Variants in FSHB Are Associated With Polycystic Ovary Syndrome and Luteinizing Hormone Level in Han Chinese Women (original) (raw)

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1Center for Reproductive Medicine (Y.T., Y.D., Z.-J.C.), Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200135, China

2Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics (Y.T., Y.D., Z.-J.C.), Shanghai, 200135, China

3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

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3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

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6Center for Genomic Translational Medicine and Prevention (H.C., J.X.), Fudan School of Public Health, Fudan University, Shanghai, 200032, China

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3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

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3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

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1Center for Reproductive Medicine (Y.T., Y.D., Z.-J.C.), Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200135, China

2Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics (Y.T., Y.D., Z.-J.C.), Shanghai, 200135, China

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3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

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7Program for Personalized Cancer Care and Department of Surgery (J.X.), North Shore University Health System, Evanston, Illinois 60201

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1Center for Reproductive Medicine (Y.T., Y.D., Z.-J.C.), Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200135, China

2Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics (Y.T., Y.D., Z.-J.C.), Shanghai, 200135, China

3Center for Reproductive Medicine (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Shandong Provincial Hospital Affiliated to Shandong University, Jinan, 250021, China

4National Research Center for Assisted Reproductive Technology and Reproductive Genetics (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China

5The Key laboratory for Reproductive Endocrinology of Ministry of Education (Y.T., H.Z., Y.P., L.C., Z.W., Z.-J.C.), Jinan, 250021, China Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, 250021, China

*Address all correspondence and requests for reprints to: Zi-Jiang Chen, MD, PhD, Center for Reproductive Medicine, Provincial Hospital Affiliated to Shandong University, 157, Jingliu Road, Jinan, 250001, China.

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Received:

26 October 2015

Accepted:

26 February 2016

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Ye Tian, Han Zhao, Haitao Chen, Yingqian Peng, Linlin Cui, Yanzhi Du, Zhao Wang, Jianfeng Xu, Zi-Jiang Chen, Variants in FSHB Are Associated With Polycystic Ovary Syndrome and Luteinizing Hormone Level in Han Chinese Women, The Journal of Clinical Endocrinology & Metabolism, Volume 101, Issue 5, 1 May 2016, Pages 2178–2184, https://doi.org/10.1210/jc.2015-3776
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Abstract

Context:

A recent genome-wide association study (GWAS) has identified three susceptibility loci (8p32.1, 11p14.1, and 9q22.32) for polycystic ovary syndrome (PCOS) in women of European ancestry. The 9q22.32 locus was previously found in our Chinese PCOS GWAS. Replication of the other two loci is necessary to determine whether the same variants confer risk to PCOS in Han Chinese women.

Objective:

This study aimed to investigate the effect of the European GWAS loci on PCOS susceptibility in Han Chinese women.

Design, Setting, and Patients:

This was a genetic association study at a university hospital in composed of 1601 PCOS cases and 1238 age-matched controls.

Interventions and Main Outcome Measure:

After screening of the regions that cover 500 kb upstream and downstream of the two single-nucleotide polymorphisms (SNPs) using our previous Chinese GWAS data, rs11031010, located in the region of follicle-stimulating hormone B polypeptide (FSHB) gene, was selected for further replication. The other SNPs near rs804279 (GATA4/NEIL2) were excluded based on our previous GWAS data. Then, the variant rs11031010 was genotyped in an independent cohort and the associations with PCOS, endocrine and metabolic traits were assessed.

Results:

In the current replication study, rs11031010 was associated with PCOS in Han Chinese women (P = 2.76 × 10−3), even after adjustment for age and body mass index. Meta-analysis with our previous GWAS data showed that the allele frequency difference of rs11031010 between PCOS and controls reached genome-wide significance (P = 4.27 × 10−8). PCOS women with AA and AC genotypes had a significantly higher LH level than individuals carrying the CC genotype (P =1.60 × 10−4). The genetic risk score based on sixteen total Chinese PCOS-risk SNPs, calculated by total number of risk alleles for each subject, was associated with the diagnosis of PCOS (P < 1.00 × 10−4).

