The Association of PPARγ Pro12Ala and C161T Polymorphisms
with Polycystic Ovary Syndrome and Their Influence on Lipid and
The aim of present study was to clarify the role of the peroxisome proliferator-activated receptor (PPAR) γ Pro12Ala and C161T polymorphisms in the pathogenesis of polycystic ovary syndrome (PCOS) and their influence on lipid and lipoprotein profiles of patients.
Materials and Methods
The present cross-sectional study consisted of 50 women with PCOS, who referred to the Kermanshah University of Medical Sciences Clinic between April and October 2015, and 233 unrelated age-matched healthy women from the same region (West Iran). The PPARγ Pro12Ala and PPARγ C161T polymorphisms were gen- otyped using the polymerase chain reaction-restriction fragment length polymorphism method. Fasting blood sugar (FBS), serum triglycerides (TG), cholesterol, low density lipoprotein- cholesterol (LDL-C), high density lipoprotein- cholesterol (HDL-C) and estradiol levels were measured.
The serum level of estradiol was significantly lower in PCOS patients compared to healthy women. The PPARγ Pro12Ala (CG) genotype increased the risk of PCOS 2.96-fold. The frequency of the PPARγ T allele (at C161T) was 21% in patients and 17.2% in controls with no significant difference (P=0.52). In all studied individuals, the PPARγ CG geno- type was associated with significantly higher levels of TG. However, significantly lower levels of total cholesterol and LDL-C were observed in PPARγ TT individuals compared with those with the CC genotype. Within the PCOS group, the PPARγ CG genotype was significantly associated with lower levels of estradiol compared with the CC genotype. Also, the CG genotype was significantly associated with higher levels of TG when compared with the CC genotype.
Our study shows that, unlike PPARγ C161T, PPARγ Pro12Ala is associated with the risk of PCOS. Also, we found that the lipid and lipoprotein profiles significantly vary based on PPARγ Pro12Ala and C161T genotypes.
Polycystic ovary syndrome (PCOS) is one of the most frequent endocrine-related gynecological disorders among women of reproductive age (1). PCOS, a leading cause of female infertility, is characterized by hyperandrogenism, menstrual irregularity, chronic anovulation and multiple small sub-capsular ovarian cystic follicles (2). Around 50 to 70% of patients with PCOS are diagnosed with dyslipidemia (3).
The peroxisome proliferator-activated receptors (PPARs) belong to the nuclear hormone receptors that regulate the transcription of a variety of genes such as those involved in the metabolism of lipids in adipose tissue, liver and skin (4). The isoform PPARγ, which participates in lipid and glucose metabolism, is mainly expressed in adipose tissue (5).
The aim of this study was to assess the association of
Materials and Methods
The present cross-sectional study consisted of 50 women with confirmed PCOS according to the Rotterdam criteria (13), who referred to the Kermanshah University of Medical Sciences Clinic between April and October 2015. The mean age of PCOS women was 23.6 ± 5.3 years (ranging between 14 and 43 years). A total of 233 unrelated age-matched healthy individuals without PCOS were also included in this study with the mean age of 22.2 ± 4.2 years, (ranging between 18 and 33 years, P=0.09). Controls were volunteers from students and staff of Kermanshah University of Medical Sciences without any history of hyperandrogenism reflected by the presence of hirsutism, acne or alopecia and menstrual irregularity.
Two out of three criteria of clinical and/or biochemical signs of PCOS, namely hyperandrogenism (the presence of hirsutism), acne or alopecia and ovarian dysfunction (oligo- and/or anovulation and/or polycystic ovaries detected by ultrasound scans) were sufficient to diagnose PCOS. Exclusion criteria were congenital adrenal hyperplasia, androgen-secreting tumors, and intake of any medication that may affect the endocrinal parameters along with the glucose and lipid profiles for at least 3 months prior to enrolment.
Height and weight were obtained from each individual and the body mass index (BMI) was calculated. All women in this study were from the Kermanshah province in West Iran, belonging to the Kurdish ethnicity.
All individuals agreed to participate in the study and signed a written informed consent before participation. The Ethics Committee of Kermanshah University of Medical Sciences approved the study. The study was in accordance with the principles of the Declaration of Helsinki II.
From each individual, a sample of 10 milliliters of venous blood was collected at 9 am under standard conditions. The sample was divided to two portions of six milliliters; portion one was centrifuged for 10 minutes at 1600 g in the absence of any anticoagulant and the obtained serum was used for biochemical analysis according to the standard protocol. The second portion (4 ml) was treated with EDTA and used for DNA extraction and further genetic analysis.
