Renin angiotensin system polymorphisms and pregnancy ... · Renin Angiotensin System Polymorphisms and Pregnancy Complications Ang Zhou BHlthSc (Hons) Thesis submitted for the degree

Renin Angiotensin System Polymorphisms and

Pregnancy Complications

Ang Zhou BHlthSc (Hons)

Thesis submitted for the degree of

Doctor of Philosophy

The Discipline of Obstetrics and Gynaecology

Research Centre for Reproductive Health

University of Adelaide

Australia

July 2012

i

Table of content Abstract iv

Declaration vi

Acknowledgments vii

Abstracts arising from this thesis ix

List of figures xi

List of tables xii

Abbreviations xiii

CHAPTER 1: Renin angiotensin system and pregnancy complications 1

Overview 2

1.1 The renin angiotensin system 4

1.2 RAS during normal pregnancy 5

1.2.1 Maternal systemic RAS 5

1.2.2 Uteroplacental RAS 7

1.3 RAS and pregnancy complications 9

1.3.1 Pregnancy complications 9

1.3.2 RAS and preeclampsia 10

1.3.2.1 Maternal systemic RAS in preeclampsia 11

1.3.2.2 Uteroplacental RAS in preeclampsia 13

1.3.3 RAS and other pregnancy complications 14

1.4 The association of RAS polymorphisms with pregnancy complications 15

1.4.1 RAS polymorphisms 15

1.4.1.1 Renin T/G 15

1.4.1.2 AGT M235T 15

1.4.1.3 AGT T174M 16

1.4.1.4 ACE A11860G 16

1.4.1.5 AGT1R A1166C 17

1.4.1.6 AGT2R C4599A 17

1.4.1.7 AGT2R A1675G 17

1.4.1.8 AGT2R T1334C 18

1.4.2 Paternal genotype in association studies 19

1.4.3 Gene and environment interactions in association studies 19

1.4.4 Fetal sex in association studies 20

1.5 Aims and structure of the current thesis 22

CHAPTER 2: Materials and Methods 26

2.1 The study population 27

2.1.1 Participants 27

2.1.2 Ethics 27

2.1.3 Recruitment 27

2.1.4 Data collection 28

2.1.5 Biological sample collection 29

2.1.6 Pregnancy outcomes 29

2.1.6.1 Uncomplicated pregnancy 29

2.1.6.2 Preeclampsia 30

2.1.6.3 Small for gestational age (SGA) 30

2.1.6.4 Spontaneous preterm birth (sPTB) 30

2.1.6.5 Gestational hypertension (GHT) 31

2.1.6.6 Gestational diabetes (GDM) 31

2.1.6.7 Placental abruption 31

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2.2 DNA Extraction 31

2.2.1 DNA extraction from buffy coats 31

2.2.2 DNA extraction from Whatman FTA cards 32

2.2.3 DNA extraction from saliva samples 32

2.3 Genotyping assay 32

2.4 Plasma prorenin concentration 33

2.5 Plasma ACE concentration 33

2.6 Plasma ANG II concentration 34

2.7 Plasma ANG 1-7 concentration 34

CHAPTER 3: Characteristics of the study population 37

3.1 Introduction 38

3.2 Results 39

3.3 Discussion 42

CHAPTER 4: The association of RAS polymorphisms with maternal circulating RAS

profile at 15 weeks’ gestation 51 4.1 Abstract 52

4.2 Introduction 53

4.3 Materials and Methods 54

4.4 Results 57

4.5 Discussion 58

CHAPTER 5: The association of RAS polymorphisms with maternal blood pressure and

uterine and umbilical artery Doppler 63

5.1 Abstract 64

5.2 Introduction 65


5.4 Results 70

5.5 Discussion 72

CHAPTER 6: The association of maternal ACE A11860G with SGA is modulated by the

environmental factors and fetal sex 81

6.1 Abstract 82

6.2 Introduction 83


6.4 Results 88

6.5 Discussion 93

CHAPTER 7: The association of AGT2R polymorphisms with preeclampsia and uterine

artery bilateral notching is modulated by maternal BMI 106

7.1 Abstract 107

7.2 Introduction 110


7.4 Results 114

7.5 Discussion 118

CHAPTER 8: General discussion 126

8.1 Paternal AGT2R C4599A is associated with preeclampsia 128

8.2 Environmental factors modify the association of RAS polymorphisms with SGA and

preeclampsia 129

8.3 Fetal sex affects the association of RAS polymorphisms with SGA and uterine and 130

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umbilical artery resistance indices at 20 weeks’ gestation

8.4 Limitations in genetic association studies 131

8.5 Implications 133

8.6 Conclusion 134

REFERENCES 135

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Abstract

Introduction: The renin angiotensin system (RAS) plays an important role in blood pressure

regulation and salt-water homeostasis. Aberrant maternal circulating and uteroplacental RAS

profiles have been implicated in pregnancy complications, in particular preeclampsia. Our

primary aims were to determine associations of polymorphisms in the RAS genes including

renin, angiotensinogen (AGT), angiotensin converting enzyme (ACE), angiotensin II type 1

receptor (AGT1R) and type 2 receptor (AGT2R) with pregnancy complications, including

preeclampsia, small for gestational age (SGA) and spontaneous preterm birth (sPTB) and to

identify potential gene-environment and gene-fetal sex interactions that may modify risks for

these pregnancy complications. The secondary aims were to determine the association of RAS

polymorphisms with maternal plasma RAS profile at 15 weeks’ gestation, maternal blood

pressure at 15 weeks’ gestation and uterine and umbilical artery resistance at 20 weeks’

gestation.

Methods: Healthy nulliparous women, their partners and babies (3234 trios) were recruited

prospectively in Adelaide, Australia and Auckland, New Zealand. Data analyses were

confined to 2121 Caucasian parent-infant trios, among which 123 had preeclampsia, 216 had

SGA and 116 had sPTB. Uncomplicated pregnancies (n=1185) served as controls. DNA was

genotyped by Sequenom MassARRAY. Maternal blood samples were taken at 15 weeks’

gestation and measured for plasma prorenin, ACE, angiotensin II (ANG II) and angiotensin 1-

7 (ANG 1-7) concentrations. Maternal blood pressure was measured at 15 weeks’ gestation.

Doppler sonography on the uterine and umbilical arteries was performed at 20 weeks’

gestation. Mean uterine or umbilical artery resistance indices (RI) above the 90th

percentile

were considered abnormal.

Results: Maternal and neonatal ACE A11860G GG genotype was associated with elevated

maternal plasma ACE concentration. Neonatal renin T/G and maternal AGT M235T were

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associated with maternal plasma ANG 1-7 concentration. In female-bearing pregnancies,

maternal AGT1R A1166C CC genotype was associated with an increased risk for abnormal

uterine artery RI, whereas in male-bearing pregnancies, the AGT M235T TT genotype in

mothers and neonates was associated with an increased risk for abnormal umbilical artery RI.

In the Australian SCOPE cohort, maternal ACE A11860G GG genotype was associated with

an increased risk for SGA and a reduction in customized birth weight centile compared with

the AA or AG genotype. Interestingly, these associations were only observed in female-

bearing pregnancies and in women with socio-economic index<34 or pre-pregnancy green

leafy vegetable intake<1 serve/day. Furthermore, maternal, neonatal and paternal AGT2R

C4599A was associated with preeclampsia in women with BMI≥25kg/m2. In the same subset

of women, paternal AGT2R C4599A and paternal AGT2R A1675G were associated with

uterine artery bilateral notching. Finally, no significant associations, gene-environment

interactions or gene-fetal sex interactions were found for sPTB.

Conclusion: The association of RAS polymorphisms with preeclampsia, SGA and abnormal

uterine and umbilical artery RI indicates the involvement of the RAS in the pathogenesis of

pregnancy complications, in particular preeclampsia and SGA. Furthermore, future genetic

association studies into pregnancy complications should take account of fetal sex and

appropriate environmental factors, otherwise genetic associations hidden by these factors may

be left unrecognized.

vi

Declaration

I certify that this work contains no material which has been accepted for the award of any

other degree or diploma in any university or other tertiary institution and, to the best of my

knowledge and belief, contains no material previously published or written by another person,

except where due reference has been made in the text. In addition, I certify that no part of this

work will, in the future, be used in a submission for any degree or diploma in any university

or other tertiary institution without the prior approval of the University of Adelaide and where

applicable, any partner institution responsible for the joint-award of this degree.

I give consent to this copy of my thesis, when deposited in the University Library, being made

available for loan and photocopying, subject to the provisions of the Copyright Act 1968.

I also give permission for the digital version of my thesis to be made available on the web, via

the University’s digital research repository, the Library catalogue and also through web

search engines, unless permission has been granted by the University to restrict access for a

period of time.

Signature: Date: July 2012

vii

Acknowledgements

The first person I would like to thank is my supervisor, Professor Claire Roberts. Thank you

for the opportunity to pursue my Ph.D. in your laboratory and your unconditional support

through the course of these studies. It has been an honour to work with someone so dedicated

and passionate about medical research, you have been an inspiration. Thanks for your

patience, encouragement and valuable feedback on my conference presentations, manuscripts

preparation and thesis writing. It has been a fantastic journey and life-changing experience for

me. I enjoyed every bit of it.

I would like to express my sincere thanks to co-supervisor Professor Gus Dekker for his

invaluable insight and advice regarding the interpretation of the data. Thanks for your prompt

feedback on my thesis drafts. It is such a privilege to have regular Friday meetings with you

and Claire. I benefited enormously from our discussions and this process really transformed

me from a stubborn person to an open-minded person.

I would also like to thank Professor Eugenie Lumbers for her valuable input into my Ph.D.

project and Shane D. Sykes for his contribution on the plasma prorenin data.

I would like to extend my sincere thanks to all my colleagues, Prabha Andraweera, Shalem

Lee, Gary Heinemann, Steven Thompson, Jessica Laurence, Dylan McCullough, Denise

Furness, Amanda Highet, Tina Bianco-Miotto, and Jamie Zhang. In particular, I would like to

thank Prabha Andraweera for generously sharing her Ph.D. experience with me, Gary

Heinemann for his technical supports with the ACE ELISA, Steven Thompson for his help

with cleaning up the database and Shalem Lee for her assistance on statistical analysis. I am

blessed with working with you guys. Thanks for making my journey so enjoyable.

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I also would like to thank my dearest friends in Australian and China, Chelsea Liu, Qiao Jun

(Pang Zi), Yang Dan (Shou Zi), Nan Hao and Sun Yue Rui for all your unwavering support

throughout my Ph.D. journey. You guys are true angels!

I would like to thank my twin brother, Xuan Zhou for his constant support and inspirational

advice throughout my Ph.D. journey.

At last but not least, I would like to extend a huge thanks to my parents. This journey would

not have been possible without your love and support from China.

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Abstracts arising from this thesis

1. S.D. Sykes, Y. Wang, A. Zhou, G.A. Dekker, C.T. Roberts, E.R. Lumbers, K.G.

Pringle. Fetal sex alters the expression of the uteroplacental and maternal circulating

renin-angiotensin systems; implications for maternal cardiovascular function and fetal

outcome. Gordon Research Seminar, 2012, USA

2. C.T. Roberts, A. Zhou, S. Thompson, G.A. Dekker. Interactions between genes

encoding renin-angiotensin system peptides and fetal sex in pregnancy complications.

International Federation of Placenta Associations 2011, Geilo, Norway.

3. A. Zhou, S. Thompson, G. Heinemann, J. Zhang, G.A. Dekker, C.T. Roberts.

Polymorphisms in RAS genes are associated with being born small for gestational age

in an Australian cohort. Renin Angiotensin System workshop, 2010, Melboune,

Australia.

4. A. Zhou, S. Thompson, R. Nowak, G. Heinemann, J. Zhang, G.A. Dekker, C.T.

Roberts. Paternal renin angiotensin system polymorphisms are associated with

pregnancy complications. International Federation of Placenta Associations annual

meeting, 2009, Adelaide, Australia.


Roberts. Renin angiotensin system polymorphisms in paternal genotypes are

associated with pregnancy complications. The Australian Society for Medical

Research annual meeting, 2009, Adelaide, Australia.


Roberts. Renin angiotensin system polymorphisms are associated with pregnancy

complications. 39th

Society for reproductive biology annual meeting, 2008, Melbourne,

Australia.

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Roberts. Renin angiotensin system polymorphisms and pregnancy success.

ARC/NHMRC Research Network in Genes & Environment in Development annual

meeting, 2008, Cairns, Australia.

xi

List of figures

Figure 1.1 The activation cascade of the RAS. 24

Figure 2.1 Sequenom iPLEX

TM MassARRAY system. 35

Figure 3.1 Flow chart of participant recruitment. 44



Figure 6.2 The association of maternal ACE A11860G with maternal plasma ACE

concentration at 15 weeks’ gestation in uncomplicated and SGA pregnancies. 98

Figure 6.3 Maternal plasma ACE concentration at 15 weeks’ gestation in uncomplicated

and SGA pregnancies. 99


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List of tables

Table 1.1 Location of RAS components in the uteroplacental unit. 25

Table 2.1 Primers for genotyping the RAS polymorphisms. 36

Table 3.1 The prevalence of pregnancy outcomes in the combined SCOPE. 45

Table 3.2 Demographic characteristics of the combined SCOPE cohort. 46

Table 3.3 Demographic characteristics of the Australian SCOPE cohort. 47

Table 3.4 Demographic characteristics of the New Zealand SCOPE cohort. 48

Table 3.5 The differences in demographic characteristics between the Australian and

New Zealand SCOPE cohorts. 49

Table 3.6 The prevalence of RAS polymorphisms in the combined SCOPE. 50

Table 4.1 Characteristics of the study population. 61

Table 4.2 The association of RAS polymorphisms with maternal plasma RAS peptide

concentrations at 15 weeks’ gestation. 62

Table 5.1 Characteristics of the study population. 78

Table 5.2 The association of AGT1R A1166C with abnormal uterine artery resistance

index at 20 weeks’ gestation, stratified by fetal sex. 79

Table 5.3 The association of AGT M235T with abnormal umbilical artery resistance

index at 20 weeks’ gestation, stratified by fetal sex. 80

Table 6.1 Demographic characteristics of the study population. 100

Table 6.2 Maternal, paternal and neonatal ACE A11860G genotype distribution in

uncomplicated pregnancies and SGA pregnancies, stratified by fetal sex and cohorts. 102

Table 6.3 The association of maternal ACE A11860G with newborn growth parameters,

stratified by fetal sex and cohorts. 103

Table 6.4 The association of maternal ACE A11860G with SGA and customised

birthweight centile, stratified by fetal sex and cohorts. 104

Table 6.5 The association of maternal ACE A11860G with customised birthweight

centile in the Australian SCOPE, stratified by maternal SEI, pre-pregnancy green leafy

vegetable intake and fetal sex. 105

Table 7.1 Demographic characteristics of the study population. 122

Table 7.2 The association of AGT1R and AGT2R polymorphisms with preeclampsia and

uterine artery bilateral notching at 20 weeks’ gestation. 123

Table 7.3 The association of AGT2R C4599A with preeclampsia and uterine artery

bilateral notching at 20 weeks’ gestation, stratified by maternal BMI. 124

Table 7.4 The association of AGT2R A1657G with preeclampsia and uterine artery

bilateral notching at 20 weeks’ gestation, stratified by maternal BMI. 125

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Abbreviations

ACE Angiotensin converting enzyme

ACE2 Angiotensin converting enzyme 2

AGRF Australian Genome Research Facility

AGT Angiotensinogen

AGT1R Angiotensin II type 1 receptor

AGT1R-AA Angiotensin II type 1 receptor agonistic autoantibody

AGT1R-B2 Angiotensin II type 1 receptor-bradykinin B2 receptor heterodimer

AGT2R Angiotensin II type 2 receptor

ANG 1-7 Angiotensin 1-7

ANG 1-9 Angiotensin 1-9

ANG I Angiotensin I

ANG II Angiotensin II

BMI Body mass index

C.I. Confidence interval

dBP Diastolic blood pressure

DNA Deoxyribonucleic acid

dNK Decidual natural killer cell

ELISA Enzyme-linked immunosorbent assay

EMT Epithelial mesenchymal transition

EVT Extravillous trophoblasts

FCS Fetal Calf Serum

GDM Gestational diabetes

GHT Gestational hypertension

hAGT Human angiotensinogen

hCG Human chorionic gonadotropin

hrenin Human renin

HUVEC Human umbilical vein endothelial cells

IL-6 Interleukin-6

IUGR Intrauterine growth restriction

NEP Neutral endopeptidase 24.11

OR Odds ratio

PAI-1 Plasminogen activator inhibitor-1

PCR Polymerase chain reaction

PEP Prolyl-endopeptidase

PIH Pregnancy-induced hypertension

RAS Renin angiotensin system

RI Resistance index

RR Relative risk

sBP Systolic blood pressure

SCOPE Screening for Pregnancy Endpoints

SEI Socio-economic index

sFlt1 Soluble fms-like tyrosine kinase 1

SGA Small for gestational age

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SNP Single nucleotide polymorphism

sPTB Spontaneous preterm birth

VEGF Vascular endothelial growth factor

1

CHAPTER 1

Renin angiotensin system and pregnancy complications

2

Overview

The classical renin angiotensin system (RAS) is an endocrine system, which plays an

important role in blood pressure regulation and salt-water homeostasis. Research over the past

30 years has shown that the RAS also exists at the tissue level and mediates a multitude of

paracrine and autocrine physiological functions.

During pregnancy, the maternal circulating RAS is activated and is important in maternal

adaptation to pregnancy. The presence of an uteroplacental RAS is well documented and it is

thought to play a role in several important processes during placentation. Aberrant maternal

circulating and uteroplacental RAS profiles have been observed in preeclamptic pregnancies,

implying the involvement of the RAS in the pathogenesis of preeclampsia.

The associations of RAS polymorphisms with pregnancy complications, especially

preeclampsia, have been investigated in several studies. However, most of these association

studies failed to address three aspects, namely, gene-environment interactions, gene-fetal sex

interactions and paternal genotype. Gene-environment and gene-fetal sex interactions are

important because they may modify the strength of gene-disease associations. In addition,

several studies have revealed that there is a paternal genetic predisposition to major pregnancy

complications.

The current review is divided into four parts: part 1-The renin angiotensin system, which

highlights the components of the RAS and its general functions; part 2-The RAS during

pregnancy, which details the changes in maternal circulating RAS components during

pregnancy and the presence of an uteroplacental RAS, as well as the role of the uteroplacental

RAS in placentation; part 3-The RAS and pregnancy complications, which delineates the

changes observed in maternal circulating RAS and the uteroplacental RAS in pregnancies

complicated by preeclampsia; part 4-The association of RAS polymorphisms with pregnancy

complications, which presents 8 single nucleotide polymorphisms in various components of

3

the RAS and also provides the rationale for addressing gene-environment interactions,

paternal genotype and fetal sex in the association of RAS polymorphisms with pregnancy

complications.

4

1.1 The renin angiotensin system

The renin angiotensin system (RAS) is a complex system and comprises several components

(Figure 1.1). It functions at both systemic and tissue levels. The systemic RAS circulates in

the blood stream and has endocrine actions on various systems or organs such as the

cardiovascular system, kidney, sympathetic nervous system and adrenal cortex [1], whereas

the local RAS is produced within tissues where it has paracrine or autocrine actions [2].

The RAS is activated through serial enzymatic cleavage (Figure 1.1). The major effectors at

the end of the activation cascade are angiotensin II (ANG II) and angiotensin 1-7 (ANG 1-7).

Angiotensinogen (AGT) is first cleaved by renin to form angiotensin I (ANG I), which is

further cleaved by angiotensin converting enzyme (ACE) to ANG II [3]. ANG 1-7 can be

formed from either ANG II or ANG I through hydrolysis by various peptidases, including

ACE, ACE2, prolyl-endopeptidase (PEP) and neutral endopeptidase 24.11 (NEP) (Figure 1.1).

The current review will focus on the following key RAS components, renin, AGT, ACE),

ACE2, ANG II, ANG 1-7, angiotensin II type 1 and type 2 receptors (AGT1R and AGT2R)

and the Mas receptor. The other RAS components will only be drawn where appropriate.

ANG II binds two main receptors, AGT1R and AGT2R, which have similar affinity for ANG

II [4]. It is generally accepted that the response to ANG II is determined by the balance in

expression of AGT1R and AGT2R [4,5]. AGT1R is abundantly expressed in various tissues,

such as heart, vasculature, brain, kidney, female and male reproductive tracts, stomach,

pancreas and colon [2]. The well known actions of ANG II, including vasoconstriction,

proliferation, angiogenesis and inflammation, are elicited via its interaction with AGT1R [6].

In the adrenal cortex, ANG II via AGT1R stimulates the secretion of aldosterone, which

promotes Na+ reabsorbtion (and hence water retention) in nephrons [7]. AGT2R is widely

expressed in fetal tissues but its expression decreases rapidly after birth [8], suggesting that it

may play a role in growth and development [5]. AGT2R appears to oppose the effects of

5

AGT1R. Upon binding with ANG II, AGT2R signalling increases apoptosis [9,10], causes

vasodilatation [11] and is anti-inflammatory [4].

The ACE2-ANG1-7-Mas receptor axis is a newly established axis of the RAS and is

considered a counter-regulatory system opposing the classic ACE-ANG II-AGT1R axis [12].

ANG 1-7 acting through the Mas receptor has been shown to mediate vasodilatation [13,14]

and potentiate the effect of bradykinin [15,16,17,18,19] and it is cardioprotective in diabetic

rats [20]. Due to the opposing effects between ANG II and ANG 1-7, it is proposed that the

RAS may be viewed as a dual function system in which its final effect depends on the balance

of ANG II and ANG 1-7 [21]. The balance of ANG II/ANG 1-7 has been shown to be

important in hemodynamic changes in human liver cirrhosis [22].

1.2 RAS during normal pregnancy

1.2.1 Maternal systemic RAS

Pregnancy is associated with a 30-50% increase in plasma volume and cardiac output

concurrent with a paradoxical decrease in maternal blood pressure [23]. These massive

hemodynamic changes can only be explained by a primary dramatic fall in peripheral vascular

resistance [24], which could be attributable to elevation of nitric oxide in endothelial cells

triggered by estrogen and progesterone [23].

The RAS is one of the first hormone systems to ‘recognise’ pregnancy [25]. Its activation is

thought to be induced by the decreased systemic vascular resistance [23] and contributes to

the plasma volume expansion by conserving sodium [23]. Plasma prorenin begins to rise

within 2 weeks after conception and reaches a peak of about 10 times the non-pregnant state

and remains high until parturition [26]. The extrarenal sites including the ovary [27] and

uteroplacental unit [28] have been shown to contribute to the rise in plasma prorenin.

Elevated plasma active renin concentration [29] and plasma renin activity [30] are also

observed. Plasma AGT concentration rises in the first 20 weeks, owing to estrogen stimulated

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hepatic synthesis of AGT, then remains constant [31,32,33]. Despite the suppression of

plasma ACE activity during pregnancy [29,30,34], plasma ANG II concentration has been

shown to be elevated in the second and third trimester [29,30,35,36]. In addition, plasma

aldosterone concentration is elevated as early as 6 weeks’ pregnancy and reaches a maximum

in the third trimester, at a level 8 to 10 fold higher than in non-pregnant women [25,29,37].

Since ANG II is also a potent vasoconstrictor, its rise during pregnancy would be expected to

elevate women’s blood pressure and make all pregnant women hypertensive, but this does not

happen because pregnancy is also associated with a profound decrease in vascular

responsiveness to ANG II [38,39,40,41]. Specifically, the vascular refractoriness to ANG II is

detected in the first trimester, peaks at mid gestation and becomes less apparent in the third

trimester [40]. At the peak refractory periods, nearly twice the amount of ANG II is required

to induce the same degree of vasoconstriction observed in the non-pregnant state [40]. This

pregnancy associated vascular refractoriness to ANG II has been attributed in part to the

vasodilatation effects caused by progesterone and prostaglandins, in particular prostacyclin

and prostaglandin E2 [25,42].

Despite the development of vascular refractoriness to ANG II in pregnant women, maternal

blood pressure during pregnancy is maintained to a significant extent by the RAS.

Administration of captopril, an ACE inhibitor, leads to a greater fall in blood pressure in

pregnant women (undergoing elective termination of pregnancy) than non-pregnant women

with similar baseline blood pressure [43]. In addition, in pregnant mice, while no changes in

blood pressure across gestation have been observed in wild type, a significant decrease in

blood pressure is demonstrated in AGT1a receptor null mice [44].

There are limited data on the ACE2-ANG 1-7-Mas receptor axis during pregnancy. Plasma

ANG 1-7 concentration is higher in third trimester pregnant women than non-pregnant

women [30]. Since urinary ANG 1-7 concentration increases throughout gestation [45],

elevation of maternal plasma ANG 1-7 likely occurs in early pregnancy. ANG 1-7 mediates

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vasodilatation [13,14], therefore, elevation of ANG 1-7 during pregnancy may contribute to

the mild decrease in blood pressure associated with pregnancy and vascular refractoriness to

ANG II.

In summary, the maternal systemic RAS is activated in early pregnancy and thought to be

important in plasma volume expansion. During pregnancy, maternal blood pressure is

maintained to a significant extent by the RAS.

1.2.2 Uteroplacental RAS

The expression of RAS components, including AGT, prorenin, ACE, ACE2, AGT1R,

AGT2R and the Mas receptor have been observed in the uteroplacental unit

[46,47,48,49,50,51,52,53] (Table 1.1), suggesting a local production of ANG II and ANG 1-7

and their potential involvement in placentation. Since the uteroplacental expression of

AGT2R [51] and Mas receptor [50] is low, it is likely that the net effect of the uteroplacental

RAS is determined by the interaction between ANG II and AGT1R. Furthermore, the

comparison between decidual and placental RAS profiles reveals that higher expression of

prorenin, AGT and ACE are observed in the decidua, whereas higher AGT1R expression is

found in the placenta, suggesting that the decidua is responsible for the production of ANG II,

whereas the placenta is the target organ [48].

In the placenta, ANG II has been suggested to play a role in regulating placental endocrine

function, nutrient transport, placental angiogenesis and feto-placental blood flow. ANG II

interacting with AGT1R on trophoblast cells stimulates the secretion of several endocrine

factors, including human placental lactogen [54], pregnancy-specific β1-glycoprotein [54,55]

and oestradiol [56]. ANG II also stimulates the synthesis of vasorelaxants, including nitric

oxide [46] and parathyroid hormone-related protein [46]. In addition, acting on AGT1R, ANG

II has been shown to inhibit the activity of system A amino acid transporters [57], which

mediates transport of small neutral amino acids, such as alanine, serine, glutamine, and

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glycine [58,59]. Consistently, syncytiotrophoblast AGT1R immunoreactivity is negatively

correlated with infant birth weight [60]. Furthermore, ANG II via AGT1R mediates angiotube

formation of human umbilical vein endothelial cells (HUVECs) [61,62] and decreases the

release of soluble fms-like tyrosin kinase 1 (sFlt1, an anti-angionenic factor) in chorionic villi

[63], suggesting its role in stimulating placental angiogenesis. Finally, in sheep, fetal infusion

of ANG II increases umbilical vascular resistance by up to 345% [64], indicating its potent

vasoconstricting action in the fetoplacental circulation.

At the maternal-fetal interface, ANG II acting on AGT1R has been shown to promote

proliferation of cytotrophoblasts in the cell columns [51,65] and alter cytotrophoblast

expression of epithelial mesenchymal transition (EMT) markers including α1 and α5 integrin,

MMP-2 and MMP-9 [65] in a way that EMT is likely to be inhibited. These data together

suggest that ANG II may arrest cytotrophoblasts in the proliferative stage and inhibit their

differentiation towards the invasive phenotype [65].

In the decidua, the interaction between ANG II and AGT1R may be important in regulating

trophoblast invasion, spiral artery remodelling and uterine blood flow. Using HTR-8/SVneo

trophoblast cells, ANG II via AGT1R has also been shown to inhibit trophoblast invasion [66].

In addition, the TT genotype of AGT M235T, a functional polymorphism in the AGT gene, is

associated with narrower spiral arteries compared with the MM or MT genotypes [67]. Since

the AGT M235T TT genotype is also associated with a higher AGT concentration in decidual

spiral arteries [68], and hence potentially a higher ANG II concentration, the association

between AGT M235T and diameter of spiral arteries may suggest that ANG II inhibits spiral

artery remodelling [67]. Consistently, in rats, activation of the RAS induced by low sodium

diet inhibits the remodelling of the arcuate arteries [69]. Furthermore, ANG II administration

to healthy pregnant women at 24 to 26 weeks' gestation leads to a significant increase in the

systolic/diastolic ratio in the uterine artery, a measure of uterine artery resistance [70,71],

indicating the vasoconstricting effect of ANG II in regulating uterine blood flow.

9

The role of uteroplacental AGT2R and ANG 1-7 is still poorly understood. Since it is

generally accepted that the response to ANG II is determined by the balance in expression of

AGT1R and AGT2R [4,5], uteroplacental AGT2R has also been suggested to modulate the

action of AGT1R in the uteroplacental unit [52]. In addition, placental AGT2R has been

suggested to play a role in apoptosis, cellular proliferation and angiogenesis during early

placentation [52], when highest AGT2R expression is observed [52]. ANG 1-7 acting on the

Mas receptor has been shown to inhibit endothelial cell tube formation in HUVECs [72],

suggesting its inhibitory role in placental angiogenesis. Furthermore, ANG 1-7

immunostaining in the decidua is found in extravillous and intravascular cytotrophoblasts

[49,73], suggests its potential role in trophoblast invasion and spiral artery remodelling.

Future studies should investigate the expression of the Mas receptor in these cells and

determine the role of ANG 1-7 in trophoblast invasion and spiral artery remodelling.