Conclusions:

Variants in FSHB gene are associated with PCOS and LH levels in Han Chinese women. FSHB is thus likely to play an important role in the etiology of PCOS, regardless of ethnicity.

Polycystic ovary syndrome (PCOS) is the most prevalent endocrine disorder, affecting 5–10% women of reproductive age (1). The diagnosis of PCOS relies on chronic oligo-/anovulation (OA), clinical and/or biochemical hyperandrogenism (HA), and polycystic ovaries (PCOs) under ultrasound. The Rotterdam criteria required two of three features whereas the National Institutes of Health (NIH) criteria required the first two features (2). PCOS is, however, heterogeneous and has broader clinical manifestations. Elevated serum concentrations of LH, normal/lower level of FSH, elevated ratio of LH to FSH (LH/FSH), and excess levels of T are common endocrine disturbances (3). Moreover, women with PCOS frequently present with a range of metabolic disorders, such as insulin resistance, obesity, type 2 diabetes, and dyslipidemia, which are associated with long-term health (4–6).

The etiology of PCOS is not fully understood, but the role of genetic factors has long been established by familial aggregation and twin studies (7, 8). PCOS is regarded as a multigenetic disorder and more than 100 candidate genes were identified (9). However, most findings from these suspected candidate gene studies were not repeatable. Currently, genetic strategies to explore susceptibility genes for mutigenetic diseases have extended to genome-wide approaches. Genome-wide association studies (GWAS) have previously identified 11 loci for PCOS in Han Chinese women, which mapped to the genomic regions of LHCGR, THADA, DENND1A, FSHR, INSR, YAP1, HMGA2, C9orf3, RAB5B, TOX3, and SUMO1P1 (10, 11). These established susceptibility genes have been replicated in multiple ethnicities, indicating that there is a common genetic risk profile for PCOS across populations (12–16). Recently, a large three-stage GWAS was performed in European-origin women and identified three susceptibility loci for PCOS (8p32.1, GATA4/NEIL2; 11p14.1, FSHB; and 9q22.32, C9orf3) (17). The C9orf3 gene was also previously found in Chinese PCOS GWAS whereas the roles of the other two loci have not been reported in Asian cohorts. The aims of this study were to replicate association of the other two new susceptibility loci identified in the European GWAS and assess the contributions of genetic variations to the endocrinal and metabolic features in a Chinese population.

Materials and Methods

Subjects

The GWAS samples were composed of 2245 PCOS cases and 895 controls. The independent replication cohort consisted of 1601 PCOS cases and 1238 controls. All individuals were Han Chinese women. Samples were recruited from the Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University. PCOS was defined by 2003 Rotterdam PCOS consensus criteria (2), which required two of the following three criteria: OA (menstrual cycle length >35 d), clinical or biochemical HA (Ferriman-Gallwey score ≥6 or elevated circulating total T ≥60 ng/dL) (10, 18), and PCO morphology on ultrasound (≥12 follicles in one ovary and/or increased ovarian volume >10 mL). Other related diseases with similar presentations such as congenital adrenal hyperplasia, androgen-secreting tumors, Cushing's syndrome, thyroid disease, and hyperprolactinemia, were excluded. The inclusion criteria for the control group in which PCOS was specifically excluded were as follows: normal menstrual cycles and neither HA nor PCOs under ultrasound. Individuals who were taking medications such as oral contraceptives and metformin during the last 3 months were also excluded.

The study was approved by Institutional Review Board of Shandong University. Written informed consents were obtained from all subjects.

Clinical and biochemical measurements

Medical history and anthropometric data (height, weight) were taken and the body mass index (BMI) was calculated as weight (kg) divided by height (m)2. A morning fasting blood sample was obtained during days 2–4 of the menstrual cycle for examination of circulating serum levels of hormones, such as FSH, LH, and T. Fasting plasma glucose levels were measured using the oxidase method and insulin levels were measured by chemiluminescence immunoassays. Insulin resistance was calculated as fasting glucose (mmol/L) × fasting insulin (mIU/L)/22.5 using homeostasis model assessment. Serum cholesterol, triglycerides, low-density lipoprotein, and high-density lipoprotein were detected using the precipitation and enzymatic methods.

