Systematic Evaluation of Genetic Variants for Polycystic Ovary Syndrome in a Chinese Population
Systematic Evaluation of Genetic Variants for Polycystic Ovary Syndrome in a Chinese Population
Yuping Xu 0 1 2 3
Zhiqiang Li 0 1 2 3
Fenglian Ai 0 1 2 3
Jianhua Chen 0 1 2 3
Qiong Xing 0 1 2 3
Ping Zhou 0 1 2 3
Zhaolian Wei 0 1 2 3
Yongyong Shi 0 1 2 3
Xiao-Jin He 0 1 2 3
Yunxia Cao 0 1 2 3
0 Funding: This work was supported by the National Basic Research Program of China 2012CB944704 (recipient:YC) and 2015CB559100 (recipient: YS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
1 Data Availability Statement: All relevant data are within the paper
2 Editor: Stephen L Atkin, Weill Cornell Medical College Qatar , QATAR
3 1 Reproductive Medicine Center, Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University , Hefei, 230022, China , 2 Institute of Reproductive Genetics, Anhui Medical University , Hefei, 230022, China , 3 Anhui Provincial Engineering Technology Research Center for Biopreservation and Artificial Organs , Hefei, 230022, China, 4 The Bio-X Institutes , Shanghai Jiao Tong University , 1954 Huashan Road, Shanghai, 200030 , China
To date, eleven genome-wide significant (GWS) loci (P < 5×10−8) for polycystic ovary syndrome (PCOS) have been identified through genome-wide association studies (GWAS). Some of the risk loci have been selected for replications and validated in multiple ethnicities, however, few previous studies investigated all loci. Scanning all the GWAS variants would demonstrate a more informative profile of variance they explained. Thus, we analyzed all the 17 single nucleotide polymorphisms (SNPs) mapping to the 11 GWAS loci in an independent sample set of 800 Chinese subjects with PCOS and 1110 healthy controls systematically. Variants of rs3802457 in C9orf3 locus (P = 5.99×10−4) and rs13405728 in LHCGR locus (P = 3.73×10−4) were significantly associated with PCOS after the strict Bonferroni correction in our data set. The further haplotype analysis indicated that in the block of C9orf3 gene (rs4385527 and rs3802457), GA haplotype played a protective role in PCOS (8.7 vs 5.0, P = 9.85×10−6, OR = 0.548, 95%CI = 0.418-0.717), while GG haplotype was found suffering from an extraordinarily increased risk of PCOS (73.6% vs79.2%, P = 3.41×10−5, OR = 1.394, 95%CI = 1.191-1.632). Moreover, the directions of effects for all SNPs were consistent with previous GWAS reports (P = 1.53×10−5). Polygenic score analysis demonstrated that these 17 SNPs have a significant capacity on predicting case-control status in our samples (P = 7.17×10−9), meanwhile all these gathered 17 SNPs explained about 2.40% of variance. Our findings supported that C9orf3 and LHCGR loci variants were vital susceptibility of PCOS.
Competing Interests: The authors have declared
that no competing interests exist.
Polycystic ovary syndrome (PCOS) is a complex metabolic and endocrine disorder in
reproductive-age women with a prevalence of approximately 5%-10% [1,2]. The syndrome is defined
by clinical or biochemical hyperandrogenism (HA), oligomenorrhea/amenorrhea (O) and
polycystic ovaries (PCO) on ultrasonography . It is associated with obesity, infertility and
metabolic complications including impaired glucose tolerance (IGT), insulin resistance (IR)
and dyslipidemia etc. Moreover, it is also common with increased risk of endometrial cancer,
type 2 diabetes (T2D) and other cardiovascular diseases [4,5,6] which leading to the
detrimental impact on women's health.
