Zoology Byprr.hec.gov.pk/jspui/bitstream/123456789/6809/1... · the subject of Zoology, hereby...

1

GENETIC AND ENDOCRINOLOGICAL STUDIES

OF FEMALE REPRODUCTIVE DYSFUNCTION

DOCTOR OF PHILOSOPHY

In

Zoology

By

IRFANA LIAQAT Roll No: 0024-PHD-GCU-Z-09

Session 2009-2012

Department of Zoology

GC University, Lahore

2

This work is submitted as a dissertation in partial fulfillment

of the requirement for the degree of

DOCTOR OF PHILOSOPHY

In

Zoology

By

IRFANA LIAQAT Roll No: 0024-PHD-GCU-Z-09

Session 2009-2012

Department of Zoology,

Government College University,

Lahore 54000,

Pakistan.

3

DECLARATION

I, Irfana Liaqat Roll No. 24-GCU-PHD-Z-09, student of Doctor of Philosophy in

the subject of Zoology, hereby declare that the matter printed in the thesis titled

Genetic and Endocrinological Studies of Female Reproductive Dysfunction is my

own work and has not been printed, published and submitted as research work, thesis

or publication in any form in any University, Research Institution etc. in Pakistan or

abroad.

Dated

Irfana Liaqat

4

RESEARCH COMPLETION CERTIFICATE

It is certified that research work contained in this thesis titled “Genetic and

Endocrinological Studies of Female Reproductive Dysfunction” has been carried

out and completed by Irfana Liaqat Roll No. 24-GCU-PHD-Z-09 under my

supervision.

Dated

Dated

Supervisor

Prof. Dr. Nusrat Jahan

Co- Supervisor

Prof. Dr. Khalid Parvez Lone

Chairperson

Department Of Zoology

GC University Lahore

Controller of Examination


6

Acknowledgements

Above all is the Almighty ALLAH; I give thanks to him for it is He who has

brought me thus far and to his Last and Beloved Prophet (Sallallallhu Alaihi

Wasallam) for whom this wide and huge universe was assembled and who is the

pioneer of education and research.

I would like to acknowledge my gratitude for everyone who has helped me

along my Ph. D thesis work.

First, I must thank Prof. Dr. Nusrat Jahan, the Chairperson, Department of

Zoology, GC University Lahore. What an amazing person my supervisor is! You have

put such a lot of time and effort in to me - I couldn’t have wished for a better role

model. The road was not always smooth, but we persevered. To her I am truly

grateful. Her knowledge, sagacity and wonderful memory have helped me a lot. I am

very grateful to have her as my supervisor and I hope her enthusiasm towards science

will continue to inspire all her students. I want to express my deepest thanks to my

supervisor. Who has helped and supported me all along my research work at the GC

University Lahore.

I also pay gratitude to Prof. Dr. Khalid Parvez Lone the Chairperson of

Department of Physiology and Cell Biology, University of Health Science, Lahore. He

was never hesitant to lend an ear, or give advice, and if he had the resources, they

were mine to use. But for his kind cooperation which he gave me in my hard times, I

would not have been able to do this effort. Your kindness and generosity has meant so

much. I want to express my deepest thanks to my co-supervisor.

A huge thank-you to Prof. Dr. Hugh S. Taylor, Professor and Chair

Department of Obstetrics, Gynecology and Reproductive Sciences Yale University

USA, for your support and guidance throughout this project. You are an amazing

teacher, your enthusiasm and positivity was much appreciated.

I acknowledge Higher Education commission Pakistan for funding my PHD

Indigenous fellowship as well as for providing International Research Support

Initiative Program (IRSIP) Scholarship. You have made so much difference to my life

over the last few years, and without you this thesis would never have been finished.

The shadows of the past have turned into a future that I can begins to look forward to

without anxiety, a future I never believed possible.

7

My heartiest thanks are due to Dr. Andrew Pakstis for patiently teaching me

the sequencing techniques and for his excellent technical assistance in genetic and

statistical analysis. You remained encouraging and positive throughout my analysis

while my self-doubt ran rampant. Thanks to everyone in the Taylor Lab, Yale School

of medicine, Graciela Krikun, Flannery Clare, Haniya, Levent, Sihyu, Hongling

Du, Yuping Zhou for assistance with the time course experiment and the training in

genetic studies.

I am grateful to my all teachers for giving me enormous help at G C

University Lahore. I am also thankful to all lab and departmental staff for their

devotive and cooperative behavior. I am in debt to Dr. Shafaqat Rehmani for

providing me an opportunity to work at WTO Labs. Thanks to everyone, Imran

Haider, Ali Imran, Asghar and Wadood in the office at GC University Lahore.

I have special thanks for my friends and colleagues for giving me enormous

help and coverage. I have to say a huge thank you to my friends Najiya, Andleeb,

Riffat, Shaista, Sonia. Asma, Mehwish, Tariq, and Ijaz. Without their support I

could not possibly have reach this point. I know my words will be embarrassed to

describe Epical favor. I am also indebted to many others who have contributed

directly or indirectly to my research work.

Thank you to my parents for your belief in the value education. I would also

like to thank my parents, my family, especially my father and my brothers, Rafaqat,

Asif and Azam for all of their support throughout my life. Without them I would not

be here. I particularly wish to thank Fateh Naseeb for being absolutely amazing

during the tough times. You have supported me emotionally throughout the last few

years.

Finally, one special person deserves my deepest gratitude and love. I want to

thank my mother who had brought me up to the person.

IRFANA LIAQAT

8

SUMMARY

Endometriosis is one of the major threats to women’s health that leads toward

infertility. The inheritable predisposition to endometriosis develops a growing interest

in identifying the genes and genomic variants involved in the pathogenesis of

endometriosis. Polycystic ovary syndrome (PCOS) is the major cause of anovulatory

infertility. The genetic basis of PCOS is not well understood, it is a common

metabolic and endocrine disorder. The current study aimed to investigate for the first

time, the possible genomic variants and single nucleotide polymorphism (SNP) in

selective genes associated with endometriosis and PCOS in Pakistani women from the

Punjab region. DNA samples from fifty-two genetically unrelated endometriosis

patients and fifty-two controls were analyzed by direct sequencing to determine the

polymorphisms of estrogen receptor alpha ESR1 (rs2234693, rs9340799), estrogen

receptor beta ESR2 (rs4986938), progesterone receptor PGR (rs1042838,

rs10895068), interleukin 10 IL10 (rs1800871, rs1800872 and rs1800896) and follicle

stimulating hormone receptor FSHR (rs6166, rs6165) genes. Genetically unrelated

PCOS patients and controls, 96 each, were selected on the basis of their Body Mass

Index (BMI) and degree of obesity. The polymorphisms of different loci on

adiponectin ADIPOQ (rs2241766, rs1501299 and rs2241767), insulin receptor INSR

(rs1799817, rs1799815 of rs2059806 and rs2229429), FSHR (rs6164, rs6165),

Follicle stimulating hormone beta FSHB (rs6169), Luteinizing hormone

choriogonadotropin receptor LHCGR (rs61996318 and rs111834744), Luteinizing

hormone beta LHB (rs1800447 and rs4002462), ESR1 (rs2234693, rs9340799) and

ESR2 (rs4986938) genes were analyzed by direct sequencing. The rs4986938 of ESR2

and rs1042838 of PGR gene show strong association (p = 0.006, OR: 1.360; CI: 0.16-

0.80; p < 0.003, OR = 1.935, 95% CI = 0.10-0.62) with endometriosis. The genotype

and allele frequency of ESR1 gene polymorphisms were distributed similarly among

patients and control groups (p > 0.050). The allele A of rs1800872 (p < 0.006, OR =

2.379, 95% CI = 0.23-0.75), T of rs1800871 (p = 0.010, OR = 0.443, 95% CI = 0.19-

0.92) and G of rs1800896 ((p = 0.007, OR = 1.435, 95% CI = 0.24-0.77) at IL10 gene

were strongly associated with the predisposition of endometriosis in Pakistani women.

Significant (p < 0.001) associations were observed within the genotype frequencies,

allele frequencies and multi-SNP haplotype analysis of the genetic polymorphisms of

FSHR gene with endometriosis. This study identified new single nucleotide

9

polymorphisms (SNPs) at positions +349 A/G in ADIPOQ, +1638 T/C in INSR and

+657 del/T in LHCGR genes associated with PCOS (p < 0.005) in Pakistani women.

The polymorphisms in the ADIPOQ (r2= 0.78), ESR1 (r

2= 0.48) and FSHR (r

2= 0.76)

genes were in strong (p < 0.001) linkage disequilibrium. The highly significant (p =

0.030, OR = 0.436, 95% CI = 0.21-0.89) SNP of ADIOPQ gene associated with

PCOS was rs2241766 when compared with their controls. In INSR gene the most

common haplotypes CGT, CAC and CAT were found to be more prevalent in the

PCOS than controls (p < 0.001). The FSHR and LHB gene polymorphism seems to be

stable loci in Pakistani PCOS women (p > 0.050). Whereas, the rs6169 of FSHB gene

was strongly (p= 0.020, OR= 0.606, 95% CI= 0.40-0.91) associated with PCOS in this

subpopulation. The rs111834744 of LHCGR (p < 0.001, OR = 1.270, 95% CI = 0.18-

0.42), rs2232693 of ESR1 and rs4986938 of ESR2 genes were significantly (p <

0.005) associated with the onset of PCOS in Pakistani women. Significant (p < 0.005)

associations were observed within the genotype frequencies, allele frequencies and

multi-SNP haplotype analysis of most polymorphisms studied. Serum progesterone

level was lower in endometriosis patients while the serum testosterone and FSH titres

were higher in PCOS women when compared with their controls (p < 0.001). The

current findings suggest that the functional promoter polymorphism of IL10 gene

ATG genotype may contribute in the risk of endometriosis. Current study provides the

novel and new to science associations of ADIPOQ, INSR, FSHB, LHCGR, ESR1 and

ESR2 genes with PCOS in Pakistani women. The genetic variants of above mentioned

gene loci might influence the fertility status of endometriosis and PCOS patients. This

suggests that the susceptible loci for endometriosis and PCOS lie within or very close

to the chromosomal regions spanning these genes.

10

TABLE OF CONTENTS

Page No.

LIST OF TABLES .................................................................................................................... i

LIST OF FIGURES ................................................................................................................. iv

LIST OF ABBREVIATIONS ................................................................................................ viii

CHAPTER 1

INTRODUCTION.................................................................................................................. 1-13

1.1 Infertility ...............................................................................................................................1

1.1.1 Causes of infertility in women ........................................................................................1

1.2 Endometriosis ........................................................................................................................2

1.3 Polycystic ovary syndrome ...................................................................................................6

CHAPTER 2

REVIEW OF LITERATURE ............................................................................................... 14-33

2.1 Endometriosis .....................................................................................................................14

2.1.1 Estrogen receptor alpha (ESR1) .....................................................................................14

2.1.2 Estrogen receptor beta (ESR2) .......................................................................................17

2.1.3 Interleukin 10 (IL10) .....................................................................................................19

2.1.4 Progesterone receptor (PGR) .........................................................................................19

2.2 PCOS ...................................................................................................................................22

2.2.1 Adiponectin (ADIPOQ) .................................................................................................22

2.2.2 Insulin receptor (INSR) ..................................................................................................25

2.2.3 Follicle stimulating hormone receptor (FSHR) .............................................................27

2.2.4 Follicle stimulating hormone beta (FSHB)....................................................................31



2.2.7 Luteinizing hormone choriogonadotropin receptor (LHCGR) ......................................32

2.2.8 Luteinizing hormone beta (LHβ) ...................................................................................32

11

CHAPTER 3

MATERIALS AND METHODS ......................................................................................... 34-54

3.1 Sampling size and study design .........................................................................................34

3.2 Subjects ...............................................................................................................................34

3.3 Sample selection ..................................................................................................................34

3.3.1 Inclusion criteria ............................................................................................................34

3.3.2 Exclusion criteria ...........................................................................................................35

3.3.3 Selection of controls ......................................................................................................35

3.4 Physical examination ..........................................................................................................37

3.4.1 Determination of Height, Weight and BMI ...................................................................37

3.4.2 Physical examinations and interviews ...........................................................................37

3.5 Blood sampling and Storage ..............................................................................................37

3.6 Genotyping and DNA sequencing .....................................................................................38

3.6.1 Genomic DNA extraction ..............................................................................................38

3.6.2 Candidate Genes ............................................................................................................39

3.6.3 Single nucleotide polymorphism selection ....................................................................39

3.6.4 Primer designing ............................................................................................................46

3.6.5 PCR Analysis.................................................................................................................49

3.6.6 Gel electrophoresis and verification of PCR products ..................................................49

3.6.7 Purification of PCR product ..........................................................................................49

3.6.8 DNA sequencing ...........................................................................................................50

3.6.9 DNA sequencing data interpretation .............................................................................50

3.7 Hormonal Analysis.................................................................................................................51

3.7.1 Follicle stimulating hormone .........................................................................................51

3.7.2 Testosterone ...................................................................................................................52

3.7.3 Progesterone ..................................................................................................................52

3.8 Statistical analysis ..............................................................................................................53

12

3.9 Haplotype and linkage disequilibrium analysis...............................................................53

CHAPTER 4

RESULTS ............................................................................................................................. 55-128

4.1 Population characteristics .................................................................................................55

4.2 Genotype, allele frequencies and Haplotype ....................................................................55

4.3 Endometriosis .....................................................................................................................60



4.3.3 Interleukin 10 (IL10) .....................................................................................................70

4.3.4 Progesterone receptor (PGR) .........................................................................................77


4.4 PCOS ...................................................................................................................................86

4.4.1 Adiponectin (ADIPOQ) .................................................................................................86

4.4.2 Insulin receptor (INSR) ..................................................................................................93


4.4.4 Follicle stimulating hormone beta (FSHB)..................................................................104

4.4.5 Luteinizing hormone choriogonadotropin receptor (LHCGR) ....................................107

4.4.1 Luteinizing hormone beta (LHB) .................................................................................111

4.4.2 Estrogen receptor alpha (ESR1) ...................................................................................116

4.4.3 Estrogen receptor beta (ESR2) .....................................................................................123

4.5 Hormonal analysis ...........................................................................................................123

4.5.1 Follicle stimulating hormone (FSH) ............................................................................123

4.5.2 Testosterone .................................................................................................................123

4.5.3 Progesterone ................................................................................................................123

CHAPTER 5

DISCUSSION ..................................................................................................................... 129-137

5.1 Population characteristics ...............................................................................................129

5.2 Endometriosis .................................................................................................................130

13

5.3 PCOS ..............................................................................................................................133

CHAPTER 6

REFERENCES ................................................................................................................... 138-162

CHAPTER 7

ANNEXURES ..................................................................................................................... 163-178

LIST OF PUBLICATIONS AND PRESENTATIONS .................................................. 179-180

14

LIST OF TABLES

Table No. Title Page No.

Table 2.1 Summary of association studies between ESR1 gene polymorphisms

(rs9340799 and rs2234693) and endometriosis.

16

Table 2.2 Summary of association studies between ESR2 (rs4986938) gene

polymorphisms and endometriosis.

18

Table 2.3 Summary of association studies between IL10 (rs1800896, rs1800871

and rs1800872) gene polymorphisms and endometriosis.

20

Table 2.4

(a)

Summary of association studies between ADIPOQ (rs2241766) gene

polymorphisms and PCOS.

23

Table 2.4

(b)

Summary of association studies between ADIPOQ (rs1501299) gene


24

Table 2.5 Summary of association studies between INSR (rs1799817 and

rs2059806) gene polymorphisms and PCOS.

26

Table 2.6 Summary of association studies between FSHR (rs6165) gene


29

Table 2.7 Summary of association studies between FSHR (rs6166) gene


30

Table 3.1 Genotyping panel for endometriosis candidate genes. 40

Table 3.2 Genotyping panel for PCOS candidate genes. 41

Table 3.3 Primers, PCR program, annealing temperatures and PCR nucleotide

product size of endometriosis polymorphisms.

42

Table 3.4 Primer, annealing temperature, PCR program and product size of

PCOS polymorphisms.

44

Table 4.1 Anthropometric characteristics of PCOS, endometriosis and controls. 56

Table 4.2 Anthropometric characteristics of women with endometriosis and

controls, the values given are mean ± S.D. The mean values of two

groups were compared by “t” test.

57

15

Table 4.3 Anthropometric characteristics of women with PCOS and controls.

The values given are mean ± S.D. The mean values of two groups

were compared by “t” test.

58

Table 4.4 Frequency distribution of single nucleotide polymorphisms of ESR1

gene with risk of endometriosis in Pakistani women.

64

Table 4.5 Multi-SNPs haplotype frequency estimates for endometriosis and

controls at ESR1 gene.

66

Table 4.6 Frequency distribution of single nucleotide polymorphism of ESR2


69

Table 4.7 Frequency distribution of single nucleotide polymorphisms of IL10


73


controls at IL10 gene.

75

Table 4.9 Frequency distribution of single nucleotide polymorphisms of PGR


79


controls at PGR gene

80

Table 4.11 Frequency distribution of single nucleotide polymorphisms of FSHR


84


controls at FSHR gene.

85

Table 4.13 Frequency distribution of single nucleotide polymorphisms of

ADIPOQ gene with risk of PCOS in Pakistani women.

90

Table 4.14 Multi-SNPs haplotype frequency estimates for PCOS and controls at

ADIPOQ gene.

91

Table 4.15 Frequency distribution of single nucleotide polymorphisms of INSR

gene with risk of PCOS in Pakistani women.

95


INSR gene.

97

Table 4.17 Frequency distribution of single nucleotide polymorphisms of FSHR


102


FSHR gene.

103

Table 4.19 Frequency distribution of single nucleotide polymorphisms of FSHB


106

16

Table 4.20 Frequency distribution of single nucleotide polymorphisms of

LHCGR gene with risk of PCOS in Pakistani women.

109


LHCGR gene.

110

Table 4.22 Frequency distribution of single nucleotide polymorphisms of LHB


114

Table 4.23 Multi-SNPs haplotype frequency estimates for PCOS and controls

at LHB gene.

115



118

Table 4.25 Multi-SNPs haplotype frequency estimates for PCOS and controls

at ESR1 gene.

121



124

17

LIST OF FIGURES

Figure No. Title Page No

Figure 1.1 Pathogenesis of endometriosis; hormone and endometrial

inflammatory related manifestation.

3

Figure 1.2 Pathogenesis of PCOS; hormone and metabolic syndrome

related manifestation.

8

Figure 3.1 Diagrammatic and schematic presentation of research layout. 36

Figure 3.2 The sequence highlighted blue represent the forward and

reverse primers and arrows (purple) shows SNP (a-d).

48

Figure 4.1 Clinical manifestation of anthropometric characteristics in

endometriosis compared with control along with percentage

symptoms.

59

Figure 4.2 Clinical manifestation of anthropometric characteristics in

PCOS compared with control along with percentage

symptoms.

59

Figure 4.3 Two sequence BLAST alignment of ESR1 gene

polymorphisms.

62

Figure 4.4 Sequence chromatogram showing homozygous and

heterozygous form of T/C base substitution of rs2234693.

62

Figure 4.5 Multi-SNPs haplotype percent frequency distribution for

endometriosis and controls at ESR1 gene.

63

Figure 4.6 Pairwise linkage disequilibrium of ESR1 gene in endometriosis

and controls.

67

Figure 4.7 Two sequence BLAST alignment of IL10 gene

polymorphisms.

71


heterozygous form of C/T base substitution of rs1800871.

71


endometriosis and controls at IL10 gene.

72

Figure 4.10 Pairwise linkage disequilibrium of IL10 gene in endometriosis

and controls.

76

18


endometriosis and controls at PGR gene.

78

Figure 4.12 Pairwise linkage disequilibrium of PGR gene in endometriosis

and controls.

80

Figure 4.13 Two sequence BLAST alignment of FSHR gene

polymorphisms.

82


heterozygous form of A/G base substitution of rs6166.

82


endometriosis and controls at FSHR gene.

83

Figure 4.16 Pairwise linkage disequilibrium of FSHR gene polymorphisms

in endometriosis and controls.

85

Figure 4.17 Two sequence BLAST alignment of ADIPOQ gene

polymorphisms.

88


heterozygous form of T/G base substitution of rs2241766.

88


PCOS and controls at ADIPOQ gene.

89

Figure 4.20 Pairwise linkage disequilibrium of ADIPOQ gene in PCOS

and controls.

92


PCOS and controls at INSR gene.

94

Figure 4.22 Pairwise linkage disequilibrium of INSR gene in PCOS and

controls.

98


PCOS and controls at FSHR gene.

101

Figure 4.24 Pairwise linkage disequilibrium of FSHR gene in PCOS and

controls.

103

Figure 4.25 Two sequence BLAST alignment of FSHB gene

polymorphisms.

105


heterozygous form of T/C base substitution of rs6169.

105

19


PCOS and controls at LHCGR gene.

108

Figure 4.28 Pairwise linkage disequilibrium of LHCGR gene in PCOS and

controls.

110

Figure 4.29 Two sequence BLAST alignment of LHB gene

polymorphisms.

112


heterozygous form of A/G base substitution of rs4002462.

112


PCOS and controls at LHB gene.

113

Figure 4.32 Pairwise linkage disequilibrium of LHB gene in PCOS and

controls.

115


PCOS and controls at ESR1 gene.

117

Figure 4.34 Pairwise linkage disequilibrium of ESR1 gene in PCOS and

controls.

122

Figure 4.35 Serum concentration of FSH in women with PCOS and

controls. Values given are mean in mIU/ml of FSH ± S.D. The

asterisk shows the significant difference between 2 groups

according to the “t” test.

125

Figure 4.36 Comparison of mean FSH values in women with PCOS and

controls according to rs6166 genotype of FSHR gene. . The

asterisk shows the significant difference between 2 groups

according to the “t” test.

125


controls according to rs6165 genotype of FSHR gene.

126


controls according to rs6169 genotype of FSHB gene.

126

Figure 4.39 Serum concentration of Testosterone in women with PCOS

and controls. Values given are mean in ng/ml of testosterone ±

S.D. The asterisk shows the significant difference between 2

groups according to the “t” test.

127

20

Figure 4.40 Serum concentration of progesterone in women with

endometriosis controls. Values given are mean in ng/ml of

progesterone ± S.D. The asterisk shows the significant

difference between 2 groups according to the “t” test.

128

21

LIST OF ABBREVIATIONS

ADIPOQ Adiponectin

ASRM American Society for Reproductive Medicine

BMI Body mass index

bp Base pair

Chi Sq Chi square

CI Confidence interval

CVD Cardio vascular disease

ddNTPs Dideoxy terminators

dNTP Deoxynuleotide

E het Estimated heterozygosity

EDTA Ethylenediaminetetraacetic acid

E-M Expectation-maximization

ESHRE European Society of Human Reproduction and Embryology

ESR1 Estrogen receptor alpha

ESR2 Estrogen receptor beta

Exp. Het Expected Heterozygosity

FSH Follicle stimulating hormone

FSHB Follicle stimulating hormone beta

FSHR Follicle stimulating hormone receptor

ftp File transfer protocol

Global LD

LR Chi Sq

Global likelihood ratio chi-square

hCG Chorionic Gonadotropin

HGVS Human Genome Variation Society

HWE Hardy–Weinberg equilibrium

IL10 Interleukin 10

INSR Insulin receptor

LD Linkage disequilibrium

LH Luteinizing hormone

LHB Luteinizing hormone beta

22

LHCGR Luteinizing hormone choriogonadotropin receptor

MgCl2 Magnesium chloride

NCBI National Center for Biotechnology Information

OD Ovulatory dysfunction

OR Odd ratios

p Significance

PCOS Polycystic ovary syndrome

PCR Polymerase chain reaction

PGR Progesterone receptor

PID Pelvic inflammatory disease

S.E.E Standard error of estimation

SD Standard deviation

SDS Sodium dodecyl sulphate

SNP Single nucleotide polymorphism

T2 DM Type 2 diabetes mellitus

TE Tris-EDTA

UCSC University of California, Santa Cruz

WBCs White blood cells

WHR Waist and hip ratio

χ2 Chi square

23

CHAPTER 1

INTRODUCTION

The need for research related to female reproduction is one of the most

significant issues presently faced by the health sector in Pakistan today.

1.1 Infertility

Infertility is the most prevalent health disorders in young adults worldwide;

approximately 8-10% of couples are unable to conceive during their reproductive age

(Inhorn, 2003). This refers to the biological inability to conceive after regular

unprotected intercourse (Makar and Toth, 2002). Infertility can be immunological,

psychological, resulting from certain surgery or blockage, or be associated with

defined abnormalities in the gametes. In 20% of couples the cause of infertility is

unexplained (Uehara et al., 2001). According to a study carried out in a Gynaecology

and Obstetrics Department at the Federal Government Services Hospital, Islamabad,

Pakistan, the estimated infertility rate in the observed population from the last three

years was 7 % (Shaheen et al., 2010).

A complete physical examination of both partners is required for infertility

evaluation. Six factors have been reported to be responsible for the cause of infertility.

These include male factor, cervical factor, endometrial-uterine factor, tubal factor,

peritoneal factor and ovulatory factor (Clark and Keefe, 1989).

1.1.1 Causes of infertility in women

The major causes of infertility comprise ovulatory dysfunction (OD), tubal

damage and endometriosis in women. According to World Health Organization

(WHO) criteria, OD is classified in to various categories including low gonadotropins,

hyperprolactinaemia, and primary ovarian failure (Lunenfeld and Insler, 1974). The

function of female reproductive organs is remarkably influenced by many genetic

factors. Different studies on various populations investigated the susceptible genes for

female reproductive disorders such as endometriosis, polycystic ovary syndrome

(PCOS), ovulation disorder, pelvic inflammatory disease (PID), premature ovarian

failure, pelvic adhesions and benign uterine fibroids (Escobar-Morreale et al., 2005).

24

1.2 Endometriosis

Endometriosis is a common cause of infertility and pelvic pain. This disease

affects approximately 7-10% of all women worldwide during their reproductive age

(Baldi et al., 2008) with substantial annual health costs (Simoens et al., 2007) and

health burdens for individuals (Jones et al., 2002). Endometriosis accounts for $22

billion annually in US healthcare costs (Simoens et al., 2007). Clinically the major

concern of endometriosis is its predisposition of infertility. It was expected that 25-

50% of endometriosis women are infertile (Gao et al., 2006). Whereas 25-30% of

women have developed endometriotic lesions and identified for infertility (Missmer

and Cramer, 2003; Giudice and Kao, 2004). Many genetic factors strongly influence

the reproductive functions of female and different studies investigated the susceptible

and candidate genes involved in the female reproduction and fertility (Missmer and

Cramer, 2003; Giudice and Kao, 2004; Montgomery et al., 2008).

Recently, the genetic polymorphisms have been suggested as genetic

biomarkers of disease (Falconer et al., 2007; Vietri et al., 2007). The human genome

project discovered the single nucleotide polymorphism (SNP) as new markers and this

opened new novel ways to establish the genetic association of complex disorders with

candidate and susceptible genes. A mutation that results in base substitution is called

single nucleotide polymorphism. SNPs in protein coding region could be classified as

non-synonymous and synonymous; the former results in missense mutation that

causes change in amino acid or may be nonsense mutation resulting in codon

termination. While the synonymous mutations are silent and do not change the amino

acid. SNPs in promoter region can cause increased or reduced expression of gene. In

addition SNPs in intron region alter the transcription rate due to mutation of

regulatory elements. The average occurrence of SNPs in genome is every 1.9 kb

whereas 1.42 million SNPs had been mapped. More than 60,000 SNPs were

represented in untranslated and exon regions (Marth et al., 2001).

The pathogenesis of endometriosis remains enigmatic (Figure 1.1). It is a

condition in which endometrial tissue implants and grows outside the uterus and

subsequently affects the function of ovaries, uterus and fallopian tubes resulting in

reduced fertility (Sasson and Taylor, 2008). The primary symptoms of endometriosis

include infertility, abdominal and pelvic pain, back pain, dysmenorrhea, dysuria,

dyschezia and dyspareunia (Giudice and Kao, 2004). Among several hypotheses

25

Figure 1.1: Pathogenesis of endometriosis; hormone and endometrial

inflammatory related manifestation.

Genetics Lifestyle and Environment

Endometriosis

Hormone driven

manifestation

Infertility

Low

Progesterone

Hyper activated

endometrial inflammatory

system

Prostaglandins

Excess estrogen Endometrium

out growths

Pelvic pain

Dysmenorrhea

Back pain

Cytokines

Ovarian cancer

Inflammatory

response

resistance

IL10, FSHR,ESR1,PGR,

ESR2 genes etc.

