METABOLIC SYNDROME AND RELATED DISORDERS Volume 12, Number 4, 2014 Mary Ann Liebert, Inc. Pp. 210–219 DOI: 10.1089/met.2014.0004
Relationships Between TCF7L2 Genetic Polymorphisms and Polycystic Ovary Syndrome Risk: A Meta-Analysis Wen-Jing Shen, MD,1 Tian-Ren Li, MD,1 Yan-Jie Hu, MD,1 Hong-Bo Liu, MD 2 and Min Song, MD 3
Abstract
Objective: This meta-analysis was performed to evaluate the relationships between genetic polymorphisms in the TCF7L2 gene and polycystic ovary syndrome (PCOS) risk. Methods: The PubMed, Centralised Information Service for Complementary Medicine (CISCOM), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, Google Scholar, EBSCO, Cochrane Library, and Common Biorepository Model (CBM) databases were searched for relevant articles published before November 1st, 2013, without language restrictions. Meta-analysis was conducted using the STATA 12.0 software. The relationships were evaluated by calculating the pooled odds ratios (ORs) and their 95% confidence intervals (CIs). Seven case–control studies with a total 2458 PCOS patients and 5109 healthy subjects’ met our inclusion criteria for qualitative data analysis. Two common polymorphisms (rs7903146 C/T and rs12255372 G/T) in the TCF7L2 gene were assessed. Results: The results of our meta-analysis suggested that TCF7L2 genetic polymorphisms might be strongly correlated with an increased risk of PCOS (allele model, OR = 1.33, 95% CI = 1.15–1.54, P < 0.001; dominant model, OR = 1.40, 95% CI = 1.12–1.75, P = 0.003), especially for the rs7903146 C/T polymorphism. A subgroup analysis was done to investigate the effect of ethnicity on an individual’s risk of PCOS. Our results revealed positive significant correlations between TCF7L2 genetic polymorphisms and an increased risk of PCOS among Caucasians (allele model, OR = 1.26, 95% CI = 1.08–1.47, P = 0.004; dominant model, OR = 1.33, 95% CI = 1.00–1.76, P = 0.046) and Asians (allele model, OR = 2.02, 95% CI = 1.42–2.89, P < 0.001; dominant model, OR = 2.02, 95% CI = 1.40–2.92, P < 0.001), but not among Africans (all P < 0.05). Conclusions: Our findings provide convincing evidence that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS, especially for the rs7903146 C/T polymorphism among Caucasians and Asians.
Introduction
P
olycystic ovary syndrome (PCOS), also known as Stein–Leventhal syndrome, is the most common reproductive endocrinopathy associated with features of metabolic syndrome, including insulin resistance, androgen excess, abdominal obesity, disturbed b-cell function, and type 2 diabetes mellitus (T2DM).1,2 Usually, PCOS is characterized by hyperandrogenism, oligomenorrhea or amenorrhea, and polycystic ovaries; 6–10% women of reproductive age are affected by PCOS.3,4 Generally, PCOS is recognized as a complex multifactorial disorder resulting from the interaction of ge-
netic, environmental, as well as lifestyle influences.5 Although the exact cellular and molecular mechanisms leading to the development of PCOS remain unclear, it is believed that environmental and genetic factors may contribute to increased susceptibility to PCOS.6,7 Transcription factor 7-like 2 (TCF7L2) is one of the four T cell transcription factors that collaborate with free b-catenin to regulate proglucagon expression via the Wnt signaling pathway by repressing the proglucagon gene in enteroendocrine cells.8 It is widely accepted that insulin resistance and its accompanying hyperinsulinemia may play a crucial role in the occurrence and progression of PCOS.9–11 Previous
1
Department of Gynecology, The First Hospital of China Medical University, Shenyang, People’s Republic of China. Department of Health Statistics, School of Public Health, China Medical University, Shenyang, People’s Republic of China. Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University; Institute of Pathology and Pathophysiology, China Medical University, Shenyang, People’s Republic of China. 2 3
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FIG. 1.
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Flow chart of literature search and study selection. Seven case–control studies were included in this meta-analysis.
studies have demonstrated that TCF7L2 might be involved in insulin resistance, b-cell dysfunction, impaired glucose tolerance, dyslipidemia, etc.12–15 Consequently, TCF7L2 has been hypothesized to be involved in the etiology of PCOS by regulating glucose homeostasis.12 Human TCF7L2 gene, located on chromosome 10q25.3, is composed of 17 exons with an overall length of approximately 21.5 kb.16 Genetic variations in the TCF7L2 gene may lead to fat deposition of peripheral tissues and muscles, and thereby increase insulin resistance, which may confer a substantially increased risk for individual’s susceptibility to PCOS.17,18 Many previous studies have demonstrated that TCF7L2 genetic polymorphisms may be implicated in the pathogenesis of PCOS.19,20 Nevertheless, contradictory results have also been reported in many other studies.21,22 Therefore, we performed the present meta-analysis to evaluate the relationships between TCF7L2 genetic polymorphisms and PCOS risk.
Methods Search strategy The PubMed, Centralised Information Service for Complementary Medicine (CISCOM), Cumulative Index to Nur-
FIG. 2.
sing and Allied Health Literature (CINAHL), Web of Science, Google Scholar, EBSCO, Cochrane Library, and Common Biorepository Model (CBM) were searched for relevant articles published before November 1st, 2013, without language restrictions. The following keywords and MeSH terms were used: [‘‘SNP’’ or ‘‘mutation’’ or ‘‘genetic polymorphism’’ or ‘‘variation’’ or ‘‘polymorphism’’ or ‘‘single nucleotide polymorphism’’ or ‘‘variant’’] and [‘‘polycystic ovary syndrome’’ or ‘‘PCOS’’ or ‘‘Stein-Leventhal syndrome’’] and [‘‘transcription factor 7-like 2 ’’ or ‘‘TCF7L2’’ or ‘‘T-cell-specific transcription factor 4’’ or ‘‘T cell factor 4’’]. We also performed a manual search to find other potential articles.
Selection criteria The included studies had to meet all four of the following criteria: (1) The study design must be a clinical cohort or case–control study that focused on the relationships between TCF7L2 genetic polymorphisms with the risk of PCOS; (2) all patients should meet the consensus definition of PCOS specified in the 2003 Rotterdam Conference by European Society for Human Reproduction and Embryology (ESHRE) and American Society for Reproductive Medicine (ASRM) or in the 1990 National Institutes of Health–National Institute
Distribution of the number of topic-related literatures in the electronic database during the last decade.
29.1 – 5.1 26.2 – 7.1 — 26.1 – 4.0 23.9 – 5.2 — 290 148 3657 Asian Caucasian Caucasian Xu et al. Christopoulos et al.19 Barber et al.21
2010 2010 2007
China Greece UK
326 183 909
28.5 – 4.9 28.5 – 4.9 386 377 Asian 2012
Korea
20
Kim et al.
SNP, single nucleotide polymorphism; PCR-RFLP, polymerase chain reaction–restriction fragment length polymorphism; AS-PCR, allele-specific polymerase chain reaction; HWE, Hardy– Weinberg equilibrium; NOS, Newcastle–Ottawa Scale.
