G) polymorphisms and endometriosis risk: A meta-analysis

Gene 508 (2012) 41–48

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Gene journal homepage: www.elsevier.com/locate/gene

Estrogen receptor-alpha gene PvuII (T/C) and XbaI (A/G) polymorphisms and endometriosis risk: A meta-analysis Ya Li a, 1, Fei Liu b, 1, Shi-Qiao Tan c, Yan Wang a, Shang-Wei Li a,⁎ a

Division of Reproductive Medical Center, West China Second University Hospital of Sichuan University, 3 Duan 20 Hao Ren Min Nan Lu, City of Chengdu, Sichuan 610041, China Department of liver and vascular surgery, West China Hospital of Sichuan University, 37 Guo Xue Road, Chengdu 610041, Sichuan Province, China Division of Reproductive Endocrinology and Infertility, West China Second University Hospital of Sichuan University, 3 Duan 20 Hao Ren Min Nan Lu, City of Chengdu, Sichuan 610041, China

b c

a r t i c l e

i n f o

Article history: Accepted 30 July 2012 Available online 4 August 2012 Keywords: Endometriosis Polymorphism ER-α Meta-analysis

a b s t r a c t Estrogen receptor-alpha (ER-α) polymorphisms have been hypothesized to be associated with the risk of endometriosis (EMT) development by many epidemiological studies, however, the available results were conflicting. To derive a more precise estimation of association between the ER-α PvuII (T/C) and XbaI (A/G) polymorphisms and risk of EMT, we performed a meta-analysis. Summary odds ratios (ORs) and 95% confidence intervals (95% CIs) for ER-α polymorphisms and EMT were calculated in a fixed-effects model and a random-effects model when appropriate. This meta-analysis included 20 case–control studies with 1752 cases and 1742 controls for PvuII polymorphism and 15 case–control studies with 1349 cases and 1411 controls for XbaI polymorphism. For PvuII T/C polymorphism, no obvious associations were found for all genetic models when all studies were pooled into the meta-analysis. In the subgroup analyses by ethnicity, country, HWE in controls and study sample size, a significantly increased risk was observed among Caucasians (recessive model, OR=2.56, 95% CI=1.06–6.16) and among studies without the HWE (recessive model, OR=1.85, 95% CI=1.20–2.84). For XbaI A/G polymorphism, also no obvious associations were found for all genetic models. In the subgroup analyses by ethnicity, country, HWE in controls and study sample size, still no obvious associations were found. No publication bias was found in the present study. This meta-analysis suggests that ER-α gene PvuII (T/C) and XbaI (A/G) polymorphisms may not be associated with EMT risk, while the observed increase in risk of EMT may be due to small-study bias. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Endometriosis (EMT) is an estrogen-dependent disorder observed in 5–10% of women of reproductive age (Giudice and Kao, 2004) and in 20–50% of women with infertility (Gao et al., 2006). Pain, including dysmenorrhea, deep dyspareunia, and chronic pelvic pain, as well as infertility are associated with endometriosis (Medicine PCotASfR, 2004). Family studies of endometriosis indicate that close relatives of patients with endometriosis have an increased risk for the disease, suggesting that genetic components perhaps contribute to endometriosis (Kennedy, 1997, 1999; Simpson et al., 1980), but the exact etiology and pathogenesis of endometriosis are still unclear (Lin et al., 2003).

Abbreviations: EMT, endometriosis; ER-α, estrogen receptor-alpha; OR, odds ratio; CI, confidence interval; SNP, single nucleotide polymorphisms; HWE, Hardy–Weinberg equilibrium. ⁎ Corresponding author. Tel./fax: +86 28 85503217. E-mail address: [email protected] (S.-W. Li). 1 Ya Li and Fei Liu have the same contributions to this study and should be considered as co-first author. 0378-1119/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.gene.2012.07.049

