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Cite this article: Deepika MLN, Ranjith K, Jahan P (2016) Association of PPAR-Γ (Rs1801282) and TNF-Α (Rs1799964) Polymorphisms with Body Mass Index in Patients with Polycystic Ovary Syndrome. J Endocrinol Diabetes Obes 4(3): 1090.

*Corresponding authorParveen Jahan, Assistant Professor, Dept. of Genetics, Osmania University, Hyderabad-500 007, Telangana, India, Tel: 91-040- 27682335; Fax: 91-040- 27095178; E mail:

Submitted: 25 July 2016

Accepted: 13 September 2016

Published: 17 September 2016

ISSN: 2333-6692

Copyright© 2016 Jahan et al.

OPEN ACCESS

Keywords•Cytokine•Genotype combination•Inflammation•PCOS•Polymorphism•TNF-α•PPAR-γ•Obesity

Research Article

Association of PPAR-g (Rs1801282) and TNF-a (Rs1799964) Polymorphisms with Body Mass Index in Patients with Polycystic Ovary SyndromeDeepika MLN, Ranjith K, and Jahan P*Department of Genetics, Osmania University, India

Abstract

Background: The etiology of PCOS suggests the involvement of obesity and inflammatory genes. The present study was aimed to investigate the role of TNF-a and PPAR-g genes in the causation of PCOS.

Method: A total of 281 patients and 299 controls were enrolled, DNA was isolated and genotyping was performed by PCR-RFLP.

Results: The genotype frequencies differed between the groups. The CG and TC hetrozygotes revealed an OR 3.5 and 1.8 respectively. Genotype analysis in obese and non-obese groups revealed the association of both SNP’s with lean and PPAR-g with obese PCOS suggesting the antagonistic role of TNF-a on PPAR-g. Haplotype analysis demonstrated that woman heterozygous for both SNP’s is having two fold risk towards PCOS.

Conclusion: The over-expression of PPAR-g in the absence/lower levels of TNF-a increases PCOS risk. However, extensive studies are warranted to identify the potentiality of these polymorphisms towards PCOS in different ethnic groups.

INTRODUCTIONObesity is emerging as a major public health problem in India

and the prevalence had almost doubled in the last 20 years. It is associated with multiple factors and strong genetic component as well [1]. Weight gain leading to obesity is often linked with several diseases such as insulin resistance, metabolic syndrome, diabetes, and thyroid and also with a common endocrine disorder, Polycystic Ovary Syndrome (PCOS). It affects 4-12% women of reproductive age worldwide and is a leading cause for female infertility. This syndrome is characterized by chronic an ovulation, clinical signs or symptoms of hyperandrogenism and polycystic ovaries on ultrasound scan. Inter-individual variation is commonly observed with respect to clinical features changing throughout the life span starting from adolescence to postmenopausal age. It predisposes the individual to serious long term consequences such as type 2 diabetes, endometrial hyperplasia, thyroid dysfunction, cardiovascular diseases and thus contributes significantly to disease burden [2]. The cause of

PCOS is not known however genetic, biochemical, immunological and environmental factors are implicated in the aetiopathogeneis of this multifactorial condition [3]. Till date, a number of candidate genes have been proposed as important contributors to PCOS although none have yet achieved acceptance as major cause [4].

Peroxisome proliferator activated receptor- gamma (PPAR-γ) is a candidate gene for obesity and regulates adipose tissue metabolism in humans [5]. It is a member of the nuclear hormone receptor super family that transcriptionally regulates the genes controlling a variety of biological functions including cell growth, differentiation and metabolism in response to hormones. Genetic variants of this gene reduce the transcriptional activity of PPAR-γ and were found to be associated with increased BMI and attenuated insulin resistance [6]. It also regulates the expression of genes involved in adipose tissue differentiation, lipid and glucose metabolism, insulin sensitization, adipokine production and also the inflammatory gene; Tumor Necrosis Factor Alpha (TNF-α) required for follicular development, ovulation and

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oocyte maturation [7-9].