7 6 6
7
7 Caucasian 2012
28
Vcelak et al.29
Czech
329
376
27.5 – 6.3
29.9 – 10.8
0.228 0.523 0.139 0.731 0.783 0.443 0.939 0.068 0.346 0.879 rs7903146 C/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs7903146 C/T rs7903146 C/T TaqMan assay AS-PCR AS-PCR TaqMan assay TaqMan assay TaqMan assay TaqMan assay PCR-RFLP AS-PCR AS-PCR 25.2 – 7.6 31.8 – 5.7 Caucasian African 2013 2013 Ramos et al.22 Ben-Salem et al.27
Brazil Tunisia
200 134
102 150
22.8 – 6.6 30.1 – 4.1
HWE test (P value) SNP type Genotyping method Control Case Control Case Ethnicity Country Year Reference
Age (years) Number
Main Characteristics and Methodological Quality of All Eligible Studies Table 1.
7 6
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NOS score
212
of Child Health and Human Development conference23; (3) the study must provide sufficient information about genotype frequencies of TCF7L2 genetic polymorphisms; and (4) the genotype frequencies should follow the Hardy–Weinberg equilibrium (HWE). If the study did not meet the inclusion criteria, it was excluded. The most recent or the largest sample size publication was included when the authors had published several studies using the same subjects.
Data extraction Relevant data were systematically extracted from all included studies by two observers by using a standardized form. The researchers collected the following data: Language of publication, publication year of article, the first author’s surname, geographical location, design of study, sample size, the source of the subjects, genotype frequencies, source of samples, genotyping method, evidence of HWE, etc.
Quality assessment Methodological quality was independently assessed by two researchers according to the Newcastle–Ottawa Scale (NOS) criteria.24 The NOS criteria included three aspects: (1) Subject selection, 0–4; (2) comparability of subject, 0–2; and (3) clinical outcome, 0–3. NOS scores ranged from 0 to 9; a score ‡ 7 indicates a good quality.
Statistical analysis The STATA version 12.0 (Stata Corp, College Station, TX) software was used for meta-analysis. We calculated crude odds ratios (ORs) with their 95% confidence intervals (95% CIs) to evaluate the relationships between of common polymorphisms in the TCF7L2 gene and PCOS risk. Genotype frequencies of healthy controls were tested for the HWE using the chi-squared test. The statistical significance of pooled ORs was assessed by the Z-test. The Cochran Q-statistic and I2-test were used to evaluate potential heterogeneity between studies.25 If the Q-test showed a P value < 0.05 or the I2-test exhibited > 50%, which indicates significant heterogeneity, the random-effect model was conducted; otherwise, the fixed-effects model was used. We also performed subgroup and meta-regression analyses to investigate potential sources of heterogeneity. We conducted a sensitivity analysis to assess the influence of single studies on the overall ORs. Begger funnel plots and the Egger linear regression test were used to investigate publication bias.26
Results Characteristics of included studies Initially, the keywords searched resulted in 96 articles. We reviewed the titles and abstracts of all articles and excluded 56 articles; full texts and data integrity were also reviewed, and 33 articles were further excluded. Finally, seven case–control studies with a total 2458 PCOS patients and 5109 healthy subjects met our inclusion criteria for qualitative data analysis.19–22,27–29 Publication years of the eligible studies ranged from 2007 to 2013. Figure 1 shows the selection process of eligible articles. The distribution of the number of topicrelated literatures in the electronic database during the last decade is shown in Figure 2. Overall, three studies were
PCOS, polycystic ovary syndrome; W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote; OR, odds ratio; 95% CI, 95% confidence interval; AS-PCR, allele specific-polymerase chain reaction; PCR-RFLP, polymerase chain reaction–restriction fragment length polymorphism; SNP, single-nucleotide polymorphism.
0.150 0.111 1.41 1.25 1.42 1.34 1.07–1.74 1.15–1.54 1.36 1.32
0.014 0.006
0.79–2.52 1.09–1.64
0.237 0.005
1.52 1.39
1.11–2.09 0.97–2.01
0.009 0.074
1.82 1.48
1.27–2.61 1.01–2.16
0.001 0.043
0.88–2.25 0.95–1.66
0.177 0.127 0.369 1.62 1.22 3.88 1.18 1.48 2.51 1.03–1.40 1.06–1.65 1.57–3.99 1.20 1.32 2.50
0.018 0.015 < 0.001
0.98–1.42 0.93–2.34 1.54–4.08
0.078 0.095 < 0.001
1.61 1.38 8.05
0.90–2.88 1.09–1.75 0.43–150.19
0.111 0.008 0.162
1.59 1.60 9.03
0.94–2.71 1.19–2.16 0.48–168.65
0.084 0.002 0.140
0.81–3.25 0.95–1.57 0.20–74.62
0.181 0.135 0.369 1.29 1.41 3.88 1.33 1.17 2.02 1.08–1.47 0.92–1.64 1.42–2.89 1.26 1.22 2.02
0.004 0.171 < 0.001
1.00–1.76 0.69–1.99 1.40–2.92
0.046 0.559 < 0.001
1.43 1.43 8.05
1.11–1.85 0.95–2.16 0.43–150.19
0.006 0.090 0.162
1.67 1.45 9.03
1.20–2.30 0.92–2.31 0.48–168.65
0.002 0.113 0.140
0.89–1.89 0.90–2.22 0.20–74.62
0.044 0.601 1.39 1.16 1.54 1.07 1.19–1.73 0.88–1.31 1.44 1.07
< 0.001 0.488
1.16–2.05 0.83–1.38
0.003 0.603
1.54 1.14
1.22–1.94 0.75–1.73
< 0.001 0.546
1.77 1.07
1.39–2.26 0.68–1.68
< 0.001 0.756
1.01–1.91 0.67–2.00
0.034 1.02–1.70 1.32 1.40 1.15–1.54
Overall SNP type rs7903146 C/T rs12255372 G/T Ethnicity Caucasians Africans Asians Genotyping method TaqMan assay AS-PCR PCR-RFLP Sample size Small (n £ 300) Large (n > 300)
1.33
< 0.001
1.12–1.75
0.003
1.43
1.17–1.76
0.001
1.61
1.26–2.07
< 0.001
95% CI OR P 95% CI OR OR
95% CI
P
95% CI
P
OR
95% CI
P
OR
MM vs. WW (homozygous model) MM vs. WW + WM (recessive model) WM + MM vs. WW (dominant model) M allele vs. W (allele model)
Table 2.
Meta-Analysis of the Associations Between Tcf7l2 Genetic Polymorphisms and PCOS Risk
MM vs. WM (heterozygous model)
P
TCF7L2 GENETIC POLYMORPHISMS AND PCOS RISK
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conducted among Asians, three studies among Caucasians, but only one study among Africans. The allele specific-PCR (AS-PCR) method was performed in three studies, the TaqMan assay method was performed in three studies, whereas only one study used the PCR restriction fragment length polymorphism (PCR-RFLP) method. Two common polymorphisms (rs7903146 C/T and rs12255372 G/T) in the TCF7L2 gene were assessed. Genotype frequencies of controls were all in HWE (all P > 0.05). None of the studies deviated from the HWE (all P > 0.05). NOS scores of all included studies were ‡ 5. The study characteristics and methodological quality are summarized in Table 1.
