Multigenic combination of estrogen-related genes is associated with age at natural menopause in a Spanish population

Abstract

Objective

Age at natural menopause (ANM) can be considered a complex parameter that depends on the interaction of multiple factors. In the present study, the role of interaction between genetic variants within estrogen synthesis and signalling pathways in the ANM in Spanish women is studied.

Material and methods

Nine single nucleotide polymorphisms (SNPs) located at different candidate genes related to the estrogen signalling pathway were analysed in 1980 Spanish postmenopausal women.

Results

Independently, none of the nine markers were significantly associated with early ANM. Only heterozygosis at the NRIP rs2229741 locus could be associated with early menopause; however, this marker does not maintain statistical significance. In contrast, linear regression analysis suggests several epistatic interactions including these markers in relation to ANM, especially between ESR2, NRIP1 and BMP15. The genetic variant that appears most in these interactions is that of the BMP15 rs3897937. It was observed that AA-TC combined genotype for NRIP-BMP15 (rs3897937), respectively, appears to be associated with a lower ANM than other possible combinations of these SNP (46.1±5.9 versus 50.4±3.3; P = 0.002). In the multilocus analysis, the multigenic interaction formed by ESR2 (AA), BMP15 rs3897937 (TC) and NRIP1 (AA) has the lower ANM (45.37±6.8 versus 48.69±5; P = 0.038).

Conclusions

The results suggest that epistatic interactions of estrogen-related alleles may contribute to variance in ANM in Spanish women. Moreover, BMP15 and NRIP1 also appear as attractive candidate genes for premature menopause but require further investigation to confirm them.

Keywords

Age at menopause polymorphism estrogen

Objective

Age at natural menopause (ANM) can be considered a complex parameter, which depends on the interaction of multiple factors including the environment, lifestyle and genetics. In addition, it is a parameter that influences the quality of life and the appearance of certain diseases; hereby precocious menopause has significant psychological consequences and is associated with an increased risk of cardiovascular diseases, osteoporosis and epithelial ovarian cancer, whereas a late menopause has been associated with an increased risk of breast cancer.

From the genetic point of view, there is strong evidence to suggest that the genome might explain the variation in the ANM.^1–10 Nevertheless, no gene has been associated independently with the ANM. Instead it is thought that the association of genetic variations might determine it. In the present study the role of interaction between genetic variants within estrogen synthesis and signalling pathways in the ANM in Spanish women is studied.

Methods

Patients

A multicentre population study of 1980 postmenopausal women (1558 natural menopause) was carried out in Spain. The referral centres involved in the research were Hospital Virgen de las Nieves (Granada), Hospital San Juan de Alicante (Alicante), CEOGA (Lugo), Sanatorio Bilbaíno (Bilbao) and Clínica Diatros (Barcelona). Blood samples, as well as clinical and epidemiological data, were collected from each of the women using a consensus protocol developed by the clinical researchers involved in this study. A brief description of the women recruited with a natural menopause is shown in Table 1. Written, informed consent was obtained from all of the individuals included in the present study. The referral centres' ethics committees and Neocodex approved this protocol.

Table 1

Demographic characteristics of the study population

Characteristics
Age in years*	58.7±8.1
Age at menarche in years*	12.8±1.6
Age at natural menopause in years*	48.4±5
Reproductive period in years*	35.5±5.2

*Mean±SD (our distribution data are similar to a normal distribution)

DNA extraction

Peripheral blood (5 mL) was obtained from all individuals to isolate germline DNA from leukocytes. DNA extraction was performed in a MagNa Pure LC Instrument (Roche Diagnostics, Penzberg, Germany), using MagNa Pure LC DNA Isolation kit (Roche Diagnostics, Germany) in accordance with the manufacturer's instructions.

Selection of candidate genes

In order to study representative genes, the follicle-stimulating hormone receptor (FSHR) gene, the CYP19 aromatase (CYP19A1) gene, the estrogen receptor alpha (ESR1) gene, the estrogen receptor beta (ESR2) gene, the nuclear receptor interacting protein 1 (NRIP1) gene and the bone morphogenetic protein 15 (BMP15) gene were selected as candidate genes to perform this work (www.ncbi.nlm.nih.gov/Omim). Most of these genes have been analysed in different association studies mainly with estrogen-dependent traits such as menstrual disorders, premature ovarian failure, ovarian hyperstimulation syndrome, endometriosis, bone mineral density, prostate cancer, osteoporosis or breast cancer (see Genetic Association Database website, www.geneticassociationdb.nih.gov).