SNP genotyping

Genomic DNA was extracted from whole peripheral blood by a standard process using QIAamp DNA mini kit (QIAGEN). Genotyping of SNP rs11031010 was carried out by direct sequencing. The primers were listed in Supplemental Table 1 and PCR products were sequenced by an automated sequencer (ABI PRISM 310; Applied Biosystems). The other 15 Chinese PCOS risk single-nucleotide polymorphisms (SNPs) that were used for genetic risk score (GRS) calculation were genotyped with Sequenom MassArray.

Statistical analysis

Quantitative variables of clinical characteristics of PCOS cases and controls were displayed as mean ± SD. Unpaired Student t tests were used to compare these features between cases and controls using SPSS version 22.0 (SPSS, Inc.). The Hardy-Weinberg equilibrium calculation was conducted by PLINK version 1.07 (http://pngu.mgh.harvard.edu/purcell/plink). In the replication study, allele frequency comparisons between cases and controls were performed by PLINK version 1.07. Then results were adjusted for age and BMI using logistic regression and were meta-analyzed with our previous PCOS GWAS data by using a fixed-effects model. The analysis procedures of our GWAS data were detailed described previously (10, 11).

The power to detect association between the tested SNP and PCOS was analyzed by Genetic Power Calculator (http://pngu.mgh.harvard.edu/purcell/gpc). A sample size of 1601 PCOS cases and 1238 controls could provide greater than 90% power (α = 0.01), assuming risk allele frequency of 0.05 and genotype relative risk of 1.8.

Genetic models were divided into additive (+/+ vs ± vs −/−), dominant (+/+ + ± vs −/−), and recessive (+/+ vs ± + −/−). In genotype-phenotype analysis for PCOS cases, the dominant model was selected considering the small number of individuals in the homozygous minor allele (AA) group. Unpaired Student t tests were used to compare clinical phenotypes between two genotype groups. Results were adjusted for age and BMI using liner regression analysis, and a P < 3.8 × 10−3 (0.05/13) was considered significant after Bonferroni correction for 13 quantitative traits.

The GRS for each individual was calculated by the total number of PCOS risk alleles. In total, one European PCOS-risk SNP that replicated in Chinese cohort and fifteen SNPs identified from Chinese PCOS GWAS were genotyped for GRS calculation. The association between the GRS and PCOS was assessed by logistic regression to adjust age and BMI. Receiver operating characteristic (ROC) curve was calculated for GRS, and area under the ROC curve (AUC) was used to estimate predictive accuracy.

Results

Basic clinical features

The clinical and metabolic characteristics of the replication cohort (1601 PCOS cases and 1238 controls) were displayed in Table 1. The age of PCOS group and control group were matched (29.98 ± 3.86 vs 30.15 ± 6.16; P > .1). PCOS cases had significantly higher mean BMI than controls (24.94 ± 4.66 vs 22.28 ± 3.12; P < .001). The serum levels of LH as well as T were significantly higher in women with PCOS compared with age-matched controls.

Table 1.

Characteristics of 1601 PCOS Cases and 1238 Controls in Current Replication Study

Table 1.

Characteristics of 1601 PCOS Cases and 1238 Controls in Current Replication Study

SNP selection

We screened the regions that cover 500 kb upstream and downstream of two European PCOS-risk SNPs (rs804279 in 8p32.1 and rs11031006 in 11p14.1) using our previous Chinese GWAS data (Figure 1). Nine independent SNPs (six located in 11p14.1 and three located in 8p32.1) with P < .05 were listed in Supplemental Table 2. Only one SNP, rs11031010, with P < 1 × 10−4 was selected for replication study in an independent cohort of 1601 PCOS cases and 1238 controls. Rs11031010, located in the region of FSHB gene, were in the same linkage disequilibrium (LD) block with European PCOS-risk SNP rs11031006 in both European and Chinese populations.

Figure 1.

Regional plots of two European PCOS loci using our previous GWAS data.

