Intro
Polycystic ovary syndrome (PCOS) is the most prevalent endocrinopathy among women of childbearing age,
affecting 5%-20% of females aged 18-44 years worldwide
( 1 ). It is a complex systemic condition linked to numerous health issues, such as type 2 diabetes, dyslipidaemia,
heart disease, increased risk of stroke, obesity, endometrial cancer, anxiety, and depression ( 2 ).
Under ultrasonography, multiple small cysts are observed
in the ovaries, leading to the term "polycystic ovaries,"
which indicates a disruption in the normal development of
follicles ( 3 ). The main characteristics associated with this
condition are anovulatory infertility, polycystic ovaries,
obesity, hyperandrogenism, and insulin resistance ( 4 ). Although the exact aetiology behind PCOS is not fully understood, it appears to be the result of an interplay of genetic,
metabolic, endocrine, and environmental factors ( 5 ). Twin
studies suggest that PCOS is a polygenic disorder linked to
the X chromosome, with 72% of the risk attributed to genetics ( 6 ). Identifying candidate genes for PCOS has been
challenging due to its uncertain causes, diverse characteristics, and clinical presentations. In Han, China, the first
genome-wide association studies (GWAS) identified three
susceptibility loci for PCOS: 2p16.3, 2p21, and 9q33.3.
These loci are mapped to thyroid adenoma-associated protein I ( THADA ), luteinising hormone/choriogonadotropin
receptor ( LHCGR ), and DENN/MADD domain-containing
1A ( DENND1A ), respectively ( 7 ).
THADA is linked to disruptions in energy metabolism
that lead to a decrease in energy production and an increased vulnerability to obesity, thus impacting the risk of
PCOS. The connections between genetic variations within
the THADA gene with type 2 diabetes and insulin resistance further exacerbate PCOS symptoms ( 1 ). Ovarian theca cells, testicular Leydig cells, and adipose tissue express
the 11-exon LHCGR gene on chromosome 2. This receptor
for luteinising hormone (LH) and human chorionic gonadotropin (hCG) is involved in steroidogenesis. Ovarian steroidogenesis may be affected by numerous LHCGR gene
single nucleotide polymorphisms (SNPs) ( 8 ). The DENN
D1A gene has a crucial role in the clathrin-mediated endo
cytosis machinery. This gene has two primary transcripts,
DENND1A variant 1 and DENND1A variant 2. The latter is
altered in theca cells of women with PCOS ( 9 ).
Another GWAS project suggested eight new candidate
risk loci for PCOS in the Chinese population, including
the follicle-stimulating hormone receptor ( FSHR ) gene
( 10 ). The cytochrome P450 17A1 ( CYP17A1 ) gene encodes an enzyme called cytochrome P450 17A1, a ratelimiting enzyme in androgen production. Research has
demonstrated that women with PCOS exhibit higher activity and expression of this specific enzyme in their ovarian theca cells, thus contributing to hyperandrogenaemia
and insulin resistance ( 11 ).
This is the first study to explore associations between DENND1A rs2479106 and rs10986105, LHCGR
rs13405728, FSHR rs6166, THADA rs13429458, and CY
P17A1 rs743572 gene polymorphisms and PCOS anovulatory infertility in Malay women. Additionally, we evaluated
the phenotypic effects of the genotypes of these SNPs on
clinical and endocrine parameters in infertile women with
PCOS (cases) and infertile women without PCOS (controls).
Results
The clinical and endocrine characteristics of the infertile-PCOS and control groups are summarised in Table 1 . Statistically significant differences were observed between the two groups in terms of age, weight, BMI, day
21 progesterone levels, testosterone levels, and the presence of dysmenorrhoea (P<0.05). Day 21 progesterone
levels were notably higher in the control group, reflecting
ovulatory cycles, whereas the infertile-PCOS group exhibited significantly lower levels, indicating anovulation.
Both groups displayed borderline elevations in LDL and
total cholesterol. Menstrual irregularities were observed
in 88.9% of the infertile-PCOS group.