Molecular detection and statistical analysis of polymorphisms

Nine polymorphisms named rs10046 and rs11575899 (CYP19), rs2234693 (ESR1), rs4986938 (ESR2), rs6166 (FSHR), rs2229741 (NRIP1), and N103S, rs3810682 and rs3897937 (BMP15) were selected to perform the genotyping of this series. The genotyping protocols employed during this work are based on the polymerase chain reaction technique coupled to realtime detection of alleles employing pyrosequencing or fluorescent resonance energy transfer protocols.

Using the standard Pearson chi-square test or Fisher's exact test, we compared allelic frequencies between groups. Quantitative traits and digenic or multigenic combination were analysed via the Kruskall–Wallis or Levene test using SPSS 15.0 software (Leads Technologies, Chicago, Illinois) in relation to ANM and early menopause (less than 45 years old). For statistical analysis of genotype distribution and test for deviation of the Hardy–Weinberg equilibrium (HWE), we used the online resource at the Institute for Human Genetics, Munich, Germany (www.ihg.gsf.de). Unadjusted and age-adjusted effects sizes for each marker or genotype pattern were calculated using linear regression analysis with the general linear model (GLM) application of SPSS 15.0.

Results

Marker-by-marker analysis of estrogen synthesis and signalling pathways

The allelic frequency and genotypic distribution of nine single nucleotide polymorphisms (SNPs) located within FSHR, CYP19, ESR1, ESR2, NRIP1 and BMP15 genes in 1191 postmenopausal women was investigated. The genotypic raw data observed in the series are completely consistent with previous findings in Spanish women. In addition, it was observed that the genotypic distribution in all genetic markers also fit with the HWE law calculated using the goodness-of-fit test χ² (P > 0.16).^11–13 These results (allelic frequencies and HWE) together with the trends observed over time in ANM support the validity of our genotyping and recruitment programmes, respectively.

As shown in Tables 2a and b, none of the studied markers were significantly associated with an early menopause (less than 45 years) or with minor ANM in the Spanish population. Only heterozygosis at the NRIP rs2229741 locus could be associated with early menopause; however, this marker does not maintain statistical significance after testing adjustments using the Bonferroni correction.

Table 2a

Allele frequencies and genotype distribution of the single nucleotide polymorphism (SNP) markers used in the study in relation with the early menopause (EM)