Quantitative data synthesis Meta-analysis findings on the relationships of TCF7L2 genetic polymorphisms with the risk of PCOS are shown in Table 2. The random-effects model was conducted due to obvious heterogeneity existing between studies. The results of our meta-analysis suggested that TCF7L2 genetic polymorphisms might be strongly correlated with an increased risk of PCOS (allele model, OR = 1.33, 95% CI = 1.15–1.54, P < 0.001; dominant model, OR = 1.40, 95% CI = 1.12–1.75, P = 0.003), especially for rs7903146 C/T polymorphism (Fig. 3) A subgroup analysis was done to investigate the effect of ethnicity on an individual’s risk of PCOS (Fig. 4). Our results revealed positive significant correlations between TCF7L2 genetic polymorphisms and an increased risk of PCOS among Caucasians (allele model, OR = 1.26, 95% CI = 1.08–1.47, P = 0.004; dominant model, OR = 1.33, 95% CI = 1.00–1.76, P = 0.046) and Asians (allele model, OR = 2.02, 95% CI = 1.42–2.89, P < 0.001; dominant model, OR = 2.02, 95% CI = 1.40–2.92, P < 0.001), but not among Africans (all P < 0.05). We also performed a subgroup analysis by genotyping method and sample size. The results indicated significant associations between TCF7L2 genetic polymorphisms and an increased risk of PCOS in the majority of subgroups (as shown in Table 2). Meta-regression analyses results confirmed that no factors could explain the sources of heterogeneity (as shown in Table 3). The results of sensitivity analysis indicated that the overall pooled ORs could not be affected by single study (Fig. 5). No evidence for asymmetry was observed in the Begger funnel plots (Fig. 6). The Egger test also failed to reveal any evidence of publication bias (allele model, t = 1.64, P = 0.139; dominant model, t = 1.16, P = 0.280).
Discussion TCF7L2 is a protein that acts as a transcription factor in the Wnt signaling pathway and may subsequently influence the transcription of several genes, thereby exerting a large variety of functions within cells.30,31 It is widely known that the Wnt signaling pathway is critical for cell proliferation, differentiation, and embryogenesis, all of which are involved in diabetes mellitus.32,33 In general, TCF7L2 regulates proglucagon expression predominantly via the Wnt signaling pathway in enteroendocrine cells, and it is also considered to be responsible for the dysfunction of b-cell and reduction of insulin secretion.34,35 Thus, TCF7L2 has been postulated to play a significant role in the pathogenesis of PCOS that is characterized by insulin resistance.12
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In the present meta-analysis, our findings revealed that PCOS patients had a higher frequency of the TCF7L2 rs7903146 C/T polymorphism than healthy controls, suggesting that common polymorphisms in the TCF7L2 rs7903146 C/T polymorphism may be a causative factor for the incidence of PCOS. However, we observed no correlations between the TCF7L2 rs12255372 G/T polymorphism and PCOS risk, indicating that this polymorphism may not be an important determinant in susceptibility to PCOS. Although the exact function of TCF7L2 in the de-
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velopment of PCOS is not yet fully understood, a possible explanation might be that genetic mutations in the TCF7L2 gene might lead to increased the expression of TCF7L2 in pancreatic cells, which may increase proinsulin/insulin ratios and pancreatic b-cell apoptosis, and decrease insulin secretion and b-cell proliferation, thereby resulting in the occurrence of PCOS.12,15 Biyasheva et al. have also demonstrated that genetic polymorphisms in the TCF7L2 gene may be related to defects in insulin secretion through altering conversion of proinsulin to insulin by the pancreatic b-cell,
FIG. 3. Forest plots for the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote.
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FIG. 4. Subgroup analyses by ethnicity and genotyping method of the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote. Table 3.
Univariate And Multivariate Meta-Regression Analyses Of Potential Source Of Heterogeneity 95%CI
Heterogeneity factors Publication year Univariate Multivariate SNP type Univariate Multivariate Ethnicity Univariate Multivariate Genotyping method Univariate Multivariate Sample size Univariate Multivariate
Coefficient
SE
Z
P
LL
UL
0.046 0.314
0.041 0.319
1.13 0.98
0.260 0.326
- 0.034 - 0.312
0.125 0.939
- 0.148 - 0.442
0.263 0.526
- 0.56 - 0.84
0.574 0.401
- 0.664 - 1.474
0.368 0.590
0.063 - 0.555
0.131 0.877
0.48 - 0.63
0.631 0.527
- 0.194 - 2.273
0.321 1.164
- 0.169 0.965
0.243 1.496
- 0.69 0.64
0.487 0.519
- 0.646 - 1.967
0.308 3.896
0.085 - 0.211
0.225 0.545
0.38 - 0.39
0.705 0.699
- 0.355 - 1.280
0.525 0.858
SE, standard error; 95%CI, 95% confidence interval; UL, upper limit; LL, lower limit; SNP, single nucleotide polymorphism.
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whereas the pathogenesis of PCOS is significantly associated with insulin resistance and pancreatic b-cell dysfunction.12 Among different ethnic subgroups, our findings suggested that TCF7L2 genetic polymorphisms were associated with an increased risk of PCOS among Caucasians and Asians, but not among Africans, revealing that ethnic differences may cause heterogeneity between studies
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concerning the role of TCF7L2 genetic polymorphisms in the pathogenesis of PCOS. This may be explained that natural selection, and random genetic drift may affect an individual’s susceptibility to PCOS. In short, the results of our meta-analysis were consistent with previous studies that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS.
FIG. 5. Sensitivity analysis of the summary odds ratio coefficients on the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote.
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FIG. 6. Begger funnel plot of publication biases on the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote. The current meta-analysis also had many limitations that should be acknowledged. First, due to the relatively small sample size, our results had lacked sufficient statistical power to assess the effects of TCF7L2 genetic polymorphisms on susceptibility to PCOS. Second, meta-analysis is a retrospective study that may lead to subject selection bias and thereby affect the reliability of our results. Third, our meta-analysis failed to obtain original data from the included studies, which may limit further evaluation of potential roles of TCF7L2 genetic polymorphisms in PCOS. Although our study has many limitations, this is the first meta-analysis focused on the relationships of TCF7L2 genetic polymorphisms with the risk of PCOS. Furthermore, we performed a highly sensitive literature search
strategy for electronic databases. A manual search of the reference lists from the relevant articles was also conducted to find other potential articles. The selection process of eligible articles was based on strict inclusion and exclusion criteria. Importantly, rigorous statistical analysis of SNP data provided a basis for pooling of information from individual studies. In conclusion, our findings provide convincing evidence that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS, especially for the rs7903146 C/T polymorphism among Caucasians and Asians. Thus, TCF7L2 genetic polymorphisms may be used as potential biomarkers for early diagnosis of PCOS. However, due to limitations mentioned above, more research with larger
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sample sizes are needed to provide a more representative statistical analysis. 15.
Acknowledgments This study was supported by the Science and Technology Research Project of the Higher Education Department of Liaoning Province (no. L2010695). We would like to acknowledge the helpful comments on this paper received from our reviewers. This work was supported by the Science Foundation of Science and Technology Bureau of Liaoning Province of China (201202259).
Author Disclosure Statement
16. 17.
18.
We declare that we have no conflicts of interest.