TNF-α is proinflammatory cytokine expressed in adipocytes and elicits inflammatory responses as a normal physiological function for ovulation [10]. It is present in follicular fluid of human ovary, granulosa cells and oocytes and the elevated levels of this cytokine have been linked to obesity and insulin resistance influence anovulation and hyperandrogenism. The TNF- α -1031 T > C polymorphism have been linked with altered promoter activity leading to varied TNF-α plasma levels in healthy individuals [11]. The present study was aimed to establish the role of PPAR-γ exon 2 C > G and TNF-α -1031 T > C polymorphisms in the aetiopathogenesis of PCOS.

MATERIALS AND METHODOLOGY

Study population

In the present study a total of 580 women comprising of 281 patients and 299 controls were enrolled and recruited from Modern Government Maternity Hospital, Hyderabad, India. Patients were selected based on Rotterdam criteria [12] according to which a woman is said to have PCOS, if she has any two features out of three such as polycystic ovaries on ultrasound scan, menstrual irregularities and/or clinical signs or symptoms of hyperandrogenism such as acne, alopecia, hirsutism and premature pubarche. Ultrasound scanned normal fertile women with no menstrual dysfunction or history of infertility was selected as controls. Written approval was obtained from the institutional ethics committee and informed consent from all subjects before peripheral blood samples were collected. Detailed information on clinical, anthropometric measures, family history of complex diseases (FHCD) such as menstrual disturbances, PCOS, diabetes and cardiovascular diseases and diet was recorded through proforma.

Molecular analysis

DNA was extracted from peripheral blood and for each subject. PCR for PPAR-γ exon-2 C > G (rs1801282) and TNF-α -1031 T > C (rs1799964) was performed using appropriate primers and the products obtained were digested with BstU I and Bbs I (Fermentas, India) respectively for 12 hrs at 37°C and then genotyped using 3% agarose gels (Figure 1).

Statistical analysis

All the statistical analysis was performed using SPSS statistical software (version 20.0, IBM SPSS). Continuous data was expressed as mean ± SD. The demographic characteristics of patients and controls were compared by the Student’s t-test for unpaired data. The association between genotypes and PCOS risk was evaluated by calculating chi-square and odds ratios (OR) at 95 % confidence interval respectively. Allele and genotype frequencies were determined from observed genotype counts. Multiple Logistic Regression (MLR) analysis was performed for both the SNPs along with anthropometric and clinical measures with respect to disease susceptibility. Haplotype analysis was performed using SNP stat online tool (http://bioinfo.iconcologia.net/SNPstats). Hardy Weinberg equilibrium was estimated by the χ2 test. A two tailed p-value < 0.05 was considered to be statistically significant.

RESULTSCharacteristics of the study group

Data analysis on a total cohort of 580 individuals revealed that the mean age of the patients and controls at the time of sample collection was 24.25 ± 4.39 and 24.89 ± 4.81 years respectively. The mean age at onset (AAO) of the clinical symptoms in the patients was 16.23 ± 4.79 years. A significant difference with respect to BMI and WHR was observed between the groups (p < 0.05). The characteristics of PCOS and controls are presented in Table (1).

Molecular analysis

Distribution of genotypes and allele frequencies in patients and controls: The distribution of PPAR-γ exon-2 and TNF-α -1031 genotypes in patients and controls and the risk contributed by the genotype and allele in patients compared to controls is given in Table (2).

• PPAR-γ exon-2 C > G polymorphism (rs1801282): The frequencies CC, CG and GG genotypes of PPAR-γ exon-2 were 82%, 17% and 1% in patients, while they were 94%, 6% and 0% in controls. An increased frequency of CC genotype in controls and CG in patients was observed and demonstrated an OR of 0.27 and 3.50 respectively. The distribution of genotypes differed significantly between the groups (p < 0.05) while the allelic frequency did not vary (p > 0.05). Mendelian effect modeling revealed an association of CG genotype with PCOS, which was compatible with dominant and over-dominant effect assumptions (CG + GG vs. CC: OR = 3.59, CI = 2.02-6.39, p < 0.0001 and CG vs. CC + CG: OR = 3.50, CI = 1.96-6.25, p < 0.0001).