Despite the pathogenesis of the disorder has not been completely elucidated yet, previous
epidemiologic studies have suggested that PCOS have a strong genetic background . Two
genome-wide association study (GWAS) conducted in Chinese Han population indicated that
common variants located in 11 genomic areas (the first GWAS: THADA, LHCGR and
DENND1A loci; the second GWAS: FSHR, C9orf3, INSR, HMGA2, YAP1, RAB5B/SUOX,
TOX3 and SUMO1P1 loci) were associated with PCOS [8,9]. And several studies in European
ancestry cohorts provided further evidence for association with variants from LHCGR, FSHR,
THADA, YAP1 and DENND1A loci and PCOS [10,11,12,13]. Moreover, another recent
followup study replicated four of the PCOS susceptibility loci (DENND1A, THADA, FSHR and
INSR) in a cohort of European population, and the risk score analysis indicated the vital role in
the etiology of PCOS across ethnicities for the susceptibility loci identified in the Chinese
Obviously, these prior GWAS and follow-up studies have improved our understanding of
the pathophysiology of PCOS. However, to our knowledge, a systematic study, to fully
determine the effects of the previous reported genome-wide significant variants in an independent
sample, is rarely conducted. Here, we sought to replicate association with all the genetic
variants identified in the two Chinese GWAS in an independent Han Chinese cohort study, which
would present a more informative profile of the previous reported variants. Additionally, a
previous study suggested that some of these variants might be correlated with some phenotypes
(such as hypersecretion of testosterone and luteinizing hormone, insulin resistance, and etc.) in
PCOS patients . Thus, in this study, we also investigate the correlations between the
phenotypes of PCOS and the PCOS susceptibility variants.
The cohort study consisted of 800 cases with PCOS and 1,110 normal controls. All the PCOS
women were recruited at the Department of Obstetrics and Gynecology of the First Affiliated
Hospital of Anhui Medical University, and the healthy controls data were collected from
hospitals (physical examination centers) and community surveys. Medical-history and basic
character profile (origin, age, height and weight) were obtained by clinical visit and surveys. All the
subjected were of central Han Chinese origin. All the PCOS cases were diagnosed by at least
two gynecologists according to the Revised 2003 Consensus on Diagnostic Criteria , and
thus met any two of the following three criteria: oligo- or anovulation, clinical and/or
biochemical signs of hyperandrogenism and polycystic ovary morphology. The body mass index (BMI)
was calculated using the following formula: weight (kg)/height (m)2. For the PCOS patients,
the levels of hormones containing follicular-stimulating hormone (FSH), luteinizing hormone
(LH), total testosterone (T) and prolactin (PRL) were measured by chemiluminescence
immunoassays. And 75-g oral glucose tolerance tests (OGTT) were conducted in the cases. Plasma
glucose levels at 0 min and 2 hours after OGTT were measured using the oxidase method and
insulin levels were measured by chemiluminescence immunoassays. The homeostasis model
assessment of insulin resistance (HOMA-IR) was derived by the calculation: fasting plasma
glucose (mmol/l) fasting insulin (mIU/ml)/22.5. Clinical characteristics are displayed in
Cases(n = 800)
Data are presented as the mean ± standard deviation. BMI: body mass index; T: total testosterone; FSH: follicular-stimulating hormone; LH: luteinizing
hormone; PRL: prolactin; 2h-Glucose and 2h-Insulin: glucose and insulin levels at 2 hours after OGTT; HOMA-IR: homeostasis model assessment-insulin
This study was conducted in accordance with the tenets of the Declaration of Helsinki and
its Amendments Approval was received from the Ethics Committee of Anhui Medical
University. After providing a complete description of the study to the subjects, written informed
consent was obtained.
The 17 previously reported independent single nucleotide polymorphisms (SNPs) from 11 loci
were genotyped in this study. Genotyping was performed using the Ligase Detection
ReactionPolymerase Chain Reaction (LDR-PCR) method. For each plate, one sample was randomly
selected to be genotyped twice, and all the non-missing genotypes were consistent. The
successful rate of genotyping for all SNPs was over 95%, and the genotype distributions in both cases
and controls obeyed Hardy–Weinberg equilibrium (HWE).
HWE analysis was conducted adopting PLINK , and a P value of > 0.05 was considered
obeying HWE. We analyzed the association between the 17 SNPs and PCOS using additive
logistic regression model. In order to eliminate the potential effect of BMI, BMI was considered
as a covariate for adjustment. The haplotype analyses of THADA, FSHR, C9orf3, DENND1A
genes were also performed with SHEsis software, available online http://analysis.bio-x.cn/
myAnalysis.php. The haplotypes were generated using expectation–maximization algorithm.