References 1. Shayya R, Chang RJ. Reproductive endocrinology of adolescent polycystic ovary syndrome. BJOG 2010;117:150– 155. 2. Carmina E. Metabolic syndrome in polycystic ovary syndrome. Minerva Ginecol 2006;58:109–114. 3. Apridonidze T, Essah PA, Iuorno MJ, Nestler JE. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2005;90:1929–1935. 4. Fauser BCJM, Tarlatzis BC, Rebar RW. Consensus on women’s health aspects of polycystic ovary syndrome (PCOS). Hum Reprod 2012;27:14–24. 5. Insenser M, Montes-Nieto R, Murri M, et al. Proteomic and metabolomic approaches to the study of polycystic ovary syndrome. Mol Cell Endocrinol 2013;370:65–77. 6. Diamanti-Kandarakis E, Papavassiliou AG. Molecular mechanisms of insulin resistance in polycystic ovary syndrome. Trends Mol Med 2006;12:324–332. 7. Diamanti-Kandarakis E, Piperi C, Spina J, et al. Polycystic ovary syndrome: The influence of environmental and genetic factors. Hormones (Athens) 2006;5:17–34. 8. Shao W, Wang D, Chiang YT, et al. The Wnt signaling pathway effector TCF7L2 controls gut and brain proglucagon gene expression and glucose homeostasis. Diabetes 2013;62:789–800. 9. Diamanti-Kandarakis E, Christakou C, Marinakis E. Phenotypes and enviromental factors: Their influence in PCOS. Curr Pharm Des 2012;18:270–282. 10. Wang L, Li S, Zhao A, et al. The expression of sex steroid synthesis and inactivation enzymes in subcutaneous adipose tissue of PCOS patients. J Steroid Biochem Mol Biol 2012; 132:120–126. 11. Arefi S, Mottaghi S, Sharifi AM. Studying the correlation of renin-angiotensin-system (RAS) components and insulin resistance in polycystic ovary syndrome (PCOs). Gynecol Endocrinol 2013;29:470–473. 12. Biyasheva A, Legro RS, Dunaif A, et al. Evidence for association between polycystic ovary syndrome (PCOS) and TCF7L2 and glucose intolerance in women with PCOS and TCF7L2. J Clin Endocrinol Metab 2009;94:2617–2625. 13. Gloyn A L, Braun M, Rorsman P. Type 2 diabetes susceptibility gene TCF7L2 and its role in beta-cell function. Diabetes 2009;58:800–802. 14. Wang J, Kuusisto J, Vanttinen M, et al. Variants of transcription factor 7-like 2 (TCF7L2) gene predict conversion to type 2 diabetes in the Finnish Diabetes Prevention Study and
19.
20. 21.
22.
23.
24. 25. 26. 27.
28.
29.
30. 31.
are associated with impaired glucose regulation and impaired insulin secretion. Diabetologia 2007;50:1192–1200. Warodomwichit D, Arnett DK, Kabagambe EK, et al. Polyunsaturated fatty acids modulate the effect of TCF7L2 gene variants on postprandial lipemia. J Nutr 2009;139: 439–446. Duval A, Busson-Leconiat M, Berger R, et al. Assignment of the TCF-4 gene (TCF7L2) to human chromosome band 10q25.3. Cytogenet Cell Genet 2000;88:264–265. Liu PH, Chang YC, Jiang YD, et al. Genetic variants of TCF7L2 are associated with insulin resistance and related metabolic phenotypes in Taiwanese adolescents and Caucasian young adults. J Clin Endocrinol Metab 2009;94: 3575–3582. Tan S, Scherag A, Janssen OE, et al. Large effects on body mass index and insulin resistance of fat mass and obesity associated gene (FTO) variants in patients with polycystic ovary syndrome (PCOS). BMC Med Genet 2010;11:12. Christopoulos P, Mastorakos G, Gazouli M, et al. Genetic variants in TCF7L2 and KCNJ11 genes in a Greek population with polycystic ovary syndrome. Gynecol Endocrinol 2008;24:486–490. Xu P, Che Y, Cao Y, et al. Polymorphisms of TCF7L2 and HHEX genes in Chinese women with polycystic ovary syndrome. J Assist Reprod Genet 2010;27:23–28. Barber TM, Bennett AJ, Groves CJ, et al. Disparate genetic influences on polycystic ovary syndrome (PCOS) and type 2 diabetes revealed by a lack of association between common variants within the TCF7L2 gene and PCOS. Diabetologia 2007;50:2318–2322. Ramos R B, Wiltgen D, Spritzer PM. Polymorphisms of TCF7L2 gene in South Brazilian women with polycystic ovary syndrome: A cross-sectional study. Eur J Endocrinol 2013;169:569–576. Geisthovel FA. Comment on the European Society of Human Reproduction and Embryology/American Society for Reproductive Medicine consensus of the polycystic ovarian syndrome. Reprod Biomed Online 2003;7:602–605. Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 2010;25:603–605. Zintzaras E, Ioannidis JP. HEGESMA: Genome search meta-analysis and heterogeneity testing. Bioinformatics 2005;21:3672–3673. Peters JL, Sutton AJ, Jones DR, et al. Comparison of two methods to detect publication bias in meta-analysis. JAMA 2006;295:676–680. Ben-Salem A, Ajina M, Suissi M, Daher HS, et al. Polymorphisms of transcription factor-7-like 2 (TCF7L2) gene in Tunisian women with polycystic ovary syndrome (PCOS). Gene 2013;533:554–557. Kim JJ, Choi YM, Cho YM, et al. Polycystic ovary syndrome is not associated with polymorphisms of the TCF7L2, CDKAL1, HHEX, KCNJ11, FTO and SLC30A8 genes. Clin Endocrinol (Oxf ) 2012;77:439–445. Vcelak J, Vejrazkova D, Vankova M, et al. T2D risk haplotypes of the TCF7L2 gene in the Czech population sample: The association with free fatty acids composition. Physiol Res 2012;61:229–240. MacDonald BT, Tamai K, He X. Wnt/beta-catenin signaling: Components, mechanisms, and diseases. Dev Cell 2009;17:9–26. Le Bacquer O, Shu L, Marchand M, et al. TCF7L2 splice variants have distinct effects on beta-cell turnover and function. Hum Mol Genet 2011;20:1906–1915.
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32. Logan CY, Nusse R. The Wnt signaling pathway in development and disease. Annu Rev Cell Dev Biol 2004;20: 781–810. 33. Jin T. The WNT signalling pathway and diabetes mellitus. Diabetologia 2008;51:1771–1780. 34. Jin T, Liu L. The Wnt signaling pathway effector TCF7L2 and type 2 diabetes mellitus. Mol Endocrinol 2008;22:2383– 2392. 35. Welters HJ, Kulkarni RN. Wnt signaling: Relevance to beta-cell biology and diabetes. Trends Endocrinol Metab 2008;19:349–355.