• TNF-α -1031 T>C polymorphism (rs1799964): The percentage distribution of TT, TC and CC genotypes of rs1799964 were 38, 60 and 2 in patients, while 53, 45 and 2 in controls correspondingly. Individuals with TT genotype predominated in controls and revealed an OR of 0.54 whereas the TC genotype was extremely elevated in patients and showed an OR value of 1.81. The distribution of genotypes varied significantly between the groups (p < 0.05).The frequency of T allele was higher in controls however did not differ between the groups (p > 0.05). Mendelian effect modeling revealed an association of TC genotype with PCOS, which was compatible with dominant and over-dominant effect assumptions (TC + CC vs. TT: OR = 2.52, CI = 1.84-3.54, p < 0.0001 and TC vs. TT + CC: OR = 2.58, CI = 1.84-3.62, p < 0.0001).

Table1: Subject characteristics of the study group.

Variables Total ControlsN=299

Total PatientsN=281 p-value

BMI(kg/m2) 22.02 ± 3.29 25.87 ± 5.02 0.0001

WHR 0.74 ± 0.04 0.79 ± 0.05 0.0001

AAM 12.21 ± 0.88 12.42 ± 1.29 NS

AAO - 16.23 ± 4.79 -BMI - Body Mass Index, WHR - Waist to hip ratioNote: Quantitative data are presented X ± SD, NS represents not significant at 5% level of significanc

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Table2: Genotype and allelic frequency distribution of PPAR-γ and TNF-α polymorphisms among patients and controls.

Exon-2 CCN(%)

CGN(%)

GGN(%) C G Comparison

of groups OR(95%CI) p-value

Controls (299) 282(94) 17(6) 0(0) 0.97 0.03 CC vs. CG + GG 0.27(0.15 – 0.49) <0.001

Patients (281) 231(82) 49(17) 1(1) 0.91 0.09 CG vs. CC + GG 3.50(1.96 – 6.24) <0.001

χ2=18.83; p=0.00008 χ2=2.22;p=0.13 GG vs. CC + CG - -

HWEPatients χ2= 0.90; p = > 0.05 C vs. G 0.31(0.08 – 1.19) 0.13

Controls χ2= 149.10; p = < 0.05 G vs. C 3.19(0.83 – 12.18) 0.13

-1031 TTN(%)

TCN(%)

CCN(%) T C Comparison

of groups OR(95%CI) p-value

Controls (299) 159(53) 135(45) 5(2) 0.76 0.24 TT vs. TC+CC 0.42(0.30 – 0. 58) <0.01

Patients (281) 106(38) 169(60) 6(2) 0.68 0.32 TC vs. TT+CC 1.57 (1.14 – 2.18) <0.01

χ2=13.17; p=0.001 χ2=1.21;p=0.27 CC vs. TT+TC 1.28 (0.38 – 4.25) 0.76

HWEPatients χ2 = 40.17; p = < 0.05 T vs. C 0.67 (0.36 – 1.25) 0.27

Controls χ2 = 16.62; p = < 0.05 C vs. T 1.49 (0.79 – 2.77) 0.27

OR – Odds Ratio, CI – Confidence Interval, HWE – Hardy Weinberg Equilibrium

Multiplelinearregression(MLR)analysisintotalpatientsand controls: Multiple linear regression analysis was performed to access the association of PCOS (dependent variable) while BMI, WHR, FHCD, non-vegetarian diet, PPAR-γ and TNF-α genotypes regarded as co-variables. For each variable in the equation, coefficient (B), standard error of B, Wald statistic, estimated OR (expB) and CI (95%) were calculated. Interestingly, all the variables except diet were found to be highly associated with PCOS. The anthropometric measures BMI and WHR showed an OR of 3.62 and 2.29 respectively. In addition, women with FHCD showed nearly 15 folds risk for PCOS. Other than this, the PPAR-γ and TNF-α SNP’s were identified as important contributors of PCOS and showed an OR of 3.45 and 1.61 respectively (p < 0.05) (Table 3).

