Metabolic Effects Following Periconceptional Alcohol Exposure in Rat Adult Offspring: Modulations by a Postnatal Western Diet

Metabolic effects following periconceptional alcohol exposure in rat adult offspring: modulations by a postnatal western diet

Emelie Marlene Gårdebjer MS.c

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in 2015

School of Biomedical Science Abstract

It is increasingly recognized that maternal health and nutritional status prior to and during pregnancy are important determinants of fetal outcome. Fetuses exposed to a suboptimal in utero environment are at higher risk of developing adult onset diseases including: type 2 diabetes, insulin resistance and obesity. Maternal alcohol intake has been extensively studied when consumed during pregnancy, at different doses, and different exposure periods. Many of these – including studies investigating low levels of prenatal alcohol consumption – have demonstrated abnormal development of fetal organs and alterations in metabolic pathways that persists into adulthood and commonly result in insulin resistance and glucose intolerance. Many women who consume alcohol do however cease upon pregnancy recognition – but the effects of alcohol consumption during the periconceptional period (defined as prior to conception until preimplantation) on adult offspring metabolism are still to be investigated. Therefore, the focus of this thesis was to ascertain whether periconceptional alcohol exposure (PC:EtOH-exposure) results in persisting metabolic effects in the adult offspring; and whether this was mediated via placental dysfunction. In addition, as adult onset disease initially programmed in utero can be potentiated or first revealed by a mismatch between the pre- and postnatal environment, or a ‘second hit’, this thesis also investigated the interaction between PC:EtOH-exposure and a postnatal consumption of a western diet (WD).

As a part of this thesis, a rat model of maternal alcohol consumption (moderate to high) was developed. 12.5% alcohol (v/v) was administered via a liquid diet to dams from 4 days pre-conception until 4 days after confirmation of pregnancy (PC:EtOH group). Control dams were given a nutritional equal liquid diet but without alcohol during the exposure period (untreated (U) group). Separate cohorts of rats were generated to study the offspring at different ages: one subset of dams was assigned for studies of the late gestation fetus and investigation of the placenta on embryonic day (E)20 (Chapter 3); another subset of dams littered down naturally to allow for examination of physiological parameters at 6-8 months of age in offspring consuming a control diet (C) (U:C and PC:EtOH:C), and in combination with a WD (U:WD and PC:EtOH:WD) (Chapter 4 & 5). Physiological parameters in the offspring included

ii investigation of glucose- and insulin homeostasis via a glucose tolerance test (GTT) and an insulin tolerance test (ITT); and assessment of the body composition via a dual X-ray (DXA)-scan. Plasma at different ages throughout development was assessed and tissue (predominantly the placenta, liver, adipose tissue and muscle) were investigated with quantitative polymerase chain reaction (qPCR), western blotting and histology.

PC:EtOH-exposure resulted in fetal growth restriction, increased the placenta:body weight ratio, and increased placental length and width in both males and females. Morphological analyses of the placenta revealed that the increase in placental size primarily was accounted for by increases in the junctional zone and sex-specific increases in the cross-sectional area of apparent glycogen cells. These changes were associated with sex-specific alterations in a wide array of placental genes and proteins involved in nutrient transportation and vasculogenesis. Importantly, the protective enzyme 11-beta hydroxysteroid dehydrogenase (11βHsd-2) was expressed at higher levels in the labyrinth zone of the placenta, which is suggestive of an augmented stress-response, apparent well beyond the exposure window. mRNA levels of DNA methyltransferases were also increased in the fetal liver, suggesting a potential epigenetic involvement.

In adulthood – regardless of postnatal diet – both male and female offspring were glucose intolerant and insensitive to exogenous insulin. This was associated with increased hepatic gluconeogenesis and sex-specific alterations in peripheral insulin signaling. Male, but not female offspring had an increased percentage of total- and abdominal fat mass; and had developed a more advanced stage of hepatic steatosis. The plasma lipid composition was abnormal; and the levels of gene expression of inflammatory genes were increased in both sexes. While the interactive effects of PC:EtOH and a postnatal WD were negligible in female offspring, a WD exacerbated the degree of insulin insensitivity and hepatic steatosis in PC:EtOH-exposed male offspring. Often, the phenotypes created by PC:EtOH and a WD were similar – suggesting the effects of PC:EtOH on adult metabolism in some circumstances are comparable to those seen after consuming a WD for the major part of adult life.

This thesis has provided compelling experimental evidence that maternal

iii periconceptional alcohol consumption can program the offspring to adult onset disease. This information should be taken into account when developing public policy guidelines regarding alcohol intake prior to and during early pregnancy and made available to women of childbearing age.

Declaration by author

This thesis IS COMPOSED OF MY ORIGINAL WORK, AND CONTAINS no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my research higher degree candidature and does not include a substantial part of work that has been submitted TO QUALIFY FOR THE AWARD OF ANY other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis.

Publications during candidature

Peer-reviewed publications GARDEBJER, E. M., CUFFE, J. S., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2014. Periconceptional alcohol consumption causes fetal growth restriction and increases glycogen accumulation in the late gestation rat placenta. Placenta, 35, 50-7.

GARDEBJER, E. M., ANDERSON, S. T., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2015. Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring which is exacerbated by a postnatal high-fat diet. FASEB J, (fj.14-268979).

In preparation

GARDEBJER, E. M., WARD, L. C., BIELFELDT-OHMANN, H., WLODEK, M. E., & MORITZ, K. M. The effects of maternal alcohol intake around conception and a postnatal high-fat diet on adiposity in male and female rat offspring.

Other publications

PROBYN, M. E., PARSONSON, K. R., GARDEBJER, E. M., WARD, L. C., WLODEK, M. E., ANDERSON, S. T. & MORITZ, K. M. 2013. Impact of Low Dose Prenatal Ethanol Exposure on Glucose Homeostasis in Sprague- Dawley Rats Aged up to Eight Months. PLoS One, 8, e59718.

International conference abstracts DOREY, E*., GARDEBJER, E. M., CAMPBELL, F., PARAVICINI, T. M., WEIR, K. A., WLODEK, M. E., & MORITZ, K. M. 2014. Periconceptional alcohol exposure causes alterations to renal and cardiac function in aged female offspring. Postgraduate Symposium in Biomedical Sciences, Brisbane, Australia, November 3-5th.

GARDEBJER, E. M*., MCMAHON, K., MORITZ, K. M., & PANTALEON, M. 2014. Periconceptional alcohol exposure programs sex specific hyperinsulinemia possibly through dysregulation of placental O-linked glycosylation. World Congress of Reproductive Biology, Edinburgh, Scotland, September 2-4th. Abstract P288. (Poster presentation).

GARDEBJER, E. M*., WARD, L. C., ANDERSON, S., & MORITZ, K. M. 2014. Periconceptional alcohol consumption or a postnatal western diet causes insulin insensitivity in a sex-specific manner in rat. Scandinavian Physiological Society, Stockholm, Sweden, August 22-24th. (Oral presentation).

GARDEBJER, E. M*., CUFFE, J. S & MORITZ, K. M. 2013. Periconceptional alcohol consumption induces placental stress and causes fetal growth restriction. Australiasian Fetal Alcohol Spectrum Disorders Conference, Brisbane, Australia, November 19-20th, 2013. (Oral Presentation).

DOREY, E*., KALISCH-SMITH, J., GARDEBJER, E. M., & MORITZ, K. M. 2013. Alterations in male kidney structure and function following periconceptional ethanol exposure. Australiasian Fetal Alcohol Spectrum Disorders Conference, Brisbane, Australia, November 19-20th.

GARDEBJER, E. M*., WARD, L. C., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2013. Periconceptional alcohol exposure contributes to insulin resistance in rat adult offspring. 2013 International Postgraduate Symposium in Biomedical Sciences, Brisbane, Australia, October 28-30th. (Poster presentation).

DOREY, E*., KALISCH-SMITH, J., GARDEBJER, E. M., WLODEK, M, E., WEIR, K., PANTALEON, M., & MORITZ, K. M. 2013. The effect of periconceptional ethanol on kidney development and function. 2013 International Postgraduate Symposium in Biomedical Sciences, Brisbane, Australia, October 28-30th.

GARDEBJER, E. M*., WARD, L. C., WLODEK, M. E., PANTALEON, M., & MORITZ, K. M. 2013. Periconceptional alcohol exposure contributes to insulin resistance. 35th European Society for Clinical Nutrition and Metabolism, Leipzig, Germany, August 31st – September 3rd. Clinical Nutrition, 32 (Suppl 1):S104. Abstract PP216-SUN. (Poster presentation).

GARDEBJER, E. M*., CUFFE, J. S & MORITZ, K. M. 2013. Periconceptional alcohol exposure impacts on placental structure and gene expression. 37th Congress of the International Union of Physiological Sciences, Birmingham, United Kingdom, July 21-26th. Wiley online. Abstract PBC343. (Poster presentation).

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GARDEBJER, E. M*., & MORITZ, K. M. 2012. Periconceptional alcohol exposure alters fetal and placental development. 2012 International Postgraduate Symposium in Biomedical Sciences, Brisbane, Australia, September 24-26th. (Poster presentation).

GARDEBJER, E. M*., & MORITZ, K. M. 2012. Periconceptional alcohol consumption alters placental and fetal development. Society for Gynecologic Investigation 2012 International Summit – Prematurity and Stillbirth, August 3-5th. Brisbane, Australia. (Poster presentation).

National conference abstracts DOREY, E*., GARDEBJER, E. M., CAMPBELL, F., PARAVICINI, T. M., WEIR, K. A., WLODEK, M. E., & MORITZ, K. M. 2014. Periconceptional alcohol alters adult renal and cardiac function in a sex dependent manner. Australian Physiological Society, Brisbane, Australia, November 30th-December 3rd.

DOREY, E*., GARDEBJER, E. M., CAMPBELL, F., PARAVICINI, T. M., WEIR, K. A., WLODEK, M. E., & MORITZ, K. M. 2014. Periconceptional alcohol exposure alters renal and cardiac function in aged female offspring. The Annual Scientific Meeting of the ANZSN & Renal Society of Australasia Annual Conference. August 25-27th. . . . .

GARDEBJER, E. M*., & MORITZ, K. M. 2012. The effect of periconceptional alcohol consumption on the late gestation fetus. The Australian Early Origin of Hypertension Workshop, Adelaide, Australia, September 27-29th. (Poster presentation).

GARDEBJER, E. M*., & MORITZ, K. M. 2012. Periconceptional ethanol consumption increase glucose concentrations in pregnant dams and alters fetal and placental growth. The Annual Scientific Meeting of the Endocrine Society of Australia and the Society for Reproductive Biology, August 26- 29th. Gold Coast, Australia. (Poster presentation).

GARDEBJER, E. M*., PANTALEON, M., & MORITZ, K. M. 2012. Does periconceptional ethanol intake predispose the embryo to adult metabolic syndrome? 26th Annual Meeting, The Fetal and Neonatal Workshop of Australia and New Zealand, Port Stephens, Australia, March 16-17th. (Oral Presentation).

*, presenting author Other presentations

GARDEBJER, E. M. 2014. Don’t drink and get pregnant! Lund University seminar, Clinical research center, Malmö, Sweden, October 13th. (Oral presentation).

GARDEBJER, E. M. 2014. Early and late effects of periconceptional alcohol exposure in rat. Nestlé Research Center, Lausanne, Switzerland, December 17th. (Oral presentation).

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Publications included in this thesis

GARDEBJER, E. M., CUFFE, J. S., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2014. Periconceptional alcohol consumption causes fetal growth restriction and increases glycogen accumulation in the late gestation rat placenta. Placenta, 35, 50-7.

Incorporated as Chapter 3 Contributor Statement of contribution Gårdebjer, E. M. Study design (45%) Animal treatment (95%) Tissue collection (50%) Gene and protein studies (100%) Histological studies (95%) Interpretation of results (70%) Writing manuscript (70%) Cuffe, J. S. Histological studies (5%) Reviewing and editing manuscript (5%) Interpretation of results (15%) Pantaleon, M. Interpretation of results (5%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (10%) Moritz, K. M. Study design (55%) Animal treatment (5%) Tissue collection (50%) Interpretation of results (10%) Reviewing and editing manuscript (10%)

GARDEBJER, E. M., ANDERSON, S., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2014. Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring which is exacerbated by a postnatal high-fat diet. FASEB. J, (fj.14-268979).

Incorporated as Chapter 4 Contributor Statement of contribution Gårdebjer, E. M. Study design (50%) Animal treatment* (80%) Tissue collection† (60%) Glucose/Insulin tolerance testing (100%) Plasma assays (100%) Gene and protein studies (100%) Interpreting results (65%) Writing manuscript (75%) Anderson, S. Interpretation of results (15%) Reviewing and editing manuscript (10%) Pantaleon, M. Tissue collection† (5%) Interpretation of results (10%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (5%) Moritz, K. M. Study design (50%) Animal treatment* (5%) Tissue collection† (20%) Interpretation of results (10%) Reviewing and editing manuscript (5%)

*, Remaining 15% performed by Kalisch-Smith, J; †, remaining 15% contributed to by other members of Moritz’s lab

GARDEBJER, E. M., WARD, L., BIEDELDT-OHMANN, H., WLODEK, M. E., & MORITZ, K. M. 2014. The effects of maternal alcohol intake around conception and a postnatal high-fat diet on adiposity in male and female rat offspring. (In preparation).

Incorporated as Chapter 5 Contributor Statement of contribution Gårdebjer, E. M. Study design (50%) Animal treatment* (80%) Tissue collection† (65%) DXA-scan (60%) Plasma assays (100%) Gene and protein studies (100%) Histological studies (80%) Interpreting results (65%) Writing manuscript (70%) Ward, S. DXA-scan (40%) Interpretation of results (10%) Reviewing and editing manuscript (10%) Biefeldt-Ohmann, H. Histological studies (20%) Interpretation of results (10%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (5%) Moritz, K. M. Study design (50%) Animal treatment* (5%) Tissue collection† (20%) Interpretation of results (15%) Reviewing and editing manuscript (10%)

*, Remaining 15% performed by Kalisch-Smith, J; †, remaining 15% contributed to by other members of Moritz’s lab

Contributions by others to this thesis

The majority of work completed throughout this thesis was undertaken by Gårdebjer, E. M. Help was provided for the design of the project, tissue collection and interpretation of results and critical revision of work by Moritz, K. M. Assistance with animal work (offspring cohort) was provided by Kalisch-Smith, J. Biefeldt-Ohmann, H. provided expertise assistance in histological analysis in Chapter 5.

Statement of parts of the thesis submitted to qualify for the award of another degree:

None

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Acknowledgements

First and foremost I would like to express my sincere thanks to my primary supervisor Associate Professor Karen Moritz. Thank you for giving me the opportunity to undertake a PhD in your lab. Without your dedicated assistance and belief in me, this thesis would not have been accomplished. I also want to express my gratitude to my secondary supervisor Dr Marie Pantaleon for enthusiastically supporting me through every issue I have encountered in my research. It has been an honour to work with both of you.

I would like to acknowledge my research committee Dr David Simmons and Dr Leigh Ward for your support and for providing expertise within your respective areas. In addition, I want to express my gratitude to Dr Stephen Anderson and Dr Helle Biefeldt-Ohmann. You have both donated your time and kindly shared your knowledge to assist me in my research and I deeply appreciate this. To all the people that have helped me at any stage or throughout my candidature with animal care, time-consuming post mortems, showing me new techniques, giving me feedback and new ideas, revised abstracts, papers, posters, or just shared a quality coffee with me, thank you. Especially to Dr James Cuffe who has been my rock and mentor from the beginning to the end. You have unselfishly donated so much of your time to revise Swenglish drafts and given me a hand whenever I have needed one. Words are inadequate – Thank you. And to the rest of the science crew: Sarah Steane, Carlie Cullen, Jacinta Kalisch-Smith, Reetu Singh, Karrona Tep, Lee O’Sullivan, Sarah Walton, Richard Schlegel, Daniel Brown, Simone Zanini, Emily Dorey, Anselm Koning, Danny Bosch. Thank you. And thanks to the animal house staff for looking after my beloved babies when I wasn’t there, especially to Mike Moore, Chelsea Stewart, Barb Arnts, Kym French and Kate Lutkins.

Getting through my dissertation required more than academic support and I have many people to thank for putting up with me and to supporting me throughout the years. I cannot begin to express my gratitude and appreciation for your friendship and endless support. Special thanks to my triathlon family in SBTC. For the endless bike rides, the long runs, swims and coffee sessions that always cleared my mind

xiii and put me back on track whenever I had fallen off. Special thanks to the people who have made my time in Australia unforgettable: Annabel Killen, Marc Russel- Pavier & Zelda, Johnny Loughrey, Jess Schaffer, Sophia Andes, John Cowley, Hamish Reid, Steve Baker. Thanks to Heidi derWald, Laura Ringdahl and Martina Barham for breathing through endless yoga sessions in preparation for extra demanding times. You are all my source of inspiration.

My deepest appreciation to the funding bodies that supported me financially and enabled me to undertake the work presented within this thesis. The study was funded by an NH&MRC project grant and I myself was supported by a UQI Postgraduate Award from the University of Queensland.

Finally. To my family, mamma och pappa. You fully supported me in my decision to move to the other side of the World with the initial intention never to return, and despite the distance you have done everything in your power to make my life easier. Thanks also to my sis Sofie who has been my dissertation support in crime from the beginning to the end. All my love to you. To my lifetime friends Martina Nilsson och Malin Thomelius thank you for supporting me with half a World distance and for taking me back with open arms upon my return to Sweden. I am forever grateful for your friendship. To Joel for your limitless support throughout the critical writing up phase, du betyder allt för mig.