Frequencies of the different haplotypes were compared with Chi Square analysis. Given the
prior evidence of association with PCOS for the SNPs, adjustment for multiple comparisons
was finished adopting Bonferroni correction. After correction, P value < 2.9 × 10−3 was
considered significant. Linear regression analyses with BMI covariate were used to test association
between the SNPs and PCOS phenotypes (hormones levels: T, FSH, LH and RPL; and glucose
homeostasis: fasting glucose, 2-hour postprandial glucose, fasting insulin, 2-hour insulin and
HOMA-IR). All phenotypes with abnormal distributions were logarithmically transformed.
The analyses were also carried out using SNPTEST . A Bonferroni corrected P value of
1.47 × 10−3 (0.05/34; accounting for 17 SNPs against 2 trait categories: hormones and glucose
homeostasis) was considered statistically significant in genotype–phenotype analyses.
Polygenic scoring analysis was conducted as listed below: the risk-profiles of the 17 SNPs
from the previous reports were selected to generate scores using PLINK “—score” function.
For each individual, the sum across SNPs of the number of reference alleles (0,1 or 2) at that
SNP multiplied by the score for that SNP was calculated, and then the average score per
nonmissing SNP was generated. The case-control status was predicted by logistic regression
analysis of polygenic scores. Nagelkerke R2 showed an estimate of the variance explained. We
conducted sign tests using the binomial distribution, comparing the direction of ORs of the 17
SNPs between current study and previous GWAS reporters. P value was generated under the
null hypothesis (H0: p = 0.50).
The Basic Information of the Study Population and the Selected SNPs
The clinical characteristics of the PCOS patients and controls have presented in Table 1.
Average ages were 26.5 years in the cases and 26.0 years in the controls, respectively. Mean BMI was
23.5 in the former group, as well as 20.4 in the latter. The hormone and glucose homeostasis
were only measured in the cases, and the average values for the characteristics were listed in
Table 1. The basic information of the 17 SNPs detected was demonstrated in Table 2. The
results indicated that all the study population obeyed the Hardy–Weinberg equilibrium.
The Association Analysis Between the 17 SNPs Variants and PCOS
Association analysis between the 17 SNPs and PCOS were systematically illustrated in Table 3.
The directions of effects for all these SNPs were consistent with previous reports (binomial test
P = 1.53 × 10−5). Of the 17 SNPs, rs13405728 of LHCGR gene and rs3802457 of C9orf3 gene
were closely related to PCOS even after the rigorous Bonferroni correction. The G allele
SNP ref.: single necleaue polymorphism reference; Allel: major > minor HWE: Hardy–Weinberg equilibrium, PHWE more than 0.05 indicated that the cases
and the controls obeyed Hardy–Weinberg equilibrium.
9.10 × 10−3
0.72 (1.59 × 10−20)
0.67 (1.73 × 10−23)
8.92 × 10−3
0.72 (3.48 × 10−23)
3.73 × 10−4
0.71 (7.55 × 10−21)
5.99 × 10−4
0.77 (5.28 × 10−14)
4.41 × 10−3
1.47 (6.90 × 10−15)
3.79 × 10−3
1.27 (1.08 × 10−22)
0.87 (9.89 × 10−13)
1.19 (2.35 × 10−12)
0.84 (5.87 × 10−9)
1.51 (9.40 × 10−18)
1.34 (8.12 × 10−19)
1.27 (8.64 × 10−26)
0.70 (1.95 × 10−21)
1.15 (3.64 × 10−11)
1.14 (1.09 × 10−8)
1.13 (1.83 × 10−9)
frequency of rs13405728 in the controls demonstrated extraordinarily higher than that of the
PCOS cases (24.6% vs 19.2%, P = 3.73 × 10−4). The results also indicated that the G allele
played a protective role in PCOS (OR = 0.72, 95 CI = 0.60–0.86). However, A allele frequency
of rs3802457 of C9orf3 gene in the controls showed extremely lower than PCOS cases (6.4% vs
10.1%, P = 5.99 × 10−4). Thus, it suggested that the A allele was a risk susceptibility to PCOS
(OR = 0.62, 95%CI = 0.48–0.82).