Distribution of genotypes and allele frequencies in lean and obese patients and controls: Obesity is often considered as an important clinical feature associated with PCOS and nearly 50% of our cases are overweight or obese with BMI ≥ 23 kg/m2. In this regard, the case cohort was categorized into groups based on BMI i.e. lean PCOS (BMI < 23 kg/m2) and obese PCOS (BMI ≥ 23 kg/m2) groups. The distribution of genotypes and alleles were analyzed in these groups and comparisons were carried out between BMI matched patients and controls [11]. Analysis yielded a significant involvement both SNP’s with lean PCOS whereas only PPAR-γ exon 2 C > G polymorphism was allied with obese PCOS. Lean PCOS women with CG and TC genotypes (heterozygous for both SNP’s) exhibited an OR of 2.23 and 2.64 respectively while obese PCOS with CG genotype of PPAR-γ showed an extremely elevated risk of 9.5 fold against genetic predisposition of PCOS (Table 4).

MLR analysis in lean and obese groups: MLR analysis in lean and obese groups demonstrated significant contribution of FHCD in the causation of PCOS. Furthermore, in lean PCOS TNF-α -1031 T > C and in obese PCOS PPAR-γ exon 2 C > G accounted for PCOS susceptibility (Table 3).

Haplotype analysis: The selected SNP’s showed linkage disequilibrium with a D′ value of 0.62. Analysis of haplotypes and

diplotypes of studied SNP’s for possible association with PCOS revealed four haplotypes and the one carrying recessive alleles at both loci predominant in patients (p = 0.000). Additionally, the haplotype with C allele of TNF-α alone was also higher in patients and showed an OR of 1.67 (p = 0.003). The haplotypes differed significantly between the groups (p < 0.0001). Further, we explored the association between diplotypes and PCOS risk. The 9 diplotypes obtained (TT – CC, TT – CG, TT – GG, TC – CC, TC – CG, TC – GG, CC – CC, CC – CG, CC – GG) were then categorized into three groups. One carrying homozygous wild type allele of TNF-α (TT) and PPAR-γ (CC) at both loci (TT – CC) designated as Homozygous wild, were extremely elevated in the controls and showed an OR 55.64; p < 0.0001). Another diplotype carrying recessive alleles at either loci, heterozygous condition (T_ – C_) predominated in patients and revealed an OR value of 2.18(1.55 –3.06) (Table 5).

DISCUSSIONPCOS is a common endocrine disorder associated with an

ovulation, hyperandrogenism, obesity and insulin resistance with incompletely understood etiology. However, it is widely accepted that inflammation and insulin resistance are the key components in the pathogenesis of this disorder [10,11]. In this regard, the present study was aimed to evaluate the influence of PPAR-γ exon 2 C > G and TNF-α -1031 T > C polymorphisms in the causation of PCOS.

A significant difference in the distribution of PPAR-γ exon-2 C > G polymorphism was indicating the contribution of this SNP in PCOS susceptibility in the studied group. Increased frequency of women with CC genotype in controls and CG heterozygotes in patients were suggestive of the protective and predisposing role of these genotypes respectively towards PCOS. Our observations were in agreement with previous findings in Finnish [13], Korean [14], Turkish [15] and Iranian [16] women. Two recent studies in India by Sheik (2016) and Jacob (2015) demonstrated a strong association of this polymorphism with PCOS, however Dasgupta et al., (2012) reported a borderline significance (p = 0.05) with disease susceptibility [17-19]. Other findings on PCOS women

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Table3: Multiple linear analysis with PCOS susceptibility as dependent variable in PCOS patients.

VariablesTotal Lean ObeseOR(95%CI) p-value OR(95%CI) p-value OR(95%CI) p-value

BMI 3.6(2.08-6.30) 0.00 - - - -

WHR 2.29(1.23-4.26) 0.009 2.22(0.86-5.77) 0.09 2.19(0.96-4.99) 0.06

FHCD 14.84(9.36-23.53) 0.00 18.87(10.81-32.94) 0.00 10.34(4.47-23.91) 0.00

Diet 0.91(0.43-1.93) 0.813 1.21(0.49-2.94) 0.67 0.44(0.08-2.52) 0.36

TNF 1.61(1.05-2.47) 0.04 2.06(1.23-3.46) 0.006 1.01(0.46-2.20) 0.97

PPAR 3.45(1.68-7.08) 0.001 2.17(0.89-5.29) 0.087 16.05(1.98-130.02) 0.009

OR – Odds Ratio, CI – Confidence Interval

Table4: Genotype distribution of TNF- α -1031 and PPAR-γ exon-2 according to BMI.