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Keywords periconceptional, alcohol, insulin resistance, developmental programming, placenta, metabolic syndrome, rat, inflammation, steatosis, gluconeogenesis

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 110102, Medical biochemistry: carbohydrates, 50%

ANZSRC code: 111401, Foetal development and medicine, 30%

ANZSRC code: 110105, Medical biochemistry: lipids, 20%

Fields of Research (FoR) Classification

FoR code: 1101, Medical biochemistry and metabolomics, 60%

FoR code: 1114, Paediatrics and Reproductive Medicine, 20%

FoR code: 1116, Medical Physiology, 20%

Table of contents

Abstract…………………………………………………………………………………..…...ii Declaration by author……………………………………………………………….…..…..v Publications during candidature…………………………………………………….……..vi Publications included in this thesis……………………………………………..…………ix Contributions by others to the thesis……………………………………………...….…..xii Acknowledgements……………………………………………………………...………...xiii Keywords…………………………………………………………………………………....xv List of tables………………………………………………………………………...….….xxii List of figures……………………………………………………………………...………xxiv List of Abbreviations used in the thesis.…………………………………………….…xxvii

1. CHAPTER 1 – REVIEW OF LITERATURE 1.1. Introduction………………………………………………………..…………….….1 1.2. Developmental origins of health and disease (DOHaD)……………………....4 1.2.1. The thrifty phenotype…………………………………………….……….…4 1.2.2. Prenatal famine exposure……………………………………………..……5 1.2.3. Intrauterine growth restriction…………………………………….………..6 1.2.4. Catch up growth……………………………………………………………..7 1.3. Timing of exposure to a sub-optimal environment…………………………...…8 1.3.1. The periconceptional period…………………………………………..….10 1.3.1.1. Preimplantation development…………………………………….10 1.3.1.2. Programming of metabolic outcomes by periconceptional exposures……………………………………………………………..…11 1.3.1.3. Mechanisms of programming in the periconceptional period…15 1.3.2. Prenatal programming of metabolic outcomes………………………….16 1.3.3. Interactions between prenatal and postnatal environments……….….16 1.4. Sex differences in fetal programming……………………………………..……18 1.5. The role of the placenta in fetal programming…………………………………20 1.5.1. Placentation in human and rat……………………………………..……..20 1.5.2. Placental nutrient transfer…………………………………………………24

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1.5.2.1. Glucose…………………………………………………………..…24 1.5.2.2. Amino acids………………………………………………...………24 1.5.3. Vasculogenesis……………………………………………………...……..25 1.5.4. Utero-placental insufficiency……………………………………………...26 1.5.5. Placental size………………………………………………………..……..26 1.5.6. The effect of alcohol on the placenta………………………….…………28 1.6. Alcohol……………………………………………………………………….……..28 1.6.1. Alcohol intake during pregnancy……………………………………...….28 1.6.2. The effect of alcohol on the fetus and fetal alcohol syndrome…..……29 1.6.3. Timing, drinking pattern and drinking level……………………………...30 1.6.4. Alcohol elimination during pregnancy – the mother, placenta and fetus……………………………………………………………………………31 1.6.5. Alcohol metabolism……………………………………………….……….32 1.6.5.1. Alcohol metabolism in rats compared with humans……………34 1.6.6. Animal models of maternal alcohol intake and programming of disease………………………………………………………………….….….34 1.6.6.1. Periconceptional alcohol consumption…………………………..34 1.6.6.2. Prenatal alcohol consumption………………………………….…35 1.7. The metabolic syndrome…………………………………………………..…….40 1.7.1. Diabetes………………………………………………………………...…..42 1.7.1.1. Pancreatic insulin secretion…………………..…………………..43 1.7.1.2. Peripheral insulin signaling………………………………………..43 1.7.1.2.1. Glycogen synthase kinase-3-beta………………….…….45 1.7.1.3. Hepatic glucose homeostasis………………………………….…46 1.7.1.3.1. Hepatic glucose homeostasis in response to fasting.....48 1.7.1.3.2. Hepatic glucose homeostasis in response to a meal…..49 1.7.1.4. Insulin and glucose homeostasis in diabetes……………….…..49 1.7.1.4.1. Insulin homeostasis in diabetes……………………….....50 1.7.1.4.2. Glucose homeostasis in diabetes……………………..…51 1.7.2. Overweight and obesity…………………………………………….……..52 1.7.2.1. Obesity in developmental programming…………………….…..52 1.7.2.2. Adipose tissue as an endocrine organ……………………….….53 1.7.2.2.1. Inflammation………………………………………….….…53 1.7.2.2.2. Adipokines…………………………………………..………55

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1.8. The scope of this thesis……………………………………………………...…..58 1.8.1. Aims and hypotheses……………………………………………………...58 1.8.1.1. Overall aims………………………………………………………...58 1.8.1.2. Overall hypotheses…………………………………………...……58 1.8.2. Aims and hypotheses for chapter 3………………………………………59 1.8.3. Aims and hypotheses for chapter 4………………………………………60 1.8.4. Aims and hypotheses for chapter 5………………………………………61

2. CHAPTER 2 – GENERAL METHODS AND MATERIALS 2.1. Ethics…………………………………………………………………...…..……..62 2.2. Animal husbandry……………………………………….……………...………..62 2.2.1. Mating and start of the experimental protocol…………...……………..62 2.2.2. Experimental diet and chow…………………………………………...….63 2.2.3. Plasma alcohol concentration cohort…………………………………....65 2.2.4. Embryonic day 20 cohort………………………………………………….65 2.2.5. Offspring cohort…………………………………………………………....65 2.3. Offspring weight…………………………………………………………………..68 2.4. Post mortem and tissue collection…………………………….………………..68 2.4.1. Embryonic day 20 cohort………………………………………………….68 2.4.2. Offspring cohort…………………………………………………………….71 2.4.3. Placental dry weight……………………………………………………….71 2.5. Blood collection……………………………………………….…………………..71 2.5.1. Tail tipping…………………………………………………………………..72 2.5.2. Tail slicing…………………………………………………………………..72 2.5.3. Cardiac puncture………….………………………………………………..72 2.6. Assessment of glucose- and insulin homeostasis…………………………….74 2.6.1. Glucose tolerance test (GTT) …………………………………………….74 2.6.2. Insulin tolerance test (ITT) ………………………………….…………….74 2.6.3. Calculations for area under curves generated in GTT and ITT……….74 2.7. Blood handling and plasma analyses…………………………………………..76 2.7.1. Cobas Integra analyses………………………………………………..….77 2.7.2. Plasma alcohol determination…………………………………………….77 2.7.3. Hormone analyses…………………………………………………………78 2.7.3.1. Plasma insulin determination……………………………………..79

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2.7.3.2. Plasma leptin determination………………………………………80 2.7.3.3. Automated data reduction procedures……………………….….83 2.7.3.4. Plasma adiponectin determination………………………..……...84 2.7.4. Plasma osmolality determination…………………………………………86 2.8. Body composition measurements…………………………………………..…..86 2.9. Gene expression analysis……………………………………………………….87 2.9.1. RNA extraction………………………………………………………..……87 2.9.1.1. RNA extraction from liver and placental compartments…….…88 2.9.1.2. RNA extraction from visceral abdominal adipose tissue………88 2.9.2. RNA concentration and purity…………………………………………….89 2.9.3. Reverse transcription of RNA to cDNA…………………………...……..91 2.9.4. Quantifying gene expression……………………………………..………91 2.9.4.1. TaqMan® detection chemistry……………………………………91 2.9.4.2. SYBR® Green-based detection chemistry………………...……94 2.9.5. Real-time PCR………………………………………………………….….95 2.9.6. Quantification of gene expression……………………………………..…97 2.9.7. Fetal genotyping……………………………………………………………97 2.10. Protein expression analyses………………………………………….…101 2.10.1. Protein extraction…………………………………………………101 2.10.2. Protein concentration…………………………………………….102 2.10.3. Western blotting…………………………………………………..102 2.11. Histology…………………………………………………………………..103 2.11.1. Hematoxylin and Eosin…………………………………………..103 2.11.2. Masson’s trichrome…………………………………………...….104 2.11.3. Immunohistochemistry………………………...…………………105 2.11.4. Cross-sectional area measurement…………………………….105 2.11.5. Kleiner scoring system for non-alcoholic fatty liver disease…106 2.12. Statistical analyses…………………………………………………...…..109

3. CHAPTER 3 - Periconceptional alcohol consumption causes fetal growth restriction and increases glycogen accumulation in the late gestation rat placenta 3.1. Introduction………………………………………………………………………113 3.2. Materials and methods…………………………………………………………115

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3.2.1. Ethics…………………………………………………………………...….115 3.2.2. Animal treatment………………………………………………………….115 3.2.3. Gene analyses…………………………………………………….……...116 3.2.4. Protein analyses………………………………………………………….116 3.2.5. Immunohistochemistry…………………………………………………...117 3.2.6. Plasma analyses………………………………………………………….117 3.2.7. Statistical analyses……………………………………………………….117 3.3. Results……………………………………………………………………………118 3.3.1. Maternal parameters and plasma alcohol levels…………………...…118 3.3.2. Fetal weight, placental ratio and placental cross-sectional area…….119 3.3.3. Placental gene and protein expression………………………………...121 3.4. Discussion……………………………………………………….………………126

4. CHAPTER 4 - Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring which is exacerbated by a postnatal high-fat diet 4.1. Introduction………………………………………………………………………134 4.2. Materials and Methods…………………………………………………………136 4.2.1. Ethics………………………………………………………………………136 4.2.2. Rats and treatment……………………………………………………….136 4.2.3. Glucose and insulin tolerance test…………………………...…………137 4.2.4. Tissue collection…………………………………...……………………..137 4.2.5. qPCR and Western blotting……………………………………………..137 4.2.6. Calculations and statistical analyses………………………………...…138 4.3. Results…………………………………………………………………………...140 4.3.1. Maternal parameters and postnatal growth…………………………....140 4.3.2. GTT and ITT at 6 months………………………………………………..142 4.3.3. Hepatic gluconeogenesis………………………………………………..146 4.3.4. Peripheral insulin signaling………………………………………………149 4.3.5. Fetal liver expression of chromatin modifiers………………………….151 4.4. Discussion………………………………………………………………………..152

5. CHAPTER 5 - The effects of maternal alcohol intake around conception and a postnatal high-fat diet on adiposity in male and female rat offspring 5.1. Introduction………………………………………………………………………160 5.2. Materials and methods…………………………………………..……………...162 5.2.1. Ethics………………………………………………………………………162 5.2.2. Animal treatment……………………………………………………….…162 5.2.3. Body composition measurements………………………………………162 5.2.4. Tissue collection…………………………………………………….……163 5.2.5. Blood sampling and plasma biochemistry………………………..……163 5.2.6. Gene analyses……………………………………………………………163 5.2.7. Histological analyses…………………………………………………..…164 5.2.8. Statistical analyses…………………………………………………….…164 5.3. Results……………………………………………………………………………165 5.3.1. Animal model……………………………………………………………...165 5.3.2. PN30 outcomes…………………………………………………………..165 5.3.3. Adult offspring outcomes………………………………………………...165 5.3.3.1. Plasma biochemistry at 8 months………………………………169 5.3.3.2. Adipose tissue gene expression………………………………..170 5.3.3.3. Assessment of non-alcoholic fatty liver disease………………172 5.4. Discussion………………………………………………………………………..174

6. CHAPTER 6 – GENERAL DISCUSSION 6.1. Thesis summary…………………………………………………………………178 6.2. Relevance of animal model, dietary intervention and study design……….181 6.3. Fetal weight and offspring growth……………………………………………..183 6.4. The effects of periconceptional ethanol exposure on the placenta………..184 6.5. Long-term consequences of periconceptional alcohol exposure and a western diet………………………………………………………………………185 6.6. Proposed mechanisms – epigenetic modifications and initial development….190 6.7. Limitations and future directions……………………………………………....192 6.8. Conclusion and clinical implications…………………………………………..195

References………………………………………………………………………………..196 Appendix – publications attained throughout candidature

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List of tables

Table 1.1 Periconceptional programming of disease 13

Table 1.2 Animal models of prenatal alcohol exposure and 37 programming Table 1.3 The metabolic disease: Criteria and definitions 40

Table 1.4 The effects of cytokines and adipokines in regulation of 57 metabolism Table 2.1 Experimental liquid diet for untreated and ethanol treated 64 dams Table 2.2 Assay specifics for parameters analysed with Cobas Integra 77 400 plus Table 2.3 Modified assay standard procedure for insulin 80 radioimmunoassay Table 2.4 Modified assay standard procedure for leptin 82 radioimmunoassay Table 2.5 Assay procedure for plasma adiponectin ELISA 85

Table 2.6 Recipe for real-time PCR reactions with Taqman® and 96 SYBR® Green Table 2.7 Lysis Buffer 98

Table 2.8 Primers and probes used in thesis 99

Table 2.9 RIPA buffer recipe 101

Table 2.10 Antibodies used for western blotting and/or 103 immunohistochemistry in this thesis Table 2.11 Kleiner scoring system 107

Table 3.1 Maternal parameters 118

Table 3.2 Fetal and placental weights and dimensions at E20 120

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Table 3.3 Relative gene expression 125

Table 4.1 Offspring weights and weight gain of untreated (U) and 141 PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD) Table 4.2 Plasma glucose and insulin chemistry of untreated (U) and 145 PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD) Table 4.3 Relative mRNA levels of hepatic genes of untreated (U) and 148 PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD) Table 5.1 Body weight and plasma parameters at postnatal day 30 166

Table 5.2 Body and organ measurements at tissue collection and 168 during dual X-ray absorptiometry scan of body composition in male and female offspring aged 7-8 months Table 5.3 Fasting plasma profile of 8 months old male and female 170 offspring Table 6.1 Summary of the major findings in fetuses and adult offspring 177 following periconceptional ethanol exposure and a postnatal western diet

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List of figures

Figure 1.1 A schematic presentation of developmental origin of health 5 and disease Figure 1.2 Critical windows of development susceptible to programmed 9 disease Figure 1.3 Human versus rat preimplantation development 10

Figure 1.4 An illustration of the in utero orientation of the fetus and 23 placenta in rat Figure 1.5 Rat placentation 23

Figure 1.6 A diagram demonstrating cell differentiation in 25 vasculogenesis Figure 1.7 Metabolism of ethanol via the alcohol dehydrogenase 33 pathway and the MEOS system Figure 1.8 Prevalence of the metabolic syndrome in a worldwide 41 population 2004 Figure 1.9 Projected numbers of diabetics in a worldwide population by 42 2025 Figure 1.10 Schematic presentation of the insulin regulated intracellular 44 signal transduction cascade Figure 1.11 The regulation of glycogenolysis, glycogenesis, glycolysis 47 and gluconeogenesis Figure 2.1 Timeline of experimental protocol from treatment to 8 67 months post mortem Figure 2.2 Fetal and placental collection procedure on embryonic day 68 20 Figure 2.3 Measurement of fetal and placental dimensions on 70 embryonic day 20 Figure 2.4 Blood collection via tail tipping and tail slicing 73

Figure 2.5 Area under glucose and insulin curves 76

Figure 2.6 Insulin RIA standard curve generated with Assay Zap 79

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Figure 2.7 Standard curve generated with Assay Zap for determination 86 of adiponectin Figure 2.8 DXA-scan of body composition 87

Figure 2.9 Measurement of RNA concentrations using a Nanodrop 90 spectrophotometer Figure 2.10 The principle of Taqman® detection chemistry 93

Figure 2.11 The principle of SYBR® Green detection chemistry 94

Figure 2.12 A melt curve generated with SYBR® Green detection 95 chemistry Figure 2.13 An amplification plot generated by the real-time PCR system 96

Figure 2.14 Cross-sectional area of a placental section 106

Figure 2.15 Traits of NAFLD assessed with the Kleiner scoring system 108

Figure 3.1 Placental morphology following periconceptional alcohol 121 exposure Figure 3.2 The effect of periconceptional alcohol exposure on glucose 122 transporters in the placenta Figure 3.3 The effect of periconceptional alcohol exposure on gene and 124 protein expression of placental insulin like growth factors Figure 4.1 The effect of periconceptional alcohol exposure on fasting 143 plasma glucose and insulin, HOMA-IR and QUICKI scores Figure 4.2 The effect of periconceptional alcohol exposure on glucose 144 and insulin homeostasis Figure 4.3 The effect of periconceptional alcohol exposure on hepatic 147 mRNA levels Figure 4.4 The effect of periconceptional alcohol exposure on AKT and 150 GSK3β-protein in adipose tissue Figure 4.5 The effect of periconceptional alcohol exposure on the 151 expression of hepatic DNA methyltransferases on E20 Figure 5.1 Effects of periconceptional alcohol and high-fat diet on adult 167 offspring weight and body composition

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Figure 5.2 Effects of periconceptional alcohol and high-fat diet on 169 plasma leptin and adiponectin

Figure 5.3 Effects of periconceptional alcohol and high-fat diet on gene 171 expression in visceral abdominal adipose tissue

Figure 5.4 Effects of periconceptional alcohol and high-fat diet on the 173 development of hepatic steatosis in adulthood

Figure 6.1 A comparison between the human and rat preimplantation 181 development Figure 6.2 A simplistic presentation of the relationship between 189 periconceptional alcohol and its early and long-term metabolic consequences.

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List of abbreviations used in this thesis

11βHSD2 11-beta hydroxysteroid dehydrogenase

125I Iodine-125

ABC avidin-biotin complex

Acetyl-CoA acetyl coenzyme A

ADH alcohol dehydrogenase

AEC animal ethics number

AKT v-akt murine thymoma viral oncogene homolog PKB protein kinase B

ALDH aldehyde dehydrogenase

ANOVA analysis of variance

AOD assay on demand

ATP adenosine triphosphate

ATPIII adult treatment panel III

AUC area under the curve

AUGC area under the glucose curve

AUIC area under the insulin curve

β-cell beta cell

B0 reference tube

BAC blood alcohol concentration

BMC bone mineral content

BMD bone mineral density

BMI body mass index cDNA complementary deoxyribonucleic acid

CO2 carbon dioxide

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Ct cycle threshold

CVD cardiovascular disease

CYP2E1 cytochrome P450 2E1

DAB 3’3 diaminobenzidine tetrahydrochloride

DNA deoxyribonucleic acid

DNase deoxyribonuclease

DNMTs DNA methyltrasferases

DOHaD developmental origins of health and disease dsDNA double-stranded DNA

DXA dual-energy X-ray absorptiometry

E embryonic day of pregnancy

E- day prior to pregnancy

EDTA ethylenediaminetetraacetic acid ELISA enzyme-linked immunosorbent assay

EtOH ethanol

FAM 6-carboxyfluorescein

FAS fetal alcohol syndrome

FASD fetal alcohol spectrum disorder

FFA free fatty acids

FFM fat-free mass

Flt-1 FMS-related tyrosine kinase 1 (Vegfr-1) vascular endothelial growth factor receptor-1

FM fat mass

FOXO1 forkhead box protein O1

FRET fluorescence resonance energy transfer

G6pc glucose-6-phosphatase

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Gck glucokinase gDNA genomic deoxyribonucleic acid

Gjb3 gap junction beta-3 protein

GLUT facilitated glucose transporter (SLC2a1) solute carrier family 2

GOI gene of interest

GS glycogen synthase

GSK3β glycogen synthase kinase-3 beta

GTT glucose tolerance test

H&E hematoxylin and eosin stain

H2O2 hydrogen peroxide

H3Ack9 histone H3, lysine residue 9

HCl hydrochloric acid

HDAC histone deactylases

HDL high density lipoprotein

HFD high-fat diet (the western diet is referred to HFD in Chapter 4&5)

HOMA-IR homeostatic model for assessment of insulin resistance i.e id est i.p. intraperitoneal

ICM inner cell mass Igf1-2 insulin like growth factor 1-2 Igf1-2R insulin like growth factor 1-2 receptor Igfbp1 insulin like growth factor binding protein 1 IgG immunoglobulin G

IL-6 interleukin 6

IQ intelligence quotient

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IRS insulin receptor substrate

IRS-1 insulin like receptor substrate 1

ITT insulin tolerance test

IUGR intrauterine growth restriction

Kdr kinase insert domain receptor Vegfr-2 vascular endothelial growth factor receptor-2 LDL low density lipoprotein MAP mitogen-activated protein MD methionine deficient MEOS microsomal ethanol oxidizing system mRNA messenger ribonucleic acid MTORC2 mechanistic target of rapamycin complex 2 MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide N/A not available, not applicable n number Na+ sodium NAD nicotineamide adenine dinucleotide NADH nicotineamide adenine dinucleotide hydrate NAFLD non-alcoholic fatty liver disease NASH non-alcoholic steatohepatitis

NCEP US national cholesterol education program NF-κβ nuclear factor kappa-light-chain-enhancer of activated B cells NS not significantly different NSB non specific binding OD optical density ON overnight PAC plasma alcohol concentration PB phosphate buffer PBS phosphate buffered saline

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PC periconceptional Pck1 phosphoenolpyruvate carboxykinase PCR polymerase chain reaction PDK1 3-phosphoinositide-dependent protein kinase 1 PFA paraformaldehyde

Pgc-1α peroxisome proliferator-activated receptor gamma, coactivator 1α Ppargc1a (referred to Ppargc1a in Chapter 4)

Pgf placental growth factor PI phosphorylating phosphatidylinositol PIP phosphatidylinositol-4-phosphate

PIP2 phosphatidylinositol-4,5-bisphosphate

PIP3 phosphatidylinositol-3,4,5-triphosphate

PI3K phosphoinositide 3-kinase

PM post mortem PMS phenazine methosulfate PN postnatal day

PPARα peroxisome proliferator-activated receptor alpha

Prl prolactin PVDF polyvinylidene fluoride QC quality control qPCR quantitative polymerase chain reaction QUICKI quantitative insulin sensitivity check index RIA radioimmunoassay RIPA (buffer) radioimmunoprecipitation (buffer) Rn18s (18s) 18s ribosomal ribonucleic acid RNA ribonucleic acid RNase ribonuclease RT-PCR reverse transcription polymerase chain reaction SDS-PAGE sodium dodecyl sulphate polyacrylamide gel electrophoresis

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SEM standard error of the mean Ser serine SGA small for gestational age SIRT2 NAD-dependent deacetylase sirutin-2