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Address correspondence to: Dr. Wen-Jing Shen Department of Gynecology The First Hospital of China Medical University No. 155 Nanjing North Street, Heping District Shenyang 110001 People’s Republic of China E-mail: [email protected] [email protected]
Relationships Between TCF7L2 Genetic Polymorphisms and Polycystic Ovary Syndrome Risk: A Meta-Analysis Wen-Jing Shen, MD,1 Tian-Ren Li, MD,1 Yan-Jie Hu, MD,1 Hong-Bo Liu, MD 2 and Min Song, MD 3
Abstract
Objective: This meta-analysis was performed to evaluate the relationships between genetic polymorphisms in the TCF7L2 gene and polycystic ovary syndrome (PCOS) risk. Methods: The PubMed, Centralised Information Service for Complementary Medicine (CISCOM), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, Google Scholar, EBSCO, Cochrane Library, and Common Biorepository Model (CBM) databases were searched for relevant articles published before November 1st, 2013, without language restrictions. Meta-analysis was conducted using the STATA 12.0 software. The relationships were evaluated by calculating the pooled odds ratios (ORs) and their 95% confidence intervals (CIs). Seven case–control studies with a total 2458 PCOS patients and 5109 healthy subjects’ met our inclusion criteria for qualitative data analysis. Two common polymorphisms (rs7903146 C/T and rs12255372 G/T) in the TCF7L2 gene were assessed. Results: The results of our meta-analysis suggested that TCF7L2 genetic polymorphisms might be strongly correlated with an increased risk of PCOS (allele model, OR = 1.33, 95% CI = 1.15–1.54, P < 0.001; dominant model, OR = 1.40, 95% CI = 1.12–1.75, P = 0.003), especially for the rs7903146 C/T polymorphism. A subgroup analysis was done to investigate the effect of ethnicity on an individual’s risk of PCOS. Our results revealed positive significant correlations between TCF7L2 genetic polymorphisms and an increased risk of PCOS among Caucasians (allele model, OR = 1.26, 95% CI = 1.08–1.47, P = 0.004; dominant model, OR = 1.33, 95% CI = 1.00–1.76, P = 0.046) and Asians (allele model, OR = 2.02, 95% CI = 1.42–2.89, P < 0.001; dominant model, OR = 2.02, 95% CI = 1.40–2.92, P < 0.001), but not among Africans (all P < 0.05). Conclusions: Our findings provide convincing evidence that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS, especially for the rs7903146 C/T polymorphism among Caucasians and Asians.
Introduction
P
olycystic ovary syndrome (PCOS), also known as Stein–Leventhal syndrome, is the most common reproductive endocrinopathy associated with features of metabolic syndrome, including insulin resistance, androgen excess, abdominal obesity, disturbed b-cell function, and type 2 diabetes mellitus (T2DM).1,2 Usually, PCOS is characterized by hyperandrogenism, oligomenorrhea or amenorrhea, and polycystic ovaries; 6–10% women of reproductive age are affected by PCOS.3,4 Generally, PCOS is recognized as a complex multifactorial disorder resulting from the interaction of ge-
netic, environmental, as well as lifestyle influences.5 Although the exact cellular and molecular mechanisms leading to the development of PCOS remain unclear, it is believed that environmental and genetic factors may contribute to increased susceptibility to PCOS.6,7 Transcription factor 7-like 2 (TCF7L2) is one of the four T cell transcription factors that collaborate with free b-catenin to regulate proglucagon expression via the Wnt signaling pathway by repressing the proglucagon gene in enteroendocrine cells.8 It is widely accepted that insulin resistance and its accompanying hyperinsulinemia may play a crucial role in the occurrence and progression of PCOS.9–11 Previous
1
Department of Gynecology, The First Hospital of China Medical University, Shenyang, People’s Republic of China. Department of Health Statistics, School of Public Health, China Medical University, Shenyang, People’s Republic of China. Department of Pathology, The First Hospital and College of Basic Medical Sciences, China Medical University; Institute of Pathology and Pathophysiology, China Medical University, Shenyang, People’s Republic of China. 2 3
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FIG. 1.
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Flow chart of literature search and study selection. Seven case–control studies were included in this meta-analysis.
studies have demonstrated that TCF7L2 might be involved in insulin resistance, b-cell dysfunction, impaired glucose tolerance, dyslipidemia, etc.12–15 Consequently, TCF7L2 has been hypothesized to be involved in the etiology of PCOS by regulating glucose homeostasis.12 Human TCF7L2 gene, located on chromosome 10q25.3, is composed of 17 exons with an overall length of approximately 21.5 kb.16 Genetic variations in the TCF7L2 gene may lead to fat deposition of peripheral tissues and muscles, and thereby increase insulin resistance, which may confer a substantially increased risk for individual’s susceptibility to PCOS.17,18 Many previous studies have demonstrated that TCF7L2 genetic polymorphisms may be implicated in the pathogenesis of PCOS.19,20 Nevertheless, contradictory results have also been reported in many other studies.21,22 Therefore, we performed the present meta-analysis to evaluate the relationships between TCF7L2 genetic polymorphisms and PCOS risk.
Methods Search strategy The PubMed, Centralised Information Service for Complementary Medicine (CISCOM), Cumulative Index to Nur-
FIG. 2.
sing and Allied Health Literature (CINAHL), Web of Science, Google Scholar, EBSCO, Cochrane Library, and Common Biorepository Model (CBM) were searched for relevant articles published before November 1st, 2013, without language restrictions. The following keywords and MeSH terms were used: [‘‘SNP’’ or ‘‘mutation’’ or ‘‘genetic polymorphism’’ or ‘‘variation’’ or ‘‘polymorphism’’ or ‘‘single nucleotide polymorphism’’ or ‘‘variant’’] and [‘‘polycystic ovary syndrome’’ or ‘‘PCOS’’ or ‘‘Stein-Leventhal syndrome’’] and [‘‘transcription factor 7-like 2 ’’ or ‘‘TCF7L2’’ or ‘‘T-cell-specific transcription factor 4’’ or ‘‘T cell factor 4’’]. We also performed a manual search to find other potential articles.
Selection criteria The included studies had to meet all four of the following criteria: (1) The study design must be a clinical cohort or case–control study that focused on the relationships between TCF7L2 genetic polymorphisms with the risk of PCOS; (2) all patients should meet the consensus definition of PCOS specified in the 2003 Rotterdam Conference by European Society for Human Reproduction and Embryology (ESHRE) and American Society for Reproductive Medicine (ASRM) or in the 1990 National Institutes of Health–National Institute
Distribution of the number of topic-related literatures in the electronic database during the last decade.
29.1 – 5.1 26.2 – 7.1 — 26.1 – 4.0 23.9 – 5.2 — 290 148 3657 Asian Caucasian Caucasian Xu et al. Christopoulos et al.19 Barber et al.21
2010 2010 2007
China Greece UK
326 183 909
28.5 – 4.9 28.5 – 4.9 386 377 Asian 2012
Korea
20
Kim et al.
SNP, single nucleotide polymorphism; PCR-RFLP, polymerase chain reaction–restriction fragment length polymorphism; AS-PCR, allele-specific polymerase chain reaction; HWE, Hardy– Weinberg equilibrium; NOS, Newcastle–Ottawa Scale.