Gene/polymorphismLean χ2

(p-value) Comparisons ofgroups OR(95%CI) p-value

Patients(128) Controls(259)

-1031TT 44(34%) 141 (54%) 12.94

(0.0015)TT vs. TC+CC 0.43(0.28-0.68) < 0.01

TC 82 (64%) 115 (44%) TC vs. TT+CC 2.23(1.44-3.45) < 0.01CC 2 (2%) 3 (2%) CC vs. TT+TC 1.35(0.22-8.21) 1

Exon-2CC 108 (84%) 243 (94%)

7.05(0.02)

CC vs. CG+GG 0.35(0.17-0.71) < 0.01CG 19 (15%) 16 (6%) CG vs. CC+GG 2.64(1.31-5.34) < 0.01GG 1(1%) 0(0%) GG vs. CC+CG -- --

Obesep-value Comparisons of

groups OR(95%CI) p-valuePatients(153) Controls(40)

-1031TT 62 (41%) 19 (47%)

0.64(0.72)

TT vs. TC+CC 0.75(0.37-1.51) 0.47TC 87 (57%) 20 (50%) TC vs. TT+CC 1.31(0.65-2.64) 0.47CC 4 (2%) 1 (3%) CC vs. TT+TC 1.04(0.11-9.63) 1

Exon-2CC 123 (80%) 39 (97%)

5.67(0.01)

CC vs. CG+GG 0.10(0.01-0.79) 0.01CG 30 (20%) 1(3%) CG vs. CC+GG 9.5(1.25-72.04) 0.01GG 0 (0%) 0(0%) GG vs. CC+CG -- --

OR – Odds Ratio, CI – Confidence Interval, HWE – Hardy Weinberg Equilibrium

Table5: Haplotype and diplotype frequency distribution between patients and controls.

S.No Haplotypea Patients Controls Diplotype Patients Controls OR(95%CI) p-value

1. T – C 0.650 0.733 Homozygous wild TT – CC 88(31%) 149(50%) 0.46(0.33 – 0.64) <0.01

2. C – C 0.259 0.237 Heterozygous T_ – C_ 193(69%) 150(50%) 2.18(1.55 – 3.06) <0.01

3. C – G 0.087 0.001 Homozygous mutantCC-GG 0 0 - -

4. T – G 0.002 0.027 Total (N) 281 299

OR – Odds Ratio, CI – Confidence Interval

from various ethnic groups like Italian [5,20], German [21], Chinese [22], Caucasian [23], Korean [24], Greek [25,26], Spanish [27] and Polish [28] failed to find so. Additionally, there are reports proposing a role of this inflammatory gene polymorphism with PCOS complications such as obesity, insulin resistance and type 2 diabetes [7,29]. Our study demonstrated a predisposing role of G allele towards PCOS whereas in Chinese population, it showed a protective role indicating ethnic variation [30].

The existence of an association between TNF α -1031 T > C polymorphism and PCOS have shown conflicting results. However there are studies suggesting a link between this SNP and various medical conditions, such as PCOS [10,11], carcinomas [31-33], peptic ulcers [34] and anemia [35]. The

TC heterozygote predominated in patients (60% vs. 45%) and marked a twofold risk for PCOS as reported in our previous paper [11].These findings were in accordance to the findings of others in Asian population [10]. The C allele of -1031 was reported to be protective against PCOS in Korean population whereas in our study, it’s the T allele that appeared to confer protection against PCOS. The predisposing role of C allele in our observation was similar to the findings of Yun et al., (2011), Wu et al., (2015) and Liu et al., (2016) and is often linked to increased transcriptional activity of TNF-α, a hallmark of inflammatory mechanism associated with PCOS [10,36-38].