Slc38a1,2,4 solute carrier family 38, members 1, 2 and 4 Sry sex determining region Y Std standard Syna syncytin TE trophectoderm cells TG triglyceride Thr threonine TNF-α tumor necrosis factor alpha trt treatment Tyr tyrosine U untreated Ucp1 uncoupling protein 1 VEGF vascular endothelial growth factor Vegfa vascular endothelial growth factor A VIC 2′-chloro-7′-phenyl-1, 4-dichloro-6-carboxyfluorescein VLDL very low density lipoprotein Vs. versus WD western diet (the western diet is referred to HFD in Chapter 4&5) WHO world health organization

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Symbols

~ approximately > greater than ≥ equal to or greater than < less than ≤ equal to or less than ± plus or minus α alpha β beta Δ delta γ gamma κ kappa x multiplied by

Units of measurements

% percent Ω ohm oC degree Celsius µg microgram µL microliter µm micrometer μU microunit cm centimeter cpm counts per minute dL deciliter E% energy percentage

xxxiii g centrifugal force gravity g gram k kilo kD kilo Dalton kg kilogram L liter m meter M molar mg milligram MJ mega joule mL milliliter mm millimeter mmHg millimeters of mercury mmol millimol ng nanogram nm nanometer psi pounds per square inch rpm revolutions per minute U unit V volts v/v volume per volume

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Chapter 1 Review of Literature

CHAPTER 1

Review of Literature

1.1 Introduction

The metabolic syndrome is a cluster of conditions that includes insulin resistance, hypertension, dyslipidaemia and central obesity (Eckel et al., 2005, Grundy, 2008). This disease is often accompanied by other medical conditions such as fatty liver, depression, obstructive sleep apnoea and cholesterol gallstones (Grundy, 2008) – all of which constitutes an economic burden for both the individual and society. Although the prevalence of metabolic syndrome declined over the last year, 56% of the U.S population are currently obese, and insulin resistance is projected to affect 366 million Americans by 2030 (Beltran-Sanchez et al., 2013, Wild et al., 2004). Many factors contribute to this: a sedentary lifestyle; low energy expenditure; and the easy access to highly calorific food (Bell et al., 2005). However, epidemiological and experimental studies now highlight the periconceptional (PC) and prenatal periods as critical for long-term development – suggesting a suboptimal in utero environment may program adult disorders. This idea originates in the ‘Barker hypothesis’ after David Barker with colleagues discovered a link between low birth weight, mortality rates from stroke and cardiovascular disease (CVD) and poor maternal nutrition in the UK (Barker and Osmond, 1986). The ‘Barker hypothesis’ – now referred to as ‘developmental origin of health and disease’ (DOHaD) – escalated to include other maternal perturbations (present both during pregnancy and/or during early postnatal life) including: maternal obesity (Samuelsson et al., 2008), diabetes (Honda et al., 1990, Moley, 1999) overnutrition (Rattanatray et al., 2010), glucocorticoid exposure (Cuffe et al., 2012), micronutrient deficiency (Maloney et al., 2011) and alcohol intake (Chen and Nyomba, 2004, Lopez-Tejero et al., 1989). Altered birth phenotypes, including low birth weight (Langley and Jackson, 1994, Kwong et al., 2000, Watkins et al., 2011, Probyn et al., 2012, Chen and Nyomba, 2003a, Pennington et al., 2002) and altered organ development, either independently or in association with other maternal perturbations (Louey et al., 2000, Wlodek et al.,

Chapter 1 Review of Literature

2007) is commonly seen in these models, increasing the susceptibility to adult diseases such as insulin resistance, CVD, anxiety, fatty liver. Interestingly, many of these phenotypes have been demonstrated following maternal alcohol consumption (Chen and Nyomba, 2003b, Chen and Nyomba, 2004, Yao et al., 2006, Pennington et al., 2002), a common social habit amongst women of childbearing age. These studies (like most DOHaD studies) examined the effects of alcohol when consumed prenatally, often throughout pregnancy, although women are far more likely to drink in the PC period, before awareness of their pregnancy (Nykjaer et al., 2014, Kesmodel, 2001, Carmichael et al., 2003, Colvin et al., 2007, Mullally et al., 2011).

The PC period (defined in this thesis as the time prior to conception until blastocyst implantation) is now regarded as a ‘critical window of development’ as it coincides with important stages of embryonic development including: cell division, genome activation and epigenetic reprogramming. Animal models examining PC insults (often nutritional perturbations, such as under- and overnutrition, low protein diets and vitamin deficiency) demonstrate similar adult outcomes as those exposing the fetus during the entire pregnancy (Watkins et al., 2011, Joshi et al., 2003, Jaquiery et al., 2012, Rattanatray et al., 2010, Sinclair et al., 2007). Alcohol has the ability to diffuse into the oviduct and uterus (Mitchell, 1994) and affect blastocyst development and implantation (Mitchell, 1994, Mitchell and Goldman, 1996, Cebral et al., 1999, Cebral et al., 2000). However, no one has examined the long-term effects of periconceptional alcohol consumption (PC:EtOH) in developmental programming.

This thesis reviews the literature regarding DOHaD, focusing on maternal alcohol intake (both prenatal and periconceptional) as the maternal insult. Consideration is then given to placental insufficiency as a mechanism, and metabolic outcomes in the adult offspring. Many experimental studies suggest females to be ‘protected’ from programmed adult disease as prenatal insults typically generates sexually dimorphic differences – with stronger phenotypes frequently seen in male offspring (Di Renzo et al., 2007, Smith et al., 2010, Watkins et al., 2011, Maloney et al., 2011). More recent evidence suggest that postnatal stressors and ‘second hits’ (for example dietary modifications, pregnancy itself, stress or disease) can reveal or exacerbate a programmed phenotype, often in both males and females (Rueda-Clausen et al., 2011, Chen and Nyomba, 2003b). This highlights the significance to consider both sexes in experimental studies; and the influence of environmental factors on the

Chapter 1 Review of Literature

future disease picture. This will serve as a rationale for the subsequent studies in this thesis, which aimed to determine whether maternal PC alcohol intake: (1) affects placental biochemistry; (2) increases the susceptibility of the adult rat offspring to develop metabolic dysfunction; and (3) interacts with a postnatal consumption of a western diet (WD) to reveal or exacerbate this phenotype.

Chapter 1 Review of Literature

1.2 Developmental origins of health and disease (DOHaD)

Over the last 20-25 years, a concept has developed that maternal insults during pregnancy can program the risks for adult diseases in the offspring (Barker, 2004). David Barker and his colleagues in the United Kingdom were the first group to publish the theory of ‘early’ or ‘fetal origins of adult disease’, after discovering a link between low birth weights and mortality rates from stroke and CVD in specific geographical regions. The group suggested that poor maternal nutrition and health contributed to a high rate of neonatal death, and that surviving children (often born small) had a greater risk of dying from CVD as adults compared with children born to healthy mothers (Barker and Osmond, 1986). The ‘Barker hypothesis’ generated large interest worldwide and was soon replicated in a number of other studies (Frankel et al., 1996, Rich-Edwards et al., 1997, Leon et al., 1998, Stein et al., 1996). Barker later proposed humans to be ‘plastic’ and able to adapt to the intrauterine environment. He explained ‘developmental plasticity’ as the ability of a genotype to respond to a critical intrauterine environment and produce more than one alternative phenotype (Barker, 2004).

1.2.1 The thrifty phenotype

The ‘thrifty phenotype’ hypothesis extends developmental plasticity further. This theory suggests that the fetus can respond to a suboptimal intrauterine environment by preserving the growth of key organs (eg, the brain) on the expense of less important organs, (eg, the liver, pancreas and muscle) to increase its chance to survive in the poor in utero conditions. (Gluckman et al., 2005, Barker, 2004, Hales and Barker, 2001). These responses, however, may induce permanent alterations in tissue gene expression, metabolic pathways and epigenetic regulations that affects the offspring’s risk of developing diseases in adulthood (Lucas, 1991) (Figure 1.1). Gluckman and Hanson (2006) have presented ‘the predictive adaptability hypothesis’, which states that the fetus, based on its intrauterine environment can ‘predict’ its postnatal environment to gain a competitive advantage postnatally. When the fetus experiences a mismatch between the pre- and postnatal environments, these early adaptations becomes unfavorable.

Chapter 1 Review of Literature

Used interchangeably, these theories describe and highlight the importance of how suboptimal in utero environments can result in adult diseases.

Maternal insults Global over/undernutrition, gestational diabetes, obesity, anemia, stress, smoking, alcohol intake, drug abuse, protein malnutrition, hypoxia, vitamin deficiency

Placental insufficiency Nutrient and oxygen deficits

Fetal programming Organ remodeling, altered growth patterns, disruptions in endocrine pathways, epigenetic modifications

Adipose tissue Skeletal muscle Pancreas Liver Kidney Cardiovascular Brain lipogenesis insulin insensitivity beta-cell failure gluconeogenesis nephron number blood pressure leptin resistance lipid accumulation lipid accumulation insulin secretion lipogenesis HPA-axis behavior lipid accumulation

Adult diseases Hyperinsulinemia, hyperglycaemia, insulin resistance, obesity, high blood pressure, cardiovascular disease, anxiety, kidney disease, osteoporosis

Figure 1.1 – A schematic presentation of developmental origin of health and disease The concept ‘developmental origin of health and disease’ states that maternal insults during pregnancy can interfere with fetal development via a range of different mechanisms that independently, or in combination can increase the susceptibility, or ‘program’ the fetus for adult onset disease.

1.2.2 Prenatal famine exposure

Although tragic, one of the best human ‘experiments’ of programming of disease which provides supportive evidence to the 'thrifty phenotype hypothesis' and highlights the importance of the timing of exposure is the ‘Dutch hunger winter’. Between September 1944 and May 1945, the Netherlands were facing an extremely severe winter which combined with war rations resulted in people, including pregnant women, having a daily energy intake of 400-1600 calories (Hart, 1993). The pattern of undernutrition differed between pregnancies: some women were undernourished

Chapter 1 Review of Literature

throughout pregnancy, others during one specific trimester, or prior to or after birth. Long term follow up studies on offspring has provided significant insights regarding the timing of exposure, as different exposure periods generated different health outcomes. For example, babies exposed to starvation during early but not late gestation were more likely to develop obesity and CVD as adults (Barker et al., 1990), whereas the lipid profile was altered in all exposure groups of the Dutch famine (Glazier et al., 1992). It was also found that adverse adult health outcomes could arise despite normal birth weights (Barker et al., 1990). Other observational studies following natural famine events showed similar results: many babies exposed to the 19th century crop failure in Sweden (Moore et al., 1996), or to the Great Leap famine in China (Roberts et al., 2008) developed adult CVD and diabetes; and individuals prenatally exposed to malnutrition in the Leningrad siege study had an increased risk of adult obesity (Winder et al., 2011). Collectively, prenatal famine outcomes strengthen the evidences that elements of metabolic disease can be programmed.

1.2.3 Intrauterine growth restriction

Intrauterine growth restriction (IUGR) refers to a condition in which the fetus is smaller than it should be at a certain gestational age (Varvarigou, 2010). This is dissimilar to preterm infants, whom are not always born small for their gestational age (Wilcox, 2001). Small for their gestational age (SGA) infants may however be small because of IUGR – or they may be small despite following a normal growth pattern in utero (Varvarigou, 2010). Thus IUGR and SGA should not be used interchangeably. Low birth weight – which is a good indication of IUGR – is defined as birth weight and/or length being at least two standard deviations below the mean for gestational age of the overall reference population (Gluckman et al., 2007). The number of babies born with low birth weight increased by nearly 20% between 1990 and 2006 and affected ~8% of all babies worldwide in 2009 (Martin et al., 2011). As a baby’s birth weight is influenced by complex interactions between maternal, placental and fetal factors (Varvarigou, 2010), a low birth weight – which is associated with adult disease (Eriksson et al., 2000, Stein et al., 1996) – can result from dysregulations in all these factors.

Chapter 1 Review of Literature

1.2.4 Catch-up growth

~85% of SGA babies experience ‘catch-up growth’ postnatally (Albertsson-Wikland et al., 1993), accelerating their growth rate to restore weight, length and head circumference by late childhood (Eriksson et al., 1999). This increases the risk for high body mass index (BMI), blood pressure and insulin resistance already during adolescence (Jaquet et al., 2000, Crowther et al., 1998). Crowther et al. (1998) reported that SGA children who underwent a rapid catch-up growth became glucose intolerant already at age 7 in a South African cohort. Similar result were found by Eriksson et al. (1999), who also demonstrated that boys born thin (a factor of IUGR) in conjunction with accelerated postnatal growth had the highest mortality rate from coronary heart disease (Eriksson et al., 1999).

It is likely that SGA babies accelerate their postnatal growth to compensate for the previously constrained growth pattern, but the mechanism linking catch-up growth to adult disease is unclear. One suggestion is that increased adiposity contributes to the adverse metabolic phenotypes commonly seen in these children, as an accelerated growth pattern is more beneficial for fat mass than lean mass (Hediger et al., 1998). This is supported by Leunissen et al. (2008) who suggest that fat accumulation – independent of birth size – is the only significant marker of insulin insensitivity. The group refers to this as the ‘fat accumulation hypotheses’ and proposes that growth acceleration only becomes problematic when it causes fat accumulation (Leunissen et al., 2008), because increased fat mass is associated with dysregulation of free fatty acids and adipocytokines (Van Gaal et al., 2006) which affect insulin sensitivity (see section 1.7.2.2.2).

Chapter 1 Review of Literature

1.3 Timing of exposure to a sub-optimal environment

As evident from the famine studies, the timing of exposure to an insult plays a large role in determining the outcome of disease. There are many ‘critical developmental windows’ in which the embryo or fetus is at higher risk of being programmed to adult disease (Figure 1.2). Some of the better understood ones are organogenesis and early postnatal growth – as the exposure period often coincides with the developmental stage of a particular organ or organ system. More recent studies have also started to recognize the PC period (prior to conception until blastocyst implantation) as a critical developmental window. The following sections review the importance of the timing of exposure.

Chapter 1 Review of Literature

Susceptible events Programming mechanism Adult disease Primordial germ cell Mature germ cell Ovulation Fertilization Epigenetic regulation conception - - Differentiation Cell cycle regulation Implantation Insulin resistance Pre Pre implantation

Placentation Placental insufficiency Glucose intolerance Organogenesis Adaptive, hormonal, Diabetes Fetal growth and developmental development of Cardiovascular integrated systems disease Organ remodeling Maximal fetal growth Kidney disease Gestation Disruptions in metabolic pathways and endocrine Osteoporosis Prepartum maturation functions

Birth Stress

Mismatch of environments Obesity Accelerated growth Hyperphagia

Suckling Environmental factors Dyslipidemia

Weaning Nutritional modifications Anxiety - Western diet - High salt diet High blood pressure Unmasking/ Disease exacerbating programed Metabolic syndrome - ischemia/reperfusion phenotype - diabetes Allergies Postnatal life Pregnancy

Stress

Figure 1.2 – Critical windows of development susceptible to programmed disease A summary of some of the critical developmental windows identified as vulnerable to maternal perturbations. This highlights the susceptible events and potential mechanisms which may program adult disease.

Chapter 1 Review of Literature

1.3.1 The periconceptional period

The PC period is defined as a time prior to conception until blastocyst implantation. In this thesis, this time span is defined as 4 days prior to conception until embryonic day (E)4. This definition does however differ between studies, and the length of the preimplantation development varies between species, which complicates the comparison of results.

To fully understand the concept of PC programming, it is important to be familiar with the preimplantation development. Therefore, before discussing the PC period in programming of disease, a brief presentation of embryonic development is provided.

1.3.1.1 Preimplantation development

Human Implantation

Fertilization 1-cell 2-cell 4-cell Early blastocyst 0 1 2 3 4 5 6 7 8 9 10

Fertilization 1-cell 2-cell 4-cell Early blastocyst

Implantation Rat

Figure 1.3 – Human versus rat preimplantation development A comparison between the preimplantation blastocyst in human (pink) compared with rats (blue).

In mammals, the fertilization of the oocyte and sperm occur in the ampulla of the oviduct, from which the fertilized zygote must travel to the uterus to implant as a blastocyst. This time span – referred to as ‘preimplantation development’ – marks the beginning of embryogenesis and precedes pregnancy recognition (Watson, 1992). Complex hormonal and metabolic interactions are occurring between the embryo and maternal environment at this stage (Watson, 1992, Watson and Barcroft, 2001). Processes fundamental for a successful preimplantation development including: zygote cleavage divisions, genomic activation, compaction and cavitation, ultimately result in an attachment-competent blastocyst on E4 (Watson, 1992, Watson and Barcroft, 2001).

Chapter 1 Review of Literature

The replication of cell numbers up to the 8-cell stage in which compaction – the initial event of morphological transition and cellular differentiation – begins in both human and rat are relatively synchronous (Hardy et al., 1989, Reeve, 1981, Pratt et al., 1982). During compaction, the cells become compressed to maximize cell contact and to develop intercellular junctions (Watson, 1992). At the 16-cell stage, the embryo becomes double layered with two distinct cell populations; the polarized blastomeres on the outside; and the apolar blastomeres on the inside (Watson, 1992). In a successful implantation, the cell mass becomes uniform to form a morula (Ducibella and Anderson, 1975). In the morula, the outer cells give rise to specialized trophectoderm cells (TE) (which later differentiate into trophoblasts to mediate attachment to the uterine wall); and the inner cells forms the inner cell mass (ICM) (which later form all the tissues of the embryo’s body) (Jones and Thomson, 2000, Watson and Barcroft, 2001, Watson, 1992). The trophoblast lineage is also essential for placental development – the first organ to be formed in embryogenesis (Scharfmann, 2000).

During cavitation (following compaction and the differentiation of the TE from the ICM), the morula becomes a blastocyst (Watson, 1992, Watson and Barcroft, 2001). At E4 in rat and E5-7 in human, the blastocyst reaches the uterus, however since it is not yet implanted in the uterine wall, it is still considered a preimplantation embryo (Aplin, 2000). In the uterus, the blastocyst ‘hatches’ out of the zona pellucida, which protectively has surrounded the oocyte to prevent implantation in the oviduct wall. Implantation usually starts late on E5 in the rat and is completed late on E6 (Mitchell, 1994). In the human, implantation normally occurs between 7-11 days after ovulation (Aplin, 2000). Pregnancy is not recognized until successful implantation, thus successful blastocyst formation is crucial for the establishment of pregnancy. The similar temporal embryonic development between human and rat is demonstrated in Figure 1.3.

1.3.1.2 Programming of metabolic outcomes by periconceptional exposures

Via largely unknown mechanisms, the preimplantation embryo is able to sense and react to the maternal environment. Animal models of PC programming have started to provide evidence of how maternal insults; preceding both implantation and conception are capable to program adult disease. These studies have mainly 11

Chapter 1 Review of Literature

focused on maternal dietary modifications including: low protein diets (Watkins et al., 2011, Kwong et al., 2000), global undernutrition (Gardner et al., 2004), increased energy intake (Rattanatray et al., 2010) and methionine deficient (MD) diets (Maloney et al., 2011, Sinclair et al., 2007). Table 1.1 summarizes maternal PC perturbations and the programmed metabolic phenotype.