Dyspareunia

Dysuria Growth factor

26

proposed to explain the endometriosis pathogenesis the retrograde mensuration is

widely accepted (Sasson and Taylor, 2008). Endometriosis exists in at least three

distinct forms: peritoneal endometriosis, rectovaginal endometriotic nodules and

endometriomas. These three types might be variants of the similar pathological

process; however it is likely that they are caused by distinct mechanisms (Brosens,

2004). Endometriosis is a complex disease that is not likely due to a single heritable

genetic defect. Endometriosis was indicated as risk factor for multiple malignancies

especially ovarian cancer in numerous epidemiological studies (Borgfeldt and Ellika,

2004; Kobayashi et al., 2007).

The development of endometriotic lesions includes genetic predisposition and

environmental factors (Sasson and Taylor, 2008). Endometriosis is recognized as

polygenic multifactorial disease with heritable tendencies (Simpson and Bischoff,

2002; Simpson et al., 2003). The candidate and susceptible genes responsible for

pathogenesis of endometriosis have been investigated in various genetic association

studies (Hadfield et al., 2001; Vigano et al., 2003).

In recent years various lines of genetic association studies have explore the

association between genetic polymorphisms with the development of endometriosis

(Luisi et al., 2006; Chun et al., 2012; Gallegos-Arreola et al., 2012), although the

exact genes involved in the pathogenesis and susceptibility of endometriosis

development are unknown.

Endometriosis is clearly a hormone dependent disease that is characterized by

responsiveness to estrogens, prostaglandins, metalloproteinases, cytokines,

chemokines and resistance to progesterone (Giudice and Kao, 2004; Borghese et al.,

2010). Estrogen is responsible for persistent growth of endometriotic tissue; however

the cytokines and prostaglandins are significant in the pathogenesis and development

of endometriosis (Jabbour et al., 2006). The large quantities of prostaglandin E2

produced by stromal cells induce local estrogen production and biosynthesis in

women with endometriosis and impair pelvic pain (Soysal et al., 2004). The

aromatase converted cholesterol into estradiol locally in endometriosis (Bulun et al.,

2005). Due to the multiple contributors and pathways leading to disease, genes

encoding inflammatory mediators, sex hormones and enzymes involved in

metabolism and biosynthesis have been investigated for their putative role in

endometriosis. For example, the inflammatory mediator interleukin-10 (1q31-q32,

IL10); sex hormone receptors, estrogen receptor alpha (6q25.1, ESR1), estrogen

27

receptor beta (14q23.2, ESR2), and progesterone receptor (11q22-q23, PGR)

(Arvanitis et al., 2003; Hsieh et al., 2005; Kim et al., 2005; De Carvalho et al., 2007;

Lee et al., 2007) have been studied by different laboratories on various populations.

Recently, the interest has focused on identifying genetic polymorphisms in various

genes underlying susceptibility to endometriosis (Falconer et al., 2007).

Estrogen and progesterone receptors mediated the pathological and

physiological activities of the sex steroid hormons. SNPs in ESR1 (rs2234693 and

rs9340799), ESR2 (rs4989638) and PGR (rs10895068) genes were associated with

expression and alteration of these sex steroid receptors (Gomes et al., 2006).

Endometriosis seems to be inhibited by progesterone (Young and Lessey, 2010) and

progression of disease is stimulated by estrogen (Bulun et al., 2000; Ness, 2003).

Gurates and Bulun, (2003) emphasized the potential involvement of PGR in the

molecular mechanism underlying the development of endometriosis. Indeed the

particular genes regulated by progesterone showed abnormal expression and defect in

function of endometrium in women with endometriosis. Moreover, alternation of PGR

gene expression was demonstrated in endometrium tissue (Gurates and Bulun, 2003;

Kao et al., 2003). Estrogen and progesterone are gonadotrophic hormones and are

essential for human reproduction. Alteration in any of these genes causes infertility

including endometriosis (Gurates and Bulun, 2003).

Similarly, many immunological factors are reported to be associated with the

pathogenesis of endometriosis (Wu and Ho, 2003). An important immune-modulatory

cytokine is IL10 was recognized for its function to inhibit activation and function of

T-cells, macrophages and monocytes. IL10 acts as to limit and terminate the

inflammatory response (Moore et al., 2001). The polymorphisms, rs1800872,

rs1800871 and rs180089 of interleukin 10 gene in the promoter region and their

relationship with endometriosis have been analyzed in recent years (Xie et al., 2009;

Riiskjaer et al., 2011), although the role of these polymorphisms in disease

development is not recognized. A study on Taiwanese patients with endometriosis

reported the association of IL10 gene polymorphism with this disease (Juo et al.,

2009).

The polymorphism in follicle stimulating hormone receptor (FSHR) gene in

relation with endometriosis is least studied. The polymorphism rs6166 is most studied

as compared to polymorphism rs6165 (Mohiyiddeen and Nardo, 2010). The amino

acid coded by this region is present in extracellular domain of follicle stimulating

28

hormone (FSH) protein binding region (Simoni et al., 2002). This is the fundamental

region for FSH mediated events of signal transduction therefore affects the hormone

binding ability of the receptor (Kene et al., 2005). The homozygous polymorphism

GG at 680 of FSHR enhanced aromatase activity which induce more production of

estrogens and stimulate the proliferation of endometriotic tissues (Wang et al., 2011).

In addition, the lower risk of endometriosis was investigated with non-synonymous

SNPs of FSHR gene including homozygous GG (Ser/Ser) and GA (Ser/Asn) at 680 in

Taiwan population (Wang et al., 2011).

A study on Taiwanese Chinese females suggests that the non-synonymous

SNP rs6165 of FSHR gene mediated the extracellular recognition events which

modulate the risk and development of endometriosis. Moreover, the conversion of

680Ser from 680Asn as a result of A to G of rs6166 showed significant association with

endometriosis suggests that phosphorylation of the cytoplasmic residue may be

important for normal signaling pathways against the development of endometriosis

(Wang et al., 2012).

1.3 Polycystic ovary syndrome (PCOS)

PCOS is a heterogeneous ovarian disorder associated with obesity,

anovulation, hyperandrogenism, hirsutism, and infertility that affect 6-10 % of women

at reproductive age worldwide (Goodarzi et al., 2011) and accounts for 70% cases of

anovulatory infertility (Brassard et al., 2008). Stein and Leventhal first described the

PCOS in 1935 (Stein and Leventhal, 1935). The etiology of PCOS is still not clear.

Some genetic and hormonal factors have been implicated for the pathogenesis of

PCOS including altered ovarian synthesis of steroids, hyperinsulinemia, aberrant

folliculogenesis, abnormal secretion of gonadotropin and neuroendocrine

abnormalities (Goodarzi et al., 2011). Among different criteria for the diagnosis of

PCOS the most widely used was proposed by Rotterdam (2004). This includes any

form of hyperandrogenemia either clinical (hirsutism and acne) or endocrine (high

level of androgens), oligomenorrhea and the ultrasound examination of polycystic

ovary. These three major criteria make PCOS a heterogeneous disease. The diagnosis

can be made if 2 out of 3 criteria are met (Rotterdam, 2004).

Both environmental and genetic factors make PCOS a heterogeneous disorder

(Figure 1.2). The multifactorial etiology of PCOS is underpinned by multiple genetic

architecture that initiated to elucidate in recent years (Fauser et al., 2011). An

29

interaction between environmental factors and polymorphisms of various genes

makes PCOS a complex polygenic disorder (Luque-Ramírez et al., 2006; Vink et al.,

2006). However the molecular genetic mechanisms and inheritance pattern of PCOS

is not fully known (Valdés et al., 2008). PCOS is an endocrinological disorder

therefore the genes involved in the sex hormones or their regulators have been studied

for polymorphisms (Simoni et al., 2008). Different studies provide evidences that

PCOS is a familial disorder (Legro et al., 1998; Ehrmann, 2005). This indicates the

significance of genetic component and involvement of multiple gene variants

contributing the metabolic and endocrine effects in PCOS (Diao et al., 2004; Roldan

et al., 2004; Ehrmann, 2005).

A number of studies investigated the association of various candidate genes

with PCOS while the pathogenesis of diseases is not accepted with any of the gene

universally (Nam and Straus, 2007; Unluturk et al., 2007; Urbanek, 2007). The

heritable basis and genetic etiology of PCOS has also been indicated by clinical

evidences (Legro et al., 1998; Vink et al., 2006).

The candidate and susceptible genes for PCOS includes: polymorphisms of

genes encoding regulatory proteins and sex hormones like follicle stimulating

hormone beta (FSHB), follicle stimulating hormone receptor (FSHR), estrogen

receptor alpha (ESR1) and estrogen receptor beta (ESR2) (Tong et al., 2000; de Castro

et al., 2004; Jun et al., 2006; Yang et al., 2006;) and variants of genes encoding

protein expressions involved in insulin resistance like adiponectin (ADIPOQ), insulin

receptor gene (INSR), (Xita et al., 2005; Jin et al., 2006). A number of genetic

variants were implicated in the susceptibility of PCOS, whereas no single marker was

associated repeatedly and conclusively with the disorder (Urbanek, 2007).

PCOS is a metabolic syndrome, therefore adiponectin was considered as

potential candidate gene for PCOS. Adiponectin possesses insulin sensitizing, anti-

atherosclerotic and anti-inflammatory properties, accumulating evidence suggest that

adiponectin has key roles in regulating female reproductive functions (Brochu-

Gaudreau et al., 2010). The ADIPOQ gene consists of 17 kb, consisting of two introns

and three exons located on chromosome 3q27 (Hu et al., 1996). Adiponectin is a

protein produced by an active endocrine organ the adipose tissue (Magkos and

Sidossis, 2007). The region 3q27 of ADIPOQ gene has been revealed as susceptibility

locus for metabolic syndromes including obesity (Kissebah et al., 2000) and insulin

resistance (Francke et al., 2001).

30

Figure 1.2: Pathogenesis of PCOS; hormone and metabolic syndrome

related manifestation.

Genetics Lifestyle and

Environment

PCOS

Hormone driven

manifestation

Insulin

Hyperandrogenism

oligo- or

anovulation

Metabolic syndrome

manifestation

Acne

Hirsutism

Androgens Adiposity

Diabetes

Cardio vascular

diseases

Obesity

Irregular

menstrual cycle

Infertility

Hyperinsulinemia

Insulin resistance

ADIPOQ, INSR, FSHR,

FSHB, ESR1, LHCGR,

LHB, ESR2 genes etc.

31

Among adipose protein the adiponectin modulate insulin activity and

represents a connection between adipocity and insulin resistance (Stefan et al., 2002).

The PCOS women showed abdominal adiposity and obesity due to occurrence of

hyperinsulinemia and insulin resistance (Dunaif, 2006). The women with PCOS

showed reduced fertility linked with metabolic syndrome including hyperinsulinemia

and insulin resistance (Tosca et al., 2008). PCOS women exhibit more susceptibility

for metabolic syndrome when compared with general population (Cussons et al.,

2008).

To date, the identified SNPs in adiponectin gene is 13 however among the

multiple polymorphisms of ADIPOQ, the two polymorphisms rs2241766 in exon 2

and rs1501299 in intron 2 attracted the most consideration. These two SNPs were

involved in alteration of serum level of adiponectin (Xita et al., 2004; Pollin et al.,

2005). To some extent these polymorphisms of adiponectin may determine the

phenotypic expression of certain metabolic syndrome. A study reported the

interaction between steroid hormone synthesis and adiponectin polymorphisms

(Meigs et al., 2005). However the gene expression or function of adiponectin under

the influence of these polymorphisms is not completely known, as rs1501299 is

intronic polymorphism while rs2241766 is synonymous polymorphism (Xita et al.,

2004).

Insulin resistance is defined as decrease in insulin mediated glucose

consumption. It is found in 50-90% PCOS women while its prevalence is 10-25% in

general population (Goodarzi et al., 2005). The beta (β) cells of pancreas produce

insulin which affects the various organs in the body. In female reproductive system

insulin enhances the growth of ovaries and stimulates the production and secretion of

androgens from ovaries; this inhibits ovarian follicle apoptosis and results in cyst

formation (Baillargeon and Nestler, 2006).

Insulin stimulates ovarian androgen production that affects ovarian

steroidogenic responses to luteinizing hormone and follicle-stimulating hormone.

Women develop PCOS because of hypersensitivity of the intra-ovarian insulin

androgen signaling pathway (Baillargeon and Nestler, 2006). In PCOS women the

major cause of insulin resistance is defect in post-binding region of INSR signiling

transduction pathway that reduced the autophosphorylation of tyrosine kinase domain

(Azziz, 2002). The insulin receptor gene located on chromosome 19p13.2 (Urbanek et

al., 2005) and the exon 17-21of INSR gene codes for tyrosine kinase residue of the

32

receptor required for insulin signal transduction. To date, among the different SNPs

detected in the region of exon 17 of INSR gene, the significant association was shown

by the rs1799817 with PCOS (Panz et al., 1996; Siegel et al., 2002). The substitution

from C to T allele at exon 17 was associated with the defect of tyrosine kinase domain

of INSR in PCOS women possibly due to its effects on the auto phosphorylation of the

INSR function (Lee et al., 2008). This also showed that polymorphism in INSR gene

may be associated with the patients of PCOS who are obese.

Follicle-stimulating hormone (FSH) is a pituitary glycoprotein that plays an

important role during folliculogenesis by promoting the proliferation and

differentiation of granulosa cells and maturation and development of follicles. The

effect of FSH is mediated by binding to a specific follicle stimulating hormone

receptor (FSHR) that is situated on the granulosa cells of the ovary (Moyle and

Campbell, 1996). Because of this important role of FSHR in the signaling

transmission of FSH, the FSHR gene may be an important candidate gene for PCOS.

A previous genome-wide association study in Chinese women with PCOS identified a

region on chromosome 2p16.3 that encodes the FSH receptor (FSHR) gene as a

reproducible PCOS susceptibility locus (Shi et al., 2012). The FSHR gene contains

two polymorphisms in exon 10 and change in amino acids at position N680S and

A370T. The rs6165 (A370T) is in the extracellular domain of FSHR gene which is the

high affinity binding site of FSH hormone (Du et al., 2010; Dolfin et al., 2011). The

polymorphisms of FSHR gene are in linkage disequilibrium therefore the haplotype of

these polymorphisms affected the FSH level (Orio et al., 2006). A number of genetic

studies showed the association between polymorphisms of FSHR gene and PCOS

(Orio et al., 2006; Bon-Hee et al., 2010).

FSHR is crucial for reproduction and mutations in this gene greatly affect the

fertility. It has been previously reviewed that mutations in FSHR cause loss of

function or gain of function in various cases (Lussiana et al., 2008; Thompson et al.,

2008; Salvi and Pralong, 2010). The mutations of FSHR gene inhibit the proper

ovarian function and causes infertility (Meduri et al., 2003; Kuechler et al., 2010). In

human the infertility including hypergonadotrophic, hypogonadism, amenorrhea and

ovarian failure is caused by inactivating mutations in the FSHR gene (Doherty et al.,

2002; Allen et al., 2003; Meduri et al., 2003; Kuechler et al., 2010). The mutations

found in any region of FSHR gene cause suppression in hormone binding capacity

and abnormality in signal transduction (Rannikko et al., 2002; Tranchant et al., 2011).

33

Estrogens play an important role in the function and development of the

reproduction system. The estrogen action was mediated by two specific high affinity

receptors, the ESR1 and ESR2, both of which belong to superfamily of nuclear

receptor and act as ligand activated transcription factor. Both receptors are necessary

for the proper functioning of the hypothalamic-pituitary-ovarian axis. Both ESR1 and

ESR2 are expressed in the human ovary, ESR2 is the main type of receptor and its

activation enhances folliculogenesis and ovulation (Hegele-Hartung et al., 2004).

Furthermore, the expression of ESR2 is lower in follicle derived from women with

PCOS compared with healthy women, while the ESR1 expression is markedly

increased in theca cells of polycystic ovaries, causing alteration in the ESR1/ESR2

ratio in PCOS and possibly abnormal follicular development (Jakimiuk et al., 2002).

Based on these observations, variants of ESR1 and ESR2 may be implicated in the

pathogenesis of PCOS. A number of polymorphic sites in ESR1 and ESR2 have been

identified with the most widely studied being rs2234693, rs9340799 polymorphism in

ESR1 and rs4986938 in ESR2.

The LHCGR gene encodes a receptor for luteinizing hormone (LHR) and

human chorionic gonadotropin (hCG) and mutations in LHCGR was associated with

infertility (Yariz et al., 2011). In PCOS women the polymorphisms of LHR gene

effect the ovarian androgen production and concentration of luteinizing hormone

(LH) which is expressed in the theca and granulose cells that leads toward anovulation

(Norman et al., 2007). Different studies investigated that mutations in LHR gene and

luteinizing hormone beta (LHβ) gene altered their structure and function by activating

and inactivating the bioactivity, moreover this cause amenorrhea, anovulation and

PCOS in women (Huhtaniemi and Themmen 2005; Huhtaniemi and Alevizaki 2006).

There were strong evidences that polymorphisms of LHβ and LHR genes involved in

the development of PCOS, however the inconsistent results were observed in different

populations and loci. LHβ gene polymorphism in exon 3 was examined to be mutant

in Singapore Chinese women with menstrual disorders (Ramanujam et al., 1999). A

Korean study found no associtaion between LHβ gene polymorphisms with PCOS

(Kim et al., 2001). However the women with LHR mutations often show infertility

and amenorrhea (Themmen, 2005). A genome wide association study (GWAS) in

Han Chinese women observed strong association between LHR gene polymorphism

and PCOS (Chen et al., 2011).

34

In most of the anovulated PCOS women the level of gonadotropic and

estrogen remains normal (Broekmans et al., 2006). The women with PCOS showed

frequent elevation in serum LH concentration and the LH to FSH ratio (Rebar et al.,

1976). The most common biochemical feature of PCOS is hyperandrogenemia

(Goodarzi et al., 2005). The high level of circulating androgen was observed in 80-

90% of PCOS women with oligomenorrhea (Hull, 1987; Goodarzi et al., 2005).

About 60% of PCOS women are hirsute due to hyperandrogenemia. This is the most

common clinical sign for PCOS phenotype (Azziz et al., 2009). Snehalatha reported

that Asian Indians have higher insulin resistance both with lean Body Mass Index

(BMI) and central obesity (Snehalatha et al., 2003).

The reproductive function is regulated by FSH, luteinizing hormone (LH) and

chorionic gonadotropin hormones; these are functionally and evolutionary related

hormones (Pierce and Parson, 1981). The elevated level of insulin stimulates the

granulosa cells to secrete FSH that results in ovarian steroidogenesis regulation and

growth of follicular cyst. As FSH plays important role in oogenesis and follicular

development, the increased FSH level leads to maturation of follicles (Simoni et al.,

1997; Sudo et al., 2002). Biochemical measurements of testosterone showed elevated

level of hormone in PCOS toward the upper limit than normal and cause

hyperandrogenism (Cho et al., 2008). The LH and FSH receptors mediate the function

in gonads, as these hormones are produced in a pulsatile manner by the anterior lobe

of pituitary gland (Dalkin et al., 2001; Ascoli et al., 2002; Dias et al., 2002). In

women the FSH stimulate estrogen production in ovaries and required for follicle

maturation (Mcgee and Hsueh, 2000). In females the LH stimulate the synthesis of

progesterone, ovulation and androgen in the theca cells (Moyle and Campbell, 1996).

Some studied have reported significant association of genetic variants with

infertility while others have not found any relationship. So far the evidence of an

association between PCOS and endometriosis with specific genetic polymorphism

giving consistent results in different populations is missing or very weak. Therefore,

large scale, well defined case control studies are required to validate these

associations in poly cystic ovary syndrome and endometriosis employing the

improved methodology for SNP detection.

In view of the important roles already identified for ESR1, ESR2, IL10, PGR,

and FSHR in endometriosis, we studied polymorphisms previously associated with

endometriosis at these loci to determine whether there is evidence for similar

35

associations in women from a previously unstudied distinct population. We are not

aware of any previous endometriosis association studies reported in Pakistani women;

here we identify conservation of these associations in this population. PCOS is one of

the major threats to women’s health that leads to anovulatory infertility, amenorrhoea,

hirsutism and oligomenorrhoea. No research evidence examining the role of genetic

polymorphisms in PCOS has been reported previously for Pakistani women. We

elucidate, for the first time in Pakistani women of the Punjab the putative functional

significance of different polymorphisms on the ADIPOQ, INSR, FSHR, FSHB,

LHCGR, LHB, ESR1 and ESR2 genes in the development of PCOS.

With this comprehensive database of information provided by the present

study about the reproductive endocrinology and genetics the possible association

between single nucleotide polymorphisms (SNPs) of genes related with PCOS and

endometriosis are likely to be identified. This will provide a starting point for

functional and biological studies to develop better diagnosis and treatment for these

debilitating diseases. There is no therapeutic treatment for the control of the

endometriosis and PCOS. The identification of genetic risk factors for female

reproductive disorders will be beneficial for the early prediction of the disease that

will potentially lead to the better diagnosis and treatment. The present project is

designed to evaluate the indigenous SNP database of genes and role of sex steroids

involved in reproductive disorders.

Aims and Objectives

The major aims and objectives of this research Project are:

1. To determine the genetic and endocrinological causes of female reproductive

disorders like endometriosis and PCOS.

2. To find the reasons of genetic disorder linked with gene SNPs for inflammation, sex

hormone regulation and steroid biosynthesis associated with endometriosis and

PCOS.

3. To compare the serum level of sex steroids and gonadotropins in diagnosed women

patients of the above mentioned syndromes with their controls.

36

CHAPTER 2

REVIEW OF LITERATURE

Infertility is a common public health problem in developing countries. The

pathogenesis of diseases is better understood due to genetic studies, this help to

improve our ability to treatment for patients (Simoni et al., 2008).

2.1 Endometriosis

Endometriosis is strongly linked with infertility, ovarian maturation, implantation and

fertilization affected by growth factors and alteration in the production of different

cytokines (Vassiliadis et al., 2005).The symptoms of endometriosis depends on the

localization of the implants, this includes dyspareunia, dysmenorrhea, dysuria,

dyschezia, chronic pelvic pain and infertility (Bulun et al., 2000; Missmer and

Cramer, 2003; Marques et al., 2004). Moreover, many inflammatory mediator

response factors and immunologic factors were investigated for their significant role

in the development and pathogenesis of endometriosis (Wu and Ho, 2003).

2.1.1 Estrogen receptor alpha (ESR1)

Endometriosis is a multifactorial and polygenic disease and associated with genetic

factors and complex interaction of cytokine activation, hormones and immuno-

inflammatory process (Vigano et al., 1998). A study on Japanese population observed

the association of ESR2 gene polymorphism with endometriosis while no association

with ESR1 SNPs (Wang et al., 2004).

Hsieh et al., (2007) elucidated the association of ESR1 -351 A/G and -397 T/C

polymorphisms of 112 women with endometriosis and 110 controls in Taiwan

population. ESR1 mutant related genotype revealed higher percentage in affected

women when compared with control. The genotype proportion AA/AG/GG of ESR1 -

351 was 26.8/57.1/16.1 in endometriosis women while 33.6/64.6/1.8 in control group.

The genotype proportion TT/TC/CC of ESR1 -397 was 24.1/60.7/15.2 in

endometriosis group and 54.5/40/5.5 in control group. They conclude that both

polymorphisms were correlated with the pathogenesis and susceptibility of

endometriosis.

37

A study on 214 Chinese women with endometriosis and 160 controls investigated no

significant association with the genotype frequency of PvuII, although the XbaI of

ESR1 showed distinct variations in allele and genotype frequency suggesting that this

SNP was associated significantly with endometriosis in studied Chinese population

(Xie et al., 2009). The data of association studies of ESR1 gene with endometriosis in

various populations is presented in Table 2.1.

38

Table 2.1: Summary of association studies between ESR1 gene polymorphisms (rs9340799 and rs2234693) and endometriosis.

a. rs9340799

Sr.

No

Population Endometriosis Control Endometriosis

(n)

Control

(n)

p Association Reference

Allele frequency

A Allele

n (%)

G Allele

n (%)

A Allele

n (%)

G Allele

n (%)

1 Japan 194 (79.5) 50 (20.5) 262 (76.6) 80 (23.4) 122 171 0.402 Negative Wang et al., 2004

2 Taiwan 124 (55.4) 100 (44.6) 145 (65.9) 75 (34.1) 112 110 0.005 Positive Hsieh et al., 2007

3 China 316 (73.83) 112 (26.17) 260 (81.25) 60 (18.75) 214 160 0.017 Positive Xie et al., 2009

b. rs2234693

Sr.

No


(n)

Control

(n)


Allele frequency

A Allele

n (%)

G Allele

n (%)

A Allele

n (%)

G Allele

n (%)


2 Taiwan 122 (54.5) 102 (45.5) 164 (74.5) 56 (25.5) 112 110 0.005 Positive Hsieh et al., 2007

3 China 246 (57.48) 182 (42.52) 204 (63.75) 116 (36.25) 214 160 0.083 Negative Xie et al., 2009

39

2.1.2 Estrogen receptor beta (ESR2)

The rs1042838 (G/A) polymorphism of ESR2 gene and its association with the risk of

endometriosis were investigated in Korean women. In this study 239 cases of

endometriosis and 287 controls were assessed by restriction fragment length

polymorphism analysis. The allele G and A frequency were not different in cases and

control group 87.4%, 12.6% vs. 85.5%, 14.5% respectively. This suggests that the

polymorphism was not associated with the pathogenesis of endometriosis in Korean

population (Lee et al., 2007).

In Brazilian women the genotype and allele frequencies showed significant difference

for rs1042838 at +1730 position, G/A polymorphism of ESR2 gene between

endometriosis and controls. The frequencies of genotypes AA, GA and GG of ESR2

gene was 1.9%, 47.2% and 50.9% in women with endometriosis while 1.4%, 24.3%

and 74.3% in controls respectively (Bianco et al., 2009). The inconsistency in results

may be due to different ethnic origin and genetic background. Genetic factors

involved in pathogenesis of disease varied in different populations.

The ESR2 +1730 G/A polymorphism were also investigated in a case control study on

another group of infertile Brazilian women. This study includes 201 women with

endometriosis and control group of 206 healthy women. A statistically significant (p =

0.003) difference was observed in endometriosis infertile women and control

regarding to the isolated frequencies of polymorphism (Christofolini et al., 2011). The

allele frequencies of ESR2 gene associated with endometriosis in different population

is given in Table 2.2.

40

Table 2.2: Summary of association studies between ESR2 (rs4986938) gene polymorphisms and endometriosis.

Sr.

No


(n)

Control

(n)


Allele frequency

G allele

n (%)

A allele

n (%)

G allele

n (%)

A allele

n (%)


2 Brazil 161 (74.5) 55 (25.5) 363 (86.4) 57 (13.6) 108 210 0.003 Positive Bianco et al., 2009

3 Brazil 216 (79.4) 56 (20.6) 368 (88.0) 50 (12.0) 136 209 0.003 Positive Zulli et al., 2010

41

2.1.3 Interleukin 10 (IL10)

The promoter region of IL10 gene spans 5 kb upstream from transcription start site,

both the promoter and coding region contain several polymorphisms (Lazarus et al.,

2002). The IL10 gene was recognized on chromosome 1q31-32 (Kim et al., 1992;

Opdal, 2004).

The associations of IL10 promoter polymorphisms with endometriosis have been

investigated in various populations. In Japanese population no significant difference

was examined in genotype and allele frequencies at position -592 (rs1800872) and -

1082 (rs1800896) in endometriosis and controls (Kitawaki et al., 2002). In addition

the frequency of haplotype GCC at rs1800872, rs1800871 and rs1800896 (-592 A>C,

-819 T>C and -1082 A>G) is about 50% in European females, 20% in African

females while lowest below 5% in Asian female (Meenagh et al., 2002). In contrast, a

significant association of endometriosis with A allele at -592 position of rs1800872 in

the promoter region of IL10 was investigated in Taiwanese population (Hsieh et al.,

2003).

A study on Chinese patients with endometriosis revealed the higher frequency of C

allele of rs1800872 and rs1800871 as compared to controls. No difference was

observed in allele frequency at position -1082 (rs1800896) (Zhang et al., 2007).

The genomic variants of IL10 gene in promoter region was studied in 214 women

with endometriosis and 160 controls in China. The variations in allele frequency was

observed at -592 and -819 regions of IL10 and seems associated with endometriosis

while the polymorphism at -1082 region was conserved with no difference in allele

frequency (Xie et al., 2009). The allele frequencies of various polymorphisms of IL10

gene associated women with endometriosis in various populations are shown in Table

2.3.

2.1.4 Progesterone receptor (PGR)

The progesterone receptor mediates the action of progesterone, encoded by

progesterone receptor gene (PGR) on chromosome 11q22-q23 consisting of seven

introns and eight exons (Gurates and Bulun, 2003).