In summary, the ACE-ANG II-AGT1R axis appears to be the dominant RAS axis in the

uteroplacental unit and may be involved in several processes, including synthesis/secretion of

endocrine factors, nutrient transport, placental angiogenesis, EMT, trophoblast invasion,

spiral artery remodelling and uterine and placental blood flow.

1.3 RAS and pregnancy complications

1.3.1 Pregnancy complications

Preeclampisa, small for gestational age (SGA) and preterm birth (PTB) are the major

complications of late pregnancy. They significantly overlap with each other and together

affect 19% of first pregnancies and are the major causes of mortality and morbidity in

mothers and babies worldwide. The three complications are not only life threatening to the

mother and or fetus at the time of pregnancy but also are associated with lifelong health,

including the development of heart disease and related stroke, diabetes and hypertension [74].

10

Preeclampsia occurs in 3-5% of pregnancies and is a major cause of maternal morbidity in

developed countries [75]. It is diagnosed as hypertension arising after 20 weeks’ gestation,

plus one or more of the following symptoms: proteinuria, renal insufficiency, liver disease,

neurological problems, haematological disturbances or fetal growth restriction [76]. Mild

preeclampsia may be managed by treatment of the hypertension and other symptoms but the

only cure is delivery of the placenta [77]. Consequently, preeclampsia is also a major

contributor to preterm birth [77], birth of a baby less than 37 weeks gestation. In addition, one

third of preeclamptic pregnancies are also complicated by intrauterine growth restriction

(IUGR) of the fetus [78].

IUGR refers to a fetus who does not reach its genetically determined growth potential [79]. In

Australia, approximately 6.5% babies are born growth restricted [80]. Since fetal growth is

difficult to measure, SGA, which is defined as birth weight less than the 10th

centile for

gestational age, is often used as a proxy for IUGR [81]. Traditionally, SGA is classified by

using population centiles, which includes not only IUGR infants but also healthy

constitutionally small infants [81] who do not have an increased risk of mortality. In order to

reduce false-positive diagnosis of IUGR for the constitutionally small infants, customized

birth weight centiles have been used to define SGA [82]. Customized centiles take account of

the following factors: infant sex, gestation at delivery and maternal variables including parity,

ethnicity, weight and height. All these factors have independent effects on birthweight [83].

Studies have shown that using customized centiles is better at identifying babies at risk of

perinatal morbidity and mortality than population centiles [81,83,84]. The SGA pregnancies

in the current study are defined by the customized birth weight centile.

1.3.2 RAS and preeclampsia

Since the RAS plays an important role in blood pressure regulation during pregnancy and

hypertension is one of the symptoms of preeclampsia, it is logical to speculate that the RAS

might be involved in its pathogenesis. Indeed in the past decades, maternal circulating and

11

uteroplacental RAS have been studied intensively for their potential roles in the pathogenesis

of preeclampsia.

1.3.2.1 Maternal systemic RAS in preeclampsia

In women with established preeclampsia, plasma total and active renin concentration and

renin activity are repressed [25,30,85]. Plasma total AGT concentration is generally

unchanged [86], although the proportion of oxidised AGT, which renin preferentially interacts

with, is increased [87]. Despite an elevation in plasma/serum ACE activity [30,85], plasma

ANG II [29,30,35,36,85] and aldosterone [29] concentrations are suppressed. The suppression

of circulating RAS levels in preeclamptic women is likely due to the negative feedback from

the elevated blood pressure once the condition is established [25]. In a prospective study,

plasma renin activity has been shown to be higher in the second trimester in women who go

on to develop preeclampsia than those with normal pregnancies [88], suggesting that maternal

RAS level/activity increases prior to the onset of preeclampsia.

Preeclampisa is associated with two features, loss of vascular refractoriness to ANG II and

development of autoantibodies against the AGT1R (AGT1R-AA), both of which would lead

to excess activation of AGT1R in the mother despite the suppression of the circulating RAS.

As mentioned earlier, normal pregnancy is associated with vascular refractoriness to ANG II

[38,39,40,41], a mechanism counteracting the elevated circulating RAS in pregnancy (section

1.2.1) but this is lost in women with preeclampsia [40,89]. The difference in vascular

responsiveness to ANG II between normal and preeclamptic women becomes apparent at 22

weeks’ gestation (before clinical manifestations of preeclampsia) and continued to diverge for

the rest of gestation [40]. The presence of AGT1R-AAs in serum of preeclamptic women has

been observed by independent groups [90,91]. Interestingly, its presence has also been

identified in animal models of preeclampsia [92,93]. AGT1R-AAs bind to the second

extracellular loop of AGT1R and have agonist actions [90]. The concentration of AGT1R-AA

is positively correlated with severity of preeclampsia [91].

12

A possible causal relationship between excess activation of AGT1R and preeclampsia has

been demonstrated in mice experiments [94,95]. Specifically, excess activation of AGT1R,

which is induced by injection of AGT1R-AA [94] or elevation of plasma ANG II due to the

secretion of placenta-derived renin [95], leads to the development of preeclampsia-like

symptoms, including hypertension, proteinuria and placental abnormalities. These symptoms

are prevented by the blockage of AGT1R activation [94,96]. Furthermore, in vitro studies

have shown that activation of AGT1R by ANG II or AGT1R-AA stimulates the synthesis

and/or secretion of several molecules, including sFlt-1 [97], type 1 plasminogen activator

inhibitor [98,99], reactive oxygen species[100], intracellular Ca2+

concentration [101] and

tissue factor [102,103]. Elevations of all these molecules have been implicated in

preeclampsia [104,105,106,107,108] and contribute to the development of preeclamptic

symptoms [109].

Finally, there is limited information on AGT2R and ANG 1-7 in preeclampsia. An in vitro

study demonstrates that AGT2R mRNA expression in HUVECs is significantly decreased

when incubated in serum from pregnancy induced hypertension [110]. The data may suggest a

suppression of vascular AGT2R expression in preeclampsia, which may act as one of the

mechanisms leading to the elevation in blood pressure. However, caution is advised when

deducing information from pregnancy induced hypertension, since it is generally accepted

that preeclampsia and pregnancy induced hypertension are pathologically distinctive.

Furthermore, maternal plasma ANG 1-7 concentration is suppressed in third trimester

preeclamptic women [30,85]. ANG 1-7 mediates vasodilatation [13,14], therefore,

suppression of ANG 1-7 may contribute to elevated blood pressure in preeclamptic women.

In summary, although the maternal circulating RAS is suppressed, preeclamptic women are

characterised by loss of vascular refractoriness to ANG II and development of AGT1R-AA,

both of which would lead to excess activation of AGT1R and contribute to the pathogenesis

of preeclampsia.

13

1.3.2.2 Uteroplacental RAS in preeclampsia

Preeclampsia is associated with an elevation of ACE-ANG II-AGT1R axis in the

uteroplacental unit. Specifically, in chorionic villi, there is a 4-fold increase in active renin

concentration [111], 2.5-fold increase in AGT mRNA level [112], 2-fold increase in ANG II

peptide concentration [112] and 3-fold increase in AGT1R mRNA level [112] associated with

preeclampsia. In the decidua, a 6-fold increase in prorenin mRNA level [49], 3-fold increase

in ACE mRNA level [49], 3-fold increase in ANG II concentration [49] and 5-fold increase in

AGT1R mRNA expression [48] are found in preeclampsia. In addition, no or subtle

difference in AGT2R mRNA expression and ACE2-ANG 1-7-Mas receptor axis are found

between normal and preeclamptic chorionic villi [112] and decidua [49].

The elevated ACE-ANG II-AGT1R axis in the uteroplacental unit of preeclampsia may be a

consequence of repairing the compromised uteroplacental perfusion. The uteroplacental RAS

has long been thought to play an important role in maintaining uteroplacental blood flow

[113,114]. Specifically, in response to a fall in uteroplacental perfusion, the uteroplacental

RAS is activated and diverts more blood flow to the uteroplacental unit by elevating maternal

blood pressure and stimulating uterine production of vasodilator prostaglandins [113].

In preeclampsia, uterine production of vasodilator prostaglandins is compromised [113]. As a

result, in the uteroplacental unit, the elevated RAS acts as a vasoconstrictor, which further

impairs uteroplacental blood flow. In addition, given the role of AGT1R in the uteroplacental

unit (section 1.2.2), elevation of the ACE-ANG II-AGT1R axis in the uteroplacental unit

would also result in the following adverse effects, inhibition of system A amino acid

transporter activity, inhibition of EMT and invasion of cytotrophoblasts and impaired spiral

artery remodelling. All these would contribute to the impaired placentation seen in

preeclampsia.

14

In summary, the uteroplacental ACE-ANG II-AGT1R axis is elevated in preeclamptic

pregnancies, which may be a consequence of compromised uteroplacental perfusion. The

elevated ACE-ANG II-AGT1R may increase blood pressure and impair uteroplacental blood

flow and placentation, which would further contribute to the development of preeclampsia.

1.3.3 RAS and other pregnancy complications

There are limited data on maternal circulating and uteroplacental RAS profiles in pregnancies

complicated by IUGR. Third trimester plasma aldosterone concentration is reduced in IUGR

pregnancies [115], which may contribute to the impaired maternal plasma volume expansion

observed in IUGR [115,116,117,118,119]. In addition, the T variant of AGT M235T, a

functional polymorphism in AGT gene, which is associated with lower plasma volume

compared with the M variant in non-pregnant women [120], is also associated with an

increased risk for IUGR [121]. These data together suggest that the RAS may be involved in

the pathogenesis of IUGR and its involvement is likely exerted through its effect on plasma

volume expansion. Furthermore, placental AGT1R density is down-regulated in placentas

from IUGR pregnancies [46,122], which may contribute to the impaired placental

angiogenesis observed in IUGR pregnancies [123].

The involvement of the RAS in the pathogenesis of preterm delivery has rarely been

investigated. Functional RAS polymorphisms, including ACE I/D [124] and AGT M235T [125]

have previously been shown to associate with preterm delivery, suggesting a potential

involvement of the RAS in the pathogenesis of the complication. Given the role of the

uteroplacental RAS in placentation (section 1.2.2), further studies should investigate the

uteroplacental RAS profiles in preterm birth, in which impaired placentation is observed

[126].

15

1.4 The association of RAS polymorphisms with pregnancy complications

1.4.1 RAS polymorphisms

Given the role of the RAS in the pathogenesis of pregnancy complications, functional

polymorphisms in genes of RAS components, which are associated with RAS protein levels

and/or activity, may predispose a woman to pregnancy complications.

1.4.1.1 Renin T/G

Renin T/G (rs5707) is located in intron 4 of the human renin gene on chromosome 1. While

the association of this polymorphism with plasma renin activity or concentration has not been

determined previously, two Spanish cohorts find women with the renin T/G GG genotype

have higher systolic blood pressure and an increase risk for hypertension than those with TT

or GT genotypes [127]. Since hypertension is both a risk factor for and a symptom of

preeclampsia, renin T/G may be associated with preeclampsia.

1.4.1.2 AGT M235T

AGT M235T (rs699) is located in exon 2 of the angiotensinogen gene on chromosome 1, is a

T to C substitution, which results in a change in the amino acid from Methionine to Threonine.

In a Meta analysis, combining a total of 6 non-pregnant cohorts, MT and TT genotypes of

AGT M235T are associated with 5% and 11% increase in plasma AGT concentration

compared to the MM genotype, respectively [128]. In addition, its association with plasma

AGT concentration has also been observed in a pregnant cohort among preeclamptic women

[129].

The AGT M235T TT genotype is found to be associated with increased risk for preeclampsia

in an American cohort [129], two Japanese cohorts [129,130] and a Greek cohort [131].

However, the result could not be replicated in other cohorts

[67,132,133,134,135,136,137,138,139,140]. In addition, in a German cohort, the AGT M235T

16

TT genotype is associated with reduced birth weight [141] and IUGR [121], suggesting that it

may potentially associate with SGA. Furthermore, in a Mexican cohort, the AGT M235T TT

genotype is associated with increased risk for preterm birth with premature rupture of

membranes [125].

1.4.1.3 AGT T174M

AGT T174M (rs4762), located in exon 2 of the AGT gene on chromosome 1, is a C to T

substitution, which leads to an amino acid change from Threonine to Methionine. AGT

T174M has been shown to be in complete linkage disequilibrium with AGT M235T [142].

However, unlike AGT M235T, studies fail to find associations of AGT T174M with plasma

AGT concentration [142,143] and preeclampsia [144]. In a recent Romanian cohort, the AGT

T174M MM genotype is associated with a 3.8 weeks reduction in gestational age and a 512 g

reduction in birth weight compared to the TT genotype [144], suggesting that AGT T174M

may potentially associate with preterm birth and SGA.

1.4.1.4 ACE A11860G

ACE A11860G or ACE G2350A (rs4343) is a silent substitution located in exon 16 of the ACE

gene on chromosome 17. It has been shown to be in near perfect linkage disequilibrium with

the well-known ACE I/D in a British cohort [145] and appears to be a stronger predictor of

plasma ACE concentration than ACE I/D [146]. In addition, ACE A11860G has been shown

to associate with serum ACE activity in two independent cohorts of young-onset hypertension

subjects [147].

The ACE A11860G GG genotype has been shown to associate with various disease

phenotypes, including type 2 diabetic nephropathy [148], Alzheimer’s disease

[149,150,151,152], coronary artery disease [153], hypertension [154] and left ventricular

hypertrophy [155]. In a Romanian cohort, the combination of maternal and fetal G alleles of

ACE A11860G is associated with a 3.3 fold increase in the risk for preeclampsia [144].

17

1.4.1.5 AGT1R A1166C

AGT1R A1166C (rs5186) is located in the 3’ UTR of AGT1R gene on chromosome 3. The

AGT1R A1166C CC genotype has been shown to associate with a greater response to ANG II,

measured by the contraction of the internal mammary artery isolated from patients who

underwent coronary artery bypass graft surgery [156]. In addition, the AGT1R A1166C CC

genotype or C alleles are also associated with coronary artery disease and myocardial

infarction [157]. Furthermore, the combination of maternal and fetal AGT1R A1166C C allele

is associated with a 2.7 fold increase in risk for preeclampsia in a Romanian cohort [144]. In a

polish cohort, women with the AGT1R A1166C CC genotype have a 2.7 fold increase in risk

for pregnancy induced hypertension [158].

1.4.1.6 AGT2R C4599A

AGT2R C4599A (rs11091046) is located in the 3’ UTR of exon 3 of the AGT2R gene on

chromosome X. The functional effect of AGT2R C4599A on AGT2R has not been

investigated previously. In a Japanese population, although the AGT2R C4599A C allele is

associated with elevated BMI [159] and higher plasma concentration of HbA1c, a measure of

plasma glucose concentration, it has been shown to protect against hypertension [160]

whereas the AGT2R C4599A A allele increases risk for hypertension [161] and myocardial

infarction [162]. In a recent Romanian study, women bearing the AGT2R C4599A AA

genotype are at an increased risk for developing preeclampsia [OR 3.8 (95% CI 1.1-12.5)]

[144].

1.4.1.7 AGT2R A1675G

AGT2R A1675G (rs1403543) is located in intron 1 of the AGT2R gene on chromosome X. It

has been shown to be in linkage disequilibrium with AGT2R C4599A in a Japanese population

[160]. Utilizing the luciferase assay, the AGT2R A1675G G allele has been shown to associate

18

with higher AGT2R expression [163]. In addition, in an Afro-Caribbean cohort, women with

AGT2R A1675G GG genotype have an increased risk for preeclampsia [164].

1.4.1.8 AGT2R T1334C

AGT2R T1334C (rs12710567) is located in the promoter of the AGT2R gene on chromosome

X. The functional effect of AGT2R T1334C on AGT2R has not been determined previously.

In a Chinese cohort, the AGT2R T1334C C allele is associated with increased risk for essential

hypertension [165]. Since hypertension is a risk factor for preeclampsia, AGT2R T1334C may

be associated with preeclampsia.

In summary, the selected RAS polymorphisms in the current thesis either have functional

effects on their respective proteins or have been shown to associate with risk factors for

pregnancy complications, such as hypertension and elevated BMI. These make them excellent

candidates for genetic association studies for pregnancy complications. In fact, some of these

RAS polymorphisms have been shown to associate with preeclampsia. However, the effect of

paternal genotype, gene-environment interactions and gene-fetal sex interactions have not

been addressed in these previous association studies.

19

1.4.2 Paternal genotype in association studies

Epidemiological studies have shown that the risks for major pregnancy complications, such as

preeclampsia, SGA and preterm birth, are determined, not only by maternal predisposition,

but also by a fetal contribution inherited from the father. Men born to a preeclamptic

pregnancy are twice as likely to father a preeclamptic pregnancy [166]. In addition, men who

have fathered a preeclamptic pregnancy are nearly twice as likely to father a preeclamptic

pregnancy with a different woman, regardless of whether she has already had a preeclamptic

pregnancy or not [167]. Men born SGA have a 3.5-fold greater risk of fathering a SGA

pregnancy [168]. Furthermore, a man’s own gestational age has been shown to positively

correlate with his offspring’s gestational age [169,170].

Recent association studies have shown that paternal HLA-C [171] and KDR [172] genotypes

are associated with risk for preeclampsia. The paternal HLA-C genotype modifies the risk for

preeclampsia through modulating decidual natural killer cell activity and hence spiral artery

remodelling [171], whereas the effect of paternal KDR genotype is thought to modulate

placental angiogenesis [171]. Given the role of the placental RAS in placentation (section

1.2.2), paternal RAS genotypes, which contribute to half of the placental RAS genotypes, may

modify risks for pregnancy complications through modulating placental development and

function. In addition, since placenta-derived renin in a transgenic mouse model has been

shown to elevate maternal circulating ANG II concentration and consequently lead to

preeclampsia-like symptoms [95], it is possible that paternal RAS genotypes may also modify

risks for pregnancy complications via modulating maternal physiology.

1.4.3 Gene and environment interactions in association studies

Gene-environment interaction describes the phenomenon in which the association of a genetic

variant with a disease phenotype varies with the degree of exposure to an environmental

factor or vice versa [173]. Lack of appreciation of environmental factors in gene association

20

studies may potentially leave the genetic effect unrecognized. CYP1A1 is one of the enzymes

involved in metabolism of toxins in cigarette smoke. In a recent study, maternal smoking has

been shown to modify the association of a polymorphism in the CYP1A1 gene with IUGR,

such that the association is only apparent in smokers [174]. Initially, when maternal smoking

status is not considered and the analysis is performed on the entire cohort, the effect of the

CYP1A1 polymorphism, which is only apparent in smokers, is diminished by non-smokers,

which makes up 83% of the cohort. Similarly, in another study, the association of ACE I/D

DD genotype with hypertension, which is only observed in smokers, would not be revealed

without examining participants’ smoking status [175]. Finally, previously published genetic

association studies for pregnancy complications have proved difficult to replicate. In the light

of the gene-environment interactions mentioned above, inconsistent results may be partly

explained by the differences in environmental factors between studies.

1.4.4 Fetal sex in association studies

Fetal sex has become an important aspect to consider in pregnancy related research. It has

been shown that fetal sex modifies the risk for pregnancy complications. Specifically, female-

bearing pregnancies are more likely to experience gestational hypertension [176],

preeclampsia [176] and IUGR [177], whereas male-bearing pregnancies are at greater risk for

preterm delivery [178,179,180,181], macrosomia [182], gestational diabetes [182], cord

complications [182] and caesarean delivery [182,183,184,185,186]. These sex differences in

risks for pregnancy complications may be partly explained by sexual dimorphism of the

placenta. Global gene expression [187] and microRNA expression [188] of the human

placenta are different between sexes. Interestingly, placental genes which display sexual

dimorphism are not limited to those linked to the X and Y chromosomes but also those in

autosomes, which are related to immune pathways [187].

Fetal sex deserves special attention in the association of RAS polymorphisms with pregnancy

complications. Recent studies have shown that fetal sex affects maternal systemic and

21

uteroplacental RAS levels/activities, such that women bearing a female fetus have higher

circulating ANG II concentration (Sykes et al submitted) and a higher level of decidual

prorenin mRNA expression and protein secretion than those bearing males [189]. These fetal

sex differences in maternal circulating and uteroplacental RAS profiles may potentially

translate to fetal sex differences in the association of RAS polymorphisms with pregnancy

complications. In adults, several RAS components are sexually dimorphic [190,191] and as a

consequence, the association of RAS polymorphisms with cardiovascular diseases varies

between the sexes, such that the associations are more profound in males than females

[192,193,194,195,196,197].

22

1.5 Aims and structure of the current thesis

The following aims will be addressed in this thesis:

1. To investigate the association of RAS polymorphisms in mothers, fathers and babies

with major pregnancy complications, including

i) Small for gestational age

ii) Preeclampsia

iii) Spontaneous preterm birth

2. To determine the association of maternal and neonatal RAS polymorphisms with

maternal plasma RAS peptide concentrations at 15 weeks’ gestation, including

prorenin, ACE, ANG II and ANG 1-7.

3. To investigate the association of RAS polymorphisms in mothers, fathers and babies

with maternal blood pressure at 15 weeks’ gestation, uterine and umbilical artery

resistance indices at 20 weeks’ gestation.

In aims 1 and 3, in order to investigate potential gene-fetal sex and gene-environment

interactions which may modify risks for pregnancy complications, the study population was

stratified by fetal sex and environmental factors, including maternal age (age <29 years versus

≥29 years), maternal BMI (BMI <25kg/m2 versus ≥25 kg/m

2), green leafy vegetable intake

(vegetable intake <1 serve/day versus ≥1 serve/day), maternal socioeconomic status (SEI <34

versus ≥34) and smoking at 15 weeks’ gestation (no smoking versus smoking). These

environmental factors have previously shown to affect the risk for pregnancy complications

[198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213].

The current thesis consists of 8 chapters and chapter 4-7 were written in publication format.

As you have seen, chapter 1 provided a comprehensive review on maternal systemic and

uteroplacental RAS in normal and complicated pregnancies and highlighted selected RAS

polymorphisms in the current study. The following chapter (i.e. chapter 2) delineates the

23

recruitment of participants, data collection, classification of pregnancy complications and

experimental protocols utilized during the study. Chapter 3 presents the characteristics of the

study population and explores the differences between Australian and New Zealand cohorts.

Chapter 4 and 5 determine the functional effects of selected RAS polymorphisms by

investigating their associations with maternal circulating RAS concentrations at 15 weeks’

gestation, maternal blood pressure at 15 weeks’ gestation and abnormal uterine and umbilical

artery resistance indices at 20 weeks’ gestation. Chapters 6 and 7 investigate the association

of RAS polymorphisms with SGA and preeclampsia, with emphasis on paternal effects, gene-

fetal sex interaction and gene-environment interactions. Chapter 8 integrates findings from

chapter 4-7 and highlights those with important implications.

24

Figure 1.1 The activation cascade of the RAS (adapted from [214])

Abbreviations: AGT: angiotensinogen; ANG I: angiotensin I; ANG II: angiotensin II; ANG 1-9: angiotensin 1-9; ANG 1-7: angiotensin 1-7;

ANG III: angiotensin III; ANG IV: angiotensin IV; ACE: angiotensin converting enzyme; ACE 2: angiotensin converting enzyme 2; PEP:

prolyl-endopeptidase; NEP: neutral endopeptidase 24.11; AGT1R: angiotensin II type 1 receptor; AGT2R: angiotensin II type 2 receptor;

AGT4R: angiotensin II type 4 receptor; RPR: renin/prorenin receptor; AMPA: aminopeptidase A; AMPM: aminopeptidase M; MCP-1:

monocyte chemoattractant protein-1; IL6: interleukin-6; PAI-1: platelet activator inhibitor-1 (PAI-1); NF-кB: nuclear factor-кB; ICAM-1:

intracellular adhesion molecule-1.

AMPA

AGT

ACE, NEP

ANG I

ACE

ANG III ANG 1-7

AGT1R AGT2R Mas receptor

ANG 1-9 ACE 2

Renin

↑ Aldosterone

Vasoconstriction

Cell proliferation

↑Angiogenesis

Pro-inflammation

Vasodilatation

↑Apoptosis

Anti-inflammation

ACE2, PEP

Vasodilatation

Cardioprotective

NEP

PEP

ANG IV AMPM

RPR AGT4R

Prorenin

ANG II

Activation of NF-кB

Induction of MCP-1, IL6,TNFα,

ICAM-1 and PAI-1

↑ Contractility

↑ Hypertrophy

↑ Fibrosis

↑ Apoptosis

25

Table 1.1 Location of RAS components in the uteroplacental unit.

Prorenin In the placenta, prorenin is localised to syncytiotrophoblasts [50]. In the decidua, it is

localized to macrophages [215] and smooth muscle cells of veins and spiral arteries

[53].

AGT Strong AGT immunostaining is detected in the syncytiotrophoblast layer of term

placental villi [50]. In the decidua, AGT mRNA expression is found in spiral artery

smooth muscle cells [68].

ACE In the placenta, ACE expression is present in the fetal endothelium [50]. In the

decidua, it is found in endothelial cells of spiral arteries and some perivascular

decidual stromal cells [53].

ACE2 In the placenta, ACE2 immunostaining is found in the syncytiotrophoblast,

cytotrophoblast, endothelium and vascular smooth muscle of primary and secondary

villi [73]. In the decidua, it is located in the extravillous interstitial and endovascular

trophoblasts and decidual cells [49,73].

AGT1R In the placenta, AGT1R is localised to syncytiotrophoblasts, cytotrophoblasts,

Hofbauer cells and endothelial cells of the villous capillaries [46,47,51,52]. At the

maternal-fetal interface, strong AGT1R expression is found in cytotrophoblasts in

cell columns and in the extravillous trophoblasts (EVTs) detaching from the columns

and entering the decidua [51]. In the decidua, AGT1R expression is observed in

stromal cells [51], epithelial cells [51] and smooth muscle cells of spiral arteries [53]

but is absent from interstitial EVTs and endovascular EVTs surrounding and lining

the spiral arteries [51].

AGT2R In the placenta, AGT2R expression is present in cytotrophoblasts and Hofbauer cells

but absent from syncytiotrophoblasts and vascular endothelial cells [51]. At the

maternal-fetal interface, weak AGT2R expression is found in a heterogeneous

population of cytrophobasts in the cell columns [51]. In the decidua, AGT2R

expression is found in decidualised stromal cells and epithelial glands but absent

from interstitial or endovascular EVTs [51].

Mas receptor In term placenta and decidua, Mas receptor mRNA level is low to undetectable [50].

26

CHAPTER 2

Materials and Methods

27

2.1 The study population

2.1.1 Participants

The participants in the current study were healthy nulliparous women with singleton

pregnancies recruited to the Screening for Pregnancy Endpoints (SCOPE) study between

November 2004 and September 2008 in Adelaide, Australia and Auckland, New Zealand

[216].

2.1.2 Ethics

In Australia, ethical approval was obtained from the Central Northern Adelaide Health

Service Ethics of Human Research Committee (study number: REC 1714/5/2008). In New

Zealand, ethical approval was given by the Northern Region Ethics Committee (study

number: AKX/02/00/364). All participants provided written informed consent. Australian

clinical trial registry number: ACTRN 12607000551493.

2.1.3 Recruitment

Women were recruited to the SCOPE study by 15 weeks’ gestation through hospital antenatal

clinics, obstetricians, general practitioners, community midwives, and self referral in response

to advertisements or recommendations of friends. Women were excluded if there was a

presence of major fetal anomaly/abnormal karyotype, or women were judged to be at high

risk of pregnancy complications due to underlying medical conditions1, gynaecological

1 Mild-severe hypertension at booking (BP> 160/100 mmHg); type I or II diabetes before pregnancy; known underlying renal

problems, such as reflux nephropathy, glomerulonephritis and renal transplant; sickle cell disease; systemic lupus

erythematosus; anti-phospholipid syndrome; HIV Positive.

28

history2, three or more previous miscarriages, three or more terminations of pregnancy, or

those who had received interventions3 that might modify pregnancy outcomes [216].

2.1.4 Data collection

Participants were interviewed and examined by a research midwife at 15±1 weeks’ gestation.

Maternal demographic and dietary information was collected, including ethnicity, age (year),

height (cm), weight (kg), birth weight (g), gestational age at birth (weeks), socio-economic

index (SEI4) [217], smoking status at 15 weeks’ gestation and pre-pregnancy (i.e. 3 months

prior to pregnancy) green leafy vegetable and fruit intake. Two consecutive manual blood

pressure measurements (mercury or aneroid sphygmomanometer, with a large cuff if the arm

circumference ≥33 cm and Korotkoff V for diastolic blood pressure) were recorded. Paternal

information, including age (year), birth weight (g), height (cm), weight (kg) and waist

circumference (cm) were also recorded.

Doppler studies of the umbilical and uterine arteries [218] were performed at 20±1 weeks’

gestation. Mean uterine artery resistance index (RI) was calculated from the left and right

uterine RI. Mean uterine, or umbilical artery RI >90th

centile or the presence of bilateral

notching of the uterine artery waveform were considered abnormal.

Newborn measurements were recorded by research midwives within 72 hours of birth. The

recorded parameters included infant’s gestational age at birth (days), body length (cm), head

circumference (cm), mid arm circumference (cm), birth weight (g) and customised

2 Major uterine anomaly, such as bicornuate, unicornuate uterus and large uterine septum; McDonald or Shirodkar suture or

transabdominal cervical suture in place in current pregnancy; ruptured membranes; knife cone biopsy.

3 Antihypertensive treatment prior to the pregnancy; long term use of steroids. However, women on inhaled steroids for

asthma are not excluded; low-dose aspirin; daily calcium intake more than 1g; daily Eicosopentanoic Acid (fish oil) intake

more than 2.7g; daily intake of Vitamin C more than 1000mg; daily intake of Vitamin E more than 400iu; heparin/low

molecular weight heparin.

