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Asian Pacific Journal of Cancer Prevention : APJCP logoLink to Asian Pacific Journal of Cancer Prevention : APJCP
. 2018;19(11):3225–3231. doi: 10.31557/APJCP.2018.19.11.3225

Angiotensin Converting Enzyme Insertion/Deletion Polymorphism is Associated with Breast Cancer Risk: A Meta-Analysis

Mansour Moghimi 1, Saeed Kargar 2,*, Mohammad Ali Jafari 3, Hossein Ahrar 4, Mohammad Hossein Jarahzadeh 5, Hossein Neamatzadeh 6, Jalal Sadeghizadeh-Yazdi 7
PMCID: PMC6318396  PMID: 30486620

Abstract

Background:

A number of case-control studies were conducted to investigate the association of angiotensin converting enzyme insertion/deletion (ACE I/D) polymorphism with breast cancer. But the results remain controversial. This meta-analysis aims to comprehensively evaluate the association of ACE I/D polymorphism with breast cancer.

Method:

A comprehensive literature search on PubMed, Google Scholar, SCOPUS and ISI Web of Knowledge databases for studies published up to June 01, 2018 was performed. Summary odds ratios (ORs) and 95% confidence intervals (CI) were estimated. Publication bias of literatures was evaluated using funnel plots and Egger’s test.

Results:

A total of 20 studies including 2846 breast cancer cases 9299 controls meeting the predefined criteria were involved in the meta-analysis. Overall, the ACE I/D polymorphisms was significantly associated with breast cancer under the allele model (I vs. D: OR= 0.803, 95% CI 0.647-0.996, p=0.046), the homozygote model (II vs. DD: OR= 0.662, 95% CI 0.462-0.947, p=0.024), the heterozygote model (ID vs. DD: OR= 0.707, 95% CI 0.528-0.946, p=0.020), the dominant model (II+ID vs. DD: OR= 0.691, 95% CI 0.507-0.941, p=0.019). In the subgroup analysis by ethnicity, a significant association was found among Asian and Caucasian populations, but not among mixed populations.

Conclusions:

This meta-analysis suggests that ACE I/D polymorphism may be associated with increased risk of breast cancer, especially among Asian and Caucasians. However, well-designed studies with larger sample size and more ethnic groups are needed to further validate the results.

Keywords: Breast cancer, ACE I/D, genetic polymorphism, cancer, Meta-analysis, susceptibility

Introduction

Breast cancer is the most frequently diagnosed cancer among women, which contributed to 25% of all cancer cases in women worldwide (Nedooshan et al., 2017; Yazdi et al., 2015). The etiology of breast cancer is still not fully understood. It is a heterogeneous disease in regard to its clinical, histological, and molecular profile (Kamali et al., 2017; Kamali et al., 2017). At present, genetic polymorphisms are increasingly recognized as contributors to breast cancer risk. Numerous breast cancer risk factors such as age, age at menarche, age at first childbirth, and number of first-degree female relatives with breast cancer have been identified (Shiryazdi et al., 2015; Shiryazdi et al., 2015). The heritable defects of BRCA1 and BRCA2 are identified in less than 50% of hereditary breast cancer cases (Forat-Yazdi et al., 2015; Forat-Yazdi et al.,2017; Neamatzadeh et al., 2015). Several epidemiological and molecular studies indicates ACE I/D gene polymorphism as a risk factor involved in the initiation and progression of different disease such as diabetic nephropathy, end-stage renal disease(ESRD) and cancer (Buraczynska et al., 2006; Singh et al., 2018).

The ACE, a zinc metalloenzyme, is a member of renin–angiotensin system (RAS) or the renin–angiotensin–aldosterone system (RAAS) involved in catalyzing the conversion of angiotensin I into a physiologically active peptide angiotensin II (Fagyas et al., 2014). The ACE gene (Gene ID: 1636; also known as: DCP; ACE1; DCP1; CD143) is localized in human chromosomes 17q23, comprises 26 exons, spans about 21 kb and more than 13 polymorphisms in this gene have been identified with susceptibility to different disease such as ACE I/D (rs 1799752), A240A>T (rs4291), 2350G>A (rs4344), and 17888C>T (rs4359) (Sayed-Tabatabaei et al., 2006). The ACE insertion/deletion (I/D) polymorphism is a nonsense and 287 bp Alu repeat sequence of DNA in the intron 16 of ACE gene, which represented by “Insertion” or “I”, and absence of the same denotes “Deletion” or “D” (Mahjoub et al., 2016).