A, Chr 11p14.1 locus (FSHB/ARL14EP). B, Chr. 8p32.1 locus (GATA4/NEIL2). In each panel, association of individual SNP is plotted as −log10 _P_-value against chromosomal position. Results for both genotyped and imputed SNPs are shown. Symbol colors represent the LD of the SNP with the most significant SNP at each locus (purple diamond). The right y-axis shows the recombination rate estimated from 1000 Genomes Project CHB (Han Chinese in Beijing) and JPT (Japanese in Tokyo, Japan) data. LD maps were based on D′ values using CHB and JPT genotypes from the 1000 Genomes Project (phase 1 integrated data version 3, released March 2012).

Association testing

Allele and genotype frequencies for rs11031010 were summarized in Table 2. The genotype distribution of the analyzed SNP did not deviate from Hardy-Weinberg equilibrium. Minor allele frequency (MAF) of rs11031010 was significantly higher in PCOS group compared with control group (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.15–1.93; P = 2.76 × 10−3), indicating that rs11031010 was strongly associated with PCOS. The results changed slightly with adjustment for age and BMI (P = 2.34 × 10−3). Meta-analysis of the current replication study and our previous GWAS data shown that MAF difference of rs11031010 between PCOS and controls reached genome-wide significance (P = 4.27 × 10−8).

Table 2.

Association Analysis of rs11031010 Alleles and PCOS in the Current Study and Our Previous GWAS Study

Abbreviations: _P_adj, adjusted P by BMI and age; _P_meta, meta-analysis of GWAS and the current study by PLINK.

OR is for the minor allele.

Table 2.

Association Analysis of rs11031010 Alleles and PCOS in the Current Study and Our Previous GWAS Study

Abbreviations: _P_adj, adjusted P by BMI and age; _P_meta, meta-analysis of GWAS and the current study by PLINK.

OR is for the minor allele.

All 1601 cases fulfilled Rotterdam criteria for PCOS and comprised of four subtypes including OA+HA, OA+PCO, HA+PCO, and OA+HA+PCO. A total of 514 cases fulfilled NIH criteria for PCOS and presented with OA and HA, with or without PCO. Rs11031010 was also significantly associated with NIH PCOS (P = 1.52 × 10−3), with a slightly higher OR than that of Rotterdam PCOS (1.70 vs 1.49; Table 3).

Table 3.

Allele and Genotype Analysis in PCOS of Different Subgroups

Abbreviation: _P_adj, adjusted P by BMI and age.

a

Compared with control group.

OR is for the minor allele.

Table 3.

Allele and Genotype Analysis in PCOS of Different Subgroups

Abbreviation: _P_adj, adjusted P by BMI and age.

a

Compared with control group.

OR is for the minor allele.

Endocrinal and metabolic traits analysis in PCOS

The dominant model was selected for genotype-phenotype analysis in PCOS cases (Table 4). The mean level of LH in the AA+AC group was significantly higher compared with the CC group (12.40 ± 6.56 vs 10.28 ± 5.91; P = 1.60 × 10−4) even after adjustment for age and BMI and Bonferroni correction, indicating that risk allele A of rs11031010 was strongly associated with LH level in PCOS cases. The FSH levels of the two genotype groups were similar (P > .05) whereas the LH to FSH ratios (LH/FSH) were significantly different.

Table 4.

The Association Between Risk Allele of rs11031010 and Clinical Characteristics in PCOS Cases Using Dominant Model

Abbreviations: CHOL, cholesterol; F-GLU, fasting glucose; F-INS, fasting insulin; HDL, high-density lipoprotein; HOMA-IR, homeostasis model for insulin resistance; LDL, low-density lipoprotein; _P_adj, adjusted _P_-value by age and BMI using logistic regression; TG, triglycerides.

Table 4.

The Association Between Risk Allele of rs11031010 and Clinical Characteristics in PCOS Cases Using Dominant Model

Abbreviations: CHOL, cholesterol; F-GLU, fasting glucose; F-INS, fasting insulin; HDL, high-density lipoprotein; HOMA-IR, homeostasis model for insulin resistance; LDL, low-density lipoprotein; _P_adj, adjusted _P_-value by age and BMI using logistic regression; TG, triglycerides.