7 6 6
7
7 Caucasian 2012
28
Vcelak et al.29
Czech
329
376
27.5 – 6.3
29.9 – 10.8
0.228 0.523 0.139 0.731 0.783 0.443 0.939 0.068 0.346 0.879 rs7903146 C/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs12255372 G/T rs7903146 C/T rs7903146 C/T rs7903146 C/T TaqMan assay AS-PCR AS-PCR TaqMan assay TaqMan assay TaqMan assay TaqMan assay PCR-RFLP AS-PCR AS-PCR 25.2 – 7.6 31.8 – 5.7 Caucasian African 2013 2013 Ramos et al.22 Ben-Salem et al.27
Brazil Tunisia
200 134
102 150
22.8 – 6.6 30.1 – 4.1
HWE test (P value) SNP type Genotyping method Control Case Control Case Ethnicity Country Year Reference
Age (years) Number
Main Characteristics and Methodological Quality of All Eligible Studies Table 1.
7 6
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NOS score
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of Child Health and Human Development conference23; (3) the study must provide sufficient information about genotype frequencies of TCF7L2 genetic polymorphisms; and (4) the genotype frequencies should follow the Hardy–Weinberg equilibrium (HWE). If the study did not meet the inclusion criteria, it was excluded. The most recent or the largest sample size publication was included when the authors had published several studies using the same subjects.
Data extraction Relevant data were systematically extracted from all included studies by two observers by using a standardized form. The researchers collected the following data: Language of publication, publication year of article, the first author’s surname, geographical location, design of study, sample size, the source of the subjects, genotype frequencies, source of samples, genotyping method, evidence of HWE, etc.
Quality assessment Methodological quality was independently assessed by two researchers according to the Newcastle–Ottawa Scale (NOS) criteria.24 The NOS criteria included three aspects: (1) Subject selection, 0–4; (2) comparability of subject, 0–2; and (3) clinical outcome, 0–3. NOS scores ranged from 0 to 9; a score ‡ 7 indicates a good quality.
Statistical analysis The STATA version 12.0 (Stata Corp, College Station, TX) software was used for meta-analysis. We calculated crude odds ratios (ORs) with their 95% confidence intervals (95% CIs) to evaluate the relationships between of common polymorphisms in the TCF7L2 gene and PCOS risk. Genotype frequencies of healthy controls were tested for the HWE using the chi-squared test. The statistical significance of pooled ORs was assessed by the Z-test. The Cochran Q-statistic and I2-test were used to evaluate potential heterogeneity between studies.25 If the Q-test showed a P value < 0.05 or the I2-test exhibited > 50%, which indicates significant heterogeneity, the random-effect model was conducted; otherwise, the fixed-effects model was used. We also performed subgroup and meta-regression analyses to investigate potential sources of heterogeneity. We conducted a sensitivity analysis to assess the influence of single studies on the overall ORs. Begger funnel plots and the Egger linear regression test were used to investigate publication bias.26
Results Characteristics of included studies Initially, the keywords searched resulted in 96 articles. We reviewed the titles and abstracts of all articles and excluded 56 articles; full texts and data integrity were also reviewed, and 33 articles were further excluded. Finally, seven case–control studies with a total 2458 PCOS patients and 5109 healthy subjects met our inclusion criteria for qualitative data analysis.19–22,27–29 Publication years of the eligible studies ranged from 2007 to 2013. Figure 1 shows the selection process of eligible articles. The distribution of the number of topicrelated literatures in the electronic database during the last decade is shown in Figure 2. Overall, three studies were
PCOS, polycystic ovary syndrome; W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote; OR, odds ratio; 95% CI, 95% confidence interval; AS-PCR, allele specific-polymerase chain reaction; PCR-RFLP, polymerase chain reaction–restriction fragment length polymorphism; SNP, single-nucleotide polymorphism.
0.150 0.111 1.41 1.25 1.42 1.34 1.07–1.74 1.15–1.54 1.36 1.32
0.014 0.006
0.79–2.52 1.09–1.64
0.237 0.005
1.52 1.39
1.11–2.09 0.97–2.01
0.009 0.074
1.82 1.48
1.27–2.61 1.01–2.16
0.001 0.043
0.88–2.25 0.95–1.66
0.177 0.127 0.369 1.62 1.22 3.88 1.18 1.48 2.51 1.03–1.40 1.06–1.65 1.57–3.99 1.20 1.32 2.50
0.018 0.015 < 0.001
0.98–1.42 0.93–2.34 1.54–4.08
0.078 0.095 < 0.001
1.61 1.38 8.05
0.90–2.88 1.09–1.75 0.43–150.19
0.111 0.008 0.162
1.59 1.60 9.03
0.94–2.71 1.19–2.16 0.48–168.65
0.084 0.002 0.140
0.81–3.25 0.95–1.57 0.20–74.62
0.181 0.135 0.369 1.29 1.41 3.88 1.33 1.17 2.02 1.08–1.47 0.92–1.64 1.42–2.89 1.26 1.22 2.02
0.004 0.171 < 0.001
1.00–1.76 0.69–1.99 1.40–2.92
0.046 0.559 < 0.001
1.43 1.43 8.05
1.11–1.85 0.95–2.16 0.43–150.19
0.006 0.090 0.162
1.67 1.45 9.03
1.20–2.30 0.92–2.31 0.48–168.65
0.002 0.113 0.140
0.89–1.89 0.90–2.22 0.20–74.62
0.044 0.601 1.39 1.16 1.54 1.07 1.19–1.73 0.88–1.31 1.44 1.07
< 0.001 0.488
1.16–2.05 0.83–1.38
0.003 0.603
1.54 1.14
1.22–1.94 0.75–1.73
< 0.001 0.546
1.77 1.07
1.39–2.26 0.68–1.68
< 0.001 0.756
1.01–1.91 0.67–2.00
0.034 1.02–1.70 1.32 1.40 1.15–1.54
Overall SNP type rs7903146 C/T rs12255372 G/T Ethnicity Caucasians Africans Asians Genotyping method TaqMan assay AS-PCR PCR-RFLP Sample size Small (n £ 300) Large (n > 300)
1.33
< 0.001
1.12–1.75
0.003
1.43
1.17–1.76
0.001
1.61
1.26–2.07
< 0.001
95% CI OR P 95% CI OR OR
95% CI
P
95% CI
P
OR
95% CI
P
OR
MM vs. WW (homozygous model) MM vs. WW + WM (recessive model) WM + MM vs. WW (dominant model) M allele vs. W (allele model)
Table 2.
Meta-Analysis of the Associations Between Tcf7l2 Genetic Polymorphisms and PCOS Risk
MM vs. WM (heterozygous model)
P
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213
conducted among Asians, three studies among Caucasians, but only one study among Africans. The allele specific-PCR (AS-PCR) method was performed in three studies, the TaqMan assay method was performed in three studies, whereas only one study used the PCR restriction fragment length polymorphism (PCR-RFLP) method. Two common polymorphisms (rs7903146 C/T and rs12255372 G/T) in the TCF7L2 gene were assessed. Genotype frequencies of controls were all in HWE (all P > 0.05). None of the studies deviated from the HWE (all P > 0.05). NOS scores of all included studies were ‡ 5. The study characteristics and methodological quality are summarized in Table 1.