The estrogen receptors (ER) are nuclear receptors existing in two isoforms, ER‐α and ER‐β (Kuiper et al., 1996), exhibiting an estrogen(E)-binding domain and a DNA-binding domain. ER-α displays a higher affinity for E and is the predominant form in normal endometrium. Because large amounts of ER‐β messenger ribo-nucleic acid (mRNA) are found in ovaries and granulosa cells, ER‐β is likely to have a role in ovulatory function (Kuiper et al., 1996). After binding to ligands, these receptors act as transcriptional factors that up-regulate or down-regulate gene expression by interacting with regulatory regions of target genes. Since the discovery that allelic variants of the genes encoding for ER are associated with altered expression of sex steroid-responsive systems, the polymorphisms of these genes have been postulated as candidate risk markers for a number of female pathologies (Hsieh et al., 2007; Wieser et al., 2002). The ER‐α gene located on chromosome 6q25 has 8 exons and spans over more than 140-kilo bases. The PvuII and XbaI polymorphisms of ER‐α gene are situated in intron 1 and their effects could be the result of high linkage disequilibrium with functional variants that affect sensitivity to estrogen (Yaich et al., 1992). Associations between ER-α gene polymorphisms and breast cancer, decreased bone mineral density (BMD), and Parkinson's disease have been identified (Hill et al., 1989; Isoe-Wada et al., 1999; Kobayashi et al., 1996).

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Y. Li et al. / Gene 508 (2012) 41–48

Over the last two decades, a number of case–control studies (Chen et al., 2011; Ding et al., 2005; Dong et al., 2005; Fu et al., 2001, 2002; Georgiou et al., 1999; Govindan et al., 2009; Hsieh et al., 2007; Huang et al., 2005; Kim et al., 2005; Kitawaki et al., 2001; Li and Xie, 2010; Luisi et al., 2006; Renner et al., 2006; Shan et al., 2006; Song et al., 2005; Sun et al., 2010; Wang et al., 2004; Xie et al., 2009; Zhang et al., 2007) were conducted to investigate the association between ER-α PvuII and XbaI polymorphisms and EMT risk in humans. But these studies reported conflicting results. In 2005, (Guo, 2005) published findings from a meta-analysis (based on 287 cases and 256 controls from 3 studies) of the ER-α PvuII T/C polymorphism and EMT risk. He found that ER-α PvuII T/C polymorphism was associated with an increased EMT risk (OR = 2.1, 95% CI = 1.20,3.68). However, Guo's study had some limitations, such as relatively small sample size, only Caucasian populations were included, and only one single nucleotide polymorphism (SNP) locus (ER-α PvuII) was analyzed. In order to derive a more comprehensive estimation of the associations between ER-α gene polymorphisms and EMT risk, we conducted a meta-analysis to assess the association between ER-α PvuII (T/C) and XbaI (A/G) polymorphisms and EMT susceptibility. 2. Material and methods 2.1. Publication search PubMed, EMBASE, CNKI (China National Knowledge Infrastructure) and Chinese Biomedicine databases were searched (the last search was updated in May 2011) using the search terms: ‘estrogen receptor-alpha’, ‘PvuII’ or ‘XbaI’, ‘polymorphism’ or ‘mutation’ or ‘variant’, and ‘endometriosis’ or ‘adenomyosis’ or ‘mulleriosis’. All published papers in English language and Chinese language with available full text matching the eligible criteria were retrieved. In addition, we also checked the references of relevant reviews and eligible articles that our search retrieved. If more than one article was published by the same author using the same case series, we selected the study where the most individuals were investigated.

2.4. Statistical analysis We first assessed HWE in the controls for each study using goodness-of-fit test (chi-square or Fisher's exact test) and a P b 0.05 was considered as significant disequilibrium. The strength of the association between EMT and the ER-α PvuII (T/C) and XbaI (A/G) polymorphisms was estimated using ORs, with the corresponding 95% CIs. For ER-α PvuII (T/C) polymorphism, we first examined the risk of the variant genotypes CC or CT on EMT compared with the wild-type TT homozygote. Then, the risk of (CC + CT) vs. TT and CC vs. (CT + TT) for EMT was evaluated in dominant and recessive models. For ER-α XbaI (A/G) polymorphism, we evaluated the risk of the variant genotypes GG or AG on EMT compared with the wild-type AA homozygote. Then, the risk of (GG + AG) vs. AA and GG vs. (AG + AA) for EMT was evaluated in dominant and recessive models. We also carried out the stratified analyses by ethnicity, country, HWE in controls and study sample size. Both the Cochran's Q statistic (Cochran, 1954) to test for heterogeneity and the I2 statistic to quantify the proportion of the total variation due to heterogeneity (Higgins et al., 2003) were calculated. A P value of more than the nominal level of 0.10 for the Q statistic indicated a lack of heterogeneity across studies, allowing for the use of a fixed-effects model (the Mantel–Haenszel method) (Mantel and Haenszel, 1959); otherwise, the random-effects model (the DerSimonian and Laird method) was used (DerSimonian and Laird, 1986). To explore sources of heterogeneity across studies, we did logistic meta-regression analyses. We examined the following study characteristics: ethnicity, country, HWE in controls (yes/no), genotyping methods and study sample size (≤200 and >200 subjects). Sensitivity analysis was performed to assess the stability of results. Several methods were used to assess the potential publication bias. Visual inspection of funnel plot asymmetry was conducted. The Begg's rank correlation method (Begg and Mazumdar, 1994) and the Egger's weighted regression method (Egger et al., 1997) were used to statistically assess publication bias (P b 0.05 was considered statistically significant). All statistical analyses were performed with the Stata software (version 11.0; STATA Corp., College Station, TX, USA) using two-sided P values.

