European Journal of Obstetrics & Gynecology and Reproductive Biology 182 (2014) 226–237
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Review
Gene variation and premature ovarian failure: a meta-analysis D. Pu a, Y. Xing a, Y. Gao b, L. Gu c, J. Wu a,* a
State Key Laboratory of Reproductive Medicine, Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China b Department of Obstetrics and Gynaecology, Huai’an First People’s Hospital, Huai’an, Jiangsu, China c Department of Obstetrics and Gynaecology, Nanjing Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Nanjing, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 7 April 2014 Received in revised form 12 July 2014 Accepted 23 September 2014
Objective: Premature ovarian failure (POF) is a complex, heterogeneous disorder that is influenced by multiple genetic components. This meta-analysis aimed to investigate the association between gene variants and susceptibility to POF. Study design: MEDLINE and CNKI were searched for studies published from inception (1950) to June 2014. Meta-analysis was performed when three or more studies reported genetic data on the same polymorphism or mutation. Additive and dominant models were analyzed using RevMan Version 5.1. Results: The literature search yielded 575 articles, of which 59 studies on the association between POF and gene variants were identified for meta-analysis. Five genes were selected for analysis, including 10 common gene polymorphisms [BMP15 (9C>G, 788insTCT and 852C>T), ESR1 (351A>G and 397C>T), FMR1 CGG repeat, FSHR (919A>G and 2039A>G), INHA (16C>T and 124A>G)] and two mutations (BMP15 538G>A and INHA 769G>A). BMP15 538G>A was found to be significantly more common in patients with POF compared with controls. No significant associations were found between the other variants of BMP15 and POF. With respect to ESR1, the accumulative results were not significant, although the findings of the individual studies were controversial. The incidence of FMR1 premutation was significantly higher in patients with POF compared with controls [odds ratio (OR) 9.2, 95% confidence interval (CI) 5.42–15.61; p < 0.001] in the overall population, as well as in both Caucasian and Asian subgroups. Stratified analysis was applied for INHA 769G>A by ethnicity; a significant association with POF was only found in the Asian subgroup (allelic frequency: OR 8.89, 95% CI 2.1–5.52; p = 0.004). No significant associations were found between the other variants of INHA and POF. Conclusions: BMP15 538A, FMR1 premutation and INHA 769A (in Asians alone) may indicate susceptibility to POF. Further well-designed studies and larger samples are required to confirm the association between gene variants and POF. ß 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: Premature ovarian failure BMP15 ESR1 FMR1 FSHR INHA
Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . Identification and eligibility of relevant studies Statistical analysis. . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Study characteristics. . . . . . . . . . . . . . . . . . . . . . Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BMP15 gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . ESR1 gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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* Corresponding author at: 300 Guangzhou Road, Nanjing, China. Tel.: +86 25 86214093; fax: +86 25 86214093. E-mail address: [email protected] (J. Wu). http://dx.doi.org/10.1016/j.ejogrb.2014.09.036 0301-2115/ß 2014 Elsevier Ireland Ltd. All rights reserved.
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D. Pu et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 182 (2014) 226–237
FMR1 gene . FSHR gene . . INHA gene . . Limitations . Funding . . . . . . . . . Acknowledgements References . . . . . . .
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Introduction Premature ovarian failure (POF) is defined as the cessation of ovarian function with follicle-stimulating hormone (FSH) concentrations exceeding 40 IU/l before 40 years of age, resulting in amenorrhoea, infertility and other systemic consequences (e.g. cardiovascular disease, osteoporosis) because of oestrogen deficiency [1]. Recently, the term ‘primary ovarian insufficiency’ (POI) has been proposed to reflect the continuum of altered ovarian function [2]. POF affects approximately 1% of women under 40 years of age [3]. In addition to environmental and iatrogenic factors, genetic background, auto-immunity and metabolism are thought to contribute to POF/POI. The exact aetiology of POF remains unknown, and various data indicate that POF has a strong genetic component. These data include the existence of several causal genetic defects in human, experimental and natural models. Familial POF research showed that 4–30% of all subjects with POF had a familial form [4], which implied a genetic predisposition to POF. Genetic causes of POF can be chromosomal or caused by single genes, involving the X chromosome or autosomes. There are many reports of mutations and polymorphisms in genes related to POF. Possible associations between gene polymorphisms and POF/POI have been investigated for several genes [5], including X-linked genes [e.g. fragile X mental retardation 1 (FMR1) and bone morphogenetic protein 15 (BMP15)] and autosomal genes [folliclestimulating hormone receptor (FSHR), luteinizing hormone receptor, inhibin alpha (INHA), forkhead box L2 and splicing factor 1, oestrogen receptor (ESR)]. Even mitochondrial DNA has been studied, and shown to have a close association with POF/POI [6]. However, these results remain controversial. The primary aim of this study was to perform a meta-analysis of the association between gene variants and POF in order to integrate the evidence for the risk of POF and genetic factors. Materials and methods Search strategy A literature search was performed to identify studies investigating the potential influence of any gene variant on POF. MEDLINE and CNKI were searched for all relevant published manuscripts from inception (1950) to June 2014 using the following keywords: ‘polymorphism’, ‘mutation’, ‘variant’, ‘variation’, ‘gene’, ‘premature ovarian failure’, ‘primary ovarian insufficiency’ and ‘premature menopause’. Identification and eligibility of relevant studies All data were extracted independently by two authors (DP and YX). Studies were included if they analyzed the association between any gene variant and POF/POI. POF was diagnosed as cessation of menstrual cycles for 4 months in women aged 40 years, with serum FSH level exceeding 40 IU/l at least twice 1 month apart. All included studies were peer-reviewed, published articles and there was no language restriction. In addition, studies
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235 235 235 235 235 236 236