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Table 1.1 Periconceptional programming of disease PC insult Species Exposure period Timing of exposure Phenotype Reference

Increased systolic blood pressure in adults (Watkins et al., Mouse 0-3.5 days gestation Increased body weight (adult females only) 2011)

9% compared with isocaloric Increased systolic blood pressure at 21 weeks (Watkins et al., Mouse -3.5 days until mating normal protein controls (18%) Attenuated vasodilation 2008)

Low birth weight Rat 0-4.25 days gestation Accelerated postnatal growth (Kwong et al., 2000) Adult hypertension Low proteinLow diet Increased blood glucose levels at 94 days Rat 50% of normal protein intake -8 weeks until mating (Joshi et al., 2003) Increased blood cholesterol at 180 days

Increased pulse pressure (Gardner et al., Sheep Reduced rate pressure product 2004) 50% of normal calorie intake 0-30 days gestation (Gardner et al.,

Sheep No effect on glucose tolerance 2005)

Fasted for 2 days, then Increased plasma insulin response to a glucose concentrates of 1-2% of body Sheep -61-30 days gestation load (E115 fetus) (Oliver et al., 2001) weight per day (control group Increased plasma taurine levels (E115 fetus) received 3-4% and no fasting)

Undernutrition Individually adjusted feeding -61-0 days and -2-30 days Greater % fat mass and perirenal rat at 3-4 (Jaquiery et al., Sheep regimen to achieve and gestation years of age (males only) 2012) maintain a weight loss of 10- Sheep 15% body weight -61-30 days gestation Glucose intolerance at 10 months of age (Todd et al., 2009)

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Table 1.1 Periconceptional programming of disease (cont.) PC insult Species Exposure period Timing of exposure Phenotype Reference

Lower plasma glucose and higher plasma insulin levels at birth (males only) Sheep 70% of energy requirement -28-7 days gestation (Smith et al., 2010) Increased insulin response to a glucose load (males only)

Altered expression of microRNAs associated 70% of the energy requirement Sheep -60-6 days and 0-6 days with alterations in the insulin signaling (Lie et al., 2014) during treatment period pathway Undernutrition

-5 months-preimplantation 170-190% maintenance energy when embryos were Increased body fat mass in females at 4 (Rattanatray et al.,

- Sheep requirements transferred to non-obese months of age 2010) ewes Over nutrition

-2 months-6 days Increased body weight and body fat in gestation when embryos Folate, vitamin B12 and adulthood (Sinclair et al., Sheep were transferred to methionine deficient diet Insulin resistance 2007) normal fed surrogate Elevated blood pressure mothers

Folate, choline and methionine (Maloney et al., Rat -3 weeks-5 days gestation Glucose intolerance at 6 months (males only) deficient diet 2011) Vitamin deficiency

PC, periconceptional

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1.3.1.3 Mechanisms of programming in the periconceptional period

A few research groups have attempted to mechanistically describe programming of disease following periconceptional insults. Kwong et al. (2000) showed that PC low protein diets in rat caused hypertension in the offspring. They linked this to changes in both the maternal environment (dams were mildly hyperglycaemic and deficient in insulin and essential amino acids); and to the blastocyst development (the early blastocyst displayed reduced cell numbers within the ICM and the mid/late stage blastocyst had reduced cell number in the TE linages). Maternal hyperglycaemia has previously been shown to impact on the preimplantation embryo (Moley, 1999). For example, rat blastocysts (E5) incubated in a hyperglycaemic environment in vitro have overall a reduced number of cells (but more apoptotic cells) in the ICM (Pampfer et al., 1997).

The preimplantation embryo is extremely responsive to its environment and susceptible to epigenetic perturbations, mechanisms believed to play a role in programming of disease (Ikeda et al., 2012). Sinclair et al. (2007) exposed female sheep to a folate, vitamin B12 and MD diet 8 weeks prior to until 6 days after conception, before transferring the embryos to normal fed surrogate mothers. The birth weights were unaffected by the MD diet, but the older offspring weighed more, had increased body fat percentage, elevated blood pressure, and were insulin resistant. All phenotypes were exaggerated in male offspring. A restriction landmark genome scanning in liver of 90d old offspring demonstrated altered methylation status of 4% of the 1.400 CpG loci studied, with 88% of the loci being unmethylated or hypometylated (Sinclair et al., 2007). This supports the concept that an insult exclusively present during the PC period can cause epigenetic alterations in offspring deoxyribonucleic acid (DNA). Similarly, a MD diet administered to rats in the PC period (3 weeks prior to conception until 5 days after) caused glucose intolerance in male offspring aged 26 weeks (Maloney et al., 2011).

The origins of periconceptionally programmed disease may also be due to events occurring well beyond the exposure time. Watkins et al. (2011) showed increased gene expression of insulin receptor and the insulin like growth factor 1 receptor (Igf1R) in white adipose tissue and reduced uncoupling protein 1 (Ucp1) in brown

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adipose tissue in adult female mice following PC low protein diet, which they suggested explained the energy storing phenotype.

Alcohol in periconceptional programming is discussed in section 1.6.6.1.

1.3.2 Prenatal programming of metabolic outcomes

Prenatal perturbations have been extensively investigated in DOHaD to study programming of metabolic disease and shall not be reviewed here is great detail (for review see (Brenseke et al., 2013, Langley-Evans and McMullen, 2010)). Soon after Barker proposed his hypothesis, Langley and Jackson (1994) reported that rat offspring of protein restricted dams (9 or 6% throughout pregnancy) had elevated systolic blood pressure at 9 and 21 weeks. This was associated with increases in pulmonary angiotensin-converting enzyme activity. Similar increases in systolic blood pressure at various ages have been demonstrated in a number of protein restricted animal models in which the diet has been maintained throughout pregnancy (Langley-Evans et al., 1996a, Langley-Evans et al., 1996b, Nwagwu et al., 2000, Brawley et al., 2003, Langley-Evans et al., 1999), often accompanied by changes in kidney nephron number (Langley-Evans et al., 1999) and altered kidney function (Langley-Evans et al., 1999, Nwagwu et al., 2000, Langley-Evans et al., 1996a). Other components of programmed metabolic diseases following a prenatal perturbation includes insulin insensitivity and glucose intolerance which has been demonstrated in models of maternal undernutrition (Vickers et al., 2000), glucocorticoid exposure (Drake et al., 2005) and maternal protein restriction (Ozanne et al., 2003). Underlying mechanisms to programmed glucose- and insulin homeostasis, the main focus of this thesis, are discussed further in section 1.6.6.2 and in section 1.7.1.4.

1.3.3 Interactions between prenatal and postnatal environments

As discussed in section 1.2.1, a suboptimal fetal environment alone can be detrimental – but it is often the mismatch between the predicted and experienced postnatal environment that causes permanent changes in offspring physiology. Evidence for this is derived from cross-fostering studies. Ozanne et al. (2004) showed that prenatally protein restricted male mice cross-fostered to control dams experienced a fast catch-up growth despite being born small, whereas control pups

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cross-fostered to low protein fed dams were growth restricted at weaning. Similarly, Gorski et al (2006) showed that obese-prone rat pups cross-fostered to obese- resistant dams improved their insulin sensitivity, despite remaining obese. Correspondingly, obese-resistant pups cross-fostered to genetically obese dams increased their adiposity, and insulin and leptin receptors (Gorski et al., 2006).

Also a later deviant postnatal environment can exacerbate or unmask disease originally programmed in utero (Eriksson et al., 1999). Most studies investigating this have focused on the postnatal diet, including diets rich in salt or fat, however this ‘second hit’ can also be exposure to other factors such as stress, pregnancy or disease. Yan et al (2014) showed that male offspring of dams with induced gestational diabetes had an accelerated blood pressure change at 20 weeks of age when fed a high salt diet (8%) after weaning. Petry et al (2007) showed that rats exposed to a low-protein diet (8%) in utero and during lactation had an additive risk of developing high blood pressure when consuming a cafeteria style diet for 70 days at 1 year of age compared with rats of either one exposure. Consistently, rats exposed to undernutrition (30%) throughout gestation and fed a hyper-caloric diet (30% fat) from weaning had higher systolic blood pressure at 14 weeks of age compared with rats of either one exposure (Vickers et al., 2000). Chen and Nyomba (2003b) found an interactive effect of in utero EtOH-exposure and a postnatal high- fat diet, in which rats exposed to both conditions displayed an exacerbated increase in glucose intolerance and insulin secretion following a glucose load. More recently, Shen et al (2014) demonstrated a significantly increased susceptibility to non- alcoholic fatty liver disease (NAFLD) in female rat offspring prenatally exposed to EtOH (E11-E20) after consuming a high-fat diet since weaning.

The influence of the postnatal environment is important as it may reveal in utero programmed diseases, but also because food preferences themselves can be programmed (Brenseke et al., 2013). Bellinger et al (2004) found that rat offspring exposed to protein restriction in utero preferred a high-fat diet over diets rich in carbohydrates or protein at 12 weeks of age. While this demonstrates how a certain food pattern might be the preferred one (and therefore a likely change of the postnatal environment), it is important to emphasize that the dosage used in animal studies are not always comparable to a human scenario. For example, the 8%

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sodium diet used in the study by Yan et al (2014) has 16-fold higher sodium levels compared with the recommended rodent diet of 0.5% sodium (Martus et al., 2005). For a human, that would be equivalent to a daily intake of 32g sodium (recommended intake is <2g/d). The mean sodium intake (globally) was however estimated to 3.95g daily in 2010 (Powles et al., 2013) and therefore the physiological relevance of such experiment is limited. Secondly, the time point by which the ‘second hit’ is introduced is not always realistic. It is for example questionable that a 30% undernutrition throughout pregnancy changes to a hyper-caloric diet containing 30% fat from the day of weaning, as was the case in Vickers et al (2000) study; or that a normal diet during weaning changes to a high-fat diet after weaning (when the rat is only 28-30 days old) as in the study of Shen et al (2014). Introducing a dietary intervention (as a second hit) is more realistic later in life, for example at a time point equivalent to a teenager moving out of home.

1.4 Sex differences in fetal programming

There is a general belief that male fetuses are more vulnerable to the in utero environment, while females have been assumed to be ‘protected’ from programmed disease. This is because adverse pregnancy outcomes including miscarriage, rupture of the fetal membranes and premature birth, are more common when the fetus is a male (Di Renzo et al., 2007). Women carrying male fetuses also have higher rates of gestational diabetes mellitus, fetal macrosomia, cord prolapse and true umbilical cord knots (Sheiner et al., 2004) and are more likely to deliver via caesarean section (Ingemarsson, 2003). Some of these sex differences may be attributable to the fact that male fetuses grow more quickly – even during embryogenesis (Mittwoch, 1993) – and have higher nutritional demands during pregnancy compared with females (Pedersen, 1980).

Many epidemiological studies support gender disparities in fetal programming. Flanagan et al (2000) showed that men who were lighter or shorter at birth were insulin insensitive at 20 years of age, but the same correlation was not found in growth restriction females. This is consistent with other epidemiological (Fall et al., 1995, Hales et al., 1991) and animal studies (Desai et al., 1997). Desai et al (1997) showed that male, but not female offspring prenatally exposed to protein restriction were glucose intolerant at 12 weeks of age. Gender disparities have also been 18

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demonstrated following PC perturbations. For example, in the study of Sinclair et al (2007) with the MD diet (see section 1.3.1.3) the insulin resistance and increased blood pressure were more pronounced in male offspring. A PC MD diet has also been shown to increase the homeostatic model for assessment of insulin resistance (HOMA-IR) and cause glucose intolerance in male, but not female rat offspring (Maloney et al., 2011). In the study by Kwong et al (2000), the PC low protein diet increased the systolic blood pressure in male offspring only.

Because of these and other studies, males are believed to “live dangerously in the womb”. In their efforts to maximize overall body weight and size (in the presence of an in utero perturbation) other organs and tissues may become compromised and increase the susceptibility to disease. Differences in the levels of sex hormones are believed to contribute to sex-specific effects, as they may have an influence both during fetal and postnatal life (Reckelhoff et al., 1998). Ojeda et al (2007a) found that IUGR male rat offspring became hypertensive at 16 weeks of age due to elevated testosterone levels whereas their female counterparts were protected by estrogen. Furthermore, they demonstrated how castration alleviated male hypertension (Ojeda et al., 2007b). These results have caused many researchers to only study male offspring in developmental programming. Many researchers also only consider offspring at a younger age, while studying female offspring may be more important later in life considering the change in estrogen levels in menopausal women. Indeed, the hypertension incidence increases in humans after menopause (Schulman et al., 2006); and ovariectomy induces hypertension in IUGR female rat offspring already at a younger age (Ojeda et al., 2007a).

The mechanisms underpinning the sex differences in programming are unknown but current research has focused on differential placenta responses of males and females to a gestational insult. In order to understand the role of the placenta in sex- specific programming, it is important to understand how the placenta develops and functions.

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1.5 The role of the placenta in fetal programming

Adult disease can be programmed by alterations in the development of specific organs or organ systems that are developing at time of exposure. The placenta – the first organ to form in embryogenesis – unites the fetal and maternal environments, produces hormones and serves as a site for exchange of nutrients, gases and waste products between the mother and the fetus (Salafia et al., 2007). Thus disrupted placental function will greatly impact on development and birth weight. It is suggested that any genetic or environmental insult that interferes with placental development, nutrient transport or vascularization at any stage of gestation can cause placental insufficiency, fetal growth retardation and death (Scharfmann, 2000). Thus a healthy and normally functional placenta is essential for a successful pregnancy outcome.

Although PC exposures precede organogenesis, it may still impair the initial clustering of embryonic cells that later will form both the placenta and embryo proper. As this thesis investigated the role of the placenta in PC programming, a brief introduction to placentation, utero-placental insufficiency, and placenta in fetal programming will be provided in the following sections.

1.5.1 Placentation in human and rat

Rat models have become important in placental studies due to the strikingly similarities to human placentation and organization: both have a hemochorial placenta where the maternal blood has direct contact with the chorion; the placentas are discoid shaped; the intrauterine trophoblast invasion is deep (compared with the mouse placenta) (Ain et al., 2003); and the uterine implantation is similar (Soares et al., 2012). There are, however still some differences in the timing of placentation and in placental structure. The following paragraphs will therefore compare some of the main events in rat and human placentation.

In human development, the trophoblast cell line starts to differentiate 4-5 days post- conception (between the morula and blastocyst stage). Following differentiation, the blastocyst consists of an ICM (which later forms the embryo, umbilical cord and placental mesenchyme); and a surrounding layer of mono-nucleated trophoblasts (which later forms the placenta and fetal membranes) (Huppertz, 2008). Placentation

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(and the implantation period) starts 6-7 days post-conception, when the blastocyst hatches from the surrounding zona pellucida and attaches to the uterine epithelium (Aplin, 2000). During the pre-lacunar stage (first stage of implantation) the polar trophoblasts (the outer layer of trophoblast cells) orient the blastocyst and fuse with the uterine and syncytial epithelium to form an oligo-nucleated syncytiotrophoblast – the first embryonic tissue with direct contact to maternal cells and fluids (Huppertz, 2008). Remaining cytotrophoblast cells (from the mono-nucleated trophoblast linage) act as stem cells, fusing with and expanding the syncytiotrophoblast (Potgens et al., 2002). In the lacunar stage (8 days post-conception), the syncytiotrophoblast exhibits fluid filled spaces which merges to generate larger lacunae; while the spaces around and between the lacunae (the trabeculae) forms the placental villous tree. The lacunae/trabeculae later develop into the intervillious space. At this stage, the placenta also consists of an early chronic plate (facing the embryo), and the primitive basal plate (facing the maternal endometrium) (Huppertz, 2008). Invading syncytiotrophoblast cells starts to penetrate the interstitium of the endometrium, to create contact with maternal capillaries. To prepare the maternal system for pregnancy, these cells starts to surround the uterine spiral arteries and stimulate maternal blood flow to the implantation site via endocrine signaling (Hertig et al., 1956). Implantation is finalized at around 12 days post-conception, when the embryo and surrounding tissues are completely embedded in the endometrtium (Huppertz, 2008). During the villous stage of placental development (13 days post-conception), the trophoblasts starts to differentiate into primary villi. As the mesenchyme invades the primary villi, their size increases to generate secondary chorionic villi (21 days post-conception) (Kingdom et al., 2000). This coincides with the formation of the first placental blood- and endothelial cells, independent of the vascular system (Dempsey, 1972). As the secondary villi undergo vasculogenesis to form tertiary chorionic villi, the villous trees – the major regulatory site for transplacental transport of nutrients and waste – are complete (Kingdom et al., 2000, Chaddha et al., 2004).

In contrast to human placentation, rat placentation starts on E3.5 (Watson and Cross, 2005). Embryo implantation occur at the anti-mesometrial side of the uterus already around E4.5, whereas the placental formation takes place at the mesometrial side (de Rijk et al., 2002) (Figure 1.4). The placenta develops from the extraembryonic ectoderm (the outer layer of the blastocyst, also referred to as the 21

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TE), as it differentiates into chorionic ectoderm (which later forms the labyrinth) and the ecoplacental cone (which later forms the spongiotrophoblast) (Soares et al., 2012, Bissonauth et al., 2006). Around E8.5, the chorionic ectoderm and allantoic mesoderm fuse together to form the labyrinth zone – the exchange region in the rat placenta (analogous to the human villous tree) (Bissonauth et al., 2006). The labyrinth zone consists of: maternal and fetal blood vessels, endothelial cells, and the syncytiotrophoblasts and cytotrophoblasts which together form the interhemal membrane – a selectively permeable barrier between the maternal and fetal circulation (Coan et al., 2004). The junctional zone develops from trophoblast progenitor cells which differentiated into four distinct cell linages: trophoblast giant cells, spongiotrophoblast cells, glycogen cells, and invasive trophoblast cells (Simmons and Cross, 2005). These cells form two distinct layers of the junctional zone: the spongiotrophoblasts which mainly provide structural support; and the trophoblast giant cells which are involved in endocrine functions and implantation of the placenta into the surrounding decidua. The glycogen cells and the invasive trophoblast cells appear first during mid-gestation. The invasive trophoblast cells invade the mesometrial uterine compartment where they penetrate and surround the uterine spiral arteries (Soares et al., 2012). Around E16, the main structures on the placenta are fully formed, however the villi continues to branch throughout pregnancy until birth (Watson and Cross, 2005) (Figure 1.5).

Despite some gross differences in placental morphology and development between rat and human, developmental processes and cell fate is similar, making the rat a good model to study placental programming.

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Figure 1.4 – An illustration of the in utero orientation of the fetus and placenta in rat The embryo is facing the anti-mesometrial side and the placenta formation occurs at the mesometrial side in rat.

Stroma Lumen Former Stroma Decidual Giant trophoblasts endometrium

Trophospongium Myometrium

Labyrinth Vacuolated cell layer with capillaries Trophoblasts Embryo

Anti-mesometrial glands/stroma

Decidual cells in the myometrium Myometrium

Figure 1.5 – Rat placentation at E6, E8, E10, E13 and E16. On E16, all the major structures of the placenta are fully formed.

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1.5.2 Placental nutrient transfer

1.5.2.1 Glucose

The amount of nutrients that can be transferred to the fetus depends on the vascular surface area of the placenta, and the availability of nutrients and nutrient transporters. As fetal gluconeogenesis is very limited (Marconi et al., 1993), the fetus rely on transplacental glucose transport from the maternal system. Although nutrients can both diffuse or be transported actively (Neerhof and Thaete, 2008), the facilitated glucose transporter (GLUT)1 and GLUT3 are responsible for transplacental glucose transfer. GLUT1 is located on the microvillus and basal membranes of the syncytium and transports glucose from the mother into the placenta (Neerhof and Thaete, 2008); and GLUT3 is expressed on the arterial endothelium and transports glucose from the placenta to the fetus (Shin et al., 1997). Importantly, glucose can also be transported from the fetal circulation back into the placenta, as the placenta is the only fetal tissue capable of storing excess fetal glucose (Schneider et al., 2003). Both glucose backflow, which normally generates increased glycogen pooling (Thomas et al., 1990, Barash et al., 1985), and Glut3 gene expression are increased in placenta of diabetic rats (Boileau et al., 1995), perhaps to protect the fetus from being exposed to excessive glucose levels. The maternal glucose concentration is generally slightly higher than fetal glucose concentration, creating a maternal-fetal glucose gradient (Neerhof and Thaete, 2008). In fetal growth restricted humans, the difference in this gradient is increased (Marconi et al., 1996) and is likely due to altered placental size and transport capacity, as well as changes in the concentration of placental glucose transporters (Jansson et al., 1993).

1.5.2.2 Amino acids

As the concentrations of amino acids are normally higher in the fetal- compared with the maternal blood circulation in humans, amino acids are believed to cross the placenta via active transport (Philipps et al., 1978). This transport is mainly facilitated by the system-A sodium-dependent amino acid transport system in the labyrinth zone and is reduced in cases of placental growth restriction (Cetin et al., 1990, Paolini et al., 2001). The system-A subtypes of amino acid transporters accept a 24

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fairly wide range of amino acids for transport, however solute carrier family 38 member 2 (Slc38a2) is the only one carrying the essential amino acid methionine (Mackenzie and Erickson, 2004). Methionine is involved in methylation of DNA and histones and is therefore implicated in epigenetic regulation of genes (Ikeda et al., 2012). As discussed previously, the preimplantation embryo is very susceptible to epigenetic perturbations (Ikeda et al., 2012), which again is supported by the PC MD study performed by Sinclair et al (2007) (discussed in section 1.3.1.3).