2.2. Inclusion and exclusion criteria

3. Results

For inclusion in this meta-analysis, the identified articles had to provide information on the following: (i) ER-α PvuII (T/C) or XbaI (A/G) polymorphisms and EMT risk, (ii) using a case–control design and (iii) sufficient data for examining an odds ratio (OR) with 95% confidence interval (CI); (iv) the most recent and/or the largest study with extractable data should be included concerning studies with overlapping patients and the controls. Major reasons for the exclusion of studies were as follows: (i) no control cases; (ii) no usable data reported; (iii) duplicates.

3.1. Characteristics of studies

2.3. Data extraction Two investigators (Ya Li and Fei Liu) extracted information from all eligible publications independently according to the inclusion criteria listed above. Disagreements were resolved by discussion between the two investigators. If the two authors could not reach a consensus, then a third investigator (Shang-Wei Li) was consulted to resolve the dispute and a final decision was made by the majority of the votes. The following characteristics were collected from each study: first author, year of publication, country/region of the first or corresponding author, ethnicity, number of cases and controls, genotyping methods, minor allele frequency (MAF) in controls, and evidence of Hardy– Weinberg equilibrium (HWE). Different ethnicities were categorized as Asian, Caucasian. If original genotype frequency data were unavailable in relevant articles, a request was sent to the corresponding author for additional data.

20 studies (nine in English Georgiou et al., 1999; Govindan et al., 2009; Hsieh et al., 2007; Kim et al., 2005; Kitawaki et al., 2001; Luisi et al., 2006; Renner et al., 2006; Wang et al., 2004; Xie et al., 2009) and eleven (Chen et al., 2011; Ding et al., 2005; Dong et al., 2005; Fu et al., 2001, 2002; Huang et al., 2005; Li and Xie, 2010; Shan et al., 2006; Song et al., 2005; Sun et al., 2010; Zhang et al., 2007) in Chinese) were included based on the search criteria for EMT susceptibility related to the ER-α gene PvuII (T/C) and XbaI (A/G) polymorphisms. The literature search and study selection procedures are shown in Fig. 1. Study characteristics were summarized in Tables 1 and 2. There were seventeen studies of subjects of Asian descent and three studies of subjects of Caucasian descent. Among these studies, five studies have investigated only PvuII (T/C) polymorphism, whereas fifteen studies included PvuII (T/C) and XbaI (A/G) polymorphisms. Therefore, there were 20 studies with 1752 cases and 1742 controls concerning the PvuII (T/C) polymorphism, and 15 studies with 1349 cases and 1411 controls concerning the XbaI (A/G) polymorphism. Studies had been carried out in China, Japan, Korea, India, Germany, Italy and Greece. 18/20 studies extracted DNA from peripheral blood and a classic PCR-RFLP assay was used in 16 out of 20 studies. Only 3/20 (9%) studies described the use of positive controls and a different genotyping assay to confirm the data. The genotype distributions among the controls of all studies were consistent with HWE except for four studies (Govindan et al., 2009; Hsieh et al., 2007; Renner et al., 2006; Xie et al., 2009).