The levels of fasting blood sugar (FBS), triglycerides (TG), cholesterol, low density lipoprotein-cholesterol (LDL-C) and high density lipoprotein-cholesterol (HDL- C) were measured using the Bionic Diagnostic Kits (Iran) on Mindray BS-480 Chemistry Analyzer (China). Serum estradiol level in the mid-follicular phase of the menstrual cycle and SHBG were measured using the chemiluminescent method by using the Abbott Architect i1000 (Abbott Laboratory, USA).
DNA was extracted from venous blood using the standard
phenol-chloroform method (14). The polymerase
chain reaction (PCR)-restriction fragment length polymorphism
(RFLP) was used to genotype the
R: 5'-GATATGTTTGCAGACAGTGTATCAGTGAAGGAATCGCTTTCCG- 3' primers.
The PCR reaction in a final volume of 25 µl contained
20 pmol of each primer, 100-200 ng DNA, 200 µM dNTPs,
1.5 mM MgCl2, 1 U Taq polymerase and 2.5 µl of
10X PCR buffer (SinaClon, Iran). The PCR conditions
were an initial denaturation at 94°C for 5 minutes followed
by 30 cycles of 94°C for 60 seconds, 55°C for 60
seconds and 72°C for 60 seconds, with a final extension
for 5 minutes at 72°C. Five microliters of the resulting
270 bp PCR product was examined using electrophoresis
on a 1% agarose gel containing the Gel Red (Kawsar
Biotech Company, Iran) stain and was visualized under a
UV Gel Documentation System (Quantum ST4). Fifteen
microliters of the PCR product was treated with 5 U of
the restriction enzyme BstU I at 37°C overnight and the
RFLP products were electrophoresed on a 2% agarose gel
(7). The C allele (ancestral) was not digested by the
The PPARγ C161T SNP was detected by PCR-RFLP using specific
F: 5'-CAA GAC AAC CTG CTA CAA GC-3'
R: 5' -TCC TTG TAG ATC TCC TGC AG -3' primers.
The PCR reaction consisted of 20 pmol of each primer, 100-200 ng DNA, 200 µM dNTPs, 1.5 mM MgCl2, 1 U Taq polymerase and 2.5 µl of 10X PCR buffer in a final volume of 25 µl. The PCR thermal cycling conditions were an initial denaturation at 94°C for 5 minutes, followed by 35 cycles by 94°C for 60 seconds, 55°C for 60 seconds and 72°C for 60 seconds, with a final extension for 5 minutes at 72°C. Five microliters of the resulting 200 bp PCR product was examined using electrophoresis on a 1% agarose gel containing Gel Red stain and visualized under a UV Gel Documentation System (Quantum ST4). Fifteen microliters of the PCR product were treated with 5 U of the restriction enzyme Pml1 at 37°C overnight and the RFLP products were electrophoresed on a 2% agarose gel (10). The ancestral allele fragment was digested into two fragments of 120 bp and 80 bp, while the derived allele remained intact (Fig .2,).
The frequency of alleles was calculated by the chromosome counting method and deviation from the Hardy-Weinberg equilibrium (HWE) was calculated using the Chi-square test. Comparison of genotype and allele frequencies of the two SNPs between PCOS patients and controls was undertaken using the Chi-square test. The SPSS logistic regression was used to calculate odds ratio (OR) as an estimate of relative risk for the disease and its 95% confidence interval (CI). The association between biochemical data and SNPs was calculated using the independent-sample t test and ANOVA. The P<0.05 was considered as statistically significant. The statistical package for social sciences (SPSS, SPSS Inc., Chicago, IL) version 16.0 was used for the statistical analysis.
Demographic and biochemical characteristics of the participants are presented in Table 1. Patients were age- matched with controls (P=0.09). Also, the two groups were BMI-matched (P=0.25, Table 1,). A significantly lower serum level of estradiol was observed in PCOS women compared with controls (70 ± 45.5 vs. 109.7 ± 91.2 pg/ml respectively, P<0.001). However, a lower level of SHBG was observed in patients (52.2 ± 24.5) compared with controls (58.6 ± 33.9) but was not statistically significant (Table 1,).
|Variable||Patient n=50 Mean ± SD||Control n=233 Mean ± SD||P value|
|Age (Y)||23.6 ± 5.3||22.2 ± 4.2||0.09|
|BMI (Kg/m2)||23.7 ± 4.9||22.8 ± 5.8||0.25|
|FBS (mg/dl)||78.6 ± 13.2||78.5 ± 14.8||0.97|
|Cholesterol (mg/dl)||131.1 ± 32.8||129.7 ± 30.6||0.78|
|TG (mg/dl)||78.8 ± 43.2||88 ± 51.5||0.25|
|HDL-C (mg/dl)||45.6 ± 11.7||46.5 ± 12.8||0.61|
|LDL-C (mg/dl)||74 ± 26.6||74.8 ± 24.5||0.82|
|Estradiol (pg/ml)||70 ± 45.5||109.7 ± 91.2||<0.001|
|SHBG (nmol/l)||52.2 ± 24.5||58.6 ± 33.9||0.13|
PCOS; Polycystic ovary syndrome, BMI; Body mass index, FBS; Fasting blood sugar, TG; Triglycerides, HDL-C; High density lipoprotein-cholesterol, LDL-C; Low density lipoprotein-cholesterol, and SHBG; Sex hormone binding globulin.