4 The New Zealand socio-economic index of occupational status, a number between 10 and 90 and is an occupationally

derived indicator of socio-economic status. It is a validated measure of an individual’s socioeconomic status and a higher

score indicates higher socio-economic status.

29

birthweight centile. The customised birthweight centile was calculated by taking account of

maternal weight, height, parity, ethnicity and infant sex.

Maternal, paternal and neonatal information were entered to the database by research

midwives.

2.1.5 Biological sample collection

Whole blood was collected in EDTA tubes from women at 15±1 weeks’ gestation, from

partners at some time during the woman’s pregnancy and umbilical cord after delivery. Blood

samples were centrifuged and plasma and buffy coat separated within 3 hours of collection.

Buccal swabs or saliva samples were collected from partners, who were unwilling to undergo

venepuncture, and babies whose cord blood was not obtained at delivery. The buccal swabs

were applied to Whatman FTA cards (Whatman, USA) immediately following sample

collection and saliva was collected using Oragene kits (DNA genotek, USA).

2.1.6 Pregnancy outcomes

The current study focused on three major pregnancy complications: preeclampsia, small for

gestational age (SGA) and spontaneous preterm birth (sPTB). Other complications such as

gestational hypertension (GHT), gestational diabetes (GDM) and placental abruption will also

be mentioned in the thesis, where appropriate. The pregnancy outcomes were reviewed by

experienced obstetricians to ensure accurate diagnosis.

2.1.6.1 Uncomplicated pregnancy

Uncomplicated pregnancies were those without any pregnancy complication and with delivery

of an appropriately grown baby at term.

30

2.1.6.2 Preeclampsia

Preeclampsia was defined as systolic blood pressure ≥140 mm Hg or diastolic blood pressure

≥90 mm Hg, or both, on at least two occasions four hours apart after 20 weeks’ gestation but

before the onset of labour, or postpartum, with either proteinuria (24 hour urinary protein

≥300 mg or spot urine protein: creatinine ratio ≥ 30 mg/mmol creatinine or urine dipstick

protein ≥++) or any multisystem complication of preeclampsia [76]. Multisystem

complications included haematological abnormalities including thrombocytopenia (platelets

<100×109/L), disseminated intravascular coagulation or haemolysis; effects on liver, defined

as raised aspartate transaminase or alanine transaminase concentration, or both, >45 IU/L

and/or severe right upper quadrant or epigastric pain or liver rupture; neurological effects

included eclampsia, imminent eclampsia (severe headache with hyper-reflexia and persistent

visual disturbance), or cerebral haemorrhage; any of acute renal insufficiency defined as a

new increase in serum creatinine concentration ≥100 μmol/L antepartum or >130 μmol/L

postpartum; and pulmonary oedema confirmed by chest x-ray.

2.1.6.3 SGA

Infants being born with SGA were those whose birth weight is less than the 10th

percentile

using customized centiles, adjusted for maternal weight, height, parity, ethnicity and infant

sex. The customised centiles of infants were calculated by using a bulk centile calculator,

which is available at http://www.gestation.net/.

2.1.6.4 sPTB

sPTB is defined as spontaneous preterm labour or preterm premature rupture of membranes

resulting in preterm birth at <37 weeks.

http://www.gestation.net/

31

2.1.6.5 GHT

A pregnancy was classified as GHT if the woman had a systolic blood pressure ≥140 mmHg

and/or diastolic blood pressure ≥90mmHg (Korotkoff V) on at least 2 occasions 4 hours apart

after 20 weeks’ gestation, but before the onset of labour in the absence of significant

proteinuria or any multisystem complication.

2.1.6.6 GDM

The pregnancy was classified as GDM, if the woman’s fasting glucose concentration was ≥

5.5 mmol/L and/or 2 hour glucose concentration was ≥ 8.0 mmol/L in a glucose tolerance test.

2.1.6.7 Placental abruption

Women had a placental abruption if a retroplacental clot was present at delivery or diagnosed

by the following clinical findings: ante- and/or intrapartum haemorrhage, vaginal bleeding

with uterine tenderness and/or fetal compromise.

2.2 DNA Extraction

DNA was extracted from buffy coats (QiAamp 96 DNA blood kit), Whatman FTA cards or

from saliva (using Oragene®DNA kits) following the manufacturers’ instructions.

2.2.1. DNA extraction from buffy coats

The QIAGEN Protease (20 μl) was aliquoted into wells before the buffy coats (200 μl) were

loaded. Buffer AL (200 μl) was added to wells. The mixture was mixed thoroughly by

shaking vigorously for 15 s and then incubated at 70°C for 10 minutes in an incubator. An

equal volume of 100% ethanol was added. The mixture was shaken vigorously for 15 s.

Buffer AW1 (500 μl) was added and then centrifuged at 6000 rpm for 2 mins. Buffer AW2

(500 μl) was added and centrifuged at 6000 rpm for 15 min. To elute DNA, buffer AE (200 μl)

was added. The samples were incubated for 1 min at room temperature then centrifuged at

32

6000 rpm for 4 min. In addition, DNA extraction for a proportion of samples was automated

and performed by using the Corbett xtractor (Corbett Robotics, Brisbane).

2.2.2 DNA extraction from Whatman FTA cards

A 2mm disc was punched from the dried sample area on the Whatman FTA cards using a hole

punch. The sample spot was fixed in a thin-walled 0.2ml PCR tube by overlaying with 7.5ul

100% methanol three times and allowed to air-dry in between. 10× PCR buffer (5 μL) and 45

μL sterile water were added to the PCR tube. The tube was then subjected to one cycle of

60°C for 30 min, 99°C for 10 min, then cooled to 4°C.

2.2.3 DNA extraction from saliva samples

The saliva sample was mixed with Oragene DNA solution in the Oragene DNA vial. The

mixture was inverted and gently shaken for a few seconds and then was incubated at 50°C in

a water incubator for an hour. The Oragene DNA Purifier (1/25th volume) was added. The

mixture was vortexed for a few seconds and then incubated on ice for 10 min. After the

incubation, the mixture was centrifuged at room temperature for 5 min at 13,000 rpm

(15,000g). The supernatant was transferred to a fresh 1.5 ml eppendorf tube. An equal

volume of room-temperature 100% ethanol was added. The mixture was gently mixed by

inversion 10 times, incubated at room temperature for 10 min and then centrifuged at room

temperature for 2 min at 13,000 rpm (15,000g). The supernatant was removed without

disturbing the DNA pellet. DNA buffer was added to dissolve the DNA pellet.

2.3 Genotyping assay

Genotyping was performed by the Australian Genome Research Facility (AGRF) utilizing the

sequenom iPLEX

TM MassARRAY system (Figure 2.1), which uses mass spectrometry

(MALDI-TOF) to discriminate products by their absolute mass. DNA regions containing

single nucleotide polymorphisms (SNPs) were first amplified using primers adjacent to the

33

SNPs. The PCR products then underwent arctic shrimp alkaline phosphatase (SAP) treatment,

in which any residual nucleotides were dephosphorylated to prevent their incorporation. In the

iPLEX reaction, in which all the reactions were terminated after a single base extension, mass

modified ddNTP terminators were utilized to create mass separation between allele-specific

products. The extension products were then cleaned up to remove salts and were dispensed

onto a 384SpectroCHIP. This Chip was analysed by MALDI-TOF mass spectrometer and the

alleles called by weight (in kilodaltons) of the extension products. The primers for the initial

PCR amplification and the iPLEX reaction of each polymorphism are listed in table 2.1.

Two quality control procedures were in place to ensure the accuracy of genotyping data: 1)

Each sample was genotyped for Amelogenin to assess the consistency between the sex of

samples and the corresponding Amelogenin genotype [219]. 2) Parental and neonatal

genotyping data were checked for a Mendelian pattern of inheritance. The samples with

inconsistent results in either step were excluded from the analyses. In addition, some samples

were excluded due to inadequate blood samples, low quality of DNA or failure to genotype.

The sample sizes for the genotyping data are shown in the results tables.

2.4 Plasma prorenin concentration

The prorenin measurement was performed by Shane Sykes, university of Newcastle, Australia.

The measurement of plasma prorenin concentration utilized a commercially available human

prorenin ELISA kit (Molecular Innovations, MI, USA). Absorbance was read at 450 nm.

Intra-assay and inter-assay CVs were 5.63% and 11.05%, respectively.

2.5 Plasma ACE concentration

Plasma ACE concentration was measured by a commercial Enzyme-linked immunosorbent

assay (ELISA) kit (ACE duoset, R & D Systems, Minneapolis, USA). The sensitivity of the

assay is 62.5pg/mL. The amount of ACE in each sample was calculated from a four parameter

34

logistic standard curve of optical density values constructed using human recombinant ACE

supplied with the kit. The kit was optimized for reagent diluent and plate blocking time. The

optimized reagent diluent is 10% Fetal Calf Serum (FCS) and 2 hours was the optimal

blocking time. Optical density of each well was determined using a microplate reader

(BioRad, Benchmark) at 450nm and corrected at 570 nm. Cases and controls were randomly

assigned on each plate. The intra-assay and inter-assay coefficients of variation were 6% and

10%, respectively.

2.6 Plasma ANG II concentration

Plasma ANG II concentration was measured by ProSearch International Australia Pty. Ltd.

(Malvern, Australia) by radioimmunoassay. Plasma samples were first incubated with rabbit

anti-human ANG II (N-terminally conjugated to bovine thyroglobulin) for 20 h at 4˚C. The

125I-Angiotensin II tracers (10000 cpm, Peninsula Laboratories, Belmont, CA, USA) were

then added and allowed to equilibrate for 16 h at 4˚C. The bound and free phases of the

tracers were separated by centrifugation with Dextran 10 coated charcoal. The sensitivity and

intra- and inter-assay coefficients of variation of the ANG II assay were 4 pmol/L, 6.4% and

12%, respectively.

2.7 Plasma ANG 1-7 concentration

Plasma ANG I-7 concentration was measured by ProSearch International Australia Pty. Ltd.

(Malvern, Australia) by radioimmunoassay. Plasma samples were first incubated with Guinea

pig anti-human angiotensin 1-7 (n-terminally conjugated to porcine thyroglobulin) for 20 h at

4˚C. The 125

I-Angiotensin 1-7 tracer (10000cpm, Auspep, Tullamarine, Australia) were then

added and allowed to equilibrate for 16 h at 4˚C. The bound and free phases of the tracers

were separated by centrifugation with Dextran 10 coated charcoal. The sensitivity and intra-

and inter-assay coefficients of variation of the ANG 1-7 assay were 13 pmol/L, 4.5% and

10%, respectively.

35

Figure 2.1 Sequenom iPLEX

TM MassARRAY system.

36

Table 2.1 Primers for genotyping the RAS polymorphisms.

RAS polymorphisms SNP ID

PCR amplification

Primers for the iPLEX reaction Forward primers Reverse primers

Renin T/G rs5707 5’-ACGTTGGATGAGAAGGGGTCCGGGGCAGA-3’ 5’-ACGTTGGATGACAGTCAGTGGCTTTCTCAG-3’ 5’-tggggCCGGGGCAGATGACCT-3’

AGT M235T rs699 5’-ACGTTGGATGCTGTGACAGGATGGAAGACT-3’ 5’-ACGTTGGATGTGGACGTAGGTGTTGAAAGC-3’ 5’-ggaatACTGGCTGCTCCCTGA-3’

AGT T174M rs4762 5’-ACGTTGGATGACAAACGGCTGCTTCAGGTG-3’ 5’-ACGTTGGATGTGATAGCCAGGCCCAGCT-3’ 5’-ttAACACGCCCACCACC-3’

ACE A11860G rs4343 5’-ACGTTGGATGCCTACCAGATCTGACGAATG-3’ 5’-ACGTTGGATGCATGCCCATAACAGGTCTTC-3’ 5’-gggCGAATGTGATGGCCAC-3’

AGT1R A1166C rs5186 5’-ACGTTGGATGAGAACATTCCTCTGCAGCAC-3’ 5’-ACGTTGGATGCCACATAATGCATTTTCTCC-3’ 5’-gggccGCACTTCACTACCAAATGAGC-3’

AGT2R C4599A rs11091046 5’-ACGTTGGATGCCTCCACTCAAGTGAAATGC-3’ 5’-ACGTTGGATGGGATTATTCAGGCTTTAGGC-3’ 5’-ATGCAAGAGGAATATAATTTATAGC-3’

AGT2R A1675G rs1403543 5’-ACGTTGGATGCCTAAACACACTCCTGTAAG-3’ 5’-ACGTTGGATGTTCCTGTGTTTTAACACTG-3’ 5’-tcctAGAAACAGCAGCTAAATAATT-3’

AGT2R T1334C rs12710567 5’-ACGTTGGATGGAATGAGCTGTTATGATTGG-3’ 5’-ACGTTGGATGCCAGCTTTCCAGAGAGGTTT-3’ 5’-CTGTTATGATTGGAGACAG-3’

SNP: single nucleotide polymorphism

37

CHAPTER 3

Characteristics of the study population

38

3.1 Introduction:

The participants in the current study were healthy nulliparous women with singleton

pregnancies recruited to the Screening for Pregnancy Endpoints (SCOPE) study between

November 2004 and September 2008 in Adelaide, Australia and Auckland, New Zealand

[216]. Overall 3234 women, their partners and babies were recruited into the study. The study

population for the thesis was confined to the 2121 Caucasian parent-infant trios (66%), which

consist of 935 Australian and 1186 New Zealand parent-infant trios (Figure 3.1). The detailed

information regarding the recruitment of SCOPE participants, data collection and definitions

of pregnancy complications can be found in chapter 2 of this thesis.

The current chapter was aimed to provide an integrated view of the SCOPE cohort and to

identify clinical risk factors for major pregnancy complications, including preeclampsia,

gestational hypertension (GHT), small for gestational age (SGA) and spontaneous preterm

birth (sPTB). We also explored the differences in demographic characteristics between the

Australian and New Zealand SCOPE cohort. Furthermore, the distribution of polymorphisms

in the renin angiotensin system (RAS) genes in the SCOPE cohort was also determined,

irrespective of pregnancy outcomes.

39

3.2 Results:

Characteristics of the combined SCOPE cohort

Preeclampsia

Preeclamptic women on average were 1.4 years younger (p=0.007), had higher BMI (↑3.3

points, p<0.001), had higher blood pressure at 15 weeks’ gestation (↑6.8mmHg in sBP,

p<0.001), had 5.4 points lower socioeconomic index (SEI, p=0.001) and they themselves

weighed 158g less at birth (p=0.002) than women without any complication. In addition,

compared to uncomplicated pregnancies, the proportion of women with pre-pregnancy green

leafy vegetable and fruit intake ≥1 serve/day was 10.4% and 9.7% lower in preeclamptic

pregnancies, respectively (both p=0.03). Partners who fathered a preeclamptic pregnancy,

were 1.6 years younger (p=0.005) and heavier (1.7 points higher BMI, p=0.001) than those

who fathered an uncomplicated pregnancy. Table 3.2

GHT

Women who later developed GHT on average were 4.2 points higher in BMI (p<0.001), had

higher blood pressure at 15 weeks’ gestation (↑9.5mmHg sBP, p<0.001), had 5.7 points lower

SEI (p<0.001) and they themselves weighed 95.7g less at birth (p=0.04) than women without

any complication. In addition, compared to uncomplicated pregnancies the proportion of

women with pre-pregnancy green leafy vegetable and fruit intake ≥1 serve/day was 13.7%

and 13.1% lower among women with pregnancies complicated by GHT, respectively (both

p=0.001). Partners who fathered a pregnancy complicated by GHT on average were 1.1 points

higher in BMI (p=0.002) than those who fathered an uncomplicated pregnancy. Table 3.2

SGA

Women who later delivered a SGA baby on average were 1.2 points higher in BMI (p=0.003),

had higher sBP at 15 weeks’ gestation (3.3 mmHg higher, p<0.001), were 3.8 points lower in

40

SEI (p=0.002) and they themselves weighed 168g less at birth (p<0.001) than women without

any complication. In addition, compared to uncomplicated pregnancies, among women who

delivered a SGA baby, the proportion of smokers at 15 weeks’ gestation was 13.7% higher

(p<0.001) and the proportion of women with pre-pregnancy green leafy vegetable and fruit

intake ≥1 serve/day was 9.3% and 10.6% lower, respectively (both p<0.05). Partners, who

fathered a SGA baby, on average were 2cm shorter (p<0.001) and weighed 174.1g less

(p<0.001) than those who fathered an uncomplicated pregnancy. Table 3.2

sPTB

Women who delivered preterm on average were 5.1 points higher in BMI (p=0.047), had

higher sBP at 15 weeks’ gestation (2.4 mmHg higher, p=0.028), had a shorter gestational age

themselves (p=0.018) and they themselves weighed 113g less at birth (p=0.03) than women

without any complication. In addition, compared to uncomplicated pregnancies, among

women who delivered preterm, the proportion of smokers at 15 weeks’ gestation was 7.8%

higher (p=0.007) and the proportion of women with pre-pregnancy fruit intake ≥1 serve/day

was 15.1% lower (p=0.001). Partners who fathered a sPTB pregnancy on average weighed

144.7g less at birth (p=0.02) than those who fathered an uncomplicated pregnancy. Table 3.2

The differences in demographic characteristics between the Australian and New

Zealand SCOPE cohort

The characteristics of the Australian and New Zealand cohort are summarised in table 3.3 and

table 3.4, respectively, and the differences between the two cohorts are presented in table 3.5.

All major pregnancy complications except for sPTB were significantly more frequent in the

Adelaide cohort than in the New Zealand cohort, with, in particular, preeclampsia and GHT

about twice as frequent (Table 3.5).

41

All the maternal and paternal characteristics were significantly different between the

Australian and New Zealand cohorts (Table 3.5). Australian women were on average 7 years

younger (p<0.001) and 22 points lower in SEI (p<0.001) than the New Zealand women (Table

3.5). In addition, the proportion of Australian women, who had pre-pregnancy vegetable

intake ≥1 serve/day was on average 37% lower than the New Zealand women (p<0.001)

(Table 3.5). The proportion of smokers at 15 weeks’ gestation in the Australian cohort was 8-

fold higher than that in the New Zealand cohort (p<0.001) (Table 3.5).

Distribution of the RAS polymorphisms in the combined cohort

The distributions of RAS polymorphisms are shown in table 3.6. All the polymorphisms were

checked for deviation from the Hardy-Weinberg Equilibrium and were all in equilibrium.

42

3.3 Discussion:

To the best of our knowledge, the SCOPE study is the largest prospective study conducted in

Australia and New Zealand on low risk nulliparous singleton pregnancy. In the SCOPE cohort,

the prevalence of hypertensive pregnancies, comprised of preeclampsia and GHT, is 13.6%.

Although it is higher than the reported 7% in South Australia in 2007 [220], this is likely due

to the nulliparous nature of our cohort. Maternal nulliparity is a well-established risk factor

for preeclampsia [166]. The approximate 10% occurrence rate of SGA is expected since SGA

is defined as customized birth weight centile below the 10th

centile. The 5.5% rate of sPTB in

the SCOPE cohort is comparable to estimated 6.4% for all PTB in 2005 in Australia and New

Zealand [221], considering that sPTB makes up 75% of all PTBs [222].

The well accepted risk factors for pregnancy complications were also observed in our SCOPE

cohort. Elevated BMI [210], elevated blood pressure (still within normal range) in early

pregnancy [223], low SEI [212], low green vegetable intake [211] and low maternal birth

weight [224], all of which have been reported to associate with an increased risk for

preeclampsia, were also risk factors for preeclampsia in the current study. In addition,

smoking is the single most important risk factor for SGA in developed countries [205,206,207]

and in the SCOPE cohort smoking at 15 weeks’ gestation was also identified as a risk factor

for SGA.

The SCOPE participants were recruited to two centers, Adelaide, Australia and Auckland,

New Zealand. We observed striking differences between participants from the two centers and

the Australian cohort appears to be a disadvantaged population compared with the New

Zealand cohort. Specifically, Australian women on average were 22 points lower in SEI, (a

10-90), had higher BMI, ate fewer green leafy vegetable and fruit prior to pregnancy and were

more likely to smoke and use marijuana at 15 weeks’ gestation than New Zealand women.

These striking differences indeed may explain why the occurrence of adverse pregnancy

43

outcomes was more frequent in the Australian cohort than the New Zealand cohort. In

particular, preeclampsia and GHT in the Australian cohort are about twice as frequent as those

in the New Zealand cohort. Since gene-environment interaction describes the phenomenon in

which the association of a genetic variant with a disease phenotype varies with the degree of

exposure to an environmental factor or vice versa, the differences in the ‘environmental

factors’ between the Australian and New Zealand cohorts provide an excellent platform to

study gene-environment interaction. Chapter 6 of the current thesis will explore more on the

differences between the two cohorts in relation to gene-environment interactions in risk for

SGA.

All the selected RAS polymorphisms in the current study are in Hardy-Weinberg Equilibrium.

In addition, genotype frequencies of renin T/G [127], ACE A11860G [153], AGT M235T

[153], AGT T174M [153], AGT1R A1166C [153] and AGTR2 A1675G [225] were comparable

to the published Caucasian cohorts. Furthermore, the prevalence of CC genotype (or C allele)

of AGTR2 C4599A [160] and AGTR2 T1334C [165] appeared to be lower than the published

Asian cohorts.

In summary, the prevalence of pregnancy complications in the SCOPE cohort was

comparable to nation (or state)-wide data and common risk factors for pregnancy

complications were also identifiable in the SCOPE cohort. In addition, the Australian and

New Zealand cohorts are strikingly different, which offers an excellent avenue to explore

gene-environment interactions. Furthermore, genotype frequencies of selected RAS

polymorphisms are comparable to previous published Caucasian cohorts and all fall into

Hardy-Weinberg Equilibrium, a pre-requisite for genetic association studies [226].

44

Figure 3.1 Flow chart of participant recruitment.

Conceived using donor gametes (n = 19)

Lost to follow up (n = 26)

Parental ethnicity non Caucasian (n = 437)

Women recruited into SCOPE study at 15±1 weeks n= 3234

Excluded due to protocol violation (n = 12)

Partner did not consent (n = 591)

Study population at 15±1 weeks n=3196

Miscarriage or termination (n = 28)

Eligible study population (parent-infant trio) n=2121

45

Table 3.1 The prevalence of pregnancy complications in the combined SCOPE. Pregnancy outcomes n (%)

Uncomplicated 1185 (59.6)

PE 123 (5.8)

GHT 165 (7.8)

SGA 216 (10.2)

sPTB 116 (5.5)

GDM1 58 (2.7)

Placental abruption 15 (0.7)

Others 268 (12.6)

PE: preeclampsia; GHT: gestational hypertension; SGA: small for gestational age; sPTB: spontaneous preterm

birth; GDM: gestational diabetes. 1The prevalence of GDM was calculated out of 1978 combined SCOPE

women. One hundred and thirty six women were excluded from the calculation because their GDM status was

undetermined.

46

Table 3.2 Demographic characteristics of the combined SCOPE cohort.

Uncomplicated PE

GHT

SGA

sPTB

GDM

Abruption

Maternal characteristics n=1185 n=123 P n=165 P n=216 P n=116 P n=58 P n=15 P

Age (yrs) at 15 wks 28.2 (5.6) 26.8 (5.4) 0.007 27.4 (6.1) 0.1 28.5 (6.2) 0.5 28.0 (6.2) 0.7 29.3 (5.0) 0.1 28.4 (7.6) 0.9

BMI (kg/m2) at 15 wks 24.9 (4.5) 28.2 (7.2) <0.001 29.1 (6.3) <0.001 26.1 (5.5) 0.003 30.0 (5.4) 0.047 30.8 (7.1) <0.001 24.0 (3.8) 0.4

sBP (mmHg) at 15 wks 106.2 (9.9) 113.0 (10.1) <0.001 115.7 (10.0) <0.001 109.5 (11.1) <0.001 108.6 (11.0) 0.028 112.7 (11.1) <0.001 107.0 (11.7) 0.8

dBP (mmHg) at 15 wks 63.3 (7.6) 68.9 (8.1) <0.001 69.9 (8.2) <0.001 66.0 (8.9) <0.001 65.1 (8.4) 0.025 69.2 (8.9) <0.001 64.7 (9.1) 0.5

Socio-economic index 41.9 (16.7) 36.5 (16.0) 0.001 36.2 (16.7) <0.001 38.1 (16.7) 0.002 39.6 (17.0) 0.2 37.5 (17.2) 0.048 36.5 (16.4) 0.2

Pre-pregnancy green leafy

vegetable intake ≥1 serve/day (%) 615 (51.9%) 51 (41.5%) 0.03 63 (38.2%) 0.001 92 (42.6) 0.012 52 (44.8%) 0.2 17 (29.3%) 0.001 6 (40.0%) 0.4

Smoking (%) at 15 wks 111 (9.4%) 12 (9.8%) 0.9 21 (12.7%) 0.2 50 (23.1) <0.001 20 (17.2%) 0.007 3 (5.2%) 0.3 6 (40.0%) 0.002

Maternal gestational age (wks) 39.9 (1.9) 39.5 (2.2) 0.1 39.7 (2.4) 0.4 39.7 (2.1) 0.4 39.3 (2.3) 0.018 39.7 (2.2) 0.6 39.6 (1.4) 0.6

Maternal birth weight (g) 3334.6 (529.7) 3176.6 (543.6) 0.002 3238.9 (594.9) 0.04 3166.6 (527.3) <0.001 3221.6 (603.7) 0.03 3102.9 (621.8) 0.001 3301.5 (362.6) 0.8

Paternal characteristics

Age (yrs) 30.7 (6.3) 29.1 (5.6) 0.005 30.6 (6.5) 0.8 31.1 (6.7) 0.5 30.3 (6.8) 0.5 32.5 (6.2) 0.04 28.7 (6.4) 0.2

Height (cm) 179.6 (6.7) 179.2 (6.9) 0.5 178.9 (6.9) 0.2 177.6 (6.9) <0.001 179.3 (6.7) 0.6 178.8 (7.4) 0.4 178 (5.9) 0.4

BMI (kg/m2) 26.6 (4.0) 28.3 (5.5) 0.001 27.7 (4.6) 0.002 27.2 (4.6) 0.07 26.5 (4.1) 0.8 28.2 (5.1) 0.003 25.9 (4.7) 0.5

Paternal birth weight (g) 3487.8 (571.4) 3506.5 (552.6) 0.7 3416.4 (632.4) 0.2 3313.7 (520.8) <0.001 3343.1 (642.2) 0.02 3553.6 (540.6) 0.4 3080.9 (606.4) 0.01

Newborn characteristics

Gestational age at birth (days) 280.7 (8.1) 266.0 (17.7) <0.001 276.7 (10.6) <0.001 271.6 (24.5) <0.001 238.4 (24.4) <0.001 269.1 (14.0) <0.001 239.2 (40.3) 0.001

Body length (cm) 51.0 (2.2) 48.4 (3.8) <0.001 49.9 (2.4) <0.001 47.1 (4.5) <0.001 45.2 (4.9) <0.001 48.9 (2.9) <0.001 43.9 (6.8) <0.001

Head circumference (mm) 35.2 (1.4) 33.8 (2.3) <0.001 34.5 (1.5) <0.001 32.9 (2.6) <0.001 31.4 (3.4) <0.001 34.1 (1.8) <0.001 29.7 (4.4) <0.001

Mid arm circumference (mm) 11.0 (0.9) 10.1 (1.5) <0.001 10.6 (1.1) <0.001 9.4 (1.1) <0.001 9.0 (1.4) <0.001 10.4 (1.1) <0.001 9.1 (1.7) <0.001

Birth weight (g) 3590.9 (393.8) 3078.4 (747.8) <0.001 3340.5 (530.5) <0.001 2587.0 (559.8) <0.001 2384.3 (743.3) <0.001 3276.5 (626.6) <0.001 2180.9 (944.1) <0.001

Customised birthweight centile 53.7 (25.0) 44.8 (32.1) 0.004 40.4 (29.5) <0.001 4.6 (2.9) <0.001 49.7 (31.0) 0.2 53.7 (25.0) 0.3 53.7 (25.0) 0.005

Female babies (%) 584 (49.3%) 64 (52%) 0.6 93 (56.4%) 0.09 109 (50.5%) 0.8 57 (49.1%) 0.09 29 (50.0%) 0.9 8 (53.3%) 0.8

Data are presented as mean (SD) or n (%).PE: preeclampsia; GHT: gestational hypertension; SGA: small for gestational age; sPTB: spontaneous preterm birth; GDM: gestational diabetes;

sBP: systolic blood pressure, the second measurement; dBP: diastolic blood pressure, the second measurement; 15 wks: 15 weeks’ gestation. Bold italics indicates significant difference.

47

Table 3.3 Demographic characteristics of the Australian SCOPE cohort.