1.5.3 Vasculogenesis

The placenta’s vascular system is complex and provides a network of capillaries through which nutrients, waste and oxygen can be transported. These blood vessels forms via two processes: vasculogenesis (de novo), and angiogenesis (generation of blood vessels from existing ones) (Arroyo and Winn, 2008).

In vasculogenesis, as shown in Figure 1.6, mesenchymal cells form hemangiogenic stem cells under control of the vascular endothelial growth factor A (VEGFA) (Coan et al., 2004). These cells give rise to hemangioblastic stem cells, which differentiate into endothelial cells to form the vascular networks (Huppertz and Peeters, 2005). The endothelial tubes then fuse with vascular smooth muscle cells from the mesenchyme (pericytes); which start to proliferate and migrate to cover the endothelial cells to form the vessels (Huppertz and Peeters, 2005).

Vasculogenesis

Mesenchymal cells

Hemangiogenic stem cells Figure 1.6 – A diagram demonstrating cell differentiation in vasculogenesis Hemangioblastic stem cells During vasculogenesis, mesenchymal cells form hemangiogenic stem cells, Endothelial cells which form hemangioblastic stem cells, which differentiate into endothelial cells Vascular networks to form the vascular networks.

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A large number of enzymes are involved in the formation of a vascular network in the placenta: the vascular endothelial growth factor (VEGF) family; placental growth factor (PGF); FMS-related tyrosine kinase 1 (FLT-1) (also called vascular endothelial growth factor receptor-1 (VEGFR-1); and the kinase insert domain receptor (KDR, or VEGFR-2) (Huppertz and Peeters, 2005). These enzymes need to be available and functional to meet the requirements of the developing fetus, as failure to develop a capillary network often results in IUGR (Torry et al., 2004) and embryonic death (Meegdes et al., 1988).

1.5.4 Utero-placental insufficiency

A low birth weight can be generated by a number of factors and combination of factors, including: maternal stress, gestational diabetes, nutritional status, drug abuse, smoking, alcohol consumption, and utero-placental insufficiency (Neerhof and Thaete, 2008). Utero-placental insufficiency which is a degenerative process depriving oxygen and nutrient transfer to the fetus (Gagnon, 2003), is one of the major factors contributing to fetal growth restriction (Tapanainen et al., 1994). This is caused by defects in vascular remodeling (Labarrere and Althabe, 1987) and abnormal vasculogenesis (Torry et al., 2004) which in turn can be attributed to abnormal angiogenesis (Chen et al., 2002) or decreased placental surface area, volume and number of terminal villi and capillaries (Jackson et al., 1995, Teasdale, 1984). Overall, defects in the vascular system of the placenta are likely to impact negatively on the developing fetus.

1.5.5 Placental size

Researchers have showed increased interest in the placenta as a mediator of fetal programming (Maloney et al., 2011, Winder et al., 2011, Moore et al., 1996, Barker et al., 1990, Barker et al., 2010, Burd et al., 2007) and both absolute placental weight and placenta-to-body weight-ratio have been independently associated with adult disease. Studies suggest a U-shaped curve in which subjects with either a low or high placental weight or ratio are more prone to disease (Godfrey, 2002). Barker et al (1990) were the first to show this by correlating placental and fetal size with blood pressure in 50 year old humans. The group demonstrated that those with the lowest birth weight and highest placental weight had the highest blood pressure as adults 26

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(25 mmHg higher than a control group with normal body and placental weight). Risnes et al (2009), found similar results in a study covering 31000 humans in Norway in which individuals born with the highest placenta-to-body weight-ratio had the highest death rates from coronary artery disease. After reviewing existing human studies, Godfrey et al (2002) suggested that any deviation in the placenta-to-body weight-ratio greater than 20% increases the risk of cardiac death.

Importantly however, a measurement of placental weight does not consider the surface area or thickness – other important determinants of fetal outcome (Winder et al., 2011). The length and width of the placenta represent placental growth along the major and minor axis (of a circular placenta). The width, which is often affected in programming models of altered maternal nutrition, is influenced by the availability of nutrients (Barker et al., 2011). The length is instead closely correlated with the length of the fetus (Roseboom et al., 2011) and is generally unaffected by poor nutrition. Human studies have associated altered placental dimensions with increased systolic blood pressure in the adult offspring, but the association is complex. Adult offspring of short mothers are more likely to have increased systolic blood pressure if they had a wide placenta with a big surface area; whereas a similar correlation in offspring from tall mothers was only found if the placenta was more oval (Winder et al., 2011) or small (Eriksson et al., 2011, Barker et al., 2011).

The correlation between the dimensions and programmed disease is more complex than just measuring the placenta, which is composed of multiple layers: the labyrinth layer, the interhemal membrane, and the spongiotrophoblast layer. As the labyrinth layer constitutes the major site of nutrient transfer (Coan et al., 2008) a thicker labyrinth is easily assumed to be beneficial for nutrient and waste exchange; however reduced nutrient availability, which can increase thickness, may be detrimental because of increased nutritional cost of producing the larger tissue. This applies to the total size of the placenta too. A small placenta would theoretically be less capable of transferring nutrients to the fetus (Harding, 2001), but can adapt to the fetal requirements (Burton and Fowden, 2012) and instead increase the abundance of nutrient transporters, thus transplacental transport (Constancia et al., 2005, Coan et al., 2008). Similarly, a large placenta may be more inefficient because

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it has a higher metabolic demand (Gu et al., 1987) and may divert more nutrients to itself on the behalf of the fetus (Harding, 2001, Angiolini et al., 2006).

1.5.6 The effect of alcohol on the placenta

There has been surprisingly little research on the effects of alcohol consumption on the placenta. When alcohol is consumed throughout pregnancy, placental weight has been shown to be either reduced (Andersson et al., 1989, Niemela et al., 1991) or unaffected (Westney et al., 1991). EtOH perfusion has also been shown to impair placental metabolism by decreasing glucose utilization, increasing the levels of lactate and triglyceride (TG) (Rice et al., 1986), introducing defects in protein synthesis (Tal et al., 1985), and reducing DNA and total protein content (Karl et al., 1996). Not surprisingly, alcohol intake increases the rate of placental abruption, fetal growth impairment, and still birth (Burd et al., 2007).

Whether the future growth and function of the placenta is affected by PC alcohol intake is currently unknown. Evidence does however suggest that preimplantation development can be disturbed in the presence of alcohol, and as the placenta arises from the rapidly dividing TE cells, PC alcohol intake is likely to impact on placental development. If it does, adult onset disease similar to other in utero perturbations may arise.

1.6 Alcohol

1.6.1 Alcohol intake during pregnancy

The guidelines given by the National Health and Medical Research Council (NHMRC) of Australia regarding alcohol consumption during pregnancy have varied during the last decades. In 1992, women were advised abstinence while pregnant; but in 2001 the guidelines changed to allow <7 standard drinks per week (with a maximum intake of 2 drinks per day). In 2009 however, the guidelines were revised and currently states that: “For women who are pregnant or planning a pregnancy, not drinking is the safest option” (NHMRC, 2009). Despite this, drinking prior to and during pregnancy is relatively common. An Australian study reported that only 41% of pregnant women abstained alcohol consumption throughout pregnancy (O'Leary et al., 2009). The percentage of women drinking prior to and during early pregnancy

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(the periconceptional period) is considerably higher in some countries: 80% of Western Australian, and Irish women; (Colvin et al., 2007, Mullally et al., 2011); and around 50% of Danish and American women (Kesmodel, 2001, Carmichael et al., 2003) admit to alcohol consumption in the months leading up to pregnancy. Binge drinking (consuming five or more drinks per session) also increased from 6.2 million to 7.2 million women (of childbearing age) between 2001 to 2003 in The United States (Tsai et al., 2007). Estimating alcohol consumption before and during pregnancy is however difficult due to various factors such as: ethnicity (Floyd et al., 1999), the woman’s own understanding of what a standard drink is, drinking patterns in different countries (O'Leary et al., 2007), and underreporting (Ernhart et al., 1988).

The prevalence of binge-like drinking patterns is highest amongst men and women of reproductive age (Naimi et al., 2003) and there is a strong association between binging, unprotected sexual activity and unplanned pregnancies (Maier and West, 2001). Being unaware of pregnancy in turn explains the higher rates of alcohol intake in early pregnancy, as women who do not plan to become pregnant are less likely to recognize early signs of pregnancy (Naimi et al., 2003, Kost et al., 1998). Around 45% of all pregnancies in Australia and The United States are unplanned (Naimi et al., 2003, Colvin et al., 2007). The median number of days elapsed before recognition of pregnancy is 31 (with a variation between 7-227 days) (Edwards and Werler, 2006). Most women cease alcohol consumption completely when they realize they are pregnant; and amongst those who continue to drink, the intake is reduced (Floyd et al., 1999). The number of women drinking before pregnancy is however still higher than the number of unplanned pregnancies (Colvin et al., 2007), suggesting that women consume alcohol despite planning a pregnancy. Peadon et al (2011) recently confirmed this when they reported that 32% of women admitted they would continue to drink despite trying to get pregnant.

The high percentage of women drinking prior to pregnancy, the time elapsed before pregnancy recognition, and women’s attitudes regarding drinking behaviour during pregnancy planning strongly indicates that many fetuses are exposed to alcohol around conception and during early gestation.

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1.6.2 The effect of alcohol on the fetus and fetal alcohol syndrome

Alcohol crosses the placenta and can directly affect the fetus, or provoke changes in maternal endocrine functions that secondarily can interfere with fetal development and cause metabolic, physiological and endocrine disruptions – or result in miscarriage (Weinberg et al., 2008). Alcohol-induced birth defects may be established before the woman is aware of her pregnancy (Floyd et al., 1999), therefore women drinking both before pregnancy confirmation and during pregnancy are at risk of delivering a baby with fetal alcohol spectrum disorder (FASD) (Abel, 1999). The more severe condition of FASD, fetal alcohol syndrome (FAS), is a result of chronic alcohol consumption during pregnancy. The diagnosis for FAS includes: facial dysmorphology, intellectual impairment, neurological abnormalities and developmental delays (Jones and Smith, 1973). The features seen in FASD are similar to these seen in FAS but more subtle (Abel, 1999).

1.6.3 Timing, drinking pattern and drinking level

Babies exposed to alcohol prenatally respond differently, suggesting the programmed characteristics are conditional to the insult, as well as the timing of exposure (O'Leary, 2004). Some have argued the effects alcohol has on the fetus are only dose dependent if a particular threshold is exceeded (Abel, 1999). Binge drinking, which easily causes these levels to be exceeded by creating high plasma alcohol concentration (PAC), are particularly harmful for fetal brain development (Naimi et al., 2003). Yet even moderate levels of alcohol are associated with adverse health outcomes including: IUGR, decreased birth weight (Windham et al., 1995), a greater risk for congenital anomalies, and reduced intelligence quotient (IQ) (Martinez-Frias et al., 2004). The specific effect alcohol has on the fetus also depends on the gestational time at which it is consumed. The fetus is most severely affected during the first trimester – the major period of organogenesis (West and Goodlett, 1990). Alcohol during the first, but not second or third trimester, increases the risk of spontaneous abortion in humans (Windham et al., 1997); whereas alcohol during the third, but not second trimester increases the risk of preterm delivery (Kesmodel et al., 2000). Thus alcohol is harmful throughout and in all trimesters of pregnancy but different organs and cell populations are more or less vulnerable at different times of exposure (West and Goodlett, 1990).

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Animal models of maternal EtOH intake suggest the peak PAC is more harmful than the average intake (Pennington and Kalmus, 1987, Bonthius et al., 1988, Zajac and Abel, 1992). A high PAC is attained by consuming large amounts of alcohol on one single occasion (binge drinking) (Tsai et al., 2007). One research group administered the same amount of EtOH to neonatal rats during postnatal day (PN)4-10 (corresponding to the third trimester of pregnancy in humans) in two different patterns and studied their brain weights. One group were continuously exposed over the day (producing PAC of 0.05%); whereas the other group were given EtOH in a binge-like pattern (generating a high and sudden PAC of 0.27%). The binge group had significantly lower brain weight on PN10 (Pierce and West, 1986). Even a lower daily dose of EtOH given in a binge-like pattern induced more severe microcephaly and neuronal loss than a larger dose given continuously during PN4-10 (Bonthius and West, 1990). Another group gavaged pregnant dams with high doses of EtOH (1g/kg body weight) once daily on E13.5 and E14.5 (generating blood alcohol concentrations (BAC) of 0.12%). The offspring of the EtOH-gavaged dams where growth restricted, had reduced nephron number and higher mean arterial pressure at 1 month compared with control offspring (Jansson et al., 1999). These studies demonstrate how a binge-like drinking pattern, creating a higher PAC, can be more severe than chronic alcohol intake.

1.6.4 Alcohol elimination during pregnancy – the mother, placenta and fetus

As discussed in the previous paragraphs, alcohol can cross the placental barrier and affect the fetus. The dosimetry of alcohol exposure depends on: the total body water content (approximately 49%, but more in pregnancy as it contains the fetus’s water content and the amniotic fluid), the amount of alcohol consumed, available metabolizing enzymes, and the duration of the drinking episode (Lukaski et al., 1994). For a woman weighing 63 kilos who consumes four standard drinks over 4 hours (assuming one standard drink contains 14 grams of alcohol) (NIH, 2007), it will take around 8.5 hours to restore the blood alcohol levels to zero. If she instead drinks 12 standard drinks, elimination would take 25.6 hours (Paintner et al., 2012). Importantly, if a second drinking episode begins before the blood alcohol concentration from the previous one is restored, the BAC will be higher and the exposure period even longer (Paintner et al., 2012).

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The placenta’s ability to metabolize EtOH is very limited and produces acetaldehyde (Brien et al., 1983). Within an hour of maternal drinking, the fetus experiences alcohol levels comparable to those in the maternal circulation (Idanpaan-Heikkila et al., 1972) – but the acetaldehyde levels are considerably higher (Brien et al., 1983). The fetus eliminates alcohol very slowly (Brien et al., 1983, Seppala et al., 1971) extending the fetal exposure period even further.

It is however important to remember that the exposure period to alcohol in this thesis precede the development of both a fetus and a placenta. The effects of alcohol during early development are discussed further in section 1.6.6.

1.6.5 Alcohol metabolism

Alcohol (EtOH) is a toxic substance which is readily absorbed in the gastrointestinal tract and mainly metabolized in the liver (Lieber, 2005). As the body is unable to store EtOH, it becomes the preferred fuel for metabolism at the expense of other nutrients, causing metabolic imbalances (Shelmet et al., 1988, Lieber, 2005). EtOH can be metabolized via three different pathways: the alcohol dehydrogenase pathway (ADH); the microsomal ethanol oxidizing system (MEOS); and by catalase in the liver peroxisomes (Figure 1.7), all of which produce the extremely toxic metabolite acetaldehyde. As catalase metabolism only has a minor influence on EtOH metabolism, it will not be discussed in this report.

The ADH pathway accounts for 90-95% of hepatic EtOH metabolism (Hernandez- Munoz et al., 1990). In this process, a hydrogen atom is removed from EtOH by mitochondrial aldehyde dehydrogenase (ALDH), producing acetaldehyde. This converts nicotineamide adenine dinucleotide (NAD) to its reduced form; nicotineamide adenine dinucleotide hydrate (NADH) and one hydrogen atom (Hernandez-Munoz et al., 1990). Acetaldehyde is then quickly metabolized to acetate (or acetyl coenzyme A, acetyl-CoA), which produces another hydrogen atom for NAD (Lieber, 2005). The increase in the NADH/NAD-ratio creates a surplus of hydrogen atoms as NAD becomes saturated (Lieber, 2005). The mitochondria (which normally uses hydrogen derived from fatty acid oxidation) starts to utilize hydrogen produced in EtOH metabolism instead, and lipids start to accumulate in the

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liver. The acetyl-CoA is eventually converted to carbon dioxide (CO2) and water and is eliminated by the body.

When alcohol consumption is high, hepatic ADH becomes saturated, and the MEOS system (5-10% of EtOH metabolism), controlled by cytochrome P450 2E1 (CYP2E1)

becomes activated. MEOS Km for EtOH is higher than the Km of the ADH pathway (8-10 mM as compared with 0.2-2 mM) (Lieber, 2005), and increases the EtOH tolerance. Activation of the MEOS system does however result in increased acetaldehyde production, which when oxidized releases free radicals (Lieber, 2005).

ADH - Deactivate proteins Ethanol - Inhibit protein repair Acetaldehyde - Mutations and cell death

NAD NADH + H+ CoA NAD

Aldehyde dehydrogenase

NADH + H+ Mitochondrial electron transport chain to generate energy MEOS – ingestion of high Acetyl-CoA doses of EtOH

O2 2H2O - Fatty acid synthesis

+ - Hyperlipidaemia NADPH + H NADP Citric acid cycle to produce ATP via - Hypoglycaemia mitochondrial electron transport chain

- Oxidative stress - Cell and tissue damage - Lipid peroxidation

Figure 1.7 – Metabolism of ethanol via the alcohol dehydrogenase pathway and the MEOS system A schematic presentation of alcohol metabolism via the alcohol dehydrogenase (ADH) pathway and the microsomal ethanol oxidizing system (MEOS).

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1.6.5.1 Alcohol metabolism in rats compared with humans

Rats metabolize EtOH faster than humans. Zorzano and Herrera (1990) gave humans and rats the same amount of EtOH (per kilogram body weight) and measured the concentrations of EtOH and acetaldehyde in their blood over time. In humans, the concentrations were low at 5 minutes (close to 1 mM), peaked at 30 minutes (5 mM) – and remained at 5 mM 3 hours after administration. In Wistar rats however, the concentrations were higher than 5 mM at 5 minutes, stayed constant for the first 30 minutes, and subsequently declined to reach a level of 0.8 mM 90 minutes after dosage. This needs to be considered when studying alcohol in rat models.

1.6.6 Animal models of maternal alcohol intake and programming of disease

The developmental programming research and the mechanisms by which programming occurs have been advanced by the development of animal models, as it is ethically inappropriate to use human models for this purpose. The uses of animal models are advantageous as they overcome many limitations of epidemiological study designs. The environment can be strictly controlled throughout the animals’ lifespan, enabling confounding factors to be kept low.

1.6.6.1 Periconceptional alcohol consumption

Periconceptional programming following maternal alcohol has received very little attention in experimental studies. It is however known that EtOH can diffuse into watery compartments of the body – including the oviduct and the uterus and be deleterious for the developing embryo (Mitchell, 1994). For example, Mitchell (1994) showed that EtOH (2g/kg body weight per day from E1-E4) advances the onset of blastocyst implantation and causes post-implantation embryo loss without affecting fecundity in rat. The same authors later speculated that these changes may be due to the ability of EtOH to increase blood flow to the vascular bed of blastocyst implantation sites (Mitchell and Goldman, 1996). Contradictory to these findings, mouse oocytes from EtOH-treated dams that were inseminated with spermatozoa in vitro had a significantly lower fertilization rate and faced an abnormal embryo development that resulted in fewer oocytes reaching the expanded blastocyst and hatching blastocyst stage on E6 (Cebral et al., 1999). This was later replicated with

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similar results in a mouse in vivo study (Cebral et al., 2000). When extending these experiments further, the research group showed that EtOH-exposed female mice had fewer embryos on E10, reduced implantation site numbers, increased resorption, delayed embryonic development and abnormal neural tube closure (Coll et al., 2011). In this study however, the PC period was defined as 17 days prior to conception until E10 (Coll et al., 2011), which is after embryonic implantation in mice.

Collectively, these studies confirm that the early embryo is affected by EtOH, yet no one has investigated the long term consequences of PC alcohol.