The genotypic distribution of
The genotype and allele frequencies of both SNPs are given in Tables 2,, 3,. The frequency of the CG genotype in patients was 32% and significantly higher than that in controls (13.7%, P=0.002, OR=2.96 (95% CI of 1.46-5.96) (Table 2,). Given that the control group deviated from Hardy-Weinberg equilibrium for the C161T SNP, no further analysis was undertaken on the potential association of this SNP with PCOS.
|Parameter||Patient n=50 (%)||Control n=233 (%)|
|χ2=9.75, P=0.002, OR=2.96 , (95% CI: 1.46-5.96, P=0.002)|
|χ2=9.75, P=0.002, OR=2.96 (95% CI: 1.46-5.96, P=0.002)|
OR; Odds ratio and CI; Confidence interval.
The effect of both polymorphisms on lipid and lipoprotein
profiles along with estradiol and SHBG levels in all
studied individuals is shown in Table 4. A significantly
higher level of TG was detected in the presence of the
|Parameter||Patient n=50(%)||Control n=233(%)|
|CC||31 (62)||155 (66.5)|
|CT||17 (34)||76 (32.6)|
|TT||2 (4)||2 (0.9)|
|C||79 (79)||386 (82.8)|
|T||21 (21)||80 (17.2)|
When each group was studied separately, the association of
We identified an association between the PPARγ Pro12Ala CG genotype and the risk of PCOS in our population. We did not detect the GG genotype among our studied individuals because the homozygote Ala genotype is rare in the overall population (7).
There are inconsistent reports on the association of
In a study from Germany, the frequency of the
|CC (n=235)||CG (n=48)||CC (n=186)||CT (n=93)||TT (n=4)|
|FBS (mg/dl)||78.7 ± 15||77.3 ± 11.6||79.4 ± 15.8||77.3 ± 11.3||63.3 ± 9.1|
|Cholesterol (mg/dl)||129.0 ± 30.5||134.1 ± 32.9||130.6 ± 30.6||130.6 ± 30.7||85.5 ± 24.4|
|TG (mg/dl)||76.0 ± 40||101.1 ± 59.4||81.7 ± 46.4||79.8 ± 42.1||40.3 ± 18.4|
|HDL-C (mg/dl)||46.8 ± 13||44.3 ± 10.6||46.9 ± 13.1||45.7 ± 11.7||36.0 ± 10.4|
|LDL-C (mg/dl)||74.3 ± 24.4||76.1 ± 26.9||75.4 ± 24.5||74.5 ± 25.1||42.5 ± 12.8|
|Estradiol (pg/ml)||103.8 ± 86.6||96.8 ± 84.1||102.3 ± 86.5||103.6 ± 87||91.6 ± 57.2|
|SHBG (nmol/l)||58.3 ± 33.8||53.2 ± 24.6||58.3 ± 34.2||55.2 ± 28.9||72.9 ± 32.1|
Data are presented as mean ± SD.*; Compared with the CC genotype, **; Compared with the CT genotype, FBS; Fasting blood sugar, TG; Triglycerides, HDL-C; High density lipoprotein-cholesterol, LDL-C; Low density lipoprotein-cholesterol, and SHBG; Sex hormone binding globulin
The PPARγ is a critical transcription factor involved in
regulating glucose and lipid metabolism (16). The PPARγ
is involved in energy regulation and fat deposition, and is
recognized as an important gene contributing to obesity,
obesity induced insulin resistance and dyslipidemia (8).
The natural ligands of PPARs are unsaturated fatty acids,
eicosanoids, oxidized LDL and VLDL, and linoleic acid
derivatives. Fibrates and thiazolidinediones are pharmacological
agonists of PPARs (17). Although we showed
significant associations between the
Our study showed an association between
We thank the Vice Chancellor Office for Research of Kermanshah University of Medical Sciences, Kermanshah, Iran for financially supporting the present study. There authors declare no conflict of interest.
Z.R.; Designed the study, interpreted the results and critically revised the manuscript. F.C.-N., S.S., Z.R., A.E.; Provided the samples and analyzed the data. E.S.; Wrote the preliminary draft of manuscript. A.V.-R.; Performed the statistical analysis. All authors read and approved the final manuscript.