8 63/47/17 0.095 7
Filippi 2005 Italy Caucasian CAD 580/466 287/241/52 266/167/33 0.338 8
Gable 2007 UK Caucasian MI 504/557 266/216/22 289/225/43 0.931 8
Ghazouani 2018 Tunisia Caucasian CAD 277/269 143/93/41 138/88/43 <0.001 8
Gui 2012 China East Asian CAD 410/431 172/185/53 239/154/38 0.072 8
Hegener 2006 USA Mixed MI 341/341 183/134/24 181/143/17 0.093 8
Jung 2006 Korea East Asian CAD 88/68 38/43/7 31/32/5 0.399 7
Katakami 2012 Japan East Asian MI 213/2424 129/71/13 1229/976/219 0.209 7
Lacquemant 2004 UK Caucasian CAD 161/309 82/66/13 169/115/25 0.387 7
Li 2018 China East Asian CAD 201/141 67/107/27 64/53/24 0.030 8
Liang 2011 China East Asian MI 78/84 30/43/5 48/30/6 0.663 7
Liang 2017 China East Asian CAD 960/962 490/388/82 617/300/45 0.275 8
Mohammadzadeh 2016 Iran South Asian CAD 100/100 38/55/7 56/42/2 0.063 7
Ohashi 2004 Japan East Asian CAD 383/368 185/164/34 190/149/29 0.977 8
Oliveira 2012 Brazil Mixed CAD 450/153 209/197/44 62/68/23 0.542 7
Pischon 2007 USA Mixed CAD 491/988 266/182/43 485/416/87 0.869 7
Qi 2005 USA Mixed CAD 228/594 105/111/12 293/249/52 0.930 7
Rizk 2012 Qatar South Asian ACS 142/121 58/64/20 46/59/16 0.667 7
Rodr´ıguez-Rodr´ıguez 2011 Spain Caucasian CAD 119/555 69/44/6 287/224/44 0.975 7
Wu 2013 China East Asian CAD 188/200 67/108/13 92/90/18 0.545 7
Zhang 2015 China East Asian CAD 561/412 309/209/43 214/170/28 0.459 8
Zhang 2018 China East Asian CAD 717/612 583/126/8 471/131/10 0.798 8
rs2241766 T/G         TT/TG/GG    
Al-Daghri 2011 Saudi Arabia South Asian CAD 122/298 77/35/10 220/72/6 0.969 7
Antonopoulos 2013 Greece Caucasian CAD 462/132 359/97/6 99/29/4 0.309 8
Bacci 2004 Italy Caucasian CAD 130/220 90/35/5 149/60/11 0.135 7
Boumaiza 2011 Tunisia Caucasian CAD 212/104 145/57/10 75/24/5 0.111 8
Chang 2009 Taiwan East Asian CAD 600/687 316/238/46 309/399/79 0.606 7
Chen 2011 China East Asian CAD 93/102 68/19/6 59/35/8 0.391 7
Cheung 2014 Hong Kong East Asian CAD 184/2012 89/83/12 1007/822/183 0.413 7
Chiodini 2010 Italy Caucasian MI 1002/503 679/304/19 359/126/18 0.102 7
Di 2011 China East Asian CAD 196/124 91/85/20 65/50/9 0.884 7
Du 2016 China East Asian CAD 493/304 253/190/50 185/97/22 0.069 8
Esteghamati 2012 Iran South Asian CAD 114/127 48/41/25 68/46/13 0.222 7
Foucan 2010 French West Indies African CAD 57/159 NA NA NA 7
Gable 2007 UK Caucasian MI 526/563 360/154/12 384/168/11 0.280 8
Ghazouani 2018 Tunisia Caucasian CAD 277/269 181/74/22 182/70/17 0.007 8
Hegener 2006 USA Mixed MI 341/341 241/95/5 252/80/9 0.389 8
Jin 2009 China East Asian CAD 110/73 53/48/9 50/20/3 0.584 8
Jung 2006 Korea East Asian CAD 88/68 41/40/7 34/30/4 0.431 7
Lacquemant 2004 UK Caucasian CAD 162/315 109/48/5 249/57/9 0.015 7
Li 2011 China East Asian CAD 118/97 51/46/21 54/31/12 0.036 8
Liang 2017 China East Asian CAD 960/982 471/382/107 608/308/46 0.387 8
Luo 2010 China East Asian CAD 221/100 100/99/22 50/41/9 0.886 7
Mofarrah 2016 Iran South Asian CAD 152/72 82/35/35 56/13/3 0.072 8
Mohammadzadeh 2016 Iran South Asian CAD 100/100 75/24/1 65/31/4 0.900 7
Nan 2012 China East Asian CAD 213/467 115/84/14 237/191/39 0.953 8
Oliveira 2012 Brazil Mixed CAD 450/153 323/114/13 117/33/3 0.708 7
Pischon 2007 USA Mixed CAD 482/979 374/102/6 759/202/18 0.290 7
Qi 2005 USA Mixed CAD 219/599 NA NA NA 7
Rizk 2012 Qatar South Asian ACS 142/122 62/42/38 56/49/17 0.245 7
Sabouri 2011 Iran South Asian CAD 329/241 253/74/2 205/35/1 0.703 7
Xu 2010 China East Asian CAD 153/73 78/65/10 50/20/3 0.584 8
Zhang 2011 China East Asian CAD 149/167 63/60/26 97/50/20 0.002 7
Zhang 2015 China East Asian CAD 561/412 276/235/50 224/164/24 0.399 8
Zhang 2018 China East Asian CAD 717/612 500/184/33 456/149/7 0.177 8
rs17300539 G/A         GG/GA/AA    
Ambroziak 2018 Poland Caucasian MI 193/153 169/23/1 130/23/0 0.315 7
Chiodini 2010 Italy Caucasian MI 1002/503 827/165/10 414/87/2 0.252 7
Gable 2007 UK Caucasian MI 529/568 446/78/5 458/107/3 0.220 8
Oliveira 2012 Brazil Mixed CAD 449/153 388/56/5 131/22/0 0.338 7
Zhang 2018 China East Asian CAD 717/612 614/100/3 542/67/3 0.553 8
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CAD: coronary artery disease; MI: myocardial infarction; ACS: acute coronary syndrome; HWE:Hardy-Weinberg Hardy–Weinberg equilibrium; NOS: Newcastle-Ottawa Newcastle–Ottawa scale; NA: not available.