Uncomplicated PE

GHT

SGA

sPTB

GDM

Abruption


Age (yrs) at 15 wks 23.6 (5.0) 24.1 (4.3) 0.4 24.4 (5.0) 0.1 24.3 (5.3) 0.1 24.3 (5.9) 0.4 28.6 (4.9) <0.001 27.3 (8.5) 0.2

BMI (kg/m2) at 15 wks 26.0 (5.6) 29.4 (8.0) 0.001 30.5 (6.7) <0.001 27.5 (6.2) 0.01 27.3 (6.1) 0.09 32.0 (7.4) <0.001 24.6 (4.0) 0.4

sBP (mmHg) at 15 wks 107.9 (8.9) 113.7 (9.8) <0.001 116.4 (10.5) <0.001 111.6 (11.2) 0.002 109.9 (11.3) 0.2 113.3 (11.0) 0.003 107.4 (13.3) 0.9

dBP (mmHg) at 15 wks 63.5 (7.5) 67.3 (8.4) <0.001 69.5 (8.6) <0.001 66.0 (8.9) 0.007 65.1 (8.2) 0.2 69.3 (8.9) <0.001 62.9 (9.1) 0.8

Socio-economic index 27.9 (10.9) 28.8 (12.4) 0.5 27.5 (10.3) 0.7 25.5 (7.5) 0.007 27.9 (10.3) 1 31.4 (12.6) 0.1 30.6 (12.9) 0.4


vegetable intake ≥1 serve/day (%) 120 (28.1%) 17 (22.7%) 0.3 23 (22.5%) 0.3 25 (22.9%) 0.3 7 (12.3%) 0.01 7 (17.1%) 0.1 4 (36.4%) 0.5

Smoking (%) at 15 wks 90 (21.1%) 11 (14.7%) 0.2 19 (18.6%) 0.6 48 (44.0%) <0.001 16 (28.1%) 0.2 3 (7.3%) 0.04 6 (54.5%) 0.02

Maternal gestational age (wks) 39.5 (1.9) 39.4 (1.9) 0.8 39.7 (2.0) 0.3 39.4 (2.3) 0.6 38.9 (2.4) 0.06 39.5 (2.3) 1 39.7 (1.5) 0.8

Maternal birth weight (g) 3287.3 (549.4) 3197.7 (562.4) 0.2 3267.7 (611.2) 0.8 3136.4 (544.4) 0.01 3190.6 (529.4) 0.2 3090.1 (648.6) 0.03 3290.9 (410.4) 1


Age (yrs) 26.4 (6.1) 26.8 (5.2) 0.5 28.4 (6.6) 0.003 27.6 (6.3) 0.054 26.5 (6.4) 0.9 32.2 (6.0) <0.001 27.8 (7.3) 0.4

Height (cm) 178.5 (6.7) 178.5 (7.3) 0.9 177.2 (6.8) 0.08 176.3 (7.2) 0.002 179.8 (7.4) 0.2 177.9 (7.1) 0.5 179.2 (5.7) 0.8

BMI (kg/m2) 26.9 (5.0) 28.7 (6.1) 0.02 27.6 (5.1) 0.2 27.3 (5.0) 0.4 26.2 (4.6) 0.3 28.7 (5.4) 0.03 26.0 (5.4) 0.6

Paternal birth weight (g) 3461.9 (593.4) 3490.0 (522.0) 0.7 3385.4 (699.7) 0.3 3346.9 (558.1) 0.09 3356.8 (575.6) 0.3 3479.5 (541.6) 0.9 3242.1 (528.9) 0.3


Gestational age at birth (days) 280.6 (8.0) 267.0 <0.001 277.2 (9.9) 0.002 271.9 (23.2) <0.001 235.1 (27.5) <0.001 268.1 (13.9) <0.001 224.6 (37.4) 0.001

Body length (cm) 50.0 (1.9) 48.0 (3.7) <0.001 49.4 (2.1) 0.005 46.2 (3.9) <0.001 43.3 (5.4) <0.001 48.3 (2.8) <0.001 42.0 (6.9) <0.001

Head circumference (mm) 34.9 (1.3) 33.6 (2.3) <0.001 34.4 (1.5) 0.001 32.8 (2.3) <0.001 30.2 (3.8) <0.001 34.0 (1.9) <0.001 28.2 (4.3) <0.001

Mid arm circumference (mm) 11.0 (0.9) 9.9 (1.7) <0.001 10.5 (1.0) <0.001 9.2 (1.2) <0.001 8.7 (1.5) <0.001 10.3 (1.2) <0.001 8.4 (2.0) <0.001

Birth weight (g) 3575.3 (390.2) 3074.9 (754.2) <0.001 3337.3 (519.9) <0.001 2553.6 (536.1) <0.001 2238.2 (789.9) <0.001 3214.8 (661.5) <0.001 1936.6 (993.4) <0.001

Customised birthweight centile 53.9 (24.9) 43.5 (31.7) 0.008 39.1 (29.8) <0.001 4.0 (2.8) <0.001 46.6 (31.6) 0.1 44.8 (33.0) 0.09 46.0 (30.8) 0.3

Female babies (%) 217 (50.8) 40 (53.3%) 0.7 58 (56.9%) 0.3 60 (55.0) 0.4 29 (50.9%) 1.0 22 (53.7%) 0.7 5 (45.5%) 0.7

Data are presented as mean (SD) or n (%).PE: preeclampsia; GHT: gestational hypertension; SGA: small for gestational age; sPTB: spontaneous preterm birth; GDM: gestational diabetes;


48

Table 3.4 Demographic characteristics of the New Zealand SCOPE cohort.

Uncomplicated PE

GHT

SGA

sPTB

GDM

Abruption


Age (yrs) at 15 wks 30.8 (4.1) 31.0 (3.9) 0.7 32.4 (3.9) 0.003 32.7 (3.8) <0.001 31.5 (4.1) 0.2 30.9 (5.1) 0.9 31.5 (3.7) 0.7

BMI (kg/m2) at 15 wks 24.3 (3.7) 26.4 (5.4) 0.01 26.9 (4.9) <0.001 24.7 (4.3) 0.3 24.6 (4.2) 0.6 27.7 (5.5) 0.02 22.2 (3.0) 0.3

sBP (mmHg) at 15 wks 105.3 (10.3) 112.0 (10.6) <0.001 114.5 (9.0) <0.001 107.5 (10.8) 0.05 107.3 (10.8) 0.1 111.1 (11.6) 0.02 106.0 (6.9) 0.9

dBP (mmHg) at 15 wks 63.2 (7.7) 71.5 (7.0) <0.001 70.6 (7.5) <0.001 66.1 (8.9) 0.002 65.2 (8.7) 0.06 68.8 (9.1) 0.003 69.5 (8.2) 0.1

Socio-economic index 49.8 (14.0) 48.4 (13.4) 0.5 50.3 (15.4) 0.8 51.0 (13.2) 0.4 50.9 (14.4) 0.5 52.1 (18.3) 0.5 52.5 (15.0) 0.7


vegetable intake ≥1 serve/day (%) 495 (65.3%) 34 (70.8%) 0.4 40 (63.5%) 0.8 67 (62.6%) 0.6 45 (76.3%) 0.09 10 (58.8%) 0.6 2 (50.0%) 0.6

Smoking (%) at 15 wks 21 (2.8%) 1 (2.1%) 1 2 (3.2%) 0.7 2 (1.9%) 1 4 (6.8%) 0.1 0 (0%) 1.0 0 (0%) 1.0

Maternal gestational age (wks) 40.0 (1.8) 39.7 (2.7) 0.3 39.7 (3.0) 0.4 40.1 (1.7) 0.9 39.7 (2.1) 0.2 40.3 (1.6) 0.6 39.0 (1.4) 0.4

Maternal birth weight (g) 3360.8 (517.0) 3144.7 (518.2) 0.006 3192.6 (569.7) 0.02 3196.8 (510.5) 0.003 3250.9 (669.9) 0.2 3134.1 (569.6) 0.08 3325.5 (274.7) 0.9


Age (yrs) 33.2 (4.9) 32.5 (4.3) 0.4 34.1 (4.4) 0.2 34.6 (5.0) 0.005 33.9 (5.0) 0.2 33.2 (6.8) 1.0 31.3 (1.9) 0.4

Height (cm) 180.3 (6.7) 180.3 (6.2) 1 181.5 (6.4) 0.2 179.0 (6.4) 0.06 178.7 (5.9) 0.09 181.1 (7.8) 0.6 174.8 (5.7) 0.1

BMI (kg/m2) 26.4 (3.3) 27.8 (4.4) 0.04 27.9 (3.7) <0.001 27.1 (4.1) 0.1 26.7 (3.5) 0.5 27.1 (4.5) 0.4 25.8 (2.8) 0.7

Paternal birth weight (g) 3501.6 (559.2) 3529.2 (597.0) 0.7 3468.4 (501.2) 0.7 3283.2 (484.9) <0.001 3331.1 (700.3) 0.08 3729.5 (512.1) 0.1 2758.5 (698.4) 0.008


Gestational age at birth (days) 280.7 (8.1) 264.6 (18.5) <0.001 276.0 (11.5) 0.003 271.4 (25.9) <0.001 241.5 (20.7) <0.001 271.4 (14.4) 0.02 279.3 (2.6) 0.4

Body length (cm) 51.5 (2.2) 49.0 (3.9) <0.001 50.6 (2.7) 0.003 48.0 (4.8) <0.001 47.1 (3.2) <0.001 50.2 (3.0) 0.02 49.2 (1.8) 0.04

Head circumference (mm) 35.3 (1.4) 34.1 (2.3) <0.001 34.7 (1.6) 0.001 32.9 (2.8) <0.001 32.7 (2.3) <0.001 34.5 (1.3) 0.01 33.8 (0.4) 0.03

Mid arm circumference (mm) 11.1 (0.9) 10.3 (1.2) <0.001 10.7 (1.2) 0.007 9.5 (1.0) <0.001 9.3 (1.3) <0.001 10.7 (0.9) 0.2 10.1 (0.5) 0.03

Birth weight (g) 3599.7 (395.8) 3083.9 (745.6) <0.001 3345.6 (551.5) <0.001 2620.9 (583.4) <0.001 2525.3 (672.2) <0.001 3425.5 (521.0) 0.08 2852.5 (224.2) <0.001

Customised birthweight centile 53.6 (25.1) 46.9 (33.1) 0.2 42.5 (29.2) 0.001 5.1 (2.9) <0.001 52.8 (30.3) 0.8 57.8 (30.8) 0.5 6.8 (6.3) <0.001

Female babies (%) 367 (48.4) 24 (50.0%) 0.8 35 (55.6%) 0.3 49 (45.8) 0.7 28 (47.5%) 0.9 7 (41.2%) 0.6 3 (75.0%) 0.4

Data are presented as mean (SD) or n (%). PE: preeclampsia; GHT: gestational hypertension; SGA: small for gestational age; sPTB: spontaneous preterm birth; GDM: gestational diabetes;


49

Table 3.5 The differences in demographic characteristics between the Australian and New

Zealand SCOPE cohorts.

AUS NZ

n=937 n=1186 P

Prevalence of pregnancy outcomes

Uncomplicated (%) 427 (45.7%) 758 (63.9%) <0.001

PE (%) 75 (8.0%) 48 (4.0%) <0.001

GHT (%) 102 (10.9%) 63 (5.3%) <0.001

SGA (%) 109 (11.7%) 107 (9.0%) 0.05

sPTB (%) 57 (6.1%) 59 (5.0%) 0.3

GDM (%)1 41 (4.5%) 17 (1.6%) <0.001

Placental abruption (%) 11 (1.2%) 4 (0.3%) 0.02

Others (%) 173 (18.5%) 95 (8.0%) <0.001

Maternal characteristics

Age (yrs) at 15 wks 23.9 (5.1) 31.1 (4.1) <0.001

BMI (kg/m2) at 15 wks 27.3 (6.5) 24.7 (4.1) <0.001

sBP (mmHg) at 15 wks 110.0 (10.1) 106.7 (10.6) <0.001

dBP (mmHg) at 15 wks 64.9 (8.0) 64.4 (8.1) 0.2

Socio-economic index 27.9 (10.60) 49.9 (14.0) <0.001

Pre-pregnancy green leafy vegetable

intake ≥1 serve/day (%) 238 (25.4%) 771 (65.0%) <0.001

Pre-pregnancy fruit intake ≥1 serve/day (%) 314 (33.5%) 937 (79.0%) <0.001

Marijuana use(%) at 15 wks 31 (3.3%) 4 (0.3%) <0.001

Smoking (%) at 15 wks 212 (22.6%) 33 (2.8%) <0.001

Maternal gestational age (wks) 39.4 (2.1) 40.0 (2.0) <0.001

Maternal birth weight (g) 3248.9 (571.1) 3319.3 (530.9) 0.004


Age (yrs) 27.0 (6.3) 33.3 (4.9) <0.001

Height (cm) 178.0 (7.0) 180.2 (6.5) <0.001

BMI (kg/m2) 27.2 (5.3) 26.6 (3.5) 0.01

Paternal birth weight (g) 3420.3 (624.5) 3485.3 (561.5) 0.02


Gestational age at birth (days) 275.6 (17.5) 276.9 (16.0) 0.09

Body length (cm) 49.1 (3.3) 50.8 (3.0) <0.001

Head circumference (mm) 34.3 (2.2) 34.9 (1.9) <0.001

Mid arm circumference (mm) 10.6 (1.2) 10.8 (1.1) 0.002

Birth weight (g) 3353.4 (640.1) 3421.4 (574.8) 0.01

Customised birthweight centile 46.7 (29.3) 48.3 (27.9) 0.2

Female babies (%) 487 (52.1%) 582 (49.1%) 0.2

Data are presented as mean (SD) or n (%).PE: preeclampsia; GHT: gestational hypertension; SGA: small for

gestational age; sPTB: spontaneous preterm birth; GDM: gestational diabetes; AUS: Australia; NZ: New

Zealand; sBP: systolic blood pressure, the second measurement; dBP: diastolic blood pressure, the second

measurement; 15 wks: 15 weeks’ gestation.1The prevalence of GDM in AUS and NZ was calculated out of 914

AUS women and 1073 NZ women, respectively. Twenty three AUS women and 113 NZ women were excluded

from the calculation because their GDM status was undetermined.

50

Table 3.6 The prevalence of RAS polymorphisms in the combined SCOPE.

ACE A11860G n AA AG GG

Mothers 1917 401 (20.9) 982 (51.2) 534 (27.9)

Partners 1637 347 (21.2) 843 (51.5) 447 (27.3)

Babies 1494 320 (21.4) 755 (50.5) 419 (28.0)

AGT T174M

CC CT TT

Mothers 1923 1490 (77.5) 409 (21.3) 24 (1.2)

Partners 1696 1332 (78.5) 339 (20.0) 25 (1.5)

Babies 1221 1221 (78.9) 303 (19.6) 24 (1.6)

AGT M235T

TT CT CC

Mothers 1946 662 (34.0) 960 (49.3) 324 (16.6)

Partners 1712 639 (37.3) 793 (46.3) 280 (16.4)

Babies 1574 538 (34.2) 772 (49.0) 264 (16.8)

AGTR1 A1166C

AA CA CC

Mothers 1923 940 (48.9) 816 (42.4) 167 (8.7)

Partners 1691 805 (47.6) 732 (43.3) 154 (9.1)

Babies 1534 756 (49.0) 659 (42.7) 128 (8.3)

AGTR2 C4599A

AA CA CC

Mothers 1938 444 (22.9) 988 (51.0) 506 (26.1)

Partners 1717 895 (52.1)

822 (47.9)

Female babies 824 183 (22.2) 417 (50.6) 224 (27.2)

Male babies 781 405 (51.9)

376 (48.1)

AGTR2 A1675G

AA AG GG

Mothers 1944 492 (25.3) 986 (50.7) 466 (24.0)

Partners 1651 839 (50.8)

812 (49.2)

Female babies 801 215 (26.8) 394 (49.2) 192 (24.0)

Male babies 752 348 (46.3)

404 (53.7)

AGTR2 T1334C

TT CT CC

Mothers 1948 1817 (93.3) 129 (6.6) 2 (0.1)

Partners 1750 1697 (97.0)

53 (3.0)

Female babies 829 774 (93.4) 53 (6.4) 2 (0.2)

Male babies 797 771 (96.7)

26 (3.3)

Renin T/G

TT GT GG

Mothers 1916 1167 (60.9) 662 (34.6) 87 (4.5)

Partners 1691 1016 (60.1) 609 (36.0) 66 (3.9)

Babies 1550 951 (61.4) 523 (33.7) 76 (4.9)

Data are presented as n (%).

51

CHAPTER 4

Association of RAS polymorphisms with maternal circulating RAS

profile at 15 weeks’ gestation

52

4.1 Abstract:

Aims: Our aim was to determine the association of maternal and neonatal RAS

polymorphisms, including renin T/G, ACE A11860G, AGT M235T and AGT T174M, with

maternal circulating RAS peptide concentrations at 15 weeks’ gestation.

Methods: Participants (n=367) were randomly selected from the SCOPE study. Blood

samples were taken at 15 weeks’ gestation. DNA was genotyped by Sequenom MassARRAY.

Plasma prorenin, ACE, ANG II and ANG 1-7 concentrations were measured.

Results: Maternal and neonatal ACE A11860G GG genotype was associated with a 36% and

26% increase in maternal plasma ACE concentration compared with the AA genotype (both

p<0.0001), respectively. Neonatal renin T/G GG genotype was associated with a 46% (p=0.03)

decrease in plasma ANG 1-7 concentration compared with the TT genotype. Maternal AGT

M235T TT genotype was associated with a 40% increase (p=0.04) in plasma ANG 1-7

concentration compared with the MM genotype.

Conclusion: The association of RAS polymorphisms with maternal circulating RAS

concentrations at 15 weeks’ gestation indicates the functional effects of these polymorphisms

and suggests their potential associations with pregnancy complications.

53

4.2 Introduction:

Determination of functional effects of genetic polymorphisms has become an indispensible

part of genetic association studies. Polymorphisms with functional effects are more likely

contributing to the risk for a disease and hence their associations with the disease are less

likely to be false positive. Therefore, candidate gene association studies commonly select

gene variants with known functional effect(s) to include in the studies. Similarly, functional

experiments are normally required to determine the functional effects of gene variants, which

reach statistical significance in genome wide association studies.

The renin angiotensin system (RAS) polymorphisms selected in the current study, including

renin T/G (rs4343), ACE A11860G (rs4343), AGT M235T (rs699) and AGT T174M (rs4762)

are functional polymorphisms. Renin T/G, located in intron 4 of the renin gene on

chromosome 1, has previously been shown to associate with systolic blood pressure in two

Spanish cohorts [127]. ACE A11860G, located in exon 17 of the ACE gene on chromosome

17, is associated with serum ACE activity in two young-onset hypertension cohorts [147].

AGT M235T, located in exon 2 of the AGT gene on chromosome 1, is associated with plasma

AGT concentration in several cohorts [128,129]. Although studies [142,143] have failed to

demonstrate an association between plasma AGT concentration and AGT T174M, which is in

complete linkage disequilibrium with AGT M235T [142], the polymorphism in a recent study

is shown to associate with infants’ gestational age and birth weight [144].

In the current study, we aimed to determine the association of these RAS polymorphisms with

maternal plasma concentration of angiotensin II (ANG II) and angiotensin 1-7 (ANG 1-7), the

main effectors of the RAS. In addition, we also determined the association between renin T/G

and maternal plasma prorenin concentration and the association between ACE A11860G and

maternal plasma ACE concentration.

54

4.3 Materials and Methods

Ethics approval

Ethical approval was obtained from the Central Northern Adelaide Health Service Ethics of

Human Research Committee (study number: REC 1714/5/2008). All participants provided

written informed consent. Australian clinical trial registry number: ACTRN 12607000551493.

Participants

The participants (n=367) in the current study were selected from the Australian SCOPE

(Screening for Pregnancy Endpoints) cohort. Women were recruited to the SCOPE study

before 15 weeks’ gestation through hospital antenatal clinics, obstetricians, general

practitioners, community midwives, and self referral in response to advertisements or

recommendations by friends. Women were not eligible if they were judged to be at high risk

of preeclampsia, small for gestational age babies, or spontaneous preterm birth because of

underlying medical conditions, gynaecological history, three or more previous miscarriages,

or three or more terminations of pregnancy, or who had received interventions that might

modify pregnancy outcome [216].

Participants were interviewed and examined by a research midwife at 15±1 weeks of gestation.

Maternal demographic and dietary information was collected, including ethnicity, age, height,

weight, birth weight, gestational age at birth, socio-economic index (SEI5) [217], smoking

status at 15 weeks’ gestation and pre-pregnancy green leafy vegetable consumption. Two

consecutive manual blood pressure measurements were taken and recorded.

Sample collection

5 The New Zealand socio-economic index of occupational status, a number between 10 and 90 and is an occupationally

derived indicator of socio-economic status. It is a validated measure of an individual’s socioeconomic status and a higher

score indicates higher socio-economic status.

55

Whole blood was collected in EDTA tubes from women at 15±1weeks of gestation, from

partners at some time during the woman’s pregnancy and umbilical cord after delivery.

Plasma and buffy coat were separated via centrifugation and stored at -80oC within 3 hours of

collection. Buccal swabs or saliva samples were collected from partners, who were unwilling

to undergo venepuncture, and babies whose cord blood was not obtained at delivery. The

buccal swabs were applied to Whatman FTA cards (Whatman, USA) immediately following

sample collection and saliva was collected using Oragene kits (DNA genotek, USA).

Genotyping assays

Maternal, paternal and neonatal DNA was extracted from buffy coats isolated from peripheral

or cord blood (QiAamp 96 DNA blood kit), Whatman FTA cards or from saliva

(Oragene®DNA kits) following the manufacturers’ instructions. Genotyping was condusted by

the Australian Genome Research Facility (AGRF) using the Sequenom MassARRAY system.

Two quality control procedures were performed to ensure the accuracy of genotyping data: 1)

Each sample was genotyped for Amelogenin, a sex-determinant gene [219]. 2) Parental and

neonatal genotyping data were checked for a Mendelian pattern of inheritance. The samples

were excluded from the analyse if an inconsistency between the sex of the sample and the

corresponding Amelogenin genotype or/and non-Mendelian pattern of inheritance were

observed. In addition, some samples were excluded due to inadequate blood samples, low

quality of DNA or failure to genotype. The sample sizes for the genotyping data are shown in

the results tables.

Plasma RAS peptides concentrations

Plasma prorenin and ACE concentrations were measured using commercially available

Enzyme-linked immunosorbent assay (ELISA) kits for human prorenin (Molecular

Innovations, MI, USA) and human ACE (R & D Systems, Minneapolis, USA), according to

the manufacturer’s recommendations.

56

Plasma ANG II and ANG 1-7 concentrations were measured by ProSearch International

Australia Pty. Ltd. (Malvern, Australia) using radioimmunoassays (RIA). Plasma was first

incubated with ANG II or ANG 1-7 antibody for 20 h at 4˚C. Radioactive ANG II or ANG 1-

7 tracers were then added and allowed to equilibrate for 16 h at 4˚C. The bound and free

phases of the tracers were separated by centrifugation with Dextran 10 coated charcoal. The

antibody and radioactive tracer for ANG II were rabbit anti-human angiotensin II (N-

terminally conjugated to bovine thyroglobulin) and 125

I-Angiotensin II tracer (10 000 cpm,

Peninsula Laboratories, Belmont, CA, USA), respectively. For ANG 1-7, guinea pig anti-

human angiotensin 1-7 (N-terminally conjugated to porcine thyroglobulin) and 125

I-

Angiotensin 1-7 tracer (10 000cpm, Auspep, Tullamarine, Australia) were used. For the ANG

II RIA, the sensitivity and intra- and inter-assay coefficients of variation were 4 pmol/L, 6.4%

and 12%, respectively. For the ANG 1-7 RIA, the sensitivity and intra- and inter-assay

coefficients of variation were 13 pmol/L, 4.5% and 10%, respectively.

Statistics

The association of RAS polymorphisms with maternal plasma RAS peptides concentrations at

15 weeks’ gestation was determined by using Mann-Whitney U Tests. All data analyses were

performed using PASW (SPSS, Chicago) version 17.02.

57

4.4 Results

Characteristics of the population

The characteristics of the participants were presented in table 4.1.

RAS polymorphisms and maternal plasma RAS concentration at 15 weeks’ gestation

Table 4.2 presents the results on the association of RAS polymorphisms with maternal RAS

concentrations at 15 weeks’ gestation. None associations were observed for maternal plasma

prorenin and ANG II concentrations at 15 weeks’ gestation. Four associations were identified

for maternal plasma ACE and ANG 1-7 concentration at 15 weeks’ gestation:

Renin T/G

Neonatal renin T/G GG genotype was associated with a 46% decrease in maternal plasma

ANG 1-7 concentration compared with the TT genotype (Table 4.2). A similar trend (non-

significant) was observed for maternal renin T/G (Table 4.2).

ACE A11860G

Maternal ACE A11860G GG and AG genotype were associated with a 36% and a 13%

increase in maternal plasma ACE concentration at 15 weeks’ gestation compared with the AA

genotype (Table 4.2). Neonatal ACE A11860G GG genotype was associated with a 26%

increase in maternal plasma ACE concentration at 15 weeks’ gestation compared with the AA

genotype (Table 4.2).

AGT M235T

Women with the AGT M235T TT genotype had 40% higher plasma ANG 1-7 concentration

than those with the MM genotype (Table 4.2).

58

4.5 Discussion:

The current study demonstrated overall 4 associations. Maternal and neonatal ACE A11860G

GG genotypes were associated with elevated maternal plasma ACE concentration at 15 weeks’

gestation compared with the AA genotype. Neonatal renin T/G GG genotype was associated

with a reduction in maternal plasma ANG 1-7 concentration compared with the TT genotype.

In addition, maternal AGT M235T MM genotype was associated with an increase in maternal

plasma ANG 1-7 concentration at 15 weeks’ gestation compared with the MM genotype.

The association of maternal and neonatal ACE A11860G with maternal plasma ACE

concentration is consistent with previous findings in non-pregnant hypertensive cohorts, in

which this polymorphism was shown to associate with serum ACE activity [147].

Prorenin is the inactive precursor of renin. The current study measured maternal plasma

prorenin concentration at 15 weeks’ gestation. Although no association between renin T/G

and plasma prorenin concentration was observed, we found an association of this

polymorphism in neonates with plasma concentration of ANG 1-7, the peptide downstream of

renin in the RAS activation cascade (Figure 1.1), suggesting that renin T/G may be associated

with plasma active renin concentration/activity.

AGT M235T is one of the most well studied AGT polymorphisms. Compared to the AGT

M235T MM genotype, the TT genotype has been shown to associate with an 11% increase in

plasma AGT concentration in a meta analysis pooling data from 6 cohorts [128]. Although the

current study did not measure maternal plasma AGT concentration, the observed association

between maternal AGT M235T and plasma concentration of ANG 1-7, the peptide

downstream of AGT in the RAS activation cascade (Figure 1.1), may indicate an association

of this polymorphism with plasma AGT. Unexpectedly, in the current study, no associations

were found for AGT T174M, which has previously been shown to be in complete linkage

disequilibrium with AGT M235T [142].

59

In the current study, two associations were found in neonates, that is, the association between

neonatal ACE A11860G and plasma ACE concentration and the association between neonatal

renin T/G and plasma ANG 1-7 concentration. This is intriguing, since the results may

suggest the secretion of fetoplacental RAS components into the maternal circulation and

affect maternal systemic RAS level/activity. Prorenin expression is found in

syncytiotrophoblasts in the human placenta [50] and data from sampling paired uterine artery

and vein at term suggest that the uteroplacental unit contributes to maternal circulating

prorenin concentrations [28]. ACE expression is present in vascular endothelium in human

term placenta [50,227], although it is unknown whether the placental ACE can be secreted to

the maternal circulation. Furthermore, the interaction between the fetoplacental and maternal

systemic RAS is well documented in human AGT (hAGT) and human renin (hrenin)

transgenic mouse experiments [95]. When female transgenic mice carrying hAGT are crossed

with transgenic males carrying hrenin, circulating ANG II concentration in these pregnant

transgenic mice is 5-fold higher than that in wild type females (i.e. carrying mouse AGT gene)

crossed with either wild type males or transgenic males carrying hrenin. Since circulating

hAGT in transgenic females carrying hAGT can only be cleaved by hrenin but not mouse

renin, excess production of ANG II observed in these pregnant transgenic mice must be due to

secretion of fetoplacenta-derived hrenin inherited from fathers carrying hrenin.

Aberrant maternal RAS profiles have been documented in preeclamptic women [86],

suggesting the involvement of RAS in the pathogenesis of preeclampsia. The associations

between RAS polymorphisms and maternal RAS profiles at 15 weeks’ gestation observed in

the current study may indicate the potential associations of these polymorphisms with

pregnancy complications, especially preeclampsia. Indeed, ACE A11860G [144] and AGT

M235T [129,130,131] have previously been shown to associate with risk for preeclampsia.

60

Although the association between renin T/G and preeclampsia has not been determined

previously, the polymorphism has been shown to associate with hypertension [127].

In summary, we found that maternal and neonatal ACE A11860G was associated with

maternal plasma ACE concentration at 15 weeks’ gestation. Neonatal renin T/G and maternal

AGT M235T were associated with plasma ANG 1-7 concentration at 15 weeks gestation.

These associations indicate the functional effects of these RAS polymorphisms on maternal

circulating RAS peptide concentrations and may potentially predispose a woman to

pregnancy complications, in particular preeclampsia.

61

Table 4.1 Characteristics of the study population. Participants

Characteristics n=367

Age (yrs) at booking 24.3 (5.5)

BMI (kg/m2) at 15 wks 28.1 (6.9)

sBP (mmHg) at 15 wks 110.1 (10.5)

dBP (mmHg) at 15 wks 65.1 (8.4)

Socio-economic index 28.6 (11.7)

Pre-pregnancy green leafy vegetable intake ≥1 serve/day (%) 93 (25.4%)

Smoking (%) at 15 wks 91 (24.8%)

Data are expressed as mean (SD) or n (%).