1.6.6.2 Prenatal alcohol consumption

The long term effects of prenatal alcohol exposure have – in contrast to PC alcohol – been extensively investigated. Many characteristics seen in humans with FAS have been observed in rodent models of prenatal EtOH-exposure (Lee and Wakabayashi, 1985, Addolorato et al., 1997), but also other effects are documented including: low birth weight and IUGR (Chen et al., 2004, Chen and Nyomba, 2003b, Lopez-Tejero et al., 1989, Villarroya and Mampel, 1985, Chen and Nyomba, 2003a); altered fetal glucose and insulin homeostasis (Chen and Nyomba, 2004, Chen and Nyomba, 2003a, Lopez-Tejero et al., 1989, Chen and Nyomba, 2003b, Villarroya and Mampel, 1985); decreased glucose tolerance (Chen and Nyomba, 2004, Chen and Nyomba, 2003b, Chen and Nyomba, 2003a); and decreased insulin sensitivity (Chen et al., 2004, Chen and Nyomba, 2003a, Yao et al., 2006). Table 1.2 provides a comprehensive summary of how prenatal alcohol affects the metabolic status of the offspring.

Researchers attempting to mechanistically describe the metabolic alterations in the offspring following prenatal EtOH-exposure have traditionally focused on changes in gene expression and molecular pathways. Alterations in gluconeogenic genes (causing deregulated hepatic glucose output) (Chen et al., 2004, Yao et al., 2006), the insulin signaling pathways (Chen et al., 2005), and in the level of circulating adipokines (Chen and Nyomba, 2003a, Chen and Nyomba, 2003b) are commonly shown in these models. More recent studies have started to examine possible epigenetic modifications and suggested that the origin to the common changes in molecular pathways and endocrine functions may recede in very early ‘metabolic

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imprints’. For example, Yao et al (2013) demonstrated changes in histone acetylation which they associated with adult glucose intolerance. Although investigating epigenetic modifications were beyond the scope of this thesis, it should be emphasized that epigenetics may have contributed to the phenotype seen in the rats in this thesis (discussed in section 6.6).

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Table 1.2 Animal models of prenatal alcohol exposure and programming effect Dosage and method of Timing of Human Species Mechanism Phenotype Reference alcohol administration exposure trimester equivalent ↑ Fasting plasma insulin but ↔ in glucose 10% EtOH (w/v) during (birth) week 1 of pregnancy Wistar Throughout Glucose intolerance with ↔ in insulin (Villarroya and and 25% EtOH (w/v) 1-2 rats gestation response (birth) Mampel, 1985) during week 2-4 of Normal glucose response with ↑ insulin pregnancy response (PN3)

35% EtOH derived calories administrated Throughout ↑TG levels with increasing age (Pennington et SD rats 1-2 via a liquid diet gestation ↑VLDL al., 2002) (BAC 100-150mg/dL)

35% EtOH derived ↓basal and insulin-dependent glucose uptake calories administrated Throughout SD rats 1-2 by muscle tissue in vitro (PN75-95, male only) (Elton et al., 2002) via a liquid diet gestation ↔in vivo insulin sensitivity (BAC 100-150mg/dL)

↑adipose tissue mRNA resistin 2g/kg/d (36%) by Throughout ↑plasma resistin ↓birth weight (Chen and SD rat* gavage twice daily 1-2 gestation ↓GLUT4 in muscle membrane following Glucose intolerance (13 weeks) Nyomba, 2003b) (~1.5g/d or 10.5kcal/d) glucose administration

PN1: ↓leptin mRNA and plasma insulin but PN1: ↓birth weight 2g/kg/d (36%) by ↔ β-cell mass Catch up growth after 7weeks gavage twice daily Throughout (Chen and SD rat* 1-2 13weeks: ↑resistin mRNA in adipose 13 weeks: ↔ in adipose tissue weight (~1.5g/d or 10.5kcal/d) gestation Nyomba, 2003a) ↓skeletal muscle GLUT4 glucose intolerance BAC 114.4mg/dL ↔ in leptin mRNA, or plasma leptin ↑plasma insulin

↔plasma FFA ↓birth weight (~50% of pups, 1a) 2g/kg/d (36%) by Throughout 1-2 (1) or 3 ↑Plasma, muscle and liver TG content at 16 Catch up growth after 4 weeks (Chen and SD rat* gavage twice daily gestation (1) or (2) weeks (1a), ↔ in other groups Insulin resistance and glucose intolerance in all Nyomba, 2004) (~1.5g/d or 10.5kcal/d) PN1-PN21 (2) EtOH-groups (16 weeks)

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Table 1.2 Animal models of prenatal alcohol exposure and programming effect (cont.) Human Dosage and method of Timing of Species trimester Mechanism Phenotype Reference alcohol administration exposure equivalent

↔baseline hepatic mRNA levels of Pck1, G6pc, Pgc-1α or Gck 2g/kg/d (36%) by ↓birth weight, ↓body length Throughout ↓ Pck1 and ↑Pgc-1α 30 minutes after SD rat* gavage twice daily 1-2 ↔basal plasma glucose or insulin (PN1) (Chen et al., 2004) gestation insulin (~1.5g/d or 10.5kcal/d) Insulin insensitive (PN1) ND in adipose tissue mRNA or serum levels of adiponectin

↓Muscle GLUT4 on membrane following insulin administration at 16 weeks 2g/kg/d (36%) by Insulin treatment had no effect on tyrosine Throughout SD rat* gavage twice daily 1-2 phosphorylation of insulin receptor β-subunit (Chen et al., 2005) gestation (~1.5g/d or 10.5kcal/d) or IRS-1 ↓PI3K activity ↔AKT activity

PN7: ND in basal Pck1 and Pgc-1α mRNA or ↓birth weight protein ↑fasting plasma insulin, ND in glucose (PN7 2g/kg/d (36%) by ↔ response of Pck1 or Pgc-1α mRNA and and 3 months) gavage twice daily Throughout protein to insulin administration SD rat* 1-2 ↔ response in glucose when tested after (Yao et al., 2006) (~1.5g/d or 10.5kcal/d) gestation 3 months: ↑Basal mRNA and protein levels insulin administration (PN7 and 3 months) BAC 114.4mg/dL of PCK1 and PGC-1α ↑Gluconeogenesis (measured by a pyruvate ↔response of Pck1 or Pgc-1α mRNA and tolerance test) protein to insulin administration ↑ gestational length 5 days per ↓birth weight 4g/kg/d (30% v/v) in ↓β-cell insulin-like immunopositive area Guinea week Catch up growth (PN1-PN7) (Dobson et al., tap water 1-3 (indicative of ↓pancreatic insulin production pig throughout ↑visceral and subcutaneous adiposity (PN100- 2012) (BAC ~281mg/dL) and/or secretion) gestation 140) ↑pancreatic adiposity (PN150-200)

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↔ β-cell density, islet density, β-cell mass or ↔ birth weight islet mass (PN30) ↑ plasma insulin and HOMA-IR (4 months) 6% EtOH (v/v) via a ↔ in hepatic Glut4, Pck1, PGC-1α, Gck or Throughout ↔ glucose tolerance but males had ↑ 1st (Probyn et al., SD rat liquid diet 1-2 insulin receptor gestation phase insulin secretion in response to glucose 2013c) (BAC ~30mg/dL) ↔ in adipose resistin, adiponectin, Glut4 or ↔ body composition insulin receptor ↓ plasma TG (males) (7 months) ↔ in muscle Pgc-1α or Glut4

2g/kg/d (36%) by Early (E1-7), ↑PCK1 and G6PC (mRNA and protein) ↓birth weight (early and late) 1 or 2 gavage twice daily mid (E8-14) or ↑in HDAC activity (4, 5 and 7) Time specific alterations in glucose handling SD rat* (critical (Yao et al., 2013) during treatment late gestation ↑SIRT2 protein ↑endogenous insulin production after GTT periods) period (E15-21) ↑free radicals in liver ↑gluconeogenesis

↓ serum corticosterone ↓birth weight Wistar 4g/kg/d via gavage ↑IGF1 and glucose E11-E20 2 ↑ hepatic microvesicular steatosis around the (Shen et al., 2014) (BAC ~395mg/dL) ↔ mRNA levels of Igf1R, Irs2, Glut2, Pparα, rats † central vein Fox01 or G6pc

AKT, protein kinase B; BAC, blood alcohol concentration; E, embryonic day; d, day; FFA, free fatty acids; FOXO1, forkhead box protein O1; G6pc, glucose-6- phosphatase; Gck, glucokinase; GLUT4, glucose transporter 4; HDAC, histone deactylases; PN, postnatal day; Pck1, phosphoenolpyruvate carboxykinase; Pgc-1α, peroxisome proliferator-activated receptor gamma, coactivator 1α; PPARα, peroxisome proliferator-activated receptor alpha; SD, Sprague Dawley rats; SIRT2, NAD-dependent deacetylase sirutin-2; TG, triglyceride; VLDL, very low density lipoprotein. *Did not specify sex or males only; †Females only; ↔, (no difference); ↑, (significantly increased); ↓, (significantly decreased).

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1.7 The metabolic syndrome

‘Metabolic disease’ was first described by a Swedish physician 80 years ago as the clustering of hypertension, hyperglycaemia and gout (Studien, 1923). Today metabolic disease characteristics also generally include: insulin resistance, hyperinsulenemia, central obesity, dyslipidaemia, impaired glucose tolerance, hypertension and/or atherosclerosis – all of which are associated with the development of both diabetes and CVD (Miranda et al., 2005, Eckel et al., 2005, Levitan et al., 2004). These risk factors have generated several diagnosis criteria where the most widely used ones: the World Health Organization (WHO) (Alberti and Zimmet, 1998); the US National Cholesterol Education Program (NCEP) (NCEP, 2001); and the adult treatment panel III (ATPIII) (ATPIII, 2002) are summarized in Table 1.3.

Table 1.3 The metabolic disease: Criteria and definitions WHO NCEP ATPIII Type 2 diabetes, impaired glucose Fasting plasma glucose 110- Fasting plasma glucose ≥ 110 tolerance, or insulin resistance by 125mg/dL mg/dL HOMA-IR

BMI > 30 or waist hip ratio > 0.90 Waist circumference > 102 (men) or Waist circumference > 102cm (men) or > 0.85 (women) > 88 (women) (men) or > 88cm (women)

Dyslipidemia: TG ≥ 150mg/dL, HDL TG ≥ 150mg/dL, HDL < 40 (men) or TG ≥ 13mg/dL, HDL < 1.0mmol/L < 35 (men) or < 39 (women) < 50 (women) (men) or < 1.3mmol/L (women)

Hypertension: on medication or Blood pressure ≥ 130/85 mm Hg Blood pressure ≥ 130/85 mm Hg untreated blood pressure ≥ 160/90 or medication mm Hg

ATPIII, adult treatment panel III; BMI, body mass index; HDL, high density lipoprotein; HOMA-IR, homeostatic model for assessment of insulin resistance; LDL, low density lipoprotein; TG, triglycerides; WHO, world health organization. WHO; must meet glucose/insulin criterion and 2 more. NCEP; must meet 3 of 5 criteria (low HDL and high TG are 2 criteria). ATPIII; must meet 3 or more (low HDL and high TG are 2 criteria).

Establishing an internationally recognized definition is complex because the degree of risk factors differ heavily between populations and age groups (Eckel et al., 2005), and therefore it is difficult to determine the prevalence accurately. Approximately 25% of the world’s population had metabolic syndrome by NCEP criteria in 1994, but this number increases parallel to the rise in obesity – one of the main drivers of metabolic syndrome (Grundy, 2008). WHO estimates that 300 million people 40

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worldwide will be diagnosed with metabolic syndrome or associate disorders by 2025 (Seidell, 2000). Although metabolic syndrome used to be prevalent mainly in older age groups (Eckel et al., 2005), the disease is now alarmingly increasing in children too (Sinha et al., 2002, Weiss et al., 2004). Figure 1.8 shows the prevalence of the metabolic syndrome in various countries in 2004.

Figure 1.8 – Prevalence of the metabolic syndrome in a worldwide population 2004 Percentage of men and women affected by the metabolic syndrome in various countries. Adapted from (Cameron et al., 2004).

Poor nutrition and environmental factors majorly contribute to the increase in metabolic syndrome; but accumulating evidence suggests developmental programming to be a strong contributor too. Therefore, programming of glucose- and insulin homeostasis and adiposity – the major focus of this thesis – are discussed in the following sections (whereas blood pressure and CVD will not be targeted).

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1.7.1 Diabetes

Figure 1.9 – Projected numbers of diabetics in a worldwide population by 2025 . . Projected numbers of people over 20 years old suffering from diabetes year 2000 (grey bars) and 2025 (black bars) compared with documented numbers year 1995 (white bars) in developed countries, developing countries and the World. Adapted from (King et al., 1998).

Type 2 diabetes – which is defined as fasting hyperglycaemia and glucose intolerance in response to insulin secretion and impaired insulin action – accounts for 90-95% of all cases of diabetes (Bell and Polonsky, 2001, Eckel et al., 2005). It is estimated to affect 300 million people (adult population) by 2025 (King et al., 1998) and 366 million people by 2030 (Wild et al., 2004), with the biggest increase incidence in developing countries (Figure 1.9) (King et al., 1998). In healthy subjects, insulin is produced and secreted by the pancreas in response to hyperglycaemia/postprandial raise in blood glucose, to facilitate glucose disposal in peripheral tissues and to attenuate hepatic gluconeogenesis (lowering blood glucose levels) (Huang, 2009). In insulin insensitivity, the tissues’ ability to respond to insulin is reduced and can progressively cause insulin resistance. Importantly, insulin resistance is an early metabolic defect that often, but not always, results in type 2 diabetes (Huang, 2009).

The following paragraphs discuss some of the common complications from which insulin resistance generally arise.

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1.7.1.1 Pancreatic insulin secretion

Pancreas organogenesis starts at 8-10 weeks of gestation and continues throughout pregnancy in humans (Mitchell et al., 2009); and occurs between E10 and E19 in rats (Navarro-Tableros et al., 2007). Pancreas develops from two buds derived from the epithelium of the digestive tracts, that fuse together and differentiate into endocrine (islets of Langerhans) and exocrine (acini) cells (Scharfmann, 2000). The endocrine pancreas comprises four distinct cell types secreting different substances: α-cells (glucagon); β-cells (insulin); δ-cells (somatostatin); and PP-cells (pancreatic polypeptide) (Fowden and Hill, 2001, Scharfmann, 2000, Clark and Rutter, 1972). The secretion of insulin from the β-cells is dynamic as such it can be adjusted to the levels of extracellular glucose. This occurs by expansion of the β-cells mass (the product of the number and size of β-cells) in pregnancy and has been shown in obese, old and insulin resistant women (Bonner-Weir, 2000). Improper regulation of β-cells, and β-cell dysfunction contributes to the pathogenesis of type 2 diabetes (Wild et al., 2004).

1.7.1.2 Peripheral insulin signaling

Insulin released by the pancreatic β-cells binds via a saturable process to the insulin receptor, a receptor tyrosine kinase which regulates multiple signaling pathways via sequences of phosphorylation cascades (Figure 1.10). The insulin receptor (a 350 kD transmembrane glycoprotein) comprises four subunits held together by disulphide bonds as a hetero-tetramer: two extracellular ligand binding (regulatory) α-subunits; and two (catalytic) β-subunits which each contains a tyrosine kinase domain. The α- and β-subunits are encoded for by the same gene and originate from the same precursor molecule (proreceptor).

When insulin binds to the α-subunits, the β-subunits are rapidly auto-phosphorylated at five tyrosine residues (Kahn and Goldfine, 1993), triggering two parallel pathways: the phosphoinositide 3-kinase (PI3K) pathway, and the mitogen-activated protein (MAP)-kinase pathway. Insulin resistance inhibits the PI3K pathway (thus endothelial nitric oxide production and GLUT4 mediated glucose uptake) – but leaves the MAP- kinase pathway and endothelin-1 production (which induces vasoconstriction) intact

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– introducing imbalances between the two. Insulin resistance therefore often coexists with vascular abnormalities (Huang, 2009).

Figure 1.10 – Schematic presentation of the insulin regulated intracellular signal transduction cascade Binding of insulin to the insulin receptor causes translocation of the intracellular GLUT4 enzyme to the cell membrane for insulin-mediated glucose uptake. Adapted from (Frojdo et al., 2009).

The PI3K pathway starts with phosphorylation of the insulin like receptor substrate 1 (IRS-1); a 185 kD cytosolic protein with several serine and tyrosine phosphorylation sites. IRS-1 is both positively and negatively regulated by insulin: increased serine phosphorylation deactivates (Li et al., 1999) and degrades PI3K (Pederson et al., 2001); whereas increased tyrosine phosphorylation activates PI3K and the PI3K/AKT complex (Rayasam et al., 2009). Similar to the insulin receptor, PI3K has one catalytic (p110α-δ) and one regulatory (p85α-β, which exists in three splice variants: AS53, p55α and p50α) subunit (Mauvais-Jarvis et al., 2002). p85α is believed to be involved in attenuation of insulin responses (Terauchi et al., 1999) as cultured cells overexpressing p85α decreases both the amount of p85/110 dimer, and the catalytic activity of the p110 subunit (Rameh et al., 1995). PI3K catalyzes the production of 44

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phosphatidylinositol-3,4,5-triphosphate (PIP3) by phosphorylating second messengers of insulin signaling: phosphatidylinositol (PI), phosphatidylinositol-4- phosphate (PIP), and phosphatidylinositol-4,5-bisphosphate (PIP2) (Tsakiridis et al.,

1995). PIP3 phosphorylates, thus activates the v-akt murine thymoma viral oncogene homolog (AKT) (also referred to as PKB or Rac), another serine/threonine kinase. AKT exists in three isoforms: AKT1, 2 and 3 (PKBα, β and γ) encoded for by three different genes. Mice knockout studies have shown that AKT1 and AKT3 are predominantly involved in growth and development, whereas AKT2 regulates energy homeostasis (Schultze et al., 2011). Human studies have confirmed this as skeletal muscle and adipocytes (which expresses all three forms of AKT) only reduces insulin-stimulated glucose uptake in response to Akt2 deletion (Cho et al., 2001). Phosphorylation of AKT2 occurs at two different sites: first on Thr309 by 3- phosphoinositide-dependent protein kinase 1 (PDK1) resulting in basal kinase activity; and then on Ser474 by the mechanistic target of rapamycin complex 2 (MTORC2), resulting in full kinase activity (Schultze et al., 2011). In skeletal muscle and adipocytes, activated AKT2 disassociate from the plasma membrane to phosphorylate intracellular vesicles of GLUT4, which translocates to the cell surface and catalyse glucose uptake (Devaskar and Thamotharan, 2007, Huang, 2009).

1.7.1.2.1 Glycogen synthase kinase-3 beta

Downstream of AKT is glycogen synthase kinase-3 beta (GSK3β), a constantly active kinase (generally keeping its substrates in an inactivated state via phosphorylation) which is inactivated in response to cellular signals (Rayasam et al., 2009). GSK3β is involved in processes that also allows for blood glucose lowering effects and improved insulin sensitivity. When AKT phosphorylates (thus inactivates) GSK3β on Ser21 and Ser9, serine residues (Ser)(641, 645, 549, 653) of glycogen synthase (GS) becomes de-phosphorylated (thus activated) and GS can mediate the conversion of glucose to glycogen (Cross et al., 1995, Rayasam et al., 2009). GSK3 also regulates hepatic gluconeogenesis via suppression of gluconeogenetic enzymes such as phosphoenolpyruvate carboxykinase (Pck1) and glucose-6- phosphatase (G6pc) (Lochhead et al., 2001). Additionally, GSK3 can phosphorylate IRS-1 on Ser332 and 336 residues (Eldar-Finkelman and Krebs, 1997) as such

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overexpression of GSK3 may contribute to reduced insulin sensitivity, as discussed in the following paragraphs.