Only the LHCGR rs13405728 and THADA rs7568365
polymorphisms showed significant differences in genotype and allele frequencies between cases and controls
(P<0.002, Table 2 ). For the rs13405728 SNP, 71% of
cases carried the minor G allele versus 29% with the major A allele, whereas 45% of controls carried the G allele
versus 55% with the A allele (χ²=13.35, P<0.001). For the
rs7568365 polymorphism, the minor T allele was more
frequent in controls than in cases: 30% of infertile-PCOS
cases carried the T allele versus 70% with the major C allele, while 59% of controls carried the T allele and 41%
the C allele (χ²=16.5, P<0.001).
A significant association was found between the LHCGR
rs13405728 and THADA rs7568365 polymorphisms and
the development of PCOS-related anovulatory infertility
under four inheritance models (P<0.05, Table 3 ). Given
that BMI exacerbates PCOS symptoms and contributes to
anovulation, and that age impacts ovarian function, odds
ratios (OR) were adjusted for both age and BMI. After adjustment, the LHCGR rs13405728 polymorphism was associated with PCOS-related anovulatory infertility in the
log-additive model, with an OR of 2.63 and a 95% confidence interval (95% CI) of 1.11-6.27 (P=0.020). In contrast, the minor T allele of the THADA rs7568365 polymorphism exhibited a protective effect in the log-additive
model, with an OR of 0.28 (95% CI: 0.08–0.90; P=0.020),
suggesting that each additional copy of the minor T allele
was associated with a 72% reduction in the odds of developing PCOS with anovulatory infertility.
Clinical and endocrine characteristics of cases and controls
PCOS; Polycystic ovary syndrome, BMI; Body mass index, FSH; Follicle-stimulating hormone, LH; Luteinising hormone, D21 Prog; Day 21 progesterone, TSH; Thyroid-stimulating
hormone, FT4; Free thyroxine, FBS; Fasting blood sugar, HDL; High-density lipoprotein, LDL; Low-density lipoprotein, US; Ultrasound, *; Significance at P<0.05, a; Mann-Whitney test
(non-parametric) data with non-normal distribution are presented by median (Q1-Q3), b; Student’s t test (parametric test) data with normal distribution are presented by mean ± standard
deviation (SD), and c; Pearson chi-square and Fisher’s exact tests were used to measure the significant differences in categorical data.
Genotype and allele distribution in cases and controls
OR; Odds ratio, 95% CI; 95% confidence interval, PCOS; Polycystic ovary syndrome, H-W test; Hardy-Weinberg test, a; One genotype from the rs2479106 control samples was excluded
from the analysis due to a lack of validation, and *; Significant results were shown in bold (P<0.05).
Association of SNPs with the risk of development of PCOS-anovulatory infertility under multiple inheritance models
PCOS; Polycystic ovary syndrome, SNP; Single nucleotide polymorphisms, OR; Odds ratio, 95% CI; 95% confidence interval, AIC; Akaike information criteria, *; Significant results are
shown in bold (P<0.05), and a; Adjusted for age and body mass index (BMI) from 31 genotypes of infertile-PCOS cases and 31 genotypes from the controls.
The SNPs in the DENND1A gene (rs2479106 and
rs10986105) showed almost complete linkage disequilibrium, with a D′ of 0.94 ( Table S3 , See Supplementary Online Information at www.ijfs.ir ). However, the low correlation coefficient (r²) is attributed to the rare minor allele
frequency of rs10986105 in our screened samples. Haplotype frequencies were also measured in the infertile
-PCOS and control groups ( Table S4 , See Supplementary
Online Information at www.ijfs.ir ). Linkage disequilibrium and haplotype analyses were further conducted for
the THADA rs13429458 polymorphism and its two neighbouring SNPs, rs7568365 and rs1317772225
( Tables S5,
S6 , See Supplementary Online Information at www.ijfs.ir ).