Overall and subgroup analyses

Results of overall and subgroup analyses are summarized in Table 2. To be brief, significant associations with the susceptibility to CAD were detected for rs266729 (overdominant model: p = 0.03, odds ratio [OR] = 1.11, 95% confidence interval [CI] 1.01–1.22), rs822395 (recessive model: p = 0.007, OR = 1.21, 95% CI 1.05–1.40) and rs2241766 (dominant model: p = 0.0009, OR = 0.82, 95% CI 0.73–0.92; recessive model: p = 0.04, OR = 1.29, 95% CI 1.02–1.64; allele model: p < 0.0001, OR = 0.80, 95% CI 0.73–0.88) polymorphisms in overall analyses. Further subgroup analyses by ethnicity revealed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, while rs2241766 polymorphism was significantly associated with the susceptibility to CAD in Caucasians, East Asians and South Asians. No any other positive results were observed in overall and subgroup analyses (see Table 2 and supplementary Figure 1).

Table 2.

Results of overall and subgroup analyses for ADIPOQ polymorphisms and CAD.

Population Sample size Dominant comparison
 Recessive comparison
 Overdominant comparison
 Allele comparison
p Value OR (95% CI) I2 statistic p Value OR (95% CI) I2 statistic p Value OR (95% CI) I2 statistic p Value OR (95% CI) I2 statistic
rs266729 C/G   CC vs. CG + GG GG vs. CC + CG CG vs. CC + GG C vs. G
Overall 8461/11,318 0.06 0.90 (0.81–1.01) 62% 0.69 1.03 (0.91–1.16) 20% 0.03 1.11 (1.01–1.22) 52% 0.20 0.94 (0.86–1.03) 65%
Caucasian 4151/4941 0.19 0.94 (0.86–1.03) 6% 0.93 1.01 (0.84–1.21) 28% 0.20 1.06 (0.97–1.16) 8% 0.40 0.97 (0.90–1.04) 36%
East Asian 3970/6035 0.12 0.85 (0.70–1.04) 79% 0.64 1.04 (0.88–1.24) 34% 0.09 1.16 (0.98–1.38) 71% 0.16 0.89 (0.76–1.05) 79%
MI 4744/4622 0.11 0.87 (0.74–1.03) 70% 0.47 1.07 (0.90–1.27) 0% 0.18 1.13 (0.95–1.34) 71% 0.08 0.90 (0.80–1.01) 60%
rs822395 A/C   AA vs. AC + CC CC vs. AA + AC AC vs. AA + CC A vs. C
Overall 4381/7034 0.83 1.01 (0.93–1.10) 0% 0.007 1.21 (1.05–1.40) 46% 0.07 0.93 (0.85–1.01) 14% 0.30 0.97 (0.91–1.03) 27%
Caucasian 2017/2165 0.63 0.97 (0.86–1.10) 0% 0.39 1.09 (0.89–1.34) 0% 0.97 1.00 (0.88–1.13) 0% 0.45 0.97 (0.88–1.06) 0%