Identification

Y. Li et al. / Gene 508 (2012) 41–48

Records identified through database searching (n = 141)

43

Additional records identified through other sources (n = 57)

Screening

Records after duplicates removed (n = 141)

Records screened (n = 141 )

Records excluded (n = 107)

Eligibility

Full-text articles assessed for eligibility (n = 34)

Full-text articles excluded, with reasons (n = 14) Not about ER-α n=2 Not about endometriosis n=3 Review n=6 Not about gene polymorphism n=1 Abstract only n=1 Not randomized n=1

Included

Studies included in qualitative synthesis (n = 20)

Studies included in quantitative synthesis (meta-analysis) (n = 20)

Fig. 1. Flow chart of study selection based on the inclusion and exclusion criteria.

3.2. Quantitative synthesis Tables 3 and 4 listed the main results of this meta-analysis. For the PvuII (T/C) polymorphism, no obvious associations were found when

all studies were pooled into the meta-analysis (CC vs. TT: OR = 1.49, 95% CI 0.95–2.35, Q = 75.99, I2 = 75.0%, Pheterogeneity b 0.001; CT vs. TT: OR= 1.29, 95% CI 0.93–1.77, Q = 70.19, I 2 = 72.9%, Pheterogeneity b 0.001; dominant model: OR = 1.34, 95% CI 0.96–1.87, Q = 86.83, I2 = 78.1%,

Table 1 Characteristics of Pvu II studies included in the meta-analysis. First author Reference

Year

Georgiou (15) Kitawaki (16) Fu (23) Fu (24) Wang (17) Dong (27) Kim (18) Huang (25) Song (26) Ding (28) Renner (20) Luisi (19) Shan (29) Hsieh (10) Zhang (30) Xie (22) Govindan (21) Sun (31) Li (32) Chen (33)

1999 2001 2001 2002 2004 2005 2005 2005 2005 2005 2006 2006 2006 2007 2007 2009 2009 2010 2010 2011

Country

Greece Japan China China Japan China Korea China China China Germany Italy China China China China India China China China

Ethnicity

Caucasian Asian Asian Asian Asian Asian Asian Asian Asian Asian Caucasian Caucasian Asian Asian Asian Asian Asian Asian Asian Asian

No. of case

57 109 50 63 121 65 180 85 49 85 98 13 40 112 78 214 110 60 107 56

No. of control

57 27 50 41 172 107 165 90 50 105 98 48 52 110 81 160 115 56 80 78

Abbreviations: MAF, minor allele frequency; HWE, Hardy–Weinberg equilibrium.

Control (genotype)

MAF

HWE

T/T

Case (genotype) T/C

C/C

T/T

T/C

C/C

in control

in control

2 36 22 25 48 42 73 23 19 29 58 0 16 27 31 62 5 18 31 25

28 59 22 26 49 16 84 49 21 49 20 6 15 68 32 122 32 33 61 21

27 14 6 12 24 7 23 13 9 7 20 7 9 17 15 30 73 9 15 10

16 3 17 27 47 46 66 42 16 40 53 15 19 60 48 64 29 22 32 31

26 12 23 11 88 49 67 39 22 53 29 27 24 44 29 76 32 23 38 38

15 12 10 3 37 12 32 9 12 12 16 6 9 6 4 20 54 11 10 9

0.49 0.33 0.43 0.21 0.47 0.34 0.4 0.32 0.46 0.37 0.31 0.41 0.40 0.25 0.23 0.36 0.61 0.40 0.36 0.36

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes No Yes Yes Yes

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Table 2 Characteristics of Xba I studies included in the meta-analysis. First author Reference

Year

Fu (24) Wang (17) Dong (27) Kim (18) Huang (25) Song (26) Ding (28) Renner (20) Luisi (19) Shan (29) Hsieh (10) Xie (22) Sun (31) Li (32) Chen (33)

2002 2004 2005 2005 2005 2005 2005 2006 2006 2006 2007 2009 2010 2010 2011

Country

China Japan China Korea China China China Germany Italy China China China China China China

Ethnicity

Asian Asian Asian Asian Asian Asian Asian Caucasian Caucasian Asian Asian Asian Asian Asian Asian

No. of case

63 122 65 180 85 49 85 98 13 40 112 214 60 107 56

No. of control

Case (genotype)

41 171 107 165 90 50 105 98 48 52 110 160 56 80 78

Control (genotype)