The A-T haplotype was more frequent in controls than in
the infertile-PCOS group (OR=0.13, 95% CI: 0.05-0.35;
P=0.001), indicating a protective effect that reduces the
risk of PCOS-related anovulatory infertility by 87%. The
relationships among rs13405728 (2p16.3), rs6166 (2p21),
and rs13429458 (2p21), all located on the short arm of
chromosome 2, were assessed ( Table S7 , See Supplementary Online Information at www.ijfs.ir ). The ATA haplotype was more frequent in controls than in infertile-PCOS
cases, decreasing the risk of PCOS-related anovulatory infertility by 81% (OR=0.19, 95% CI: 0.06-0.57; P=0.003).
Similarly, the ACA haplotype showed a protective effect,
reducing the risk by 70% (OR=0.30, 95% CI: 0.09-0.95;
P=0.044) ( Table S8 , See Supplementary Online Information at www.ijfs.ir ).
A significant difference in triglyceride levels among
rs2479106 genotypes was observed in the infertile-PCOS
group (P=0.013, Table S9 , See Supplementary Online
Information at www.ijfs.ir ). Similarly, triglyceride levels differed among rs13405728 genotypes in the control
group (P=0.037, Table S10 , See Supplementary Online
Information at www.ijfs.ir ). Diastolic blood pressure was
higher in cases with the AA genotype of rs13429458 compared to those with the AC
genotype (P=0.001, Table S11 ,
See Supplementary Online Information at www.ijfs.ir ).
There were no statistically significant differences in the
clinical and endocrine parameters among the genotypes
of rs10986105, rs6166, and rs743572 ( Tables S12, S13 ,
and S14 , See Supplementary Online Information at www.
ijfs.ir ).
Discussion
The wide, complex clinical spectrum in PCOS indicates
the heterogeneous pathogenesis of this disease and the involvement of multiple genes. A combination of genetic
interactions and environmental factors is believed to play
a crucial role in its predisposition ( 14 ).
PCOS is a major cause of anovulatory infertility ( 15 )
and is estimated to account for approximately 40% of
female infertility ( 16 ). The condition was first characterised in 1972 with the observation of infertile women presenting with small, shiny ovaries ( 17 ). In our replication
study, we aimed to investigate the association of selected
PCOS-susceptible loci in Malay women who phenotypically presented with anovulatory infertility. Our intent
was to identify which polymorphisms play a crucial role
in the development of infertility related to this condition. The DENND1A gene (also known as connecedin1)
produces two main transcripts through alternative splicing: DENND1A variant 1 and DENND1A variant 2 ( 18 ).
A study utilising theca cells obtained from women with
normal menstrual cycles and those with PCOS provided
initial evidence of a functional connection between elevated DENND1A.V2 and CYP17A1 expression, leading to
increased androgen production in PCOS theca cells ( 19 ).
We investigated the association between the two most
screened polymorphisms, rs2479106 and rs10986105,
and found no association between these polymorphisms
and PCOS-anovulatory infertility. Similarly, a study on
Arab women from Bahrain found no association between
the two polymorphisms ( 20 ). Another study on North
African Arabs from Tunisia reported an association with
rs10986105, but no association with rs2479106 ( 9 ). The
frequency of the rs10986105 minor allele is 0.018 in East
Asians; in our study, it was 0.01, as reported by the National Centre for Biotechnology Information, and it is
0.055 in Europeans. This suggests the need for a large
sample size to find an association in Asians. Nonetheless, we did not observe any association for rs2479106,
which might be attributed to the small sample size. The
DENND1A gene may contribute to the development of
PCOS through pathways related to metabolic disorders
and insulin resistance, as suggested by Tian et al. ( 21 ). We
observed a significant difference in infertile-PCOS cases
with the homozygous mutant GG genotype of rs2479106,
which had notably elevated triglyceride levels compared
to the other genotypes. Elevated triglyceride levels are a
key component of metabolic syndrome. Obesity, on the
other hand, is an essential element in metabolic syndrome
and dyslipidaemia through multiple pathways ( 22 ). Notably, patients with the GG genotype were obese with a
mean BMI of 34.8 ± 7.5, which could solely lead to the
high triglyceride levels observed in this genotype.