Moreover, additional four variants in the DENND1A, THADA and YAP1 loci presented
marginally significance (P value < 0.01). They were rs10986105 at DENND1A locus
(OR = 1.48, 95%CI = 1.13–1.94, P = 4.41 × 10−3), rs12478601/rs12468394 at THADA locus
(OR = 0.79 and 0.80, P = 8.92 × 10−3 and 9.10 × 10−3) and rs1894116 at YAP1 locus
(OR = 1.30, 95%CI = 1.09–1.55, P = 3.79 × 10−3), respectively (Table 3).
To assess the polygenic signal from the previous GWAS report adapted to our samples, we
conducted a polygenic scoring analysis. We used the published GWAS data set as the training
set, and tested on our data set. It indicates that the 17 SNPs have a significant capacity to
predict case-control status in our samples (P = 7.17 × 10−9), and the proportions of variance in
case-control status explained by these SNPs is 2.40% (based on all 17 SNPs analyzed together).
The non-significant SNPs set (n = 15), where the significant C9orf3 and LHCGR SNPs
(rs13405728 and rs3802457) are not included, can explain about 1.42% of the variance
(P = 7.93 × 10−6). Whereas, the SNPs with association P > 0.05 (n = 10) can explain about
0.95% of the variance (P = 2.47 × 10–4). These scores reveal association with PCOS for SNPs
that individually were not powered to show association
Haplotype Analysis of THADA, FSHR, C9orf3 and DENND1A and
In this systematic study, four blocks were produced for the further haplotype analysisme in
THADA, FSHR, C9orf3 and DENND1A loci. After strict Bonferroni correction, P value less
than 0.125 was considered to be significantly different. From the results in Table 4, GA
haplotype (rs4385527 and rs3802457 of C9orf3 gene) in the controls was significantly higher than
that of the cases (8.7% vs 5.0%, P = 9.85×10−6). This indicated that women with GA haplotype
might be a protective factor (OR = 0.548, 95%CI = 0.418–0.717) against PCOS. However, GG
haplotype in the cases was significantly higher than that in the controls (79.2% vs 73.6%,
P = 3.41×10−5), which revealed GG haplotype to be a risk factor suffering from PCOS
(OR = 1.394, 95%CI = 1.191–1.632).
We also explored some other haplotypes presented with marginally significance between
the controls and the PCOS cases (P values marked with# in Table 4), however, the differences
failed to reach statistical level after strict Bonferroni correction.
The SNP sites for the block of THADA gene is: rs12468394, rs13429458 and rs12478601. The SNP sites for the block of FSHR gene is: rs2268361 and
rs2349415. The SNP sites for the block of C9orf3 gene is: rs4385527 and rs3802457. The SNP sites for the block of DENND1A gene is: rs10818854,
rs2479106 and rs10986105. P value less than 0.0125 are marked in bold. P value less than 0.05 but more than 0.0125 are marked with#
Association analyses of the 17 SNPs against quantitative traits were conducted in the PCOS
group (S1 Table). Unfortunately, none of the SNPs illustrated significant association with the
quantitative traits after multiple test corrections.
PCOS is defined as a complicated genetic disease, whereas the etiology has not been elucidated
sufficiently. Previous GWAS had identified 11 loci (including 17 independent SNPs) associated
with PCOS with P <5×10−8 [8,9]. McAllister et al. predicted that the candidate genes by
the PCOS GWAS might comprise a hierarchical signaling network which would influence the
theca cell hormone biosynthesis. This would bring a completely new era of the genetic
diagnostic for PCOS. In this study, we tended to confirm the effects of all these variants on PCOS
adopting an independent sample. We found that the effects of all the 17 SNPs were
directionally consistent with those in previous Chinese GWAS  and other ethnicity [12,13]. Even
after strict Bonferroni correction, two of the 11 previously reported susceptibility loci
demonstrated significant association with PCOS in our sample (LHCGR and C9orf3). The further
polygenic score analysis showed that these SNPs collectively accounted for approximately
2.40% of the variance to PCOS, suggested an important role in the etiology of PCOS for them.
To our knowledge, it was the first systematic replication study of all the reported SNPs
variants from the GWAS studies with strict statistical analysis (Bonferroni correction). The validity
of the findings should be convincing as the bias was controlled to the lowest level. Additional
scores for non-significant SNPs (P>2.9×10−3 or 0.05) revealed association with PCOS for
SNPs that individuals were not valid to show association, whereas risk score analysis
demonstrates the validity contrasted with individual SNP analysis.