62

Table 4.2 The association of RAS polymorphisms with maternal plasma RAS peptide concentrations at 15 weeks’ gestation.

n

Maternal plasma

[Prorenin] ng/ml P

Maternal plasma

[ACE] ug/l P

Maternal plasma

[ANG 1-7] pg/ml P

Maternal plasma

[ANG II] pg/ml P

Maternal Renin T/G

TT 202 3.2 (1.5) Ref 105.6 (58.9) Ref 107.3 (100.0) Ref 131.8 (63.5) Ref

GT 107 3.1 (1.4) - 118.7 (72.7) - 99.0 (95.1) - 126.5 (64.7) -

GG 19 3.1 (1.4) - 99.8 (40.0) - 71.2 (45.7) - 133.3 (62.8) -

Neonatal Renin T/G

TT 130 3.2 (1.6) Ref 110.5 (63.1) Ref 104.5 (97.9) Ref 128.2 (59.4) Ref

GT 93 3.2 (1.5) - 106.1 (62.1) - 95.0 (94.1) 0.6 128.2 (66.2) -

GG 12 3.4 (1.5) - 100.8 (38.5) - 57.0 (39.7) 0.03 138.9 (47.7) -

Maternal ACE A11860G

AA 69 2.9 (1.3) Ref 90.8 (56.4) Ref 89.1 (79.8) Ref 129.8 (54.3) Ref

AG 171 3.2 (1.6) - 109.5 (61.5) 0.001 107.0 (100.5) - 127.5 (65.6) -

GG 89 3.2 (1.5) - 123.6 (68.0) <0.001 96.9 (78.7) - 132.3 (64.9) -

Neonatal ACE A11860G

AA 61 3.0 (1.2) Ref 97.4 (57.9) Ref 91.1 (73.8) Ref 126.8 (57.7) Ref

AG 118 3.3 (1.7) - 105.1 (55.0) 0.2 102.5 (98.1) - 129.2 (60.8) -

GG 58 3.1 (1.7) - 122.5 (73.0) 0.001 84.2 (74.5) - 132.0 (61.4) -

Maternal AGT T174M

TT 246 3.1 (1.5) Ref 111.7 (67.4) Ref 100.1 (89.5) Ref 128.9 (63.1) Ref

TM 78 3.3 (1.6) - 102.6 (49.6) - 101.7 (104.3) - 129.6 (62.5) -

MM 5 2.7 (1.3) - 96.4 (21.3) - 114.7 (81.4) - 150.5 (63.5) -

Neonatal AGT T174M

TT 182 3.1 (1.5) Ref 109.0 (65.5) Ref 100.2 (97.6) Ref 131.0 (62.6) Ref

TM 52 3.3 (1.6) - 104.3 (44.8) - 94.9 (85.0) - 133.3 (62.0) -

MM 4 2.5 (0.5) - 70.5 (18.7) - 70.4 (26.7) - 111.8 (23.6) -

Maternal AGT M235T

MM 112 3.0 (1.4) Ref 112.1 (68.2) Ref 92.2 (86.7) Ref 129.9 (65.0) Ref

MT 153 3.3 (1.7) - 106.5 (59.3) - 95.4 (82.8) 1.0 128.1 (61.2) -

TT 71 2.9 (1.3) - 109.6 (61.1) - 129.4 (124.9) 0.04 131.5 (65.1) -

Neonatal AGT M235T

MM 70 3.3 (1.7) Ref 119.8 (72.7) Ref 86.0 (75.0) Ref 122.8 (57.0) Ref

MT 132 3.1 (1.4) - 105.2 (59.2) - 97.6 (89.3) - 131.2 (64.6) -

TT 43 3.3 (1.7) - 96.7 (39.2) - 114.7 (130.2) - 140.7 (56.3) -

Data are expressed as mean (SD). Ref: Referent. Bold italics indicate significant difference.

63

CHAPTER 5

Association of RAS polymorphisms with maternal blood pressure and

uterine and umbilical artery Doppler

64

5.1 Abstract

Aims: Our aims were to determine the association of RAS polymorphisms with maternal

blood pressure at 15 weeks’ gestation, uterine and umbilical artery resistance indices at 20

weeks’ gestation and determine whether the associations are affected by fetal sex.

Methods: 3234 healthy nulliparous women, their partners and babies were recruited

prospectively in Adelaide and Auckland. Data analyses were confined to 2121 Caucasian

parent-infant trios. DNA was extracted from buffy coats and genotyped by utilizing the

Sequenom MassARRAY system. Blood pressure was measured at 15 weeks’ gestation.

Doppler sonography on the uterine and umbilical arteries was performed at 20 weeks’

gestation.

Results: RAS polymorphisms were not associated with blood pressure at 15 weeks’ gestation,

regardless of fetal sex. Among pregnancies bearing females, women with AGT1R A1166C CC

genotype had a 2.4-fold increase in risk for abnormal uterine artery resistance index at 20

weeks’ gestation compared to those with AA genotypes [OR 2.4 95%CI (1.2-4.8)]. Among

pregnancies bearing males, maternal and neonatal AGT M235T TT genotype was associated

with a 2.5-fold and 3.0-fold increase in risk for abnormal umbilical artery resistance index at

20 weeks’ gestation, respectively, compared to those with MM genotypes [OR 2.5 95%CI

(1.3-5.0) and 3.0 95%CI (1.1-7.9), respectively].

Conclusion: The fetal sex specific association of RAS polymorphisms with abnormal uterine

and umbilical artery resistance at 20 weeks’ gestation may suggest sex differences in vascular

tone and RAS activity in the uterine and feto-placental circulation and imply potential fetal

sex specific associations of RAS polymorphisms with pregnancy complications.

65

5.2 Introduction

Pregnancy is associated with a profound decrease in maternal blood pressure and

paradoxically with a concurrent 30-50% increase in plasma volume and cardiac output [23].

These massive hemodynamic changes can only be explained by a primary dramatic fall in

peripheral vascular resistance [24]. In addition, the progression of pregnancy is also

associated with a considerable increase in blood flow to the placenta both on the maternal side

(i.e. uterine blood flow) [228,229] and fetal side (i.e. umbilical blood flow) [230]. The

percentage of maternal cardiac output going to the uterus increases from 3-6% in early

pregnancy to ~12% at term [229,231]. Umbilical vein blood flow rises 444% from mid-

gestation to 38 weeks' gestation [230].

During pregnancy, maternal blood pressure is maintained to a significant extent by the renin

angiotensin system (RAS). Pregnant women are more sensitive to the blood-pressure-

lowering effect of captopril (an ACE inhibitor) than non-pregnant women with similar blood

pressure [43]. While no changes in blood pressure across gestation are observed in wild type

mice, a significant decrease and increase in blood pressure are demonstrated in AGT1a

receptor null mice and AGT2 receptor null mice, respectively [232].

Angiotensin II (ANG II) acts as a vasoconstrictor and plays an important role in regulating

uterine and umbilical blood flow. ANG II administration to healthy pregnant women at 24 -

26 weeks' gestation significantly increases uterine artery resistance index, indicated by an

elevation of uterine artery systolic/diastolic ratio [70]. In sheep, fetal infusion of ANG II

increases umbilical vascular resistance by up to 345% [64].

Over the past decade, several polymorphisms in the RAS component genes have been

identified. ACE A11860G (rs4343) [147], AGT M235T (rs699) [128,129], AGT2R A1675G

(rs1403543) [163] and AGT1R A1166C (rs5186) [156] are functional polymorphisms and are

associated with functional changes of their corresponding proteins. AGT T174M (rs4762)

66

[233], Renin T/G (rs4343) [127], AGT2R C4599A (rs11091046) [160,161], AGT2R T1334C

(rs12710567) [165] are either associated with blood pressure or hypertension.

In the current study, our aim was to determine the association of RAS polymorphisms with

maternal blood pressure at 15 weeks’ gestation, uterine and umbilical artery resistance indices

at 20 weeks’ gestation. Since some of the RAS components are sexually dimorphic [190,191],

in the current study, we stratified our cohort according to fetal sex and explored our aims in

each stratum.

67

5.3 Materials and Methods:

Participants

The participants were healthy nulliparous women with singleton pregnancies prospectively

recruited to the Screening for Pregnancy Endpoints (SCOPE) study between November 2004

and September 2008 in Adelaide, Australia and Auckland, New Zealand [216]. The main aim

of the SCOPE is to develop screening tests to predict preeclampsia, small for gestational age

infants and spontaneous preterm birth. Ethical approval was gained from local ethics

committees (Australia REC 1712/5/2008 and New Zealand AKX/02/00/364) and all women

and partners provided written informed consent. Overall 3234 parent-infant trios were

recruited into the study and the population for this genetic study was constrained to the 2121

Caucasian parent-infant trios (66%) (Figure 5.1).

Women were recruited to the SCOPE study prior to 15 weeks’ gestation through hospital

antenatal clinics, obstetricians, general practitioners, community midwives and self referral in

response to advertisements or recommendations of friends. Women were excluded if they

were judged to be at high risk of preeclampsia, small for gestational age babies or

spontaneous preterm birth because of underlying medical conditions, gynaecological history,

three or more previous miscarriages or three or more terminations of pregnancy or if they had

received interventions that might modify pregnancy outcome [216].

Participants were interviewed and examined by a research midwife at 15±1 weeks of gestation.

Maternal demographic and dietary information was collected, including ethnicity, age, height,

weight, birth weight, gestational age at birth, socio-economic index (SEI6)[217], smoking

status at 15 weeks’ gestation and pre-pregnancy green leafy vegetable intake. Two

6 The New Zealand socio-economic index of occupational status, a number between 10 and 90, is an occupationally derived

indicator of socio-economic status. It is a validated measure of an individual’s socioeconomic status and a higher score

indicates higher socio-economic status.

68

consecutive manual blood pressure measurements were recorded. Paternal information,

including age, birth weight, height and weight, were also recorded. Newborn measurements

were recorded by research midwives usually within 72 hours of birth. The recorded

parameters included infant’s gestational age at birth, body length, head circumference, mid

arm circumference, birth weight and customised birthweight centile. Ultrasound and Doppler

studies of the umbilical and uterine arteries were performed at 20 weeks’ gestation [218]. The

uterine and umbilical artery resistance indices were classified as abnormal if the value was

above the 90th

centile.

Sample collection

Whole blood was collected in EDTA tubes from women at 15 ± 1 weeks of gestation, from

partners at some time during the woman’s pregnancy and umbilical cord after delivery. Blood

samples were centrifuged and plasma and buffy coat separated and stored at -80oC within 3

hours of collection. Buccal swabs or saliva samples were collected from partners who were

unwilling to undergo venepuncture and babies whose cord blood was not obtained at delivery.

The buccal swabs were applied to Whatman FTA cards (Whatman, USA) immediately

following sample collection and saliva was collected using Oragene kits (DNA genotek,

USA).

Genotyping assays

DNA was extracted from buffy coats isolated from peripheral or cord blood (QiAamp 96 DNA

blood kit), Whatman FTA cards or from saliva (Oragene®DNA kits) following the

manufacturers’ instructions. Genotyping was performed by the Australian Genome Research

Facility (AGRF) utilizing the Sequenom MassARRAY system. Two quality control

procedures were in place to ensure the accuracy of genotyping data: 1) Each sample was

genotyped for Amelogenin to assess the consistency between the sex of samples and the

corresponding Amelogenin genotype [219]; 2) Parental and neonatal genotyping data were

69

checked for a Mendelian pattern of inheritance. The samples with inconsistent results in either

step were excluded from the analyses. In addition, some samples were excluded due to

inadequate blood samples, low quality of DNA or failure to genotype. The sample sizes for the

genotyping data are shown in the results tables.

Statistics

Independent samples t test (for continuous variable) and chi-square (for categorical variable)

were used to compare the differences between participants ≤90th

centile uterine or umbilical

artery resistance index and those >90th

centile. Linear regression was used to test the

relationship between the polymorphisms and mean arterial blood pressure at 15 weeks’

gestation. Logistic regression was used to test the association of the polymorphisms with

abnormal uterine/umbilical artery resistance index at 20 weeks’ gestation and odds ratios (OR)

with 95% confidence interval (C.I.) were generated. The interaction between polymorphisms

and environmental factors was assessed by introducing the interaction term in the linear or

logistic regression. All data analyses were performed using PASW (SPSS, Chicago) version

17.02. P < 0.05 was considered statistically significant.

70

5.4 Results:

Characteristics of the study population

There were no differences in maternal and paternal characteristics between pregnancies

bearing males and females (Table 5.1). Male babies had longer body length (↑0.9cm

p<0.0001), greater head circumference (↑0.6mm p<0.0001), greater mid arm circumference

(↑0.2mm p<0.001) and higher birth weight (↑116.2g p<0.0001) than female babies, adjusted

for gestational age (Table 5.1). Pregnancies bearing female babies were 5.5% more likely to

have umbilical artery resistance index >90th

centile at 20 weeks gestation (p<0.0001) (Table

5.1).

Association of RAS polymorphisms with mean arterial pressure (MAP) at 15 weeks’

gestation

RAS polymorphisms were not associated with MAP at 15 weeks’ gestation, regardless of fetal

sex (data not shown).

Association of RAS polymorphisms with uterine artery resistance index at 20 weeks’

gestation

Among pregnancies bearing female babies, women with AGT1R A1166C CC genotype had a

2.4-fold increase in risk for abnormal uterine artery resistance index at 20 weeks’ gestation

compared to those with AA genotypes [OR 2.4 95%CI (1.2-4.8)] (Table 5.2).

Association of RAS polymorphisms with umbilical artery resistance index at 20 weeks’

gestation

Among pregnancies bearing males, women with AGT M235T TT genotype had a 2.5-fold

increase in risk for abnormal umbilical artery resistance index at 20 weeks’ gestation

compared to those with MM genotypes [OR 2.5 95%CI (1.3-5.0)] (Table 5.3). In addition,

71

male babies with AGT M235T TT genotype had 3.0-fold increase in risk for abnormal

umbilical artery resistance index at 20 weeks’ gestation compared to those with MM

genotypes [OR 3.0 95%CI (1.1-7.9)] (Table 5.3).

72

5.5 Discussion:

In the current study, we observed three associations, namely, the association of maternal

AGT1R A1166C with abnormal uterine artery resistance index (>90th

centile) at 20 weeks’

gestation and associations of maternal and neonatal AGT M235T with abnormal umbilical

artery resistance index (>90th

centile) at 20 weeks’ gestation. Interestingly, all three

associations appeared to be affected by fetal sex, such that the maternal AGT1R A1166C-

abnormal uterine artery resistance association was only apparent in female-bearing

pregnancies and the maternal and neonatal AGT M235T-abnormal umbilical artery resistance

associations were only observed in male-bearing pregnancies.

AGT1R A1166C is located in the 3’ UTR of AGT1R gene on chromosome 3. The CC

genotype of AGT1R A1166C has been previously demonstrated to associate with a greater

response to ANG II than the AA genotype [156]. Consistently, in our SCOPE cohort, the

AGT1R A1166C CC genotype was associated with a greater risk for abnormal uterine artery

resistance than the AA genotype. More interestingly, this association was only observed in

pregnancies bearing females. The fact that the maternal association is affected by fetal sex

suggests that the secretion of sex specific placental factors (yet to be identified) into the

maternal circulation modulates maternal physiology. The concept of fetal sex affecting

maternal physiology has also been demonstrated in asthmatic studies, in which fetal sex was

found to affect severity of asthma during pregnancy by influencing maternal inflammatory

pathways [234,235,236].

In the current study, fetal sex may influence the association of maternal AGT1R A1166C by

modulating uterine vascular tone and/or uterine RAS activity. Two lines of evidence support

this hypothesis. Firstly, fetal sex has previously been shown to affect uterine artery resistance,

measured by pulsality index, such that the second trimester uterine artery resistance is lower

in female-bearing pregnancies than male-bearing pregnancies [237]. Secondly, a recent study

73

demonstrates that fetal sex affects pro-renin expression in term decidua, specifically,

pregnancies bearing females have higher pro-renin mRNA expression and secretion than

those pregnancies bearing males [189]. All together, it appears that women bearing females

have lower uterine vascular tone but higher decidual RAS activity than those bearing males,

both of which would enhance the functional effect of AGT1R A1166C and ultimately lead to

the emergence of the association of AGT1R A1166C with uterine artery resistance observed in

the current study. Given the vasoconstricting effect of ANG II, it seems counter intuitive that

female-bearing pregnancies have reduced uterine vascular tone but also the elevated decidual

RAS activity, however, vascular tone is also regulated by other vasoactive substances, such as

bradykinin, NO, prostaglandin, all of which are vasodilators and would counteract the

vasoconstricting effect of ANG II.

Estrogen and testosterone are potential candidates for the feto-placental derived factors that

may mediate the sex specific effects, since they are known to affect the RAS and are

responsible for sexual dimorphism of the RAS in adults [190,191]. However, third trimester

maternal circulating estrogen [238] and testosterone [238,239] concentrations are similar

between pregnancies bearing males and females. Human chorionic gonadotropin (hCG) and

leptin are also possible candidates, since they both stimulate RAS activity [240,241] and both

molecules are higher in the maternal circulation in pregnancies bearing females than males

[237,239,242,243].

AGT M235T is one of the most well studied AGT polymorphisms. Compared to the AGT

M235T MM genotype the TT genotype was shown to associate with an 11% increase in

plasma AGT concentration in a meta-analysis pooling data for Caucasians from 6 cohorts

[128]. Since maternal AGT M235T genotype has previously been shown to associate with

diameters of spiral arteries [244], one would expect an association of this polymorphism with

abnormal uterine artery resistance. However, this was not observed in our cohort. The

74

inconsistency may be partly due to differences in the ethnicity and clinical characteristics

between the cohorts. The cohort in the former study was a homogenous population of

Mormons in Utah [244] and the association of AGT M235T with preeclampsia [129], which

was originally identified in the same Utah cohort, has also failed to be replicated by others

[133,134,135,136,137,140].

In the current study, maternal and fetal AGT M235T TT genotype was associated with a

greater risk for abnormal umbilical artery resistance than the MM genotype. The maternal

association suggests that maternal AGT or even ANG II may cross the placenta and affect

fetal-placental vascular tone. In sheep, maternal infusion of ANG II has been shown to

increase fetal mean arterial pressure and heart rate [245].

More interestingly, the associations of maternal and fetal AGT M235T with abnormal

umbilical artery resistance were specific to pregnancies bearing males, suggesting sex

differences in fetal vascular tone or fetal RAS activity. In adults, RAS activity varies between

males and females due to differences in sex hormones [190,191]. As a consequence, the

associations of RAS polymorphisms with cardiovascular diseases vary between sexes, such

that the associations are more profound in males than females [192,193,194,195,196,197].

Estrogen and testosterone concentrations in the third trimester umbilical vein have been

measured and compared between pregnancies bearing males and females [246,247]. Although

no difference is observed for estradiol, testosterone concentration in the third trimester

umbilical vein is higher in male-bearing pregnancies than female-bearing pregnancies

[246,247], which may potentially be an important factor contributing to the male-specific

associations observed in the current study.

In vitro testosterone has been shown to relax human umbilical arteries via an androgen

receptor-independent mechanism(s), involving stimulation of Ca2+

activated and voltage

sensitive potassium channels [248] and activation of protein kinase G [249]. Indeed, the

75

vasodilating effect of testosterone may partly explain our observation that female-bearing

pregnancies, which would have lower umbilical testosterone concentration, were more likely

to have abnormal umbilical artery resistance index than male-bearing pregnancies. In addition,

despite its vasodilating effect on placental vasculature, testosterone may potentially stimulate

placental RAS activity. In rats, it was demonstrated that the renal AGT mRNA level is higher

in males than in females [250] and castration reduces, whereas testosterone treatment

increases, renal AGT mRNA expression [251]. All together, higher concentration of umbilical

testosterone in male-bearing pregnancies would be expected to dilate placental vasculature

and stimulate placental RAS activity, consequently allowing the emergence of the association

of AGT M235T with umbilical artery resistance observed in the current study.

In our SCOPE cohort, abnormal uterine artery resistance index (>90th

centile) at 20 weeks’

gestation is associated with an increased risk for preeclampsia, small for gestational age and

preterm birth (Chapter 3). In addition, abnormal umbilical artery resistance index (>90th

centile) at 20 weeks’ gestation is associated with preeclampsia (Chapter 3). The associations

of AGT1R A1166C and AGT M235T with abnormal uterine or umbilical artery observed in the

current study suggest the two polymorphisms may associate with pregnancy complications.

Indeed, both polymorphisms have previously been shown to associate with preeclampsia

[129,130,131,144,158]. However, these associations have previously been investigated

without considering fetal sex. In the light of the current study, it would be interesting to

determine if these associations are fetal sex specific.

In conclusion, the sex differences in the association of RAS polymorphisms with abnormal

uterine and umbilical artery resistance at 20 weeks’ gestation may suggest sex differences in

vascular tone and RAS activity in the uterine and feto-placental circulations. In addition,

given the association of elevated uterine and umbilical artery resistance with pregnancy

76

complications, the sex specific associations observed in the current study may potentially

imply sex differences in associations of RAS polymorphisms with pregnancy complications.

77











78

Table 5.1 Characteristics of the study population.

Pregnancies bearing females Pregnancies bearing males

Maternal characteristics n=1069 n=1052 P

Age (yrs) at 15 wks 27.8 (5.6) 28.1 (5.9) 0.3

BMI (kg/m2) at 15 wks

BMI<25 kg/m2 522 (51.0%) 502 (49.0%)

BMI≥25 kg/m2 547 (49.9%) 550 (50.1%) 0.6

MAP (mmHg) at 15 wks 78.9 (8.2) 79.3 (7.7) 0.3

Socio-economic index 39.7 (16.7) 40.7 (16.6) 0.2

Green leafy vegetable intake (%)

≥1 serve/day 493 (48.9%) 515 (51.1%)

<1 serve/day 576 (51.8%) 537 (48.2%) 0.2

Smoking (%) at 15 wks

No Smoking 947 (50.5%) 930 (49.5%)

Smoking 122 (50.0%) 122 (50.0%) 0.9

Maternal gestational age (wks) 39.8 (2.0) 39.8 (2.1) 1.0

Maternal birth weight (g) 3296.1 (565.5) 3281.9 (533.0) 0.6

Uterine artery resistance index

≤90th centile 956 (91.5%) 924 (89.5%)

>90th centile 89 (8.5%) 108 (10.5%) 0.1


Age (yrs) 30.5 (6.3) 30.6 (6.5) 0.7

Height (cm) 179.2 (6.9) 179.2 (6.7) 1.0

BMI (kg/m2) 26.8 (4.3) 26.9 (4.4) 0.8

Paternal birth weight (g) 3453.3 (619.4) 3462.1 (559.3) 0.7


Gestational age at birth (days) 276.8 (16.1) 275.9 (17.3) 0.2

Body length (cm) 49.7 (3.0) 50.4 (3.5) <0.0001

Head circumference (mm) 34.4 (1.8) 34.9 (2.2) <0.0001

Mid arm circumference (mm) 10.6 (1.1) 10.8 (1.2) <0.0001

Birth weight (g) 3345.6 (582.1) 3438.1 (624.8 <0.0001


Umbilical artery resistance index

≤90th centile 929 (88.8%) 972 (94.3%)

>90th centile 117 (11.2%) 59 (5.7%) <0.0001

Data are presented as mean (SD) or n (%). MAP: mean arterial blood pressure, the second measurement; 15 wks:

15 weeks’ gestation. Bold italics indicates significant difference.

79

Table 5.2 The association of AGT1R A1166C with abnormal uterine artery resistance index at

20 weeks’ gestation, stratified by fetal sex.

Maternal AGT1R A1166C n Ute RI>90th centile OR (95% CI) P

Whole AA 919 87 (9.5%) Ref

CA 802 76 (9.5%) 1.0 (0.7-1.4) 1.0

CC 19 19 (11.7%) 1.3 (0.8-2.1) 0.4

Males AA 476 55 (11.6%) Ref

CA 389 39 (10.0%) 0.9 (0.6-1.3) 0.5

CC 80 6 (7.5%) 0.6 (0.3-1.5) 0.3

Females AA 443 32 (7.2%) Ref

CA 413 37 (9.0%) 1.3 (0.8-2.1) 0.4

CC 83 13 (15.7%) 2.4 (1.2-4.8) 0.01

Paternal AGT1R A1166C

Whole AA 794 78 (9.8%) Ref

CA 718 73 (10.2%) 1.0 (0.7-1.5) 0.8

CC 153 15 (9.8%) 1.0 (0.6-1.8) 1.0

Males AA 381 44 (11.5%) Ref

CA 358 35 (9.8%) 0.8 (0.5-1.3) 0.4

CC 80 9 (11.3%) 1.0 (0.5-2.1) 0.9


CA 360 38 (10.6%) 1.3 (0.8-2.1) 0.3

CC 73 6 (8.2%) 1.0 (0.4-2.5) 1.0

Neonatal AGT1R A1166C n

Whole AA 740 67 (9.1%) Ref

CA 651 66 (10.1%) 1.1 (0.8-1.6) 0.5

CC 125 7 (5.6%) 0.6 (0.3-1.3) 0.2

Males AA 360 42 (11.7%) Ref

CA 325 37 (11.4%) 1.0 (0.6-1.6) 1.0

CC 62 4 (6.5%) 0.5 (0.2-1.5) 0.5


CA 326 29 (8.9%) 1.4 (0.8-2.4) 0.3

CC 63 3 (4.8%) 0.7 (0.2-2.4) 0.6

The data were analysed in the whole cohort irrespective of infant sex, and then in pregnancies bearing females

and those bearing males, separately. Data are presented as n (%).Ute RI>90th centile: uterine artery resistance

index> 90th

centile; Ref: Referent, OR: odds ratio. Bold italics indicates significant difference.

80

Table 5.3 The association of AGT M235T with abnormal umbilical artery resistance index at

20 weeks’ gestation, stratified by fetal sex.

Maternal AGT M235T n Umb RI>90th centile OR (95% CI) P

Whole MM 651 55 (8.4%) Ref

MT 937 69 (7.4%) 0.9 (0.6-1.5) 0.4

TT 319 37 (11.6%) 1.4 (0.9-2.2) 0.1

Males MM 328 17 (5.2%) Ref

MT 461 15 (3.3%) 0.6 (0.3-1.3) 0.2

TT 165 20 (12.1%) 2.5 (1.3-5.0) 0.007

Females MM 323 38 (11.8%) Ref

MT 476 54 (11.3%) 1.0 (0.6-1.5) 0.9

TT 154 17 (11.0%) 0.9 (0.5-1.7) 0.8

Paternal AGT M235T

Whole MM 624 50 (8.0%) Ref

MT 783 68 (8.7%) 1.1 (0.8-1.6) 0.7

TT 272 17 (6.3%) 0.8 (0.4-1.4) 0.4

Males MM 304 14 (4.6%) Ref

MT 377 24 (6.4%) 1.4 (0.7-2.8) 0.3

TT 139 9 (6.5%) 1.4 (0.6-3.4) 0.4


MT 406 44 (10.8%) 1.0 (0.6-1.5) 0.9

TT 133 8 (6.0%) 0.5 (0.2-1.1) 0.09

Neonatal AGT M235T n

Whole MM 526 43 (8.2%) Ref

MT 761 57 (7.5%) 0.9 (0.6-1.4) 0.7

TT 263 22 (8.4%) 1.0 (0.6-1.8) 0.9

Males MM 259 7 (2.7%) Ref

MT 371 18 (4.9%) 1.8 (0.8-4.5) 0.2

TT 132 10 (7.6%) 3.0 (1.1-7.9) 0.03


MT 390 39 (10.0%) 0.7 (0.4-1.2) 0.2

TT 131 12 (9.2%) 0.7 (0.3-1.3) 0.2

The data were analysed in the whole cohort irrespective of infant sex, and then in pregnancies bearing females

and those bearing males, separately. Data are presented as n (%).Umb RI>90th centile: umbilical artery

resistance index> 90th

centile; Ref: Referent, OR: odds ratio. Bold italics indicates significant difference.

81

CHAPTER 6

The association of maternal ACE A11860G with SGA is modulated by

the environmental factors and fetal sex

82

6.1 Abstract:

Aims: We aimed to determine whether ACE A11860G genotype is associated with small for

gestational age babies (SGA) and to determine whether the association is affected by

environmental factors and fetal sex.

Methods: 3234 healthy nulliparous women with singleton pregnancies, their partners and

babies were prospectively recruited to the Screening for Pregnancy Endpoints (SCOPE) study

in Adelaide, Australia and Auckland, New Zealand. Data analyses were confined to 2121

Caucasian parent-infant trios, among which 216 were SGA pregnancies. 1185 uncomplicated

pregnancies served as controls. DNA was genotyped by Sequenom MassARRAY. Maternal

plasma ACE concentration at 15 weeks’ gestation was measured by ELISA.

Results: In the combined cohort, mothers with ACE A11860G GG genotype had increased

risk for SGA (OR 1.5, 95%CI 1.1-2.1) and delivered lighter babies (p=0.02). These

associations were only observed in Australian pregnancies and not New Zealand pregnancies.

Socio-economic index (SEI) and pre-pregnancy green leafy vegetable intake were

significantly different between Australian and New Zealand participants (both p<0.001).

When the Australian pregnancies were stratified by maternal SEI and pre-pregnancy green

leafy vegetable intake, maternal ACE A11860G GG genotype was associated with SGA only

among women with SEI <34 or pre-pregnancy green leafy vegetable intake <1 serve/day (OR

4.9, 95%CI 1.8-13.4 and OR 3.3, 95%CI 1.6-7.0, respectively). Furthermore, after

stratification by infant sex, these interactions were specific to pregnancies bearing females.

Conclusion: The current study identified an association of maternal ACE A11860G with SGA.

This association was influenced by modifiable environmental factors and fetal sex, suggesting

an ACE A11860G-environment-fetal sex interaction. Future genetic association studies into

pregnancy complications should take account of appropriate environmental factors and fetal

sex.