MAF

HWE

A/A

A/G

G/G

A/A

A/G

G/G

in control

in control

30 78 41 125 42 27 51 62 1 19 30 112 41 56 36

24 38 19 50 38 17 31 25 6 18 64 92 18 46 18

9 6 5 5 5 5 3 11 6 3 18 10 1 5 2

24 103 76 112 50 21 53 60 22 29 37 110 34 55 44

14 56 26 45 36 25 44 26 22 18 71 40 21 20 32

3 12 5 8 4 4 8 12 4 5 2 10 1 5 2

0.24 0.23 0.17 0.18 0.24 0.33 0.29 0.26 0.31 0.27 0.35 0.19 0.21 0.19 0.23

Yes Yes Yes Yes Yes Yes Yes No Yes Yes No No Yes Yes Yes

Abbreviations: MAF, minor allele frequency; HWE, Hardy–Weinberg equilibrium.

Pheterogeneity b 0.001; and recessive model: OR = 1.25, 95% CI 0.90–1.73, Q = 54.38, I2 = 65.1%, Pheterogeneity b 0.001) (Figs. 2A–D). When stratifying by country and study sample size,still no obvious associations were found. However, in the subgroup analysis by ethnicity, a significantly increased risk was observed among Caucasian (recessive model, OR= 2.56, 95% CI= 1.06–6.16, Q = 5.49, I 2 = 63.5%, Pheterogeneity = 0.064). Moreover, when stratifying by HWE in control, a significantly elevated risk was found among studies with controls deviated from HWE (recessive model, OR= 1.85, 95% CI= 1.20–2.84, Q = 1.31, I2 = 23.6%, Pheterogeneity = 0.25). For the XbaI (A/G) polymorphism, also no obvious associations were found when all studies were pooled into the meta-analysis (GG vs. AA: OR = 1.23, 95% CI 0.78–1.94, Q = 23.74, I2 = 41.0%, Pheterogeneity = 0.049; AG vs. AA: OR= 1.13, 95% CI 0.89–1.43, Q = 26.30, I2 = 46.8%, Pheterogeneity = 0.024; dominant model: OR=1.13, 95% CI 0.90–1.43, Q = 27.43, I2 = 49.0%, Pheterogeneity = 0.017; and recessive model: OR = 1.20, 95% CI 0.78–1.87, Q = 23.86, I2 = 41.3%, Pheterogeneity = 0.048) (Figs. 3A–D). In the subgroup analysis by ethnicity, country, HWE in controls and study sample size, still no obvious associations were found.

3.3. Heterogeneity analysis There was heterogeneity among studies in overall comparisons and also subgroup analyses. To explore sources of heterogeneity across studies, we assessed all of the comparison models by ethnicity (Asian or Caucasian), country (China or other), HWE in controls (yes or not), and study sample size (≤200 subjects or >200 subjects). However, none of these variables could explain the heterogeneity (P > 0.05).

3.4. Sensitivity analysis In the sensitivity analysis, the influence of each study on the pooled OR was examined by repeating the meta-analysis while omitting each study, one at a time. This procedure proved that our results were reliable and robust. In addition, when excluding the studies that were not in HWE, the estimated pooled OR still did not change at all (Tables 3 and 4).

Table 3 Stratified analyses of the ER-α Pvu II T/C polymorphism on endometriosis risk. Variables

Na

CC vs. TT

CT vs. TT

Dominant model

Recessive model

OR (95% CI)

Pb

OR (95% CI)

Pb

OR (95% CI)

Pb

OR (95% CI)

Pb

Total

20

1.49 (0.95,2.35)

b0.001

1.29 (0.93,1.77)

b0.001

1.34 (0.96,1.87)

b0.001

1.25 (0.90,1.73)

b0.001

Ethnicity Asian Caucasian

17 3

1.30 (0.81,2.07) 6.43 (0.66,62.29)

b0.001 b0.001

1.25 (0.90,1.73) 2.81 (0.33,23.73)

b0.001 b0.001

1.26 (0.90,1.78) 3.89 (0.43,35.0)

b0.001 b0.001

1.11 (0.79,1.55) 2.56 (1.06,6.16)

b0.001 0.064

Country China Other

13 7

1.51 (0.98,2.32) 1.61 (0.56,4.62)

0.008 b0.001

1.31 (0.93,1.85) 1.35 (0.65,2.80)

b0.001 b0.001

1.35 (0.95,1.92) 1.44 (0.67,3.11)

b0.001 b0.001

1.29 (1.00,1.66) 1.22 (0.62,2.40)