were identified by a manual search of original publications from review articles. Studies were included in the meta-analysis if: (1) they were genetic association studies evaluating gene polymorphisms and POF, or gene mutations and POF; (2) patients with POF were diagnosed according to the following criteria [7]: 4 months of amenorrhoea and serum FSH levels exceeding 40 IU/l obtained twice 1 month apart in women aged 40 years; (3) they showed genotypic and/or allelic frequencies; (4) they were published studies; and (5) they were designed as case–control or cohort studies. Studies were excluded if: (1) they did not investigate the relationship between gene variants and POF; (2) they were review articles, animal studies, commentaries, case reports or unpublished reports; and (3) they were duplicate publications. Data on first author, publication year, location/ethnicity, sample size and genes were extracted for each study (Table 1). In addition, genotype distributions and/or allelic frequencies were extracted (Table 2). In cases where data were missing from published papers, relevant information was obtained by direct communication with the corresponding authors. Meta-analytic calculations were performed when three or more studies reported the same genetic variation. Statistical analysis Statistics were analyzed using RevMan Version 5.1 (Cochrane Collaboration, Copenhagen, Denmark). The association between gene variants and the risk of POF was expressed using odds ratios (ORs) and 95% confidence intervals (CIs). The statistical significance of pooled ORs was evaluated using Z-test. Two comparisons were performed: allelic frequency and dominant genetic model between cases and controls. The meta-analysis was stratified by ethnicity if data were available. A test of heterogeneity between the studies was conducted using a x2-based Q-test [8]. Statistical heterogeneity was assessed using I2. I2 > 50% was taken to indicate substantial heterogeneity [9]. If substantial heterogeneity was detected, a random effects model was used instead of a fixed effects model. The significance analysis of intercept was calculated by t-test, and p < 0.05 was considered to indicate significance. Results Study characteristics The literature search yielded 575 articles. Review articles (n = 119), studies that were not related to human research (n = 57), studies that did not have a case–control/cohort/randomized design (n = 62), studies that were not related to POF/POI (n = 110), and studies that were not available for meta-analysis because of fewer than three articles on the same gene polymorphism locus (n = 146) were excluded. After reading the full text of the remaining papers, six were excluded because of duplication, 11 were excluded due to lack of data after efforts to contact the authors, and five articles were excluded as they did not present the required single nucleotide polymorphism (SNP)/mutant site. Fifty-nine studies
228
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Table 1 Characteristics of studies included in the meta-analysis. Study
Location
Cases
Takebayashi et al. (2000) Di Pasquale et al. (2006) Dixit et al. (2006a) Laissue et al. (2006) Zhang et al. (2007) Ledig et al. (2008) Tiotiu et al. (2010) Wang et al. (2010) Ma et al. (2012) Ferrarini et al. (2013)
Japan America and Europe India France and Finland China Germany Belgium China China Italy
15 166 133 203 92 20 50 100 63 50
3 95 197 54 76 127 214 100 62 150
Bretherick et al. (2008)
Canada
55
27
Yoon et al. (2010) Yang et al. (2010) Cordts et al. (2012) Li et al. (2013) Liu et al. (2013) Kenneson et al. (1997) Syrrou et al. (1999) Bussani et al. (2004) Bretherick et al. (2005) Bodega et al. (2006) Costa et al. (2006) Chatterjee et al. (2009) Fic¸icioglu et al. (2010) Ishizuka et al. (2011) Schuettler et al. (2011) Barasoain et al. (2013) Lai et al. (2013) Lin et al. (2013) De Geyter et al. (2014) Murray et al. (2014) Tosh et al. (2014) Ye et al. (2014) da Fonte Kohek et al. (1998) Layman et al. (1998) Liu et al. (1998) Conway et al. (1999) Takakura et al. (2001) Tong et al. (2001) Sundlblad et al. (2004) Loutradis et al. (2006) Vilodre et al. (2008) Prakash et al. (2009) Du et al. (2010) Kim et al. (2011a) Chen et al. (2012) Woad et al. (2013) Shelling et al. (2000) Marozzi et al. (2002) Dixit et al. (2006b) Jeong et al. (2004) Chen et al. (2004) Sundblad et al. (2006) Chen et al. (2006) Woad et al. (2009)
Korea Korea Brazil Serbia China USA Greece Italy Canada Italy Brazil India Turkey Japan German Spain Hong Kong China Switzerland UK India China Brazil USA USA UK Japan Singapore Argentina Greek Brazil India China Korea China New Zealand Several countries (New Zealand, Slovenia) Italy Hyderabad Korea China Argentina China New Zealand Slovenia Central Italian Northern Italian German India Korea Korea
126 46 70 197 155 33 23 45 53 190 41 78 9 128 74 7 196 85 48 254 289 117 15 35 5 49 15 16 15 33 36 50 40 98 63 80 43 92 133 84 34 43 77 56 138 169 299 143 50 52 159
221 200 73 547 155 107 100 28 161 200 96 70 40 98 42 32 204 80 199 1915 360 82 42 10 4 51 3 236 44 20
Corre et al. (2009)
Prakash et al. (2010) Kim et al. (2011b) Yoon et al. (2012)
Controls
50 92 218 58 80 150 100 200 100 125 82 35 114 48 395 387 302 50 55 233
Gene BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 FMR1 ESR1 FSHR ESR1 ESR1 ESR1 ESR1 ESR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR INHA INHA INHA INHA INHA INHA INHA INHA INHA
INHA INHA INHA
BMP15, bone morphogenetic protein 15; ESR1, oestrogen receptor a; FMR1, fragile X mental retardation 1; FSHR, follicle-stimulating hormone receptor; INHA, inhibin alpha. Criteria for diagnosing premature ovarian failure: 4 months of amenorrhoea and serum follicle-stimulating hormone levels of 40 IU/l twice, obtained 1 month apart, in women aged A; p. Ala180Thr (mutation) 161 5 0 327
5
132 201 18 48 49
2 2 1
Cases
1 2 2 2 1
0 0 0
38 98 99
Cases
129 193 95 47 61
4 10 5 3 2
Cases TT
Article
Cases
Article
ESR1 2008 2008 2010 2010 2010 2012 2013 2013
Bretherick (1) Bretherick (2) Yang (1) Yang (2) Yoon Cordts Li Liu
Article
FMR1 1997 Kenneson 1999 Syrrou 2004 Bussani 2005 Bretherick 2006 Bodega 2006 Costa 2009 Chatterjee 2010 Bennett
37 33 49 3 63 3
0 10 1
149 345 119
3 83 5
GG
AG
AA
G allele
A allele
95 116 197 54 126 212 150
0 0 0 0 1 2 0
0 0
190 232
0 0
0 0 0
426 300
2 0
Wild
Mutant
90 116 193 45 85 209 62
5 0 4 9 15 5 0
T allele
CC
CT
TT
C allele
T allele
29
1 177 54 2 209 3
3 20 0 76 5 60
0
0
6
0
0
0
152
0
2
0
122
2
182 123
Controls CT/Pp
TT/pp
C allele
23 31 59
T allele
CC/PP
CT/Pp
TT/pp
C allele
T allele
45
20 4 28
48 14 106
39 9 66
88 22 162
126 32 238
46 52 134 10
117
209
233
267 69
58 21 146 76
535 89
559 221
33 55 89
59 53 163
99 74
18 11 52 10 58 59
179 118
215 192
AG/xX
GG/XX
A allele
G allele
AA/xx
AG/xX
GG/XX
A allele
G allele
56
49 13 90
47 12 102
11 2 8
145 38 282
69 16 118
133 65 210 116
77
11 8 82 6
343
99
675 265
419 45
Cases
Controls
Promoter: c. 351A>G, Xbal x>X (rs9340799) 7 40 8 54 24 34 78 64 81 95
G allele
C allele
Promoter: c.397T>C, Pvull p>P (rs2234693) 13 39 3 65
AA/xx
C allele
Controls CC
Exon 2: c.852C>T; silent (rs17003221) 14 1 0 124 9 199 4 90 2 0 47 3 60 3 0
5 12 15 60 40 22
GG
Controls Mutant
Exon 2: c. 788insTCT; p. 262insLeu (rs79377927) 164 2
CC/PP
CG
Controls
BMP15 2000 Takebayashi 2006a Dixit 2006 Laissue 2007 Zhang 2010 Tiotiu 2012 Ma
Bretherick (1) Bretherick (2) Yang (1) Yang (2) Yoon Cordts Li Liu
58 83 148 73 141 58
0 5 0
CC
ESR1 2008 2008 2010 2010 2010 2012 2013 2013
CC
44 4 12 5
Wild BMP15 2006 Di Pasquale (1) 2006 Di Pasquale (2) 2006a Dixit 2006 Laissue 2010 Wang 2010 Tiotiu 2012 Ma
G allele
Promoter: c. 9C>G (rs3810682) 144 22
GG BMP15 2006 Di Pasquale (1) 2006 Di Pasquale (2) 2006a Dixit 2006 Laissue 2008 Ledig 2010 Tiotiu 2013 Ferrarini
Controls CG
21 17 43 92 55
1 3 5 6 24 5
69 85 199
23 23 53
254 245
140 65
Cases
255 33
Controls
Total
Premutation
Total
Premutation
Exon 1: CGG repeats 33 23 45 53 190 41 78 732
0 1 3 2 19 3 0 18
107 100 28 161 200 96 70 2779
1 0 0 1 0 0 0 7
230
D. Pu et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 182 (2014) 226–237
Table 2 (Continued ) Article
2010 2011 2011 2011 2013 2013 2013 2013 2014 2014 2014 2014
Fic¸icioglu Ishizuka Karimov Schuettler Barasoain Ferrarini Lai Lin De Geyter Murray Tosh Ye
Article
Cases Total
Premutation
Total
Premutation
9 128 535 45 7 50 392 85 48 254 286 117
0 2 7 2 0 4 7 0 1 5 0 1
40 98 521 42 32 150 408 80 199 1915 360 82
0 0 1 0 0 0 0 0 1 7 0 0
Cases CC
FSHR 1998 da Fonte Kohek 1998 Layman 1998 Liu 2001 Takakura 2001 Tong 2004 Sundblad 2006 Loutradis 2009 Prakash 2013 Woad Article
Article
Article
Article
9 20 33 28
T allele
CC
CT
TT
C allele
T allele
0 0 0 0 0 0 0 0 0
42 10 5 3 236 44 20 50 80
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
84 20 10 6 472 88 40 100 160
0 0 0 0 0 0 0 0 0
Controls AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
16
13 3 102
24 1 110
5
50
34
24
13 40 28 25
24 37 25 38
5 15 5 17
314 48 124 26 50 117 81 88
158 40 90 28 34 67 35 72
15 14 41
19 18 25 34
7 2 5 18
37 58 91 90
33 22 35 70
AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
Exon 10: c. 2039A>G; p. Asn680Ser (rs6166) 5 7 3 17 57 5 11 0 21 16 72
13 41 11 14 38
13
24
5
91
132
13
15 16 23 31 29
13 40 67 32 26
24 34 89 22 37
5 16 20 4 17
50 61 314 48 124 27 50 114 223 86 89
34 41 158 40 90 27 34 66 129 30 71
Cases
Controls
15 19 51 30 33
5 2 9 2 18
45 51 97 92 91
25 23 69 34 69
AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
81 344 349 261 40 111 58 112
110
74
16
39 12 2 78
51 24 29 113
24 12 24 42
294 190 326 166 129 48 33 269
106 148 272 120 99 48 77 197
Cases
Controls
Promoter: c. 124A>G (rs11893842) 66 53 14 185 446 425 343 21 30 5 72 48 69 21 165 7 32 13 46 65 76 18 206
Cases CC
INHA 2002 Marozzi 2006b Dixit 2006 Sundblad (1) 2009 Corre (1) 2009 Corre (2) 2009 Corre (3)
C allele
Exon 10: c. 919A>G; p. Thr307Ala (rs6165) 3 8 4 14 2 3 2 13 1 17 16 69
AA INHA 2006b Dixit 2009 Corre (1) 2009 Corre (2) 2009 Corre (3) 2009 Woad (1) 2009 Woad (2) 2011b Kim 2012 Yoon
TT
Cases
AA FSHR 1998 da Fonte Kohek 1999 Conway 2001 Tong 2004 Sundblad 2008 Bretherick (1) 2008 Bretherick (2) 2008 Vilodre 2010 Du 2011a Kim 2012 Chen 2013 Woad
Controls CT
Exon 7: c. 566C>T; p. Ala189Val (mutation) 15 0 0 30 35 0 0 70 5 0 0 10 15 0 0 30 16 0 0 32 15 0 0 30 33 0 0 66 50 0 0 100 80 0 0 160
AA FSHR 1998 de Fonte Kohek 1998 Liu 2001 Tong 2004 Sundblad 2008 Bretherick (1) 2008 Bretherick (2) 2008 Vilodre 2010 Du 2012 Chen 2013 Woad
Controls
Controls CT
TT
Promoter: c. 16C>T (rs35118453) 114 28 117 16 22 18 3
C allele
62 644 631 476
T allele
24 146 143 128
CC
CT
TT
C allele
T allele
46 174 49
23 26 29
4
127 278 477 237
37 60 121 49
D. Pu et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 182 (2014) 226–237
231
Table 2 (Continued ) Cases
Article
2009 Woad (1) 2009 Woad (2) 2011b Kim 2012 Yoon
Controls
CC
CT
TT
C allele
T allele
CC
CT
TT
C allele
T allele
42 87 44 110
14 47 8 44
0 4 1 5
98 221 96 264
14 55 10 54
70 31 54 153
39 16 1 68
5 1 0 12
179 78 109 374
49 18 1 92
AG
AA
G allele
A allele
GG
AG
AA
G allele
A allele
3
149 100 125 100 35 199 74 67 357 364 287 48 55
1 0 0 0 0 1 2 6 37 23 15 2 0
0
299 200 250 200 70 399 150 140 751 751 589 98 110
1 0 0 0 0 1 2 6 39 23 15 2 0
Cases
Article
GG INHA 2000 Shelling 2002 Marozzi 2004 Chen 2004 Jeong 2006 Chen 2006b Dixit 2006 Sundblad (1) 2006 Sundblad (2) 2009 Corre (1) 2009 Corre (2) 2009 Corre (3) 2010 Prakash 2011b Kim
Controls
Exon 2: c. 769G>A, p. Ala257Thr (mutation) 40 3 0 83 150 7 32 2 0 66 84 0 0 168 77 0 0 154 119 13 1 251 42 0 0 84 166 285 139 44 52
3 14 4 6 0
0 0 0 0 0
172 313 147 94 104
2 0 0 15 0 3 14 4 6 0
0 0 0 0 0 0 1 0 0 0 0
BMP15, bone morphogenetic protein 15; ESR1, oestrogen receptor a; FMR1, fragile X mental retardation 1; FSHR, follicle-stimulating hormone receptor; INHA, inhibin alpha. 2006 Di Pasquale (1): controls were women who were menopausal at >50 years of age; 2006 Di Pasquale (2): controls were general population. 2006 Sundblad (1): controls were women with normal menstruation history aged >40 years; 2006 Sundblad (2): controls were women with normal menstruation history aged G rs3810682 538G>A
ESR1
FMR1
FSHR
INHA
788insTCT rs79377927 852C>T rs17003221 PvuII (397T>C) rs2234693 XbaI (351A>G) rs9340799 CGG repeats
919A>G rs6165 2039G>A rs6166 124A>G 16C>T 769G>A
No. of studies 3 4 4 6 6 3 6 5 5 5 5 18 10 7 1 8 7 10 7 7 5 8 7 11
12
Comparisons
OR [95% CI]
Allele frequency Dominant model Allele frequency Dominant model Mutant vs wild-type
G vs C CG+GG vs CC A vs G AA+AG vs GG
1.14 1.28 6.89 5.22 0.65
Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Premutation vs normal/intermediate Caucasian dominant Asian dominant Other Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Allele frequency Caucasian dominant Asian dominant Dominant model Caucasian dominant Asian dominant
T vs C CT+TT vs CC C vs T CC+CT vs TT G vs A AG+GG vs AA
1.73 1.06 1.02 0.99 1.13 1.30 8.68 9.17 5.58 17.55 0.96 1.10 0.97 1.12 0.94 0.85 1.00 0.88 2.00 1.08 8.89 1.93 0.85 8.95
G vs A AG+GG vs AA A vs G AG+AA vs GG G vs A AG+GG vs AA T vs C CT+TT vs CC A vs G
AG+AA vs GG
I2 (%)
p
(0.71–1.81) (0.89–1.83) (1.84–25.80) (1.65–16.54) (0.25–1.66)
0 0 0 0 62
0.59 0.19 0.004 0.005 0.37
(0.44–6.89) (0.58–1.93) (0.70–1.49) (0.58–1.69) (0.81–1.57) (0.79–2.14) (4.40–17.12) (4.30–19.52) (1.01–30.79) (0.89–347.74) (0.78–1.20) (0.78–1.54) (0.81–1.17) (0.83–1.49) (0.84–1.05) (0.66–1.09) (0.87–1.16) (0.60–1.30) (0.75–5.33) (0.44–2.67) (2.10–37.68) (0.65–5.73) (0.30–2.44) (2.23–35.92)
0 0 81 63 68 78 0 0 0 0 28 22 0 0 31 37 49 52 69 56 29 75 66 23
0.43 0.85 0.92 0.96 0.47 0.31 G, 538G>A, 788insTCT and/or 852C>T, involving 892 patients with POF and 1078 controls [11,16–24]. No significant differences in BMP15-9C>G, 788insTCT or 852C>T polymorphisms were found between patients with POF and controls (p > 0.05). Laissue et al. [18] and Tiotiu et al. [21] found that 788insTCT was a common polymorphism in populations of African origin. 538G>A mutation was significantly more common in patients with POF than in controls (A allele vs G allele: OR 6.89, 95% CI 1.84–25.80, p = 0.004; AA+AG vs GG: OR 5.22, 95% CI 1.65–16.54, p = 0.005; Table 3 and Fig. 2.) Six studies [10,13,25–28] investigated ESR1-397C>T and 351A>G polymorphisms, including 649 cases and 1223 controls. No significant difference was found between the patients with POF and controls (p > 0.05; Table 3). Eighteen papers examined the relationship between FMR1 CGG repeat polymorphism and the risk of POF, including 1720 cases and 3964 controls [24,29–45]. FMR1 premutation (CGG repeat number ranging from 55 to 200) was significantly more common in patients with POF compared with controls (OR 9.20, 95% CI 5.42– 15.61; p < 0.001]. Where possible, the meta-analysis was stratified into three subgroups: predominantly Caucasian (10 studies), predominantly Asian (seven studies) and other ethnicity (one study from Brazil). In both the Caucasian and Asian populations, FMR1 premutation was significantly more common in patients
with POF than in controls [Caucasian: OR 9.37, 95% CI 5.35–16.41, p < 0.001; Asian: OR 6.83, 95% CI 1.27–36.73, p = 0.03; Table 3 and Fig. 3]. Concerning FSHR, 15 studies [10,14,21,46–57] related to two polymorphisms (919A>G and 2039A>G) were available for analysis, involving 605 cases and 935 controls. As shown in Table 3, no significant differences were found between the patients with POF and controls (p > 0.05). Twelve studies [12,23,58–67] investigated INHA-124A>G, 16C>T and 769G>A polymorphisms, involving 1572 cases and 2376 controls. Only 769G>A mutation was suitable for stratification analysis, and Caucasian-dominant and Asian-dominant subgroups were used. The 769A allele was found to be significantly more common in patients with POF in the Asian subgroup [A allele vs G allele: OR 8.89, 95% CI 2.10–37.68, p = 0.003; dominant model: OR 8.95, 95% CI 2.23–35.92, p = 0.002; detailed in Table 3 and Fig. 4], but this was not seen in the Caucasian subgroup. No significant differences in the incidence rates of INHA-124A>G and 16C>T were found between the patients with POF and controls (Table 3). Comments Many studies have investigated the correlation between gene variants and the risk of POF/POI, but the results from individual studies were inconsistent. Therefore, a meta-analysis was conducted when at least three studies had been undertaken on the same gene locus. Accumulative analysis was performed for five genes: BMP15, ESR1, FMR1, FSHR and INHA. BMP15 gene BMP15 is a member of the transforming growth factor b (TGFb) family, located on Xp11.2. In ovarian folliculogenesis, BMP15 is
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Fig. 2. Association between bone morphogenetic protein 15 538G>A mutation and risk of premature ovarian failure (POF). (A) Frequency of A allele vs G allele, (B) dominant model comparison AG+AA vs GG. Di Pasquale (1) 2006: controls were women who were menopausal at >50 years of age; Di Pasquale (2) 2006: controls were general population.