83

6.2 Introduction

Small for gestational age (SGA) babies are usually defined as those with birth weight less

than the 10th

population centile for gestational age [252,253]. Low birth weight or being born

SGA not only increases the risk of morbidity and mortality in the perinatal period [254,255],

but is also associated with an increased risk of the metabolic syndrome in later life, in

particular type II diabetes mellitus, cardiovascular disease and hypertension

[256,257,258,259].

The renin angiotensin system (RAS) plays an important role in regulating blood pressure,

fluid and electrolyte balance [260]. The RAS components including angiotensinogen (AGT),

renin, angiotensin converting enzyme (ACE) and angiotensin type 1 receptor (AGT1R) are

abundantly expressed in the human placenta throughout gestation [47,261] and are proposed

to play a role in placentation. ANG II inhibits trophoblast invasion [66] and stimulates

placental angiogenesis [61]. Furthermore, expression of RAS components has also been

observed in and around spiral arterioles of the first trimester uterus [53], suggesting their

involvement in the remodelling of these vessels. Finally, the T variant of the functional

polymorphism AGT M235T is known to be associated with narrower uterine spiral arterioles

during pregnancy [244], which would be expected to result in reduced maternal blood flow to

the placenta and hence impaired placental exchange functions.

Impaired placentation is implicated in SGA pregnancies. SGA placentas have reduced

volumes of chorionic villi [262,263] and intervillous space [262], reduced peripheral villous

vascularisation [264] and increased placental apoptosis [265,266]. Given the potential role of

the RAS in placentation, RAS genetic polymorphisms, which have functional effects on RAS

expression levels or activity, may be associated with placental abnormalities, and hence with

SGA.

84

The human ACE gene is on Chromosome 17. The ACE A11860G single nucleotide

polymorphism (rs4343) is located in exon 16 and in close proximity to the well-known 287 bp

insertion/deletion polymorphism (i.e. ACE I/D), which has been shown to account for 47% of

the variance in serum ACE concentration in healthy Caucasian subjects [267]. ACE A11860G

is in near perfect linkage disequilibrium with ACE I/D [145] and appears to be a stronger

predictor of plasma ACE concentration than ACE I/D [146], and is therefore an excellent

candidate for gene association studies. In the current study, our primary aim was to determine

the association of ACE A11860G in mothers, fathers and babies with SGA in a prospective

cohort. Our secondary aim was to determine the association of maternal ACE A11860G with

maternal plasma ACE concentration at 15 weeks’ gestation.

In the current study, our primary aim was to determine the association of ACE A11860G in

mothers, fathers and babies with SGA in the prospective SCOPE study. Since assessing gene-

environment interaction on the risk for common diseases, including pregnancy complications

[174,268], is becoming an increasingly important aspect of genetic association studies, our

secondary aim was to determine whether any association of ACE A11860G with SGA was

affected by previously described environmental risk factors for SGA, including maternal age

[198,199,200,201,202], BMI [202], green leafy vegetable intake [203], socioeconomic status

[204] and smoking [205,206,207]. In addition, since RAS components are sexually dimorphic

in adults [191], we explored our primary and secondary aims in pregnancies bearing female

and male infants separately.

85

6.3 Materials and Methods

Participants

Healthy nulliparous women with singleton pregnancies were prospectively recruited to the

Screening for Pregnancy Endpoints (SCOPE) study between November 2004 and September

2008 in Adelaide, Australia and Auckland, New Zealand [216]. The main aim of SCOPE

study was to develop screening tests to predict preeclampsia, small for gestational age infants,

and spontaneous preterm birth. Overall 3196 women, their partners and babies participated in

the study. The study population for the current genetic study was confined to the 2123

Caucasian parent-infant trios (66%) (Figure I).

Participants were recruited to the SCOPE study prior to 15 weeks’ gestation through hospital

antenatal clinics, obstetricians, general practitioners, community midwives, and self referral in

response to advertisements or recommendations of friends. Women were not eligible if they

were considered at high risk of preeclampsia, small for gestational age babies, or spontaneous

preterm birth because of underlying medical conditions, gynaecological history, three or more

previous miscarriages, or three or more terminations of pregnancy, or who had received

interventions that might modify pregnancy outcome [216].

Women were interviewed and examined by research midwives at 15±1 weeks of gestation.

Maternal demographic and dietary information, including ethnicity, age, height, weight, birth

weight, gestational age at birth, socio-economic index (SEI7) [269], smoking status at 15

weeks’ gestation and pre-pregnancy green leafy vegetable intake (PPGLV), were recorded. In

addition, women’s blood pressure at 15 weeks’ gestation was measured twice consecutively.

Paternal information, including age, birth weight, height and weight, were also recorded.

Newborn parameters, including infant’s gestational age at birth, body length, head

7 The New Zealand socio-economic index of occupational status, a number between 10 and 90. It is a validated measure of the individual

socioeconomic status and derived from the specific occupation of the women. A higher score indicates higher socioeconomic status.

86

circumference, mid arm circumference, birth weight and customised birthweight centile, were

measured and recorded by research midwives usually within 72 hours of birth.

Sample collection

Whole blood was collected into EDTA tubes from women at 15±1 weeks of gestation, from

partners at some time during the woman’s pregnancy and umbilical cord after delivery.

Plasma and buffy coat were separated via centrifugation within 3 hours of collection. Buccal

swabs or saliva samples were collected from partners, who were unwilling to undergo

venepuncture, and babies whose cord blood was not obtained at delivery. The buccal swabs

were applied to Whatman FTA cards (Whatman, USA) immediately following sample

collection and saliva was collected using Oragene kits (DNA genotek, USA).

Pregnancy outcome definitions

SGA was defined as birth weight less than the tenth customised centile, adjusted for maternal

height, booking weight, ethnicity, parity and infant gestation and sex [270]. Uncomplicated

pregnancies were those without any pregnancy complication and with delivery of an

appropriately grown baby at term.

Genotyping assays

Maternal, paternal and neonatal DNA was extracted from buffy coats isolated from peripheral

or cord blood (QiAamp 96 DNA blood kit), Whatman FTA cards or from saliva

(Oragene®DNA kits) following the manufacturers’ instructions. Genotyping was conducted

by the Australian Genome Research Facility (AGRF) using the Sequenom MassARRAY

system. Two quality controls were performed to ensure the accuracy of the genotyping data, 1)

each sample was genotyped for the Amelogenin, a sex-determinant gene [219]; 2) parental

and neonatal genotyping data were checked for a Mendelian pattern of inheritances. Samples

were excluded if an inconsistency between the sex of the sample and the corresponding

87

Amelogenin genotype or/and non-Mendelian pattern of inheritance were observed. In addition,

some samples were excluded due to inadequate blood samples, low quality of DNA or failure

to genotype.

Plasma ACE concentration

Plasma ACE concentration was measured in 451 women, who were randomly selected from

the Australian cohort, using a commercial Enzyme-linked immunosorbent assay (ELISA) kit

(ACE duoset, R & D Systems, Minneapolis, U.S.A). The sensitivity of the assay was 62.5

pg/mL. Optical density was determined using a microplate reader (BioRad, Benchmark) at

450nm and corrected at 570 nm.

Statistics

The chi-square test was used to test the ACE A11860G genotypes for Hardy-Weinberg

equilibrium and to compare the categorical variables (i.e. percentage of smokers, percentage

of female babies and genotype) between SGA and uncomplicated pregnancies. Odds ratios

(OR) were calculated. Student’s t-test was performed to compare continuous variables

between pregnancy outcomes and between ACE A11860G genotypes. One way analysis of

variance (ANOVA) with Dunnett’s posthoc adjustment was used to compare customised birth

weight centiles between subgroups created by stratifying the cohort by maternal ACE

A11860G genotypes and environmental factors, including maternal age, maternal BMI,

maternal SEI, pre-pregnancy green leafy vegetable intake and smoking status at 15 weeks’

gestation. Covariate analsysis was used to adjust for the effect of gestational age on baby

length, birth weight and head circumference. Mann-Whitney test was performed to test the

difference in plasma ACE concentration between pregnancy outcomes and between genotypes.

All data analyses were performed using PASW (SPSS, Chicago) version 17.02. P < 0.05 was

considered statistically significant.

88

6.4 Results

Demographic and clinical characteristics of the participants

Combined, Australian and New Zealand SCOPE

In the combined, Australian and New Zealand SCOPE population, all the newborn/placental

measurements were lower in the SGA pregnancies compared to those in uncomplicated

pregnancies (Table 6.1). In all three cohorts, women who delivered SGA infants had

significantly higher blood pressure at 15 weeks’ gestation but lower birth weight than those

with uncomplicated pregnancies (Table 6.1). The proportions of female babies in the

combined, Australian and New Zealand SCOPE cohorts were similar between SGA and

uncomplicated pregnancies.

Australian SCOPE vs. New Zealand SCOPE

Australian SCOPE women with uncomplicated or SGA pregnancies were 7 years younger

(p<0.001), had higher BMI (2 kg/m2, p<0.001), higher systolic blood pressure (3mmHg,

p<0.001) and an average SEI that was 23 points lower (p<0.001) than New Zealand SCOPE

women. Twenty six percent of Australian SCOPE Caucasian women with uncomplicated or

SGA pregnancies smoked at 15 weeks’ gestation in contrast to 3% in New Zealand SCOPE

Caucasian women. In addition, only 27% of Australian SCOPE women with uncomplicated

or SGA pregnancies had ≥1 serve of green leafy vegetable per day in the 3 months prior to

pregnancy whereas this percentage in New Zealand SCOPE participants was 65%.

Association of ACE A11860G with SGA

Maternal, paternal and neonatal ACE A11860G genotype distributions in uncomplicated and

SGA pregnancies were in Hardy-Weinberg Equilibrium in the combined, Australian and New

Zealand SCOPE pregnancies. No associations of paternal or neonatal ACE A11860G with

89

SGA were found in the combined, Australian and New Zealand SCOPE pregnancies (Table

6.2).

In the combined and Australian SCOPE cohorts, the maternal ACE A11860G GG genotype

was significantly more frequent in SGA pregnancies than in healthy pregnancies and

increased the odds of a SGA pregnancy (OR 1.5, 95% CI 1.1-2.1 for the combined SCOPE

cohort; OR 2.0, 95% CI 1.3-2.3 for the Australian SCOPE) (Table 6.2). In addition, when

pregnancies were stratified by infant sex, maternal ACE A11860G GG genotype was only

associated with SGA in pregnancies bearing females (OR 1.7, 95% CI 1.1-2.6 for the

combined SCOPE cohort and OR 2.8, 95% CI 1.5-5.2 for Australian pregnancies) (Table 6.2).

In the New Zealand SCOPE pregnancies maternal ACE A11860G genotype distribution was

similar between uncomplicated and SGA pregnancies and stratification by infant sex did not

change this.

Association of maternal ACE A11860G with newborn growth parameters

When all Australian SCOPE pregnancies were combined (uncomplicated pregnancies, SGA

and other complications combined) maternal ACE A11860G GG genotype was associated

with a 94 g reduction in birth weight (-3%, p=0.007 adjusted for gestational age) and a 5.6

point reduction in customised birth weight centile (-12%, p=0.016). This association was

specific to pregnancies bearing females (Table 6.3). No such associations were found in New

Zealand SCOPE pregnancies. In the combined SCOPE cohort, the association of maternal

ACE A11860G GG genotype with lower birth weight was still apparent and again was specific

to pregnancies bearing females (Table 6.3).

Interaction between maternal ACE A11860G and environmental factors

To investigate gene-environment interactions with fetal growth, we first examined the

association of various environmental factors with SGA and customised birth weight centile

90

without considering maternal ACE A11860G genotypes and then stratified the population by

maternal ACE A11860G genotypes and assessed whether these associations varied between

genotype groups.

The selection of environmental factors to assess gene-environment interactions was based on

previously published risk factors for SGA, particularly those identified in our previous study

[203]. The environmental factors must also satisfy the criterion that they are significantly

different between the Australian and New Zealand SCOPE pregnancies. The selected

environmental factors were maternal age (age <29 years versus ≥29 years), maternal BMI

(BMI <25kg/m2 versus ≥25kg/m

2), socio-economic index (SEI <34 versus ≥34), pre-

pregnancy green leafy vegetable intake (vegetable intake <1 serve/day versus ≥1 serve/day)

and smoking status at 15 weeks’ gestation (no smoking versus smoking). Since maternal age,

socio-economic index and pre-pregnancy green leafy vegetable intake were strikingly

different between Australian and New Zealand SCOPE women (Table 6.1), the cut off points

for these environmental factors were carefully chosen so that the less frequent subgroup in

either cohort included at least 15 - 25 percent of the population.

In New Zealand SCOPE pregnancies, no interactions between maternal ACE A11860G with

any of the environmental factors were observed (Table 6.4). In Australian SCOPE

pregnancies, there was no interaction between maternal ACE A11860G and maternal age/BMI.

In Australian SCOPE pregnancies, without consideration of ACE A11860G genotypes, SEI

<34 was associated with SGA (OR 2.4, 95% CI 1.1-5.2). When maternal ACE A11860G

genotypes were considered, this association remained in mothers with ACE A11860G GG

genotype (OR 4.9, 95%CI 1.8-13.4) but not in those with ACE A11860G AA/AG genotypes

(OR 2.3, 95%CI 0.9-6.1). In addition, using women with SEI >34 and ACE A11860G AA/AG

genotypes as a referent, SEI <34 was associated with a 12 points reduction in customised

birthweight centiles (p=0.04) in babies delivered by mothers with ACE A11860G GG

91

genotype compared to a non-significant reduction of 6 points (p=0.39) in babies delivered by

mothers with AA/AG genotypes.

In Australian SCOPE pregnancies, irrespective of ACE A11860G genotypes, < 1 serve of

green leafy vegetable/day pre-pregnancy was not associated with SGA and a reduction in

customised birth weight centile. However, when maternal ACE A11860G genotypes were

considered, using mothers with ACE A11860G AA/AG genotypes and ≥1 serve of green leafy

vegetable/day pre-pregnancy as the referent, in those mothers with < 1 serve of green leafy

vegetable/day pre-pregnancy ACE A11860G GG genotype was associated with SGA (OR 3.3,

95% CI 1.6-7.0) and a reduction of 11 points in the mean birthweight centile (p=0.03)

whereas this association was not observed in mothers with ACE A11860G AA/AG genotypes.

We further stratified Australian SCOPE pregnancies by infant sex to investigate whether the

interactions between maternal ACE A11860G, low maternal SEI and low pre-pregnancy green

leafy vegetable intake were modified by fetal sex. In this analysis, in addition to women with

uncomplicated and SGA pregnancies, we also included women with other pregnancy

complications (Figure 6.1) so that we had sufficient sample size for each stratum after

stratification by maternal ACE A11860G genotypes, maternal SEI or pre-pregnancy green

leafy vegetable intake.

The interaction of maternal ACE A11860G with low SEI and low pre-pregnancy green leafy

vegetable intake in association with customised birthweight centile remained in pregnancies

bearing females but not those bearing males (Table 6.5).

Plasma ACE concentration at 15 weeks’ gestation

Women bearing the ACE A11860G GG genotype had higher circulating ACE concentration at

15 weeks’ gestation than those bearing AA or AG genotypes (p<0.001) (Figure 6.2). In

addition, women who delivered SGA infants had higher plasma ACE concentrations at 15

92

weeks’ gestation than women with uncomplicated pregnancies (p=0.034) and this relationship

was specific to pregnancies bearing females (p=0.008) (Figure 6.3).

93

6.5 Discussion

In our combined SCOPE cohort, we have identified a novel association of the maternal ACE

A11860G with SGA. Specifically, women with homozygous ACE A11860G GG had

increased risk of delivering a SGA infant. Consistent with this, in the combined SCOPE

cohort, we also found that babies delivered by women with ACE A11860G GG genotype

weighed less at birth (corrected for gestational age) than those born to women with ACE

A11860G AA or AG genotypes.

ACE A11860G, located in exon 16 of the ACE gene and in near perfect linkage disequilibrium

with ACE I/D [145], has previously been shown to associate with ACE activity in two

independent cohorts of young-onset hypertension patients [147]. In our pregnant cohort,

mothers bearing maternal ACE A11860G GG genotype had higher plasma ACE concentration

at 15 weeks’ gestation than those bearing AA or AG genotypes. In addition, we also observed

that women who later delivered a SGA baby, had higher plasma ACE concentration at this

time than women with uncomplicated pregnancies. These results together support the

observed association of ACE A11860G with SGA.

The mechanism behind the association of maternal ACE A11860G with SGA is yet to be

elucidated. However, ACE I/D, which is in linkage disequilibrium with ACE A11860G [145],

is associated with arterial stiffness [271] and an increase in arterial stiffness has previously

been linked to a significant reduction in birthweight centiles (potentially via diminished

maternal plasma volume expansion and utero-placental blood flow) [272]. Therefore, we

speculate that arterial stiffening in the maternal systemic vasculature may be involved in the

association between maternal ACE A11860G and SGA. That is, women with ACE A11860G

GG genotype may chronically have stiffer arteries than those bearing AA or AG genotypes

and therefore may be more likely to experience a deficit in plasma volume expansion and

consequently deliver a SGA baby. Furthermore, since an increase in arterial stiffness has also

94

been shown to associate with an increased risk for preeclampsia [273], if ACE A11860G is

indeed associated with arterial stiffness as proposed, one would also expect an association

between ACE A11860G and preeclampsia. Indeed, in a recent Romanian cohort, the

combination of maternal and fetal G allele of ACE A11860G is associated with a 3.3 fold

increase in the risk for preeclampsia [144]. We also examined the association in our SCOPE

cohort. Though not significant, there was a trend for ACE A11860G GG genotype to associate

with an increased risk for preeclampsia (data not shown).

Participants in the SCOPE study were recruited from two centres, Adelaide, Australia and

Auckland, New Zealand. The Adelaide participants were recruited at a hospital that serves a

socio-economically disadvantages community. Australian participants were less affluent than

New Zealand participants. Specifically, Australian women on average were younger, had

higher BMI, ate fewer green leafy vegetables prior to pregnancy, had a lower socio-economic

status and were more likely to smoke at 15 weeks’ gestation than New Zealand women. We

divided our SCOPE cohort to Australian and New Zealand cohorts and conducted post-hoc

analyses in each cohort. Interestingly, the associations of maternal ACE A11860G with SGA

and newborn growth parameters previously observed in the combined SCOPE cohort

remained in the Australian SCOPE cohort (the disadvantaged population) but were not seen in

the New Zealand cohort (the affluent population), suggesting gene-environment interactions.

To identify the environmental factor(s), which maternal ACE A11860G potentially interacts

with, we conducted further post-hoc analyses and stratified Australian and New Zealand

cohorts by environmental factors, which have previously been shown to affect risks for

preeclampsia, including maternal age (age <29 years versus ≥29 years)

[198,199,200,201,202], maternal BMI (BMI <25kg/m2 versus ≥25 kg/m

2) [202], maternal SEI

(SEI <34 versus ≥34) [204], pre-pregnancy green leafy vegetable intake (vegetable intake <1

serve/day versus ≥1 serve/day) [203] and smoking status at 15 weeks’ gestation (no smoking

95

versus smoking) [205,206,207]. Maternal SEI and pre-pregnancy green leafy vegetable intake

appeared to be the environmental factors modulating the association between maternal ACE

A11860G and SGA. Specifically, in the Australian cohort, maternal ACE A11860G GG

genotype was only associated with SGA and a reduction in customised birthweight centile

among women with SEI<34 or pre-pregnancy green leafy vegetable intake <1 serve/day.

The interactions between maternal ACE A11860G genotypes and maternal SEI and pre-

pregnancy green leafy vegetable intake are biologically plausible, since these two

environmental factors have previously been shown to associate with vascular stiffness

[274,275], which, as proposed earlier, may also be associated with maternal ACE A11860G.

Furthermore, these observed gene-environment interactions may suggest that the adverse

effects associated with maternal ACE A11860G GG genotype on its own are subtle and can

only place women at risk for SGA if superimposed on adverse effects associated with

maternal SEI<34 and pre-pregnancy green leafy vegetable intake <1 serve/day. Previously

published genetic association studies for pregnancy complications have proved difficult to

replicate. The gene-environment interactions observed in the current study may shed some

light on this and suggest that conflicting results in the literature may be, in part, due to failure

to appreciate interactions between genetic polymorphisms and environmental factors.

Accumulating evidence suggests that female and male fetuses institute different mechanisms

to cope with an adverse environment [188]. In pregnancies complicated by maternal asthma

and preeclampsia, a significant reduction in birth weight is observed in female but not males

fetuses [236,276]. Data from the Medical Birth Registry of Norway from 1967 to 1998 reveal

that among preterm babies the proportion of male fetuses is significantly higher than that of

female fetuses [277]. The differences in fetal growth and survival between female and male

fetuses are thought to be attributable to sex specific placental function [188]. In a recent

microarray study, sex specific differences in placental global gene expression were observed

96

[187]. Interestingly, the differences are not limited to genes linked to the X and Y

chromosomes but also autosomal genes, which are related to immune pathways [187]. In

addition, in pregnancies complicated by maternal asthma, global gene expression [278],

miroRNA expression [188], proteomic profile [279] and structure [280] vary between female

and male placentas.

In the current study, when the combined SCOPE and Australian cohorts were stratified by the

sex of infants, the associations between maternal ACE A11860G GG genotype and an

increased risk for SGA and reduction in infant size were only apparent in pregnancies bearing

females, which may suggest that only the female fetus responds to the adverse maternal

environments associated with maternal ACE A11860G GG genotype. This is consistent with

the aforementioned studies that show that female and male fetuses utilize different strategies

to cope with the same adverse maternal environment [188]. Specifically, female fetuses

reduce their growth trajectory to adapt to an adverse environment while males maintain their

growth rate, a strategy that puts them at greater risk of stillbirth and pre-term delivery [188].

The strength of this study is its large multicentre prospective design. In addition, the outcome

data of these cases were reviewed by highly skilled SCOPE clinicians to ensure accurate

diagnoses. The weakness of the study is the missing genotypes of some participants, which

reduced our sample size and may potentially introduce bias into our results. However, there

are no systematic reasons for missing genotypes identified. In addition, in order to strengthen

the reliability of our results, independent cohorts are required to replicate the current study.

In summary, we have shown that maternal ACE A11860G is associated with SGA. Of great

interest is the finding that association was influenced by modifiable environmental factors

(maternal SEI and pre-pregnancy green leafy vegetable intake) as well as fetal sex, suggesting

an ACE A11860G-environment-fetal sex interaction.

97

Figure 6.1 Flow chart of participant recruitment. AUS: Australia, NZ: New Zealand.




SGA n=216 (AUS: n=109; NZ: n=107)







No specimen, unable to genotype or inconsistent parent-infant genotypes: 206 women, 486 partners, 629 infants

Uncomplicated n=1185 (AUS: n=427; NZ: n=758)

Other complications n=720 (AUS: n=399; NZ: n=321)

Final population for genetic association analysis 1917 women, 1637 partners, 1494 infants

Uncomplicated AUS: 382 women, 337 partners, 308 infants NZ: 682 women, 584 partners, 580 infants

SGA AUS: 101 women, 97 partners, 71 infants

NZ: 102 women, 82 partners, 74 infants

Other complications AUS: 355 women, 306 partners, 230 infants NZ: 295 women, 231 partners, 231 infants

98

A

0

100

200

300

400

500

AA/AG GG

Mate

rnal p

lasm

a A

CE

(ug/L

)

B

0

100

200

300

400

500

AA/AG GG AA/AG GG

Female babies Male babies

Mate

rnal p

lasm

a A

CE

(ug/L

)

Figure 6.2 The association of maternal ACE A11860G with maternal plasma ACE

concentration at 15 weeks’ gestation in uncomplicated and SGA pregnancies. (A) All mothers

in whom plasma ACE concentration at 15 weeks’ gestation was measured irrespective of

infant sex, Mann-Whitney U test, p<0.001. NAA/AG=183, NGG=57 (B) pregnancies stratified by

the sex of babies. For pregnancies bearing females, Mann-Whitney U test, p=0.012

NAA/AG=87, NGG=29; for pregnancies bearing males, Mann-Whitney U test, p=0.007

NAA/AG=96, NGG=28.

P <0.001

P = 0.012

P = 0.007

99

A

0

100

200

300

400

500

Uncomplicated SGA

Mate

rnal p

lasm

a A

CE

(ug/L

)

B

0

100

200

300

400

500

Uncomplicated SGA Uncomplicated SGA


Mate

rnal p

lasm

a A

CE

(ug/L

)

Figure 6.3 Maternal plasma ACE concentration at 15 weeks’ gestation in uncomplicated and

SGA pregnancies. (A) All mothers in whom plasma ACE at 15 weeks’ gestation was

measured irrespective of infant sex, Mann-Whitney U test, p=0.034. Nuncomplicated=190,

NSGA=77 (B) pregnancies stratified by the sex of babies. For pregnancies bearing females,

Mann-Whitney U test, p=0.008. Nuncomplicated=96, NSGA=33; for pregnancies bearing males,

Mann-Whitney U test, p=0.690. Nuncomplicated=94, NSGA=44.

P = 0.034

P = 0.008

P = 0.69

100

Table 6.1 Demographic characteristics of the study population.

Combined SCOPE Australian SCOPE New Zealand SCOPE AUS vs. NZ

Uncomplicated SGA

Uncomplicated SGA

Uncomplicated SGA

Uncomplicated SGA

Maternal characteristics n=1185 n=216 P n=427 n=109 P n=758 n=107 P P P

Age (yrs) at 15 wks 28.2 (5.6) 28.5 (6.2) 0.5 23.6 (5.0) 24.3 (5.3) 0.1 30.8 (4.1) 32.7 (3.8) <0.001 <0.001 <0.001

BMI (kg/m2) at 15 wks 24.9 (4.5) 26.1 (5.5) 0.003 26.0 (5.6) 27.5 (6.2) 0.01 24.3 (3.7) 24.7 (4.3) 0.3 <0.001 <0.001

sBP (mmHg) at 15 wks 106.2 (9.9) 109.5 (11.1) <0.001 107.9 (8.9) 111.6 (11.2) 0.002 105.3 (10.3) 107.5 (10.8) 0.05 <0.001 0.006

dBP (mmHg) at 15 wks 63.3 (7.6) 66.0 (8.9) <0.001 63.5 (7.5) 66.0 (8.9) 0.007 63.2 (7.7) 66.1 (8.9) 0.002 0.5 1.0

Socioeconomic index 41.9 (16.7) 38.1 (16.7) 0.002 27.9 (10.9) 25.5 (7.5) 0.007 49.8 (14.0) 51.0 (13.2) 0.4 <0.001 <0.001

Pre-pregnancy high green leafy vegetable intakea (%) 615 (51.9%) 92 (42.6%) 0.012 120 (28.1%) 25 (22.9%) 0.3 495 (65.3%) 67 (62.6%) 0.6 <0.001 <0.001

Smoking (%) at 15wks 111 (9.4%) 50 (23.1%) <0.001 90 (21.1%) 48 (44.0%) <0.001 21 (2.8%) 2 (1.9%) 1.0 <0.001 <0.001

Gestational age at birth (wks)1 39.9 (1.9) 39.7 (2.1) 0.4 39.5 (1.9) 39.4 (2.3) 0.6 40.0 (1.8) 40.1 (1.7) 0.9 <0.001 0.02

Maternal birth weight (g)2 3334.6 (529.7) 3166.6 (527.3) <0.001 3287.3 (549.4) 3136.4 (544.4) 0.01 3360.8 (517.0) 3196.8 (510.5) 0.003 0.02 0.4


Age (yrs) 30.7 (6.3) 31.1 (6.7) 0.5 26.4 (6.1) 27.6 (6.3) 0.054 33.2 (4.9) 34.6 (5.0) 0.005 <0.001 <0.001

Height (cm)3 179.6 (6.7) 177.6 (6.9) <0.001 178.5 (6.7) 176.3 (7.2) 0.002 180.3 (6.7) 179.0 (6.4) 0.06 <0.001 0.005

BMI (kg/m2)3 26.6 (4.0) 27.2 (4.6) 0.07 26.9 (5.0) 27.3 (5.0) 0.4 26.4 (3.3) 27.1 (4.1) 0.1 0.07 0.7

Paternal birth weight (g)4 3487.8 (571.4) 3313.7 (520.8) <0.001 3461.9 (593.4) 3346.9 (558.1) 0.09 3501.6 (559.2) 3283.2 (484.9) <0.001 0.2 0.4


Gestational age at birth (days) 280.7 (8.1) 271.6 (24.5) <0.001 280.6 (8.0) 271.9 (23.2) <0.001 280.7 (8.1) 271.4 (25.9) <0.001 0.8 0.9

Body lengthb (cm) 51.0 (2.2) 47.1 (4.5) <0.001 50.0 (1.8) 46.2 (3.9) <0.001 51.5 (2.2) 48.0 (4.8) <0.001 <0.001 0.003

Head circumferenceb (mm) 35.2 (1.3) 32.9 (2.5) <0.001 34.9 (1.3) 32.8 (2.3) <0.001 35.3 (1.4) 32.9 (2.8) <0.001 0.001 0.7

Mid arm circumferenceb (mm) 11.0 (0.9) 9.4 (1.1) <0.001 11.0 (0.9) 9.2 (1.2) <0.001 11.1 (0.9) 9.5 (1.0) <0.001 0.2 0.2

Birth weighta (g) 3590.9 (393.8) 2587.0 (559.8) <0.001 3575.3 (390.2) 2553.6 (536.1) <0.001 3599.7 (395.8) 2620.9 (583.4) <0.001 0.3 0.4

Customised birthweight centile 53.7 (25.0) 4.6 (2.9) <0.001 53.9 (24.9) 4.0 (2.8) <0.001 53.6 (25.1) 5.1 (2.9) <0.001 0.9 0.004

Female babies (%) 584 (49.3%) 109 (50.5%) 0.8 217 (50.8%) 60 (55.0%) 0.4 367 (48.4%) 49 (45.8%) 0.7 0.4 0.2

101

Data are presented as mean (SD) or n (%). sBP: systolic blood pressure, the second measurement; dBP: diastolic blood pressure, the second measurement; 15 wks: 15 weeks’ gestation;

AUS: Australia; NZ: New Zealand. a ≥1 serve of green leafy vegetable/day,

badjusted for gestational age at birth.