Genetic risk score analysis

A genetic risk score (GRS) was calculated using sixteen PCOS-risk SNPs in Chinese population: rs13429458 (THADA gene), rs12478601 (THADA gene), rs13405728 (LHCGR gene), rs2268361 (FSHR gene), rs2349415 (FSHR gene), rs4385527 (C9orf3 gene), rs3802457 (C9orf3 gene), rs10818854 (DENND1A gene), rs2479106 (DENND1A gene), rs1894116 (YAP1 gene), rs705702 (RAB5B gene), rs2272046 (HMGA2 gene), rs4784165 (TOX3 gene), rs2059807 (INSR gene), rs6022786 (SUMO1P1 gene), and rs11031010 (FSHB gene). The distribution of the GRS in PCOS and controls is displayed in Figure 2A. The mean GRS was 15 in the PCOS cases, with a range of 7–24, whereas the mean GRS was 14 in controls, with a range of 7–22. The GRS was highly associated with the diagnosis of PCOS (OR, 1.18; 95% CI, 1.15–1.21; P < 1.00 × 10−4). The overall OR changed only slightly after inclusion of age and BMI as covariates in logistic regression model (OR, 1.20; 95% CI, 1.17–1.23; P < 1.00 × 10−4). As shown in Figure 2B and Supplemental Table 3, the percentage of PCOS cases as well as the OR increased steadily with increasing GRS. ROC curve was calculated for GRS. The predictive accuracy of GRS, as demonstrated by AUC, was 0.601.

Figure 2.

The association between GRS and PCOS risk.

A, The distribution of the GRS in PCOS group and control group. B, The distribution of PCOS cases and control in each GRS group.

Discussion

In the present study, we replicated a recent European PCOS GWAS and identified a new genetic locus 11p14.1, FSHB, for Han Chinese women with PCOS. The genotype-phenotype analysis provided clues that FSHB plays an important role in the etiology of PCOS based on its association with LH level.

The FSHB gene codes for the beta subunit of FSH, which confers hormone specificity (19). FSH is a pituitary-secreted glycoprotein and shares a common alpha subunit with LH, thyroid stimulating hormone (TSH), and human chorionic gonadotropin (hCG). The FSH dimer binds to the FSH receptors (FSHR) expressed in granulosa cells of the ovary and Sertoli cells of the testis, and then initiates a subsequent signaling and biologic effects (20). The ovary response to FSH includes estradiol production and follicular development from the early antral stage to ovulation (21). FSHR has been established to be a PCOS risk gene, regardless of ethnicity. Our group first elucidated the association between the FSHR gene and PCOS using the GWAS approach and the identified most significant SNPs, rs2268361 and rs2349415, were also used for GRS calculation in the present study (11). Then, the role of FSHR gene in PCOS risk was confirmed by replication study in women of European ancestry and meta-analysis of recent published studies from China, the United States, and the Netherlands (14, 15). As a complement to FSHR gene, the ligand of FSH signaling, FSHB, is a novel PCOS-susceptibility gene which was identified in the European GWAS and replicated in a Chinese cohort in the present study. Both the ligand (FSHB gene) and the receptor (FSHR gene) confer risks to PCOS, indicating the importance of neuroendocrine in the pathogenesis of PCOS. In a PCOS rat model using letrozole, serum FSH level and Fshb mRNA level in the pituitary were significantly decreased whereas the Fsh receptor mRNA expression in the ovary was increased (22). PCOS women had higher FSHR mRNA expression in granulosa cells from stimulated follicles during controlled ovarian hyperstimulation (23). Additional functional studies are needed to clarify the functional role of FSHB gene as well as FSHR gene in PCOS pathogenesis.

The variant rs11031010 is located in the upstream of FSHB gene, which mapped to the 11p14.1 region. In our Chinese cohort, rs11031010 was the most significant marker; and in the previous European cohort, rs11031006 was the most significant marker. Rs110311010 is approximately 14 kb away from rs11031006 and they both map to the same LD in 11p14.1. The MAF difference of rs11031006 was also significant in our PCOS GWAS data (P = 1.20 × 10−4). These findings all support a common genetic susceptibility for PCOS given that the European GWAS–identified FSHB gene as well as the C9orf3 gene were shown to be associated with Chinese PCOS. Neither rs11031010 nor rs11031006 were reported to be functional SNPs in the published literature. There is a previously reported functional SNP rs10835638 (G > T), which located 211 bp upstream from the transcription start site of the FSHB gene. The T allele of rs10835638 presented with 50% reduced transcriptional activity in vitro compared with the G allele (24, 25). The rs10835638 is located 12 kb away from rs11031010 and also located in the same LD with rs11031010. Rs10835638 was also associated with PCOS subjects from our GWAS (P = 1.95 × 10−5). The identification of causative SNPs calls for fine-mapping and well-organized functional studies.