To date, several studies have evaluated the association between ACE I/D polymorphism and breast cancer risk. However, the results are inconsistent and inconclusive, with some studies found significant association, while others were not. Although previous meta-analyses has tried to explore the whether the ACE I/D polymorphism is associated with increased risk of breast cancer, recently, new case-control studies in different ethnicities have been published. Therefore, we pooled all eligible studies in the present meta-analysis to evaluate the association of ACE I/D polymorphism with the risk of breast cancer.

Materials and Methods

Search Strategy

Electronic databases of PubMed (Medline), EMBASE and Google Scholar, ISI Web of Knowledge, Chinese National Knowledge Infrastructure database (CNKI), and Chinese Biomedical Literature Database (CBM) were used to identify all studies that evaluate the associations of ACE I/D polymorphism with breast cancer up to June 01, 2018. The key words used for search were: (breast, cancer, carcinoma, tumor, neoplasm, malignancy) and (angiotensin converting enzyme insertion/deletion, ACE I/D) and (polymorphism, mutation, variant, SNP). In addition, we have hand searched reference list of all eligible studies and related reviews for additional suitable studies. Studies in English, Persia, chinses and Portuguese languages were included to the meta-analysis. In addition, we have not set any restriction on time period, sample size, and ethnicity.

Data extraction

Two authors reviewed and extracted data independently in accordance with the inclusion criteria. The results were compared, and if any disagreement appeared, a third investigator was invited to evaluate such studies, and then the discrepancy was resolved by discussion. The following data were extracted: the name of first author, year of publication, country, ethnicity, sample size, allele numbers and genotype distributions in cases and controls, and the results of Hardy-Weinberg equilibrium (HWE) test.

Inclusion and exclusion criteria

The studies included in this meta-analysis had to meet the following criteria: (1) only case-control or cohort studies; (2) evaluation of the ACE I/D polymorphism and breast cancer risk; (3) provided sufficient genotyping data to calculate odds ratios (ORs) and their 95% confidence intervals (CIs). On the other side, the major reasons for study exclusion were: (1) studies were not relevant to ACE I/D polymorphism or breast cancer; (2) studies did not report genotype frequencies; (3) case only studies and control group including malignant tumor patients; (4) the design were based on sibling pairs or linkage studies; (5) reviews, case reports, abstracts, posters, letter and animal studies; and (6) overlapped or duplicated publications. When, more than one of the same populations was included in several studies, the most recently published study or the largest study with extractable data was selected. If original necessary data were unavailable in the selected studies, we have sent a request to the corresponding author for additional data.

Statistical analysis

Pooled ORs with corresponding 95% CIs were calculated to evaluate the association between ACE I/D polymorphism and breast cancer risk. We have used the Z-test to assess the significance of the pooled OR, in which P<0.05 was considered as statistically significant. Pooled ORs was calculated under the following five genetic models: the allele model (I vs. D), the homozygote model (II vs. DD), the heterozygote model (ID vs. DD), the dominant model (II+ID vs. DD), and the recessive model (II vs. ID+DD). The Q-test was used to evaluate between-study heterogeneity, was considered significant when p-value <0.05. Additionally, the I2 statistics was used to quantify or describe the percentage of between-study heterogeneity, which was considered as significant when I2>50% (I2 <25% indicating low heterogeneity; 25%-50% indicating moderate heterogeneity; and >50% indicating high heterogeneity) (Sobhan et al., 2018; Yazdi et al., 2017). Therefore, a fixed-effects model (the Mantel–Haenszel method) as used to calculate pooled OR in the absence of heterogeneity (Mantel and Haenszel, 1959). Otherwise, the random-effects model (the DerSimonian and Laird method) was used (DerSimonian and Laird 1986). The control genotypes were tested for Hardy- Weinberg equilibrium (HWE) using the Goodness of fit Chi-square test. The heterogeneity was adjusted by subgroup analysis and meta-regression. Sensitivity analyses were conducted to evaluate the effect of individual study on pooled ORs and assess the stability of results. The evidence of potential publication bias was evaluated by the funnel plot and Egger’s test, in which P<0.01 was considered as statistically significant. In addition, publication bias was assessed using visual inspection an asymmetric plot (Begg and Mazumdar, 1994; Egger et al., 1997). When publication bias observed, the Duval and Tweedie non-parametric ‘‘trim and fill’’ method was applied to adjust for it. The Comprehensive Meta-Analysis (CMA) Version 2.2 software program (Biostat, USA) was used to perform all statistical analysis, and all the P values were two sided.