East Asian 1634/3254 0.36 1.07 (0.93–1.24) 42% 0.20 1.20 (0.91–1.59) 39% 0.11 0.89 (0.77–1.03) 33% 0.75 1.03 (0.85–1.25) 55%
rs1501299 G/T   GG vs. GT + TT TT vs. GG + GT GT vs. GG + TT G vs. T
Overall 11,544/15,642 0.30 0.94 (0.84–1.05) 73% 0.42 0.94 (0.80–1.10) 57% 0.08 1.09 (0.99–1.19) 60% 0.71 0.98 (0.90–1.08) 76%
Caucasian 5481/5107 0.82 1.01 (0.93–1.09) 39% 0.12 0.80 (0.61–1.06) 67% 0.29 1.04 (0.96–1.13) 2% 0.47 1.04 (0.93–1.17) 64%
East Asian 4074/7814 0.08 0.82 (0.66–1.03) 82% 0.03 1.20 (1.02–1.42) 40% 0.10 1.18 (0.97–1.43) 76% 0.14 0.88 (0.74–1.04) 80%
South Asian 479/645 0.88 1.04 (0.61–1.77) 78% 0.97 0.99 (0.68–1.45) 42% 0.79 0.95 (0.65–1.38) 55% 0.90 1.03 (0.68–1.56) 80%
MI 4159/5883 0.67 1.04 (0.87–1.23) 65% 0.63 0.91 (0.63–1.32) 74% 0.42 0.96 (0.88–1.05) 47% 0.71 1.03 (0.88–1.21) 75%
rs2241766 T/G   TT vs. TG + GG GG vs. TT + TG TG vs. TT + GG T vs. G
Overall 10,135/11,577 0.0009 0.82 (0.73–0.92) 67% 0.04 1.29 (1.02–1.64) 63% 0.08 1.12 (0.99–1.27) 71% <0.0001 0.80 (0.73–0.88) 67%
Caucasian 2771/2106 0.09 0.89 (0.79–1.02) 27% 0.39 0.87 (0.62–1.20) 0% 0.04 1.15 (1.01–1.32) 33% 0.24 0.93 (0.84–1.05) 20%
East Asian 4856/6280 0.02 0.80 (0.66–0.96) 77% 0.06 1.35 (0.99–1.84) 68% 0.30 1.12 (0.90–1.40) 83% 0.0006 0.80 (0.71–0.91) 66%
South Asian 959/960 0.04 0.69 (0.48–0.99) 66% <0.0001 2.67 (1.82–3.91) 39% 0.76 1.05 (0.76–1.46) 56% 0.01 0.64 (0.45–0.91) 76%
MI 1869/1407 0.19 0.90 (0.77–1.05) 0% 0.11 0.68 (0.43–1.09) 18% 0.06 1.16 (0.99–1.36) 30% 0.48 0.95 (0.83–1.09) 0%
rs17300539 A/G   AA vs. AG + GG GG vs. AA + AG AG vs. AA + GG A vs. G
Overall 2890/1989 0.73 1.03 (0.88–1.21) 27% 0.12 1.86 (0.85–4.10) 0% 0.46 0.94 (0.80–1.11) 40% 0.89 1.01 (0.87–1.18) 9%
Caucasian 1724/1224 0.19 1.14 (0.94–1.39) 0% 0.12 2.17 (0.81–5.82) 0% 0.09 0.84 (0.69–1.03) 0% 0.37 1.09 (0.90–1.31) 0%
MI 1724/1224 0.19 1.14 (0.94–1.39) 0% 0.12 2.17 (0.81–5.82) 0% 0.09 0.84 (0.69–1.03) 0% 0.37 1.09 (0.90–1.31) 0%
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OR: odds ratio; CI: confidence interval; NA: not available; CAD: coronary artery disease; MI: myocardial infarction.

