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. 2019 Mar 18;19:63. doi: 10.1186/s12872-019-1041-3

Associations between ADIPOQ polymorphisms and coronary artery disease: a meta-analysis

Xia Zhang 1, Yan Jun Cao 1, Hong Yu Zhang 1, Hongliang Cong 2,✉, Jian Zhang 3,✉
PMCID: PMC6421689  PMID: 30885128

Abstract

Background

Whether adiponectin (ADIPOQ) polymorphisms are associated with coronary artery disease (CAD) remain controversial. Therefore, we performed this meta-analysis to better explore potential roles of ADIPOQ polymorphisms in CAD.

Methods

PubMed, Web of Science, Embase and CNKI were searched for eligible studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.

Results

Totally 45 studies were included for pooled analyses. A significant association with the susceptibility to CAD was detected for 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) polymorphism in overall population. Further subgroup analyses by ethnicity showed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, whereas rs2241766 polymorphism was significantly associated with the susceptibility to CAD in Caucasians, East Asians and South Asians.

Conclusions

Our findings indicated that rs1501299 and rs2241766 polymorphisms both affect the susceptibility to CAD in certain populations.

Keywords: Adiponectin (ADIPOQ), Genetic polymorphisms, Coronary artery disease (CAD), Meta-analysis

Background

Coronary artery disease (CAD) is the leading cause of death and disability worldwide [1, 2]. To date, the exact pathogenesis of CAD remains largely unknown. Nevertheless, plenty of evidences demonstrated that genetic factors are crucial for the development of CAD. First, family clustering of CAD was observed extensively, and past twin studies showed 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 indicated that genetic predisposition to CAD is important for its occurrence and development.

Adiponectin (ADIPOQ), an adipocytokine that regulates energy and material metabolism, is implicated in the development of multiple metabolic disorders including obesity and type II diabetes. And it was evident that these two common metabolic disorders were associated with an increased risk of CAD [7]. Furthermore, previous studies demonstrated that adipoenctin have both anti-atherogenic and anti-inflammatory property [8, 9]. Moreover, the expression level of adiponectin was also significantly decreased in CAD patients [10, 11]. Overall, these evidences jointly suggested that adipoenctin might exert favorable protection effects against CAD. Therefore, functional ADIPOQ genetic polymorphisms, which may alter the expression level of adiponectin, may also affect individual susceptibility to CAD. Recently, some pilot studies already investigated associations of two common functional ADIPOQ polymorphisms, rs1501299 and rs2241766, with the susceptibility to CAD. However, the results of these studies were not consistent, 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.

Methods

The current meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist [20–22].

Literature search and inclusion criteria

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) was used to searched for potentially eligible articles that were published prior to December 1, 2018 in PubMed, Web of Science, Embase and China National Knowledge Infrastructure (CNKI). We also reviewed the reference lists of all retrieved articles for other potentially eligible studies.

To test the research hypothesis of this meta-analysis, included studies must meet all the following criteria: (1) case-control study on associations between ADIPOQ polymorphisms (rs1501299 and rs2241766) and CAD; (2) provide genotypic and/or allelic frequency of investigated polymorphisms; (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; (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.

Data extraction and quality assessment

We extracted the following information from eligible studies: 1. name of the first author; 2. year of publication; 3. country and ethnicity of participants; 4. sample size; and 5. 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 [23]. The NOS has a score range of zero to nine, and studies with a score of more than seven were thought to be of high quality.

Two reviewers conducted data extraction and quality assessment independently (Xia Zhang and YanJun Cao). 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, Review Manager Version 5.3.3 was used to perform statistical analyses. We calculated ORs and 95% CIs to estimate potential associations between ADIPOQ polymorphisms and CAD in all possible genetic models, and a p value of 0.05 or less was defined as statistically significant. Between-study heterogeneities were evaluated by I2 statistic. Random-effect models (REMs) would be used for analyses if I2 was greater than 50%. Otherwise, analyses would be performed with fixed-effect models (FEMs). Subgroup analyses by ethnicity and type of disease were subsequently carried out. Stabilities of synthetic results were tested in sensitivity analyses. Publication biases were assessed by funnel plots.

Results

Characteristics of included studies

We found 442 potential relevant articles. Among these articles, totally 45 eligible studies were finally included for pooled analyses (see Fig. 1). Baseline characteristics of included studies were shown in Table 1.

Fig. 1.

Fig. 1

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Flowchart of study selection for the present study

Table 1.

The characteristics of included studies

First author, year Country Ethnicity Type of disease Sample size Genotype distribution P-value for HWE NOS score
Cases Controls
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
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Abbreviations: CAD Coronary artery disease, MI Myocardial infarction, ACS Acute coronary syndrome, HWE Hardy-Weinberg equilibrium, NOS Newcastle-Ottawa scale, NA Not available

Overall and subgroup analyses

Results of overall and subgroup analyses were summarized in Table 2. To be brief, a significant association with the susceptibility to CAD was detected for 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) polymorphism in overall analyses. Further subgroup analyses by ethnicity revealed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, whereas 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 Fig. 2).

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
rs1501299 G/T GG vs. GT + TT TT vs. GG + GT GT vs. GG + TT G vs. T
Overall 11,544/15642 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 10,135/11577 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%
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Abbreviations: OR Odds ratio, CI Confidence interval, NA Not available, CAD Coronary artery disease, MI Myocardial infarction

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

Fig. 2.