Gene	SNP	Genotype distribution		Statistical analysis
		EM	Rest	Effect size OR (CI)	P values*
					0.71^†
		AA: 38	AA: 137	0.9 (0.7–1.3)^‡	0.82^‡
FSHR	rs6166	AS: 55	SS: 218	0.9 (0.6–1.4)^§	0.69^§
		SS: 24	SS: 91	0.9 (0.5–1.7)**	0.86**
				0.9 (0.6–1.4)^††	0.71^††
				0.9^‡‡	0.82^‡‡
					0.85^†
				0.9 (0.7–1.3)^‡	0.81^‡
		CC: 31	CC: 116	1.0 (0.6–1.6)^§	0.97^§
ESR1	rs2234693	CT: 60	CT: 223	0.9 (0.5–1.7)**	0.80**
		TT: 25	TT: 101	0.9 (0.6–1.6)^††	0.94^††
				0.9^‡‡	0.81^‡‡
					0.71^†
				1.2 (0.9–1.7)^‡	0.15^‡
ESR2	rs4986938	AA: 37	AA: 166	1.2 (0.8–1.9)^§	0.44^§
		AG: 56	AG: 209	1.5 (0.9–2.8)**	0.15**
		GG: 24	GG: 70	1.3 (0.8–2.0)^††	0.26^††
				1.2^‡‡	0.15^‡‡
					1.00^†
				1.1 (0.8–1.4)^‡	0.54^‡
		AA: 47	AA: 201	1.1 (0.7–1.6)^§	0.70^§
CYP19	rs10046	AG: 90	AG: 356	1.1 (0.7–1.8)**	0.54**
		GG: 44	GG: 163	1.1 (0.8–1.6)^††	0.60^††
				1.1^‡‡	0.54^‡‡
					0.76^†
				1.1 (0.9–1.4)^‡	0.29^‡
		11:69	11:296	1.1 (0.8–1.5)^§	0.67^§
CYP19	rs11575899	12:84	12:334	1.3 (0.8–2.2)**	0.25**
		22:28	22:90	1.1 (0.8–1.6)^††	0.46^††
				1.1^‡‡	0.29^‡‡
					0.46^†
				0.8 (0.6–1.0)^‡	0.06^‡
		AA: 32	AA: 135	0.5 (0.3–0.9)^§	0.01^§
NRIP1	rs2229741	AG: 54	AG: 239	0.6 (0.3–0.9)**	0.04**
		GG: 31	GG: 72	0.5 (0.3–0.9)^††	0.01^††
				0.8^‡‡	0.06^‡‡
					0.55^†
				1.5 (0.9–1.5)^‡	0.33^‡
		CC: 112	CC: 468	1.1 (0.8–1.6)^§	0.54^§
BMP15	rs3810682	CT: 59	CT: 221	1.4 (0.7–2.9)**	0.38**
		TT: 10	TT: 30	1.5 (0.8–1.6)^††	0.42^††
				1.2^‡‡	0.34^‡‡
					0.18^†
				1.1 (0.8–1.4)^‡	0.49^‡
		CC: 91	CC: 397	1.3 (0.9–1.8)^§	0.16^§
BMP15	rs3897937	CT: 78	CT: 266	0.9 (0.5–1.8)**	0.80**
		TT: 12	TT: 57	1.2 (0.9–1.7)^††	0.24^††
				1.0^‡‡	0.49^‡‡
					1.00^†
				1.0 (0.6–1.7)^‡	0.89^‡
		AA: 163	AA: 647	0.9 (0.5–1.7)^§	0.86^§
BMP15	N103S	AG: 17	AG: 71	3.9 (0.2–63.8)**	0.29**
		GG: 1	GG: 1	0.9 (0.6–1.7)^††	0.98^††
				1.1^‡‡	0.89^‡‡

OR = odds ratio; CI = 95% confidence interval; FSHR = follicle-stimulating hormone receptor; ESR1 = estrogen receptor alpha; ESR2 = estrogen receptor beta; CYP19 = cytochrome P450 family 19; NRIP1 = nuclear receptor interacting protein 1; BMP15 = bone morphogenetic protein 15

*Risk allele 2 (except to NRIP1 allele); ^†Hardy–Weinberg chi-square exact test; ^‡Allele frequency differences test; ^§Heterozygous test; **Homozygous test; ^††Allele positivity test; ^‡‡Armitage's trend test

Table 2b

Allele frequencies and genotype distribution of the single nucleotide polymorphism (SNP) markers used in the study in relation with the age at natural menopause (ANM)

Gene	SNP	Genotype distribution	n	ANM	P*
FSHR	rs6166	AA	175	48.2203 + 4.84909	0.904
		AS	273	48.4436 + 4.92494
		SS	115	48.4224 + 4.91166
ESR1	rs2234693	CC	126	48.3701 + 5.21263	0.875
		TC	283	48.2561 + 4.83688
		TT	147	48.5235 + 4.76981
ESR2	rs4986938	AA	94	47.8125 + 4.94243	0.479
		GA	265	48.3358 + 4.98529
		GG	203	48.6552 + 4.74073
CYP19A1	rs10046	AA	248	48.3855 + 4.76758	0.600
		GA	446	48.4035 + 4.87409
		GG	207	48.5192 + 5.44002
CYP19A1	rs11575899	11	360	48.4022 + 4.76090	0.664
		12	418	48.4716 + 4.87155
		22	118	48.3305 + 5.95145
NRIP1	rs2229741	AA	103	47.7981 + 5.28486	0.426
		GA	293	48.4441 + 4.72971
		GG	167	48.5917 + 4.92009
BMP15	N103S	AA	810	48.4093 + 4.96778	0.296
		AG	88	48.5955 + 5.05587
		GG	2	44.0000 + 2.82843
BMP15	rs3810682	CC	580	48.4820 + 4.97857	0.790
		TC	280	48.2746 + 5.00832
		TT	40	48.6750 + 4.85897
BMP15	rs3897937	CC	69	49.1884 + 4.44004	0.123
		TC	344	48.0086 + 5.04832
		TT	488	48.6143 + 4.98014