Fig. 3. Association between fragile X mental retardation 1 premutation and risk of premature ovarian failure.
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Fig. 4. Association between inhibin alpha 769G>A mutation and risk of premature ovarian failure. (A) Allelic frequency comparison A vs G, (B) dominant model comparison AA+AG vs GG. Sundblad (1) 2006: controls were normal menopausal women; Sundblad (2) 2006: controls were normal menstruating women; Corre (1) 2009: cases and controls were Central Italian; Corre (2) 2009: cases and controls were Northern Italian; Corre (3) 2009: cases and controls were German. Condensation BMP15 538A, FMR1 premutation and INHA 769A (in Asians alone) may indicate susceptibility to premature ovarian failure.
a key regulating factor of granulosa cell biological processes, and is therefore a candidate gene for POF [11]. An association between BMP15 mutations and the risk of POF has been reported, which may impair the mature peptide and cause a dramatic reduction in the amount or bioactivity of protein [68]. Ten studies were included in the meta-analysis and the results showed no direct association between BMP15-9G or 852T (two common SNPs) and the development of POF, which is consistent with previous studies [16,19,23]. The mutation 538G>A (Ala180Thr) was found to increase the risk of POF, which is in agreement with Ledig et al. [20]. Women with the 538A mutation are up to five times more likely to develop POF than women without this mutation. However, in vitro studies did not detect marked deleterious
effects on BMP15 [21,69]. The insertion of three nucleotides (788insTCT) leading to insertion of leucine at position 263 was analyzed in six studies. This polymorphism has been reported to have low biological impact [69] because it was identified in both cases and controls, and is very common in populations of African origin [18,21]. ESR1 gene The ESR1 gene is another candidate genes for POF, located on 6q25.1. It encodes ERa, one of the most important factors in human reproduction [55]. The relationships between ESR1-397T>C and 351A>G and the risk of POF were of interest, but the results from
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individual studies were conflicting. Some researchers found that ESR1 polymorphisms could increase the risk of POF significantly [10,28], others detected no relationship between them [13,70], and others found that the SNPs might reduce the risk [25]. For both 351A>G and 397T>C, Bretherick et al. [10] and Liu [28] found that the 351G and 397C alleles were associated with the risk of POF among Caucasians and Chinese Han, respectively. However, contrasting results were reported by Yoon et al. [25] for 397T>C among Koreans. In the present analysis, accumulated results found no significant association between ESR1-397T>C and 351A>G and POF. A previous study reported that the presence of the 397C allele may significantly increase downstream reporter activity compared with the 397T allele, indicating that this SNP could affect a functional binding site for the myb family of transcription factors, and decrease ERa expression [71]. Another report found that the 397CC genotype decreased ESR1 mRNA, and reduced ERa bioactivity [72]. FMR1 gene The FMR1 gene is mapped to the X chromosome at position q27.3, which contains an unstable CGG repeat in the 50 untranscribed region of the first exon [73]. The repeat length is variable in the general population, ranging from six to 55 repeats. The American College of Medical Genetics currently defines the borders between genotypic classes as follows: 5–44 repeats, normal; 45–54 repeats, intermediate; 55–200 repeats, premutation; and 200–230 repeats, full mutation [74]. It has been reported that full mutations cause fragile X syndrome and that premutations are associated with fragile X tremor and ataxia syndrome and POF [75,76]. Concerning the relationship between CGG repeat and POF, some studies have shown that amplification of the number of CGG repeats above the normal range, from intermediate to premutation status, represents a high risk factor for POF [77–79]. In FMR1 premutation carriers, it has been found that FMR1 protein expression was decreased by blocking the translation of FMR1 message [80]. FMR1 protein is reported to be involved in oocyte and synaptic function, and a reduced FMR1 protein level is thought to alter the expression of oocyte developing related genes, resulting in POF [5,80]. However, the results were conflicting. The present study included 20 studies on the association between FMR1 premutation and the risk of POF/POI. The meta-analysis indicated significant correlation between FMR1 premutation and higher risk of POF in the overall population, as well as in the stratified subgroups (Caucasians and Asians). The findings are generally in agreement with Tosh et al., who pooled 11 studies for meta-analysis [44]. FSHR gene The FSHR gene is a member of the family of G protein-coupled receptors, located on chromosome 2p21 [81]. FSH is very important in human reproduction, including gonadal development and sexual maturation during the fertile period [81]. FSH action is mediated by the FSHR which is expressed in the granulosa cells of the ovary. The finding that FSHR 566C>T mutation led to amino acid substitution of Ala189Val and played an important role in the development of POF was first made in a Finnish population [82]. The present study included nine published articles [15,46,47,49–53,57] that concerned this mutation. Unfortunately, no such mutation was found in any subjects of these studies (patients or controls). In addition, two well-known SNPs, 919A>G (Thr307Ala) and 2039A>G (Asn680Ser) [81], were analyzed in 11 studies, and the results found that neither of these SNPs had a direct role in the development of POF,
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which is consistent with a previous meta-analysis [54]. Position 307 is known to code for amino acid in the transmembrane region of the FSHR protein, while position 680 is located in the intracellular region. Both are critical for the hormone-binding ability of FSHR and FSH-mediated signal transduction in infertile women undergoing ovarian stimulation [83,84]. Several studies have observed that women with homozygous 680Ser/Ser with or without 307Ala/Ala appear to have a higher basal level of FSH, which is associated with decreased ovarian reserve [85–87]. It has been reported that FSHR 919A>G is usually linked to 2039A>G; however, the linkage analysis of the two SNPs did not perform for few data. Interestingly, Kim et al. [55] found that the combined genetic effect of CYP19A1 rs4646 (CA+AA) and FSHR 2039 (AG+GG) genotype may be related to the risk of POF. INHA gene Inhibin is a member of the TGFb superfamily. Two forms of inhibin exist in human tissue: inhibin A (a-bA) and inhibin B (abB). Inhibin A is encoded by the INHA gene, located on 2q33-q36. Inhibin regulates FSH secretion by inhibition of the HPO axis in order to ensure the normal menstrual cycle and scheduled ovulation [88]. The present meta-analysis examined the relationship between INHA-124A>G, 16C>T and 769G>A gene variants and the risk of POF by summarizing 12 studies. This updates the analyses of Zintzaras [89] (pooled six studies) and Chand et al. [90] (pooled five studies). Chand [90] found that the 769G>A mutation alone was correlated with POF. The present study did not find an association between INHA-124A>G and 16C>T and the risk of POF, in contrast to Kim et al. [66] who found that 16C>T polymorphism was associated with increased risk of POF. Individual studies showed controversial results for 769G>A mutation. After performing the stratified analysis by ethnicity, Asian women with the 769A allele were found to be susceptible to POF, while no such relationship was found for the Caucasian population. This result is consistent with Chand et al.’s metaanalysis [90]. Previous in vitro studies have found that 769G>A (Ala257Thr) mutation may impair the bioactivity of inhibin B [91]. Limitations This study has several limitations. First, the main limitation is the small study/sample size for meta-analysis. Secondly, stratification analyses by ethnicity or region were only performed for FMR1 premutation and INHA 769G>A mutation because of insufficient studies or deficient data from the primary studies. Thirdly, some studies evaluated the relationship between FMR1 CGG intermediate repeat and POF, but were not eligible for the meta-analysis because of an inconsistent definition of intermediate repeats. Despite these limitations, the findings of this meta-analysis did find associations between gene (BMP15, ESR1, FMR1, FSHR and INHA) polymorphisms and the risk of POF/POI. This study found that BMP15 538G>A mutation, FMR1 premutation and INHA-769G>A mutation (in Asians alone) were associated with increased susceptibility to POF. Further welldesigned studies and larger samples are required to confirm the association between gene variants and POF.
Funding This study was supported by a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, and Jiangsu Province Women and Children Health Program (Grant No. FXK201201, FRC201201).