Fig. 2

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Forest plots for overall analyses of investigated polymorphisms. a Forest plot of rs1501299 polymorphism and CAD under dominant comparison; b Forest plot of rs1501299 polymorphism and CAD under recessive comparison; c Forest plot of rs1501299 polymorphism and CAD under overdominant comparison; d Forest plot of rs1501299 polymorphism and CAD under allele comparison; e Forest plot of rs2241766 polymorphism and CAD under dominant comparison; f Forest plot of rs2241766 polymorphism and CAD under recessive comparison; g Forest plot of rs2241766 polymorphism and CAD under overdominant comparison. h Forest plot of rs2241766 polymorphism and CAD under allele comparison

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.

Discussion

Based on combined analyses of 45 eligible studies, our study showed that rs1501299 and rs2241766 polymorphisms were both significantly associated with the susceptibility to CAD in certain populations, which suggested that these two polymorphisms may be used to identify individuals with higher susceptibility to CAD. There are two possible explanations for our positive findings. First, genetic variations of the ADIPOQ gene may lead to alternations in gene expression or changes in ADIPOQ protein structure, which may subsequently affect biological functions of ADIPOQ and ultimately impact individual susceptibility to CAD. Second, it is also possible that ADIPOQ polymorphisms may be linked to each other or even linked to other unidentified genes, which could also impact individual susceptibility to CAD.

There are several points that should be noted about this meta-analysis. Firstly, previous experimental studies demonstrated that mutant alleles of investigated polymorphisms could lead to decreased adiponectin generation, which may partially explain our positive findings [12–19]. Secondly, it is also worth noting that for rs1501299 polymorphism, 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 that these inconsistent findings may be resulted from a complex interaction of both genetic and environmental factors. Thirdly, it should be noted that significant between-study heterogeneities were observed in all genetics comparisons of overall analyses, which may partially attributed to ethnic and racial differences of eligible studies. To overcome between-study heterogeneities, REMs were used for pooled analyses, and in further subgroup analyses, we noticed that between-study heterogeneities among studies that were conducted in Caucasians were relatively small, which also supported that ethnic background could impact individual susceptibility to CAD. Fourthly, a recent meta-analyses conducted by Hou et al. [24] also tried to explore potential associations between ADIPOQ polymorphisms and CAD. However, our findings should be considered as more conclusive compared to that of previous meta-analysis since many related studies were published in the last three years, which warranted an update meta-analysis. Totally 10 more eligible studies were enrolled in our pooled analyses, and the sample sizes of our analyses were also significantly larger than that of previous meta-analyses, which could significantly reduce the risk of obtaining false positive or false negative results. Compared with the previous meta-analysis, similar positive results were detected for rs2241766 polymorphism in overall and subgroup analyses. However, positive results in Caucasians for rs1501299 polymorphism were no longer observed in our meta-analysis. Instead, we found that rs1501299 polymorphism could impact individual susceptibility to CAD in East Asians under recessive genetic model. Therefore, future studies with larger sample sizes are still needed to test the potential associations between ADIPOQ polymorphisms and CAD, especially for rs1501299 polymorphism. Fifthly, our study only focused on two mostly investigated ADIPOQ polymorphisms, and future meta-analyses should try to investigate the associations between CAD and other common ADIPOQ polymorphisms such as rs266729, rs822395 and rs17300539. These polymorphisms were not analyzed by us because we failed to find any additional eligible studies compared to the previous meta-analysis conducted by Hou et al. [24].

Some limitations of this meta-analysis should also be acknowledged when interpreting our findings. First, our pooled analyses were based on unadjusted estimations due to lack of raw data, and failure to perform further adjusted analyses may impact the reliability of our findings [25, 26]. Second, since our pooled analyses were based on retrospective case-control studies, despite our positive findings, future perspective studies are still needed to examine whether there is direct causal relationship between ADIPOQ polymorphisms and CAD [27, 28]. Third, associations between ADIPOQ polymorphisms and CAD may also be modified by gene-gene and gene-environmental interactions. However, due to lack of raw data, we could not conduct relevant analyses [29, 30]. Fourth, our analyses were based on retrospective case-control studies. Thus, despite the relatively high NOS score, it was still possible that our findings might be impacted by potential selection, measurement and confounding biases. Taking the above mentioned limitations into consideration, our findings should be interpreted with caution.

Conclusions

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

Acknowledgments

None.

Funding

None.

Availability of data and materials

The current study was based on results of relevant published studies.

Abbreviations

ADIPOQ

Adiponectin

CAD

Coronary artery disease

HWE

Hardy-Weinberg equilibrium

NOS

Newcastle-Ottawa scale

Authors’ contributions

XZ, HC and JZ conceived of the study, participated in its design. XZ and YC conducted the systematic literature review. HZ performed data analyses. XZ, HC and JZ drafted the manuscript. All gave final approval and agree to be accountable for all aspects of work ensuring integrity and accuracy.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Xia Zhang, Email: zhangxiayfu@163.com.

Yan Jun Cao, Email: caoyanjnu@163.com.

Hong Yu Zhang, Email: zhanghongyul1@yeah.net.

Hongliang Cong, Email: conghongliang88@163.com.

Jian Zhang, Email: zhangjianopy@yeah.net.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The current study was based on results of relevant published studies.

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