0.145 b0.001

HWEc in controls Yes 18 No 2

1.37 (0.86,2.20) 2.90 (0.43,19.43)

b0.001 b0.001

1.25(0.91,1.73) 1.84 (0.21,16.34)

b0.001 b0.001

1.28(0.91,1.79) 2.31 (0.27,19.73)

b0.001 b0.001

1.20(0.84,1.71) 1.85 (1.20,2.84)

b0.001 0.253

Sample size >200 ≤200

1.86 (0.72,4.81) 1.37 (0.80,2.34)

b0.001 b0.001

1.70 (0.86,3.36) 1.15 (0.80,1.66)

b0.001 b0.001

1.77 (0.85,3.68) 1.21 (0.83,1.75)

b0.001 b0.001

1.28 (0.74,2.20) 1.24 (0.81,1.90)

0.005 b0.001

a b c

5 15

Number of comparisons. P value of Q-test for heterogeneity test. Random-effects model was used when P value for heterogeneity test b0.1; otherwise, fixed-effects model was used. HWE, Hardy–Weinberg equilibrium.

Y. Li et al. / Gene 508 (2012) 41–48

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Table 4 Stratified analyses of the ER-α Xba I A/G polymorphism on endometriosis risk. Variables

Na

GG vs. AA

AG vs. AA

Dominant model

Recessive model

OR (95% CI)

Pb

OR (95% CI)

Pb

OR (95% CI)

Pb

OR (95% CI)

Pb

Total

15

1.23 (0.78,1.94)

0.049

1.13 (0.89,1.43)

0.024

1.13 (0.90,1.43)

0.017

1.20 (0.78,1.87)

0.048

Ethnicity Asian Caucasian

13 2

1.18 (0.84,1.67) 4.56 (0.13,160.31)

0.215 0.005

1.13 (0.88,1.44) 1.15 (0.63,2.12)

0.022 0.108

1.13 (0.89,1.42) 2.46 (0.23,26.34)

0.030 0.028

1.14 (0.81,1.60) 2.69 (0.27,26.62)

0.204 0.008

Country China Other

11 4

1.42 (0.96,2.10) 1.19 (0.39,3.61)

0.247 0.018

1.17 (0.86,1.58) 0.99 (0.74,1.34)

0.016 0.428

1.19 (0.90,1.56) 0.98 (0.74,1.29)

0.032 0.165

1.34 (0.91,1.97) 1.20 (0.43,3.31)

0.196 0.017

HWEc in controls Yes 12 No 3

1.10 (0.74,1.61) 1.84 (0.50,6.79)

0.207 0.012

1.05 (0.87,1.27) 1.38 (0.78,2.43)

0.126 0.046

1.05 (0.82,1.36) 1.41 (0.89,2.23)

0.067 0.100

1.07 (0.73,1.57) 1.67 (0.42,6.57)

0.234 0.006

Sample size >200 ≤200

1.26 (0.42,3.79) 1.25 (0.83,1.87)

0.010 0.262

1.24 (0.80,1.92) 1.07 (0.80,1.44)

0.027 0.096

1.22 (0.81,1.84) 1.09 (0.82,1.46)

0.032 0.056

1.18 (0.39,3.59) 1.21 (0.81,1.80)

0.007 0.305

a b c

4 11

Number of comparisons. P value of Q-test for heterogeneity test. Random-effects model was used when P value for heterogeneity test b0.1; otherwise, fixed-effects model was used. HWE, Hardy–Weinberg equilibrium.