FSHR = follicle-stimulating hormone receptor; ESR1 = estrogen receptor alpha; ESR2 = estrogen receptor beta; CYP19A1 = cytochrome P450 family 19; NRIP1 = nuclear receptor interacting protein 1; BMP15 = bone morphogenetic protein 15

*Kruskal–Wallis test

In contrast, linear regression analysis suggests several epistatic interactions including these markers in relation to ANM in our series, especially between FSHR, ESR2, NRIP1 and BMP15. In Table 3 the genetic interactions that relate to minor ANM are displayed. Four couples of allele appear in the majority of them: rs2229741 (AA), rs3897937 (TC), rs4986938 (AA) and rs6166 (SS).

Specifically, it seems that women carrying some of the digenic interactions have a lower mean of ANM, whereas none of them seems to offer protection opposite to the praecox menopause (PM) (Table 4). The genetic variant that appears more in these interactions is that of the BMP15 rs3897937. Concretely, it was observed that AA-TC combined genotype for rs2229741-rs3897937, respectively, appears to be associated with a lower ANM with other possible combinations of these SNPs (46.1 [5.9] versus 50.4 [3.3]; P = 0.002).

Table 3

Interaction between loci

	ESR1	ESR2	CYP19A1 (3′UTR)	CYP19A1 (IVS4)	NRIP1	BMP15 (N103S)	BMP15 (−9C > G)	BMP15 (905 A > G)
FSHR	0.05*	0.971	0.615	0.034*	0.765	0.961	0.730	0.257*
ESR1		0.917	0.663	0.621	0.306*	0.983	0.205*	0.038*
ESR2			0.406*	0.642	0.646	0.299	0.521	0.097*
CYP19A1 (3′UTR)				0.906	0.402	0.794	0.771	0.225
CYP19A1 (IVS4)					0.439	0.754	0.917	0.564
NRIP1						0.483	0.652	0.012*
BMP15 (N103S)							0.508	0.077*
BMP15 (−9C > G)								0.238
BMP15 (905 A > G)

*At least two significantly different couples (P < 0.05)

Table 4

Digenic interaction

Interaction loci	SNP	Genotype	ANM	Genotype	ANM	P value
FSHR–ESR1	rs6166-rs2234693	SS-TT	47.2±5.1	AS-TT	50±4.2	0.003
		AA-TT	47.4±4.8			0.004
FSHR–CYP19A1	rs6166-rs11575899	AA-11	47.5±4.4	AS-22	50.1±4.1	0.002
		AS-12	47.8±5.1			0.003
FSHR–BMP15	rs6166-rs3897937	AA-TC	46.9±5.3	AA-CC	49.7±3.8	0.038
				AA-TT	48.9±4.4	0.012
ESR1–NRIP1	rs2234693-rs2229741	TC-AA	46.9±5.7	TC-GG	48.9±4.8	0.032
ESR1–BMP15	rs2234693-rs3810682	TT-GC	46.7±5.4	TT-CC	49.2±4.2	0.006
ESR1–BMP15	rs2234693-rs3897937	TT-TC	46.7±5.2	TT- CC	50.6±4.2	0.014
				TT-TT	49.6±4.1	0.000
				CC-TT	48.6±5.4	0.016
				TC-TT	48.5±4.5	0.018
ESR2–CYP19A1	rs4986938-rs10046	AA-GG	45.8±5.3	GG-GG	49.3±4.8	0.009
ESR2–BMP15	rs4986938-rs3897937	GG-TC	47±5.3	GG-CC	50.4±4.3	0.013
				GG-TT	49.4±4.2	0.005
		AA-TC	47.1±5.3	GG-CC	50.4±4.3	0.028
				GG-TT	49.4±4.2	0.057
NRIP1–BMP15	rs2229741-rs3897937	AA-TC	46.1±5.8	GA-CC	50.4±3.3	0.002
				AA-TT	49.4±4.3	0.005
				GA-TT	48.7±4.6	0.008
				GG-TT	48.6±4.9	0.016
BMP15–BMP15	N103S-rs3897937	AA-TC	47.8±5	CC-AA	49.9±4.3	0.010