The higher risk allele A of FSHB variant rs11031010 was shown to be associated with higher LH levels, which is one hallmark of PCOS features, in both Chinese and European PCOS subjects. Increased LH could stimulate theca cells in the ovary and result in an excess of androgen production, elevating T-level feedback to the hypothalamus and affecting the production of gonadotropin (26). Besides higher LH levels, women with PCOS carrying the AA or AC genotype had higher T levels than those carrying the CC genotype, although the difference did not reach a significant threshold (46.53 ± 17.68 vs 44.88 ± 25.03; P > .05). Moreover, the homozygous Fshb knockout female mice demonstrated lower serum FSH levels, higher serum LH levels, and doubled Fshr expression in the ovary compared with wide-type mice (27). The SNP located in the promoter region of FSHB gene, rs10835638, was found to be associated with lower FSH and higher LH in men (25). The disturbance of feedback regulation of gonadotropin release may partly explicate the increased LH level that related to the FSHB gene. The precise mechanism that accounts for the association between the FSHB variant and LH level needs to be elucidated by additional studies.

This study did not replicate the European PCOS-associated locus 8p32.1 (GATA4/NEIL2 gene). We screened a region that covers 500 kb upstream and downstream of the identified SNP (rs804279) using our previous Chinese GWAS data. No SNPs were selected for further replication study given that mostly P > .05 and the minimum P ≈ 4 × 10−3. It has been well accepted that LD patterns are distinct across ethnicities. The LD between European-identified variants in GATA4/NEIL2 and truly functional variants may be disrupted in the Han Chinese. Replication studies on locus 8p32.1 are needed in other non-European populations.

A GRS based on 16 SNPs in 12 loci showed strong and graded associations with PCOS, providing evidence for the genetic basis of PCOS etiology. However, the predictive ability of GRS was not very high (AUC = 0.601). PCOS is a complex disease and both genetic and nongenetic factors contribute to its pathogenesis. This study did not incorporate nongenetic influence, such as different environmental exposures.

Thus, we replicated that the FSHB gene is associated with PCOS and LH level in Han Chinese women. FSHB is likely to play an important role in the etiology of PCOS, regardless of ethnicities.

Acknowledgments

We thank all participants in this study.

This work was supported by the National Basic Research Program of China (973 Program) (2012CB944700), the National Natural Science Foundation of China (81430029, 81490743, 31371453, 31571548, 81501223), and the Young Scholars Program of Shandong University (2015WLJH54), Doctoral Innovation Fund Projects from Shanghai Jiao Tong University School of Medicine (BXJ201422).

Author Contributors: H.Z. and Z.-J.C. designed and supported the study; L.C. and Z.W. collected all clinical data and blood samples; Y.T. and Y.P. performed the experiments; Y.T. and H.C. analyzed the data; Y.T. drafted the manuscript; H.Z., J.X., and Y.D. revised the manuscript; Y.T., H.Z., H.C., Y.P., L.C., Y.D., Z.W., J.X., and Z.-J.C. gave their final approval of the version to be published.

Disclosure Summary: The authors have nothing to disclose.

Y.T., H.Z., and H.C. contributed equally to the study.

Abbreviations

• AUC
• BMI
• CI
• FSHB
  follicle-stimulating hormone B polypeptide
• GRS
• GWAS
  genome-wide association study
• HA
• LD
• MAF
• NIH
  National Institutes of Health
• OA
• OR
• PCO
• PCOS
  polycystic ovary syndrome
• ROC
  receiver operating characteristic
• SNP
  single-nucleotide polymorphism.

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