In the present study, after the strict Bonferroni correction, A allele of rs3802457 (C9orf3
gene) was considered as a risk susceptibility to PCOS (P = 5.99×10−4). Compared with the
previous GWAS results, the risk rate were extremely similar to each other (OR:0.62 vs 0.77). It was
well acknowledged that haplotype analysis could identify chromosomes where sequencing
might be finished to explore functional variants. To our knowledge, it was the first time to
perform the haplotype analysis of C9orf3 gene (rs4385527 and rs3802457) in such a large cohort
study of Chinese PCOS patients. The results revealed GG haplotype of C9orf3 gene as a risk
factor suffering from PCOS, whereas haplotype GA might be a protective factor against PCOS.
C9orf3, known as Aminopeptidase O, encodes a member of the M1 zinc aminopeptidase family
that catalyzes the removal of an amino acid from the amino terminus of a protein or peptide. It
has been reported to play an important role in the generation of angiotensin IV [19,20].
However, the function of C9orf3 was rarely discussed. Kerns et al. reported that variants within
C9orf3 was detected to be associated with the development of erectile dysfunction in
AfricanAmerican men who have received radiotherapy for prostate cancer . Arefi et al.
considered that rennin-angiotensin system (RAS) played a vital role in the pathogenesis of PCOS
including insulin resistance. Renin activity combining with other clinical variables behaved
more sensitive to diagnose women with PCOS according to the previous study . Therefore,
we hypothesized that C9orf3 variants might lead to rennin-angiotensin system abnormality
which would cause or deteriorate the pathogenesis of PCOS. Although rs3802457 located in
intron, there were plentiful possible mechanisms that could explain the alteration of C9orf3,
such as: splicing variation, microRNAs regulation or some other undetected copy-number
variation (CNV), etc.
The LHCGR gene encodes the LH/choriogonadotropin (HCG) receptor of two structurally
homologous glycoproteins which belongs to the family of G-protein coupled receptors .
LHCGR is expressed on theca cells, differentiated granulosa cells (GCs) and luteal cells of the
ovary. It has been well known that, LH induces follicular development containing maturation,
ovulation and luteinization during the midcycle surge of female menstrual cycle and hCG is
required for the maintenance of a successful pregnancy [25,26]. LHCGR SNP variants were
identified as PCOS susceptibility loci (rs13405728) in the first Chinese GWAS. In our study
population, we found that G allele frequency of rs13405728 in the controls was closely
associated with the PCOS cases (24.6% vs 19.2%, P = 3.73 × 10−4) and the risk factor behaved
extremely similar to the former GWAS study (OR: 0.72 vs 0.71). Meanwhile, a
genotype-phenotype correlation analysis also revealed that LHCGR (rs13405728) variant was associated with
the phenotype in PCOS with oligo-ovulation or anovulation in another Chinese population
. Our results combining with the previous reports provided forceful supports for the
relations between LHCGR gene variants and PCOS in Chinese population. Interestingly, due to the
rarity of rs13405728 in Europeans (comparing to Chinese), most of the previous replication
analysis in European cohorts study failed to explore any significant evidence between
rs13405728 and PCOS [10,11,13,27]. But one excellent mapping study in a European ancestry
cohort identified another two SNPs in LHCGR locus were significantly associated with PCOS
. Nevertheless, plentiful evidences from different ethnicity have confirmed that LHCGR
variants as a vital genetic factor for the pathogenesis of PCOS.
Although the present results offered the most significant genetic value for C9orf3 and
LHCGR variants of PCOS, the OR of the two variants for association with PCOS was not
particularly greater than the other variants. This raised the possibility that they might be emerged
as the most significant by statistical chance, even with the current sample size.
In summary, we successfully confirmed that two (LHCGR and C9orf3) of 11 previously
identified PCOS loci by a systematic variants association study in an independent Chinese
cohort. Haplotype analysis of C9orf3gene revealed GG haplotype as a risk genetic factor for
PCOS. However, the detailed mechanisms by which LHCGR and C9orf3 caused PCOS need
further clinical investigation and functional studies in vitro and in vivo.
We especially appreciate all the voluntary women for participating in this study. This work was
supported by the National Basic Research Program of China (2012CB944704 and
Conceived and designed the experiments: YS YC XH. Performed the experiments: YX ZL JC.