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European Journal of Obstetrics & Gynecology and Reproductive Biology journal homepage: www.elsevier.com/locate/ejogrb
Review
Gene variation and premature ovarian failure: a meta-analysis D. Pu a, Y. Xing a, Y. Gao b, L. Gu c, J. Wu a,* a
State Key Laboratory of Reproductive Medicine, Department of Obstetrics and Gynaecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China b Department of Obstetrics and Gynaecology, Huai’an First People’s Hospital, Huai’an, Jiangsu, China c Department of Obstetrics and Gynaecology, Nanjing Maternity and Child Health Care Hospital Affiliated to Nanjing Medical University, Nanjing, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 7 April 2014 Received in revised form 12 July 2014 Accepted 23 September 2014
Objective: Premature ovarian failure (POF) is a complex, heterogeneous disorder that is influenced by multiple genetic components. This meta-analysis aimed to investigate the association between gene variants and susceptibility to POF. Study design: MEDLINE and CNKI were searched for studies published from inception (1950) to June 2014. Meta-analysis was performed when three or more studies reported genetic data on the same polymorphism or mutation. Additive and dominant models were analyzed using RevMan Version 5.1. Results: The literature search yielded 575 articles, of which 59 studies on the association between POF and gene variants were identified for meta-analysis. Five genes were selected for analysis, including 10 common gene polymorphisms [BMP15 (9C>G, 788insTCT and 852C>T), ESR1 (351A>G and 397C>T), FMR1 CGG repeat, FSHR (919A>G and 2039A>G), INHA (16C>T and 124A>G)] and two mutations (BMP15 538G>A and INHA 769G>A). BMP15 538G>A was found to be significantly more common in patients with POF compared with controls. No significant associations were found between the other variants of BMP15 and POF. With respect to ESR1, the accumulative results were not significant, although the findings of the individual studies were controversial. The incidence of FMR1 premutation was significantly higher in patients with POF compared with controls [odds ratio (OR) 9.2, 95% confidence interval (CI) 5.42–15.61; p < 0.001] in the overall population, as well as in both Caucasian and Asian subgroups. Stratified analysis was applied for INHA 769G>A by ethnicity; a significant association with POF was only found in the Asian subgroup (allelic frequency: OR 8.89, 95% CI 2.1–5.52; p = 0.004). No significant associations were found between the other variants of INHA and POF. Conclusions: BMP15 538A, FMR1 premutation and INHA 769A (in Asians alone) may indicate susceptibility to POF. Further well-designed studies and larger samples are required to confirm the association between gene variants and POF. ß 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: Premature ovarian failure BMP15 ESR1 FMR1 FSHR INHA
Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . Identification and eligibility of relevant studies Statistical analysis. . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Study characteristics. . . . . . . . . . . . . . . . . . . . . . Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . BMP15 gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . ESR1 gene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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* Corresponding author at: 300 Guangzhou Road, Nanjing, China. Tel.: +86 25 86214093; fax: +86 25 86214093. E-mail address: [email protected] (J. Wu). http://dx.doi.org/10.1016/j.ejogrb.2014.09.036 0301-2115/ß 2014 Elsevier Ireland Ltd. All rights reserved.
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FMR1 gene . FSHR gene . . INHA gene . . Limitations . Funding . . . . . . . . . Acknowledgements References . . . . . . .
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Introduction Premature ovarian failure (POF) is defined as the cessation of ovarian function with follicle-stimulating hormone (FSH) concentrations exceeding 40 IU/l before 40 years of age, resulting in amenorrhoea, infertility and other systemic consequences (e.g. cardiovascular disease, osteoporosis) because of oestrogen deficiency [1]. Recently, the term ‘primary ovarian insufficiency’ (POI) has been proposed to reflect the continuum of altered ovarian function [2]. POF affects approximately 1% of women under 40 years of age [3]. In addition to environmental and iatrogenic factors, genetic background, auto-immunity and metabolism are thought to contribute to POF/POI. The exact aetiology of POF remains unknown, and various data indicate that POF has a strong genetic component. These data include the existence of several causal genetic defects in human, experimental and natural models. Familial POF research showed that 4–30% of all subjects with POF had a familial form [4], which implied a genetic predisposition to POF. Genetic causes of POF can be chromosomal or caused by single genes, involving the X chromosome or autosomes. There are many reports of mutations and polymorphisms in genes related to POF. Possible associations between gene polymorphisms and POF/POI have been investigated for several genes [5], including X-linked genes [e.g. fragile X mental retardation 1 (FMR1) and bone morphogenetic protein 15 (BMP15)] and autosomal genes [folliclestimulating hormone receptor (FSHR), luteinizing hormone receptor, inhibin alpha (INHA), forkhead box L2 and splicing factor 1, oestrogen receptor (ESR)]. Even mitochondrial DNA has been studied, and shown to have a close association with POF/POI [6]. However, these results remain controversial. The primary aim of this study was to perform a meta-analysis of the association between gene variants and POF in order to integrate the evidence for the risk of POF and genetic factors. Materials and methods Search strategy A literature search was performed to identify studies investigating the potential influence of any gene variant on POF. MEDLINE and CNKI were searched for all relevant published manuscripts from inception (1950) to June 2014 using the following keywords: ‘polymorphism’, ‘mutation’, ‘variant’, ‘variation’, ‘gene’, ‘premature ovarian failure’, ‘primary ovarian insufficiency’ and ‘premature menopause’. Identification and eligibility of relevant studies All data were extracted independently by two authors (DP and YX). Studies were included if they analyzed the association between any gene variant and POF/POI. POF was diagnosed as cessation of menstrual cycles for 4 months in women aged 40 years, with serum FSH level exceeding 40 IU/l at least twice 1 month apart. All included studies were peer-reviewed, published articles and there was no language restriction. In addition, studies
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were identified by a manual search of original publications from review articles. Studies were included in the meta-analysis if: (1) they were genetic association studies evaluating gene polymorphisms and POF, or gene mutations and POF; (2) patients with POF were diagnosed according to the following criteria [7]: 4 months of amenorrhoea and serum FSH levels exceeding 40 IU/l obtained twice 1 month apart in women aged 40 years; (3) they showed genotypic and/or allelic frequencies; (4) they were published studies; and (5) they were designed as case–control or cohort studies. Studies were excluded if: (1) they did not investigate the relationship between gene variants and POF; (2) they were review articles, animal studies, commentaries, case reports or unpublished reports; and (3) they were duplicate publications. Data on first author, publication year, location/ethnicity, sample size and genes were extracted for each study (Table 1). In addition, genotype distributions and/or allelic frequencies were extracted (Table 2). In cases where data were missing from published papers, relevant information was obtained by direct communication with the