The values in bold represent there are statistically significant differences between cases and controls.

Sensitivity analyses

We performed sensitivity analyses by excluding studies that deviated from HWE. No alterations of results were detected in sensitivity analyses, which suggested that our findings were statistically reliable.

Publication biases

Publication biases were evaluated with funnel plots. We did not find obvious asymmetry of funnel plots in any comparisons, which indicated that our findings were unlikely to be impacted by severe publication biases (see supplementary Figure 2).

Discussion

To the best of our knowledge, this is so far the most comprehensive meta-analysis on associations between ADIPOQ polymorphisms and CAD, and our pooled analyses demonstrated that rs266729, rs822395, rs1501299 and rs2241766 polymorphisms were all significantly correlated with the susceptibility to CAD in certain populations.

There are several points that need to be addressed about this meta-analysis. First, previous experimental studies showed that mutant alleles of investigated polymorphisms were correlated with decreased adiponectin generation, which may partially explain our positive findings [12–19]. Second, it is also notable that the trends of associations in different ethnicities were not always consistent, and this may be attributed to ethnic differences in genotypic distributions of investigated polymorphisms. However, it is also possible that these inconsistent findings may have resulted from a complex interaction of both genetic and environmental factors. Third, the pathogenic mechanism of CAD is highly complex, and hence, it is unlikely that a single genetic polymorphism could significantly contribute to its development. As a result, to better illustrate potential associations of certain genetic polymorphisms with CAD, we strongly recommend further studies to perform haplotype analyses and explore potential gene–gene interactions.

Some limitations of this meta-analysis should also be noted when interpreting our findings. First, our pooled analyses were based on unadjusted estimations due to lack of raw data, and we have to admit that failure to perform further adjusted analyses may impact the reliability of our findings [22,23]. Second, since our pooled analyses were based on case–control studies, despite our positive findings, future prospective studies are still needed to examine whether there is a direct causal relationship between ADIPOQ polymorphisms and CAD [24,25]. Third, associations between ADIPOQ polymorphisms and CAD may also be modified by gene–gene and gene–environmental interactions. However, most studies did not consider these potential interactions, which impeded us to conduct relevant analyses [26,27]. Considering the above-mentioned limitations, our findings should be interpreted with caution.

In conclusion, our meta-analysis suggested that rs266729, rs822395, rs1501299 and rs2241766 polymorphisms were all significantly correlated with the susceptibility to CAD in certain populations. However, further well-designed studies are still warranted to confirm our findings.

Authors’ contributions

Zhiyuan WANG and Jingquan ZHONG conceived the study and participated in its design. Zhiyuan WANG and Jinglan DIAO conducted the systematic literature review. Xin YUE performed data analyses. Zhiyuan WANG and Jingquan ZHONG drafted the manuscript. All gave final approval and agreed to be accountable for all aspects of work ensuring integrity and accuracy.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

For this type of study, formal consent is not required.

Supplementary material

Supplemental data for this article can be accessed here.

Supplemental Material

References

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