Analyzed the data: YX ZL XH. Contributed reagents/materials/analysis tools: YX FA QX PZ
ZW. Wrote the paper: YX ZL XH.
1. Goodarzi MO , Dumesic DA , Chazenbalk G , Azziz R. Polycystic ovary syndrome: etiology, pathogenesis and diagnosis . Nat Rev Endocrinol . 2011 ; 7 ( 4 ): 219 - 31 . PMID: 21263450. doi: 10.1038/nrendo. 2010.217
2. Li R , Zhang Q , Yang D , Li S , Lu S , Wu X , et al. Prevalence of polycystic ovary syndrome in women in China: a large community-based study . Hum Reprod . 2013 ; 28 ( 9 ): 2562 - 9 . PMID: 23814096. doi: 10. 1093/humrep/det262
3. Rotterdam ESHRE / ASRM-Sponsored PCOS consensus workshop group . Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome(PCOS) . Hum Reprod . 2004 ; 19 ( 1 ): 41 - 7 . PMID: 14688154.
4. Carmina E. Cardiovascular risk and events in polycystic ovary syndrome . Climacteric . 2009 ; 12 Suppl 1 : 22 - 5 . PMID: 19811236.
5. Kandaraki E , Christakou C , Diamanti-Kandarakis E. Metabolic syndrome and polycystic ovary syndrome . . . and vice versa . Arq Bras Endocrinol Metabol . 2009 ; 53 ( 2 ): 227 - 37 . PMID: 19466215 .
6. Lindholm A , Andersson L , Eliasson M , Bixo M , Sundström-Poromaa I. Prevalence of symptoms associated with polycystic ovary syndrome . Int J Gynaecol Obstet . 2008 ; 102 ( 1 ): 39 - 43 . PMID: 18321516. doi: 10.1016/j.ijgo. 2008 .01.023
7. Legro RS . The genetics of polycystic ovary syndrome . Am J Med. 1995 Jan 16 ; 98 (1A): 9S - 16S . PMID: 7825646.
8. Chen ZJ , Zhao H , He L , Shi Y , Qin Y , Shi Y , et al. Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16 .3, 2p21 and 9q33.3. Nat Genet . 2011 ; 43 ( 1 ): 55 - 9 . PMID: 21151128. doi: 10.1038/ng.732
9. Shi Y , Zhao H , Shi Y , Cao Y , Yang D , Li Z , et al. Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome . Nat Genet . 2012 Sep; 44 ( 9 ): 1020 - 5 . PMID: 22885925. doi: 10. 1038/ng.2384
10. Goodarzi MO , Jones MR , Li X , Chua AK , Garcia OA , Chen YD , et al. Replication of association of DENND1A and THADA variants with polycystic ovary syndrome in Europeancohorts . J Med Genet . 2012 ; 49 ( 2 ): 90 - 5 . PMID: 22180642. doi: 10.1136/jmedgenet- 2011 -100427
11. Welt CK , Styrkarsdottir U , Ehrmann DA , Thorleifsson G , Arason G , Gudmundsson JA , et al. Variants in DENND1A are associated with polycystic ovary syndrome in women of European ancestry . J Clin Endocrinol Metab . 2012 ; 97 ( 7 ): E1342 -7. PMID: 22547425. doi: 10.1210/jc.2011- 3478
12. Mutharasan P , Galdones E , Peñalver Bernabé B , Garcia OA , Jafari N , Shea LD , et al. Evidence for chromosome 2p16.3 polycystic ovary syndrome susceptibility locus in affected women of Europeanancestry . J Clin Endocrinol Metab . 2013 ; 98 ( 1 ): E185 - 90 . PMID: 23118426. doi: 10.1210/jc.2012- 2471
13. Louwers YV , Stolk L , Uitterlinden AG , Laven JS . Cross-ethnic meta-analysis of genetic variants for polycystic ovary syndrome . J Clin Endocrinol Metab . 2013 ; 98 ( 12 ): E2006 - 12 . PMID: 24106282. doi: 10.1210/jc.2013- 2495
14. Brower MA , Jones MR , Rotter JI , Krauss RM , Legro RS , Azziz R , et al. Further investigation in europeans of susceptibility variants for polycystic ovary syndrome discovered in genome-wide association studies of Chinese individuals . J Clin Endocrinol Metab . 2015 ; 100 ( 1 ): E182 -6. PMID: 25303487. doi: 10.1210/jc.2014- 2689
15. Cui L , Zhao H , Zhang B , Qu Z , Liu J , Liang X , et al. Genotype-phenotype correlations of PCOS susceptibility SNPs identified by GWAS in a large cohort of Han Chinese women . Hum Reprod . 2013 Feb; 28 ( 2 ): 538 - 44 . PMID: 23208300. doi: 10.1093/humrep/des424
16. Purcell S , Neale B , Todd-Brown K , Thomas L , Ferreira MA , Bender D , et al. PLINK: a tool set for wholegenome association and population-based linkage analyses . Am J Hum Genet . 2007 ; 81 ( 3 ): 559 - 75 . PMID: 17701901 .