LHCGR is primarily expressed in the granulosa cells of
preovulatory follicles and constitutively expressed in theca
cells of the ovaries. In the later stages of follicular development, it triggers ovulation in response to the mid-cycle LH
surge ( 23 ). The LH level remained within the normal range
in the infertile-PCOS group, with no biochemical evidence
of hyperandrogenism observed in this group. This finding
supports studies where non-obese women with PCOS exhibit elevated levels of LH secreted by the pituitary gland,
increased LH activity, and abundant production of androgens in the ovaries in response to LH compared to obese
PCOS women ( 24 ). The LHCGR rs13405728 polymorphism was identified as one of the three susceptible loci associated with PCOS in the initial GWAS investigation conducted in the Han Chinese population ( 7 ). Another study on
Indian ethnicity reported an association with PCOS ( 25 ).
Similarly, our study found that the rs13405728 polymorphism was strongly associated with PCOS cases that presented with anovulatory infertility, with an OR of 2.63 (95%
CI: 1.11-6.27; P=0.020) after adjustments for age and BMI.
In contrast to our findings, there was no observed association between the LHCGR rs13405728 polymorphism
and Caucasian populations ( 26 ). The infertile-PCOS group
had higher BMI, with a median of 29.7 kg/m² (IQR: 25.4-38.2), compared to the control group median of 24.5 kg/m²
(IQR: 20-29.4). This difference was statistically significant
(P<0.002). It is well-documented that women with PCOS
frequently have an elevated BMI compared to those without PCOS. This observation highlights a consistent correlation between PCOS and increased BMI ( 27 ). The association between PCOS and obesity is intricate and lacks
a straightforward causative relationship. Both conditions
have the potential to interact and exacerbate each other’s
symptoms, making it challenging to pinpoint whether
PCOS directly leads to obesity or vice versa ( 28 ). Furthermore, obesity exacerbates PCOS symptoms and contributes to anovulation ( 29 ), which was typically seen in our
study. Accordingly, our results indicate that Malay women
have a 2.6-fold increased propensity to develop PCOS,
characterised by anovulatory infertility, with each copy of
the minor allele G of the LHCGR rs13405728 polymorphism. This finding further supports the conclusions of the
initial genotype-phenotype study identified by GWAS in
a large cohort of Han Chinese women, which suggested
that the LHCGR rs13405728 polymorphism may contribute to anovulation in PCOS ( 30 ). Mutations that inactivate
LHCGR are linked to irregular menstruation and infertility
in women ( 23 ). Our study is the first to highlight an association between the LHCGR rs13405728 polymorphism and
PCOS-related infertility; however, the precise mechanism
by which this polymorphism influences LHCGR function
remains undetermined. This finding may pave the way
for early screening of PCOS in Malay women, as well as
for predicting the development of infertility. Despite the
limitation of our small sample size, we observed a notably higher minor allele frequency of 0.71 in the infertile
-PCOS group compared to 0.45 in the control group. Our
findings demonstrated a statistical power of 74%, suggesting a reasonable confidence level in the results.
FSHR is regulated by FSH and plays a crucial role in
promoting granulosa cell proliferation, differentiation,
and the development of antral follicles ( 31 ). Two missense polymorphisms in the FSHR gene, Ala307Thr
(rs6165) and Ser680Asn (rs6166), have been extensively
studied and characterised ( 32 ). Given that PCOS is characterised by follicular growth failure, numerous studies have thoroughly examined the relationship between
FSHR Thr307Ala or Asn680Ser coding sequence changes and PCOS, with varying and disputed findings ( 33 ).
Our research shows no apparent link between the FSHR
rs6166 missense polymorphism (Asn680Ser) and PCOS.
This conclusion is in line with a study that examined Han
Chinese women in northern China and found no association with the rs6166 polymorphism ( 34 ). Another study
conducted on European individuals also failed to find an
association with this polymorphism ( 35 ).