42

Table 2.3: Summary of association studies between IL10 (rs1800896, rs1800871 and rs1800872) gene polymorphisms and endometriosis.

a. rs1800896

Sr.

No


(n)

Control

(n)


Allele frequency

A allele

n (%)

G allele

n (%)

A allele

n (%)

G allele

n (%)

1 Japan 310 (96.9) 10 (3.1) 379 (96.7) 13 (3.3) 160 196 0.885 Negative Kitawaki et al., 2002b

2 China 402 (93.2) 26 (6.0) 300 (93.7) 20 (6.2) 214 160 0.921 Negative Xie et al., 2009

3 Denmark 92 (46.0) 108 (54.0) 326 (45.5) 390 (54.5) 100 358 >0.050 Negative Riiskjaer et al., 2011

b. rs1800871

Sr.

No


(n)

Control

(n)


Allele frequency

T allele

n (%)

C allele

n (%)

T allele

n (%)

C allele

n (%)



43

Table Continued……

c. rs1800872

Sr.

No


(n)

Control

(n)


Allele frequency

A allele

n (%)

C allele

n (%)

A allele

n (%)

C allele

n (%)

1 Japan 214 (66.9) 106 (33.1) 233 (59.4) 159 (40.6) 160 196 0.041 Positive Kitawaki et al., 2002b



44

2.2 PCOS

The association of various genetic variants with PCOS was studied in different

ethnicities.

2.2.1 Adiponectin (ADIPOQ)

The association of PCOS and polymorphism in adiponectin gene was investigated in

several studies. In 2001, 2 independent groups identified that adiponectin effects the

insulin sensitivity (Berg et al., 2001; Yamauchi et al., 2001).

The Japanese population was examined for the association of rs2241766 (T45G)

polymorphism with increased risk of type 2 diabetes mellitus (Hara et al., 2002). A

significant association was investigated between T45G polymorphism with insulin

resistance and obesity in an Italian population (Menzaghi et al., 2002). PCOS being

metabolic syndrome show insulin resistance and type 2 diabetes mellitus (T2 DM); it

is suggested that the polymorphism of adiponectin gene was related with the

development of T2 DM (Filippi et al., 2004).

Conversely an association was observed between PCOS and adiponectin

polymorphism in various studies. Panidis et al., (2004) observed low frequency of T

allele and high frequency of G allele at T45G position of rs2241766 adiponectin gene

in Greek population of obese PCOS women; however this difference was not

statistically significant (p > 0.050).

Haap et al. (2005) investigated the adiponectin gene polymorphism with higher

frequency of T to G substitution at +45 position of rs2241766 in PCOS women as

compared to control. Studies provide the evidences that the polymorphism in

adiponectin gene in women with PCOS showed abnormalities in reproductive system

as well as high risk of T2 DM, obesity and cardio vascular disease (CVD) when

compared with normal control (Kadowaki and Yamauchi, 2005). The association of

ADIPOQ gene with PCOS in various populations is given in Table 2.4.

45

Table 2.4 (a): Summary of association studies between ADIPOQ (rs2241766) gene polymorphisms and PCOS.

Sr.

No

Population PCOS Control PCOS

(n)

Control

(n)


Allele frequency

T allele

n (%)

G allele

n (%)

T allele

n (%)

G allele

n (%)

1 Spain 54(37.5) 90(62.5) 28 (19.4) 56 (66.6) 72 42 0.004

Positive San Millan et al., 2004

2 Spain 53 (34.9) 99 (65.1) 29 (36.3) 51 (63.7) 76 40 0.201 Negative Escobar-Morreale et al., 2005

3 Finland 74(25.9) 212(74.1) 160 (32.9) 330 (67.3) 143 245 0.005

Positive Heinonen et al., 2005

4 Greece 73(36.5) 127(63.5) 103 (32.5) 177 (63.2) 100 140 0.061

Negative Xita et al., 2005

5 Spain 53(34.9 99(65.1) 29 (19.08) 51 (63.7) 76 40 0.050

Positive Escobar-Morreale et al., 2006

6 China 82(34.2) 158(65.8) 108 (45.0) 132 (55.0) 120 120 0.050

Positive Zhang et al.,2008

7 Korea 93 (32.3) 195 (67.7) 135 (42.5) 183 (57.5) 144 159 0.010

Positive Li et al., 2011

8 Iran 101(27.9) 261(72.1) 101(27.9) 261(72.1) 181 181 0.52

Negative Ranjzad et al., 2012

46

Table 2.4 (b): Summary of association studies between ADIPOQ (rs1501299) gene polymorphisms and PCOS.

Sr.

No


(n)

Control

(n)


Allele frequency

T allele

n (%)

G allele

n (%)

T allele

n (%)

G allele

n (%)

1 Greece 217 (82.2) 47 (17.8) 179 (89.5) 21 (10.5) 132 100 0.050 Positive Panidis et al., 2004

2 Spain 118 (81.9) 26 (18.0) 70 (83.3) 14 (16.6) 72 42 0.005 Positive San Millan et al., 2004

3 Germany 84 (79.2) 22 (20.7) 940 (86.7) 144 (13.2) 53 542 0.005 Positive Haap et al., 2005

4 Finland 267 (93.3) 19 (6.6) 466 (95.1) 24 (4.9) 143 245 0.402 Negative Heinonen et al., 2005

5 Greece 177 (88.5) 23 (11.5) 242 (86.4) 38 (13.5) 100 140 0.004 Positive Xita et al., 2005

6 Spain 130 (85.5) 22 (14.5) 65 (81.3) 15 (18.8) 76 40 0.201 Negative Escobar-Morreale et al., 2005

7 Finnish 267(93.4) 19(6.6) 466(95.1) 24(4.8) 143 245 0.601 Negative Heinonen et al., 2005

8 Spain 130 (85.5) 22 (14.4) 65 (81.2) 15 (18.7) 76 40 0.004 Positive Escobar-Morreale et al., 2006

9 China 168 (70.0) 72 (30.0) 190 (79.1) 50 (20.8) 120 120 0.020 Positive Zhang et al., 2008

10 Turkey 160 (83.3) 32 (16.6) 164 (88.1) 22 (11.8) 96 93 0.004 Positive Demirci et al., 2010

11 Korea 217 (75.3) 71 (24.7) 228 (71.7) 90 (28.3) 144 159 0.350 Negative Li et al., 2011

12 Iran 296(81.8) 66(18.2) 322(88.9) 40(11.1) 181 181 0.005 Positive Ranjzad et al., 2012

47

In Finnish population no difference was reported in genotype and allele frequencies of

rs2241766 ADIPOQ gene variants between PCOS and control group (Heinonen et al.,

2005). A study conducted on Greek population had detected no difference in genotype

frequencies and association with the development of PCOS (Xita et al., 2005). A

study on women of Spain confirmed the same findings with no association of PCOS

and rs2241766 polymorphism when compared with their control (San Millian et al.,

2004; Escobar-Morreale et al., 2006). An association was observed between SNPs of

adiponectin gene rs2241766 and rs1501299 in Han Chinese PCOS women than

controls (Zhang et al., 2008).

2.2.2 Insulin receptor (INSR)

Insulin receptor gene consists of 22 exons (Seino et al., 1990). Insulin resistance and

hyperinsulinemia was observed in PCOS women with polymorphisms in the region of

exon 17-21 of INSR gene. This region codes for tyrosine kinase residue of the

receptor necessary for insulin transduction pathway (Krook et al., 1994). The patients

with PCOS were examined with several polymorphisms in exons and introns of INSR

gene (Siegel et al., 2002).

The evidences showed that the susceptible loci for PCOS are present in the INSR gene

at chromosome 19 suggested that it might be the susceptible region for disease (Tucci

et al., 2001). According to Azziz, insulin receptor has post binding defect in

signalling pathway that considered as one of the major contributor in pathogenesis of

PCOS (Azziz, 2002). The polymorphisms in INSR gene bring mild change in function

of the gene which may contribute in the development of PCOS (Siegel et al., 2002).

Insulin resistance has metabolic consequences and play important role in development

and pathogenesis of PCOS (Azziz, 2002; Ehrmann, 2005).

48

Table 2.5: Summary of association studies between INSR (rs1799817 and rs2059806) gene polymorphisms and PCOS.

(a) rs1799817

Sr.

No


(n)

Control

(n)


Allele frequency

T allele

n (%)

C allele

n (%)

T allele

n (%)

C allele

n (%)

1 Korea 130(37.4) 218(62.6) 75(40.3) 111(59.6) 174 93 >0.050 Negative Lee et al., 2007

2 Korea 79(29.9) 185(70.0) 68(34) 132(66.0) 132 100 >0.050 Negative Lee et al., 2008

3 India 125(34.7) 235(65.2) 80(27.7) 208(72.2) 144 180 >0.050 Negative Mukherjee et al., 2009

4 Turkey 66 (75.0) 22 (25.0) 71 (71.0) 29 (29.0) 44 50 0.538 Negative Unsal et al., 2009

5 Iran 88 (24.3) 274 (75.7) 79 (21.8) 283 (78.2) 181 181 0.427 Negative Ranjzad et al., 2012

(b) rs2059806

1

Iran 265 (73.2) 97 (26.8) 256 (70.7) 106 (29.3) 181 181 0.456 Negative Ranjzad et al., 2012

49

PCOS being metabolic syndrome is also called as insulin resistant disease (Rotterdam,

2004; Legro et al., 2004).

Insulin resistance has an important role in the pathogenesis and metabolic

consequences of PCOS (Azziz, 2002; Legro et al., 2004; Ehrmann, 2005). Legro et al,

(2004) described that 50-70% of PCOS women exhibits insulin resistance and insulin

insensitivity that leads toward the hyperandrogenism; a major contributor of PCOS

symptoms and sign.

2.2.3 Follicle stimulating hormone receptor (FSHR)

FSH is a pituitary glycoprotein responsible for folliculogenesis by activating the

maturation of follicles; this cause granulosa cells to proliferate and trigger the

synthesis of aromatase which is an androgen converting enzyme (Gharib et al., 1990;

Moyle and Campbell, 1996). The FSH receptor (FSHR) which belongs to G-protein

coupled receptor mediates the action of FSH signal transduction (Segaloff and Ascoli,

1993). The first inactivated mutation in FSHR gene with ovarian failure was observed

in some Finnish women (Aittomaki et al., 1995). The substitution of A to G of rs6165

polymorphism causes change of threonine (ACT) codon to alanine (GCT) at 307

coding position of protein. The replacement of G with A of rs6166 SNP at coding

position 680 leads to change of amino acid serine (AGT) codon to asparagine (AAT)

(Aittomaki et al., 1995).

The worldwide screening of patients and control in different ethnicities for FSHR

gene explore two non-synonymous SNPs in exon 10. These SNPs in the coding region

had been identified for frequency of >30% in the normal population. The rs6165 at

position 919 showed substitution of A to G changing the amino acid threonine to

alanine. Whereas the rs6166 at position 2039 replaced G with A, this change the

amino acid sequence from serine to asparagine (Aittomaki et al., 1995).

The two polymorphisms N680S and A307T of FSHR gene in exon 10 were in linkage

disequilibrium. The polymorphism A307T of FSHR gene is located in the high

affinity binding site of FSH hormone in extracellular domain of (Davis et al., 1995).

This site affects the signal transduction and hormone trafficking (Hipkin et al., 1995).

The FSHR gene consist of 10 exons in which the largest one encodes for intracellular

domain while the remaining nine smaller encodes for extracellular domain (Simoni et

al., 1997).

50

In a study of Japanese PCOS women a significant increase was observed in the

Ala307Thr frequency with 66.7% compared with 43.5% in normal ovulating women

(Sudo et al., 2002).

The alteration in the amino acid affects the function of receptors of FSHR protein at

post-translational modifications (de Castro et al., 2004). The genetic association

between women with PCOS and FSHR gene polymorphisms has been studied

previously (Tong et al., 2001; Orio et al., 2006)

The candidate genes involved in insulin metabolism, gonadotropin secretions,

steroidogenesis and inflammation were studied in the previous years. The

susceptibility genes for PCOS have been explored and identified in women of Spain

(Escobar-Morreale et al., 2005). However the results of various studies were so far

inadequate (Diamanti- Kandarakis et al., 2006).

The existence of association of Ala307Thr polymorphism with PCOS was not

confirmed in Turkish women (Unsal et al., 2009) and in women with Caucasian

origin (Valkenburg et al., 2009). However a study on Chinese women reported

significant association of Ala307Thr polymorphism of FSHR gene with PCOS (du et

al., 2010). The associations of PCOS and polymorphisms of FSHR gene have been

studied extensively in various ethnicities (de Koning et al., 2006; Jun et al., 2006;

Simoni et al., 2008; Achrekar et al., 2009; Livshyts et al., 2009; Overbeek et al.,

2009; Valkenburg et al., 2009; Du et al., 2010; Gu et al., 2010; Kuijper et al., 2010;

Rendina et al., 2010), however the consistency of these findings are not without

contradictions.

Previous genetic studies revealed that the genes involved in the hormone metabolism

and energy regulation, such as INSR, LH and CYP19 play important role in

pathogenesis of PCOS (Rajkhowa et al., 1995; Kahsar-Miller et al., 2004; Witchel et

al., 2005; Unsal et al., 2009).

Mohiyiddeen and Nardo (2010) reviewed 15 studies and examine the polymorphism

of FSHR gene; this review suggest that the homozygous serine variant was associated

with higher FSH level in all ovulatory patients but three studies did not showed

consistent results with these findings (Falconer et al., 2005; Klinkert et al., 2006;

Loutradis et al., 2006). More recent studies could not confirm the association of

homozygous serine variant with the FSH concentration at follicular phase as was

51

Table 2.6: Summary of association studies between FSHR (rs6165) gene polymorphisms and PCOS.

Sr.

No


(n)

Control

(n)


Allele frequency

A allele

n (%)

G allele

n (%)

A allele

n (%)

G allele

n (%)

1 UK 92 (49.5) 94 (50.5) 41 (40.2) 61 (59.8) 93 51 >0.050 Negative Conway et al., 1999

2 Singapore 162 (65.3) 86 (34.7) 314 (66.5) 158 (33.5) 124 236 >0.050 Negative Tong et al.., 2001

3 Japan 18 (50.0) 18 (50.0) 219 (65.2) 117 (34.8) 18 168 >0.050 Negative Sudo et al., 2002

4 Italian 43 (43.0) 57 (57.0) 43 (43.0) 57 (57.0) 50 50 >0.050 Negative Orio et al., 2006

5 Caucasian 496 (50.1) 494 (49.9) 3064 (50.0) 3060 (50.0) 495 3062 >0.050 Negative Valkenburg et al., 2009

6 Turkey 51 (58.0) 37 (42.0) 57 (57.0) 43 (43.0) 44 50 >0.050 Negative Unsal et al., 2009

7 China 72 (65.5) 38 (34.5) 117 (63.6) 67 (36.4) 55 92 0.007 Positive Du et al., 2010

8 China 228(29.7) 540(70.3) 483(31.4) 1053(68.8) 384 768 0.390 Negative Fu et al., 2013

52

Table 2.7: Summary of association studies between FSHR (rs6166) gene polymorphisms and PCOS.

Sr.

No


(n)

Control

(n)


Allele frequency

A allele

n (%)

G allele

n (%)

A allele

n (%)

G allele

n (%)

1 UK 92 (49.5) 94 (50.5) 41 (40.2) 61 (59.8) 93 51 >0.050 Negative Conway et al., 1999

2 Singapore 162 (65.3) 86 (34.7) 314 (66.5) 158 (33.5) 124 236 >0.050 Negative Tong et al.., 2001

3 Japan 18 (50.0) 18 (50.0) 219 (65.2) 117 (34.8) 18 168 >0.050 Negative Sudo et al., 2002

4 Italian 43 (43.0) 57 (57.0) 43 (43.0) 57 (57.0) 50 50 >0.050 Negative Orio et al., 2006

5 Caucasian 496 (50.1) 494 (49.9) 3064 (50.0) 3060 (50.0) 495 3062 >0.050 Negative Valkenburg et al., 2009

6 Turkey 51 (58.0) 37 (42.0) 57 (57.0) 43 (43.0) 44 50 >0.050 Negative Unsal et al., 2009

7 China 72 (65.5) 38 (34.5) 117 (63.6) 67 (36.4) 55 92 0.007 Positive Du et al., 2010

8 China 228(29.7) 540(70.3) 483(31.4) 1053(68.8) 384 768 0.390 Negative Fu et al., 2013

53

observed previously (Kuijper et al., 2010; Genro et al., 2012; Mohiyiddeen et al.,

2012).

2.2.4 Follicle stimulating hormone beta (FSHB)

The non-coding region of FSHB gene comprises less number of polymorphism but

consider as highly frequent alleles in human. However the variants of this gene are in

strong linkage disequilibrium (Simoni et al., 2008).


Both ESR1 and ESR2 genes were involved in the physiological action on estrogen

production in the ovary (Byers et al., 1997; Drummond et al., 1999). The alternation

in the expression of ESR1 and ESR2 genes may cause anomalous development of

follicles (Jakimiuk et al., 2002).

Estrogen play substantial role in the function and development of reproductive

system. The estrogen action is mediated by two specific receptors, the ESR1 and

ESR2 which belongs to nuclear receptor family. Both ESR1 and ESR2 are required for

the proper function of hypothalamus pituitary ovarian axis. Estrogen acts on the

ESR1 to regulate the cyclic process of gonadotropin release in the hypothalamic

pituitary axis (Hillisch et al., 2004), and enhance the process of folliculogenesis and

ovulation by its action on ESR2 in the ovary (Hegele-Hartung et al., 2004). The ESR1

gene found on chromosome 6q25.1and consists of 1 intron and 8 exons spanning 140

Kb, contains two SNPs r2234693 and rs9340799 (Ale´ssio et al., 2007).

Kim et al, (2010) in Korean population observed significant difference in allele and

genotype frequencies between women with PCOS and controls. The “A” allele was

significantly different with 11.7% in PCOS and 19.1% in control. The study

concludes that the ESR2 polymorphism was significantly associated with the

pathogenesis of PCOS (Kim et al., 2010).

A study conducted on Greece population showed the association of rs9340799

polymorphism of ESR1 gene with FSH level in PCOS women. The association of

allele A was observed with low serum FSH level indicates the contribution of this

genomic variant with reduced development of follicles (Nectaria et al., 2012).

54


ESR2 gene spans approximately 62 Kb, consists of 9 exons and resides on

chromosome 14q23.1 (Pettersson and Gustafsson, 2001).

2.2.7 Luteinizing hormone choriogonadotropin receptor (LHCGR)

LHR mediate the effect of LH and this is expressed in granulosa and theca cells

(Balen, 1993). LHCGR belongs to G-protein receptor located on 2p16.3 chromosome

(Atger et al., 1995). A single non synonymous mutation at G1052A of LHβ replaces

amino acid glycine with serine in exon 3 (Tapanainen et al., 1999). The LHR gene

comprises of 10 introns and 11 exons (Ascoli et al., 2002). The anomalous signalling

of LH is believed to enhance the production of ovarian androgen in women with

PCOS and leads toward anovulation (Norman et al., 2007).

The LHCGR is expressed in various tissues including testis, ovaries and some non-

gonadal tissues (Rahman and Rao, 2009). In Han Chinese PCOS women the two

susceptible loci were identified at 9q33.3 and 2p21 encoding for LHCGR and FSHR

gene respectively in a genome wide association study (Chen et al., 2011). The

LHCGR gene comprises a receptor for chorionic gonadotropin (HCG) and luteinizing

hormone (LH) and mutations in these receptors were related with infertility (Yariz et

al., 2011).

Studies have investigated that the mutations in LHR and LHβ gene may alter the

function or structure of LHR and LH, either inactivating or activating their bioactivity.

The mutations in LHR cause amenorrhea, anovulation, infertility and PCOS in women

(Themmen and Huhtaniemi, 2000; Themmen, 2005; Huhtaniemi and Themmen,

2005; Huhtaniemi and Alevizaki, 2006).

2.2.8 Luteinizing hormone beta (LHβ)

The convincing evidences suggest the LHR and LHB gene as the genetic determinant

of PCOS. Whereas, the studies on different populations showed inconsistent results

with polymorphisms of this gene. The mutations in LHβ gene Trp8Arg and Ile15Thr

polymorphisms were associated with the PCOS women of Japan and UK whereas the

low frequency of mutations was observed in North European obese PCOS women

(Rajkhowa et al., 1995; Suganuma et al., 1995; Tapanainen et al., 1999). A study on

Singapore Chinese women speculated that G1052A mutation of LHβ gene affect the

function of gonads and this polymorphism was related with menstrual disorder. The A

55

allele (4%) was present only in women with menstrual irregularities and absent in

controls (Ramanujam et al., 1999). Kim et al. (2001) found no homozygous

polymorphic variant at G1052A of LHβ in 108 Korean women with PCOS. The

secretion of androgens was mediated by LH in theca cells of ovaries and help in

follicles maturation (Laven et al., 2002). The LHR was over-expressed in theca and

granulosa cells of women with PCOS (Jakimiuk et al., 2001).

These findings suggest that different regional and ethnical groups may express

different genotypes of G1052A polymorphism of LHβ. A genome-wide association

study on Han Chinese women with PCOS investigated significant association with

LHR gene polymorphisms (Chen et al., 2011).

A study conducted on Chinese women showed that the frequency of heterozygous and

homozygous variants were 3.2% (10/315) and 1.0% (3/315) respectively at G1052A

polymorphism of LHβ in PCOS. In contrast no polymorphism (0/212) was observed

at G1052A of LHβ gene in control. The mutant allele A of LHβ gene was significantly

associated (p = 0.001) with PCOS (Liu et al., 2012).

In PCOS women the LHR is expressed in theca cells, the LHR function is altered by

multiple polymorphisms in the LH receptor (Jakimiuk et al., 2001). LHR stimulates

the ovarian theca cells to secrete androgens which consequently arrest follicular

maturation (Laven et al., 2002). The PCOS women have normal limits of FSH level

(Laven et al., 2002).

56

CHAPTER 3

MATERIALS AND METHODS

3.1 Sampling size and study design

This research has been approved by the research ethics Committee Board of Advance

Studies and Research (BASR) of Government College University Lahore as well as

from infertility clinics of obstetrics/gynecology teaching hospitals. This was a Case

control analytical study and the sample size was calculated by the following formula

(Lwanga and Lemeshow, 1991).

n = z2

α/2 π (1- π)/e2

3.2 Subjects

The diagnosed female subjects with known infertility (endometriosis and PCOS) were

recruited from the outpatient’s infertility clinics of Gynecology /Obstetrics wards of

tertiary hospitals (Sir Ganga Ram hospital Lahore and Lady Willington hospital

Lahore). The women were referred from clinics, hospitals and physicians from all

over the Punjab province. The written informed consent on a prescribed performa was

obtained from all subjects (Annexure I). The anthropometric data of all the subjects

were collected and every individual was assessed after registering their medical

history on specially designed subject data sheets (Annexure II) (Sue et al., 2007). The

healthy Pakistani women from the Punjab with regular menses and history of

spontaneous conception volunteered as controls.

3.3 Sample selection

There were separate cases for endometriosis and PCOS.

Ninety-six (96) Pakistani women with PCOS.

Fifty-two (52) Pakistani women with endometriosis.

One hundred forty eight (148) healthy Pakistani women as control.

3.3.1 Inclusion criteria:

Age 20 to 40 years.

Females married for at least 1 year.

57

The diagnosed cases of PCOS according to Rotterdam ESHRE/ASRM-

Sponsored PCOS Consensus Workshop Group, 2004 (Rotterdam, 2004).

Therefore, diagnostic criteria included women who displayed two of the

following three criteria: clinical and/or biochemical signs of

hyperandrogenism, oligo- or anovulation and polycystic ovary morphology.

The patients of endometriosis were diagnosed clinically (e.g. pelvic pain,

dysmenorrhea and infertility).

The reproductively active age group was taken.

3.3.2 Exclusion criteria:

Known causes of congenital adrenal hyperplasia, hyperandrogenism, Cushing

syndrome, hyperprolactinemias, adrenal tumor and virilizing ovarian tumor

were excluded.

Hyperthyroidism, Pregnancy, Smoking, Hypertension.

Intake of any medications including hormonal treatment in last 1 year.

Use of anti-obesity drugs, anti-diabetic, glucocorticoids.

Any neoplastic, metabolic, Cardiovascular, or other relevant medical illness.

Inflammatory conditions of pelvis and abdomen.

On treatment of infertility i.e. IVF.

Laparotomy/laparoscopy.

3.3.3 Selection of controls

Females of age 20 to 40 year married for more than 1 year.

BMI matched healthy controls with regular menstruation.

No symptoms of hyperandrogenism, e.g. hirsutism, Virilism.

History of spontaneous conception.

Had not taken any hormonal contraception.

Agreeable to participate in the study.

58

Figure 3.1 Diagrammatic and schematic presentation of research layout.

Blood Sampling

(Cases=150, Control= 150

DNA extraction

AGTGTGGC

ATGCYAGC

AGGACAGA

SNP selection

Primer designing

PCR

Amplification

PCR product

Purification

Gel Electrophoresis

PCR product

Sequencing

analysis

Sequence

chromatogram

Sampling

Anthropometric

data (n=500)

Age, Family history, weight, height,

waist and hip ratio, physical

examination, pelvic ultrasonography,

patient’s medical, gynecological and

surgical history

Data Tabulation and

Statistical Analysis

Sequence reading in Chromas

program, Data analysis by Chi

square test & HAPLO program

Serum

Hormonal Analysis

FSH, Testosterone,

Progesterone

http://www.google.com.pk/imgres?imgurl=http://images.wisegeek.com/blood-sample.jpg&imgrefurl=http://www.wisegeek.com/what-is-an-edta-anticoagulant.htm&h=800&w=740&tbnid=ZkWgHgS9TyKMxM:&zoom=1&docid=DmBf4chINeutIM&hl=en&ei=L05uU4CODIeX1AW-q4CQAQ&tbm=isch&ved=0CLMBEDMoWTBZ&iact=rc&uact=3&dur=1198&page=7&start=87&ndsp=16

59

3.4 Physical examination

3.4.1 Determination of weight, height and Body Mass Index

The standing height of each subject was measured using a portable Standiometer,

whereas weight was determined with a digital weight scale nearest to 0.1 cm. The

Body Mass Index (BMI) of every subject was calculated by using the equation

demonstrated by Cole et al. (1997):

BMI = Weight in kilogram / (Height in meter) 2

3.4.2 Physical examinations and interviews

All participants completed a structured questionnaire covering family history,

education level, weight and height, waist and hip ratio (WHR), patient’s medical,

gynecological and surgical history. Complete physical examination and pelvic

ultrasonography was conducted. All the eligible controls were matched on the bases

of age, residential area and were genetically unrelated to minimize possible selection

bias. Hence all subjects had the same similar socioeconomic status and ethnicity. All

subjects were recruited by gynecologists after reviewing patient’s medical records to

meet with eligibility criteria.

3.5 Blood sampling and Storage

The blood samples (5-10ml) were drawn from each patient and were stored at 4 oC

after dividing into sub-samples until further process for genetic and hormonal

analysis. The sub-samples of blood for molecular genetic studies were collected in

tubes containing ethylenediaminetetraacetic acid (EDTA) as an anticoagulant.

Whereas the blood samples for serum separation were collected in gel coated tubes.

The serum was stored at -80 oC for further analysis. All the collected blood samples

were transported to laboratory on ice.

60

3.6 Genotyping and DNA sequencing

3.6.1 Genomic DNA extraction

Genomic DNA of all subjects including endometriosis, PCOS and healthy controls

were extracted from the blood using a modified standard extraction method

(Sambrook et al., 1989). (The recipe of solutions prepared for DNA extraction was

presented in Annexure III).

The protocol followed for genomic DNA isolation consists of following steps.

1) In 500 µl of blood 500-700 µl of Tris-EDTA (TE) buffer was added, mixed the

buffer by inverting tubes ups and down several times. The tubes were left at room

temperature for 10-15 min.

2) Centrifugation was performed at 25 oC with 13500 rpm for 5-10 min.

3) Supernatant was discarded leaving the white blood cells (WBCs) pellet at the

bottom of 1.5 ml eppendorf. The pellet was broken by gentle tapping and vortexing.

After adding 1 ml of TE buffer the step 2 was repeated until the WBCs pellet became

clear or light pink.

4) The broken clear pellet was dissolved into 375 µl of 3M sodium acetate, 25 µl of

10% sodium dodecyl sulphate (SDS) and 10 µl of proteinase K (10 µg/µl) and

incubated at 37 oC overnight in a shaking water bath.

5) One volume of chilled chloroform: isoamyl alcohol (24:1) was added into three

volumes of digested pellet, mixed by gently inverting eppendorfs ups and down until

a milky emulsion was formed and centrifuged at 25 oC with 13500 rpm for 5-10 min.