3.5. Publication bias Begg's Funnel plot and Egger's test were performed to evaluate publication bias of the literature on EMT. Figs. 4 and 5 displayed funnel plots that examined the ER-α PvuII T/C, Xba I A/G polymorphisms and overall EMT risk included in the meta-analysis in the recessive model. The shape of funnel plots did not reveal any evidence of funnel plot asymmetry. The statistical results still did not show publication bias (for ER PvuII polymorphism: CC vs. TT: Begg's test P = 0.46, Egger's test P = 0.11; CT vs. TT: Begg's test P = 0.82, Egger's test P = 0.55; dominant model: Begg's test P = 0.54, Egger's test P = 0.35; recessive model: Begg's test P = 0.42, Egger's test P = 0.48; for ER Xba I polymorphism: GG vs. AA: Begg's test P = 0.08, Egger's test P = 0.08; AG vs. AA: Begg's test P = 0.92, Egger's test P = 0.96; dominant model: Begg's test P = 0.84, Egger's test P = 0.70; recessive model: Begg's test P = 0.14, Egger's test P = 0.17). 4. Discussion In the present study, to clarify controversial results from previous reports, we identified all available studies and performed a metaanalysis to examine the association between the ER-α PvuII (T/C) and XbaI (A/G) polymorphisms and EMT risk. To the best of our knowledge, this is the first meta-analysis of the assessment for the relationship between both the two ER-α gene polymorphisms and the risk of EMT (although previous meta-analysis Luisi et al. (2006) assessed the association between only ER-α PvuII (T/C) polymorphism and EMT risk). Twenty studies on the PvuII (T/C) (3494 subjects) and fifteen studies on the XbaI (A/G) genotype (2760 subjects) were critically reviewed. For PvuII (T/C) polymorphism, obvious associations were found among Caucasians and among studies without the HWE in the recessive model. For XbaI (A/G) polymorphisms, no obvious associations were found for all genetic models. The significant association was mainly observed among studies (Caucasian population) with small sample size and studies without HWE, so the ER-α gene PvuII (T/C), XbaI (A/G) polymorphisms may be not associated with EMT risk, while the observed increase in risk of EMT may be due to small-study bias. Both circumstantial and laboratory evidence indicate a critical role for estrogen in the growth of endometriotic tissues (Dizerega et al., 1980), although the exact molecular mechanisms for the development of endometriosis are unclear. While the ER-α displays a higher affinity for estrogen and is the predominant form in normal

endometrium, which suggests that ER-α may play a role in EMT. The human ER-α gene is localized on chromosome 6q25, it extends more than 140 kb and includes eight exons (Ponglikitmongkol et al., 1988). The most studied variants in this gene are the PvuII (T/C) and XbaI (A/G) polymorphisms in intron 1, 397 and 351 bp upstream of exon 2 respectively (Andersen et al., 1994; Castagnoli et al., 1987). These variants have been implicated in gene expression by influencing transcription (Cai et al., 2003). Associations between ER-α gene polymorphisms and breast cancer, decreased bone mineral density (BMD), and Parkinson's disease have been identified (Hill et al., 1989; Isoe-Wada et al., 1999; Kobayashi et al., 1996). To date, a number of studies have investigated the association between ER-α gene polymorphisms and EMT risk, and most of them have focused on the PvuII (T/C) and XbaI (A/G) polymorphisms. However, some of the results were conflicting, even in the same population, and thus a systematic review and meta-analysis of association between ER-α gene polymorphisms and EMT risk was of great value. For the PvuII (T/C) polymorphism, no obvious associations were found for all genetic models when all studies were pooled into the meta-analysis. When subgroup analyses were performed, obvious associations were found among Caucasians and among studies without the HWE in the recessive model. Although the pooled OR suggested evidence of an increase in the risk of EMT among Caucasians, the robustness of this summary estimate is uncertain. First, our study found a null association of the ER-α PvuII (T/C) variant with EMT in the overall analysis. Moreover, there was no substantial evidence of a positive effect in the subgroups by country and study sample size. Second, the significant association was mainly observed among studies with small sample size and studies without HWE. Furthermore, since only the published literature was included, it is possible that including unpublished studies (which more often provide evidence of negative or null effects) would have provided additional evidence of small-study bias. Taken together, these findings point to small-study bias as a potential explanation for the results observed in the meta-analysis. Small-study bias in genetic association studies was not new in the field of meta-analysis and systematic review. For example, Serrano et al. (2006) published a meta-analysis to assess the association between angiotensin-converting enzyme (ACE) I/D polymorphism and preeclampsia risk in 2006. They found that the observed small nominal increase in risk of preeclampsia associated with the ACE D-allele is due to small-study bias, similar to that observed in cardiovascular disease. This meta-analysis, to the best of our knowledge, investigated the association between ER-α XbaI (A/G) polymorphisms and risk of EMT