1numbers for women’s gestational age at birth were 1166,208,419,105,747

and 103, for each group respectively, 2numbers for women’s birth weight were 1153,208,411,104,742 and 104, for each group respectively,

3numbers for partner’s height or BMI were

1157,210,422,108,735 and 102, for each group respectively, 4numbers for partner’s birthweight were 1107,197,385,94,722 and 103, for each group respectively. Bold italics indicates

significant difference

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Table 6.2 Maternal, paternal and neonatal ACE A11860G genotype distribution in uncomplicated pregnancies and SGA pregnancies, stratified by fetal sex and cohorts.

Combined SCOPE Australian SCOPE New Zealand SCOPE

All babies Uncomplicated SGA OR (95% CI) Uncomplicated SGA OR (95% CI) Uncomplicated SGA OR (95% CI)

Maternal ACE A11860G n=1064 n=203

n=382 n=101

n=682 n=102

AA/AG 778 (73.1) 131 (64.5) Ref 295 (77.2) 63 (62.4) Ref 483 (70.8) 68 (66.7) Ref

GG 286 (26.9) 72 (35.5) 1.5(1.1-2.1) 87 (22.8) 38 (37.6) 2.0(1.3-3.3) 199 (29.2) 34 (33.3) 1.2(0.8-1.9)

Paternal ACE A11860G n=921 n=179

n=337 n=97

n=584 n=82

AA/AG 654 (71.0) 128 (71.5) Ref 237 (70.3) 72 (74.2) Ref 417 (71.4) 56 (68.3) Ref

GG 267 (29.0) 51 (28.5) 1.0(0.7-1.4) 100 (29.7) 25 (25.8) 0.8(0.5-1.4) 167 (28.6) 26(31.7) 1.2(0.7-1.9)

Neonatal ACE A11860G n=888 n=145

n=308 n=71

n=580 n=74

AA/AG 625 (70.4) 100 (69.0) Ref 224 (72.7) 48 (67.6) Ref 401 (69.1) 52 (70.3) Ref

GG 263 (29.6) 45 (31.0) 1.1(0.7-1.6) 84 (27.3) 23 (32.4) 1.3(0.7-2.2) 179 (30.9) 22 (29.7) 1.0(0.6-1.6)

Female babies Maternal ACE A11860G n=524 n=102

n=194 n=56

n=330 n=46

AA/AG 386 (73.7) 64 (62.7) Ref 155 (79.9) 33 (58.9) Ref 231 (70.0) 31 (67.4) Ref

GG 138 (26.3) 38(37.3) 1.7(1.1-2.6) 39 (20.1) 23 (41.1) 2.8(1.5-5.2) 99 (30.0) 15 (32.6) 1.1(0.6-2.2)


n=177 n=56

n=275 n=40

AA/AG 323 (71.5) 70 (72.9) Ref 124 (70.1) 46 (82.1) Ref 199 (72.4) 24 (60.0) Ref

GG 129 (28.5) 26 (27.1) 0.9(0.6-1.5) 53 (29.9) 10 (17.9) 0.5(0.2-1.1) 76 (27.6) 16 (40.0) 1.7(0.9-3.4)


n=158 n=46

n=290 n=30

AA/AG 321 (71.7) 51 (67.1) Ref 117 (74.1) 31 (67.4) Ref 204 (70.3) 20 (66.7) Ref

GG 127 (28.3) 25 (32.9) 1.2(0.7-2.1) 41 (25.9) 15 (32.6) 1.3(0.7-2.8) 86 (29.7) 10 (33.3) 1.2(0.5-2.6)

Male babies

Maternal ACE A11860G n=540 n=101

n=188 n=45

n=352 n=56

AA/AG 392 (72.6) 67 (66.3) Ref 140 (74.5) 30 (66.7) Ref 252 (71.6) 37 (66.1) Ref

GG 148 (27.4) 34 (33.7) 1.3(0.9-2.1) 48 (25.5) 15 (33.3) 1.5(0.7-3.0) 100 (28.4) 19 (33.9) 1.3(0.7-2.3)


n=160 n=41

n=309 n=42

AA/AG 331 (70.6) 58 (69.9) Ref 113 (70.6) 26 (63.4) Ref 218 (70.6) 32 (76.2) Ref

GG 138 (29.4) 25 (30.1) 1.0(0.6-1.7) 47 (29.4) 15 (36.6) 1.4(0.7-2.8) 91 (29.4) 10 (23.8) 0.7(0.4-1.6)


n=150 n=25

n=290 n=44

AA/AG 304 (69.1) 49 (71.0) Ref 107 (71.3) 17 (68.0) Ref 197 (67.9) 32 (72.7) Ref

GG 136 (30.9) 20 (29.0) 0.9(0.5-1.6) 43 (28.7) 8 (32.0) 1.2(0.5-2.9) 92 (32.1) 12 (27.3) 0.8(0.4-1.6)

The data were analysed in the whole cohort irrespective of infant sex, and then in pregnancies bearing females and those bearing males, separately. Data are presented as n (%). AUS:

Australia; NZ: New Zealand; Ref: Referent. Bold italics indicates significant difference.

103

Table 6.3 The association of maternal ACE A11860G with newborn growth parameters, stratified by fetal sex and cohorts.

Combined maternal ACE A11860G Australian maternal ACE A11860G New Zealand maternal ACE A11860G

AA/AG GG p AA/AG GG p AA/AG GG p All babies

n=1371 n=529

n=616 n=219

n=755 n=310 Body lengtha (cm) 50.1 (3.2) 49.9 (3.2) 0.2 49.1 (3.5) 48.9 (3.0) 0.4 50.9 (2.8) 50.6 (3.2) 0.08

n=1383 n=532

n=617 n=219

n=766 n=313

Birth weighta (g) 3394.4 (606.6) 3344.4 (584.2) 0.02 3363.4 (643.7) 3269.3 (626.1) 0.007 3418.6 (574.4) 3398.8 (545.8) 0.5

n=1382 n=531

n=617 n=219

n=765 n=312

Customised birthweight centile 47.6 (28.1) 45.5 (29.3) 0.2 47.8 (28.7) 42.3 (30.4) 0.02 47.4 (27.6) 47.7 (28.3) 0.9

Female babies

n=685 n=267

n=323 n=110

n=362 n=157

Body lengtha (cm) 49.7 (2.9) 49.4 (3.3) 0.049 48.9 (3.0) 48.4 (2.7) 0.04 50.5 (2.6) 50.2 (3.4) 0.1

n=692 n=269

n=323 n=110

n=369 n=159

Birth weighta (g) 3355.7 (588.9) 3276.4 (557.4) 0.007 3334.2 (602.1) 3167.2 (597.1) 0.001 3372.5 (577.7) 3356.7 (507.0) 0.7

n=691 n=268

n=323 n=110

n=368 n=158 Customised birthweight centile 47.4 (28.1) 44.5 (28.9) 0.2 48.1 (28.7) 38.9 (29.5) 0.004 46.8 (27.6) 48.3 (28.0) 0.6

Male babies

n=686 n=262

n=239 n=109

n=393 n=153

Body lengtha (cm) 50.4 (3.6) 50.4 (3.1) 0.9 49.2 (3.9) 49.4 (3.1) 0.5 51.2 (3.0) 51.0 (3.0) 0.5

n=691 n=263

n=294 n=109

n=397 n=154

Birth weighta (g) 3433.1 (622.0) 3413.9 (602.6) 0.5 3395.3 (686.8) 3372.6 (631.1) 0.7 3460.3 (568.2) 3444.0 (582.7) 0.7

n=691 n=263

n=294 n=109

n=397 n=154

Customised birthweight centile 47.8 (28.1) 46.5 (29.7) 0.2 47.6 (28.8) 45.7 (31.0) 0.6 48.0 (27.6) 47.1 (28.8) 0.8

The data were analysed in the whole cohort irrespective of infant sex, and then in pregnancies bearing females and those bearing males, separately. Data are presented as mean (SD). a

adjusted for gestational age at birth. Bold italics indicates significant difference.

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Table 6.4 The association of maternal ACE A11860G with SGA and customised birthweight centile, stratified by fetal sex and cohorts.

Australian SCOPE New Zealand SCOPE


genotype Maternal SEI n SGA OR (95% CI)

Customised

birthweight centile p n SGA OR (95% CI)

Customised

birthweight centile p

Total samples SEI ≥ 34 74 8 (10.8) Ref 47.3 (27.1) Ref 681 91 (13.4) Ref 46.5 (28.5) Ref

SEI < 34 409 93 (22.7) 2.4 (1.1-5.2) 42.4 (30.3) 0.2 103 11 (10.7) 0.8 (0.4-1.5) 48.4 (28.0) 0.5

AA/AG SEI ≥ 34 54 5 (9.3) Ref 49.8 (26.7) Ref 483 58 (12.0) Ref 47.0 (28.0) Ref

AA/AG SEI < 34 304 58 (19.1) 2.3 (0.9-6.1) 44.0 (29.4) 0.4 68 10 (14.7) 1.3 (0.6-2.6) 45.6 (28.2) 1.0

GG SEI ≥ 34 20 3 (15.0) 1.7 (0.4-8.0) 40.3 (27.8) 0.5 197 33 (16.8) 1.5 (0.9-2.3) 45.4 (29.6) 0.9

GG SEI < 34 105 35 (33.3) 4.9 (1.8-13.4) 37.5 (32.4) 0.04 36 1 (2.8) 0.2 (0.03-1.6) 53.7 (26.8) 0.4


genotype


vegetable intake

Total samples ≥ 1 serve/day 127 20 (15.7) Ref 46.4 (29.5) Ref 506 62 (12.3) Ref 47.5 (28.1) Ref

< 1 serve/day 356 81 (22.8) 1.6 (0.9-2.7) 41.9 (29.9) 0.2 278 40 (14.4) 1.2 (0.8-1.8) 45.5 (28.9) 0.4

AA/AG ≥ 1 serve/day 94 12 (12.8) Ref 48.1 (28.9) Ref 361 40 (11.1) Ref 47.4 (27.6) Ref

AA/AG < 1 serve/day 264 51 (19.3) 1.6 (0.8-3.2) 43.8 (29.1) 0.5 190 28 (14.7) 1.4 (0.8-2.3) 45.8 (28.9) 0.9

GG ≥ 1 serve/day 33 8 (24.2) 2.2 (0.8-5.9) 41.5 (31.0) 0.6 145 22 (15.2) 1.4 (0.8-2.5) 47.6 (29.5) 1

GG < 1 serve/day 92 30 (33.3) 3.3 (1.6-7.0) 36.7 (31.9) 0.03 88 12 (13.6) 1.3 (0.6-2.5) 45.1 (29.0) 0.9

The data are presented as mean (SD) or n (%). SEI: socioeconomic index. Ref: Referent. Bold italics indicates significant difference.

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Table 6.5 The association of maternal ACE A11860G with customised birthweight centile in the Australian SCOPE, stratified by maternal SEI, pre-pregnancy green leafy vegetable intake

and fetal sex.


Maternal ACE A11860G genotype Maternal SEI n Customised birthweight centile p n Customised birthweight centile p

Total samples SEI ≥ 34 81 50.0 (28.3) Ref 73 51.1 (27.9) Ref

SEI < 34 352 44.8 (29.3) 0.2 330 46.2 (29.6) 0.2

AA/AG SEI ≥ 34 63 52.9 (27.0) Ref 49 50.9 (28.2) Ref

AA/AG SEI < 34 260 46.9 (29.1) 0.3 245 46.9 (28.9) 0.7

GG SEI ≥ 34 18 39.8 (31.4) 0.2 24 51.4 (27.8) 1

GG SEI < 34 92 38.8 (29.3) 0.008 85 44.1 (31.8) 0.4

Maternal ACE A11860G genotype Pre-pregnancy green leafy vegetable intake

Total samples ≥ 1 serve/day 109 47.4 (29.3) Ref 103 49.2 (29.5) Ref

< 1 serve/day 324 45.3 (29.2) 0.5 300 46.3 (29.3) 0.4

AA/AG ≥ 1 serve/day 74 49.7 (28.8) Ref 75 49.7 (29.8) Ref

AA/AG < 1 serve/day 249 47.6 (28.7) 0.9 219 46.8 (28.4) 0.8

GG ≥ 1 serve/day 35 42.5 (30.1) 0.5 28 47.9 (29.2) 1.0

GG < 1 serve/day 75 37.3 (29.3) 0.03 81 44.9 (31.7) 0.6

The data are presented as mean (SD). SEI: socioeconomic index. Ref: Referent. Bold italics indicates significant difference.

106

CHAPTER 7

The association of AGT2R polymorphisms with preeclampsia

and uterine artery bilateral notching is modulated by maternal

BMI

107

7.1 Abstract

Aims: The study was aimed to determine the association of AGT1R and AGT2R

polymorphisms with preeclampsia and determine whether the associations are

affected by environmental factors and fetal sex.

Methods: 3234 healthy nulliparous women, their partners and babies were recruited

prospectively to the SCOPE study in Adelaide and Auckland. Data analyses were

confined to 2121 Caucasian parent-infant trios, among which 123 were preeclamptic

pregnancies. 1185 uncomplicated pregnancies served as controls. DNA was extracted

from buffy coats and genotyped by utilizing the Sequenom MassARRAY system.

Doppler sonography on the uterine arteries was performed at 20 weeks’ gestation.

Results: When the cohort was stratified by maternal BMI, in women with

BMI≥25kg/m2, the AGT2R C4599A AA genotype in mothers and neonates was

associated with an increased risk for preeclampsia compared with the CC genotype

[OR 2.1 (95% CI 1.0-4.2) and OR 3.0 (95% CI 1.4-6.5), respectively]. In the same

subset of women, paternal AGT2R C4599A A allele was associated with an increased

risk for preeclampsia and uterine artery bilateral notching at 20 weeks’ gestation

compared with the C allele [OR 1.9 (95% CI 1.1-3.2) and OR 2.1 (95% CI 1.3-3.4),

respectively].

Conclusion: AGT2R C4599A in mothers, fathers and babies was associated with

preeclampsia and this association was only apparent pregnancies in which the women

had a BMI≥25kg/m2, suggesting a gene-environment interaction.

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7.2 Introduction:

Preeclampsia affects 3-8% of pregnancies in Australia and is a major cause of

maternal mortality in developed countries [75]. To date, the exact cause of

preeclampsia is still unknown. Since hypertension is both a risk factor and a symptom

of preeclampsia, the renin angiotensin system (RAS), which plays an important role in

blood pressure regulation, electrolyte and volume homeostasis [281], has been studied

intensively for its contribution to the development of the disorder.

Third trimester preeclamptic women are reported to have reduced plasma renin

activity [30], increased serum angiotensin converting enzyme (ACE) activity [30],

reduced angiotensin II (ANG II) concentration [30] and increased responsiveness to

ANG II [40,89] compared to women with normal pregnancy. The aberrant RAS

levels/activities observed in preeclamptic pregnancies may indicate the involvement

of RAS in the pathogenesis of preeclampsia. Therefore, genetic polymorphisms in the

RAS components, which modulate RAS levels/activities, may potentially predispose

woman to preeclampsia.

Over the past decade, several polymorphisms in the AGT1R and AGT2R genes have

been identified. AGT1R A1166C (rs5186) is located in the 3’ UTR of AGT1R on the

chromosome 3. The AGT1RA1166C CC genotype is associated with greater ANG II

responsiveness [156] and increases risk for coronary artery disease and myocardial

infarction [157] compared with the AA genotype. AGT2R C4599A (rs11091046),

AGT2R A1675G (rs1403543) and AGT2R T1134C (rs12710567) are located in the 3’

UTR of exon 3, intron 1 and the promoter region of the AGT2R gene on the X

chromosome, respectively. The AGT2R A1675G G allele is associated with higher

AGT2R expression compared with the A allele [163]. The functional effects of

109

AGT2R C4599A and AGT2R T1334C on AGT2R have not been investigated

previously. AGT2R A1675G and AGT2R C4599A have been shown to be in linkage

disequilibrium in a Japanese population [160]. In a Chinese cohort, the AGT2R

T1334C C allele is associated with an increased risk for essential hypertension

compared with the T allele [165].

In the current study, our primary aim was to determine if the aforementioned AGT1R

and AGT2R polymorphisms in mothers, fathers and babies were associated with

preeclampsia. Since assessing gene-environment interactions is becoming an

increasingly important aspect of genetic association studies [174,268], our secondary

aim was to determine whether the association of AGT1R and AGT2R polymorphisms

with preeclampsia is affected by risk factors for preeclampsia, including maternal age

[208,209], BMI [210], green leafy vegetable intake [211], socioeconomic status [212]

and smoking [213]. In addition, since RAS components are sexually dimorphic in

adults [191], we explored our primary and secondary aims in pregnancies bearing

female and male infants separately.

110

7.3 Materials and Methods:

Ethics approval

In Australia, ethical approval was obtained from the Central Northern Adelaide

Health Service Ethics of Human Research Committee (study number: REC

1714/5/2008). In New Zealand, ethical approval was given by the Northern Region

Ethics Committee (study number: AKX/02/00/364). All participants provided written

informed consent. Australian clinical trial registry number: ACTRN 12607000551493

Participants

The participants were healthy nulliparous women with singleton pregnancies recruited

to the Screening for Pregnancy Endpoints (SCOPE) study between November 2004

and September 2008 in Adelaide, Australia and Auckland, New Zealand [216].

SCOPE is a prospective, multicentre cohort study with the main aim of developing

screening tests to predict preeclampsia, small for gestational age infants and

spontaneous preterm birth. Overall 3196 women, their partners and babies were

recruited into the study. The population for this genetic study was confined to the

2121 Caucasian parent-infant trios (66%) (Figure 7.1).

Women were recruited to the SCOPE study by 15 weeks’ gestation through hospital

antenatal clinics, obstetricians, general practitioners, community midwives and self

referral in response to advertisements or recommendations of friends. Women were

excluded if they were judged to be at high risk of preeclampsia, small for gestational

age babies or spontaneous preterm birth because of underlying medical conditions,

gynaecological history, three or more previous miscarriages or three or more

111

terminations of pregnancy or if they had received interventions that might modify

pregnancy outcome [216].

Participants were interviewed and examined by a research midwife at 15±1 weeks of

gestation. Maternal demographic and dietary information was collected, including

ethnicity, age, height, weight, birth weight, gestational age at birth, socio-economic

index (SEI8)[217], smoking status at 15 weeks’ gestation and pre-pregnancy green

leafy vegetable intake. Two consecutive manual blood pressure measurements were

recorded. Paternal information, including age, birth weight, height and weight, were

also recorded. Newborn measurements were recorded by research midwives usually

within 72 hours of birth. The recorded parameters included infant’s gestational age at

birth, body length, head circumference, mid arm circumference, birth weight and

customised birthweight centile. Ultrasound and Doppler studies of the umbilical and

uterine arteries were performed at 20 weeks’ gestation [218]. Bilateral notching is

defined as the presence of early diastolic notching in the waveform of both uterine

arteries [282].

Sample collection

Whole blood was collected in EDTA tubes from women at 15 ±1 weeks of gestation,

from partners at some time during the woman’s pregnancy and umbilical cord after

delivery. Blood samples were centrifuged and plasma and buffy coat separated and

stored within 3 hours of collection. Buccal swabs or saliva samples were collected

from partners who were unwilling to undergo venepuncture and babies whose cord

blood was not obtained at delivery. The buccal swabs were applied to Whatman FTA

8 The New Zealand socio-economic index of occupational status, a number between 10 and 90 and is an

occupationally derived indicator of socio-economic status. It is a validated measure of an individual’s

socioeconomic status and a higher score indicates higher socio-economic status.

112

cards (Whatman, USA) immediately following sample collection and saliva was

collected using Oragene kits (DNA genotek, USA).

Pregnancy outcome definitions

Preeclampsia was defined as systolic blood pressure ≥140 mm Hg or diastolic blood

pressure ≥90 mm Hg, or both, on at least two occasions four hours apart after 20

weeks’ gestation but before the onset of labour or postpartum, with either proteinuria

(24 hour urinary protein >300mg or spot urine protein: creatinine ratio >30mg/mmol

creatinine or urine dipstick protein >++) or any multisystem complication of

preeclampsia [283].

Uncomplicated pregnancies were those without any pregnancy complication and with

delivery of an appropriately grown baby at term.

Genotyping assays

DNA was extracted from buffy coats isolated from peripheral or cord blood (QiAamp

96 DNA blood kit), Whatman FTA cards or from saliva (Oragene®DNA kits)

following the manufacturers’ instructions. Genotyping was performed by the

Australian Genome Research Facility (AGRF) utilizing the Sequenom MassARRAY

system. Two quality control procedures were in place to ensure the accuracy of

genotyping data: 1) Each sample was genotyped for Amelogenin to assess the

consistency between the sex of samples and the corresponding Amelogenin genotype

[219]. 2) Parental and neonatal genotyping data were checked for a Mendelian pattern

of inheritance. The samples with inconsistent results in either step were excluded from

the analyses. In addition, some samples were excluded due to inadequate blood

113

samples, low quality of DNA or failure to genotype. The sample sizes for the

genotyping data are shown in the results tables.

Statistics

Chi-square test was used to test the genotypes at each polymorphic locus for Hardy-

Weinberg Equilibrium (HWE). Independent samples t test (for continuous variables)

and chi-square (for categorical variables) were used to compare characteristics

between uncomplicated pregnancies and preeclampsia. The association of

polymorphisms with preeclampsia and uterine artery bilateral notching was assessed

by using logistic regression and odds ratios (OR) were generated. All data analyses

were performed using PASW (SPSS, Chicago) version 17.02. P<0.05 was considered

statistically significant.

114

7.4 Results:

Study population

Of the 3234 recruited women, 1113 (34%) women were excluded due to one of the

reasons shown in figure 7.1. The final analyses were conducted on 2121 Caucasian

women, consisting of 1185 (55.9%) women with uncomplicated pregnancies, 123

(5.8%) preeclamptic women and 813 (38.3%) women with other complications.

For the 2121 Caucasian parent-infant trios, genotype data of up to 199 (9.4%) women,

470 (22.2%) partners and 578 (27.3%) infants could not be analysed for one of the

following reasons: non availability of samples, genotyping failure or Mendelian

inconsistencies in parent-infant genotypes. The available genotype data of each

polymorphism for uncomplicated and preeclamptic pregnancies are shown in table 7.2.

Characteristics of the population

Women who later developed preeclampsia were on average younger, heavier, had

higher sBP and dBP at 15 weeks’ gestation, were less likely to consume ≥1 serve/day

of fruit or green vegetables prior to pregnancy and they themselves weighed less at

birth than the women with uncomplicated pregnancies (Table 7.1). Partners who

fathered a preeclamptic pregnancy on average were younger and heavier than those

with uncomplicated pregnancies. Infants born to preeclamptic pregnancies were

smaller (adjusted for gestational age where appropriate) in all neonatal measures than

those born to uncomplicated pregnancies (Table 7.1). In addition, there was no

difference in sex ratio between preeclampsia and uncomplicated pregnancy groups

(Table 7.1).

115

The association of polymorphisms with preeclampsia and bilateral notching at 20

weeks’ gestation

The analyses for the association of polymorphisms with preeclampsia were performed

comparing the uncomplicated and preeclampsia groups (Figure 7.1). The association

of polymorphisms with uterine artery bilateral notching at 20 weeks’ gestation were

analysed in uncomplicated, preeclampsia and other complications group (Figure 7.1).

For subgroup analyses, the cohort were stratified by environmental factors, including

maternal age (age <29 years versus ≥29 years), maternal BMI (BMI <25kg/m2 versus

≥25kg/m2), SEI (SEI <34 versus ≥34), pre-pregnancy green leafy vegetable intake

(vegetable intake <1 serve/day versus ≥1 serve/day) and smoking status at 15 weeks’

gestation (no smoking versus smoking).

Since AGT2R is on the X chromosome, partners and male neonates only have one

allele of the AGT2R polymorphisms. Accordingly, analyses on partners were

performed in the fashion of alleles. However, for analyses on neonates, to avoid a

reduction in sample size, we did not split the female and male neonates and the

neonatal polymorphism data as a whole were analysed in the fashion of genotypes.

AGT1R A1166C and AGT2R T1334C

Since the frequency of maternal and neonatal AGT2R T1334C CC genotype was less

than 3%, the CC and CT genotype were combined. AGT1R A1166C and AGT2R

T1334C were not associated with preeclampsia nor with uterine artery bilateral

notching at 20 weeks’ gestation (Table 7.2).

116

AGT2R C4599A

AGT2R C4599A in mothers, partners and neonates was not associated with

preeclampsia nor with uterine artery bilateral notching at 20 weeks’ gestation (Table

7.2). However, when the cohort was stratified by maternal BMI using 25kg/m2 as the

cut-off point, among women with BMI≥25kg/m2, maternal AGT2R C4599A AA

genotype and paternal AGT2R C4599A A allele were associated with an increased risk

for preeclampsia with OR 2.1 (95% CI 1.0-4.2) and OR 1.9 (95% CI 1.1-3.2),

respectively (Table 7.3). In neonates, AGT2R C4599A CA and AA genotype both

increased the risk for preeclampsia in women with BMI ≥25kg/m2

with OR 3.5 (95%

CI 1.6-7.9) and OR 3.0 (95% CI 1.4-6.5), respectively (Table 7.3). In addition, the

paternal AGT2R C4599A A allele was also associated with an increased risk for

uterine artery bilateral notching at 20 weeks’ gestation [OR 2.1 (95% CI 1.3-3.4)]

(Table 7.3).

AGT2R A1675G

AGT2R A1675G was not associated with preeclampsia nor with uterine artery bilateral

notching at 20 weeks’ gestation (Table 7.2). When the cohort was stratified by

maternal BMI, among women with BMI≥25kg/m2, neonatal AGT2R A1675G AG

genotype was associated with an increased risk for preeclampsia with OR 2.5 (95% CI

1.2-5.4). There was a trend for maternal GG genotype, paternal G allele and neonatal

GG genotype of AGT2R A1675G to associate with an increased risk for preeclampsia

(Table 7.4). In addition, among women with BMI≥25kg/m2, paternal AGT2R A1675G

G allele increased the risk for uterine artery bilateral notching [OR 1.6 (95% CI 1.0-

2.7] (Table 7.4). Moreover, neonatal AGT2R A1675G GG genotype also tended to

117

associate with an increased risk for uterine artery bilateral notching among women

with BMI≥25kg/m2 (Table 7.4).

118

7.5 Discussion:

In the current study, in women with BMI≥25kg/m2, maternal, paternal and neonatal

AGT2R C4599A was associated with preeclampsia. In the same subset of women, a

similar non-significant trend was also observed for maternal, paternal and neonatal

AGT2R A1675G, which has previously been shown to be in linkage disequilibrium

with AGT2R C4599A [160]. Furthermore, in women with BMI≥25kg/m2, paternal

AGT2R C4599A A allele and paternal AGT2R A1675G G allele were associated with

an increased risk for uterine artery bilateral notching at 20 weeks’ gestation.

The observed association of maternal AGT2R C4599A with preeclampsia is consistent

with a recent Romanian study, in which women bearing the AGT2R C4599A AA

genotype were at an increased risk of developing preeclampsia with OR 3.8 (95% CI

1.1-12.5). The novelties of the current study include 1) paternal and neonatal

association of this polymorphism with preeclampsia and 2) modulation of these

associations by maternal BMI.

Epidemiological studies have shown that the risk of preeclampsia is determined not

only by maternal predisposition, but also by a paternal contribution. Men born to a

preeclamptic pregnancy are twice as likely to father a preeclamptic pregnancy [166].

In addition, men who have fathered a preeclamptic pregnancy are nearly twice as

likely to father a preeclamptic pregnancy with a different woman, regardless of

whether she has already had a preeclamptic pregnancy or not [167]. The paternal and

neonatal association of AGT2R C4599A with preeclampsia observed in the current

study provides further evidence for the paternal genetic contribution to preeclampsia.

119

The mechanism behind the association of AGT2R C4599A with preeclampsia is yet to

be determined. However, since the association was found in fathers and neonates and

since the polymorphism in fathers was also associated with uterine artery bilateral

notching, an indication of high uterine artery resistance and inadequate trophoblast

invasion [282], the placenta is likely to be involved. The expression of AGT2R in the

placenta has been documented across gestation [50,52], however, its role in

placentation is poorly understood. Since AGT2R has been shown to induce apoptosis

in various cells types [9,10,284] and preeclampsia is characterised by an increased

rate of trophoblast apoptosis [285,286], it is tempting to speculate that trophoblast

apoptosis may hold the key to the association of AGT2R C4599A with preeclampsia.

Furthermore, since AGT2R A1675G, known to be in linkage disequilibrium with

AGT2R C4599A [160], associates with AGT2R expression in vitro [163], one would

expect such an association for AGT2R C4599A, that is, the A allele of AGT2R

C4599A is associated with higher AGT2R expression. Taken all together, the A allele

or AA genotype of AGT2R C4599A in parent-infant trios, which may associate with

higher AGT2R expression in the placenta, potentially links to an increased rate of

trophoblast apoptosis and consequently leads to an increased risk for preeclampsia.