Results

According to the present meta-analysis selection criteria, a total of 127 articles were retrieved by literatures search of online databases and hand searching. After review of titles and abstracts, 139 publications were excluded because were reviews, duplication and overlapping data, non-case-control studies, not relevant to ACE I/D polymorphism and breast cancer risk. Finally, a total of 20 case-control studies (Alves Corrêa et al., 2009; Felipe et al., 2011; Fishchuk and Gorovenko, 2013; Ghosh Roy et al., 2015; Gonzalez-Zuloeta Ladd et al., 2005; Haiman et al., 2003; van der Knaap et al., 2008; Koh et al., 2003; Kumar et al., 2016; Mendizábal-Ruiz et al., 2011; Namazi et al., 2010; El Sharkawy et al., 2014; Siddiqi et al., 2010; Singh et al., 2018; Xiaomei et al., 2014; Yaren et al., 2007, 2006) were included in our meta-analysis, consisting of 2,846 cases 9,299 controls. The detailed characteristics of the included studies are listed in Table 1. The original populations contain Singapore, Japan, Netherlands, Turkey, Brazil, Iran, India, Mexico, Colombia, Ukraine, china, and Egypt. There were 8 studies of subjects of Asians, 7 studies of subjects of Caucasian descent, 4 studies of subjects with mixed-ethnicity studies, and one study of subjects of African descent. All the genotype distributions of control subjects were in agreement with HWE for ACE I/D polymorphism except for 7 case-control studies (Table 1).

Table 1.

Characteristics of the Studies Included in the Meta-analysis

First Author Country Ethnicity Case Control Cases Control HWE
Genotypes Alleles Genotypes Alleles
DD ID II D I DD ID II D I
Koh 2003 Singapore Asian 182 643 23 80 79 126 238 56 305 282 417 869 0.036
Haiman 2003a African Americans 257 631 77 118 62 272 242 221 310 100 752 510 0.614
Haiman 2003b Japan Asian 284 357 37 128 119 202 366 43 160 154 246 460 0.884
Haiman 2003c Mixed 249 652 49 127 73 225 273 162 301 189 463 679 0.055
Haiman 2003d Caucasians 292 402 84 129 79 297 287 124 187 91 435 369 0.204
Ladd 2005 Netherlands Caucasians 114 4203 37 55 22 129 99 1133 2192 878 4458 3948 0.002
Yaren 2006 Turkey Caucasians 44 46 25 17 2 67 21 28 12 6 68 24 0.028
Yaren 2007 Turkey Caucasians 57 52 31 24 2 85 28 33 12 7 78 26 0.005
Van der 2008 Netherlands Caucasians 153 655 54 67 32 175 131 185 329 141 699 470 0.815
Alves Corrêa 2009 Brazil Mixed 101 307 61 20 20 142 60 141 113 53 395 219 ≤0.001
Namazi 2010 Iran Asian 70 70 20 42 8 82 58 29 34 7 92 48 0.514
Siddiqi 2010 India Asian 130 228 62 43 25 167 93 96 107 25 299 157 0.552
Mendizábal-Ruiz 2011 Mexico Mixed 63 288 53 6 4 112 14 63 151 74 277 299 0.394
Felipe 2011 Colombia Mixed 50 50 10 23 17 43 57 10 24 16 44 56 0.854
Fishchuk 2013 Ukraine Caucasians 131 102 41 53 37 135 127 21 50 31 92 112 0.918
Xiaomei 2014 China Asian 123 72 61 32 30 154 92 36 19 17 91 53 ≤0.001
El-Sharkawy 2014 Egypt African 70 50 29 28 13 86 54 21 21 8 63 37 0.483
Ghosh 2015 India Asian 108 128 62 28 18 152 64 32 50 46 114 142 0.017
Kumar 2016 India Asian 213 213 35 86 92 156 270 24 77 112 125 301 0.061
Singh 2018 India Asian 155 150 86 59 10 231 79 29 74 47 132 168 0.989
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HWE, Hardy Weinberg Equilibrium