In the multilocus analysis the aim was to combine these four markers and compare them with a control group formed by women who did not carry them. In this way, a multigenic interaction formed by ESR2 (AA), BMP15 rs3897937 (TC) and NRIP1 (AA) has the lower ANM (45.37±6.8 versus 48.69±5.0, P = 0.038). The small sample size gave non-significant results in the rest of the combinations (Table 5).

Table 5

Multilocus interaction

Interaction loci	n	ANM	P values*
ESR2(AA)-BMP15 905 A > G(TC)-NRIP1(AA)	13	45.37±6.8	0.148^†
			0.038^‡
			0.068^§
FSHR(SS)-ESR2(AA)-BMP15 905 A > G(TC)	7	47.50±4.8	0.564^†
			0.566^‡
			0.477^§
FSHR(SS)-ESR2(AA)-NRIP1(AA)	4	47.75±4.1	0.462^†
			0.711^‡
			0.540^§
FSHR(SS)-BMP15 905 A > G(TC)-NRIP1(AA)	3	48.33±3.8	0.574^†
			0.903^‡
			0.753^§
All (four markers)	3	47.67±6.0	0.869^†
			0.727^‡
			0.680^§
None (control group)	526	48.69±5.0

*Respect control goup

^†Equality of the varianza (Levene test)

^‡Equality of the mean

^§Kruskal–Wallis test

Discussion

The ANM is considered to be a complex parameter that depends on the interaction of multiple environmental, lifestyle and genetic factors,¹⁴ although the environmental ones explain only a small part of this variability.⁶ This determines that the genetic factors form the principal mechanisms of variation in ANM. Due to the fact that estrogens play an important role in the regulation of ovary follicle development, the estrogen synthesis and signalling pathway genes were regarded as important candidate genes for ANM¹⁵; however, until now, none of the SNP of this metabolic route that has been studied has been associated individually with the ANM. Some studies begin to give importance to the digenic interaction in the variability of the ANM or of the age at menarche.^15,16

On the other hand, this article proposes that the genes that influence the ANM also influence the PM due to being close entities. PM is defined as the cessation of ovarian function before 40 years; and if this occurs between 40–45 years it is named early menopause.¹⁷ According to the information of the survey entrusted by the Spanish Menopause Society, in Spain the average age in which the menopause takes place is 47 years, slightly lower than the average in Western countries (www.aeem.es).

In spite of the efforts towards the investigation of estrogen-related diseases such as PM, most of the molecular genetic studies available in the literature employed only the marker-by-marker approach¹⁸ and are compared only by a single locus versus a disease status or a specified physiological parameter. Unfortunately, this strategy completely ignores the multigenic nature of the complex traits and the joint effects on phenotypes of multiple unlinked loci. In this way, it was recently proposed that combined genetic patterns of genes involved in estrogen signalling, and genes involved in estrogen's mechanisms of action or degradation could interact to confer risk or protection to multiple estrogen-related diseases.¹⁹ In fact, interaction related to osteoporosis,²⁰ controlled ovarian stimulation outcome¹⁵ and male infertility has been detected.¹⁹ In the present paper, the role of these genes in relation with ANM was analysed.

Two types of receptors exist for estrogen, the alpha or type 1 (ESR1) and the beta or type 2 (ESR2). ESR1 and ESR2 behave as regulators of the transcription of the DNA, and close to CYP19 markers have been associated with the ANM in different populations.¹⁵ For this reason, we investigated the role of each SNP marker regarding the ANM in our series with more details.