Quantitative data synthesis Meta-analysis findings on the relationships of TCF7L2 genetic polymorphisms with the risk of PCOS are shown in Table 2. The random-effects model was conducted due to obvious heterogeneity existing between studies. The results of our meta-analysis suggested that TCF7L2 genetic polymorphisms might be strongly correlated with an increased risk of PCOS (allele model, OR = 1.33, 95% CI = 1.15–1.54, P < 0.001; dominant model, OR = 1.40, 95% CI = 1.12–1.75, P = 0.003), especially for rs7903146 C/T polymorphism (Fig. 3) A subgroup analysis was done to investigate the effect of ethnicity on an individual’s risk of PCOS (Fig. 4). Our results revealed positive significant correlations between TCF7L2 genetic polymorphisms and an increased risk of PCOS among Caucasians (allele model, OR = 1.26, 95% CI = 1.08–1.47, P = 0.004; dominant model, OR = 1.33, 95% CI = 1.00–1.76, P = 0.046) and Asians (allele model, OR = 2.02, 95% CI = 1.42–2.89, P < 0.001; dominant model, OR = 2.02, 95% CI = 1.40–2.92, P < 0.001), but not among Africans (all P < 0.05). We also performed a subgroup analysis by genotyping method and sample size. The results indicated significant associations between TCF7L2 genetic polymorphisms and an increased risk of PCOS in the majority of subgroups (as shown in Table 2). Meta-regression analyses results confirmed that no factors could explain the sources of heterogeneity (as shown in Table 3). The results of sensitivity analysis indicated that the overall pooled ORs could not be affected by single study (Fig. 5). No evidence for asymmetry was observed in the Begger funnel plots (Fig. 6). The Egger test also failed to reveal any evidence of publication bias (allele model, t = 1.64, P = 0.139; dominant model, t = 1.16, P = 0.280).
Discussion TCF7L2 is a protein that acts as a transcription factor in the Wnt signaling pathway and may subsequently influence the transcription of several genes, thereby exerting a large variety of functions within cells.30,31 It is widely known that the Wnt signaling pathway is critical for cell proliferation, differentiation, and embryogenesis, all of which are involved in diabetes mellitus.32,33 In general, TCF7L2 regulates proglucagon expression predominantly via the Wnt signaling pathway in enteroendocrine cells, and it is also considered to be responsible for the dysfunction of b-cell and reduction of insulin secretion.34,35 Thus, TCF7L2 has been postulated to play a significant role in the pathogenesis of PCOS that is characterized by insulin resistance.12
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In the present meta-analysis, our findings revealed that PCOS patients had a higher frequency of the TCF7L2 rs7903146 C/T polymorphism than healthy controls, suggesting that common polymorphisms in the TCF7L2 rs7903146 C/T polymorphism may be a causative factor for the incidence of PCOS. However, we observed no correlations between the TCF7L2 rs12255372 G/T polymorphism and PCOS risk, indicating that this polymorphism may not be an important determinant in susceptibility to PCOS. Although the exact function of TCF7L2 in the de-
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velopment of PCOS is not yet fully understood, a possible explanation might be that genetic mutations in the TCF7L2 gene might lead to increased the expression of TCF7L2 in pancreatic cells, which may increase proinsulin/insulin ratios and pancreatic b-cell apoptosis, and decrease insulin secretion and b-cell proliferation, thereby resulting in the occurrence of PCOS.12,15 Biyasheva et al. have also demonstrated that genetic polymorphisms in the TCF7L2 gene may be related to defects in insulin secretion through altering conversion of proinsulin to insulin by the pancreatic b-cell,
FIG. 3. Forest plots for the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote.
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215
FIG. 4. Subgroup analyses by ethnicity and genotyping method of the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote. Table 3.
Univariate And Multivariate Meta-Regression Analyses Of Potential Source Of Heterogeneity 95%CI
Heterogeneity factors Publication year Univariate Multivariate SNP type Univariate Multivariate Ethnicity Univariate Multivariate Genotyping method Univariate Multivariate Sample size Univariate Multivariate
Coefficient
SE
Z
P
LL
UL
0.046 0.314
0.041 0.319
1.13 0.98
0.260 0.326
- 0.034 - 0.312
0.125 0.939
- 0.148 - 0.442
0.263 0.526
- 0.56 - 0.84
0.574 0.401
- 0.664 - 1.474
0.368 0.590
0.063 - 0.555
0.131 0.877
0.48 - 0.63
0.631 0.527
- 0.194 - 2.273
0.321 1.164
- 0.169 0.965
0.243 1.496
- 0.69 0.64
0.487 0.519
- 0.646 - 1.967
0.308 3.896
0.085 - 0.211
0.225 0.545
0.38 - 0.39
0.705 0.699
- 0.355 - 1.280
0.525 0.858
SE, standard error; 95%CI, 95% confidence interval; UL, upper limit; LL, lower limit; SNP, single nucleotide polymorphism.
216
whereas the pathogenesis of PCOS is significantly associated with insulin resistance and pancreatic b-cell dysfunction.12 Among different ethnic subgroups, our findings suggested that TCF7L2 genetic polymorphisms were associated with an increased risk of PCOS among Caucasians and Asians, but not among Africans, revealing that ethnic differences may cause heterogeneity between studies
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concerning the role of TCF7L2 genetic polymorphisms in the pathogenesis of PCOS. This may be explained that natural selection, and random genetic drift may affect an individual’s susceptibility to PCOS. In short, the results of our meta-analysis were consistent with previous studies that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS.
FIG. 5. Sensitivity analysis of the summary odds ratio coefficients on the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. References cited in figure are: Ramos et al.,22 Ben-Salem et al.,27 Vcelak et al., 29 Kim et al.,28 Christopoulos et al.,19 Barber et al., 21 and Xu et al.20 W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote.
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217
FIG. 6. Begger funnel plot of publication biases on the relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome (PCOS) risk under the allele and dominant models. W, wild allele; M, mutant allele; WW, wild homozygote; WM, heterozygote; MM, mutant homozygote. The current meta-analysis also had many limitations that should be acknowledged. First, due to the relatively small sample size, our results had lacked sufficient statistical power to assess the effects of TCF7L2 genetic polymorphisms on susceptibility to PCOS. Second, meta-analysis is a retrospective study that may lead to subject selection bias and thereby affect the reliability of our results. Third, our meta-analysis failed to obtain original data from the included studies, which may limit further evaluation of potential roles of TCF7L2 genetic polymorphisms in PCOS. Although our study has many limitations, this is the first meta-analysis focused on the relationships of TCF7L2 genetic polymorphisms with the risk of PCOS. Furthermore, we performed a highly sensitive literature search
strategy for electronic databases. A manual search of the reference lists from the relevant articles was also conducted to find other potential articles. The selection process of eligible articles was based on strict inclusion and exclusion criteria. Importantly, rigorous statistical analysis of SNP data provided a basis for pooling of information from individual studies. In conclusion, our findings provide convincing evidence that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS, especially for the rs7903146 C/T polymorphism among Caucasians and Asians. Thus, TCF7L2 genetic polymorphisms may be used as potential biomarkers for early diagnosis of PCOS. However, due to limitations mentioned above, more research with larger
218
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sample sizes are needed to provide a more representative statistical analysis. 15.
Acknowledgments This study was supported by the Science and Technology Research Project of the Higher Education Department of Liaoning Province (no. L2010695). We would like to acknowledge the helpful comments on this paper received from our reviewers. This work was supported by the Science Foundation of Science and Technology Bureau of Liaoning Province of China (201202259).
Author Disclosure Statement
16. 17.