Quantitative Data Synthesis

In the overall analysis, statistically significant association between ACE I/D polymorphism and breast cancer susceptibility was observed under the allele model (I vs. D: OR= 0.803, 95% CI 0.647-0.996, p=0.046, Figure 1A), the homozygote model (II vs. DD: OR= 0.662, 95% CI 0.462-0.947, p=0.024), the heterozygote model (ID vs. DD: OR= 0.707, 95% CI 0.528-0.946, p=0.020), the dominant model (II+ID vs. DD: OR= 0.691, 95% CI 0.507-0.941, p=0.019), but not under the recessive model (II vs. ID+DD: OR= 0.841, 95% CI 0.663-1.067, p=0.154, Figure 1B). When stratified, the association between ACE I/D polymorphism and breast cancer risk was observed among Asian populations under the heterozygote model (ID vs. DD: OR= 0.655, 95% CI 0.436-0.984, p=0.041) and Caucasian populations under the allele model (I vs. D: OR= 1.115, 95% CI 1.002-1.241, p=0.046), but not among mixed populations. In the subgroup analysis by studies quality (fulfilling HWE or not), a significant association between the ACE I/D polymorphism and breast cancer risk was observed under the heterozygote model (ID vs. DD: OR= 0.656, 95% CI 0.454-0.946, p=0.024).

Figure 1.

Figure 1

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Forest Plots for Association between ACE I/D Polymorphism and Breast Cancer Risk. A, the allele model (I vs. D) and B, the recessive model (II vs. ID+DD).

Heterogeneity Test

We observed high to extreme heterogeneities under all genetic model including the allele model (I vs. D: I2= 88.84% and PH≤0.001), the homozygote model (II vs. DD: I2= 83.10% and PH≤0.001), the heterozygote model (ID vs. DD: I2= 81.79% and PH≤0.001), the dominant model (II+ID vs. DD: I2= 86.52% and PH≤0.001), and the recessive model (II vs. ID+DD: I2= 74.01% and PH≤0.001, Table 2). In the subgroup analysis by ethnicity, results were similar in the Asians and mixed population. While, in the Caucasians, between study heterogeneity was significantly reduced under the allele model (I vs. D: I2= 51.31% and PH=0.055), the heterozygote model (ID vs. DD: I2= 47.68% and PH=0.075), and the dominant model (II+ID vs. DD: I2= 46.81% and PH=0.080).

Table 2.

Summary Risk Estimates for Association between ACE I/D Polymorphism and Risk of Breast Cancer