The THADA rs13429458 polymorphism, one of the
first three loci identified as associated with PCOS in the
initial GWAS, was investigated in our study of infertile
anovulatory Malay women with PCOS. We observed no
association between this gene polymorphism and PCOS-
anovulatory infertility, with only two genotypes identified. Similar findings of no association were reported in
various other ethnic groups and populations, including
European-derived cohorts ( 36 ), Iranian ( 37 ), and Colombian women ( 2 ).
Several case-control studies have explored the potential correlation between the CYP17A1 -34T/C polymorphism (rs743572) and PCOS, given the crucial role of
the 17α-hydroxylase/17,20-lyase enzyme in the hyperandrogenism that characterises PCOS ( 38 ). The rs743572
polymorphism, located in the promoter region of the
CYP17A1 gene, regulates gene expression and may promote increased androgen synthesis ( 39 ). Our investigation found no association between the CYP17A1 rs743572
polymorphism and the risk of developing PCOS-related
anovulatory infertility, with only two genotypes detected.
The infertile-PCOS group had normal total testosterone
levels; only two cases presented with hirsutism, which
may explain the lack of an association. Recent research
on the phenotypic classification of infertile Malay women with PCOS found that they predominantly have phenotype D, characterised by oligo-anovulation and polycystic ovarian morphology on ultrasound, but without
hyperandrogenism. These findings are consistent with
our results ( 40 ). A larger sample size is recommended
for future research. Further categorising PCOS cases according to their phenotypes and investigating the association of the polymorphisms with each subgroup would
be advantageous. Additionally, including an assessment
of insulin resistance and determining the prevalence of
metabolic syndrome would allow for more comprehensive comparisons.
Conclusions
This study demonstrates a significant association between
the LHCGR rs13405728 polymorphism and the development of anovulatory infertility in Malay women with PCOS.
Our finding underscores the critical role of the LHCGR
gene in the anovulatory presentation of PCOS. This polymorphism may serve as an early predictive and prognostic
biomarker for the onset of PCOS and subsequent infertility
in Malay adolescent girls and married women affected by
this condition. Early interventions could include lifestyle
modifications, weight reduction, and dietary adjustments.
Conversely, no associations were found between DENND1A rs2479106 and rs10986105, FSHR rs6166, THADA
rs13429458, or CYP17A1 rs743572 polymorphisms and the
development of PCOS-related anovulatory infertility. Interestingly, the minor allele of the THADA rs7568365 polymorphism, which has not been previously reported, appeared to
exert a protective effect against the development of PCOS
-related anovulatory infertility.
Materials Methods
The case control study was designed as an exploratory
(preliminary) investigation rather than a full-scale genetic association study, as it is the first study to screen these
polymorphisms in the Malay population. The effect size
could only be estimated after determining the minor allele
frequencies (MAFs) in this population. Consequently, different effect sizes were obtained for each SNP, resulting
in different required sample sizes for each polymorphism.
A total of 96 participants, 48 cases and 48 controls, were
recruited from Serdang Hospital, Putrajaya Hospital, and
Sultan Abdul Aziz Shah Hospital. Cases and controls were
non-randomly selected and matched by ethnicity and age.
Only Malay, non-lactating women aged 20-40 years were
recruited for this study. Participants completed a questionnaire that described the research objectives and provided
written consent. Written ethical approval and permission
were granted by the Medical Research and Ethics Committee, Ministry of Health Malaysia, and Clinical Research
Centre of Hospital Serdang, Putrajaya and Hospital Sultan Abdul Aziz Shah (NMRR-18-3175-44106). Written
informed consent was obtained from all participants and
included on the first pages of the questionnaire.
The cases were infertile women with PCOS diagnosed
according to the Rotterdam criteria who attended the infertility clinics.
The controls were infertile women with regular menstrual cycles who attended infertility clinics due to male factor infertility, tubal dysfunction, or endometriosis. Those
with PCOS and endocrine disorders, including Cushing’s
syndrome/disease, androgen-secreting tumours, hyperprolactinaemia, congenital adrenal hyperplasia, malignant disease, chronic liver disease, and thyroid disorders
were excluded.