The PI3K/AKT-pathway also controls hepatic glucose metabolism in hepatocytes by inhibition of the forkhead box protein O1 (FOXO1). FOXO1 normally exists in an active (non-phosphorylated) form in the cell nucleus where it binds to the G6pc promoter and stimulates G6pc transcription (Nakae et al., 2001, Taniguchi et al., 2006). When AKT phosphorylates FOXO1 it becomes inhibited and hepatic glucose production decreases. Both AKT1 and AKT2 are expressed in the liver and it may therefore be a functional overlap between the two isoforms, although this is unclear (Schultze et al., 2011). Collectively, the levels of AKT phosphorylation in skeletal muscle, adipocytes and hepatocytes following insulin stimulation is often considered as a benchmark for insulin sensitivity (Schultze et al., 2011).

1.7.1.3 Hepatic glucose homeostasis

Apart from the pancreas and peripheral insulin signaling, the liver plays a critical role in regulation and maintenance of glucose homeostasis. This occurs via: uptake (glycogenesis); storage (glycolysis); production (glycogenolysis); and release (gluconeogenesis) of glucose (Figure 1.11) under the influence of hormones, particularly insulin, glucagon and epinephrine.

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Glycogenolysis Glycogen Glycogen Glycogen phosphorylase Glucose-1-phosphate synthase Phopoglucomutase Glucose Glucokinase Glucose-6-Phosphatase Glucose-6-phosphate Phosphohexose isomerase Phosphofructo Fructose-1,6- kinase-1 Fructose-6-phosphate bisphosphatase

Fructose-1,6-bisphosphate Glycogenesis

Aldolase Triosephosphate Dihydroxyaceton- isomerase Glyceraldehyde-3- phosphate phosphate Glyceraldehyde Phosphate

Glycolysis Dehydrogenase 1,2-bisphosphoglycerate Phosphoglycerate Kinase 3-phosphoglycerate Phosphoglycerate Mutase 2-phosphoglycerate

Enolase Gluconeogenesis Phosphoenolpyruvate Pyruvate Kinase PEP carboxykinase Oxaloacetate Pyruvate carboxylase Pyruvate

Figure 1.11 – The regulation of glycogenolysis, glycogenesis, glycolysis and gluconeogenesis In glycogenolysis glucose-6-phosphate is generated from glycogen, whereas in glycogenesis, glycogen is synthesized from glucose-6-phosphate. In glycolysis, glucose is metabolized to pyruvate with the concomitant net production of two adenosine triphosphate (ATP) molecules. In gluconeogenesis, glucose is generated by the liver from non-carbohydrate precursors such as pyruvate and lactic acid.

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The initial development of the liver is similar in human and rat. Cellular differentiation starts at somite stage 11 in both species (corresponds to E24 in human and E10.5 in rat). During the following stages, up to the embryonic stage 23 (corresponds to E57 in human and E16 in rat) the same hepatic structures are present in both species. At embryonic stage 23, more than 90% of the hepatic structures are present in both human and rat (Godlewski et al., 1997), suggesting that the rat is a good animal model for liver investigation.

1.7.1.3.1 Hepatic glucose homeostasis in response to fasting

Both glycogenolysis and gluconeogenesis are activated during fasting or hypoglycaemia via post-translational modifications and allosteric activation of rate- limiting enzymes (Oh et al., 2013). During initial fasting, glucose is primarily made available via glycogenolysis, which is dependent on the activities of GS and glycogen phosphorylase (Gerich, 1993). In prolonged fasting, glycogenolysis becomes less important and glucose is instead produced de novo from precursors such as lactate, glutamine and alanine during prolonged fasting (Aronoff et al., 2004, Konig et al., 2012). The rate of gluconeogenesis increases gradually as blood glucose levels falls (Konig et al., 2012). DeFronzo et al (1992) suggested that plasma glucose levels following an overnight fasting period (~10 hrs) reflects endogenous glucose production (gluconeogenesis): but according to more recent evidence, fasting has to be maintain for up to ~40 hours to truly reflect gluconeogenesis (Konig et al., 2012) as it takes approximately 40 hours for glycogenolysis to deplete the glycogen stores (Konig et al., 2012). Gluconeogenesis, which comprises a series of eleven enzyme-catalysed reactions, is dependent on the amount of glucogneogenic substrates and their regulatory enzymes. These genes are controlled at transcriptional level by hormones such as insulin, glucagon and corticosteroid (Yoon et al., 2001) as such gluconeogenesis and glycogenolysis increases when pancreas excretes glucagon, and decreases when insulin is present (Hanson and Reshef, 1997). The liver can also utilize free fatty acids as a source for glucose production (Postic et al., 2004). Hepatic lipid oxidation increases the levels of acetyl-CoA/CoA, NADH/NAD+ ratios, and acetyl-CoA esters, which reciprocally inhibits glycolytic enzymes and further stimulates gluconeogenic enzymes (Gerich, 1993). As discussed in the following sections, insulin resistance generally leads to an

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inability to control the expression of gluconeogenic enzymes, which results in increased hepatic glucose production.

1.7.1.3.2 Hepatic glucose homeostasis in response to a meal

Following a meal, blood glucose levels rise within 15 minutes, peak at around 30 minutes and decline to base levels after around 4-5 hours (depending on meal size and glucose content). The rapid increase in glucose levels, together with neurogenic stimuli and gastrointestinal hormones stimulate insulin and suppresses glucagon secretion (Gerich, 1993). Insulin is released in a biphasic manner: phase one, a rapid release of stored insulin; and phase two, a slower release of newly synthesised insulin (Gerich, 1993, Del Prato and Tiengo, 2001). First-phase insulin secretion exerts an important effect on the liver (Steiner et al., 1982, Luzi and DeFronzo, 1989) as it acutely suppresses endogenous glucose production (by decreasing gene transcription of Pck1 and G6pc (Barthel and Schmoll, 2003)); and reciprocally increases peripheral glucose disposal, as demonstrated by hyperglycaemic clamp studies (Luzi and DeFronzo, 1989). If first-phase insulin release is suppressed, peripheral glucose utilization will not be stimulated, and endogenous glucose production will only decrease by 50% (Luzi and DeFronzo, 1989). In healthy people, glucose enters the hepatocytes via GLUT2, become phosphorylated to glucose-6- phosphate via glycolysis, and subsequently enters the Krebs cycle to produce energy (Gerich, 1993). If a surplus of glucose is ingested, glycogenesis is initiated by GSK3 inactivation, (thus GS activation) to produce glycogen (Oh et al., 2013). The immediate response to increased blood glucose levels is thereby mediated by insulin-mediated glucose uptake in peripheral tissues and in the liver; but the removal of glucose from the circulation also results from suppressed endogenous glucose production (Aronoff et al., 2004, Oh et al., 2013).

1.7.1.4 Insulin and glucose homeostasis in diabetes

The rate of insulin-mediated glucose disposal varies greatly within the population due to genetic variation, fitness and adiposity. Impaired glucose homeostasis can arise from either: fasting hyperglycaemia (most common), which results from increased hepatic glucose release (gluconeogenesis); or postprandial

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hyperglycaemia, caused by failure to suppress gluconeogenesis and/or impaired peripheral uptake of glucose; or a combination of both.

1.7.1.4.1 Insulin homeostasis in diabetes

Insulin resistance occurs when the sensitivity to insulin is decreased in peripheral tissues (skeletal muscle, adipose tissue and liver) (Huang, 2009), and is often due to dysregulations in the insulin signaling pathway (Czech and Corvera, 1999, Morino et al., 2006, Schultze et al., 2011). Many insulin signaling substrates can be affected in insulin resistance, but activation of the insulin receptor is generally fully functional (Frojdo et al., 2009). Both animal and human studies have shown that reduced IRS-1 protein can contribute (Saad et al., 1992, Kerouz et al., 1997, Cusi et al., 2000, Danielsson et al., 2005): mice lacking IRS-1 exhibit insulin resistance in the absence of diabetes (Araki et al., 1994); and obese and type 2 diabetic humans have diminished IRS-1 phosphorylation in skeletal muscle (Cusi et al., 2000) and adipocytes (Danielsson et al., 2005). PI3K activation is difficult to measure and its role in insulin resistance is controversial (Frojdo et al., 2009). Mice lacking all splice variants of p85α exhibit improved insulin sensitivity (Terauchi et al., 1999), lower fasting plasma glucose concentrations, and have a lower diabetes incidence (Mauvais-Jarvis et al., 2002). This may be due to a more beneficial stoichiometry of the p85/p110/IRS complex, and/or increased PI3K-dependent signaling (as p85 overexpression inhibits PI3K signaling, whereas p85 deficiency facilitates bridging of the IRS-1 with the catalytic p110 subunit) (Mauvais-Jarvis et al., 2002). Others have confirmed impaired activation of PI3K when measured in vitro as IRS-1 associated activity (Beeson et al., 2003, Kim et al., 2003). The role of AKT in diabetes is also debatable. Down-regulation of AKT2 inhibits insulin induced GLUT4 translocation to the cell surface (Jiang et al., 2003), Akt2 knockout mice are insulin resistant and mildly glucose intolerant (Schultze et al., 2011), and AKT2 overexpression rescues impaired glucose transport in AKT2-deficient adipocytes (Bae et al., 2003). In agreement with this, many have reported decreased muscle Ser474 and Thr309 phosphorylation of AKT in diabetic patients (Cozzone et al., 2008, Frojdo et al., 2009). Others did however find AKT2 activation to be unaltered in insulin resistance (Kim et al., 2003, Cusi et al., 2000, Nikoulina et al., 2001), but discovered reductions in insulin-induced PI3K activity instead (Beeson et al., 2003, Kim et al., 2003).

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Importantly, all groups did not specify which isoform of AKT they measured, and/or the origin of skeletal muscle biopsies, and the severity of obesity/diabetes differed in these studies. More consistent findings of reduced AKT phosphorylation and activity are reported in adipose tissue (Rondinone et al., 1999, Carvalho et al., 2000). Researchers have also found increased GSK3β activity in skeletal muscle of type 2 diabetes patients (Nikoulina et al., 2000) and in diabetic mice (Eldar-Finkelman et al., 1999). Correspondingly, GSK3β inhibition improves insulin signaling and glucose tolerance (Meijer et al., 2004). Other substrates in insulin signaling, including GLUT4 and protein kinase C, are also commonly impaired in type 2 diabetic patients (Frojdo et al., 2009).

Collectively, these studies suggest that impairments of most substrates in the insulin signaling pathway can result in insulin resistance and/or diabetes.

1.7.1.4.2 Glucose homeostasis in diabetes

In insulin resistance, hepatic glucose output remains high despite the presence of insulin (Mitrakou et al., 1992, DeFronzo et al., 1989), contributing to both postprandial and fasting hyperglycaemia (Yoon et al., 2001, Del Prato and Tiengo, 2001). Both increased accessibility to glucose precursors and dysfunctions at the enzymatic level contribute to this. For example, type 2 diabetic patients produce more lactate, and their livers converts lactate to glucose more efficiently (Zawadzki et al., 1988); and the rate of the Cori cycle is increased in obese patients with diabetes compared with healthy controls (Consoli et al., 1990).

Regarding enzymatic dysregulation, one of the most characterized alterations in diabetic patients is increased gene expression of the rate-limiting gluconeogenic enzyme Pck1 (Rognstad, 1979), as it can affect gluconeogenesis already at relatively small changes (Sun et al., 2002). Hyperglycaemic, transgenic mice overexpressing the Pck1 gene (under control of its own promoter), exhibit increased steady state levels of both hepatic Pck1 and G6pc (but normal Glut2 and glucokinase (Gck)), and these increased levels remains unaltered even when the insulin levels are decreased (Sun et al., 2002). Previously, Valera et al (1994) had shown that mice overexpressing Pck1 develop impaired glucose tolerance, fasting hyperglycaemia and hyperinsulinemia. Other experiments have revealed that Zucker

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diabetic rats – which have an impaired suppression of hepatic glucose output genetically – have perturbed whole body glucose homeostasis in association with increased G6PC activity (Trinh et al., 1998). In agreement with this, GCK (which catalyses the opposite reaction to G6PC) lowers plasma glucose concentration when up-regulated (Niswender et al., 1997).

Thus the increase in endogenous glucose output is complex and likely to be multifactorial in its origin. Intriguingly, as described in section 1.6.6, dysregulation of gluconeogenesis is common in fetal programming of adult disease.

1.7.2 Overweight and obesity

The prevalence of obesity has increased more than 2-fold worldwide over the past 30 years. According to WHO, over 200 million men and 300 million women were classified as obese in 2008 (Withrow and Alter, 2011). Adiposity and/or obesity, which often coexists with type 2 diabetes, hypercholesterolemia, hypertriglyceridemia, CVD and cancers (Mokdad et al., 2003), is a major public health issue. It also burdens the economy as it accounts for an average of 0.7-2.8% of a country’s total healthcare expenditures – and the medical cost for obese individuals are approximately 30% higher compared with normal weight people (Withrow and Alter, 2011). Just like diabetes, accumulating evidence suggests the intrauterine environment and IUGR are strongly associated with the onset of adiposity and obesity in adult life (Sarr et al., 2012).

1.7.2.1 Obesity in developmental programming

Many animal models that have examined in utero insults have showed a link between the maternal environment, IUGR and adult adiposity. Birth weight strongly correlates with adult fat mass (Fall et al., 1995, McMillen and Robinson, 2005) in a J- or U-shaped manner, where the obesity risk is highest in babies with low or high birth weights. Intriguingly, both diabetic (including type 2 diabetes, gestational diabetes and mildly glucose intolerant) (Buchanan and Kjos, 1999, Dorner and Plagemann, 1994) and overweight mothers (Parsons et al., 2001) are more likely to give birth to a heavy baby, potentially creating a vicious cycle. Babies born with a low birth weight usually have a lower BMI in adulthood – but they have more body fat which is often abdominally distributed (Fall et al., 1995, Singhal et al., 2003, Law et al., 1992). Also

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the well-established maternal low protein diet (50% protein restriction during pregnancy) leads to offspring obesity (Langley-Evans, 2001, Zambrano et al., 2006). Female but not male offspring exposed to protein restriction in utero had increased body fat and decreased lean mass at 70 days of age (Langley-Evans et al., 1996b). Maternal global undernutrition during the first 2 weeks of intrauterine life caused similar outcomes, but in offspring of both sexes (Anguita et al., 1993). Also placental insufficiency resulted in increased adiposity in male adolescent rat offspring (Joss- Moore et al., 2010). In agreement with this, human studies from the Dutch Winter famine resulted in low birth weight and subsequent obesity (Ravelli et al., 1976) (see section 1.2.2).

1.7.2.2 Adipose tissue as an endocrine organ

White adipose tissue consists of unilocular adipocytes with one large lipid filled vacuole and a cell nucleus pressed closely against the plasma membrane. Its fundamental role is to store energy (as triaglycerols) which can be released as fatty acids during food deprivation (Fantuzzi, 2005). It was long believed that adipose tissue was devoted to energy storage only, but during the last decades, it has become evident that it is highly metabolically active and regulates both physiologic and pathologic processes. It produces and secretes both pro-inflammatory and antiinflammatory factors including: cytokines and chemokines (tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6)) and adipokines (adiponectin, leptin) (Fantuzzi, 2005). As many of these have been implicated in the development of insulin resistance and CVD, and were examined in chapter 5 of this thesis, the following paragraphs discuss some of them briefly. Table 1.4 summarizes some of the established effects of cytokines and adipokines in metabolic dysfunction.

1.7.2.2.1 Inflammation

During obesity, the adipose tissue becomes inflamed via macrophagic infiltration and cytokine secretion (by adipocytes) (Wellen and Hotamisligil, 2005). The functional capability of adipocytes and marcophages overlaps as macrophages can accumulate lipids and become atherosclerotic foam cells (Wellen and Hotamisligil, 2005) – a crucial process in the development of peripheral insulin resistance. Obesity thereby itself promotes both a chronic low-grade inflammatory and insulin

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resistant state, but infusion of cytokines to non-obese animals also causes insulin resistance (Yu et al., 2002). Similarly, humans with chronic inflammatory conditions (including hepatitis C (Knobler et al., 2003) and rheumatoid arthritis (Sattar et al., 2003)), are more likely to develop diabetes, and removal of inflammatory pathways protects against insulin resistance (Wellen and Hotamisligil, 2005), supporting inflammation to be a primary cause of obesity-linked insulin resistance.

TNF-α was the first molecular link found between obesity and inflammation in both rodents (Sethi and Hotamisligil, 1999, Hotamisligil et al., 1993) and humans (Kern et al., 1995). Mice lacking TNF-α or its receptors exhibit improved insulin sensitivity compared with wild-type mice (Hotamisligil et al., 1993, Uysal et al., 1997). Many human studies have also correlated TNF-α messenger ribonucleic acid (mRNA) and protein levels in adipose tissue (Kern et al., 1995, Hotamisligil et al., 1995, Arner, 1996), and circulating TNF-α (Corica et al., 1999, Winkler et al., 1999) with insulin resistance. TNF-α phosphorylates serine residues and inactivates IRS-1, which reduces the relocation of GLUT4 to the cell membrane (Hotamisligil et al., 1996). Importantly, although circulating TNF-α modifies molecules in the insulin signaling pathway via posttranslational modifications, Tnf-α overexpression are seen in adipocytes from both obese rodents (Hotamisligil et al., 1993) and humans (Hotamisligil et al., 1995, Rotter et al., 2003). TNF-α also increases plasma TG, very low density lipoprotein (VLDL) (Peraldi and Spiegelman, 1998) and IL-6 (Kern et al., 1995).

Similar to TNF-α, plasma IL-6 is increased, and adipose expression levels up to 10- fold higher in obese and diabetic subjects compared with healthy controls (Fried et al., 1998, Kern et al., 1995). A range of factors, including nuclear factor kappa-light- chain-enhancer of activated B cells (NF-κB) (Ahn and Aggarwal, 2005), TNF-α, IL-6 itself (Fasshauer and Paschke, 2003, Rotter et al., 2003), stress and sex hormones (Eder et al., 2009) affects gene expression and circulating levels of IL-6. IL-6, a 21- 28 kDa polypeptide (depending on phosphorylation and glycosylation state) (May et al., 1988) exhibits both pro- and anti-inflammatory effects (Xing et al., 1998). Adipose tissue and adipocytes cultured in IL-6 also exhibit increased lipolysis (Eder et al., 2009, Trujillo et al., 2004) and IL-6 administration to non-obese humans increases systemic lipolysis (van Hall et al., 2003), which indirectly may induce insulin

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resistance (van Hall et al., 2003, Eder et al., 2009). Unlike TNF-α, IL-6 does not alter the phosphorylation status of IRS-1, but inhibits Irs-1, Glut4 and Pgc-1α on a transcriptional level (Rotter et al., 2003). Unsurprisingly, both insulin resistant (Pickup et al., 1997) and obese subjects (Mohamed-Ali et al., 1997, Fried et al., 1998) often have increased circulating levels of IL-6, which correlates with a prospect risk of developing type 2 diabetes – irrespective of amount body fat (Pradhan et al., 2001). According to a review by Eder et al (2009), although IL-6 increases plasma insulin, it reduces hepatic insulin sensitivity, insulin dependent glycogen synthesis, and glucose uptake in adipocytes – thus contributes to hyperglycaemia and hyperlipidaemia.

It is speculated that the inflammatory response is initiated in the cells first affected by adiposity – the adipocytes (Wellen and Hotamisligil, 2005). The adipocytes may trigger this inflammatory response via endoplasmic reticulum stress (which activates inflammatory pathways) (Ozcan et al., 2004); or via oxidative stress (caused by augmented glucose delivery to adipocytes and endothelial cells). The second mechanism produces reactive oxygen species in the mitochondria, inflicting oxidative damage and activation of inflammatory pathways (Brownlee, 2001). Inflammation is therefore both the cause and the result of obesity and diabetes, forming a vicious cycle in which either condition once, established can further contribute to the production of the other.

1.7.2.2.2 Adipokines

Altered levels of adipokines often coexist with inflammatory conditions, but our understanding of their mechanisms and pathogenic roles are incomplete.