18.
We declare that we have no conflicts of interest.
References 1. Shayya R, Chang RJ. Reproductive endocrinology of adolescent polycystic ovary syndrome. BJOG 2010;117:150– 155. 2. Carmina E. Metabolic syndrome in polycystic ovary syndrome. Minerva Ginecol 2006;58:109–114. 3. Apridonidze T, Essah PA, Iuorno MJ, Nestler JE. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2005;90:1929–1935. 4. Fauser BCJM, Tarlatzis BC, Rebar RW. Consensus on women’s health aspects of polycystic ovary syndrome (PCOS). Hum Reprod 2012;27:14–24. 5. Insenser M, Montes-Nieto R, Murri M, et al. Proteomic and metabolomic approaches to the study of polycystic ovary syndrome. Mol Cell Endocrinol 2013;370:65–77. 6. Diamanti-Kandarakis E, Papavassiliou AG. Molecular mechanisms of insulin resistance in polycystic ovary syndrome. Trends Mol Med 2006;12:324–332. 7. Diamanti-Kandarakis E, Piperi C, Spina J, et al. Polycystic ovary syndrome: The influence of environmental and genetic factors. Hormones (Athens) 2006;5:17–34. 8. Shao W, Wang D, Chiang YT, et al. The Wnt signaling pathway effector TCF7L2 controls gut and brain proglucagon gene expression and glucose homeostasis. Diabetes 2013;62:789–800. 9. Diamanti-Kandarakis E, Christakou C, Marinakis E. Phenotypes and enviromental factors: Their influence in PCOS. Curr Pharm Des 2012;18:270–282. 10. Wang L, Li S, Zhao A, et al. The expression of sex steroid synthesis and inactivation enzymes in subcutaneous adipose tissue of PCOS patients. J Steroid Biochem Mol Biol 2012; 132:120–126. 11. Arefi S, Mottaghi S, Sharifi AM. Studying the correlation of renin-angiotensin-system (RAS) components and insulin resistance in polycystic ovary syndrome (PCOs). Gynecol Endocrinol 2013;29:470–473. 12. Biyasheva A, Legro RS, Dunaif A, et al. Evidence for association between polycystic ovary syndrome (PCOS) and TCF7L2 and glucose intolerance in women with PCOS and TCF7L2. J Clin Endocrinol Metab 2009;94:2617–2625. 13. Gloyn A L, Braun M, Rorsman P. Type 2 diabetes susceptibility gene TCF7L2 and its role in beta-cell function. Diabetes 2009;58:800–802. 14. Wang J, Kuusisto J, Vanttinen M, et al. Variants of transcription factor 7-like 2 (TCF7L2) gene predict conversion to type 2 diabetes in the Finnish Diabetes Prevention Study and
19.
20. 21.
22.
23.
24. 25. 26. 27.
28.
29.
30. 31.
are associated with impaired glucose regulation and impaired insulin secretion. Diabetologia 2007;50:1192–1200. Warodomwichit D, Arnett DK, Kabagambe EK, et al. Polyunsaturated fatty acids modulate the effect of TCF7L2 gene variants on postprandial lipemia. J Nutr 2009;139: 439–446. Duval A, Busson-Leconiat M, Berger R, et al. Assignment of the TCF-4 gene (TCF7L2) to human chromosome band 10q25.3. Cytogenet Cell Genet 2000;88:264–265. Liu PH, Chang YC, Jiang YD, et al. Genetic variants of TCF7L2 are associated with insulin resistance and related metabolic phenotypes in Taiwanese adolescents and Caucasian young adults. J Clin Endocrinol Metab 2009;94: 3575–3582. Tan S, Scherag A, Janssen OE, et al. Large effects on body mass index and insulin resistance of fat mass and obesity associated gene (FTO) variants in patients with polycystic ovary syndrome (PCOS). BMC Med Genet 2010;11:12. Christopoulos P, Mastorakos G, Gazouli M, et al. Genetic variants in TCF7L2 and KCNJ11 genes in a Greek population with polycystic ovary syndrome. Gynecol Endocrinol 2008;24:486–490. Xu P, Che Y, Cao Y, et al. Polymorphisms of TCF7L2 and HHEX genes in Chinese women with polycystic ovary syndrome. J Assist Reprod Genet 2010;27:23–28. Barber TM, Bennett AJ, Groves CJ, et al. Disparate genetic influences on polycystic ovary syndrome (PCOS) and type 2 diabetes revealed by a lack of association between common variants within the TCF7L2 gene and PCOS. Diabetologia 2007;50:2318–2322. Ramos R B, Wiltgen D, Spritzer PM. Polymorphisms of TCF7L2 gene in South Brazilian women with polycystic ovary syndrome: A cross-sectional study. Eur J Endocrinol 2013;169:569–576. Geisthovel FA. Comment on the European Society of Human Reproduction and Embryology/American Society for Reproductive Medicine consensus of the polycystic ovarian syndrome. Reprod Biomed Online 2003;7:602–605. Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 2010;25:603–605. Zintzaras E, Ioannidis JP. HEGESMA: Genome search meta-analysis and heterogeneity testing. Bioinformatics 2005;21:3672–3673. Peters JL, Sutton AJ, Jones DR, et al. Comparison of two methods to detect publication bias in meta-analysis. JAMA 2006;295:676–680. Ben-Salem A, Ajina M, Suissi M, Daher HS, et al. Polymorphisms of transcription factor-7-like 2 (TCF7L2) gene in Tunisian women with polycystic ovary syndrome (PCOS). Gene 2013;533:554–557. Kim JJ, Choi YM, Cho YM, et al. Polycystic ovary syndrome is not associated with polymorphisms of the TCF7L2, CDKAL1, HHEX, KCNJ11, FTO and SLC30A8 genes. Clin Endocrinol (Oxf ) 2012;77:439–445. Vcelak J, Vejrazkova D, Vankova M, et al. T2D risk haplotypes of the TCF7L2 gene in the Czech population sample: The association with free fatty acids composition. Physiol Res 2012;61:229–240. MacDonald BT, Tamai K, He X. Wnt/beta-catenin signaling: Components, mechanisms, and diseases. Dev Cell 2009;17:9–26. Le Bacquer O, Shu L, Marchand M, et al. TCF7L2 splice variants have distinct effects on beta-cell turnover and function. Hum Mol Genet 2011;20:1906–1915.
TCF7L2 GENETIC POLYMORPHISMS AND PCOS RISK
32. Logan CY, Nusse R. The Wnt signaling pathway in development and disease. Annu Rev Cell Dev Biol 2004;20: 781–810. 33. Jin T. The WNT signalling pathway and diabetes mellitus. Diabetologia 2008;51:1771–1780. 34. Jin T, Liu L. The Wnt signaling pathway effector TCF7L2 and type 2 diabetes mellitus. Mol Endocrinol 2008;22:2383– 2392. 35. Welters HJ, Kulkarni RN. Wnt signaling: Relevance to beta-cell biology and diabetes. Trends Endocrinol Metab 2008;19:349–355.
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Address correspondence to: Dr. Wen-Jing Shen Department of Gynecology The First Hospital of China Medical University No. 155 Nanjing North Street, Heping District Shenyang 110001 People’s Republic of China E-mail: [email protected] [email protected]