Subgroup Genetic Model Type of Model Heterogeneity Odds Ratio (OR) Publication Bias
I2 (%) PH OR 95% CI ZOR POR PBeggs PEggers
Overall I vs. D Random 88.84 ≤0.001 0.803 0.647-0.996 -1.992 0.046 0.035 0.048
II vs. DD Random 83.10 ≤0.001 0.662 0.462-0.947 -2.256 0.024 0.030 0.024
ID vs. DD Random 81.79 ≤0.001 0.707 0.528-0.946 -2.332 0.020 0.528 0.233
II+ID vs. DD Random 86.52 ≤0.001 0.691 0.507-0.941 -2.348 0.019 0.363 0.157
II vs. ID+DD Random 74.01 ≤0.001 0.841 0.663-1.067 -1.427 0.154 0.234 0.048
By Ethnicity Asian I vs. D Random 90.25 ≤0.001 0.735 0.512-1.055 -1.668 0.095 0.710 0.606
II vs. DD Random 86.73 ≤0.001 0.578 0.303-1.103 -1.663 0.096 0.710 0.657
ID vs. DD Random 74.70 ≤0.001 0.655 0.436-0.984 -2.040 0.041 0.265 0.494
II+ID vs. DD Random 84.71 ≤0.001 0.628 0.388-1.015 -1.899 0.058 0.536 0.705
II vs. ID+DD Random 82.10 ≤0.001 0.739 0.483-1.131 -1.394 0.163 0.265 0.513
Caucasian I vs. D Fixed 51.31 0.055 1.115 1.002-1.241 1.992 0.046 0.133 0.232
II vs. DD Random 62.26 0.014 0.913 0.620-1.343 -0.462 0.644 0.367 0.064
ID vs. DD Fixed 47.68 0.075 0.925 0.778-1.099 -0.885 0.376 1.000 0.587
II+ID vs. DD Fixed 46.81 0.080 0.964 0.821-1.132 -0.443 0.658 0.548 0.800
II vs. ID+DD Random 54.24 0.041 1.044 0.772-1.414 0.282 0.778 0.035 0.018
Mixed I vs. D Random 94.34 ≤0.001 0.582 0.262-1.293 -1.329 0.184 0.308 0.299
II vs. DD Random 88.51 ≤0.001 0.562 0.195-1.618 -1.068 0.286 0.734 0.308
ID vs. DD Random 91.16 ≤0.001 0.410 0.107-1.564 -1.306 0.192 0.734 0.330
II+ID vs. DD Random 95.17 ≤0.001 0.450 0.126-1.611 -1.227 0.220 0.734 0.427
II vs. ID+DD Random 68.67 0.023 0.819 0.466-1.439 -0.694 0.488 0.308 0.422
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Sensitivity Analysis

To evaluate the robustness of the association results, a meta-analysis was performed repeatedly with each study removed. The results indicated that the fixed-effect estimates before or after the deletion of any single study were generally similar, suggesting a high stability of the meta-analysis results (data not shown). After excluding studies which not fulfilling HWE the pooled ORs were materially altered under the allele model (I vs. D: OR= 0.814, 95% CI 0.608-1.090, p=0.167), the homozygote model (ID vs. DD: OR= 0.709, 95% CI 0.439-1.147, p=0.161), and the dominant model (II+ID vs. DD: OR= 0.672, 95% CI 00.438-1.029, p=0.064; data not shown). The sensitivity analyses substantially alter the pooled ORs except heterozygote model in overall populations, suggesting that the results of this meta-analysis were generally robust.

Publication bias

Publication bias were qualitatively assessed by Begg’s funnel plot and quantitatively assessed by Egger’s test. A significant publication bias was detected by Egger’s test under the allele model (PBeggs= 0.035, PEggers=0.048, Figure 2), the homozygote model (PBeggs= 0.030, PEggers=0.024) and the recessive model (PBeggs= 0.234, PEggers=0.048). In the stratified analysis by ethnicity, still obvious publication bias were found among Caucasians under the recessive model (PBeggs= 0.035, PEggers=0.018). Thus, we have repeated meta-analysis with the ‘‘trim and fill’’ method to adjust publication bias under the three genetic models. Adjusting these three genetic models by ‘‘trim and fill’’ method did not influence the conclusion, which indicated the robustness our results (data not shown).

Figure 2.

Figure 2

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Begg’s Funnel Plots for the Association between ACE I/D Polymorphism and Breast Cancer under the Allele Model (I vs. D).

Discussion

ACE is well known to be a key part of the RAS that regulates blood pressure through conversion of the angiotensin I to the angiotensin II by removing the two C-terminal amino acids. The ACE I/D polymorphism, the most widely studied polymorphism within ACE gene, which individuals carrying the D allele have higher ACE activity. Rigat et al has initially detected ACE I/D polymorphism by restriction fragment length polymorphism (RFLP) analysis (Rigat et al., 1990). There have been a few meta-analyses focusing on association of ACE I/D polymorphism with breast cancer risk. However, most of these analyses wrongly not included all published studies and a new meta-analysis is needed to give a comprehensive conclusion due to the increasing data of case-control studies.