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Fig. 2. Forest plots of ORs with 95% CIs for ER-α PvuII T/C polymorphism and risk for EMT. The center of each square represents the OR, the area of the square is the number of sample and thus the weight used in the meta-analysis, and the horizontal line indicates the 95% CI. (A) CC vs. TT; (B) CT vs. TT; (C) CC + CT vs. TT; (D) CC vs. CT + TT.

for the first time. We found 15 studies that had examined the association between ER-α XbaI (A/G) polymorphism and EMT risk. The pooled result showed that no obvious associations were found for all genetic models. In the subgroup analyses by ethnicity, country, HWE in controls and study sample size, still no obvious associations were found. Our results were consistent with previous meta-analyses based on other diseases. For example, previous two meta-analyses had confirmed XbaI (A/G) polymorphism was not associated with risk of breast cancer (Li et al., 2010) and hand osteoarthritis (Wise et al., 2009). It seemed that selection bias could have played a role because the genotype distribution among control subjects disobeyed the law of HWE in 2 studies (Govindan et al., 2009; Renner et al., 2006) for PvuII (T/C) polymorphism and 3 studies (Hsieh et al., 2007; Renner et al., 2006; Xie et al., 2009) for XbaI (A/G) polymorphism. It is widely believed that deviation from HWE may be due to genetic reasons including non-random mating, or the alleles reflect recent mutations that have not reached equilibrium, as well as methodological reasons including biased selection of subjects from the population or genotyping errors (Hosking et al., 2004; Mitchell

et al., 2003). Despite the reasons of disequilibrium, the results of genetic association studies might be spurious if the distribution of genotypes in the control groups was not in HWE (Salanti et al., 2005; Trikalinos et al., 2006). When excluding the studies that were not in HWE, the estimated pooled OR still did not change at all, suggesting that this factor probably had little effect on the overall estimates. Obvious heterogeneity between studies was observed in overall comparisons and also some subgroup analyses, and then metaregression analysis was used to explore sources of heterogeneity. Unfortunately, possible sources of heterogeneity, such as ethnicity, country, HWE in controls, genotyping methods and study sample size did not demonstrate the evidence of any significant variation by metaregression. It is possible that other limitations of recruited studies may partially contribute to the observed heterogeneity. Another important issue for any meta-analysis is publication bias due to selective publication of reports. In the current study, Begg's funnel plot and Egger's test were performed to evaluate this problem. Both the shape of funnel plots and statistical results did not show publication bias. It is worth

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Fig. 3. Forest plots of ORs with 95% CIs for ER-α XbaI A/G polymorphism and risk for EMT. The center of each square represents the OR, the area of the square is the number of sample and thus the weight used in the meta-analysis, and the horizontal line indicates the 95% CI. (A) GG vs. AA; (B) AG vs. AA; (C) GG + AG vs. AA; (D) GG vs. AG + AA.

mentioning that the results held when the sensitivity analysis was performed, which implied that the results were reliable. However, there are still some limitations in this meta-analysis. First, the number of studies and the number of subjects in the studies included in the meta-analysis by specific subgroups were small. Therefore, more studies with larger sample size and providing more detail information are needed. Second, our meta-analysis was based on unadjusted OR estimates because not all published studies presented adjusted ORs, or when they did, the ORs were not adjusted by the same potential confounders, such as age, ethnicity and exposures. Lack of information for the data analysis might cause serious confounding bias. Third, there was significant between-study heterogeneity from studies of the ER-α polymorphisms, and the genotype distribution also showed deviation from HWE in some studies. In spite of these, our meta-analysis also had some advantages. First, perfect searching strategy based on computer-assisted and manual search allowed the eligible studies to be included as possible as it can. Second, the quality of case–control studies included in the current meta-analysis was satisfactory and met our inclusion criterion. In addition, the method of this meta-analysis was well designed before initiating, by using explicit methods for study selection, data extraction, and data analysis.

Fig. 4. For ER-α PvuII T/C polymorphism, Begg's funnel plot for publication bias test. (CC vs. CT + TT). Each point represents a separate study for the indicated association. LogOR, natural logarithm of OR. Horizontal line, mean effect size.

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Fig. 5. For ER-α XbaI A/G polymorphism, Begg's funnel plot for publication bias test. (GG vs. AG + AA). Each point represents a separate study for the indicated association. LogOR, natural logarithm of OR. Horizontal line, mean effect size.

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