6) Three layers can be visualized after centrifugation. The upper layer contains DNA,

the lower layer chloroform: isoamyl alcohol and the middle whitish layer proteins.

The DNA layer was carefully transferred into a new labeled eppendorf avoiding

contamination from other layers, mixed with equal volume of chilled absolute ethanol

by gently inverting eppendorfs ups and down until DNA threads became visible, left

at room temperature for 10 min and centrifuged at 25 oC with 13500 rpm for 5-10

min.

7) Supernatant was discarded and the DNA pellet was washed with 500-1000 µl

chilled 70% ethanol by centrifuging at 25o C with 13500 rpm for 5-10 min.

8) Ethanol was discarded and the DNA pellet was dried by air keeping eppendorfs

open inside the laminar air flow at room temperature for 15-30 min.

61

9) The dried DNA pellet was dissolved into 30-50 µl low TE buffer, incubated in a

shaking water bath at 70 oC for 30 min, cooled at room temperature and spinned by

brief centrifugation.

10) DNA was stored in duplicate at -20oC and -80

oC after assessing its quality and

quantity by nanodrop (Thremoscientific, Nanodrop 2000) and gel electrophoresis.

11) All the DNA samples (endometriosis, PCOS and control) were extracted in

duplicate to avoid the mishandling waste and troubleshooting with optimization.

3.6.2 Candidate Genes

Various candidate genes were selected from three metabolic pathways that have been

implicated in the etiology of endometriosis and PCOS (Table 3.1, 3.2). These genes

map to distinct chromosomal locations. The common variants in these regions,

1q32.1, 6q25.1, 11q22.1, 2p21, 3q27.3, 6q25.1, 11p14.1, 15q21.2, 19q13.2, and

19p13.33 were analyzed. The single nucleotide polymorphisms (SNPs) of ESR1,

ESR2, PGR, IL10, FSHR, FSHB, LHCGR, LHB, ADIPOQ and INSR genes were

selected (Table 3.1, 3.2). The NCBI reference sequence assembly was used for

chromosome position, gene ID and gene symbol GRCh37.p5 along with build 37.3.

Nomenclature guidelines suggested by the Human Genome Variation Society

(HGVS) was followed, the coding reference position of the relevant DNA used along

with the Ensemble accession file is shown in Table 3.1 and 3.2.

3.6.3 Single nucleotide polymorphism (SNPs) selection

All SNPs were selected for their functional relevance to PCOS and endometriosis

after searching databases of “University of California, Santa Cruz” (UCSC)

(https://genome.ucsc.edu/), “National center for biotechnology information” (NCBI)

(http://www.ncbi.nlm.nih.gov) and prior publications. The SNPs were searched using

the NCBI website (http://www.ncbi.nlm.nih.gov/snp/). The search for endometriosis

susceptible SNPs has been focused on genes encoding inflammatory mediators, sex

hormones, enzymes involved in metabolism and steroid biosynthesis. The susceptible

and candidate genes for PCOS involved in insulin sensitivity, steroid biosynthesis,

detoxification and sex hormone regulation were selected.

https://genome.ucsc.edu/

http://www.ncbi.nlm.nih.gov/

http://www.ncbi.nlm.nih.gov/snp/

66

Table 3.1: Genotyping panel for endometriosis candidate genes.

Marker locus Candidate

genes

Gene

symbol

Gene

ID

Ensemble accession *SNP ID *Chr Genomic

position

Coding DNA

reference

position

Gene

mode

Protein

position

Residue

change

Sex Steroid

hormone

Estrogen receptor α ESR1 2099 ENST00000440973 rs2234693 6q25.1 g.152163335 c.453-397T>C Intron

rs8179176 g.152163334 c.453-398C>T Intron

rs9340799 g.1521633381 c.453-351A>G Intron

Estrogen receptor β ESR2 2100 ENST00000557772 rs4986938 14q23.2 g.64699816 c.1859G>A UTR-3

Progesterone

receptor

PGR 5241 ENST00000325455 rs10895068 11q22.1 g.101000214 c.-413G>A UTR-5

rs1042838 g.100933412 c.1978G>T missense 660 Val-Leu

Inflammatory

mediators

Interleukin 10 IL10 3586 ENSG00000136634 rs1800872 1q32.1 g.206946407 c. -592 A>C UTR-5

rs1800871 g.206946634 c.-819C>T UTR-5

rs1800894 g.206946666 c.886G>A UTR-5

rs1800896 g.206946897 c.-1082A>G UTR-5

Gonadotropin

action

Follicle-stimulating

hormone receptor

FSHR 2492 ENST00000406846 rs6166 2p16.3 g.49189921 c.2039G>A missense 680 Ser-Asn

rs6165 g.49191041 c.919G>A missense 307 Ala-Thr

Assembly used for chromosome position, gene ID and gene symbol is GRCh37.p5 along build 37.3

SNP: Single nucleotide polymorphism; * Chr: Chromosome

67

Table 3.2: Genotyping panel for PCOS candidate genes.

Assembly used for chromosome position, gene ID and gene symbol is GRCh37.p5 along build 37.3; * Chr: Chromosome; SNP: Single nucleotide polymorphism

Marker locus Candidate gene Gene

symbol

Gene

ID

Ensemble accession SNP ID *Chr Genomic

position

Coding DNA

reference

position

Gene

mode

Protein

position

Residue

change

Steroid

hormone

Estrogen receptor α ESR1 2099 ENST00000440973 rs2234693 6q25.1 g.152163335 c.453-397T>C Intron

rs8179176 g.152163334 c.453-398C>T Intron

rs9340799 g.1521633381 c.453-351A>G Intron

Estrogen receptor β ESR2 2100 ENST00000557772 rs4986938 14q23.2 g.64699816 c.1859G>A UTR-3

Gonadotropin

action


hormone beta

FSHB 2488 ENST00000417547 rs6169 11p14.1 g.30255185 c.228C>T cds-Synon 76 Tyr-Tyr


hormone receptor

FSHR 2492 ENST00000406846 rs6166 2p16.3 g.49189921 c.2039G>A missense 680 Ser-Asn

rs6165 g.49191041 c.919G>A missense 307 Ala-Thr

Luteinizing

hormone

LHCGR 3973 ENST00000294954 rs61996318 2p21 g.48941162 c.568C>A missense 190 Gln-Lys

choriogonadotropin

receptor

rs111834744 g.48941073 c.605+52delT intron

Luteinizing

hormone beta

LHB 3972 ENST00000221421 rs1800447 19q13.33 g.49519905 c.82T>C missense 28 Trp-Arg

rs4002462 g.49519997 c.16-26T>C intron

Insulin action Adiponectin ADIPOQ 9370 ENST00000412955 rs2241766 3q27.3 g.186570892 c.45T>G intron

rs1501299 g.186571123 c.214+62G>T missense 190 Gln-Lys

rs2241767 g.186571196 c.214+135A>G intron

Insulin receptor INSR 3643 ENST00000341500 rs1799817 19p13.2 g.7125297 c.3219C>T cds-Synon 1085 HiS-His

rs1799815 g.7125519 c.2997C>T cds-Synon 1011 Tyr-Tyr

rs2059806 g.7166376 c.1650G>A cds-Synon 550 Ala-Ala

rs2229429 g.7166388 c.1638C>T missense 546 Asp-Glu

http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?type=rs&rs=rs111834744

http://www.ncbi.nlm.nih.gov/SNP/snp_ref.cgi?type=rs&rs=rs4002462

68

Table 3.3: Primers, PCR program, annealing temperatures and PCR nucleotide product size of endometriosis polymorphisms.

Gene

ID

*SNPs ID Primer sequence Annealing

temperature

(◦C)

PCR Program

(35 cycles)

Product size

(*bp)

ESR1

(2099)

rs2234693 F: CTGCCACCCTATCTGTATC

R: ACCCTGGCGTCGATTATCT

53 ⁰C 95⁰C 15min, 95⁰C 45 Sec

53⁰C 45 Sec, 72⁰C 1 min

1366



53 ⁰C 95⁰C 15min, 95⁰C 45 Sec

53⁰C 45 Sec, 72⁰C 1 min

1366

ESR2

(2100)

rs4986938 F: CGGCAGAGGACAGTAAAAGC

R: TGAGAGTTGGGAAGGTGGAG

58 ⁰C 95⁰C 15min, 94⁰C 45 Sec

58⁰C 45 Sec, 72⁰C 45 Sec

213

IL10

(3586)

rs1800872 F: GGACAGCTGAAGAGGTGGAA

R: GAGGGGGTGGGCTAAATATC

60 ⁰C 95⁰C 15min, 94⁰C 45 Sec

60⁰C 45 Sec, 72⁰C 1 min

166

rs1800871

F: TCATTCTATGTGCTGGAGATGG

R: TGGGGGAAGTGGGTAAGAGT

60 ⁰C 95⁰C 15min, 94⁰C 45 Sec

60⁰C 45 Sec, 72⁰C 45 Sec

208

rs1800896

F: TTCCCCAGGTAGAGCAACAC

R: GATGGGGTGGAAGAAGTTGA

56 ⁰C 95⁰C 15min, 94⁰C 45 Sec

56⁰C 45 Sec, 72⁰C 45 Sec

238

PGR

(5241)

rs10895068 F: GTACGGAGCCAGCAGAAGTC

R: GAGGACTGGAGACGCAGAGT

56 ⁰C 95⁰C 15min, 94⁰C 45 Sec

56⁰C 45 Sec, 72⁰C 1 min

220

rs1042838 F: TTCGAAACTTACATATTGATGACCA

R: CACTTAAAATAACAAAAACAACAAAAG

56 ⁰C 95⁰C 15min, 94⁰C 45 Sec

56⁰C 45 Sec, 72⁰C 45 Sec

180

http://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=1800871




69

Table continues……………..

FSHR

(2492)

rs6166 F: GCAAGTGTGGCTGCTATGAA

R: GTGACATACCCTTCAAAGGC

55 ⁰C 95⁰C 15min, 95⁰C 1min

55⁰C 1 min, 72⁰C 1 min

231

rs6165 F: CCTGCACAAAGACAGTGATG

R: TGGCAAAGACAGTGAAAAAG

55 ⁰C 95⁰C 15min, 95⁰C 1min

55⁰C 1 min, 72⁰C 1 min

577

*SNP: Single nucleotide polymorphism

F: Forward; R: Reverse

*bp: base pair

70

Table 3.4: Primer, annealing temperature, PCR program and product size of PCOS polymorphisms.

Gene

ID

*SNPs ID Primer sequence Annealing

temperature

(◦C)

PCR Program

(35 cycles)

Product

size

(*bp)

ADIPOQ

(9370)

rs2241766 F:GAAGTAGACTCTGCTGAGATGG

R:TATCAGTGTAGGAGGTCTGTGATG

56 ⁰C 95⁰C 15min, 93⁰C 45 Sec

56⁰C 30 Sec, 72⁰C 45 Sec

372

rs1501299

F: CCTGGTGAGAAGGGTGAGAA

R: AGATGCAGCAAAGCCAAAGT

56 ⁰C 95⁰C 15min, 93⁰C 45 Sec

56⁰C 30 Sec, 72⁰C 45 Sec

241

rs2241767

F: CCTGGTGAGAAGGGTGAGAA

R: AGATGCAGCAAAGCCAAAGT

56 ⁰C 95⁰C 15min, 93⁰C 45 Sec

56⁰C 30 Sec, 72⁰C 45 Sec

241

INSR

(3643)

rs1799817

F: CCAAGGATGCTGTGTAGATAAG

R: TCAGGAAAGCCAGCCCATGTC

56 ⁰C 95⁰C 15min, 93⁰C 45 Sec

56⁰C 30 Sec, 72⁰C 45 Sec

317

rs1799815 F: CCAAGGATGCTGTGTAGATAAG

R: TCAGGAAAGCCAGCCCATGTC

56 ⁰C 95⁰C 15min, 93⁰C 45 Sec

56⁰C 30 Sec, 72⁰C 45 Sec

317

rs2059806

F: CGGTCTTGTAAGGGTAACTG

R: GAATTCACATTCCCAAGACA

62 ⁰C 95⁰C 15min, 93⁰C 45 Sec

62⁰C 30 Sec, 72⁰C 45 Sec

324

rs2229429

F: CGGTCTTGTAAGGGTAACTG

R: GAATTCACATTCCCAAGACA

62 ⁰C 95⁰C 15min, 93⁰C 45 Sec

62⁰C 30 Sec, 72⁰C 45 Sec

324

FSHR

(2492)

rs6166 F: GCAAGTGTGGCTGCTATGAA

R: GTGACATACCCTTCAAAGGC

55 ⁰C 95⁰C 15min, 95⁰C 1min

55⁰C 1 min, 72⁰C 1 min

231





71

Table continues…………….

rs6165

F: CCTGCACAAAGACAGTGATG

R: TGGCAAAGACAGTGAAAAAG

55 ⁰C 95⁰C 15min, 95⁰C 1min

55⁰C 1 min, 72⁰C 1 min

577

FSHB

(2488)

rs6169 F: TGTTAGAGCAAGCAGTATTCAATTTCT

R: GTATGTGGCCTGAAATGTCCACTGATC

60 ⁰C 95⁰C 15min, 94⁰C 1min

60⁰C 30 Sec, 72⁰C 1 min

357

LHCGR

(3973)

rs61996318 F: TGATGGTGGTGGTGATGATG

R: GGTTTCTAGCCAGCCAGTTG

60 ⁰C 95⁰C 15min, 94⁰C 1 min

60⁰C 40 Sec, 72⁰C 1 min

379

rs111834744 F: TGATGGTGGTGGTGATGATG

R: GGTTTCTAGCCAGCCAGTTG

60 ⁰C 95⁰C 15min, 94⁰C 1 min

60⁰C 40 Sec, 72⁰C 1 min

379

LHB

(3972)

rs1800447 F: GTCTCAGACCTGGGTGAAGC

R: GCACAGATGGTGGTGTTGAC

58 ⁰C 95⁰C 15min, 94⁰C 45 Sec

58⁰C 45 Sec, 72⁰C 45 Sec

185

rs4002462 F: GTCTCAGACCTGGGTGAAGC

R: GCACAGATGGTGGTGTTGAC

58 ⁰C 95⁰C 15min, 94⁰C 45 Sec

58⁰C 45 Sec, 72⁰C 45 Sec

186

ESR1

(2099)



53 ⁰C 95⁰C 15min, 95⁰C 45 Sec

53⁰C 45 Sec, 72⁰C 1 min

1366



53 ⁰C 95⁰C 15min, 95⁰C 45 Sec

53⁰C 45 Sec, 72⁰C 1 min

1366

ESR2

(2100)

rs4986938 F: CGGCAGAGGACAGTAAAAGC

R: TGAGAGTTGGGAAGGTGGAG

58 ⁰C 95⁰C 15min, 94⁰C 45 Sec

58⁰C 45 Sec, 72⁰C 45 Sec

213

*SNP: Single nucleotide polymorphism; F: Forward; R: Reverse; *bp: base pair



72

3.6.4 Primer designing

The forward and reverse primers were designed using primer 3

(http://gmdd.shgmo.org/primer3/?seqid=47) website. The sequences of the PCR

primers, forward and reverse sets (Figure 3.2), annealing temperature, cycling

conditions and product size are shown in Table 3.3 and 3.4. The validity of primers

was checked through NCBI database.

(a) SNPs and primer sequence of ESR1 gene

TGAAACTCCTTGCTAAGAGTCTGCTTTGTCAGGTCTGAATTCACTTAACCAGTCTTT

GCTTTGTTGGACTTCTCTCTGCCACCCTATCTGTATCATCATCCTCTCCATAAACCT

TTCTACTTAAAGCATTTTACTTCCTTATTTTCTTGGTTTTCCTAGAATCTCCTTACT

GTTCATTTTCAGCTTCCTTTCTGTGTTCCTCTTCTCTTCCTACATTTTTTTTTAGCT

TTCTACTTTCTTAAAGCATTTTACTTCCTTATTTTCTTGGTTTTCCTAGAATTTTCT

TACTGTTCATTTTCAGTTTCCTTTCTGTGTTCCTCTGATTGTCTCTCTTTCTACATT

TTTTTTTTCTGTGTTCCTCTGATTTTCACGCAGTCTGGAGTTGTCATGATCAATCAT

AGCCTACTGCAGCCTCGACATCCTAGGCTCAAGTGATTCTCCCACCTCAGCCTTACA

AGTAGCTAGGACTACAGTCACACATCACCATTCTCAGCTAATTTTTTTAAGAAGCAT

TTTTATAGAGATGGAGTCTTGCTATATTGTGCAGGCTGGGCTCAAACTACAGGGCTT

AAACAATTCTCCTGCTTTGGCCTCCCAAAGTGCTGGGATTCCAGGCATGAACCACCA

TGCTCAGTCTCTACATGTTCCTAAAGAGGAGTTTTGAATATTGAAGAACAGTATTTT

CAAATTACATTATTCAAGTTATAAAAACTGATATCCAGGGTTATGTGGCAATGACGT

AAAAATTTGAATTGTTATTTTTTTGACACATGTTCTGTGTTGTCCATCAGTTCATCT

GAGTTCCAAATGTCCCAGCTGTTTTATGCTTTGTCTCTGTTTCCCAGAGACCCTGAG

TGTGGTCTAGAGTTGGGATGAGCATTGGTCTCTAATGGTTCTGAAATAATTGTATAT

TCCTGCAAAAACATTAAGTCTATTAGAAACCAGCTAATTTCATTTTGTCATTTTTAT

AGGTAACATATTCTGGTGCAGGTAGTATGTTTTTAAAACAAGTTTGCAATAAACAAT

TTCCCCTCAAGGTTAATATAATAGGCAACACCTTTTGCTGCAACAGACGGCAAGAGG

TAATGAAAGATTAGCTTACATTATGATTCATTATTTCAAAATGTCAGGATAAAGTGG

ATCTGCTGCATCTCCCAGAGAGTGCATGTTTTGCTTTTCTAATGTTAATGGATTTAC

TGTTTTTTTCCCCCCAGGCCAAATTCAGATAATCGACGCCAGGGTGGCAGAGAAAGA

TTGGCCAGTACCAATGACAAGGGAAGTATGGCTATGGAATCTGCCAAGGAGACTCGC

TACTGTGCAGTGTGCAATGACTATGCTTCAGGCTACCATTATGGAGTCTGGTCCTGT

GAGGGCTGCAAGGCCTTCTTCAAGAGAAGTATTCAAGGTAATAGTGTGTTGAAAACG

ACTTCTATTTTTGATCCTATGAGCAGATCCTAAGAGCCAAAGCGACTGGACTGGACT

http://gmdd.shgmo.org/primer3/?seqid=47

73

(b) SNPs and primers sequences of IL10 gene promoter region

GACTATAGAGTGGCAGGGCCAAGGCAGAGCCCAGGCCTCCTGCACCTAGGTCAGTGT

TCCTCCCAGTTACAGTCTAAACTGGAATGGCAGGCAAAGCCCCTGTGGAAGGGGAAG

GTGAAGGCTCAATCAAAGGATCCCCAGAGACTTTCCAGATATCTGAAGAAGTCCTGA

TGTCACTGCCCCGGTCCTTCCCCAGGTAGAGCAACACTCCTCGCCGCAACCCAACTG

GCTCCCCTTACCTTCTACACACACACACACACACACACACACACACACACACACACA

CACAAATCCAAGACAACACTACTAAGGCTTCTTTGGGAAGGGGAAGTAGGGATAGGT

AAGAGGAAAGTAAGGGACCTCCTATCCAGCCTCCATGGAATCCTGACTTCTTTTCCT

TGTTATTTCAACTTCTTCCACCCCATCTTTTAAACTTTAGACTCCAGCCACAGAAGC

TTACAACTAAAAGAAACTCTAAGGCCAATTTAATCCAAGGTTTCATTCTATGTGCTG

GAGATGGTGTACAGTAGGGTGAGGAAACCAAATTCTCAGTTGGCACTGGTGTACCCT

TGTACAGGTGATGTAATATCTCTGTGCCTCAGTTTGCTCACTATAAAATAGAGACGG

TAGGGGTCATGGTGAGCACTACCTGACTAGCATATAAGAAGCTTTCAGCAAGTGCAG

ACTACTCTTACCCACTTCCCCCAAGCACAGTTGGGGTGGGGGACAGCTGAAGAGGTG

GAAACATGTGCCTGAGAATCCTAATGAAATCGGGGTAAAGGAGCCTGGAACACATCC

TGTGACCCCGCCTGTACTGTAGGAAGCCAGTCTCTGGAAAGTAAAATGGAAGGGCTG

CTTGGGAACTTTGAGGATATTTAGCCCACCCCCTCATTTTTACTTGGGGAAACTAAG

GCCCAGAGACCTAAGGTGACTGCCTAAGTTAGCAAGGAGAAGTCTTGGGTATTCATC

CCAGGTTGGGGGGACCCAATTATTTCTCAATCCCATTGTATTCTGGAATGGGCAATT

TGTCCACGTCACTGTGACCTAGGAACACGCGAATGAGAACCCACAGCTGAGGGCCTC

TGCGCACAGAACAGCTGTTCTCCCCAGGAAATCAACT

(c) SNPs and primers sequence of FSHB gene

AATCCTGTCATGTTTTTCATCATTTTTCTATGCTAAAATTCAAAGTTCCTTTATATTTTGAA

AAATAGTTAATATTTTGATATAGCCATAGGAAGTAAGAAAAGAAATTACTTGTATTTTCTGG

AAGATTTCAAGAACAATTTAGAAATGTAAATAGCATATAGGTCATTTATGAGGTCATGTTTT

AATGGGTAAATGTTAGAGCAAGCAGTATTCAATTTCTGTCTCATTTTGACTAAGCTAAATAG

GAACTTCCACAATACCATAACCTAACTCTCTTCTTAAACTCCTCAGGATCTGGTGTATAAGG

ACCCAGCCAGGCCCAAAATCCAGAAAACATGTACCTTCAAGGAACTGGTATACGAAACAGTG

AGAGTGCCCGGCTGTGCTCACCATGCAGATTCCTTGTATACATACCCAGTGGCCACCCAGTG

TCACTGTGGCAAGTGTGACAGCGACAGCACTGATTGTACTGTGCGAGGCCTGGGGCCCAGCT

ACTGCTCCTTTGGTGAAATGAAAGAATAAAGATCAGTGGACATTTCAGGCCACATACCCTTG

TCCTGAAGGACCAAGATATTCAAAAAGTCTGTGTGTGTGCAATGTGCCCAGGGGACAAACCA

CTGGATCAGGGGATTCAGACTCTACTGATCCCTGGTCTACTGGCAGAGGGAACTCTGGGAAT

74

TGAGAGTGCTGGGGGCCAGGACTCCATCATGATTCAGCTCTATATTCCTAGGTCTGATTTCA

TAAGGTTT

(d) SNPs and primers sequence of INSR gene

GTAGCATCATTCCATAGCAAGGGTCTGAAATCAGACAAGAAGGATGGGGATGCAGGT

TTGCCTCAGGACATATTGGCCAGGATCTTGGACCAGTTGTGGCTCCTTCCTTGAGTC

TCTGCCATGCCCTCTCCATGGGTGCAGATGCCTGTCCTGTTCTCGGCCATATGCCCA

GTGCCCGGCATGGGTCCTGGATCACAGAACTCATTTCATGAGTGTTTTCGAGGGGGT

TTGGGTGAGGGCTTGGGTGGAAGGTGGCTGCAGACCCCCAAGGGATCCTCCAAGGAT

GCTGTGTAGATAAGTAAGAAGTAGTGTTTCCATGCTCTGTGTACGTGCCGGACGAGT

GGGAGGTGTCTCGAGAGAAGATCACCCTCCTTCGAGAGCTGGGGCAGGGCTCCTTCG

GCATGGTGTATGAGGGCAATGCCAGGGACATCATCAAGGGTGAGGCAGAGACCCGCG

TGGCGGTGAAGACGGTCAACGAGTCAGCCAGTCTCCGAGAGCGGATTGAGTTCCTCA

ATGAGGCCTCGGTCATGAAGGGCTTCACCTGCCATCACGTGGTGAGTCCAGTGGGGG

TGGGACATGGGCTGGCTTTCCTGACCCTTCCCTTTCTCTGCCTCCTCCTCCTGCACA

GAGCGACAGAGGACACAGGGTGTAACCTCCTACCCACCCCTCACTCCACTAAGCTTC

CCATCCTAGAGGTGTGAGGAGGGATCATTCCCTTCTCAAATCCCATCCTCTCCCACT

TCGCCTGGAACCAGACTCTATCACTGTCTCATCACTTTCTGGAATGTTTCATTGCTT

TCCAGAATCTTTCATCACTTTC

Figure 3.2: The sequence highlighted blue represent the forward and reverse

primers and arrows (purple) shows SNP (a-d).

75

3.6.5 PCR Analysis

PCR was carried out in a total volume 25 μl reaction mixtures consisting of 50-100 ng

of DNA template, 10 μmol of each primer, 10 mM dNTP , 10X PCR buffer

containing15 mM MgCl2 and 5 U/μl Hotstart Taq DNA polymerase (Qiagen, Hilden

Germany). A DNA-free control was also run at parallel conditions.

PCR reaction mixture

Volume of reaction

Single reaction 96 reactions

Master mix

10X PCR buffer including

MgCl2

2.5ul 240ul

Primer forward 0.5 ul 48 ul

Primer reverse 0.5 ul 48 ul

dNTPs 0.5 ul 48 ul

Hot star Taq polymerase 0.5 ul 48 ul

Total master mix 4.5 ul 432 ul

Template DNA Variable according to the

concentration

Molecular grade water Adjustable

Total volume of reaction 25 ul

3.6.6 Gel electrophoresis and verification of PCR products

PCR products were visualized by ethidium bromide staining on a 2 % agarose gel

(Sigma Aldrich, St.Louis Missouri) (Annexure IV). The identities of the PCR

products were verified by sequencing. The gel electrophoresis of optimized PCR

products of selected genes was presented in Annexure V.

3.6.7 Purification of PCR product

The amplification PCR products were purified with Qiaquick PCR purification kit

(Qiagen, Hilden Germany). The PCR product was purified from nucleotides, primers,

salts and polymerases using Qiaquick spin columns. (The reagent preparation was

given in Annexure VI).

76

Procedure

In 25 µl of PCR sample 125 µl of PB buffer was added and mixed. The QIAquick

spin column was placed in a provided 2 ml collection tube. The DNA of sample

bound to the QIAquick column after centrifugation for 30–60 seconds. The flow-

through was discarded and the QIAquick column was placed back into the same tube.

The membrane bounded DNA was washed by adding 750 µl buffer PE to the

QIAquick column and centrifuge for 30–60 seconds. The flow-through was discarded

and placed the QIAquick column back in the same tube then centrifuged the column

for an additional 1 minute. The QIAquick column was placed in a clean 1.5 ml micro-

centrifuge tube. The DNA was eluted with DEPC treated water (pH 7.0–8.5) to the

center of the QIAquick membrane and centrifuged the column for 1 minute. The DNA

concentration and purity were measured using an absorbance ratio of 260/280 nm by

nanodrop (Thremoscientific, Nanodrop 2000).

3.6.8 DNA sequencing

The purified products were subject to direct sequencing with either the forward or

reverse primers. DNA sequencing was carried out with Applied Biosystems, 3730xL

capillary instruments at Keck Biotechnology Resource Laboratory Yale University

USA. The Sanger chemistry for this platform involves dideoxy terminators (ddNTPs)

tagged with a difference fluorescent dye (Big Dye Terminators), along with AmpliTaq

polymerase. The sample undergoes cycle sequencing in a thermo-cycler and then the

product is bead purified with Beckman Coulter’s Clean SEQ particles (Applied

Biosystem, New Haven CT).

3.6.9 DNA sequencing data interpretation

The electrophoretic chromatogram data were received as a computer readable

sequence file through file transfer protocol (ftp). For each gene the sequence data was

assembled using the DNA star software to ensure the sequence counting.

Polymorphisms were identified by using the Laser gene DNA Star sequence counting

program and were confirmed manually. Each genomic variant was verified only if it

was observed with forward and reverse primer. All the sequence entries were BLAT

using UCSC (https://genome.ucsc.edu/cgi-bin/hgBlat?command=start) to confirm the

related relevance of SNPs with PCOS and endometriosis in prior publications.

https://genome.ucsc.edu/cgi-bin/hgBlat?command=start

77

Then specificity of the selected optimized DNA fragment of all the SNPs were

validated against human genome from NCBI database by two sequence nucleotide

alignment BLAST.

(http://blast.stva.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch&BLAST_SP

EC=blast2seq&LINK_LOC=align2seq).