This present meta-analysis, including 2846 breast cancer cases and 9,299 controls from 20 case-control studies, explored the association between the ACE I/D polymorphism and breast cancer risk. This is the largest scale meta-analysis so far. Our results suggested that the ACE I/D polymorphism was significantly associated with increased risk of breast cancer. To further elucidate the association between the ACE I/D and the risk of breast cancer, we have performed subgroup analysis. In subgroup analysis by ethnicity, we found a marginal association of ACE I/D and breast cancer among Asian populations under the heterozygote model (ID vs. DD: OR= 0.655, 95% CI 0.436-0.984, p=0.041) and Caucasian populations under the allele model (I vs. D: OR= 1.115, 95% CI 1.002-1.241, p=0.046), but not among mixed populations. The inconsistency of genetic effects across the ethnicities was detected for breast cancer, and it showed that Asian populations had a greater genetic risk in developing depression on account of genetic variation in this locus than White populations. Results of this meta-analysis indicated that there was a significant association of ACE I/D polymorphism with increased risk of breast cancer. The present meta-analysis results are inconsistent with all previous the meta-analysis (Li et al., 2015; Pei and Li, 2012; Xi et al., 2011; Zhang et al., 2011). The inconsistent results between ours and previous meta-analyses might mainly be due to relevant smaller sample size from previous meta-analyses. Furthermore, most studies included in the present meta-analysis performed among Asians, while previous meta-analyses only had very limited Asian populations.

The great discrepancy among different studies indicated the existence of between-studies heterogeneity and it is generally introduced that meta-analyses should assess heterogeneity (Abedinzadeh et al., 2015; Nedooshan et al., 2017). There are several factors responsible for such heterogeneity such as the study designs, ethnicity of cases and controls, genotyping method, sample size, selection criteria and etc., (Mehdinejad et al., 2017; Sobhan et al., 2017). In the present meta-analysis, there was an extreme heterogeneity (I2 = 75% to 100%) under all five genetic models in overall estimations. Thus, we have performed stratified analysis by ethnicity to identify possible sources for the observed heterogeneity. However, after stratified analysis, there were still heterogeneities in Asian and mixed populations.

To our best knowledge, the present meta-analysis is the most comprehensive, latest one and has the largest sample size. Thus, the statistical power of our analyses was noticeably increased as a large sample size pooled from different studies, and has more statistical powerful than any single case-control study and previous meta-analyses. However, the conclusions of this meta-analysis should be interpreted cautiously due to some limitations. First, the number of published studies was not sufficiently large for stratified analyses by ethnicity. Because of limited available data for mixed population and Africans, our results should be interpreted with caution. Therefore, larger studies are required to explore the association ACE I/D polymorphism with susceptibility to the breast cancer in different ethnicities, especially among mixed population and Africans. Second, there was a significant between study heterogeneity under all five genetic models in overall estimations. One possible reason for such heterogeneity is a wide variation in various included ethnicities. Therefore, we have performed subgroup analysis by ethnicity to eliminate heterogeneity. However, the results showed that the heterogeneity did not reduced or disappeared significantly. Third, there was a significant publication bias under three genetic models which could influence the results of our meta-analysis. However, adjusting pooled ORs for these genetic models by ‘‘trim and fill’’ method did not influence the conclusion, which indicated the robustness our results. Forth, we included only published studies, so there was space for publication bias, which in fact was confirmed by formal statistical tests. Finally, lacking the original data for the included studies limited our further evaluation of potential interactions among gene–gene, gene–environment, or even different polymorphism loci of the ACE gene.

In summary, the present meta-analysis suggested that suggest that the ACE I/D polymorphism is significantly associated with risk of breast cancer. Considering the limited sample size among different ethnicities included in the present meta-analysis, further well-designed and unbiased studies with larger sample studies are needed to confirm our results.

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