The involvement of BMI, FHCD and selected SNP’s in MLR analysis suggest the interaction of genes and environment in

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the causation of PCOS. Lean and obese groups also showed a significant association of FHCD and the risk contributed was 18.87 and 10.34 in lean and obese groups respectively. The highly significant values obtained suggest a significant genetic background to develop this multifactorial disorder [4].

Furthermore it was observed that lean women with homozygous wild type for both SNP’s (TT or CC) are at lesser risk compared to heterozygotes (TC or CG) and exhibited around two fold risk for PCOS. Our study differed from the findings by Brand et al., (2001) where -1031 T > C polymorphism was associated with higher BMI [39]. Lack of association of this polymorphism in overweight/obese women group proposes TNF-α to be a marker for inflammation but not for obesity. It was interesting to note further that PPAR-γ exon-2 SNP was strongly associated with obesity and obese women with CG genotype showed an extremely elevated risk of around 10 fold for PCOS. These results could be explained on the basis that the -1031C is associated with increased TNF-α expression [38] that in turn inhibit the transcriptional activity of PPAR-γ [40]. In lean women, presence of mutant allele of TNF-α in single dose produces TNF-α levels that is large enough to reduce the expression of PPAR-γ at the m-RNA level thus enabling normal adipogenesis, energy storage and lipid redistribution. Ilhan et al., (2006) demonstrated that elevated TNF-α level in lean PCOS may contribute to insulin resistance [41]. This suggest that in lean PCOS, obesity gene (PPAR-γ) is not causative factor for PCOS but the increased TNF-α levels disturbing the insulin pathway predisposes these women to develop the disease.

In overweight/obese women the absence of C allele prevent the anti-adipogenic effects of TNF-α, leading to increased adipogenesis and lipid redistribution in these women, making them extremely obese. The major allele (C) of PPAR-γ represents one of the thrifty gene that convert excessive food to body fat for energy storage and thus increasing the risk of obesity. Furthermore, an animal study by Chanda et al., (2003) showed the interaction of TNF-α with other specific genes involved in adipose tissue accumulation (PPAR-γ, GLUT), insulin resistance (PPAR-γ, TNF-α) and ovarian activity (TNF-α) [42].

Haplotype analysis of the selected SNP’s illustrated a significant interaction of PPAR-TNF genes in the causation of PCOS. In addition, the diplotype with wild type genotypes at both loci was protective while the other having mutant alleles in a single dose (heterozygotes) were having around 10 fold risk for PCOS susceptibility. Since there are no studies pertaining to the selected SNP’s of TNF-α and PPAR-γ haplotypes, there was no scope in the present study to precisely compare the haplotypes/diplotypes of other studies.

In conclusion, our findings suggest the direct involvement of PPAR-γ and TNF-α SNPs in genetic predisposition to PCOS in South Indian women. The association of TNF-α and PPAR-γ with lean and PPAR-γ with obese PCOS suggests the antagonistic role of TNF-α on PPAR-γ. The over-expression of PPAR-γ in the absence/lower levels of TNF-α increases PCOS risk. The involvement of FHCD with PCOS women in our study group implies the influence of other genes associated with obesity, diabetes and cardiovascular disease in the causation of PCOS. The limitation of the present study was the inability to measure

TNF-α and PPAR-γ levels for clinical correlation. However, extensive studies in different ethnic groups are warranted to identify the potentiality of these polymorphisms as markers of obesity in PCOS women.

ACKNOWLEDGEMENTWe thank all the subjects for their co-operation in giving

consent for blood sample and clinical information. We further thank the doctors and nursing staff of various endocrine clinics of Hyderabad, (India) for supporting the implementation of the study and assisting with data collection.

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Deepika MLN, Ranjith K, Jahan P (2016) Association of PPAR-Γ (Rs1801282) and TNF-Α (Rs1799964) Polymorphisms with Body Mass Index in Patients with Polycystic Ovary Syndrome. J Endocrinol Diabetes Obes 4(3): 1090.

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