3.7 Hormonal Analysis

The hormonal analysis of gonadotropins (FSH), sex steroids (Testosterone and

progesterone) hormones of the samples was measured using specific commercially

available ELISA kits according to the manufacturer’s instructions.

3.7.1 Follicle stimulating hormone (FSH)

The hormone, FSH was measured in PCOS women and controls by an ELISA kit

(Monobind Lake forest, CA, USA), that uses an enzyme immunoassay performed in

micro-titre plate. With every plate a standard curve was also run and the absorbance

of the unknown were read against this standard curve. The standards S0-S5 have the

following concentrations of FSH (0, 5, 10, 25, 50 and 100 mIU/ml). All the samples

and standards were run in duplicate.

Expected values for the FSH ELISA test system (mIU/ml)

Follicular phase 3.0-12.0

Mid cycle 8.0-22.0

Luteal phase 2.0-12.0

The cross-reactivity of the FSH Monobind ELISA test system to selected substances

was evaluated by adding the interfering substances to a serum matrix at various

concentrations.

Substance Cross reactivity Concentration

Follitropin (FSH) 1.0000 -

Lutropin Hormone (hLH) <0.0001 1000 ng/ml

Chorionic Gonadotropin (hCG) <0.0001 1000 ng/ml

Thyrotropin (TSH) <0.0001 1000 ng/ml

http://blast.stva.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch&BLAST_SPEC=blast2seq&LINK_LOC=align2seq

http://blast.stva.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch&BLAST_SPEC=blast2seq&LINK_LOC=align2seq

78

3.7.2 Testosterone

The elevated level of testosterone was measured in PCOS and control group to assess

the phenotype of the disease. Competitive Enzyme Immunoassay (EIA) was

performed to measure the serum level of testosterone by using an ELISA kit

(Monobind, Lake forest, CA, USA). Testosterone concentration in the sample is

calculated based on a series of standard. The concentration of standards S1-S5 was 0,

0.1, 0.5, 1.0, 2.5 and 5 ng/ml. Intra and inter-assay coefficient of variance have been

determined at multiple points on the standard curve.

Expected values for the testosterone ELISA test system (ng/ml)

Female 0.2-0.95

Male 2.5-10.0

The cross-reactivity of the testosterone Monobind ELISA test system to selected

substances was evaluated by adding the interfering substances to a serum matrix at

various concentrations.

3.7.3 Progesterone

Progesterone hormone was measured in endometriosis women and control group

using an ELISA kit (Monobind, Lake forest, CA, USA). A standard curve was plotted

and progesterone concentrations in samples were determined by interpolation the

standard curve.

Expected values for the testosterone ELISA test system (ng/ml)

Follicular phase 0.15-1.40

Luteal phase 2.0-25.0

Substance Cross reactivity

Testosterone 1.0000

Dihydotestosterone 0.0178

Cortisol <0.0001

Progesterone <0.0001

Estradiol <0.0001

79

The cross-reactivity of the testosterone Monobind ELISA test system to selected

substances was evaluated by adding the interfering substances to a serum matrix at

various concentrations.

3.8 Statistical analysis

A simple chi-square test was used to test for Hardy–Weinberg equilibrium in the

cases and controls. The odd ratios and confidence interval was calculated using

SigmaPlot 11.0. The mean of various anthropometric parameters was compared by

student t-test. The maximum likelihood haplotype frequency estimates and standard

errors were computed using the HAPLO software (Hawley & Kidd, 1995) which

implements the expectation-maximization (E-M) algorithm of Dempster et al. (1977).

3.9 Haplotype and linkage disequilibrium analysis

The estimation of haplotype frequencies was carried out by employing the

FORTRAN software called HAPLO described in Hawley and Kidd (1995). This set

of computer programs applies the Expectation-Maximization (EM) algorithm of

Dempster et al (1977) which has been widely applied to estimation problems that can

only be solved by iterative calculations. The HAPLO calculations for this thesis

project were run using a Linux compiler on the Louise cluster at the Yale University

Biomedical High Performance Computing Center which is supported by NIH grants

RR19895 and RR029676-01.

“HAPLO is designed to compute haplotype frequency estimates from phenotype data

based on samples of unrelated individuals. The EM algorithm is a generalized

iterative maximum likelihood approach to estimation that is useful when data are

Substance Cross reactivity

Progesterone 100.00

Testosterone 0.015

Androstenedione 0.158

Dihydotestosterone 0.006

Cortisol 0.005

Estradiol 0.004

80

ambiguous and/or incomplete. The next three paragraphs quoted from Hawley and

Kidd (1995) presents the key ideas underlying the estimation of the haplotype

frequencies and standard errors.”

"The EM algorithm is an iterative process; each iteration gives a set of frequency

estimates that converge to Table maximum likelihood estimates. The iterations start

with all haplotypes (alleles) at equal frequency. It is easy to show that the frequency

estimates for haplotypes that are not definitely “observed,” i.e., required to explain a

phenotype, will go to zero."

"The HAPLO program optionally estimates standard errors in two ways. First a

jackknife procedure is used. Estimates of all haplotype frequencies are recalculated

with each individual in turn removed from the data set. For each haplotype the

standard deviation of those frequency estimates is an estimate of the standard error of

the original frequency estimate. This estimate of the standard error takes into account

the added uncertainty in the data because of the ambiguity and missing data as well as

the sampling error. The second estimate of the standard error of each haplotype

frequency applies the formula for the binomial standard error assuming all haplotypes

were directly observed and counted. This assumption can be correct or a very close

approximation in some instances and in any case the binomial standard error estimate

serves as a lower bound check on the jackknife estimates, which can become

inaccurate when the number of observations is small."

"The use of a genotype-phenotype correspondence list gives users great flexibility in

defining the haplotype system. Because the user defines the correspondence, it is not

necessary to supply any explicit information about the component polymorphic

systems. Definitions need to be entered only for the observed phenotypes and

whatever genotypes may be implied; it is not necessary to define all the possible

combinations of alleles. It is possible to define phenotypes that make use of any

available phase information or that cover cases where data on the component systems

are incomplete. Individuals with an ambiguous phenotype that is partially or fully

resolved are included in the analysis by simply defining a new phenotype that

corresponds to only the single or few remaining genotype(s). Individuals with missing

data are included by defining a phenotype that corresponds to the set of genotypes that

includes all phenotypes at the missing site but only those possible for the typed sites."

81

CHAPTER 4

RESULTS

4.1 Population characteristics

The selected anthropometric characteristics of the study population are summarized in

Table 4.1-4.3 for endometriosis, PCOS and controls women. The women of

reproductive active age group between 20 to 40 years were selected. No significant

difference (p > 0.05) was observed in endometriosis, PCOS and controls regarding

Body Mass Index (BMI), Waist/Hip Ratio (WHR) and mean age of menarche, they

were well matched on all other demographic characteristics (Table 4.2, 4.3). The

proportion of obese women was 96.87 % vs. 95.83% within the PCOS and control

group respectively (p > 0.05) (Table 4.3).

The clinical manifestation of various anthropometric characteristics associated with

endometriosis and PCOS (primary, secondary infertility, pelvic pain and

dysmenorrhea; oligomenorrhea, hirsutism, infertility and obesity) were represented in

Figure 4.1, 4.2. The women volunteered as control were without oligomenorrhea,

hirsutism, dysmenorrhea and infertility.

4.2 Genotype, allele frequencies and Haplotype

The genotype distribution and relative allele frequencies of all the studied

polymorphism of ninety-six PCOS patients, fifty-two endometriosis and one hundard-

fourty eight controls were investigated in the female population of Pakistan. The

Tables in the preceding section illustrates the number of relative genotypes (n),

percentage of genotype (%), allele frequencies and their percentage, estimated

heterozygosity (E het), chi square value (χ2) and odd ratios (OR) at 95% confidence

interval (CI) along with the p-values. The genotype frequencies of all the single

nucleotide polymorphisms fit the Hardy-Weinberg principle in all endometriosis,

PCOS and controls; non-significant p values suggest that alleles are in equilibrium.

No noteworthy deviations of Hardy-Weinberg ratios were observed for all of the

SNPs studied and tested separately in the affected and control groups since the

expected and observed genotype frequencies were not significantly different using a

“p” value of 1%. The genotype and allele frequencies of the polymorphisms in the

study were determined by simple allele and genotype counting.

82

Table 4.1: Anthropometric characteristics of PCOS, endometriosis and controls.

Population

characteristics

PCOS (n= 96) Endometriosis (n= 52) Controls (n= 148)

n (%) n (%) n (%)

Education

Illiterate 37 (38.5) 19 (36.5) 47 (31.8)

Up to primary 11 (11.5) 8 (15.4) 23 (15.5)

Higher secondary 33 (34.4) 18 (34.6) 56 (37.8)

Graduate and above 16 (16.7) 7 (13.5) 22 (19.9)

Age of patients

20-30 years 47 (48.9) 21 (40.4) 63 (42.6)

31-40 years 49 (51.1) 31 (59.6) 85 (57.4)

Duration of

marriage

01-05 years 35 (36.4) 25 (48.0) 67 (45.3)

06-10 years 31 (32.2) 17 (32.7) 54 (36.5)

11-15 years 14 (14.6) 8 (15.4) 17 (11.4)

16 and above 16 (16.6) 2 (3.8) 10 (6.7)

Primary Infertility 59 (61.5) 30 (57.6) 0

Secondary

Infertility 37 (38.5) 22 (42.3) 0

Family H/O

Hirsutism 23 (23.9) 4 (9.6) 9 (6.0)

Obesity 43 (44.8) 11 (21.2) 29 (30.2)

Menstrual problems 23 (23.9) 7 (13.5) 5 (5.2)

Thyroid

abnormalities 3 (3.13)

0 0 (0)

DM 39 (40.6) 9 (17.3) 11 (11.5)

Infertility 23 (23.9) 2 (3.8) 1 (1.04)

PCOS 19 (19.8) 1 (1.9) 0

Endometriosis

13 (25)

Patient H/O

Diabetes Mellitus 11 (11.5) 0 16 (10.8)

Infertility 86 (89.6) 49 (94.2) 0

Weight gain 88 (91.7) 5 (9.6) 13 (8.8)

Hirsutism 89 (92.7) 0 0

Facial hair 90 (93.75) 2 (3.9) 4 (2.7)

Acne 70 (72.9) 7 (13.5) 9 (6.0)

Oligomenorrhea 88 (91.7) 0

Diagnosis

Ultrasound, Clinically 87 (90.6) 37 (71.1) -

Clinically 9 (9.3) 15 (28.8)

Age of Menarche

11-13 year 88 (91.7) 47 (90.3) 131 (88.5)

14 to onward 8 (8.3) 5 (9.6) 17 (11.5)

83

Table Continued…

Pattern of cycle

Regular 9 (9.4) 23 (44.2) 131 (88.5)

Irregular 87 (90.6) 29 (55.7) 11 (7.5)

History of pain

Pelvic pain 23 (24.0) 43 (82.7) 11 (7.4)

Back pain 27 (28.1) 44 (84.5) 44 (29.7)

Dysmenorrhea 11 (11.5) 37 (71.2) 23 (15.5)

Dyschezia 5 (5.2) 27 (51.9) 5 (3.4)

Dysuria 7 (7.3) 11 (21.2) 4 (2.7)

Dyspareunia 11 (11.5) 31 (59.6) 19 (12.8)

Table 4.2: Anthropometric characteristics of women with endometriosis and

controls, the values given are mean ± S.D. The mean values of two groups were

compared by “t” test.

Characteristics Endometriosis

(n= 52)

Controls

(n= 52)

p

Mean ± S.D Mean ± S.D

Age (year) 30.25 ± 5.46 30.59 ± 4.95 > 0.05

BMI (Kg/m2) 25.12 ± 2.72 25.57 ± 2.08 > 0.05

WHR 0.80 ± 0.04 0.79 ± 0.06 > 0.05

Gynaecological history n (%) n (%)

Primary Infertility 30 (57.69) 0 < 0.001

Secondary Infertility 22 (42.31) 0 < 0.001

Pelvic pain 49 (94.23) 12 (23.07) < 0.001

Dysmenorrhea 50 (96.15) 6 (11.53) < 0.001

84

Table 4.3: Anthropometric characteristics of women with PCOS and controls.

The values given are mean ± S.D. The mean values of two groups were compared

by “t” test.

Characteristics PCOS (n= 96) Controls (n= 96)

Mean ± S.D Confidence

Level 95%

Mean ± S.D Confidence

Level 95%

p

Age (Year) 26.87 ± 4.42 0.89 26.02 ± 3.52 0.561 > 0.05

BMI (Kg/m2) 31.10 ± 1.47 0.83 30.49 ± 1.66 0.742 > 0.05

WHR 1.16 ± 0.07 0.01 1.12 ± 0.05 0.011 > 0.05

Age of Menarche

(Year)

13.09 ± 1.06 0.21 13.07 ± 1.52 0.022 > 0.05

Gynecological history

Characteristics n= 96 % n= 96 % p

Oligomenorrhea

(Less than 9 menses

per year)

88 91.67 0 0 < 0.001

H/O irregular

menses with weight

gain

85 88.54 0 0 < 0.001

Family history

Hirsutism 23 23.96 0 0.00 < 0.001

Obesity 43 44.79 29 30.21 < 0.001

Menstrual problems 23 23.96 5 5.21 < 0.001

Thyroid

abnormalities

3 3.13 0 0.00 < 0.001

DM 39 40.63 11 11.46 < 0.001

Infertility 23 23.96 1 1.04 < 0.001

PCOS 19 19.79 0 0.00 < 0.001

Subject Symptoms

Infertility 86 89.58 0 0.00 < 0.001

Obesity 93 96.87 92 95.83 > 0.05

Hirsutism 89 92.71 0 0.00 < 0.001

Facial hair 90 93.75 0 0.00 < 0.001

Acne 70 72.91 0 0.00 < 0.001

85

Figure 4.1: Clinical manifestation of anthropometric characteristics in

endometriosis compared with control along with percentage symptoms.

Figure 4.2: Clinical manifestation of anthropometric characteristics in PCOS

compared with control along with percentage symptoms.

86

4.3 Endometriosis

The SNPs and genetic variations of ESR1, ESR2, PGR, IL10 and FSHR genes

associated with the diagnosis of endometriosis with infertility were studied.


The contribution of the genomic variants of ESR1 was studied for two SNPs

rs2234693 and rs9340799. Both ESR1 polymorphisms are in intron 1 and separated

by only 51 base pairs. The rs2234693 polymorphism is characterized by a T→C

transition 397 nucleotide upstream in the intron 1. The rs9340799 polymorphism

marks an A→G transition 351 nucleotides upstream in intron 1. The mutations of

ESR1 gene in two sequence BLAST alignment are shown in Figure 4.3. The sequence

chromatogram showed homozygous and heterozygous form of T/C base substitution

of rs2234693 (Figure 4.4). The genotype distribution and relative allele frequencies

for ESR1 gene are shown in Table 4.4. The frequency of the rs2234693 “C” allele was

43.3% in the patients and 35.6 % in the control group. No significant differences were

observed for comparative genotype distribution and relative allele frequencies of SNP

rs2232693 between endometriosis and controls (p = 0.301, OR = 1.381, 95% CI =

0.79-2.41, χ2

= 0.99). We had also found no statistically significant differences in the

genotypes and allele frequencies between endometriosis and control group for

rs9340799 (p = 0.220, OR = 1.425, 95% CI = 0.82-2.47, χ2

= 1.26). A novel SNP

rs11155815 was found during the screening of DNA sequencing map. Two were

homozygous for rs11155815 T allele, 16 were heterozygous and there were 34

subjects homozygous for C allele. The heterozygotes CT were 30.8% in patients with

endometriosis and 21.2% in controls. As the homozygous TT genotype and

heterozygous CT genotype was rare both in endometriosis and controls, the TT and

CT were combined together and are referred as variants genotype of this new SNP.

The frequency of variant genotype was different in both groups. The frequency of the

rs11155815 “T” allele was 19.2% in the patients and 12.5% in the control group.

Comparison of frequencies between patients and control groups show no statistically

significant difference between them (p = 0.150, OR = 1.833, 95% CI = 0.87-3.87, χ2

=

2.02). The SNPs rs8179176, rs11155816, rs4986936 and rs4986937 were not

significantly associated with endometriosis (Table 4.4). This suggested that the

87

genetic variants of ESR1 gene were not related in the occurrence of endometriosis in

Pakistani women. Interestingly, the haplotype analysis showed distinct variations

among endometriosis and control groups. The frequency of haplotypes “GAT, AAC

and GGC” was 0.301, 0.091 and 0.164 respectively in endometriosis whereas the

haplotypes “GAC, AAT and GGT” were common in controls with frequencies 0.301,

0.035 and 0.264 respectively (Table 4.5; Figure 4.5). The overall haplotype

distributions in the two groups differ at a p-value of less than 0.005. Also the highly

significant value (p < 0.005, χ2

= 24.3) of genetic heterogeneity test showed that the

haplotype frequency estimates for the population samples being compared are from

the same population. The pairwise linkage disequilibrium (LD) or Delta-squared

value for the ESR1 gene is shown in Figure 4.6.

88

(a) Alignment of two sequences BLAST (Endometriosis)

Query 493 CCAATGCTCATCCCAACTCTAGACCACACTCAGGGTCTCTGGGAAACAGAGACAAAGCAT 552

||||||||||||||||||| ||||||||||||||||||||||||||||||||||||||||

Sbjct 327 CCAATGCTCATCCCAACTCCAGACCACACTCAGGGTCTCTGGGAAACAGAGACAAAGCAT 386

Query 553 AAAACAGCTGGGACATTTGGAACTCAGATGAACTGATGGACAACACAGAACATGTGTCAA 612

||||| ||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 387 AAAACGGCTGGGACATTTGGAACTCAGATGAACTGATGGACAACACAGAACATGTGTCAA 446

(b) Alignment of two sequences BLAST (Control)

Query 480 GAACCATTAGAGACCAATGCTCATCCCAACTCTAGACCACACTCAGGGTCTCTGGGAAAC 539

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 316 GAACCATTAGAGACCAATGCTCATCCCAACTCTAGACCACACTCAGGGTCTCTGGGAAAC 375

Query 540 AGAGACAAAGCATAAAACAGCTGGGACATTTGGAACTCAGATGAACTGATGGACAACACA 599

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 376 AGAGACAAAGCATAAAACAGCTGGGACATTTGGAACTCAGATGAACTGATGGACAACACA 435

Figure 4.3: Two sequence BLAST alignment of ESR1 gene polymorphisms.

Figure 4.4: Sequence chromatogram showing homozygous and heterozygous

form of T/C base substitution of rs2234693.

C

T

89

Figure 4.5: Multi-SNPs haplotype percent frequency distribution for

endometriosis and controls at ESR1 gene.

30.1

17.4 16.8 16.4

9.1

5.94.3

0

26.8

31

26.4

3.3 3.24.9

0.9

3.5

0

5

10

15

20

25

30

35

GAT GAC GGT GGC AAC AGT AGC AAT

Pe

rce

nt

Fre

qu

en

cy (

%)

Haplotypes

Affected

Control

90

Table 4.4: Frequency distribution of single nucleotide polymorphisms of ESR1 gene with risk of endometriosis in Pakistani women.

SNPs ID Genotype/allele

frequencies

Endometriosis

(n= 52)

Controls

(n= 52)

OR (95% CI) χ2 p HWE

n % n %

rs2234693 TT 17 32.7 22 42.3 0.662

(C>T) CT 25 48.1 23 44.2 (0.29-1.47) 0.65 0.410 >.05

Intron 1 CC 10 19.2 7 13.5

Allele frequency

C allele 45 43.3 37 35.6 1.381

T allele 59 56.7 67 64.4 (0.79-2.41) 0.99 0.301 >.05

E(HET) 49 46

rs9340799 AA 15 28.8 20 38.5 0.686

(G>A) GA 25 48.1 24 46.2 (0.30-1.56) 0.48 0.480 >.05

Intron 1 GG 12 23.1 8 15.4

Allele frequency

G allele 49 47.1 40 38.5 1.425

A allele 55 52.9 64 61.5 (0.82-2.47) 1.26 0.220 >.05

E(HET) 50 47

rs11155815 CC 34 65.4 40 76.9 0.567

(C>T) CT 16 30.8 11 21.2 (0.24-1.34) 1.17 0.270 >.05

Intron 1 TT 2 3.8 1 1.9

Allele frequency

C allele 84 80.8 91 87.5 1.833

T allele 22 19.2 13 12.5 (0.87-3.87) 2.02 0.150 >.05

Table continues……………

91

E(HET) 31 22

rs8179176 CC 41 78.8 48 92.3 0.285

(C>T) CT 11 21.1 4 7.7 (0.08-0.95) 3.69 0.060 >.05

Intron 1 TT 1 1.9 0 0

Allele frequency

C Allele 96 92.3 100 96.5 0.295

T Allele 13 12.5 4 3.8 (0.09-0.93) 3.46 0.050 >.05

E(HET) 20 7

rs11155816 TT 46 88.5 46 88.5 1

(C>T) TC 5 9.6 6 11.5 (0.30-3.31) 0.09 0.750 >.05

Intron 1 CC 1 1.9 0 0

Allele frequency

C Allele 7 6.7 6 5.8 1.212

T Allele 97 93.3 98 94.2 (0.35-4.10) 0.05 1.000 >.05

E(HET) 13 11

rs4986936 TT 46 88.5 51 98.1 0.150

(G>A) CT 5 9.6 1 1.9 (0.01-1.29) 2.45 0.110 >.05

Intron 1 CC 1 1.9 0 0

Allele frequency

G Allele 7 6.7 1 99 6.280

A Allele 97 93.3 103 1 (0.88-45.02) 7.28 0.070 >.05

E(HET) 9 2

rs4986937 GG 46 88.5 48 92.3 0.640

(C>T) AG 6 11.5 4 7.7 (0.17-2.41) 0.11 0.730 >.05

92

Table Continue…...

Intron 1 AA 0 0 0 0

Allele frequency

G Allele 98 94.2 100 96.2 1.531

A Allele 6 5.8 4 3.8 (0.41-5.59) 0.11 0.701 >.05

SNPs ID: single nucleotide polymorphism identity; OR: Odd ratios; CI: Confidence interval; p: Significance; HWE: Hardy Weinberg equilibrium; χ2: Chi square.

Table 4.5: Multi-SNPs haplotype frequency estimates for endometriosis and controls at ESR1 gene.

Groups Haplotype frequencies ± S.E.E Exp.

Het

Global LD

LR ChiSq

p Genetic

Heterogeneity

Test

GAT GAC GGT GGC AAC AGT AGC AAT Chi Sq p

Endometriosis 0.301

±

0.037

0.174

±

0.017

0.168

±

0.016

0.164

±

0.010

0.091

±

0.015

0.059

±

0.033

0.043

±

0.023

0.000

±

0.000

81.00 4.70 0.050

24.30 0.005 Control 0.268

±

0.028

0.310

±

0.067

0.264

±

0.039

0.033

±

0.060

0.032

±

0.049

0.049

±

0.062

0.009

±

0.029

0.035

±

0.018

75.70 10.40 0.050

Exp. Het: Expected Heterozygosity; Global LD LR Chi Sq: Global likelihood ratio chi-square; Chi Sq: Chi square; S.E.E: Standard error of estimation; p: Significance

93

ESR1 Endometriosis

rs4986936

rs11155815

rs8179176

rs2234693

rs11155816

rs9340799

rs4986937

Figure 4.6: Pairwise linkage disequilibrium of ESR1 gene in endometriosis and

controls.

ESR1 Control

rs4986936

rs11155815

rs8179176

rs2234693

rs11155816

rs9340799

rs4986937

.10

.20

.13

.10

.20 .30

.16

.12 .16 .12

.11

.02

.16

.11

.25

.26

.15 .10 .22

.48

.12

.22

.10

.02

.02

.03 .03

.02

.12 .11 .12

.02

.02

.02

.02

.02

.02

.02 .02 .02

.16

.02

.02

.02

94


The ESR2 gene was studied for polymorphism rs4986938 which is a G→A change at

position 1859 in the 3′-untranslated region (3′-UTR) of exon 8. The genotype

frequency of G/A polymorphism in endometriosis group was significantly different

from that of controls. The mutant allele “A” was in significantly higher frequency

among the endometriosis (38.5%) compared to the controls (20.2%) yielding an odds

ratio of 2.470 (p = 0.006, OR: 1.360; CI: 0.16-0.80; χ2

= 7.52). As the homozygous

GG genotype was more frequent in controls (63.5%) compared with (38.5%) in

endometriosis (Table 4.6). The heterozygous GA genotype and the AA were

combined together and are referred as variants genotype of rs4986938. The frequency

of variant genotype of rs4986938 was different in both groups (32/52 vs. 19/52 in

endometriosis and controls respectively).

95

Table 4.6: Frequency distribution of single nucleotide polymorphism of ESR2 gene with risk of endometriosis in Pakistani

women.

SNP ID Genotype/allele

frequencies

Endometriosis

(n= 52)

Controls

(n= 52)


n % n %

rs4986938 GG 20 38.5 33 63.5 1.360

(G>A) AG 24 46.2 17 32.7 (0.16-0.80) 5.54 0.010 >.05

UTR-3 AA 8 15.4 2 3.8

Allele frequency

G allele 64 61.5 83 79.8 2.470

A allele 40 38.5 21 20.2 (0.20-0.75) 7.52 0.006 >.05

E(HET) 47 32

SNP ID: single nucleotide polymorphism identity; OR: Odd ratios; CI: Confidence interval; p: Significance; HWE: Hardy Weinberg equilibrium; χ2: Chi square.

96

4.3.3 Interleukin 10 (IL10)

To determine whether the IL10 SNP loci were associated with endometriosis; we

initially compared the single-point genotype and allele distribution of these SNPs in

the endometriosis and control groups. The mutations of IL10 gene in two sequence

BLAST alignment for endometriosis and controls are shown in Figure 4.7. The

sequence chromatogram showed homozygous and heterozygous form of T/C base at

rs1800871 (Figure 4.8). We observed an association of IL10 gene polymorphism and

endometriosis group, the genotype distribution and relative allele frequencies of the

inflammation mediator gene are shown in Table 4.7. The IL10 rs1800872 mutant

allele “A” was significantly overexpressed (2.379 folds) in women with endometriosis

than controls (44.2% vs. 25%; p < 0.006, OR = 2.379, 95% CI = 0.23-0.75). We found

highly significant association between different genotypes (Table 4.7) with

endometriosis group. In SNP rs1800871 the frequency of T allele was higher in

endometriosis patient (38.5% vs. 26%; p = 0.010, OR = 0.443, 95% CI = 0.19-0.92).

In the IL10 PCR products DNA sequencing map, a new SNP rs1800894 was found at

genomic position 206946666 in which the substitution is G to A. No significant

association was found in both groups with this SNP (Table 4.7). In rs1800896 a

statistically significant (p = 0.007) higher frequency of the “G” allele was observed in

patients than in controls (Table 4.7). The frequency of “A” (51.9% in endometriosis

and 71.2% in controls) and “G” (48.1% in endometriosis and 28.8% in control) allele

differ significantly in endometriosis and control groups (p = 0.007, OR = 1.435, 95%

CI = 0.24-0.77).

Haplotype estimation analysis of three SNPs genotype data by means of maximum

likelihood method revealed that estimated overall haplotype frequencies in

endometriosis and control groups differ significantly (Table 4.8). Eight major

haplotypes of IL10 were present in the study population and the frequency of most

common haplotypes is shown in Figure 4.9. In single haplotype association the ATG,

CTG and ACG are more frequent in the endometriosis group, while the haplotype

CCA, CCG and CTA were found frequent in the control group. The other low

frequencies haplotypes showed borderline difference. The genetic heterogeneity test

showed a strong significance (p < 0.005, χ2

= 22.2) between endometriosis and control

groups. The pairwise LD analysis between four loci revealed week R-squared or

Delta-squared value in both the groups (Figure 4.10).

97


Query 13 AATTCTCAGTTGGCACTGGTGTACCCTTGTACAGGTGATGTAACATCTCTGTGCCTCAGT 72

||||||||||||||||||||||||||||||||||||||||||| ||||||||||||||||

Sbjct 46 AATTCTCAGTTGGCACTGGTGTACCCTTGTACAGGTGATGTAATATCTCTGTGCCTCAGT 105

Query 73 TTGCTCACTATAAAATAGAGACGGTAGGGGTCATGGTGAGCACTACCTGACTAGCATATA 132

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 106 TTGCTCACTATAAAATAGAGACGGTAGGGGTCATGGTGAGCACTACCTGACTAGCATATA 165

(b) Alignment of two sequences BLAST (Control) Query 15 AATTCTCAGTTGGCACTGGTGTACCCTTGTACAGGTGATGTAATATCTCTGTGCCTCAGT 74

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 46 AATTCTCAGTTGGCACTGGTGTACCCTTGTACAGGTGATGTAATATCTCTGTGCCTCAGT 105

Query 75 TTGCTCACTATAAAATAGAGACGGTAGGGGTCATGGTGAGCACTACCTGACTAGCATATA 134

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 106 TTGCTCACTATAAAATAGAGACGGTAGGGGTCATGGTGAGCACTACCTGACTAGCATATA 165

Figure 4.7: Two sequence BLAST alignment of IL10 gene polymorphisms.


form of C/T base substitution of rs1800871.