corresponding authors. Meta-analytic calculations were performed when three or more studies reported the same genetic variation. Statistical analysis Statistics were analyzed using RevMan Version 5.1 (Cochrane Collaboration, Copenhagen, Denmark). The association between gene variants and the risk of POF was expressed using odds ratios (ORs) and 95% confidence intervals (CIs). The statistical significance of pooled ORs was evaluated using Z-test. Two comparisons were performed: allelic frequency and dominant genetic model between cases and controls. The meta-analysis was stratified by ethnicity if data were available. A test of heterogeneity between the studies was conducted using a x2-based Q-test [8]. Statistical heterogeneity was assessed using I2. I2 > 50% was taken to indicate substantial heterogeneity [9]. If substantial heterogeneity was detected, a random effects model was used instead of a fixed effects model. The significance analysis of intercept was calculated by t-test, and p < 0.05 was considered to indicate significance. Results Study characteristics The literature search yielded 575 articles. Review articles (n = 119), studies that were not related to human research (n = 57), studies that did not have a case–control/cohort/randomized design (n = 62), studies that were not related to POF/POI (n = 110), and studies that were not available for meta-analysis because of fewer than three articles on the same gene polymorphism locus (n = 146) were excluded. After reading the full text of the remaining papers, six were excluded because of duplication, 11 were excluded due to lack of data after efforts to contact the authors, and five articles were excluded as they did not present the required single nucleotide polymorphism (SNP)/mutant site. Fifty-nine studies
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Table 1 Characteristics of studies included in the meta-analysis. Study
Location
Cases
Takebayashi et al. (2000) Di Pasquale et al. (2006) Dixit et al. (2006a) Laissue et al. (2006) Zhang et al. (2007) Ledig et al. (2008) Tiotiu et al. (2010) Wang et al. (2010) Ma et al. (2012) Ferrarini et al. (2013)
Japan America and Europe India France and Finland China Germany Belgium China China Italy
15 166 133 203 92 20 50 100 63 50
3 95 197 54 76 127 214 100 62 150
Bretherick et al. (2008)
Canada
55
27
Yoon et al. (2010) Yang et al. (2010) Cordts et al. (2012) Li et al. (2013) Liu et al. (2013) Kenneson et al. (1997) Syrrou et al. (1999) Bussani et al. (2004) Bretherick et al. (2005) Bodega et al. (2006) Costa et al. (2006) Chatterjee et al. (2009) Fic¸icioglu et al. (2010) Ishizuka et al. (2011) Schuettler et al. (2011) Barasoain et al. (2013) Lai et al. (2013) Lin et al. (2013) De Geyter et al. (2014) Murray et al. (2014) Tosh et al. (2014) Ye et al. (2014) da Fonte Kohek et al. (1998) Layman et al. (1998) Liu et al. (1998) Conway et al. (1999) Takakura et al. (2001) Tong et al. (2001) Sundlblad et al. (2004) Loutradis et al. (2006) Vilodre et al. (2008) Prakash et al. (2009) Du et al. (2010) Kim et al. (2011a) Chen et al. (2012) Woad et al. (2013) Shelling et al. (2000) Marozzi et al. (2002) Dixit et al. (2006b) Jeong et al. (2004) Chen et al. (2004) Sundblad et al. (2006) Chen et al. (2006) Woad et al. (2009)
Korea Korea Brazil Serbia China USA Greece Italy Canada Italy Brazil India Turkey Japan German Spain Hong Kong China Switzerland UK India China Brazil USA USA UK Japan Singapore Argentina Greek Brazil India China Korea China New Zealand Several countries (New Zealand, Slovenia) Italy Hyderabad Korea China Argentina China New Zealand Slovenia Central Italian Northern Italian German India Korea Korea
126 46 70 197 155 33 23 45 53 190 41 78 9 128 74 7 196 85 48 254 289 117 15 35 5 49 15 16 15 33 36 50 40 98 63 80 43 92 133 84 34 43 77 56 138 169 299 143 50 52 159
221 200 73 547 155 107 100 28 161 200 96 70 40 98 42 32 204 80 199 1915 360 82 42 10 4 51 3 236 44 20
Corre et al. (2009)
Prakash et al. (2010) Kim et al. (2011b) Yoon et al. (2012)
Controls
50 92 218 58 80 150 100 200 100 125 82 35 114 48 395 387 302 50 55 233
Gene BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 BMP15 FMR1 ESR1 FSHR ESR1 ESR1 ESR1 ESR1 ESR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FMR1 FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR FSHR INHA INHA INHA INHA INHA INHA INHA INHA INHA
INHA INHA INHA
BMP15, bone morphogenetic protein 15; ESR1, oestrogen receptor a; FMR1, fragile X mental retardation 1; FSHR, follicle-stimulating hormone receptor; INHA, inhibin alpha. Criteria for diagnosing premature ovarian failure: 4 months of amenorrhoea and serum follicle-stimulating hormone levels of 40 IU/l twice, obtained 1 month apart, in women aged A; p. Ala180Thr (mutation) 161 5 0 327
5
132 201 18 48 49
2 2 1
Cases
1 2 2 2 1
0 0 0
38 98 99
Cases
129 193 95 47 61
4 10 5 3 2
Cases TT
Article
Cases
Article
ESR1 2008 2008 2010 2010 2010 2012 2013 2013
Bretherick (1) Bretherick (2) Yang (1) Yang (2) Yoon Cordts Li Liu
Article
FMR1 1997 Kenneson 1999 Syrrou 2004 Bussani 2005 Bretherick 2006 Bodega 2006 Costa 2009 Chatterjee 2010 Bennett
37 33 49 3 63 3
0 10 1
149 345 119
3 83 5
GG
AG
AA
G allele
A allele
95 116 197 54 126 212 150
0 0 0 0 1 2 0
0 0
190 232
0 0
0 0 0
426 300
2 0
Wild
Mutant
90 116 193 45 85 209 62
5 0 4 9 15 5 0
T allele
CC
CT
TT
C allele
T allele
29
1 177 54 2 209 3
3 20 0 76 5 60
0
0
6
0
0
0
152
0
2
0
122
2
182 123
Controls CT/Pp
TT/pp
C allele
23 31 59
T allele
CC/PP
CT/Pp
TT/pp
C allele
T allele
45
20 4 28
48 14 106
39 9 66
88 22 162
126 32 238
46 52 134 10
117
209
233
267 69
58 21 146 76
535 89
559 221
33 55 89
59 53 163
99 74
18 11 52 10 58 59
179 118
215 192
AG/xX
GG/XX
A allele
G allele
AA/xx
AG/xX
GG/XX
A allele
G allele
56
49 13 90
47 12 102
11 2 8
145 38 282
69 16 118
133 65 210 116
77
11 8 82 6
343
99
675 265
419 45
Cases
Controls
Promoter: c. 351A>G, Xbal x>X (rs9340799) 7 40 8 54 24 34 78 64 81 95
G allele
C allele
Promoter: c.397T>C, Pvull p>P (rs2234693) 13 39 3 65
AA/xx
C allele
Controls CC
Exon 2: c.852C>T; silent (rs17003221) 14 1 0 124 9 199 4 90 2 0 47 3 60 3 0
5 12 15 60 40 22
GG
Controls Mutant
Exon 2: c. 788insTCT; p. 262insLeu (rs79377927) 164 2
CC/PP
CG
Controls
BMP15 2000 Takebayashi 2006a Dixit 2006 Laissue 2007 Zhang 2010 Tiotiu 2012 Ma
Bretherick (1) Bretherick (2) Yang (1) Yang (2) Yoon Cordts Li Liu
58 83 148 73 141 58
0 5 0
CC
ESR1 2008 2008 2010 2010 2010 2012 2013 2013
CC
44 4 12 5
Wild BMP15 2006 Di Pasquale (1) 2006 Di Pasquale (2) 2006a Dixit 2006 Laissue 2010 Wang 2010 Tiotiu 2012 Ma
G allele
Promoter: c. 9C>G (rs3810682) 144 22
GG BMP15 2006 Di Pasquale (1) 2006 Di Pasquale (2) 2006a Dixit 2006 Laissue 2008 Ledig 2010 Tiotiu 2013 Ferrarini
Controls CG
21 17 43 92 55
1 3 5 6 24 5
69 85 199
23 23 53
254 245
140 65
Cases
255 33
Controls
Total
Premutation
Total
Premutation
Exon 1: CGG repeats 33 23 45 53 190 41 78 732
0 1 3 2 19 3 0 18
107 100 28 161 200 96 70 2779
1 0 0 1 0 0 0 7
230
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Table 2 (Continued ) Article
2010 2011 2011 2011 2013 2013 2013 2013 2014 2014 2014 2014
Fic¸icioglu Ishizuka Karimov Schuettler Barasoain Ferrarini Lai Lin De Geyter Murray Tosh Ye
Article
Cases Total
Premutation
Total
Premutation
9 128 535 45 7 50 392 85 48 254 286 117
0 2 7 2 0 4 7 0 1 5 0 1
40 98 521 42 32 150 408 80 199 1915 360 82
0 0 1 0 0 0 0 0 1 7 0 0
Cases CC
FSHR 1998 da Fonte Kohek 1998 Layman 1998 Liu 2001 Takakura 2001 Tong 2004 Sundblad 2006 Loutradis 2009 Prakash 2013 Woad Article
Article
Article
Article
9 20 33 28
T allele
CC
CT
TT
C allele
T allele
0 0 0 0 0 0 0 0 0
42 10 5 3 236 44 20 50 80
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0
84 20 10 6 472 88 40 100 160
0 0 0 0 0 0 0 0 0
Controls AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
16
13 3 102
24 1 110
5
50
34
24
13 40 28 25
24 37 25 38
5 15 5 17
314 48 124 26 50 117 81 88
158 40 90 28 34 67 35 72
15 14 41
19 18 25 34
7 2 5 18
37 58 91 90
33 22 35 70
AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
Exon 10: c. 2039A>G; p. Asn680Ser (rs6166) 5 7 3 17 57 5 11 0 21 16 72
13 41 11 14 38
13
24
5
91
132
13
15 16 23 31 29
13 40 67 32 26
24 34 89 22 37
5 16 20 4 17
50 61 314 48 124 27 50 114 223 86 89
34 41 158 40 90 27 34 66 129 30 71
Cases
Controls
15 19 51 30 33
5 2 9 2 18
45 51 97 92 91
25 23 69 34 69
AG
GG
A allele
G allele
AA
AG
GG
A allele
G allele
81 344 349 261 40 111 58 112
110
74
16
39 12 2 78
51 24 29 113
24 12 24 42
294 190 326 166 129 48 33 269
106 148 272 120 99 48 77 197
Cases
Controls
Promoter: c. 124A>G (rs11893842) 66 53 14 185 446 425 343 21 30 5 72 48 69 21 165 7 32 13 46 65 76 18 206
Cases CC
INHA 2002 Marozzi 2006b Dixit 2006 Sundblad (1) 2009 Corre (1) 2009 Corre (2) 2009 Corre (3)
C allele
Exon 10: c. 919A>G; p. Thr307Ala (rs6165) 3 8 4 14 2 3 2 13 1 17 16 69
AA INHA 2006b Dixit 2009 Corre (1) 2009 Corre (2) 2009 Corre (3) 2009 Woad (1) 2009 Woad (2) 2011b Kim 2012 Yoon
TT
Cases
AA FSHR 1998 da Fonte Kohek 1999 Conway 2001 Tong 2004 Sundblad 2008 Bretherick (1) 2008 Bretherick (2) 2008 Vilodre 2010 Du 2011a Kim 2012 Chen 2013 Woad
Controls CT
Exon 7: c. 566C>T; p. Ala189Val (mutation) 15 0 0 30 35 0 0 70 5 0 0 10 15 0 0 30 16 0 0 32 15 0 0 30 33 0 0 66 50 0 0 100 80 0 0 160
AA FSHR 1998 de Fonte Kohek 1998 Liu 2001 Tong 2004 Sundblad 2008 Bretherick (1) 2008 Bretherick (2) 2008 Vilodre 2010 Du 2012 Chen 2013 Woad
Controls
Controls CT
TT
Promoter: c. 16C>T (rs35118453) 114 28 117 16 22 18 3
C allele
62 644 631 476
T allele
24 146 143 128
CC
CT
TT
C allele
T allele
46 174 49
23 26 29
4
127 278 477 237
37 60 121 49
D. Pu et al. / European Journal of Obstetrics & Gynecology and Reproductive Biology 182 (2014) 226–237
231
Table 2 (Continued ) Cases
Article
2009 Woad (1) 2009 Woad (2) 2011b Kim 2012 Yoon
Controls
CC
CT
TT
C allele
T allele
CC
CT
TT
C allele
T allele
42 87 44 110
14 47 8 44
0 4 1 5
98 221 96 264
14 55 10 54
70 31 54 153
39 16 1 68
5 1 0 12
179 78 109 374
49 18 1 92
AG
AA
G allele
A allele
GG
AG
AA
G allele
A allele
3
149 100 125 100 35 199 74 67 357 364 287 48 55
1 0 0 0 0 1 2 6 37 23 15 2 0
0
299 200 250 200 70 399 150 140 751 751 589 98 110
1 0 0 0 0 1 2 6 39 23 15 2 0
Cases
Article
GG INHA 2000 Shelling 2002 Marozzi 2004 Chen 2004 Jeong 2006 Chen 2006b Dixit 2006 Sundblad (1) 2006 Sundblad (2) 2009 Corre (1) 2009 Corre (2) 2009 Corre (3) 2010 Prakash 2011b Kim
Controls
Exon 2: c. 769G>A, p. Ala257Thr (mutation) 40 3 0 83 150 7 32 2 0 66 84 0 0 168 77 0 0 154 119 13 1 251 42 0 0 84 166 285 139 44 52
3 14 4 6 0
0 0 0 0 0
172 313 147 94 104
2 0 0 15 0 3 14 4 6 0
0 0 0 0 0 0 1 0 0 0 0
BMP15, bone morphogenetic protein 15; ESR1, oestrogen receptor a; FMR1, fragile X mental retardation 1; FSHR, follicle-stimulating hormone receptor; INHA, inhibin alpha. 2006 Di Pasquale (1): controls were women who were menopausal at >50 years of age; 2006 Di Pasquale (2): controls were general population. 2006 Sundblad (1): controls were women with normal menstruation history aged >40 years; 2006 Sundblad (2): controls were women with normal menstruation history aged G rs3810682 538G>A
ESR1
FMR1
FSHR
INHA
788insTCT rs79377927 852C>T rs17003221 PvuII (397T>C) rs2234693 XbaI (351A>G) rs9340799 CGG repeats
919A>G rs6165 2039G>A rs6166 124A>G 16C>T 769G>A
No. of studies 3 4 4 6 6 3 6 5 5 5 5 18 10 7 1 8 7 10 7 7 5 8 7 11
12
Comparisons
OR [95% CI]
Allele frequency Dominant model Allele frequency Dominant model Mutant vs wild-type
G vs C CG+GG vs CC A vs G AA+AG vs GG
1.14 1.28 6.89 5.22 0.65
Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Premutation vs normal/intermediate Caucasian dominant Asian dominant Other Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Allele frequency Dominant model Allele frequency Caucasian dominant Asian dominant Dominant model Caucasian dominant Asian dominant
T vs C CT+TT vs CC C vs T CC+CT vs TT G vs A AG+GG vs AA
1.73 1.06 1.02 0.99 1.13 1.30 8.68 9.17 5.58 17.55 0.96 1.10 0.97 1.12 0.94 0.85 1.00 0.88 2.00 1.08 8.89 1.93 0.85 8.95
G vs A AG+GG vs AA A vs G AG+AA vs GG G vs A AG+GG vs AA T vs C CT+TT vs CC A vs G
AG+AA vs GG
I2 (%)
p
(0.71–1.81) (0.89–1.83) (1.84–25.80) (1.65–16.54) (0.25–1.66)
0 0 0 0 62
0.59 0.19 0.004 0.005 0.37
(0.44–6.89) (0.58–1.93) (0.70–1.49) (0.58–1.69) (0.81–1.57) (0.79–2.14) (4.40–17.12) (4.30–19.52) (1.01–30.79) (0.89–347.74) (0.78–1.20) (0.78–1.54) (0.81–1.17) (0.83–1.49) (0.84–1.05) (0.66–1.09) (0.87–1.16) (0.60–1.30) (0.75–5.33) (0.44–2.67) (2.10–37.68) (0.65–5.73) (0.30–2.44) (2.23–35.92)
0 0 81 63 68 78 0 0 0 0 28 22 0 0 31 37 49 52 69 56 29 75 66 23
0.43 0.85 0.92 0.96 0.47 0.31 G, 538G>A, 788insTCT and/or 852C>T, involving 892 patients with POF and 1078 controls [11,16–24]. No significant differences in BMP15-9C>G, 788insTCT or 852C>T polymorphisms were found between patients with POF and controls (p > 0.05). Laissue et al. [18] and Tiotiu et al. [21] found that 788insTCT was a common polymorphism in populations of African origin. 538G>A mutation was significantly more common in patients with POF than in controls (A allele vs G allele: OR 6.89, 95% CI 1.84–25.80, p = 0.004; AA+AG vs GG: OR 5.22, 95% CI 1.65–16.54, p = 0.005; Table 3 and Fig. 2.) Six studies [10,13,25–28] investigated ESR1-397C>T and 351A>G polymorphisms, including 649 cases and 1223 controls. No significant difference was found between the patients with POF and controls (p > 0.05; Table 3). Eighteen papers examined the relationship between FMR1 CGG repeat polymorphism and the risk of POF, including 1720 cases and 3964 controls [24,29–45]. FMR1 premutation (CGG repeat number ranging from 55 to 200) was significantly more common in patients with POF compared with controls (OR 9.20, 95% CI 5.42– 15.61; p < 0.001]. Where possible, the meta-analysis was stratified into three subgroups: predominantly Caucasian (10 studies), predominantly Asian (seven studies) and other ethnicity (one study from Brazil). In both the Caucasian and Asian populations, FMR1 premutation was significantly more common in patients
with POF than in controls [Caucasian: OR 9.37, 95% CI 5.35–16.41, p < 0.001; Asian: OR 6.83, 95% CI 1.27–36.73, p = 0.03; Table 3 and Fig. 3]. Concerning FSHR, 15 studies [10,14,21,46–57] related to two polymorphisms (919A>G and 2039A>G) were available for analysis, involving 605 cases and 935 controls. As shown in Table 3, no significant differences were found between the patients with POF and controls (p > 0.05). Twelve studies [12,23,58–67] investigated INHA-124A>G, 16C>T and 769G>A polymorphisms, involving 1572 cases and 2376 controls. Only 769G>A mutation was suitable for stratification analysis, and Caucasian-dominant and Asian-dominant subgroups were used. The 769A allele was found to be significantly more common in patients with POF in the Asian subgroup [A allele vs G allele: OR 8.89, 95% CI 2.10–37.68, p = 0.003; dominant model: OR 8.95, 95% CI 2.23–35.92, p = 0.002; detailed in Table 3 and Fig. 4], but this was not seen in the Caucasian subgroup. No significant differences in the incidence rates of INHA-124A>G and 16C>T were found between the patients with POF and controls (Table 3). Comments Many studies have investigated the correlation between gene variants and the risk of POF/POI, but the results from individual studies were inconsistent. Therefore, a meta-analysis was conducted when at least three studies had been undertaken on the same gene locus. Accumulative analysis was performed for five genes: BMP15, ESR1, FMR1, FSHR and INHA. BMP15 gene BMP15 is a member of the transforming growth factor b (TGFb) family, located on Xp11.2. In ovarian folliculogenesis, BMP15 is
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Fig. 2. Association between bone morphogenetic protein 15 538G>A mutation and risk of premature ovarian failure (POF). (A) Frequency of A allele vs G allele, (B) dominant model comparison AG+AA vs GG. Di Pasquale (1) 2006: controls were women who were menopausal at >50 years of age; Di Pasquale (2) 2006: controls were general population.