Gene-environment interaction describes the phenomenon in which association of a

genetic variant with a disease phenotype varies with the degree of exposure to an

environmental factor or vice versa. In the current study, the associations of AGT2R

polymorphisms with preeclampsia and uterine artery bilateral notching at 20 weeks’

gestation were only observed among women with BMI≥25kg/m2 but not among those

with BMI<25kg/m2, suggesting an interaction between AGT2R polymorphisms and

maternal BMI. Elevated BMI is a well established risk factor for preeclampsia [287].

120

In our SCOPE cohort, for every 5 unit increment in maternal BMI, there is a 1.3-fold

increase in risk for preeclampsia [283]. The AGT2R-BMI interaction observed in the

current study may suggest that the adverse effects associated with AGT2R C4599A A

allele or AA genotype are subtle and can only place women at risk for preeclampsia

or uterine artery bilateral notching if superimposed on adverse effects associated with

elevated BMI such as chronic inflammation [288].

The strength of this study is its large multicentre prospective design. In addition, the

outcome data of these cases were reviewed by highly skilled SCOPE clinicians to

ensure accurate diagnosis. The weakness of the study is the missing genotypes of

some participants, which reduced our sample size and may potentially introduce bias

into our results. However, there are no systematic reasons for missing genotypes

identified. In addition, in order to strengthen the reliability of our results, independent

cohorts are required to replicate our findings.

In summary, we have shown that AGT2R C4599A in mothers, fathers and neonates is

associated with preeclampsia. The association was further strengthened by its

association with uterine artery bilateral notching at 20 weeks’ gestation, an indication

of poor placental blood flow. More interestingly, these associations were modulated

by maternal BMI and only observed in women with BMI≥25kg/m2, suggesting an

AGT2R polymorphism-BMI interaction.

121


Conceived using donor gametes (n=19)

Lost to follow up (n=26)

Parental ethnicity non Caucasian (n=437)

Preeclampsia

n=123

Women recruited into SCOPE study

n=3234

Excluded due to protocol violation (n=12)

Partner did not consent (n=591)

Study population at 15±1 weeks

n=3196

Miscarriage or termination (n=28)

Eligible study population (parent-infant trio)

n=2121

Uncomplicated

n=1185

Other complications

n=813

122

Table7.1 Demographic characteristics of the study population.

Uncomplicated Preeclampsia

Maternal characteristics n=1185 n=123 P

Age (yrs) at 15 wks 28.2 (5.6) 26.8 (5.4) 0.007

BMI (kg/m2) at 15 wks 24.9 (4.5) 28.2 (7.2) <0.001

sBP (mmHg) at 15 wks 106.2 (9.9) 113.0 (10.1) <0.001

dBP (mmHg) at 15 wks 63.3 (7.6) 68.9 (8.1) <0.001

Socio-economic index 41.9 (16.7) 36.5 (16.0) 0.001

Pre-pregnancy green leafy vegetable

intake ≥1 serve/day (%) 615 (51.9%) 51 (41.5%) 0.03

Pre-pregnancy fruit intake ≥1

serve/day (%) 751 (63.4%) 66 (53.7%) 0.03

Smoking (%) at 15 wks 111 (9.4%) 12 (9.8%) 0.9

Gestational age (wks) 39.9 (1.9) 39.5 (2.2) 0.1

Birth weight (g) 3334.6 (529.7) 3176.6 (543.6) 0.02*


Age (yrs) 30.7 (6.3) 29.1 (5.6) 0.005

Height (cm) 179.6 (6.7) 179.2 (6.9) 0.5

BMI (kg/m2) 26.6 (4.0) 28.3 (5.5) 0.001

Birth weight (g) 3487.8 (571.4) 3506.5 (552.6) 0.7


Gestational age at birth (days) 280.7 (8.1) 266.0 (17.7) <0.001

Body length (cm) 51.0 (2.2) 48.4 (3.8) <0.001*

Head circumference (mm) 35.2 (1.4) 33.8 (2.3) <0.001*

Mid arm circumference (mm) 11.0 (0.9) 10.1 (1.5) <0.001*

Birth weight (g) 3590.9 (393.8) 3078.4 (747.8) <0.001*


Female babies (%) 584 (49.3%) 64 (52%) 0.6

Data are presented as mean (SD) or n (%).*adjusted for gestational age. sBP: systolic blood pressure, the second measurement; dBP:

diastolic blood pressure, the second measurement; 15 wks: 15 weeks’ gestation. Bold italics indicate significant difference.

123

Table7.2 The association of AGT1R and AGT2R polymorphisms with preeclampsia and

uterine artery bilateral notching at 20 weeks’ gestation. Uncomplicated Preeclampsia OR (95% CI) No bilateral notching Bilateral notching OR (95% CI)

Maternal AGT1R A1166C n=1068 n=115

n=1716 n=202

AA 525 (49.2) 59 (51.3) Ref

839 (48.9) 99 (49.0) Ref

CA 445 (41.7) 50 (43.5) 1.0 (0.7-1.5)

736 (42.9) 78 (38.6) 0.9 (0.7-1.2)

CC 98 (9.2) 6 (5.2) 0.6 (0.2-1.3) 141 (8.2) 25 (12.4) 1.5 (0.9-2.4)

Paternal AGT1R A1166C n=951 n=101

n=1510 n=178

AA 443 (46.6) 50 (49.5) Ref

715 (47.4) 88 (49.4) Ref

CA 412 (43.3) 43 (42.6) 0.9 (0.6-1.4)

660 (43.7) 71 (39.9) 0.9 (0.6-1.2)

CC 96 (10.1) 8 (7.9) 0.7 (0.3-1.6) 135 (8.9) 19 (10.7) 1.1 (0.7-1.9)

Neonatal AGT1R A1166C n=912 n=90

n=1366 n=172

AA 451 (49.5) 51 (56.7) Ref

677 (49.6) 77 (44.8) Ref

CA 381 (41.8) 32 (35.6) 0.7 (0.5-1.2)

576 (42.2) 81 (47.1) 1.2 (0.9-1.7)

CC 80 (8.8) 7 (7.8) 0.8 (0.3-1.8) 113 (8.3) 14 (8.1) 1.1 (0.6-2.0)

Maternal AGT2R C4599A n=1074 n=117

n=1727 n=206

CC 280 (26.1) 24 (20.5) Ref

457 (26.5) 49 (23.8) Ref

CA 545 (50.7) 59 (50.4) 1.3 (0.8-2.1)

884 (51.2) 99 (48.1) 1.1 (0.7-1.5)

AA 249 (23.2) 34 (29.1) 1.6 (0.9-2.8) 386 (22.4) 58 (28.2) 1.4 (0.9-2.1)

Paternal AGT2R C4599A n=974 n=101

n=1540 n=174

C allele 508 (52.2) 47 (46.5) Ref

814 (52.9) 80 (46.0) Ref

A allele 466 (47.8) 54 (53.5) 1.3 (0.8-1.9) 726 (47.1) 94 (54.0) 1.3 (1.0-1.8)

Neonatal AGT2R C4599A* n=951 n=88

n=1419 n=180

CC 358 (37.6) 24 (27.3) Ref

531 (37.4) 66 (36.7) Ref

CA 232 (24.4) 24 (27.3) 1.5 (0.9-2.8)

371 (26.1) 46 (25.6) 1.0 (0.7-1.5)

AA 361 (38.0) 40 (45.5) 1.7 (1.0-2.8) 517 (36.4) 68 (37.8) 1.1 (0.7-1.5)

Maternal AGT2R A1675G n=1084 n=119

n=1732 n=207

AA 277 (25.6) 24 (20.2) Ref

442 (25.5) 50 (24.2) Ref

AG 544 (50.2) 61 (51.3) 1.3 (0.8-2.1)

888 (51.3) 94 (45.4) 0.9 (0.7-1.4)

GG 263 (24.3) 34 (28.6) 1.5 (0.9-2.6) 402 (23.2) 63 (30.4) 1.4 (0.9-2.1)

Paternal AGT2R A1675G n=931 n=98

n=1482 n=166

A allele 479 (51.5) 46 (46.9) Ref

760 (51.3) 79 (47.6) Ref

G allele 452 (48.5) 52 (53.1) 1.2 (0.8-1.8) 722 (48.7) 87 (52.4) 1.2 (0.8-1.6)

Neonatal AGT2R A1675G** n=917 n=87

n=1384 n=163

AA 330 (36.0) 26 (29.9) Ref

509 (36.8) 51 (31.3) Ref

AG 225 (24.5) 25 (28.7) 1.4 (0.8-2.5)

350 (25.3) 44 (27.0) 1.3 (0.8-1.9)

GG 362 (39.5) 36 (41.4) 1.3 (0.8-2.1) 525 (37.9) 68 (41.7) 1.3 (0.9-1.9)

Maternal AGT2R T1334C n=1085 n=119

n=1735 n=207

TT 1011 (93.2) 108 (90.8) Ref

1620 (93.4) 192 (92.8) Ref

CT&CC 74 (6.8) 11 (9.2) 1.4 (0.7-2.7) 115 (6.6) 15 (7.2) 1.1 (0.6-1.9)

Paternal AGT2R T1334C n=994 n=104

n=1568 n=179

T allele 964 (97.0) 98 (94.2) Ref

1524 (97.2) 171 (95.5) Ref

C allele 30 (3.0) 6 (5.8) 2.0 (0.8-4.8) 44 (2.8) 8 (4.5) 1.6 (0.8-3.5)

Neonatal AGT2R T1334C*** n=961 n=93

n=1444 n=176

TT 914 (95.1) 88 (94.6) Ref

1374 (95.2) 167 (94.9) Ref

CT&CC 47 (4.9) 5 (5.4) 1.1 (0.4-2.9) 70 (4.8) 9 (5.1) 1.1 (0.5-2.2)

Data are presented as n (%).*CC genotype = female neonatal CC genotype + male neonatal C allele; CA genotype = female neonatal CA

genotype; AA genotype = female neonatal AA genotype + male neonatal A allele. **AA genotype = female neonatal AA genotype + male

neonatal A allele; AG genotype = female neonatal AG genotype; GG genotype = female neonatal GG genotype + male neonatal G allele.

***TT genotype = female neonatal TT genotype + male neonatal T allele; CT&CC genotype= female neonatal CT & CC genotype + male

neonatal C allele.

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Table7.3 The association of AGT2R C4599A with preeclampsia and uterine artery bilateral notching at 20 weeks’ gestation, stratified by maternal BMI. Maternal BMI Maternal AGT2R C4599A n Uncomplicated Preeclampsia OR (95% CI) n No bilateral notching Bilateral notching OR (95% CI)

BMI<25kg/m2 CC 153 143 (93.5) 10 (6.5) Ref

236 211 (89.4) 25 (10.6) Ref

CA 333 308 (92.5) 25 (7.5) 1.2 (0.5-2.5)

490 431 (88.0) 59 (12.0) 1.2 (0.7-1.9)

AA 152 141 (92.8) 11 (7.2) 1.1 (0.5-2.7)

214 184 (86.0) 30 (14.0) 1.4 (0.8-2.4)

BMI≥25kg/m2 CC 151 137 (90.7) 14 (9.3) Ref

270 246 (91.1) 24 (8.9) Ref

CA 271 237 (87.5) 34 (12.5) 1.4 (0.7-2.7)

493 453 (91.9) 40 (8.1) 0.9 (0.5-1.5)

AA 131 108 (82.4) 23 (17.6) 2.1 (1.0-4.2) 230 202 (87.8) 28 (12.2) 1.4 (0.8-2.5)

Paternal AGT2R C4599A

BMI<25kg/m2 C allele 294 272 (92.5) 22 (7.5) Ref

430 379 (88.1) 51 (11.9) Ref

A allele 282 267 (94.7) 15 (5.3) 0.7 (0.4-1.4)

402 360 (89.6) 42 (10.4) 0.9 (0.6-1.3)

BMI≥25kg/m2 C allele 261 236 (90.4) 25 (9.6) Ref

464 435 (93.8) 29 (6.3) Ref

A allele 238 199 (83.6) 39 (16.4) 1.9 (1.1-3.2) 418 366 (87.6) 52 (12.4) 2.1 (1.3-3.4)

Neonatal AGT2R C4599A*

BMI<25kg/m2 CC 184 170 (92.4) 14 (7.6) Ref

276 241 (87.3) 35 (12.7) Ref

CA 141 135 (95.7) 6 (4.3) 0.5 (0.2-1.4)

215 188 (87.4) 27 (12.6) 1.0 (0.6-1.7)

AA 233 216 (92.7) 17 (7.3) 1.0 (0.5-2.0)

311 272 (87.5) 39 (12.5) 1.0 (0.6-1.6)

BMI≥25kg/m2 CC 198 188 (94.9) 10 (5.1) Ref

321 290 (90.3) 31 (9.7) Ref

CA 115 97 (84.3) 18 (15.7) 3.5 (1.6-7.9)

202 183 (90.6) 19 (9.4) 1.0 (0.5-1.8)

AA 168 145 (86.3) 23 (13.7) 3.0 (1.4-6.5) 274 245 (89.4) 29 (10.6) 1.1 (0.7-1.9)

Data are presented as n (%). Bold italics indicate significant difference. *CC genotype = female neonatal CC genotype + male neonatal C allele; CA genotype = female neonatal CA genotype; AA genotype = female neonatal AA genotype

+ male neonatal A allele.

125

Table7.4 The association of AGT2R A1657G with preeclampsia and uterine artery bilateral notching at 20 weeks’ gestation, stratified by maternal BMI. Maternal BMI Maternal AGT2R A1675G n Uncomplicated Preeclampsia OR (95% CI) n No bilateral notching Bilateral notching OR (95% CI)

BMI<25kg/m2 AA 149 139 (93.3) 10 (6.7) Ref

233 208 (89.3) 25 (10.7) Ref

AG 333 308 (92.5) 25 (7.5) 1.1 (0.5-2.4)

489 433 (88.5) 56 (11.5) 1.1 (0.7-1.8)

GG 163 151 (92.6) 12 (7.4) 1.1 (0.5-2.6)

225 193 (85.8) 32 (14.2) 1.4 (0.8-2.4)

BMI≥25kg/m2 AA 152 138 (90.8) 14 (9.2) Ref

259 234 (90.3) 25 (9.7) Ref

AG 272 236 (86.8) 36 (13.2) 1.5 (0.8-2.9)

493 455 (92.3) 38 (7.7) 0.8 (0.5-1.3)

GG 134 112 (83.6) 22 (16.4) 1.9 (1.0-4.0) 240 209 (87.1) 31 (12.9) 1.4 (0.8-2.4)

Paternal AGT2R A1675G

BMI<25kg/m2 A allele 276 255 (92.4) 21 (7.6) Ref

395 347 (87.8) 48 (12.2) Ref

G allele 267 253 (94.8) 14 (5.2) 0.7 (0.3-1.4)

390 349 (89.5) 41 (10.5) 0.9 (0.6-1.3)

BMI≥25kg/m2 A allele 249 224 (90.0) 25 (10.0) Ref

444 413 (93.0) 31 (7.0) Ref

G allele 237 199 (84.0) 38 (16.0) 1.7 (1.0-2.9) 419 373 (89.0) 46 (11.0) 1.6 (1.0-2.7)

Neonatal AGT2R A1675G*

BMI<25kg/m2 AA 170 157 (92.4) 13 (7.6) Ref

253 225 (88.9) 28 (11.1) Ref

AG 137 130 (94.9) 7 (5.1) 0.7 (0.3-1.7)

203 177 (87.2) 26 (12.8) 1.2 (0.7-2.1)

GG 236 220 (93.2) 16 (6.8) 0.9 (0.4-1.9)

318 279 (87.7) 39 (12.3) 1.1 (0.7-1.9)

BMI≥25kg/m2 AA 186 173 (93.0) 13 (7.0) Ref

307 284 (92.5) 23 (7.5) Ref

AG 113 95 (84.1) 18 (15.9) 2.5 (1.2-5.4)

191 173 (90.6) 18 (9.4) 1.3 (0.7-2.5)

GG 162 142 (87.7) 20 (12.3) 1.9 (0.9-3.9) 275 246 (89.5) 29 (10.5) 1.5 (0.8-2.6)

Data are presented as n (%). Bold italics indicate significant difference. *AA genotype = female neonatal AA genotype + male neonatal A allele; AG genotype = female neonatal AG genotype; GG genotype = female neonatal GG

genotype + male neonatal G allele.

126

CHAPTER 8

General discussion

127

The primary aims of the current study were to determine the associations of RAS

polymorphisms in mothers, fathers and babies with pregnancy complications, including

preeclampsia, small for gestational age (SGA) and spontaneous preterm birth (sPTB) and to

identify potential gene-environment and gene-fetal sex interactions that may modify risks for

pregnancy complications. The secondary aims were to determine the association of RAS

polymorphisms with maternal plasma RAS profile at 15 weeks’ gestation and parameters

closely related to pregnancy outcomes, including maternal blood pressure at 15 weeks’

gestation, uterine and umbilical artery resistance at 20 weeks’ gestation. To the best of our

knowledge, the SCOPE study is one of the largest prospective, multicentre cohort studies on

low risk nulliparous women conducted in Australia and New Zealand and the first study to

explore gene-environment and gene-fetal sex interactions in the association of RAS

polymorphisms with pregnancy complications.

The RAS polymorphisms included in the current study are renin T/G (rs5707), AGT M235T

(rs699), AGT T174M (rs4762), ACE A11860G, AGT1R A1166C (rs5186), AGT2R C4599A

(rs11091046), AGT2R A1675G (rs1403543), AGT2R T1334C (rs12710567). These selected

polymorphisms either have functional effects on their respective proteins or have been shown

to associate with risk factors for pregnancy complications, such as hypertension and elevated

BMI (chapter 1). Although some of the polymorphisms, including AGT M235T [129,130,131],

ACE A11860G [144], AGT1R A1166C [144], AGT2R C4599A [144] and AGT2R A1675G

[144] have previously been shown to associate with risk for preeclampsia, the effect of

paternal genotypes and potential gene-environment and gene-fetal sex interactions have not

been investigated in previous studies.

In the current study, ACE A11860G and AGT2R C4599A were associated with SGA (chapter

6) and preeclampsia (chapter 7), respectively. We also observed an association of ACE

A11860G with maternal plasma ACE concentration at 15 weeks’ gestation (chapter 5) and

128

associations of Renin T/G and AGT M235T with plasma ANG 1-7 concentration at 15 weeks’

gestation (chapter 4). In addition, AGT1R A1166C and AGT M235T were associated with

abnormal uterine and umbilical artery resistance index at 20 weeks’ gestation, respectively

(chapter 5). The potential mechanisms behind these associations and their implications have

been discussed in detail in previous chapters. This chapter will highlight three common

themes emerging from these associations, namely contribution of paternal genotype, gene-

environment interactions and gene-fetal sex interaction.

8.1 Paternal AGT2R C4599A is associated with preeclampsia

Epidemiological studies have shown that the risk for major pregnancy complications, such as

preeclampsia, SGA and PTB, is determined not only by maternal predisposition, but also by a

fetal contribution inherited from the father. Men who were born to preeclamptic pregnancies

are twice as likely to father a preeclamptic pregnancy [166]. In addition, men who fathered a

preeclamptic pregnancy are nearly twice as likely to father a preeclamptic pregnancy with a

different woman, regardless of whether she has already had a preeclamptic pregnancy or not

[167]. Fathers who were born SGA, have a 3.5-fold greater risk of fathering a SGA pregnancy

[168]. Furthermore, paternal gestational age has been shown to positively correlate with his

offspring’s gestational age [169,170] and paternal obesity is an independent risk factor for

SGA [289].

In the current study, we assessed the paternal contribution in the association of RAS

polymorphisms with pregnancy complications (including preeclampsia, SGA and sPTB),

maternal blood pressure at 15 weeks’ gestation and uterine and umbilical artery indices at 20

weeks’ gestation. We found that paternal AGT2R C4599A affects a woman’s risk for

preeclampsia. Specifically, among women with BMI≥25kg/m2, partners with AGT2R C4599A

A allele increased women’s risk for preeclampsia and uterine artery bilateral notching at 20

weeks’ gestation compared to those with the C allele. These data provide further evidence for

129

the paternal genetic contribution to pregnancy complications. It seems likely that this

contribution is mediated through functional effects on the placenta.

8.2 Environmental factors modify the association of RAS polymorphisms with SGA and

preeclampsia

Gene-environment interaction describes the phenomenon in which association of a genetic

variant with a disease phenotype varies with the degree of exposure to an environmental

factor or vice versa. The gene-environment interactions have previously been demonstrated in

genetic association studies on perinatal outcomes. For example, the associations of

polymorphisms in metabolic genes CYP1A1 and GSTT with birth weight and preterm delivery

were modified by maternal smoking status, such that the associations were only apparent

among women who smoked during pregnancy [174,268].

In the current study, we explored gene-environment interactions in the associations of RAS

polymorphisms with pregnancy complications, blood pressure at 15 weeks’ gestation and

uterine and umbilical artery resistance index at 20 weeks’ gestation. The environmental

factors included were maternal age, BMI, green leafy vegetable intake, socio-economic status

and smoking at 15 weeks’ gestation. These factors have previously been shown to affect the

risk for pregnancy complications, including preeclampsia [208,209,210,211,212,213] and

SGA [198,199,200,201,202,203,204,205,206,207]. In our SCOPE cohort, we demonstrated

several gene-environment interactions. Specifically, maternal SEI and pre-pregnancy green

leafy vegetable intake modified associations of maternal ACE A11860G with SGA and

customized birth weight centile, such that associations were only observed among women

with SEI <34 or pre-pregnancy green leafy vegetable intake <1 serve/day. Furthermore,

maternal BMI modified associations of AGT2R C4599A in mothers, fathers and neonates with

preeclampsia and uterine artery bilateral notching at 20 weeks’ gestation, such that the

associations were only observed among women with BMI ≥25kg/m2.

130

Although the underlying mechanisms of gene-environment interactions may vary between

studies, it is interesting that gene variant-disease associations observed in the current study

and studies on CYP1A1 and GSTT polymorphisms [174,268] were all found in a poor

environment (i.e. maternal SEI<34, pre-pregnancy green leafy vegetable intake <1 serve/day,

maternal BMI≥25kg/m2

and maternal smoking). One possible explanation for this observation

is that the adverse effects associated with individual polymorphisms are likely subtle and can

only put women at risk for a pregnancy complication if superimposed on a poor environment.

In the presence of a good environment, the effects of polymorphisms are likely to be offset by

the beneficial effects of that environment. This is intriguing since it offers an avenue of

modifying genetic predisposition to pregnancy complications and implies that the adverse

effects of polymorphisms may be avoided by maintaining a healthy lifestyle (i.e. a good

environment).

8.3 Fetal sex affects the association of RAS polymorphisms with SGA and uterine and

umbilical artery resistance indices at 20 weeks’ gestation

Fetal sex deserves special attention in pregnancy association studies related to RAS

polymorphisms. In adults, RAS components are differentially affected by estrogen and

testosterone and appear to be sexually dimorphic [190,191]. As a consequence, the

associations of RAS polymorphisms with cardiovascular diseases vary between the sexes,

such that the associations are more profound in males than females

[192,193,194,195,196,197]. During pregnancy, women bearing a female fetus have higher

circulating ANG II concentration (Sykes et al. submitted) and a higher level of decidual pro-

renin mRNA expression and protein secretion than those bearing males [189]. These fetal sex

differences in maternal circulating and uteroplacental RAS profile may potentially affect the

association of RAS polymorphisms with pregnancy complications.

131

The current study demonstrated several fetal sex specific associations. The female-specific

associations were found for maternal ACE A11860G and birth weight and SGA and the

association of maternal AGT1R A1166C with abnormal uterine artery resistance index (>90th

centile) at 20 weeks’ gestation. In addition, the association of maternal and fetal AGTM235T

with abnormal umbilical artery resistance index (>90th

centile) at 20 weeks’ gestation was

specific to male-bearing pregnancies. To our knowledge, our data provide the first evidence

that fetal sex can modulate the association of RAS polymorphisms with pregnancy

complications and pregnancy-related parameters.

Furthermore, since the human placenta, which is pivotal in pregnancy success [290], is

sexually dimorphic [188], the impact of fetal sex on genetic associations with pregnancy

complications is likely well beyond the RAS. Indeed, recent studies have demonstrated

female specific associations of progesterone receptor polymorphism [291] and peroxisome

proliferator-activated receptor gamma2 polymorphism [292] with maternal glycaemic control,

which is closely related to pregnancy outcomes among diabetic women [293]. Therefore,

associations between gene variants and pregnancy complications in general should consider

the impact of fetal sex.

8.4 Limitations in genetic association studies

One of the major issues in genetic association studies is the lack of reproducibility of results.

Among the selected RAS polymorphisms, AGT M235T [129,130,131], ACE A11860G [144],

AGT1R A1166C [144], AGT2R C4599A [144] and AGT2R A1675G [144] in mothers have

previously been shown to associate with preeclampsia. However, only the association of

AGT2R C4599A with preeclampsia could be replicated in the current study. This lack of

reproducibility could be attributed to several factors. Differences in ethnicity between studies

may be one of the factors since it commonly indicates differences in genotype frequencies of

polymorphisms. In addition, since it is increasingly being recognised that early and late onset

132

preeclampsia are two distinct phenotypes and have different underlying pathogenic

abnormalities [294], it is reasonable to speculate that studies with different proportions of

early and late onset preeclampsia would yield different results. Finally, as demonstrated in

chapter 6 and 7 of this thesis, fetal sex and maternal environmental factors such as BMI

modify the associations of RAS polymorphisms with pregnancy complications. Therefore,

differences in these factors between studies may also contribute to the inconsistency in

association results between studies.

With advances in genotyping technology, allowing examination of greater than 1 million

polymorphisms at once, the inflation of false positive rate due to multiple comparisons has

become a concern for genetic association studies. The multiple comparison procedures such

as Bonferroni adjustment and false discovery rate have been widely used in genome-wide

association studies to control the false positive rate [295]. However, these multiple

comparisons procedures also increase the likelihood of obtaining false negative results. The

current study, unlike genome-wide association studies, is a candidate gene association study

and only investigated 8 polymorphisms. Therefore, it may not be necessary to apply multiple

comparison procedures in the current study.

The significant results identified in our study are unlikely to be false positive for the

following reasons. Firstly, the RAS polymorphisms selected are either functional or have

previously been shown to associate with risk factors for pregnancy complications (chapter 1).

For example, ACE A11860G, which was shown to associate with SGA in the current study,

has previously been shown to associate with plasma ACE activity [147]. The polymorphism

was also associated with maternal plasma ACE concentration at 15 weeks’ gestation in the

current study. Secondly, consistencies between associations also suggest that the significant

results observed in the current study are unlikely to be false positives. AGT2R C4599A and

AGT2R A1675G are known to be in linkage disequilibrium [160]. In the current study, both

133

polymorphisms in partners were associated with uterine bilateral notching at 20 weeks’

gestation. In addition, the association of AGT2R A1675G with preeclampsia was consistently

observed in mothers, fathers and neonates. Furthermore, the ACE A11860G GG genotype was

not only associated with an increased risk for SGA determined by customized centiles, but

also a reduction in infants’ birth weight and size.

8.5 Implications

Despite the fact that considerable efforts have been made to predict risk for pregnancy

complications, to date, there are still no effective prediction tests for these [76]. In the current

study, maternal ACE A11860G and AGT2R C4599A in mothers, partners and neonates were

shown to associate with SGA and preeclampsia, respectively. Assuming these results can be

replicated in a larger independent cohort, the two polymorphisms, combining with other

genetic polymorphisms and clinical risk factors, can potentially be used to predict risk for

pregnancy complications. Recent studies demonstrate that some genetic polymorphisms are

associated with multiple pregnancy complications [171,296], suggesting some overlap

between pregnancy complications that may be due to the similar underlying pathogenic

mechanisms [297]. Although these polymorphisms may be used to identify women at risk for

pregnancy complications, additional markers are needed to differentiate one complication

from another. In the current study, ACE A11860G and AGT2R C4599A each were only

associated with one pregnancy complication (i.e. SGA and preeclampsia, respectively), and

hence may be utilized to differentiate patients between pregnancy complications.

In light of gene-environment and gene-fetal sex interactions observed in the current study,

future research should take account of them. In addition, these interactions may also be

relevant to meta-analysis. That is, fetal sex and appropriate environmental factors should be

considered before pooling genetic association data between studies otherwise the information

134

generated from the pooled data may be misleading. Unfortunately, not all of these data are

always available for meta analyses.

The current study focused on polymorphisms in ACE, AGT, AGT1R and AGT2R genes.

Given the complexity of the renin angiotensin system (Figure 1.1), future study should also

investigate genetic associations of RAS polymorphisms in other gene components, including

AGT4R, Mas receptor, ACE2, and renin/prorenin receptor.

Finally, the current study determined the functional effects of the selected RAS

polymorphisms on maternal circulating RAS profiles but not uteroplacental RAS

levels/activities. Given the role of the uteroplacental RAS in placentation (Chapter 1), future

studies should investigate the functional effects of RAS polymorphisms on uteroplacental

RAS levels/activities, which would further strengthen the associations observed in the current

study.

8.6 Conclusion

In the current prospective study, functional RAS polymorphisms were associated with SGA,

preeclampsia, as well as parameters closely related to pregnancy complications, including

abnormal uterine and umbilical artery resistance indices at 20 weeks’ gestation. These support

the involvement of the RAS in the pathogenesis of pregnancy complications, especially SGA

and preeclampsia. More interestingly, some of these associations were found with partner

genotypes, suggesting a paternal contribution to pregnancy complications. Furthermore, some

associations were modulated by environmental factors and fetal sex, implying the importance

of considering these and potentially other factors in future genetic association studies.

135

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Renin angiotensin system polymorphisms and pregnancy ... · Renin Angiotensin System Polymorphisms and Pregnancy Complications Ang Zhou BHlthSc (Hons) Thesis submitted for the degree