T

TC

98


endometriosis and controls at IL10 gene.

18.6

16.5

12

16.9

7.58.7

15.4

4.4

36.8

19.5

16.1 16.5

4.22.6 2.5 1.8

0

5

10

15

20

25

30

35

40

CCA CCG CTA ACA ACG CTG ATG ATA

Perc

en

t fr

eq

uen

cy (

%)

Haplotypes

Affected

Control

99

Table 4.7: Frequency distribution of single nucleotide polymorphisms of IL10 gene with risk of endometriosis

in Pakistani women.


frequencies

Endometriosis

(n= 52)

Controls

(n= 52)


n % n %

rs1800872 CC 17 32.7 29 55.8 0.385

(C>A) AC 24 46.2 20 38.5 (0.17-0.85) 4.71 0.030 >.05

UTR-5 AA 11 21.2 3 5.8

Allele frequency

C allele 58 55.8 78 75 2.379

A allele 46 44.2 26 25 (0.23-0.75) 7.67 0.006 >.05

E(HET) 47 38

rs1800871 CC 19 36.5 30 57.7 0.422

(C>T) TC 24 46.2 20 38.5 (0.24-0.80) 3.86 0.049 >.05

UTR-5 TT 9 17.3 2 3.8

Allele frequency

C allele 62 61.5 80 74 0.443

T allele 42 38.5 24 26 (0.19-0.92) 6.41 0.010 >.05

E(HET) 48 38

rs1800894 GG 44 84.6 48 92.3 0.357

(G>A) AG 7 13.5 4 7.7 (0.12-1.60) 0.85 0.357 >.05

UTR-5 AA 1 1.9 0 0

Allele frequency

100

Table continues…………

G allele 95 91.3 100 96.2 0.543

A allele 9 8.7 4 3.8 (0.15-1.91) 0.43 0.501 >.05

rs1800896 AA 14 26.9 26 50 0.368

(G>A) AG 26 50 22 42.3 (0.16-0.83) 4.91 0.027 >.05

UTR-5 GG 12 23.1 4 7.7

Allele

frequency

A allele 54 51.9 74 71.2 1.435

G allele 50 48.1 30 28.8 (0.24-0.77) 7.33 0.007 >.05

E(HET) 50 41

SNPs ID: single nucleotide polymorphism identity; OR: Odd ratios; CI: Confidence interval; p: Significance; HWE: Hardy Weinberg Equilibrium; χ2: Chi square.

101

Table 4.8: Multi-SNPs haplotype frequency estimates for endometriosis and controls at IL10 gene.


Het

Global

LD LR

ChiSq

p Genetic

Heterogeneity

Test

CCA CCG CTA ACA ACG CTG ATG ATA

ChiSq

p

Endometriosis 0.186

±

0.029

0.165

±

0.038

0.120

±

0.031

0.169

±

0.042

0.075

±

0.028

0.087

±

0.025

0.154

±

0.027

0.044

±

0.030

84.70 4.90 0.050

22.20 0.050 Control 0.368

±

0.031

0.195

±

0.062

0.161

±

0.016

0.165

±

0.081

0.042

±

0.058

0.026

±

0.035

0.025

±

0.052

0.018

±

0.057

78.40 2.00 0.050


102

IL 10 Endometriosis

IL10 Control

rs1800872

rs1800871

rs1800894

rs1800896

rs1800872

rs1800871

rs1800894

rs1800896

Figure 4.10: Pairwise linkage disequilibrium of IL10 gene in endometriosis and

controls.

.11

.02 .04

.08

.07

.04

.02

.05 .04

.04

.02

.04

103

4.3.4 Progesterone receptor (PGR)

PGR gene was analyzed for rs1042838 in exon 4 and rs10895068 in promoter region

by direct sequencing. In SNP rs1042838 the genotype and allele frequencies showed

distinct variations (Table 4.9) in endometriosis group. In contrast little variations were

found in control group. The frequency of “T” (22.1% in endometriosis and 6.7% in

control) and “G” (77.9% in endometriosis and 93.3% in controls) allele differ

significantly in endometriosis and control groups (p = <0.003, OR = 1.935, 95% CI =

0.10-0.62). The PGR rs1042838 mutant allele “T” was significantly overexpressed

(1.935 folds) in women with endometriosis than controls (p < 0.003). We studied

another polymorphism in rs10895068, no significant difference in genotype and allele

frequencies was observed between endometriosis and control groups (p = 0.210)

(Table 4.9).

Much stronger associations were observed when the two SNPs were considered

together as haplotypes. When the estimated haplotype frequencies were compared

between endometriosis and control, the most common haplotype GG (0.875 vs. 0.679

in controls and endometriosis respectively) was found to be more prevalent in the

control group (Figure 4.11) whereas the TG (0.205 vs. 0.067 in endometriosis and

controls respectively), GA (0.099 vs. 0.058 in endometriosis and controls

respectively) was more common among endometriosis patients (Table 4.10). The

genetic heterogeneity test comparing the affected and control haplotype frequencies

overall differ from each other at p-value = 0.010 significance level. The pairwise LD

analysis revealed week LD for the pairs of loci in the endometriosis and control group

(Figure 4.12).

104


endometriosis and controls at PGR gene.

67.9

20.5

9.9

1.7

87.5

6.7 5.8

00

10

20

30

40

50

60

70

80

90

100

GG TG GA TA

Perc

en

t fr

eq

uen

cy (

%)

Haplotypes

Affected

Control

105

Table 4.9: Frequency distribution of single nucleotide polymorphisms of PGR gene with risk of endometriosis in Pakistani women.


frequencies

Endometriosis

(n= 52)

Controls

(n= 52)


n % n %

rs1042838 GG 32 61.5 45 43.3 1.249

(G>T) TG 17 32.7 7 6.7 (0.09-0.65) 7.20 0.007 >.05

Exon 4 TT 3 5.8 0 0

Allele frequency

G allele 81 77.9 97 93.3 1.935

T allele 23 22.1 7 6.7 (0.10-0.62) 8.76 0.003 >.05

E(HET) 34 13

GG 41 78.8 46 88.5 0.482

rs10895068 AG 10 19.2 6 11.5 (0.16-1.40) 1.12 0.280 >.05

(G>A) AA 1 1.9 0 0

UTR Allele frequency

G allele 92 88.5 98 94.2 1.130

A allele 12 11.5 6 5.8 (0.17-1.30) 1.52 0.210 >.05

E(HET) 20 11

SNPs ID: single nucleotide polymorphisms identity; OR: Odd ratios; CI: Confidence interval; p: Significance; HWE: Hardy Weinberg Equilibrium; χ2: Chi square.

106

Table 4.10: Multi-SNPs haplotype frequency estimates for endometriosis and controls at PGR gene.

Groups Haplotype frequencies ± S.E.E Exp. Het Global LD

LR ChiSq

p Genetic

Heterogeneity

Test

GG TG GA TA Chi Sq p

Endometriosis 0.679±0.046 0.205±0.040 0.099±0.029 0.017±0.013 48.90 0.40 0.050

12.60 0.010 Control 0.875±0.032 0.067±0.025 0.058±0.023 0.000±0.000 22.70 0.90 0.050


Figure 4.12: Pairwise linkage disequilibrium of PGR gene in endometriosis and controls

PGR Endometriosis

PGR Endometriosis rs

108950

68

rs10428

38

rs108950

68

rs10428

38

.24

.0 .0

.06

.0 .0

107


The two common polymorphisms of the FSHR gene in exon 10 were screened among

104 individuals (52 endometriosis and 52 controls). The mutations of FSHR gene in

two sequence BLAST alignment are shown in Figure 4.13. The sequence

chromatogram showed homozygous and heterozygous form of A/G base substitution

of rs6166 (Figure 4.14).The genotype, allele and haplotype frequencies of both the

polymorphisms were agreed with the Hardy-Weinberg equilibrium in endometriosis

and controls. The distribution of allele and genotype frequency along with odd ratios

and significance for association with endometriosis are shown in Table 4.11. In SNP

rs6166 A>G, the frequencies of genotype AA, AG and GG were 46.2% (24/52),

44.2% (23/52) and 9.6 % (5/52) in women with endometriosis while 11.5% (6/52),

44.2% (23/52) and 44.2 % (23/52) in healthy controls respectively. Moreover, we

observed that in SNP rs6166 the women with endometriosis had significantly higher

frequency of allele A in comparison with control (68.3% vs. 33.7%; OR. 4.240, 95%

CI. 2.37- 7.57, p < 0.001). In SNP rs6165 A>G the frequencies of genotype AA, AG

and GG were 46.2% (24/52), 42.3% (22/52) and 11.5 % (6/52) in the women with

endometriosis while 13.5% (7/52), 48.1% (25/52) and 38.5 % (20/52) in healthy

controls respectively. In rs6165 the frequency of allele A was 67.3 vs. 37.5 in

endometriosis and in controls respectively (OR = 3.430, 95% CI = 1.94-6.07, p <

0.001).

The frequency of AA haplotype was 45.5% and 16.3% in patients and controls.

Interestingly the frequency of GG haplotype was inverse, 9.9% and 45.2% was

observed in patients and controls respectively Figure 4.15. The haplotypes AA and

GG showed distinct difference both in women with endometriosis and controls (Table

4.12). The pairwise LD value was 0.76 for both sites. This r2 value suggests that these

two polymorphisms are in strong linkage disequilibrium (Figure 4.16).

108


Query 93 TCTTCAGCTCCCAGAGTCACCAGTGGTTCCACTTACATACTTGTCCCTCTAAGTCATTTA 152

|||||||||||||||||||||| |||||||||||||||||||||||||||||||||||||

Sbjct 62 TCTTCAGCTCCCAGAGTCACCAATGGTTCCACTTACATACTTGTCCCTCTAAGTCATTTA 121

Query 153 GCCCAAAACTAAAACACAATGTGAAAATGTATCTGAGTATTGAATGATAATTCAGTCTTG 212

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 122 GCCCAAAACTAAAACACAATGTGAAAATGTATCTGAGTATTGAATGATAATTCAGTCTTG 181

(b) Alignment of two sequences BLAST (Control) Query 95 TTCAGCTCCCAGAGTCACCAGTGGTTCCACTTACATACTTGTCCCTCTAAGTCATTTAGC 154

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 66 TTCAGCTCCCAGAGTCACCAGTGGTTCCACTTACATACTTGTCCCTCTAAGTCATTTAGC 125

Query 155 CCAAAACTAAAACACAATGTGAAAATGTATCTGAGTATTGAATGATAATTCAGTCTTGCC 214

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 126 CCAAAACTAAAACACAATGTGAAAATGTATCTGAGTATTGAATGATAATTCAGTCTTGCC 185

Figure 4.13: Two sequence BLAST alignment of FSHR gene polymorphisms.


form of A/G base substitution of rs6166.

A

AG

109


endometriosis and controls at FSHR gene.

45.5

21.8 22.8

9.9

16.3

21.2

17.3

45.2

0

5

10

15

20

25

30

35

40

45

50

AA GA AG GG

Perc

en

t fr

eq

uen

cy (

%)

Haplotypes

Affected

Control

110

Table 4.11: Frequency distribution of single nucleotide polymorphisms of FSHR gene with risk of endometriosis in Pakistani women.


frequencies

Endometriosis

(n= 52)

Controls

(n= 52)


n % n %

rs6166 AA 24 46.2 6 11.5 6.570

(A>G) AG 23 44.2 23 44.2 (2.39-18.01) 13.53 0.001 >.05

Exon 10 GG 5 9.6 23 44.2

Allele frequency

A Allele 71 68.3 35 33.7 4.240

G Allele 33 31.7 69 66.3 (2.37- 7.57) 23.56 0.001 >.05

E(HET) 43 45

rs6165 AA 24 46.2 7 13.5 5.511

(A>G) AG 22 42.3 25 48.1 (2.09-14.46) 11.76 0.001 >.05

Exon 10 GG 6 11.5 20 38.5

Allele frequency

A Allele 70 67.3 39 37.5 3.430

G Allele 34 32.7 65 62.5 (1.94-6.07) 17.35 0.001 >.05

E(HET) 44 47


111

Table 4.12: Multi-SNPs haplotype frequency estimates for endometriosis and controls at FSHR gene.


Het

Global LD

LRChiSq

p Genetic

Heterogeneity

Test

AA GA AG GG Chi Sq p

Endometriosis 0.455±0.049 0.218±0.041 0.228±0.041 0.099±0.029 68.90 0.00 >0.05

38.60 0.001 Control 0.163±0.051 0.212±0.061 0.173±0.054 0.452±0.049 69.90 1.00 >0.05


FSHR Endometriosis

FSHR Control rs

616

6

rs6165

rs6169

rs6166

rs6165

rs6169

Figure 4.16: Pairwise linkage disequilibrium of FSHR gene polymorphisms in endometriosis and controls.

.11

.04 .76

.04

.01 .13

112

4.4 PCOS

The SNPs of ADIPOQ, INSR, FSHR, FSHB, LHCGR, LHB, ESR1 and ESR2 genes

were investigated in PCOS Pakistani women.

4.4.1 Adiponectin (ADIPOQ)

To determine whether the adiponectin SNP loci at exon 2 (45T→G) and Intron 2

(276G→T) were associated with PCOS; we initially compared the single-point

genotype and allele distribution of these SNPs in the PCOS and control groups. The

mutations of ADIPOQ gene in two sequence BLAST alignment are shown in Figure

4.17. The sequence chromatogram showed homozygous and heterozygous form of

T/C base substitution of rs2241766 (Figure 4.18). We observed an association of

ADIPOQ gene polymorphism and PCOS group, the gene and allele frequencies are

given in Table 4.13. Seventy five subjects were homozygous for rs2241766 T allele,

20 were heterozygous GT and there was 1 subject homozygous for G in PCOS group.

The ADIPOQ rs2241766 “TT” genotype compared with “TG and GG” genotypes was

associated with a 3.725 folds increased risk for PCOS in the study population (p <

0.001, OR = 3.725, 95% CI = 1.98-6.97). Furthermore, the ADIPOQ rs2241766

mutant allele “T” was significantly overexpressed (3.345 folds) in women with PCOS

(88.5%) than controls (69.8%), (p < 0.001, OR = 3.345, 95% CI = 1.95-5.74). In

rs1501299 the homozygous TT genotype and heterozygous TG genotype was

infrequent both in PCOS and controls (Table 4.13), the TT and TG was combined

together as referred variants genotype of rs1501299. The frequency of variant

genotype of rs1501299 was different in both groups. We did find a moderate

significant association between different genotypes (Table 4.13) in both the groups. In

SNP rs1501299 the frequency of T allele was higher in PCOS patient (23.4% vs.

15.1%, p = 0.050, OR = 0.581, 95% CI = 0.34-0.97). In the ADIPOQ PCR products

DNA sequencing map, we found a new SNP rs2241767 in ADIPOQ gene at +345

coding reference gene positions in intron 2, in which the substitution is A to G. In

PCOS group, there were 2 homozygous “GG” of this new SNP and heterozygous

frequency was higher in PCOS than that in controls (26% vs. 14.6%; p = 0.030, OR =

0.436, 95% CI = 0.21-0.89). On 3q27.3, the most significant SNP was rs2241766

which locates in the exon 2 of ADIPOQ gene.

113

Haplotype estimation analysis of three SNPs genotype data by means of maximum

likelihood method revealed that estimated overall haplotype frequencies in PCOS and

controls groups differ significantly (Table 4.14). Seven major haplotypes of ADIPOQ

were present in the study population (Figure 4.19). The frequency of most common

haplotypes TGA, TTA, GGA and GGG was 63.9%, 22.1%, 0.00% and 10.9 % in

PCOS; while 53.7%, 12.0%, 24.2% and 3.0% in controls groups (p < 0.001, LR Chi

Sq = 79.100, 3.200 respectively in PCOS and controls). Whereas in single haplotype

association the TGA, TTA and GGG are more frequent in PCOS group, while the

haplotype GGA was found only in controls group (Figure 4.19). The other low

frequencies haplotypes showed borderline difference. So the null hypothesis that the

haplotype frequency distributions of the two groups are the same is rejected strongly.

The genetic heterogeneity test showed a strong significance (p < 0.001, χ2

= 69.4)

between PCOS and controls. In order to study the linkage disequilibrium between

exon 2 and intron 2 loci, we performed pairwise LD analysis between rs2241766,

rs1501299 and rs2241767. The R-squared or Delta-squared value for the PCOS

between rs2241766 and rs2241767 was 0.78 (p < 0.001) and for the Control group

was 0.06 (p < 0.001). This revealed very strong LD for the pair of loci which are

located approximately 300 bp from each other and haplotype correlate well in the

PCOS group as compared to the control group (Figure 4.20). The polymorphisms in

the ADIPOQ were in linkage disequilibrium.

114

(a) Alignment of two sequences BLAST (PCOS)

Query 105 GCTCAGGATGCTGTTGCTGGGAGCTGTTCTACTGCTATTAGCTCTGCCCGGTCATGACCA 164

||||||||||||||||||||||||||||||||||||||||||||||||||| ||||||||

Sbjct 79 GCTCAGGATGCTGTTGCTGGGAGCTGTTCTACTGCTATTAGCTCTGCCCGGGCATGACCA 138

Query 165 GGAAACCACGACTCAAGGGCCCGGAGTCCTGCTTCCCCTGCCCAAGGGGGCCTGCACAGG 224

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 139 GGAAACCACGACTCAAGGGCCCGGAGTCCTGCTTCCCCTGCCCAAGGGGGCCTGCACAGG 198

(b) Alignment of two sequences BLAST (Control)

Query 105 GCTCAGGATGCTGTTGCTGGGAGCTGTTCTACTGCTATTAGCTCTGCCCGGTCATGACCA 164

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 75 GCTCAGGATGCTGTTGCTGGGAGCTGTTCTACTGCTATTAGCTCTGCCCGGTCATGACCA 134

Query 165 GGAAACCACGACTCAAGGGCCCGGAGTCCTGCTTCCCCTGCCCAAGGGGGCCTGCACAGG 224

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 135 GGAAACCACGACTCAAGGGCCCGGAGTCCTGCTTCCCCTGCCCAAGGGGGCCTGCACAGG 194

Figure 4.17: Two sequence BLAST alignment of ADIPOQ gene polymorphisms.


form of T/G base substitution of rs2241766.

T

TG

115

Figure 4.19: Multi-SNPs haplotype percent frequency distribution for PCOS and

controls at ADIPOQ gene.

63.9

22.1

0

10.9

1.8 0.5 0.8

53.7

12

24.2

3 4.2 2.90

0

10

20

30

40

50

60

70

TGA TTA GGA GGG TGG GTA TTG

Perc

en

t fr

eq

uen

cy (

%)

Haplotypes

Affected

Control

116

Table 4.13: Frequency distribution of single nucleotide polymorphisms of ADIPOQ gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs2241766 TT 75 78.1 47 49 3.725

(T>G) GT 20 20.8 40 41.7 (1.98-6.97) 16.39 0.001 >.05

Exon 2 GG 1 1 9 9.4

Allele frequency

T Allele 170 88.5 134 69.8 3.345

G Allele 22 11.5 58 30.2 (1.95-5.74) 19.34 0.001 >.05

E(HET) 20 42

rs1501299 GG 56 58.3 69 71.9 0.548

(G>T) TG 35 36.5 25 26 (0.30-1.00) 3.30 0.060 >.05

Intron 2 TT 5 5.2 2 2.1

Allele frequency

T Allele 45 23.4 29 15.1 0.581

G Allele 147 76.6 163 84.9 (0.34-0.97) 3.77 0.050 >.05

E(HET) 36 26

rs2241767 AA 69 71.9 82 85.4 0.436

(A>G) GA 25 26 14 14.6 (0.21-0.89) 4.46 0.030 >.05

Intron 2 GG 2 2.1 0 0

Allele frequency

A Allele 163 86.5 178 92.7 1.262

G Allele 29 13.5 14 7.3 (0.22-0.86) 5.13 0.020 >.05

117

Table 4.14: Multi-SNPs haplotype frequency estimates for PCOS and controls at ADIPOQ gene.


Het

Global LD

LR ChiSq

p Genetic

Heterogeneity

Test

TGA TTA GGA GGG TGG GTA TTG Chi Sq p

PCOS 0.639

±

0.035

0.221

±

0.030

0.000

±

0.000

0.109

±

0.023

0.018

±

0.010

0.005

±

0.005

0.008

±

0.006

53.10 79.10 0.001

69.40 0.001 Control 0.537

±

0.039

0.120

±

0.027

0.242

±

0.031

0.030

±

0.017

0.042

±

0.017

0.029

±

0.003

0.000

±

0.000

63.60 3.20 0.050


118

ADIPOQ PCOS

ADIPOQ Control

rs2241766

rs1501299

rs2241767

rs2241766

rs1501299

rs2241767

Figure 4.20: Pairwise linkage disequilibrium of ADIPOQ gene in PCOS and

controls.

.78

.06 .04

.04

.01 .03

119

4.4.2 Insulin receptor (INSR)

INSR gene was analyzed for rs1799817, rs1799815 of exon 17 and SNPs rs2059806,

rs2229429 of exon 8 by direct sequencing. This revealed presence of association of

these polymorphisms with PCOS as shown in Table 4.15. In SNP rs1799817 a silent

polymorphism C/T SNP at 1085 site (His-His) was observed. The genotype and allele

frequencies are shown in Table 4.15. In contrast the frequency of “C” (76% in PCOS

and 57.8% in controls) and “T” (24% in PCOS and 42.2% in controls) allele differ

significantly in PCOS and control groups (p < 0.001, OR = 2.316, 95% CI = 1.45-

3.59). The frequency of CC genotype was overrepresented as compared to CT_TT

genotype in PCOS (p < 0.001, OR = 2.935, 95% CI = 1.62-5.29). We also observed

another novel polymorphism in exon 17 rs1799815. The frequency of CC, CT and TT

genotypes is shown in Table 4.15. The frequency of “T” and “C” allele differ

significantly between PCOS and control group (p = 0.05, OR = 0.261, 95% CI = 0.07-

0.95). We analyzed exon 8 for polymorphism rs2059806 (G/A). In SNP rs2059806

the genotype and allele frequency of GG, GA and AA in PCOS and controls is shown

in Table 4.15. The frequency of “A” allele was high in PCOS group as compared to

controls (24% vs. 16.1%, p = 0.030, OR = 0.520, 95% CI = 0.34-0.92) and was

statistically significant. During the screening of exon 8 we found another SNP

rs2229429. The genotype distribution of rs2229429 C/T polymorphism in PCOS

group was significantly different from that of controls.

120


controls at INSR gene.

121

Table 4.15: Frequency distribution of single nucleotide polymorphisms of INSR gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs1799817 CC 56 58.3 31 32.3 2.935

(C>T) TC 34 35.4 49 51 (1.62-5.29) 12.1 0.001 >.05

Exon 17 TT 6 6.3 16 16.7

Allele frequency

C Allele 146 76 111 57.8 2.316

T Allele 46 24 81 42.2 (1.45-3.59) 13.6 0.001 >.05

E(HET) 36 49

rs1799815 CC 86 89.5 93 96.8 0.277

(C>T) TC 9 9.3 3 3.1 (0.07-1.04) 2.97 0.080 >.05

Exon 17 TT 1 1.9 0

Allele frequency 0

C Allele 181 94.2 189 98.4 0.261

T Allele 11 5.7 3 1.6 (0.07-0.95) 3.63 0.050 >.05

E(HET) 6 3

rs2059806 GG 54 58.7 67 72.8 0.557

(G>A) AG 35 38 27 29.3 (0.30-1.00) 3.21 0.070 >.05

Exon 8 AA 7 7.6 2 2.2

122

Table continues……………

Allele frequency

G Allele 143 76 161 83.9 0.520

A Allele 49 24 31 16.1 (0.34-0.92) 4.56 0.030 >.05

E(HET) 37 29

rs2229429 CC 33 38 57 59.4 0.358

(C>T) CT 45 46.8 35 36.4 (0.19-0.64) 11.06 0.001 >.05

Exon 8 TT 18 18.7 4 4.1

Allele frequency

C Allele 111 57.8 149 77.6 0.395

T Allele 81 42.2 43 22.4 (0.25-0.61) 16.31 0.001 >.05

E(HET) 49 35


123

Table 4.16: Multi-SNPs haplotype frequency estimates for PCOS and controls at INSR gene.



Het

Global LD

LR Chi Sq

p Genetic

Heterogeneity

Test

CGC CGT TGC CAC TGT TAC CAT TAT Chi Sq p

PCOS 0.308

±

0.033

0.27

±

0.032

0.139

±

0.025

0.105

±

0.022

0.044

±

0.015

0.027

±

0.019

0.078

±

0.019

0.029

±

0.012

79.30 2.30 1.000

54.60 0.001 Control 0.401

±

0.045

0.101

±

0.034

0.214

±

0.038

0.076

±

0.021

0.122

±

0.031

0.086

±

0.021

0.000

±

0.00

0.000

±

0.000

75.50 11.70 0.050

124

INSR PCOS

INSR Control

rs1799817

rs2059806

rs2229429

rs1799817

rs2059806

rs2229429

Figure 4.22: Pairwise linkage disequilibrium of INSR gene in PCOS and

controls.

.07

.06 .04

.04

.01 .03

125

A similar trend toward association with features of insulin resistance was observed for

the “TT and CT” genotype at position 1638 (Table 4.15). There was also a significant

difference in the “C” (57.8% in PCOS vs. 77.6% in controls) and “T” (42.2% in PCOs

vs. 22.4% in controls) allele frequencies between the two groups (p < 0.001, OR =

0.395, 95% CI = 0.25-0.61).

Single point analysis was expanded to pair of loci haplotype analysis to depict the

estimated haplotype frequencies of the three SNPs of INSR gene of unknown phase in

the PCOS and control groups. Much stronger associations were observed when the

three SNPs were considered together as haplotypes. The SNP rs1799815 was

excluded from haplotype analysis due to low variations. When the estimated

haplotype frequencies were compared between PCOS and controls, the most common

haplotype CGC (0.401 vs. 0.308 in controls and PCOS respectively) and TGC (0.214

vs. 0.139 in controls and PCOS respectively) was found to be more prevalent in the

control group, whereas the CGT (0.270 vs. 0.101 in PCOS and controls respectively),

CAC (0.105 vs. 0.076 in PCOS and controls respectively) and CAT (0.078 vs. 0.000

in PCOS and controls respectively) was more common among PCOS patients (Table

4.16; Figure 4.21). So the null hypothesis that the haplotype frequency distributions of

the two groups are the same is rejected strongly. The genetic heterogeneity test

showed strong association (p < 0.001, χ2

= 54.6). In order to study the extent of

linkage disequilibrium between exon 17 and exon 8 loci, we performed pairwise LD

analysis. The pairwise LD analysis revealed week LD for the pairs of loci in the

PCOS and control group (Figure 4.22).


Genotype distribution of genes encoding sex hormones and hormones regulator SNPs

rs6166 and rs6165 are shown in Table 4.17. The allele “A” and “G” frequencies of

SNP rs6166 were not different between PCOS and controls (p = 0.350, OR = 1.232,

95% CI = 0.85-1.84). We also did not find any statistically significant differences in

the genotypes and allele frequencies between PCOS and controls for rs6165 in exon

10 (p = 0.470, OR = 1.181, 95% CI = 0.79-1.76). Haplotype-specific tests for

association were also performed. Four major haplotypes of FSHR were present in the

study population (Table 4.18). The haplotype frequencies were significantly different

between the patients and controls for the two SNPs as shown in Figure 4.23.

126

The haplotype “AA” (0.504 vs. 0.305 in PCOs and controls) and “GG” (0.431 vs.

0.326 in PCOs and controls) were more common in PCOS while haplotype “GA”

(0.022 vs. 0.179 in PCOs and controls) and “AG” (0.043 vs. 0.190 in PCOs and

controls) were frequent in controls (p < 0.001, LR Chi Sq=117.4, 6.1 respectively in

PCOS and controls). The genetic heterogeneity test gives a p-value of <0.001 (Table

4.18). To calculate the extent of LD in pairwise combinations of the SNPs, we

calculate LD value. The pairwise LD values were 0.76 (p < 0.001) for both sites

which are situated in exon 10 within only hundreds of bases of each other (Figure

4.24).