17. Marchini J , Howie B , Myers S , McVean G , Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes . Nat Genet . 2007 ; 39 ( 7 ): 906 - 13 . PMID: 17572673 .
18. McAllister JM , Legro RS , Modi BP , Strauss JF 3rd. Functional genomics of PCOS: from GWAS to molecular mechanisms . Trends Endocrinol Metab . 2015 ; 26 ( 3 ): 118 - 24 . PMID: 25600292. doi: 10. 1016/j.tem. 2014 .12.004
19. Díaz-Perales A , Quesada V , Sánchez LM , Ugalde AP , Suárez MF , Fueyo A , et al. Identification of human aminopeptidase O, a novel metalloprotease with structural similarity to aminopeptidase B and leukotriene A4 hydrolase . J Biol Chem . 2005 ; 280 ( 14 ): 14310 - 7 . PMID: 15687497.
20. Li XC , Campbell DJ , Ohishi M , Yuan S , Zhuo JL. AT1 receptor-activated signaling mediates angiotensin IV-induced renal cortical vasoconstriction in rats . Am J Physiol Renal Physiol . 2006 ; 290 ( 5 ): F1024 - 33 . PMID: 16380463 .
21. Kerns SL , Ostrer H , Stock R , Li W , Moore J , Pearlman A , et al. Genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with the development of erectile dysfunction in African-American men after radiotherapy for prostate cancer . Int J Radiat Oncol Biol Phys . 2010 ; 78 ( 5 ): 1292 - 300 . PMID: 20932654. doi: 10.1016/j.ijrobp. 2010 .07.036
22. Arefi S , Mottaghi S , Sharifi AM . Studying the correlation of renin-angiotensin-system (RAS) components and insulin resistance in polycystic ovary syndrome (PCOs) . Gynecol Endocrinol . 2013 ; 29 ( 5 ): 470 - 3 . PMID: 23461768. doi: 10.3109/09513590.2013.769513
23. Uncu G , Sözer MC , Develioğlu O , Cengiz C. The role of plasma renin activity in distinguishing patients with polycystic ovary syndrome (PCOS) from oligomenorrheic patients without PCOS . Gynecol Endocrinol . 2002 ; 16 ( 6 ): 447 - 52 . PMID: 12626031 .
24. Atger M , Misrahi M , Sar S , Le Flem L , Dessen P , Milgrom E. Structure of the human luteinizing hormone-choriogonadotropin receptor gene: unusual promoter and 5' non-coding regions . Mol Cell Endocrinol . 1995 ; 111 ( 2 ): 113 - 23 . PMID: 7556872 .
25. Dufau ML . The luteinizing hormone receptor . Annu Rev Physiol . 1998 ; 60 : 461 - 96 . PMID: 9558473 .
26. Kubota T. Update in polycystic ovary syndrome: new criteria of diagnosis and treatment in Japan . Reprod Med Biol . 2013 ; 12 ( 3 ): 71 - 77 . PMID: 23874146 .
27. Lerchbaum E , Trummer O , Giuliani A , Gruber HJ , Pieber TR , Obermayer-Pietsch B. Susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2p21, and 9q33.3 in a cohort of Caucasian women . Horm Metab Res . 2011 ; 43 ( 11 ): 743 - 7 . PMID: 22009367. doi: 10.1055/s- 0031 - 1286279