Regarding FSHR, our results suggest that this gene is not a major locus of ANM, as observed in other studies.²¹ Given the negative results of a recent genome wide scan and our results after multiple testing corrections, we annotated the results at FSHR locus with great caution and encourage further studies of our findings.²²

Nevertheless, using the multilocus analysis, we discovered two new candidate genes for ANM: NRIP and BMP15. NRIP1 gene encodes a highly pleiotropic nuclear receptor co-regulator (rip140)²³ that interacts and regulates multiple members of the nuclear receptor super-family; targeting disruption experiments of this function in mice have demonstrated that nuclear receptor interacting protein 1 gene (NRIP1 gene), the gene encoding for rip140 protein, is essential for female fertility.²⁴ Specifically, mice negative for NRIP1 gene are viable, butfemales are infertile because of the complete failure of mature follicles to release oocytes at the ovulation stage. The ovarian phenotype observed in mice devoid of rip140 closely resembles the luteinized unruptured follicle syndrome that is observed in a high proportion of women affected by endometriosis. More recently, an interesting role of rip140 in the regulation of fat accumulation has also been discovered in animal models.²⁵ Alternatively, specific NRIP1 alleles might alter the ovarian production of estrogens during the fertile period of life conferring protection or susceptibility to multiple estrogen-related diseases in women.

BMP15 (Bone Morphogenetic Protein 15) has been investigated in PM due to its importance in ovarian function. Direct evidence of the role of BMP15 gene in follicle production in mammals strongly suggest that this oocyte factor might play a key role in an early ANM and consequently in PM phenotype. Different research groups described several heterozygous variations affecting the pro-region and mature peptide of BMP15 gene in women affected with PM.^26–28 To clarify the role of BMP15 gene in the onset of natural menopause in the Spanish population, we decided to genotype four SNPs in a large series of menopausal women.²⁹ Furthermore, we analysed these markers in digenic combinations with other markers located at different candidate genes related to the estrogen signalling pathway. In this regard, our results suggest that the BMP15 gene may contribute to variance in ANM and reproductive period in a complex manner, but this idea must be viewed with caution.

We employed the GLM package of SPSS analysing (full factorial model) that permits the adjustment of specific genotypic effects by other important co-variants such as birth year, weight, age at menarche and other markers. None of the genotypic groups tested displayed any significant difference in ANM in the studied population after testing adjustments using the Bonferroni correction. In contrast, linear regression analysis suggests several epistatic interactions including these markers in relation to ANM in our series, especially for four couples of allele: rs2229741 (AA), rs3897937 (TC), rs4986938 (AA) and rs6166 (SS). This means that women carrying some of the digenic interactions have a lower mean of ANM, whereas none of them seems to offer protection opposite to the PM (Table 4). The genetic variant that appears most in these interactions is that of the BMP15 rs3897937. Concretely, we have observed that AA-TC combined genotype for rs2229741-rs3897937, respectively, appears to be associated with a lower ANM.

Next step in this research was to combine these four markers and to compare them with a control group formed by women who carried none of them. The small sample size gave nonsignificant results in all possible combinations, although the multigenic interaction formed by ESR2 (AA), BMP15 rs3897937 (TC) and NRIP1 (AA) has the lower ANM compared with the control group (45.37±6.8 versus 48.69±5.0 P = 0.038).

Probably the limitation of this work and in general for all the studies of multigenic interaction is the need for a major statistical significance. Therefore care needs to be taken with some of the digenic or trigenic opposing interactions, especially those of P > 0.01. The difficulty in this type of study predicting common diseases is the need for a large sample size, allowing comparisons between genetic variants. Hence the lack of publications of this nature in gynaecology. In addition, large populations are also necessary to look at complicated multilocus interactions, and complex interactions require appropriate statistical evaluation.³⁰

In conclusion, our results suggest that epistatic interactions of estrogen-related alleles may contribute to variance in ANM in a complex manner in Spanish women. Moreover, BMP15 and NRIP1 also necessary to appear as attractive candidate genes for praecox menopause but require further independent studies to confirm this.

Footnotes

Acknowledgments

The authors are deeply grateful to postmenopausal women for having participated in this study, and are very grateful to Juan Eloy Ruiz and Francesca Falconi for their collaboration during this work. The referral centres' ethics committees approved this protocol.

Competing interests: None declared.

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