127


controls at FSHR gene.

128

Table 4.17: Frequency distribution of single nucleotide polymorphisms of FSHR gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs6166 AA 29 30.2 24 25 0.777

(A>G) AG 47 48.9 47 48.9 (0.40-1.45) 0.41 0.510 >.05

Exon 10 GG 20 20.8 25 26

Allele frequency

A Allele 105 54.7 95 49.5 1.232

G Allele 87 45.3 97 50.5 (0.85-1.84) 0.85 0.350 >.05

E(HET) 50 50

rs6165 AA 27 28.1 22 22.9 1.310

(A>G) AG 47 48.9 49 51 (0.68-2.52) 0.44 0.500 >.05

Exon 10 GG 22 22.9 25 26

Allele frequency

A Allele 101 52.6 93 48.4 1.181

G Allele 91 47.4 99 51.6 (0.79-1.76) 0.51 0.470 >.05

E(HET) 50 50


129

Table 4.18: Multi-SNPs haplotype frequency estimates for PCOS and controls at FSHR gene.


Het

Global LD

LR Chi Sq

p Genetic

Heterogeneity

Test

AA GG GA AG Chi Sq p

PCOS 0.504±0.036 0.431±0.036 0.022±0.028 0.043±0.028 55.70 117.40 0.001

58.30 0.001 Control 0.305±0.042 0.326±0.038 0.179±0.037 0.190±0.035 73.30 6.10 0.050


FSHR PCOS

FSHR Control

rs6166

rs6165

rs6169

rs6166

rs6165

rs6169

Figure 4.24: Pairwise linkage disequilibrium of FSHR gene in PCOS and controls.

.03

.04 .76

.04

.01 .07

130

4.4.4 Follicle stimulating hormone beta (FSHB)

FSHB gene was analyzed for SNP rs6169 T/C in exon 3. The mutations of FSHB gene

in two sequence BLAST alignment are shown in Figure 4.25. The sequence

chromatogram showed homozygous and heterozygous form of T/C base substitution

of rs6169 (Figure 4.26).Genotype and allele frequencies were significantly different

for PCOS and controls. A statistically significant (p < 0.005) higher frequency of the

“T” allele was observed in patients than in controls (Table 4.19). The frequency of

“C” (34.4% in PCOS and 46.4% in controls) and “T” (65.6% in PCOS and 53.6% in

controls) allele differ significantly in PCOS and control groups (p= 0.020, OR= 0.606,

95% CI= 0.40-0.91). The frequency of TT genotype was overrepresented as compared

to CT_CC genotype in PCOS (p = 0.020, OR = 2.094, 95% CI = 1.14-3.83).

131

(a) Alignment of two sequences BLAST (PCOS) Query 94 CTCAGGATCTGGTGTATAAGGACCCAGCCAGGCCCAAAATCCAGAAAACATGTACCTTCA 153

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 61 CTCAGGATCTGGTGTATAAGGACCCAGCCAGGCCCAAAATCCAGAAAACATGTACCTTCA 120

Query 154 AGGAACTGGTATACGAAACAGTGAGAGTGCCCGGCTGTGCTCACCATGCAGATTCCTTGT 213

||||||||||||| ||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 121 AGGAACTGGTATATGAAACAGTGAGAGTGCCCGGCTGTGCTCACCATGCAGATTCCTTGT 180

(b) Alignment of two sequences BLAST (Control) Query 94 CTCAGGATCTGGTGTATAAGGACCCAGCCAGGCCCAAAATCCAGAAAACATGTACCTTCA 153

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 61 CTCAGGATCTGGTGTATAAGGACCCAGCCAGGCCCAAAATCCAGAAAACATGTACCTTCA 120

Query 154 AGGAACTGGTATACGAAACAGTGAGAGTGCCCGGCTGTGCTCACCATGCAGATTCCTTGT 213

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 121 AGGAACTGGTATACGAAACAGTGAGAGTGCCCGGCTGTGCTCACCATGCAGATTCCTTGT 180

Figure 4.25: Two sequence BLAST alignment of FSHB gene polymorphisms.


form of T/C base substitution of rs6169.

T

TC

132

Table 4.19: Frequency distribution of single nucleotide polymorphisms of FSHB gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs6169 TT 42 43.7 26 27 2.094

(T>C) CT 42 43.7 51 53.1 (1.14-3.83) 5.12 0.020 >.05

Exon 3 CC 12 13.5 19 19.7

C Allele 66 34.4 89 46.4 0.606

T Allele 126 65.6 103 53.6 (0.40-0.91) 5.24 0.020 >.05

E(HET) 45 50


133

4.4.5 Luteinizing hormone choriogonadotropin receptor (LHCGR)

LHCGR gene on region 2p16.3 was analyzed for rs61996318. Heterozygotes CA were

greater in patients (16.6%) than controls (7.2%). As the homozygous AA genotype

and heterozygous CA genotype was rare both in cases and controls (Table 4.20), the

AA and CA were combined together and are referred as variants genotype of

rs6199318. The frequency of variant genotype of rs6199318 was different in both

groups. We did find a significant association between different genotypes (Table

4.20). In SNP rs61996318 the genotype frequencies CC, CA and AA were 82.2%

(79/96), 16.6% (16/96), 1.0% (01/96) in PCOS whereas 92.7% (89/96), 7.2% (07/96)

and 0% (0/96) in controls. Although the genotype and allele frequencies showed little

variations but these were statistically significant (p = 0.030, OR = 1.366, 95% CI =

0.14-0.89).

A novel SNP in LHCGR

In LHCGR PCR product DNA sequencing map, we found a new SNP at 48941073

nucleotide position, where there was a loss of base “A” in which the gene sequence

changes at AGCC A GAG. In PCOS group, there were 28 homozygous of this new

SNP and in controls there were 6. Heterozygotes D/T was greater in patients (50%)

than controls (36.4%) which increased the risk of disease. A statistically significant

higher frequency of the “missing” allele was observed in patients than in controls

(54.2% vs. 24.5%, p < 0.001, OR = 1.270, 95% CI = 0.18-0.42). As the homozygous

D/D genotype and heterozygous D/T genotype was prevalent in PCOS (Table 4.20),

the D/D and D/T was combined together and referred as variants genotype of this new

SNP. The frequency of variant genotype of new SNP was different in both groups

(76/96 vs. 41/96 in PCOS and controls respectively). The frequency of D/D genotype

was overrepresented as compared to TT_DT genotype in PCOS (p < 0.001, OR =

1.220, 95% CI = 0.11-0.43).

The haplotype analysis revealed that the most common haplotype “TC” was frequent

in controls as compared with PCOS group (72.4% vs. 40.9% in controls and PCOS

respectively) (Figure 4.27). Whereas the other three nonzero haplotypes; DC (0.497

vs. 0.239 in PCOS and controls), TA (0.049 vs. 0.031 in PCOS and controls) and DA

(0.045 vs. 0.006 in PCOS and controls) were more common in PCOS group (Table

4.21). The genetic heterogeneity test showed strong significance (p < 0.001,

134


controls at LHCGR gene.

135

Table 4.20: Frequency distribution of single nucleotide polymorphisms of LHCGR gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs61996318 CC 79 82.2 89 92.7 0.365

(C>A) CA 16 16.6 7 7.2 (0.14-0.92) 3.86 0.050 >.05

Exon AA 1 1 0 0

Allele frequency

C Allele 174 90.6 185 96.4 1.366

A Allele 18 9.4 7 3.6 (0.14-0.89) 4.28 0.030 >.05

E(HET) 17 7

rs111834744

TT 20 20.8 55 57.2 1.220

(D>T) DT 48 50 35 36.4 (0.11-0.43) 20.3 0.001 >.05

Intron DD 28 29.1 6 6.2

Allele frequency

T Allele 88 45.8 145 75.5 1.270

D Allele 104 54.2 47 24.5 (0.18-0.42) 34.22 0.001 >.05

E(HET) 50 37


136

Table 4.21: Multi-SNPs haplotype frequency estimates for PCOS and controls at LHCGR gene.


LR ChiSq

p Genetic

Heterogeneity

Test

TC DC TA DA Chi Sq p

PCOS 0.409±0.036 0.497±0.035 0.049±0.015 0.045±0.016 58.10 0.20 0.05

40.80 0.001 Control 0.724±0.034 0.239±0.035 0.031±0.010 0.006±0.015 47.70 0.10 0.05


Figure 4.28: Pairwise linkage disequilibrium of LHCGR gene in PCOS and controls.

LHCGR PCOS

LHCGR PCOS

rs61996318

rs111834744

rs61996318

rs111834744

.26

0 0

.04

0 0

137

χ2

= 40.8) between the PCOS and control groups. The pairwise LD values were week

for both sites (Figure 4.28).

4.4.6 Luteinizing hormone beta (LHB)

The LHB was analyzed for two polymorphisms rs1800447 and rs4002462. The

mutations of LHB gene in two sequence BLAST alignment are shown in Figure 4.29.

The sequence chromatogram showed homozygous and heterozygous form of T/C base

substitution of rs4002462 (Figure 4.30). Overall, there was no statistically significant

(p > 0.05) difference in the distribution of either polymorphism between PCOS and

controls, the genotype frequency and allele frequency showed little variations among

both groups. This indicate that individual polymorphism of LHB may not be

associated with increased risk of PCOS (Table 4.22). Haplotype-specific tests for

association were also performed. Three major haplotypes of LHB were present in the

study population (Table 4.23).

However the haplotype analysis showed that the most common haplotype “AC”

(94.3% vs. 86.5%) was more frequent in controls than in PCOS (Figure 4.31).

Whereas, the haplotypes “AT and GC” were frequent in PCOS group (Table 4.23).

The genetic heterogeneity test showed a border line significance among the two

groups (p = 0.05, χ2

= 6.7). The pair wise LD analysis revealed no significant

association (Figure 4.32).

138

(a) Alignment of two sequences BLAST (PCOS) Query 94 CTGTTTCTTTCAGTTTCTTCCCATTCCTAAACCCTCTCCTCCCTCCTTCAGCAAACTATA 153

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 60 CTGTTTCTTTCAGTTTCTTCCCATTCCTAAACCCTCTCCTCCCTCCTTCAGCAAACTATA 119

Query 154 TGGAAATGGATTTGAAGAAGTAAAAAGTCATGCATTCAATGGGACGACACTGACTTCACT 213

|||||||||||||||||||||| |||||||||||||||||||||||||||||||||||||

Sbjct 120 TGGAAATGGATTTGAAGAAGTAGAAAGTCATGCATTCAATGGGACGACACTGACTTCACT 179

(b) Alignment of two sequences BLAST (Control) Query 99 TCTTTCAGTTTCTTCCCATTCCTAAACCCTCTCCTCCCTCCTTCAGCAAACTATATGGAA 158

||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 65 TCTTTCAGTTTCTTCCCATTCCTAAACCCTCTCCTCCCTCCTTCAGCAAACTATATGGAA 124

Query 159 ATGGATTTGAAGAAGTAGAAAGTCATGCATTCAATGGGACGACACTGACTTCACTGTAAG 218

|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||

Sbjct 125 ATGGATTTGAAGAAGTAGAAAGTCATGCATTCAATGGGACGACACTGACTTCACTGTAAG 184

Figure 4.29: Two sequence BLAST alignment of LHB gene polymorphisms.


form of A/G base substitution of rs4002462.

G

AG

139


controls at LHB gene.

140

Table 4.22: Frequency distribution of single nucleotide polymorphisms of LHB gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs1800447 CC 80 83.3 88 91.7 0.450

(C>T) TC 15 15.6 8 8.3 (0.18-1.40) 2.33 0.140 >.05

Exon TT 1 1 0 0

Allele frequency

A Allele 183 95.3 189 98.4 0.323

G Allele 9 4.7 3 1.6 (0.08-1.21) 2.15 0.120 >.05

E(HET) 9 3

rs4002462 AA 87 90.6 93 96.9 0.312

(A>G) AG 9 9.4 3 3.1 (0.08-1.11) 2.22 0.130 >.05

Intron GG 0 0 0 0

Allele frequency

A Allele 175 91.1 184 95.8 0.448

G Allele 17 8.9 8 4.2 (0.18-1.06) 2.74 0.090 >.05

E(HET) 16 8


141

Table 4.23: Multi-SNPs haplotype frequency estimates for PCOS and controls at LHB gene.


LR ChiSq

p Genetic

Heterogeneity

Test

AC AT GC ChiSq p

PCOS 0.865±0.025 0.088±0.020 0.046±0.015 24.10 0.30 1.000

6.70 0.050 Control 0.943±0.017 0.042±0.014 0.016±0.009 10.90 0.30 1.000


Figure 4.32: Pairwise linkage disequilibrium of LHB gene in PCOS and controls.

LHB PCOS

LHB PCOS rs

1800447

rs4002462

rs1800447

rs4002462

.08

0 0

.04

0 0

142


The contribution of the genomic variants of ESR1 was studied for seven SNPs. The

genotype distribution and relative allele frequencies for ESR1 gene polymorphisms

are shown in Table 4.24. Twenty two subjects were homozygous for rs2234693 C

allele, 47 were heterozygous and there were 27 subjects homozygous for T allele. The

frequency of the rs2234693 “C” allele was 47.4% in the PCOS and 32.8 % in the

control group. Significant differences were observed for comparative genotype

distribution and relative allele frequencies of SNP rs2232693 between PCOS and

controls (p < 0.005, OR = 1.845, 95% CI = 1.22-2.79, χ2

= 7.90). We had also find

statistically significant differences in the genotypes and allele frequencies between

PCOS and control group for rs9340799 (p < 0.010, OR = 1.688, 95% CI = 0.96-2.19,

χ2

= 5.74).

A new SNP rs8179176 was found during the screening of DNA sequencing map. Two

were homozygous for new SNP T allele, 23 were heterozygous and there were 71

subjects homozygous for C. Heterozygotes CT were greater in patients (24%) than

controls (10.4%). As the homozygous TT genotype and heterozygous CT genotype

was rare both in cases and controls, the AA and GA were combined together and are

referred as variants genotype of this new SNP. The frequency of variant genotype of

was different in both groups. The frequency of the rs8179176 “T” allele was 14.1 %

in the patients and 5.2% in the control group. Comparison of frequencies between

patients and control groups show statistically difference between them (P < 0.006, OR

= 1.336, 95% CI= 0.15-0.71, χ2

= 7.66). This suggested that these genetic variants are

related in the occurrence of PCOS in Pakistani women. However the genotype and

allele frequencies of SNPs rs11155816, rs4986936 and rs4986937 were not

significantly different between PCOS women and controls (Table 4.24).

Interestingly, the haplotype analysis showed distinct variations among PCOS and

control groups. Two haplotypes “AT and GC” are more frequent in PCOS whereas

the other two haplotypes “AC and GT” are common in controls (Table 4.25; Figure

4.33). Also the genetic heterogeneity test showed a highly significant association

between PCOS and controls (p < 0.001, χ2

= 75.5). LD value between rs2234693 and

rs9340799 was 0.46 (p < 0.001) in PCOS group which are located 51 bp from each

other. This showed a strong LD for the pair of loci and haplotype correlate well in the

PCOS group as compared to the control group (Figure 4.34).

143


controls at ESR1 gene.

144

Table 4.24: Frequency distribution of single nucleotide polymorphisms of ESR1 gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs2234693 TT 27 28.1 43 44.8 0.482

(C>T) CT 47 49 43 44.8 (0.26-0.87) 5.05 0.020 >.05

Intron 1 CC 22 22.9 10 10.4

Allele frequency

C Allele 91 47.4 63 32.8 1.845

T Allele 101 52.6 129 67.2 (1.22-2.79) 7.90 0.005 >.05

E(HET) 49 45

rs9340799 AA 28 29.2 42 43.8 0.529

(G>A) GA 47 49 43 44.8 (0.29-0.96) 3.80 0.050 >.05

Intron 1 GG 21 21.9 11 11.5

Allele frequency

G Allele 89 46.4 65 33.9 1.688

A Allele 103 53.6 127 66.1 (0.96-2.19) 5.74 0.010 >.05

E(HET) 49 45

rs8179176 CC 71 74 86 89.6 0.330

(C>T) CT 23 24 10 10.4 (0.40-0.73) 6.85 0.009 >.05

Intron 1 TT 2 2.1 0 0

Allele frequency

C Allele 165 85.9 182 94.8 1.336

T Allele 27 14.1 10 5.2 (0.15-0.71) 7.66 0.006 >.05

145

Table continues………………..

E(HET) 24 10

rs11155816 CC 81 84.4 87 90.6 0.559

(C>T) TC 14 14.6 9 9.4 (0.23-1.34) 1.19 0.210 >.05

Intron TT 1 1 0 0

Allele frequency

T Allele 16 8.3 9 4.7 1.848

C Allele 176 91.7 183 95.3 (0.79-4.29) 1.54 0.215 >.05

E(HET) 15 9

rs11155815

TT 66 68.8 75 78.1 0.616

(C>T) CT 28 29.2 20 20.8 (0.32-1.17) 1.70 0.180 >.05

Intron CC 2 2.1 1 1

Allele frequency

C Allele 160 83.3 170 88.5 0.647

T Allele 32 16.7 22 11.5 (0.36-1.16) 1.75 0.186 >.05

E(HET) 28 20

rs4986936 TT 86 89.6 94 97.9 0.183

(G>A) CT 10 10.4 2 2.1 (0.03-0.85) 4.35 0.031 >.05

Intron CC 0 0 0 0

Allele frequency

C Allele 10 5.2 2 99 5.22

T Allele 182 94.8 190 1 (1.12-24.14) 4.21 0.040 >.05

E(HET) 10 2

146

Table continues………………..

rs4986937 GG 89 92.7 93 96.9 0.41 >.05

(C>T) AG 7 7.3 3 3.1 (0.10-1.63) 0.95 0.310

AA 0 0 0 0

Allele frequency

G Allele 185 96.4 189 98.4 0.42

A Allele 7 3.6 3 1.6 (0.10-1.64) 0.92 0.336 >.05

E(HET) 7 3

SNPs ID: single nucleotide polymorphism identity; OR: Odd ratios; CI: Confidence interval; p: Significance; HWE: Hardy Weinberg Equilibrium;

χ2: Chi square.

147

Table 4.25: Multi-SNPs haplotype frequency estimates for PCOS and controls at ESR1 gene.


LR ChiSq

p Genetic

Heterogeneity

Test

AT AC GT GC Chi Sq p

PCOS 0.479±0.036 0.073±0.035 0.084±0.020 0.364±0.019 62.60 62.30 0.001

75.50 0.001 Control 0.384±0.042 0.267±0.029 0.267±0.038 0.082±0.039 70.30 2.70 0.060


148

ESR1 PCSO

rs4986936

rs11155815

rs8179176

rs2234693

rs11155816

rs9340799

rs4986937

ESR1 Control

rs4986936

rs11155815

rs8179176

rs2234693

rs11155816

rs9340799

rs4986937

Figure 4.34: Pairwise linkage disequilibrium of ESR1 gene in PCOS and

controls.

.10

.22

.13

.10

.20 .06

.10

.12 .11 .1

.11

.02

.16

.11

.04

.26

.15 .10 .22

.41

.12

.22

.10

.02

.06

.10 .03

.02

.12 .11 .14

.04

.05

.02

.02

.04

.02

.02 .02 .02

.20

.02

.02

.02

149


The ESR2 gene was studied for polymorphism rs4986938 which is a G→A change at

position 1859 in the 3′-untranslated region (3′-UTR) of exon 8. The genotype

frequency of G/A polymorphism in PCOS group was significantly different from that

of controls. The mutant allele “A” was in significantly higher frequency among the

cases (41.7%) compared to the controls (27.6%) yielding an odds ratio of 0.534 (p =

0.005, 95% CI = 0.35-0.81, χ2

= 7.78). As the homozygous GG genotype was more

frequent in controls (52.1%) compared with (34.4%) in PCOS (Table 4.26). The

heterozygous GA genotype and the AA were combined together and are referred as

variants genotype of rs4986938. The frequency of variant genotype of rs4986938 was

different in both groups (63/96 vs. 46/96 in PCOS and controls respectively).

4.5 Hormonal analysis

The results regarding the hormonal levels in controls, endometriosis and PCOS

women are given in the following paragraphs.

4.5.1 Follicle stimulating hormone (FSH)

FSH levels (mIU/ml) in controls and PCOS women were different from each

other. The difference between the 2 groups was significant statistically (p < 0.005).

The detail can be seen in Figure 4.35. Different genotypes, i.e, AA, AG and GG seem

to affect the FSH levels in PCOS group; details are given in Figure 4.36-4.38.

4.5.2Testosterone

The testosterone (ng/ml) titres were lower in controls group (p < 0.001) as compared

to women with PCOS. The profile of testosterone is presented in Figure 4.39.

4.5.3 Progesterone

Serum progesterone (ng/ml) was lower in endometriosis women as compared with

controls (p < 0.001) (Figure 4.40).

150

Table 4.26: Frequency distribution of single nucleotide polymorphisms of ESR2 gene with risk of PCOS in Pakistani women.


frequencies

PCOS

(n= 96)

Controls

(n= 96)


n % n %

rs4986938 GG 33 34.4 50 52.1 0.482

(G>A) GA 46 47.9 39 40.6 (0.27-0.86) 5.43 0.020 >.05

UTR-3 AA 17 17.7 7 7.3

Allele frequency

G Allele 112 58.3 139 72.4 0.534

A Allele 80 41.7 53 27.6 (0.35-0.81) 7.78 0.005 >.05

E(HET) 48 41


151

Figure 4.35: Serum concentration of FSH in women with PCOS and controls.

Values given are mean in mIU/ml of FSH ± S.D. The asterisk shows the significant

difference between 2 groups according to the “t” test.

Figure 4.36: Comparison of mean FSH values in women with PCOS and controls

according to rs6166 genotype of FSHR gene. . The asterisk shows the significant difference

between 2 groups according to the “t” test.

152


according to rs6165 genotype of FSHR gene.


according to rs6169 genotype of FSHB gene.

153

Figure 4.39: Serum concentration of Testosterone in women with PCOS and

controls. Values given are mean in ng/ml of testosterone ± S.D. The asterisk shows the

significant difference between 2 groups according to the “t” test.

154

Figure 4.40: Serum concentration of progesterone in women with endometriosis

controls. Values given are mean in ng/ml of progesterone ± S.D. The asterisk shows

the significant difference between 2 groups according to the “t” test.

155

CHAPTER 5

DISCUSSION

Infertility is a common public health problem in developing countries.

However a limited data is available about the prevalence of infertility. Generally it is

believed that more than 70 million couples affect from infertility worldwide (Boivin

et al., 2007). The pathogenesis of diseases is better understood on the base of genetic

studies, which help to improve the treatment of patients (Simoni et al., 2008).

This is the first integrated study on the single nucleotide polymorphism of ESR1,

ESR2, PGR, IL10, ADIPOQ, INSR, FSHR, FSHB, LHCGR and LHB genes, to identify

genetic factors which might have an impact on the etiology of the endometriosis and

PCOS in Pakistani women. All SNPs in this study were chosen for their functional

relevance to endometriosis and PCOS after searching databases and previous

publications. Study of genomic variants and genes contributing in molecular

mechanism develop understanding of disease pathogenesis involving DNA sequence

among individuals. Current studies provide novel and detailed information on

polymorphism of various genes in Pakistani subpopulation of women. Since this is the

first study on Pakistani women, the present data will be compared with the results of

all the polymorphisms investigated with similar studies conducted on other

populations.

5.1 Population characteristics

The excess body fat is commonly measured in terms of Body Mass Index

(BMI). The BMI classified as overweight 25 kg/m2 < BMI < 30 kg/m

2 and obese with

BMI > 30 kg/m2 (Lo et al., 2006). In current study the women with PCOS were obese

when compared with respective controls. The mean BMI was 31.10 kg/m2 in PCOS

women and 30.49 kg/m2 in controls but this difference were not statistically

significant (p > 0.05). The prevalence of obesity in PCOS women varied (BMI >

30kg/m2) across different Asian countries reported by several authors (Al-Azemi et

al., 2004; Lam et al., 2005; Haq et al., 2007; Kurioka et al., 2007; Li et al., 2007; Shi

et al., 2007). Obesity, mainly the abdominal phenotype may be responsible for

hyperinsulinemia and associated with insulin resistance in PCOS women (Broekmans

et al., 2006; Lo et al., 2006; Norman et al., 2007). In USA the PCOS constitutes a

significant economic and health burden estimated over $4 billion with 12.2% for

156

infertility care, >30.1% costs hormonal related treatment due to menstrual

dysfunction, 40.5% for diabetes mellitus 2 and 14.2% for hirsutism treatment (Azziz

et al., 2005). The published trials on different populations showed the prevalence and

prediction of metabolic syndrome from 33.4 to 47.3% in PCOS women (Apridonidze

et al., 2005; Dokras et al., 2005; Ehrmann et al., 2005). The ethnicity of PCOS

women showed variations in hormonal, metabolic and clinical characteristics.

5.2 Endometriosis

In spite of high prevalence the molecular mechanism involved in the

development of endometriosis puzzled many investigators for years and still remain

enigmatic. Endometriosis is considered as sex hormone dependent disease that affects

women of reproductive age and regresses after menopause (Kitawaki et al., 2002a).

The interaction between multiple genes and environmental factors is involved in the

pathogenesis of endometriosis. The identification of genes or genetic polymorphisms

involved in susceptibility of endometriosis has attracted a growing interest in recent

years (Falconer et al., 2007). In view of the involvement of various genes, present

study explores the association between genetic polymorphisms with the predisposition

of endometriosis.

Estrogen receptor genes harbour certain DNA sequence variants that may

contribute to the risk of infertility. In the present study no association was observed in

genotype and allele frequencies between genetic variants rs2234693 and rs9340799 of

ESR1 gene polymorphisms and endometriosis (p > 0.050). In contrast, distinct

variations were observed in haplotype frequencies (p < 0.005) indicated that the

polymorphisms in ESR1 gene may affect the other regions of the gene in study

population. During screening of the ESR1 gene the other five genetic polymorphisms

rs11155815, rs8179176, rs11155816, rs4986936 and rs4986937 were also

investigated. These genetic variants were more frequent in women with endometriosis

than control however these were statistically not significant (p ≥ 0.050). These

findings were in agreement with the prior studies when compared with other

populations (Table 2.1). A study on Japanese women failed to detect an association

between ESR1 gene polymorphisms and endometriosis (Matsuzaka et al., 2012). In

Estonian women no association was observed in genetic variants of ESR1 rs2234693

with endometriosis (Lamp et al., 2011). In the present study the polymorphisms

rs2234693 and rs9340799 may act through linkage disequilibrium (LD = 0.48; p =

157

0.005) for a functional sequence variation in the gene of endometriotic women. By

contrast a highly significant (p = 0.006) difference was observed in the genotype and

allele frequencies of rs4986938 of ESR2 gene polymorphism in the endometriosis

compared with control group. A study on Japanese population showed that the ESR2

gene polymorphism was associated with an increased risk of endometriosis (Wang et

al., 2004). In Brazilian women, the polymorphism in ESR2 gene has been associated

with the risk of endometriosis development, irrespective to the stage of endometriosis

(Bianco et al., 2009). However a study conducted on Korean women with

endometriosis and controls suggests that the polymorphism rs4986938 of ESR2 gene

may not be associated with the severity of disease (Lee et al., 2007). The allele

frequencies of rs4986938 of ESR2 gene was significantly (p = 0.003) associated with

endometriosis in women from Brazil population (Bianco et al., 2009; Zulli et al.,

2010).

In the progesterone receptor gene two polymorphisms, rs10895068 in the

promoter region and rs1042838 in exon 4 were studied. A highly significantly (p =

0.003) association between endometriosis and progesterone receptor gene rs1042838

was observed in present population. Both polymorphisms of PGR gene are present in

the coding region of genome so it is predictable that these polymorphisms are

associated with the susceptibility of endometriosis. In current study the low level of

progesterone in serum was observed with endometriosis patient when compared with

their controls (p < 0.001). This elevation in serum progesterone level indicates the fact

that the production of this hormone was affected by PGR gene. Previously a German

study revealed that both these polymorphisms influenced the function of progesterone

receptors (Romano et al., 2007). A study on Dutch population investigated an

association of rs10895068 polymorphism (p < 0.050) with endometriosis (van Kaam

et al., 2007). However, no association with any of the variant rs1042838 and

rs10895068 polymorphism was observed with the susceptibility of endometriosis in a

pooled analysis from Australia and India (Treloar et al., 2005).

Interleukin 10 is the chief immune-modulatory cytokine and function to

terminate and limit the inflammatory responses (Moore et al., 2001). The associations

of IL10 promoter polymorphism and endometriosis have been investigated in various

populations.