Clinical evaluation was conducted through interviews
and physical examinations. Data about age, menarche,
menstrual irregularities, dysmenorrhoea, menorrhagia,
type and duration of infertility, ovulation induction, miscarriages, smoking, hypercholesterolaemia, and histories
of diabetes and hypertension were obtained from the questionnaire. Each questionnaire was labelled with the participant’s medical record number. During the physical examination, height and weight were measured to calculate
body mass index (BMI) using the formula BMI=weight
(kg)/height (m²), and blood pressure was recorded for
both groups. Information pertaining to PCOS features
was obtained by transvaginal ultrasound, and hirsutism
was obtained from the patients’ medical records.
Routine investigations at the infertility clinics involved
obtaining early morning blood samples after at least eight
hours of overnight fasting during the early follicular
phase. Samples were collected to measure follicle-stimulating hormone (FSH), LH, total testosterone, oestradiol,
prolactin, thyroid-stimulating hormone (TSH), free thyroxine (FT4), total cholesterol, triglycerides, high-density
lipoprotein (HDL), low-density lipoprotein (LDL), and
fasting blood glucose (FBS). Additionally, blood samples
were taken on day 21 of the menstrual cycle to measure
progesterone (D21) and assess ovulation in both groups.
TSH and prolactin were specifically measured to exclude
infertility due to thyroid disorders and hyperprolactinaemia. The results were subsequently retrieved from the patients’ medical records.
Five millilitres of venous blood were collected from each
participant in Royal Blue K2EDTA BD Vacutainer® tubes.
The tubes were transported in an ice bag for DNA extraction on the same day (using fresh blood). Genomic DNA was
extracted from the whole blood of anticoagulated samples
using the QIAamp® DNA Mini Kit (Qiagen, Germany).
Six selected polymorphisms were genotyped, including the intronic variants DENND1A rs2479106 (A/G) and
rs10986105 (T/G) , THADA rs13429458 (A/C) , and LHCGR rs13405728 (A/G) , as well as the FSHR rs6166 (C/T)
missense polymorphism and the CYP17A1 rs743572 (A/G)
polymorphism located in the 5′ UTR. Primer sequences
for these six SNPs were designed using the Primer3 tool
( Table S1 , See Supplementary Online Information at www.
ijfs.ir ). The primers were synthesised by Integrated DNA
Technologies, Singapore. The predicted effects of the selected SNPs were determined using the Variant effect
predictor (VEP) and are presented in Table S2 (See Supplementary Online Information at www.ijfs.ir ) ( 13 ). Two
additional SNPs located within the targeted amplicon of
THADA rs13429458, rs1317772225 (C insertion/deletion)
and rs7568365 (T/C) were also included. High-resolution
melting (HRM) analysis was utilised for genotyping, with
amplification performed on the LightCycler® 480 System.
HRM analysis was validated by sequencing 10% of the
amplified products, which showed 100% concordance with
the HRM assays the HRM assays ( 13 ).
Categorical variables are presented as percentages and
analysed using the chi-square test. Biochemical data and
genotype comparisons were analysed using the student’s
t-test and one-way ANOVA for normally distributed data
and are presented as mean ± standard deviation (SD).
Non-parametric tests, such as the Mann-Whitney U and
Kruskal-Wallis tests, were applied for non-normally distributed data and presented as median (Q1-Q3). SNP
genotypes were analysed using SNPStats software with
univariate logistic regression. SPSS software (IBM Corp.,
Armonk, NY, USA, version 27) was used to evaluate the
phenotypic effects of genotypes on clinical and biochemical parameters. The chi-square test in SPSS was used to
determine whether there were significant differences in
genotype and allele frequencies between the cases and
controls. Additionally, linkage disequilibrium analysis
of SNPs on the same chromosome was performed using
SNPStats (multivariate logistic regression), generating D′
and r² values, as well as haplotype frequencies and their
associations with PCOS-related anovulatory infertility.
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