Fig. 3. Association between fragile X mental retardation 1 premutation and risk of premature ovarian failure.
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Fig. 4. Association between inhibin alpha 769G>A mutation and risk of premature ovarian failure. (A) Allelic frequency comparison A vs G, (B) dominant model comparison AA+AG vs GG. Sundblad (1) 2006: controls were normal menopausal women; Sundblad (2) 2006: controls were normal menstruating women; Corre (1) 2009: cases and controls were Central Italian; Corre (2) 2009: cases and controls were Northern Italian; Corre (3) 2009: cases and controls were German. Condensation BMP15 538A, FMR1 premutation and INHA 769A (in Asians alone) may indicate susceptibility to premature ovarian failure.
a key regulating factor of granulosa cell biological processes, and is therefore a candidate gene for POF [11]. An association between BMP15 mutations and the risk of POF has been reported, which may impair the mature peptide and cause a dramatic reduction in the amount or bioactivity of protein [68]. Ten studies were included in the meta-analysis and the results showed no direct association between BMP15-9G or 852T (two common SNPs) and the development of POF, which is consistent with previous studies [16,19,23]. The mutation 538G>A (Ala180Thr) was found to increase the risk of POF, which is in agreement with Ledig et al. [20]. Women with the 538A mutation are up to five times more likely to develop POF than women without this mutation. However, in vitro studies did not detect marked deleterious
effects on BMP15 [21,69]. The insertion of three nucleotides (788insTCT) leading to insertion of leucine at position 263 was analyzed in six studies. This polymorphism has been reported to have low biological impact [69] because it was identified in both cases and controls, and is very common in populations of African origin [18,21]. ESR1 gene The ESR1 gene is another candidate genes for POF, located on 6q25.1. It encodes ERa, one of the most important factors in human reproduction [55]. The relationships between ESR1-397T>C and 351A>G and the risk of POF were of interest, but the results from
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individual studies were conflicting. Some researchers found that ESR1 polymorphisms could increase the risk of POF significantly [10,28], others detected no relationship between them [13,70], and others found that the SNPs might reduce the risk [25]. For both 351A>G and 397T>C, Bretherick et al. [10] and Liu [28] found that the 351G and 397C alleles were associated with the risk of POF among Caucasians and Chinese Han, respectively. However, contrasting results were reported by Yoon et al. [25] for 397T>C among Koreans. In the present analysis, accumulated results found no significant association between ESR1-397T>C and 351A>G and POF. A previous study reported that the presence of the 397C allele may significantly increase downstream reporter activity compared with the 397T allele, indicating that this SNP could affect a functional binding site for the myb family of transcription factors, and decrease ERa expression [71]. Another report found that the 397CC genotype decreased ESR1 mRNA, and reduced ERa bioactivity [72]. FMR1 gene The FMR1 gene is mapped to the X chromosome at position q27.3, which contains an unstable CGG repeat in the 50 untranscribed region of the first exon [73]. The repeat length is variable in the general population, ranging from six to 55 repeats. The American College of Medical Genetics currently defines the borders between genotypic classes as follows: 5–44 repeats, normal; 45–54 repeats, intermediate; 55–200 repeats, premutation; and 200–230 repeats, full mutation [74]. It has been reported that full mutations cause fragile X syndrome and that premutations are associated with fragile X tremor and ataxia syndrome and POF [75,76]. Concerning the relationship between CGG repeat and POF, some studies have shown that amplification of the number of CGG repeats above the normal range, from intermediate to premutation status, represents a high risk factor for POF [77–79]. In FMR1 premutation carriers, it has been found that FMR1 protein expression was decreased by blocking the translation of FMR1 message [80]. FMR1 protein is reported to be involved in oocyte and synaptic function, and a reduced FMR1 protein level is thought to alter the expression of oocyte developing related genes, resulting in POF [5,80]. However, the results were conflicting. The present study included 20 studies on the association between FMR1 premutation and the risk of POF/POI. The meta-analysis indicated significant correlation between FMR1 premutation and higher risk of POF in the overall population, as well as in the stratified subgroups (Caucasians and Asians). The findings are generally in agreement with Tosh et al., who pooled 11 studies for meta-analysis [44]. FSHR gene The FSHR gene is a member of the family of G protein-coupled receptors, located on chromosome 2p21 [81]. FSH is very important in human reproduction, including gonadal development and sexual maturation during the fertile period [81]. FSH action is mediated by the FSHR which is expressed in the granulosa cells of the ovary. The finding that FSHR 566C>T mutation led to amino acid substitution of Ala189Val and played an important role in the development of POF was first made in a Finnish population [82]. The present study included nine published articles [15,46,47,49–53,57] that concerned this mutation. Unfortunately, no such mutation was found in any subjects of these studies (patients or controls). In addition, two well-known SNPs, 919A>G (Thr307Ala) and 2039A>G (Asn680Ser) [81], were analyzed in 11 studies, and the results found that neither of these SNPs had a direct role in the development of POF,
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which is consistent with a previous meta-analysis [54]. Position 307 is known to code for amino acid in the transmembrane region of the FSHR protein, while position 680 is located in the intracellular region. Both are critical for the hormone-binding ability of FSHR and FSH-mediated signal transduction in infertile women undergoing ovarian stimulation [83,84]. Several studies have observed that women with homozygous 680Ser/Ser with or without 307Ala/Ala appear to have a higher basal level of FSH, which is associated with decreased ovarian reserve [85–87]. It has been reported that FSHR 919A>G is usually linked to 2039A>G; however, the linkage analysis of the two SNPs did not perform for few data. Interestingly, Kim et al. [55] found that the combined genetic effect of CYP19A1 rs4646 (CA+AA) and FSHR 2039 (AG+GG) genotype may be related to the risk of POF. INHA gene Inhibin is a member of the TGFb superfamily. Two forms of inhibin exist in human tissue: inhibin A (a-bA) and inhibin B (abB). Inhibin A is encoded by the INHA gene, located on 2q33-q36. Inhibin regulates FSH secretion by inhibition of the HPO axis in order to ensure the normal menstrual cycle and scheduled ovulation [88]. The present meta-analysis examined the relationship between INHA-124A>G, 16C>T and 769G>A gene variants and the risk of POF by summarizing 12 studies. This updates the analyses of Zintzaras [89] (pooled six studies) and Chand et al. [90] (pooled five studies). Chand [90] found that the 769G>A mutation alone was correlated with POF. The present study did not find an association between INHA-124A>G and 16C>T and the risk of POF, in contrast to Kim et al. [66] who found that 16C>T polymorphism was associated with increased risk of POF. Individual studies showed controversial results for 769G>A mutation. After performing the stratified analysis by ethnicity, Asian women with the 769A allele were found to be susceptible to POF, while no such relationship was found for the Caucasian population. This result is consistent with Chand et al.’s metaanalysis [90]. Previous in vitro studies have found that 769G>A (Ala257Thr) mutation may impair the bioactivity of inhibin B [91]. Limitations This study has several limitations. First, the main limitation is the small study/sample size for meta-analysis. Secondly, stratification analyses by ethnicity or region were only performed for FMR1 premutation and INHA 769G>A mutation because of insufficient studies or deficient data from the primary studies. Thirdly, some studies evaluated the relationship between FMR1 CGG intermediate repeat and POF, but were not eligible for the meta-analysis because of an inconsistent definition of intermediate repeats. Despite these limitations, the findings of this meta-analysis did find associations between gene (BMP15, ESR1, FMR1, FSHR and INHA) polymorphisms and the risk of POF/POI. This study found that BMP15 538G>A mutation, FMR1 premutation and INHA-769G>A mutation (in Asians alone) were associated with increased susceptibility to POF. Further welldesigned studies and larger samples are required to confirm the association between gene variants and POF.
Funding This study was supported by a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, and Jiangsu Province Women and Children Health Program (Grant No. FXK201201, FRC201201).
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