158

The genotype and allele frequencies at each 4 SNPs of IL10 gene

polymorphisms rs1800872, rs1800871, rs1800894 and rs1800896 of promoter region

differ significantly (p ≤ 0.005) in endometriosis women when compared with control

group. In IL10 gene, multi-SNP haplotypes at each 3 SNPs (rs1800872, rs1800871

and rs1800896) differ significantly (p = 0.005) in endometriosis women compared

with their controls, suggesting that “ATG” genotype may contribute to the risk of

disease. Interestingly this haplotype was not reported in any previous population

suggesting that “ATG” was a novel haplotype in Pakistani women with

endometriosis. The findings of present study in terms of association are in line with

the previous studies. A study on Chinese women with endometriosis revealed that the

patients having rs1800871 polymorphism had a higher IL10 level when compared

with controls (Zhang et al., 2007). A recent study suggests that the ACC/ACC

haplotype, which is known to be a “low-producer” of IL10, is associated with

endometriosis (Riiskjaer et al., 2011). However in present study population the

ATG/ATG haplotype in the promoter region is related to the risk of endometriosis. In

Pakistani women the frequency of GCC is 16.5 % in endometriosis and 19.5 % in

controls. In addition the frequency of haplotype GCC is about 50% in European

females, 20% in African females while lowest below 5% in Asian female that is

(Meenagh et al., 2002).

No statistically significant (p > 0.050) difference was observed in allele and

genotype frequencies of rs1800872 and rs1800896 in Japanese patients with

endometriosis compared with controls (Kitawaki et al., 2002b). In contrast, a

significant association of endometriosis with rs1800872 in the promoter region of

IL10 was found in Taiwanese population (Hsieh et al., 2003). The frequency of C

allele of rs1800872 was lower in endometriosis patients (55.8 %) than in controls (78

%). A study on Chinese patients with endometriosis revealed the higher frequency of

C allele at rs1800872 as compared to controls (Zhang et al., 2007). Moreover, the

polymorphism in promoter region of IL10 gene was also studied in Chinese women

with endometriosis compared with controls. The distinct variations (p < 0.050) in

allele frequency were observed at rs1800872 and rs1800871 of IL10 gene, this seems

to be associated with endometriosis while the polymorphism rs1800896 was

conserved with no difference in allele frequency (Xie et al., 2009). These findings

were in agreement with the prior studies when compared with other populations

(Table 2.3).

159

5.3 PCOS

In current study the polymorphisms of various genes ADIPOQ, INSR, FSHR,

FSHB, LHCGR, LHB, ESR1 and ESR2 and their association with the development of

PCOS was investigated. PCOS is the second reproductive disorder studied in the

present research.

In this study, the association of three individual SNPs rs2241766, rs1501299 and

rs2241767 of ADIPOQ gene along with their haplotypes with susceptibility to PCOS

was studied. The rs2241766 has synonymous variation in the exon 2 (Gly-Gly)

whereas rs1501299 and rs2241767 are located in intron. The allele frequencies at each

of 3 above mentioned SNPs rs2241766, rs1501299 and rs2241767 (p < 0.001) as well

as multi-SNP haplotypes differ significantly (p < 0.001) between PCOS patients and

controls, suggesting that these SNPs may contribute to the risk development of PCOS.

Current findings are in line with previous studies (Panidis et al., 2004; San Millan et

al., 2004; Zhang et al., 2008) showing a significant association between the ADIPOQ

rs2241766 polymorphism and risk of PCOS. In addition, “T” allele of rs2241766 was

more frequent in PCOS women compared with control. However in a study on Han

Chinese women “G” allele was related to an increased risk of PCOS, this may be due

to difference in ethnicities (Demirci et al., 2010). In present study “TT” genotype of

ADIPOQ genetic variant rs2241766 was associated with a 3.725 folds increased risk

for PCOS patients similar with a study in Iran where 1.93-fold increase risk for PCOS

with the same genotype was observed (Ranjzad et al., 2012). A previous study on the

same gene ADIPOQ revealed that there are two strong LD blocks, one LD block

reside in the putative promoter and other appears to extend over the region between

rs2241766 and rs1501299 (Heid et al., 2006). In current study strong LD value (r2 =

0.78; p < 0.001) in ADIPOQ gene in Pakistani women with PCOS supports previous

finding. In addition, a new SNP at 186571196 genomic position was also investigated,

the heterozygous gene frequency was 26.0 % in PCOS women than 14.6 % in

controls. Moreover, rs2241767 showed strong linkage disequilibrium with rs2241766

present in the coding region of genome. The rs2241767 was not observed in any

population previously. The distribution of allele frequencies of rs2241766 and

rs1501299 polymorphisms of ADIPOQ gene in present study were in agreement with

the prior studies (Table 2.4a and 2.4b).

160

PCOS is a heterogeneous disorder; the patients of PCOS have an increased

susceptibility of type 2 diabetes as insulin resistance and glucose tolerance (San

Millan et al., 2004). In the present study a novel substitution of T→C within the

rs1799817 exon 17 of INSR gene with significantly different allele and genotype

frequencies (p = 0.001) was observed. Previous studies of exon 17 have shown that a

C→T substitution was associated with PCOS (Siegel et al., 2002). In current study,

the frequency of mutant homozygous “CC” genotype was significantly higher (58.3

%) in women with PCOS compared with (32.3 %) in controls (p = 0.001)).

Interestingly the frequency of “T” allele was significantly higher 42.2 % in control

group than 24 % in PCOS (p < 0.001). However one previous study reported the T/C

polymorphism associated with PCOS and decreased insulin sensitivity in Chinese

population (Jin et al., 2006). In present study another novel SNP, rs1799815 was

detected during the screening of exon 17. Whereas, no other novel polymorphism was

observed in a study on Indian PCOS women other than rs1799817 in exon 17 of INSR

gene (Mukherjee et al., 2009). The exon 8 of INSR gene is rarely studied for

association of polymorphism with PCOS. Furthermore, the association of genetic

variant rs2229429 in exon 8 of INSR gene with PCOS risk was also investigated

currently, which was not analysed previously in any study. A highly significant

difference (p = 0.001) in the genotype and allele frequencies was observed among the

PCOS and control group for this polymorphism. The haplotype frequencies showed a

clear difference in control group and PCOS women where the haplotype “CAT”

(0.078) and “TAT” (0.029) was observed only in PCOS women (p = 0.001).

The polymorphism of FSHR rs6166 and rs6165 was not responsible for any

significant association (p > 0.050) with PCOS in the current studied population. The

frequency of non-synonymous polymorphisms rs6166 and rs6165 in coding region of

exon 10 of FSH gene was greater than 30% in normal population. In a previous study

on Italian women no significant association was studied in FSHR gene

polymorphisms rs6166 and rs6165 in PCOS group (Orio et al., 2006). Similar results

in these two polymorphisms were reported in Chinese Singapore patients with PCOS

(Tong et al., 2001). However the haplotype analysis showed distinct variations

between the PCOS and control group. In present findings two haplotypes GG (43.1

%) and AA (50.4 %) were more frequent in PCOS than 32.6 % and 30.5 %

respectively in controls (p < 0.001)). This suggest that at least one susceptible locus

161

for PCOS lies within or very close to the region spanning rs6166 and rs6165 in the

FSHR gene in Pakistani women. This explained that the haplotype analysis has strong

effect than individual genetic markers in association analysis; therefore haplotype

analysis takes into account the correlation between these markers (Dudbridge, 2003).

Both the polymorphisms of FSHR gene were in strong linkage disequilibrium, which

shows that they may act as haplotype rather than individual marker. The two SNPs of

FSHR gene rs6166 and rs6165 are in linkage disequilibrium but most focused is on

rs6165 variant. Several studies demonstrate the effect of these polymorphisms on

reproduction and influence on FSHR functional activity (Simoni et al., 2008).

This study found that in rs6169 polymorphism of FSHB gene the allele

frequency and homozygosity was significantly higher (p = 0.020) in patients with

PCOS when compared with controls. The FSHB rs6169 polymorphism was

previously found to be associated with obese PCOS patients in Southeast Asian

population (Liao et al., 1999; Tong et al., 2000). A more recent study in Italy revealed

that the joint conjunction of genetic polymorphisms in FSHR and FSHB demonstrated

that serum FSH level may be affected by these polymorphisms (La Marca et al.,

2013). Currently serum FSH level was higher in PCOS women as compared to

controls (p < 0.005). However, the previous studies revealed that the PCOS women

either have normal limits of FSH level or there is slight increase in serum FSH level

when compared with their controls (Laven et al., 2003).

The polymorphism rs61996318 of LHCGR gene seems to be a stable locus in

Pakistani women (p > 0.050), and it was not related with the development and

pathogenesis of PCOS. A similar finding was observed in Chinese Han women

suggesting that LHR rs6168318 polymorphism may be highly conserved in the

studied subpopulation (Liu et al., 2012). A novel SNP of LHCGR was found in

current study where there is a loss of base “A”. The frequency of missing base was

significantly higher (54.2 %) in PCOS women than (24.5 %) in controls (p < 0.001).

This showed that this novel SNP had a strong relation with the development and

susceptibility of PCOS in Pakistani women.

In present study two polymorphisms rs1800447 and rs4002462 in LHB gene

were also studied. Both of these LHB polymorphisms in Pakistani women were not

associated with PCOS (p > 0.050). Similar findings were observed in a previous study

where polymorphisms of LHB gene were not associated with PCOS and infertility in

162

various populations (Lamminen et al., 2002). However, another study on Finland,

Netherland, United Kingdom and United State showed that the silent mutation of the

LHB genomic variant may have influenced the polymorphism rs1800447 which might

lead to ovulatory disorder (Tapanainen et al., 1999). In PCOS women the LH is

overexpressed in theca cells and its function is altered by multiple polymorphisms in

the LHRCGR gene (Jakimiuk et al., 2001). LH stimulates the ovarian theca cells to

secrete androgens which consequently arrest follicular maturation (Laven et al.,

2002). Mutations in LHB subunit gene are rarely studied. The allelic frequency of this

variant varies extensively between different ethnic groups. The wide occurrence of

this polymorphism in populations with different evolutionary histories and wide

frequency variability may imply that this polymorphism represent an ancient form of

LH (Lamminen & Hutaniemi 2001).

In the present study the polymorphisms rs2234693 and rs9340799 of ESR1 gene

may act through linkage disequilibrium (41 %) for a functional sequence variation in

the gene (p = 0.001). A significant (p = 0.005) difference was observed in genotype

and allele frequencies of rs2234693 and rs9340799 polymorphisms in PCOS and

control group. In a recent study on these polymorphisms in Greek women; no

difference in genotype frequency was observed among PCOS and controls, however

the association of rs2234693 and rs9340799 with insulin resistance and FSH level

suggests the possible contribution of these genomic variants to the phenotype of

PCOS (Nectaria et al., 2012). The present study provides data showing that the two

polymorphisms may be associated with PCOS, but the mechanism underlying this

association remains to be elucidated. In addition rs2234693 and rs9340799

polymorphisms do not result in amino acid change; the observed effect may be due to

linkage disequilibrium among these polymorphisms. The present study suggests the

association of ESR2 rs4986938 polymorphism with the PCOS (p = 0.005). A previous

study evaluating the rs4986938 in women with ovulatory dysfunction found a higher

frequency of this polymorphism in PCOS patients than in controls (Sundarrajan et al.,

2001). In our study the strong LD value (p < 0.001) and genetic heterogeneity test (p

< 0.001) of ADIPOQ, FSHR and ESR1 genes in PCOS group revealed that these

polymorphisms may act through linkage disequilibrium for a functional sequence

variation in the gene.

163

Reproduction in vertebrates is under the control of hormonal regulation by

hypothalamus-pituitary-gonadal axis. Gonadotropins and steroids control the process

of reproduction. Androgens are correlated with gonadal development. In present study

the serum level of FSH and testosterone was higher (p = 0.005) in PCOS women. The

increase level of testosterone presents a classic picture of PCOS symptoms in study

population (i.e hirsutism, acne, weight gain and obesity) while the serum level of

progesterone was lower in endometriosis women when compared with normal control

(p = 0.005).

In conclusion, this study demonstrates that genetic variation in the studied

genes is associated with the diagnosis of endometriosis and PCOS with infertility in

Pakistani (Punjabi) women in a fashion similar to reports in other ethnic groups. The

consistent and new finding of these associations suggests a biologically plausible role

for genetic polymorphisms in the etiology of endometriosis and PCOS. To conclude,

endometriosis and PCOS are complex genetic disorders and previous studies have

investigated many genes for their possible role as susceptibility loci. This is the first

report to explore in Pakistani women from Punjab the association between different

polymorphisms of the ESR1, ESR2, PGR, IL10, ADIPOQ, INSR, FSHR, FSHB,

LHCGR and LHB genes and the development of endometriosis and PCOS. This study

provides evidence that susceptibility loci for endometriosis and PCOS lie within or

very close to the chromosomal region spanning these genes. By investigating, the

functional role of these SNPs in Pakistani women and building up more information’s

underlying the genetic basis for PCOS; the onset of disease in the individuals at risk

can be delayed by changing the life style that will reduce expenditures to control the

disease and its complications. Further this information could also be beneficial for the

prevention of other long term complications such as obesity, diabetes and heart

diseases. Moreover, samples from other Provinces should be investigated for any

change in SNP to get the true picture of the country.

164

CHAPTER 6

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Z.J. (2008). Association of +45 (T/G) and +276 (G/T) polymorphisms in the

ADIPOQ gene with polycystic ovary syndrome among Han Chinese women.

Eur J Endocrinol., 158: 255–260.

Zhang, X., Hei, P., Deng, L. and Lin, J. (2007). Interleukin-10 gene promoter

polymorphisms and their protein production in peritoneal fluid in patients with

endometriosis. Mol Hum Reprod., 13: 135–140.

188

Zulli, K., Bianco, B., Mafra, F.A., Teles, J.S., Christofolini, D.M. and Barbosa, C.P.

(2010). Polymorphism of the estrogen receptor b gene is related to infertility

and infertility associated endometriosis. Arq Bras Endocrinol Metab., 54(6):

567-71.

189

Annexure I

3.2 CONSENT FORM

Genetic and endocrinological studies of female reproductive dysfunction


I __________________, wife/daughter of ________________ hereby, fully agree to

participate in the above mentioned study under ID #__________________________

I understand that the study is designed to add to the medical knowledge. I have been

informed about possible risks/discomforts involved and had the opportunity to ask

any question about the study. I agree to give my medical history and blood sample.

All the information collected in the data sheet will be kept confidential and will only

be used solely for research purposes. I have no objection if in case the data obtained

from my investigation is published in any scientific journal.

________________

Patient’s Signature

Date: ____________

190

Annexure II

3.2 SUBJECT DATA SHEET

Patient Identity No.: _______________ Date: ______________

Name: _______________________ Age: ______________

W/O or D/O: __________________ DOB: ______________

Phone Number: _________________ Cast: ______________

Postal Address:

_____________________________________________________________________

_____________________________________________________________________

Marital Status: Married__________ Unmarried___________

Pregnant: Yes ___________ No__________ No. of children: _______________

General physical examination:

Height: _________ Weight: ________ Kg BMI: _____________

Waist circumference: _____________ Cm Hip circumference: __________

Cm

WHR: _________________ Pulse: ___________ Blood pressure: ____________

Cardiovascular system: _____________ Central Nervous system: ____________

Family H/O:

Smoking ________ HTN ______ DM ______

IHD _______ PCOS _____ Endometriosis

_____

Did you have any history of? Yes No

Diabetes Mellitus (DM) ___ ___

Hypertension ( HTN) ___ ___

Smoking ___ ___

Alcohol ___ ___

Hyperthyroidism ___ ___

Any hospitalization in past ___ ___

Ischemic heart (IHD) ___ ___

Any concurrent medical illness ___ ___

Any surgery in past ___ ___

(Hysterectomy, Oophorectomy)

191

Gynecological history

Menstrual history:

Age of Menarche: ____________ Pattern of cycle: Regular ___ Irregular_______

Less than 9 menses per year: Yes _____ No _____

H/O irregular menses with weight gain: Yes _____ No _____

Pelvic pain: __________ Back pain: ____________

Dysmenorrhea: _________ Abnormal vaginal discharge: ________

Dyschezia: ____________ Dysuria: _______________ Dyspareunia ____________

Have you had a physician give you a medical diagnosis of Polycystic Ovarian

Syndrome (PCOS)? YES__________ NO ___________

If yes, how was the diagnosis made? ________________

Do you have a history of any of the following?

Endometriosis _______ Uterine fibroids________

Ovarian cysts________ Breast lumps (or fibrocystic breast disease)

________

Do you have a family history of any of the following?

PCOS _______ Excessive hair growth_______

Infertility_______ Obesity_______

Menstrual problems _______ Thyroid abnormalities_______

Hormonal problems_______ Miscarriage_______

Which symptoms you are currently experiencing as a result of your PCOS?

Infertility_______ Anxiety_______

Weight gain_______ Insulin resistance_______

Food cravings _______ Facial hair_______

Specifically: _______ Mood swings_______

Acne _______ Depression_______

Which of the following treatments for PCOS have you attempted?

Low carbohydrate diet_______ Acne medication_______

General healthy eating_______ Psychological counseling_______

Insulin sensitizing medications_______ Nutritional counseling_______

Oral Contraceptive_______ Antidepressants_______

Exercise/Personal Trainer_______ Mood stabilizing medication ______

Other_______

192

Medications to regulate period_______ Please describe:

Did you take any contraceptic medicine in past Yes ______ No ______

If yes, for how long _____________

Did you take any other hormonal medication in past Yes ______ No ______


Did you take any anti-obesity drugs Yes ______ No ______


Did you take any anti-diabetic medicine Yes ______ No ______


Any history of miscarriage:

How many previous pregnancies were attempted ______________?

Successful pregnancies ______________________

How many previous attempted pregnancies were without success

______________

History of hirsutism: _____________ History of Acne: _____________

History of obesity: _______________ History of prostin: _________________

Pattern of obesity: Generalized ___________Visceral __________ Buffalo hump

_______

Ovarian ultrasound:

Rt ovary: ___________ Lt ovary: ___________Size: _________ Morphology:

__________

Any cyst: _______________ If cysts present then blood flow: ____________

Investigations

Pelvic scan: ________ Laparoscopic findings: ________USG _______ TVS _____

Rectosigmoidoscopy _________ Cystoscopy _________ CA-125: ______________

CT SCAN (pelvis/abdomen) ___________ MRI. Pelvis/abdomen ____________

Laboratory tests

Fasting glucose: _______ Fasting insulin: ________Serum Estradiol: ___________

Serum Testosterone: _____________ Serum LH: _________________

Serum FSH: _________ Serum Progesterone __________ Serum Prolactin _______

193

QUESTIONNAIRE FOR DIAGNOSIS PCOS (Sue et al., 2007)

-*If score is equal or more than 2, PCOS is present

* If score is less than 2, not consistent with diagnosis of PCOS

1. Between ages of 16-40 years about how long was your average menstrual cycle

Less than 25 days

25-35

36-60

More than 60

Totally variable

*1 score for 36 days onward

2. During your menstruation years (not including your pregnancy period) did you have a

tendency to grow dark, coarse hair on your

Upper lip

Chin

Breast

Back

Belly

Upper arm

Upper thigh

Chest b/w breast

* For more than 3 sites _______ I score

3. Were you ever overweight and obese b/w ages of 16-40 years

Yes __________ 1 score

No ________ 0

4. Between ages of 16-40 years, have you ever noticed a milky discharge from your

nipples ( not including during pregnancy or recent child birth)

Yes __________ - 1

No ___________ 0

194

Annexure III

3.6.1 Preparation of solutions

1L 1M Tris-HCl

Weigh 121.1g tris base (2-Amino-2-hydroxymethyl-propane-1,3-diol), dissolve into

700 ml distilled H2O, adjust pH to 7.4-8.0, raise final volume to 1L, autoclave and “if

possible” filter the solution and store at room temperature.

1L 3M sodium acetate

Weigh 246.1 × 3g sodium acetate, dissolve into distilled H2O, adjust pH to 5.2, raise

final volume to 1L, autoclave and “if possible” filter the solution and store at room

temperature.

1L 10M NaOH

Weigh 40 × 10g sodium hydroxide (NaOH), dissolve into 700 ml distilled H2O, raise

final volume to 1L and store at room temperature.

1L 1M HCl

Measure 86.2 ml of 11.6M HCl, dilute into 913.8 ml distilled H2O and store at room

temperature. Precaution Add acid into distilled H2O not distilled H2O into acid.

1L 0.5M EDTA

Weigh 372.2/2g ethylene-diamine-tetraacetic acid (EDTA), dissolve into 700 ml

distilled H2O, adjust pH to 8.0 by using NaOH pellets or 10M NaOH solution, raise

final volume to 1L, autoclave and “if possible” filter the solution and store at room

temperature. Note The dissolution of EDTA is pH-sensitive. EDTA will start

dissolving on stirrer only when pH is increased towards 8.0 by the pellet-wise or

drop-wise addition of NaOH into the starting mixture. Once EDTA solution becomes

clear, stop adding NaOH. If excessive NaOH is added during EDTA dissolution, pH

may become greater than 8.0, which will then be adjusted to 8.0 by using 1M HCl.

1L TE buffer (10 mM Tris-HCl, 2 mM EDTA, pH 8.0)

Dilute 10 ml of 1M Tris-HCl solution and 4 ml of 0.5M EDTA solution into 500 ml

distilled H2O, raise final volume to 1L and store at room temperature.

50 ml 10% SDS

Dissolve 5g sodium dodecyl sulphate (SDS) into 45 ml distilled H2O, heat up to 68oC

for dissolution, adjust pH to 7.2 by using 1M HCl and “if possible” filter the solution

195

and store at room temperature. Note Don’t use fume hood while preparing SDS

solution.

10 ml 10 µg/µl proteinase K

Dissolve 100 mg proteinase K into 10 ml distilled H2O, make aliquots of 100 µl and

store at -20oC.

500 ml chloroform: isoamyl alcohol (24:1)

Mix 480 ml chloroform into 20 ml isoamyl alcohol and store at 4oC.

500 ml 70% ethanol

Mix 350 ml absolute ethanol into 150 ml distilled H2O and store at 4oC.

100 ml low TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0)

Dilute 1 ml of 1M Tris-HCl solution and 200 µl of 0.5M EDTA solution into 50 ml

distilled H2O; raise final volume to 100 ml and store at room temperature.

196

Annexure IV

3.6.3 Agarose Gel Electrophoresis

The lengths of optimized DNA fragments of PCR products were quantify and

visualized through agarose gel electrophoresis.

TAE Buffer 1L

4.84 g Tris Base

1.14 ml Glacial Acetic Acid

2 ml 0.5M EDTA (pH 8.0)

The Tris base was added to 500 ml of distilled H2O. After Adding acetic acid and

EDTA the solution was mixed. The volume was made 1 liter with more distilled

water. For convenience a concentrated stock of TAE buffer of 50X was prepared and

before use it was diluted with distilled water to 1X concentration.

1L 10X TBE buffer

Dissolve 108g tris-borate, 55g boric acid and 40 ml of 0.5M EDTA solution into 700

ml distilled H2O, raise final volume to 100 ml and store at room temperature.

1L 1XTBE buffer

Dilute 100 ml of 10× TBE buffer into 900 ml distilled H2O and store at room

temperature.

10 ml 10 µg/µl ethidium bromide (EtBR)

Dissolve 100 mg EtBR into 10 ml distilled H2O or low TE buffer, make aliquots of 1

ml, cover tubes with aluminum foil and store at room temperature. Note EtBR is a

strong mutagen and protection from exposure is needed.

50 ml 6× loading dye

Dissolve 0.125g bromophenol blue (0.25%), 0.125g xylene cyanol FF (0.25%) and 15

ml of 100% glycerol (30%) or 20g sucrose (40%) or 7.5g Ficoll type 400 (15%) into

distilled H2O for making final volume up to 50 ml and store at 4oC or -20

oC.

197

Preparing the Agarose gel

Take 100 ml TAE Buffer to the 250 ml flask and add 1 g of Agarose powder. The

flask was heated in a microwave until the solution became clear. The solution was

cooled to about 50-55°C and added 2 l of Ethidium Bromide in 100 ml solution,

swirling the flask occasionally to cool evenly. Place the combs in the gel casting tray.

Poured the melted agarose solution into the casting tray and cooled it until it is solid

(it should appear milky white). Carefully pull out the combs. Placed the gel in the

electrophoresis chamber.

Loading the gel

Added 1 l of Sample Loading Dye to 5l of PCR product on a thin film and mix it.

The order of the samples loading was recorded. Carefully pipette 6 l of each sample

Loading Buffer mixture into separate wells in the gel. Pipette 2 l of the DNA ladder

into at least one well of on the gel.

Running the gel

Placed the lid on the gel box, connecting the electrodes. Connected the electrode

wires to the power supply, making sure the positive (red) and negative (black) were

correctly connected. Turned on the power supply, about 100 volts for 30 minutes. The

power run until the blue dye approaches the end of the gel. Remove the lid of the

electrophoresis chamber. Carefully removed the tray and gel with DNA bands were

observed in gel doc system (BioRad, Gel doc system)

198

Annexure V

3.6.6 Optimization of selected fragments of DNA of various genes

Figure 3.1: PCR product size: LHCGR 379 bp; FSHR

577 bp (base pairs); column 1: DNA ladder; Column 2-

16: PCR products of different DNA samples

199

Figure 3.2: PCR product size: FSHB 577 bp (base pairs);

column 1: DNA ladder; Column 2-15: PCR products of

different DNA samples

200

Figure 3.3: PCR product size: ADIPOQ 241 bp (base pairs);



201

Figure 3.4: PCR product size: INSR 317 bp (base pairs);



202

Figure 3.5: PCR product size: PGR 238 bp (base pairs);



203

Figure 3.6: PCR product size: IL10 208 bp (base pairs);

column 1: DNA ladder; Column 2-8: PCR products

of different DNA samples

204

Annexure VI

3.6.7 PCR purification reagents preparation

• Add molecular grade ethanol (98–100%) to Buffer PE

• Add 1:250 volume pH indicator I to Buffer PB (add 600 μl pH

indicator I to 150 ml Buffer PB). The yellow color of Buffer PB with pH indicator I

indicates a pH of 7.5.

205

LIST OF PUBLICATIONS AND PRESENTATIONS FROM THESIS

PUBLICATIONS

Liaqat, I., Jahan, N., Krikun, G. and Taylor, H.S. (2014). Genetic Polymorphisms

in Pakistani Women with Polycystic Ovary Syndrome. Reproductive Sciences.

22(3): 347-357. (DOI: 10.1177/1933719114542015).(IF. 2.23)

Liaqat, I., Jahan, N., Lone, K.P, Pakstis, A. and Taylor, H.S. (2013). Genetic

polymorphisms associated with endometriosis in Pakistani women. Journal of

Endometriosis. 5(4): 134 – 143. DOI:10.5301/je.5000165 (H. INDEX. 7).

Liaqat, I., Jahan, N., Lone, K.P, and Taylor, H.S. (2015). Genetic polymorphisms

of INSR and ADIPOQ genes associated with PCOS Pakistani population.

(Submitted to Plos One. Manuscript Number. Pone-S-15-20751: IF 3.730)

ORAL PRESENTATIONS

Oral presentation entitled “Genetic polymorphisms in adiponectin and insulin receptor

genes in Pakistani women with polycystic ovary syndrome”. 34th Pakistan Congress

of Zoology (International). Feb. 25-27, 2014. CBGP-46.

Oral presentation entitled “Endometriosis and Genetic Polymorphisms in Pakistani

Women”. IBPHR (International). May6-8, 2014. (BcGc-1406).

POSTER PRESENTATION

Poster presentation entitled Genetic Polymorphisms Associated with Endometriosis in

Pakistani Women at "Transforming Women's Health via Translational Investigation:

A Global Perspective". SGI, Florence Italy. March 25-28, 2014. (F-246).

ABSTRACTS

Liaqat, I., Jahan, N., Loneb, K. P., Pakstis, A., and Taylor, H. S. (2014). Genetic

Polymorphisms Associated with Endometriosis in Pakistani Women. Reproductive

Sciences. 21(3):318A-318A.

Liaqat, I., Jahan, N., Lone, K.P., Pakstis, A. and Taylor, H.S. (2014). Genetic

polymorphisms in adiponectin and insulin receptor genes in Pakistani women with

polycystic ovary syndrome. Abstracts of 34th Pakistan Congress of Zoology

(International). Feb. 25-27, 2014. CBGP-46

206

Liaqat, I., Jahan, N., Lone, K.P., Batool, A. and Taylor, H.S. (2014). Endometriosis

and Genetic Polymorphisms (FSHR, IL10, ESR1) in Pakistani Women. IBPHR

(International). May6-8, 2014. (BcGc-1406).

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