Leptin

Leptin (a 16kD adipocyte-derived peptide hormone) circulates at levels proportional to fat and regulates fat mass and appetite by acting on the central nervous system (Trujillo et al., 2004). As reviewed by others (Friedman, 2002, Coleman, 1978), mice and humans with a mutation in the leptin gene (ob/ob mice), or in the leptin receptor gene (db/db mice) develop obesity (from hyperphagia), as the absence of leptin fail to communicate that there are adequate fat stores. In obesity, however, leptin levels are elevated due to leptin resistance, and plasma levels normally correlate positively

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with adipose tissue mass (Maffei et al., 1995), and increased IL-6 expression (Trujillo et al., 2004). Leptin’s role in developmental programming has been highlighted in several studies (Mantzoros et al., 2009, Martinez-Cordero et al., 2006). Leptin cord levels and fetal serum levels are lower in SGA children compared with normal weight infants; and neonatal leptin treatment of growth restricted piglets reverse both the high levels of cell proliferation in fetal adipose tissue, and the adult increase in adiposity (Vickers et al., 2005). It is therefore suggested that leptin regulates substrate utilization and maintenance of adipose tissue prior to birth; and that altered levels contribute to adult adiposity (McMillen and Robinson, 2005).

Adiponectin

Adiponectin is another adipose dervived adipokine synthesized from 4-6 trimers. Both the polymerized form and free trimers circulate in the plasma (Fantuzzi, 2005). Because the adiponectin gene locus overlaps with a diabetes susceptible locus (on human chromosome 3q27), adiponectin levels is suggested to affect the development of type 2 diabetes (Saito et al., 1999). In contrast to leptin, circulating adiponectin and mRNA expression tend to decrease with increased adiposity and diabetes (Hu et al., 1996, Arita et al., 1999); and correspondingly, high adiponectin levels are associated with a lower relative risk of type 2 diabetes (Spranger et al., 2003). Adiponectin also inhibits the activity of TNF-α and IL-6 (Fantuzzi, 2005, Masaki et al., 2004); and TNF-α and IL-6 suppress adiponectin secretion (Rotter et al., 2003). The literature regarding adiponectin levels in fetal programming is however inconsistent. Cianfarani et al (2004) reported adiponectin levels to be lower in SGA children and further reduced in the ones experiencing a postnatal catch-up growth, whereas others have shown a reverse relationship between adiponectin levels and birth weight (Lopez-Bermejo et al., 2004), or no changes at all (Chen et al., 2004). This inconsistency may result from differences in the study design and/or in the data analysis. For example, the study by Cianfarini et al (2004) did not adjust the levels of adiponectin the degree of insulin resistance or height (Cianfarani et al., 2004), whereas Lopez-Bermejo et al (2004) considered the inversely correlation between adiponectin levels and height in their study. Houde et al (2013) recently examined DNA methylation in the placenta and found that maternal glycaemia correlated with DNA methylation changes at two adipokine gene loci. However the

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involvement of epigenetics in fetal programming of adipokines requires more investigation.

Table 1.4 The effects of cytokines and adipokines in regulation of metabolism Factor Effect of obesity Mechanism TNF-α Increased in obesity Promotes insulin resistance Reduces adiponectin

IL-6 Increased in obesity Reduces hepatic insulin sensitivity and glycogen synthesis Reduces glucose uptake in adipocytes Increases plasma insulin and glucose levels Causes hyperlipidaemia Reduces adiponectin Increases leptin

Leptin Increased in obesity Suppresses appetite Protects T-lymphocytes from apoptosis

Adiponectin Decreased in obesity Anti-inflammatory; promotes insulin sensitivity Inhibits the activity of TNF-α and IL-6

TNF-α, tumour necrosis factor alpha; IL-6, interleukin 6.

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1.8 The scope of this thesis

Previous studies have shown that maternal alcohol when consumed prenatally, or throughout gestation harms the developing fetus and causes long-lasting changes in offspring physiology. The significance of the periconceptional period as a critical window of development has been emphasized in many studies; however the impact of periconceptional alcohol consumption on offspring metabolism has not been explored. This study therefore aimed to provide novel knowledge in the field of periconceptional alcohol exposure, particularly with respect to the developmental programming of metabolic outcomes.

1.8.1 Aims and hypotheses

1.8.1.1 Overall aims

The overall aims of this thesis were to:

1) Develop a rat model of maternal periconceptional alcohol consumption to investigate the role of the placenta in fetal programming and the metabolic phenotype of the adult offspring. 2) Examine whether a consumption of a western diet postnatally would unmask or exacerbate the programmed phenotype.

1.8.1.2 Overall hypotheses

We hypothesized that periconceptional exposure to alcohol would:

1) Impact on fetal growth via changes in placental biochemistry and morphology. 2) Result in sex-specific outcomes in glucose and lipid homeostasis in adult offspring. 3) Interact with a postnatal western diet to exacerbate the adult phenotype.

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1.8.2 Aims and hypotheses for chapter 3

Other studies of developmental programming demonstrate the importance of the placenta in the regulation of fetal body and organ development. Any alteration in placental physiology and function may contribute to adult onset disease – but whether periconceptional alcohol impacts on the placenta is unknown. The periconceptional period precedes placental development, but accompanying changes (secondary to PC:EtOH-exposure) may still affect the placenta, thus the developing fetus. Placental biochemistry and morphology were therefore examined as a possible mechanism to the adult phenotype in chapter 3.

The specific aims addressed in chapter 3 were to determine if periconceptional alcohol exposure:

i. Altered fetal phenotype in late gestation.

ii. Was associated with any morphological changes in the placenta.

iii. Affected placental gene expression of nutrient transporters or vasculogenesis.

iv. Resulted in sexually dimorphic differences.

We hypothesized that periconceptional exposure to alcohol would:

i. Result in utero growth restriction.

ii. Affect the morphology and biochemistry of genes involved in nutrient transport and vasculogenesis in the placenta.

iii. Affect placentas and fetuses in a sexually dimorphic manner.

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1.8.3 Aims and hypotheses for chapter 4

Fetal programming studies commonly demonstrate metabolic dysfunction following both prenatal and periconceptional insults. Often, these changes can be unmasked or exacerbated when a mismatch between the in utero and postnatal environment is introduced. Chapter 4 examined whether offspring of dams fed alcohol periconceptionally develop glucose intolerance and/or insulin resistance in adulthood; and whether a postnatal western diet exacerbated this phenotype.

The specific aims addressed in chapter 4 were to determine if periconceptional alcohol exposure:

i. Caused glucose intolerance and/or insulin insensitivity in offspring aged 6 months.

ii. Affected hepatic gluconeogenesis by examining mRNA expression of key gluconeogenic enzymes.

iii. Resulted in peripheral changes in the insulin signaling pathway.

v. Resulted in sexually dimorphic differences.

And;

iv. To examine if a postnatal western diet revealed or exacerbated any phenotype caused by periconceptional alcohol.

We hypothesized that:

i. Periconceptional alcohol would cause glucose intolerance and peripheral insulin sensitivity, accompanied by alterations in the insulin signaling pathway and increases in hepatic gluconeogenesis.

ii. Male offspring would be more susceptible to periconceptional alcohol, displaying a more severe phenotype than their female counterparts.

iii. A postnatal western diet would interact with periconceptional alcohol and exacerbate disease outcomes.

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1.8.4 Aims and hypotheses for chapter 5

While chapter 4 examined the propensity for a diabetic programmed phenotype following periconceptional alcohol exposure and a postnatal western diet; chapter 5 investigated the same combination on the development of adiposity and fat synthesis in offspring at 8 months of age.

The specific aims addressed in chapter 5 were to determine if periconceptional alcohol exposure:

i. Affected body composition in adult offspring.

ii. Induced changes in liver morphology and inflammation.

iii. Altered the plasma lipid profile.

iv. Resulted in sexually dimorphic differences.

And;

v. To examine if a postnatal western diet revealed or exacerbated any phenotype caused by periconceptional alcohol.

We hypothesized that:

i. Periconceptional alcohol would cause changes in offspring body composition, associated with changes in the plasma lipid profile and changes in liver morphology.

ii. Consumption of a postnatal western diet would exacerbate the programmed phenotype, especially in male offspring.

Chapter 2 General Methods and Materials

CHAPTER 2

General Methods and Materials

2.1 Ethics

All animal experiments and procedures were approved by The University of Queensland Anatomical Bioscience Animal Ethics Committee (AEC approval number SBS/022/12/NHMRC) prior to commencement of this study.

2.2 Animal husbandry

Outbred, virgin female Sprague Dawley rats 6-8 weeks of age were obtained from The Animal Resource Centre (Canning Vale, WA, Australia) and housed at the animal facility in the Australian Institute for Bioengineering and Nanotechnology at the University of Queensland. All rats were allowed to acclimatize to the new environment for at least one week and were exposed to the experimental control diet during a five hour period on two separate occasions to ensure acceptance. 3-4 rats were housed together in plastic cages with stainless steel wire lids under controlled temperature (20-22oC), relative humidity (40-50%) and an artificial 12 hour light-dark cycle. Of particular importance, the dark cycle was between 12.00 and 24.00 hours). All rats received standard rat chow (4.0% fat, 13.6% protein, 64.3% carbohydrates; 15.5 MJ/kg) (SF-08-020 Specialty feeds, Glenforrest, WA, Australia) and had access to ad libitum access to tap water.

2.2.1 Mating and start of the experimental protocol

For a summary of the experiment protocol, see Figure 2.1. Vaginal impedance was measured with an EC40 estrous cycle monitor (Fine Science Tools, Foster City, CA, USA) to determine the appropriate stage of the estrous cycle for mating. Vaginal secretions with a resistance of > 4.5×103 Ω at 9.00 hours indicated pro-estrous (and a high likelihood that the female rat would be in estrous within the following 12 hours). As the estrous cycle of a rat lasts for four days (Marcondes et al., 2002), dams were randomly allocated either a control liquid diet or a liquid diet containing

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12.5% EtOH (v/v) (13.8 EtOH-derived kcal/day, or ~22 energy percentages (E%) from EtOH). From this day, dams were housed individually and the allocated diet was provided. Dams that were in pro-estrous again four days after entering the experimental protocol were paired with a male Sprague-Dawley rat overnight (mating window 12.00 until 8.00 hours). Mating was confirmed by the presence of a seminal plug and this day was designated as E1. In cases where no plug was observed, a second mating was performed the following day. If mating was unsuccessful even the second time, the dam was excluded from the experimental protocol. Pregnant dams were returned to their individual cages on E1 and remained on their allocated experimental diets until E4. On E5, dams returned to standardized rat chow. All dams were weighed daily throughout the experimental protocol.

2.2.2 Experimental diet and chow

The liquid diet consisted of Sustagen® hospital formula (Mead Johnson® Nutritionals, Auckland, New Zealand), reduced fat milk (Coles supermarket, Australia) and corn flour (Coles supermarket, Australia). Minerals (ferric citrate, copper II sulphate and magnesium sulphate were obtained from Sigma-Aldrich (Missouri, USA) and selenium yeast from Selmenite®Blackmore (Balgowlah, NSW, Australia). The energy content of the EtOH liquid diet was modified to give similar energy percentages of protein, fat and calories compared with the control diet (Table 2.1). This diet was adapted following preliminary experiments that showed that dams consuming an EtOH containing diet drank a relative smaller volume than dams consuming a control diet (~22 mL/day vs. ~30 mL/day) (see section 6.2). The experimental liquid diets were made up daily. Absolute EtOH was added separately to each bottle to generate a diet consisting of 12.5% EtOH (v/v). This was achieved by adding 10 mL absolute EtOH to 70 mL liquid diet. The liquid diets were weighed prior to presenting them to the dams at 12.00 hours, and again 5 and 21 hours after. Standard curves were generated for both diets in order to determine the volume of diets consumed from the recorded weights, and EtOH and caloric intake were calculated from these curves. Dams had ad libitum access to the diet for 21 hours (between 12.00 and 9.00 hours). Tap water was offered between 9.00 and 12.00 hours. Water consumption was monitored throughout pregnancy by weighing the water bottles prior to and after administration of water. Following the 8 day exposure

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period, dams were returned to standardized rat chow and ad libitum access to water. Food intake over the remainder of pregnancy was recorded daily by subtracting the weight of remaining chow including any spill from the amount offered.

Table 2.1 Experimental liquid diet for untreated and ethanol treated dams Control diet (7.7 MJ/kg) Component Amount Energy (cal) Protein (g) Fat (g) Starch (g) Sustagen hospital formula 19.5 g 74.1 4.5 0.5 12.7 Corn flour 15.7 g 62.8 0.1 0.1 15.7 Selenium yeast 0.03 g 0.1 0.01 0.0 0.0 Low fat milk 58.3 mL 30.9 2.5 0.8 0.0 Sunflower oil 0.8 mL 6.7 0.0 0.8 0.0 Copper sulphate (50mM) 33.3 µL 0.0 0.0 0.0 0.0 Ferric citrate (199mM) 33.3 µL 0.0 0.0 0.0 0.0 Manganese sulphate (303mM) 33.3 µL 0.0 0.0 0.0 0.0 Absolute ethanol 0.0 mL 0.0 0.0 0.0 0.0 Total ~80.0 mL 174.7 7.1 2.2 28.4 Energy% 17.0 11.3 68.2

Ethanol diet (11.8 MJ/kg) Sustagen hospital formula 22.0 g 83.6 5.0 0.6 14.3 Corn flour 15.0 g 60.0 0.1 0.1 15.0 Selenium yeast 0.03 g 0.1 0.01 0.0 0.0 Low fat milk 50.0 mL 26.1 2.1 0.7 0.0 Sunflower oil 2.0 mL 16.2 0.0 1.8 0.0 Copper sulphate (50mM) 33.3 µL 0.0 0.0 0.0 0.0 Ferric citrate (199mM) 33.3 µL 0.0 0.0 0.0 0.0 Manganese sulphate (303mM) 33.3 µL 0.0 0.0 0.0 0.0 Absolute ethanol 10.0 mL 56.1 0.0 0.0 0.0 Total ~80.0 mL 242.5 7.3 3.2 29.3 Energy% 12.6 11.9 50.7

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2.2.3 Plasma alcohol concentration cohort

To avoid inducing stress to dams used for fetal and offspring studies, a separate cohort of dams (PC:EtOH-exposed dams (nPC:EtOH) = 10; untreated dams (nU) = 10) were generated to determine the PAC reached by the EtOH diet. This set of dams had blood collected from a tail vein (see section 2.5.1) two days prior to conception (E-2) and on day two of pregnancy (E2). Blood samples were collected prior to, and at 0.5, 1, 3, 5 and 21 hours after administration of the liquid diet. To limit stress to the dam and minimize blood loss, only two blood samples were taken from any one animal. These animals were not used for any other experiments.

2.2.4 Embryonic day 20 cohort

All animals from this cohort followed the experimental protocol outlined in sections 2.2-2.2.2. Dams allocated to this cohort were sacrificed for tissue collection on E20

(nPC:EtOH = 11; nU = 9) (see section 2.4.1).

2.2.5 Offspring cohort

All animals from this cohort followed the experimental protocol outlined in sections

2.2-2.2.2. Dams allocated to this cohort (nPC:EtOH = 12; nU = 12) delivered their pups naturally ~22 days after conception (designated as PN1). All pups were toe clipped for identification on PN6-PN8. Pups were weaned on PN28 and separated into plastic cages with stainless steel wire lids together with 3-4 littermates from the same sex. Offspring were allocated to various thesis experiments at the time of weaning. Offspring were kept under controlled temperature (20-22oC), relative humidity (40- 50%) and an artificial 12 hour light-dark cycle (dark cycle maintained between 12.00 and 24.00 hours). Offspring received standard rat chow (4.0% fat, 13.6% protein, 64.3% carbohydrates; 15.5 MJ/kg) (SF-08-020 Specialty feeds, Glenforrest, WA, Australia) until the age of 3 months. Water was offered ad libitum.

At 3 months of age, all rats were transferred to the animal house facility in the OTTO Hirschfield Building at The University of Queensland, with controlled temperature (20-22oC), relative humidity (40-50%) and an artificial 12 hour light-dark cycle (dark cycle maintained between 18.00 and 6.00 hours). Rats were allowed 1.5-2 weeks to acclimatize to the new environment and light-dark cycle. Following acclimatization, one subset of offspring from both sexes were randomly assigned a WD wth 65

Chapter 2 General Methods and Materials

increased fat and cholesterol (21% fat, 0.15% cholesterol, 19% protein, 59.9% carbohydrates; 19.4MJ/kg) (SF00-219 Specialty feeds, Glenforrest, WA, Australia) while one remained on the standardized chow. All groups had ad libitum access to allocated diet and water until termination of the study.

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E-4 Exposure to 12.5% (v/v) or 0% alcohol via a liquid diet E0 Mating E5 All dams on standard chow

E20 E20 post mortem Birth (PN1)

PN28 Weaning Blood sampling PN30 post mortem

Blood sampling

Half of the offspring starts a WD 3 3 months

Blood sampling

IPGTT & IPITT 6 6 months

DXA scan of body composition 7 7 months

Blood sampling

8 8 months 8 months post mortem Figure 2.1 – Timeline of experimental protocol from treatment to 8 months post mortem . . . . Dams were exposed to 12.5% alcohol (v/v) from 4 days prior to mating (E-4) until embryonic day (E)4 when all dams were offered standard chow. The fetal cohort was collected on E20. The offspring cohort was born on day 22 of gestation. One subset of offspring was sacrificed 2 days after weaning, on postnatal day (PN)30. At 3 months, half of the remaining offspring started a western diet (WD). Blood sampling was performed at 1, 2, 4, 6 and 8 months. An intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (ITT) were performed on rats at 6 months; and a dual-energy X-ray absorptiometry (DXA-scan) of body composition at 7 months. At 8 months, the last subset of animals for this thesis was sacrificed for tissue collection. 67

Chapter 2 General Methods and Materials

2.3 Offspring weight

Body weight of individual pups were taken daily from PN1-PN30. Weights for postnatal growth studies were taken as an average of the entire litter for each sex. Offspring > the age of PN30 were weighed weekly until the end of the experimental protocol, and postnatal growth studies used the average of the entire litter for each particular sex (and diet when age > 3 months).

2.4 Post mortem and tissue collection

2.4.1 Embryonic day 20 cohort

A B

Figure 2.2 – Fetal and placental collection procedure on embryonic day 20 . . Deeply anesthetized pregnant dam with the two uterine horns exposed (A), embryonic day (E)20 fetus attached to its placenta (B) and the placenta separated into the labyrinth (left) and the junctional layer (right) (C).

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On E20, maternal blood was collected via a tail vein (see section 2.5.1) prior to being deeply anesthetized with an intraperitoneal (i.p.) injection of a mixed solution containing 50/50 Ketamine/Xylazile (Lyppard Australia Ltd., Northgate, QLD, Australia) (0.1 mL/100g body weight) to ensure maternal blood supply continued to the fetuses during fetal and placental collection. Once the dam was adequately anesthetized and displayed no corneal and pedal reflexes, it was placed supine and the abdominal cavity open to expose the uterus (Figure 2.2 A). The uteri were placed on saline soaked gauze while each horn was cut open to expose fetuses in their amniotic sacs. Amniotic fluid was extracted from the amniotic sac with a syringe prior to being opened to expose the fetus. Fetal sex was at first determined anatomically by visual observation of the ano-genital distance and was later confirmed via genotyping (see section 2.9.7). A small incision was made in the fetal chest and blood drawn with a hematocrit capillary (see section 2.5.3) and pooled with blood collected from the same litter and sex. All fetuses and placentas (Figure 2.2 B) were separated and weighed to the nearest 0.1 µg. Fetal body dimensions (head width, measured from the front of the ears across the head; hind limb, measured from the base of the left heel to the knee; crown-to-rump length, measured from the middle of the ears in the center of the head to the hair line of the tail; snout-to-rump length, measured from the tip of the nose to the hair line of the tail) were taken using digital vernier calipers (accurate to 0.01 mm) (Figure 2.3 A-C). Placental dimensions (width, length and thickness) were measured to the nearest 0.01 mm (Figure 2.3 D-G) and immediately separated into the labyrinth and junctional zone (Figure 2.2 C). Placentas, fetal heart, kidneys and liver were quickly extracted and weighed, and either snap-frozen in liquid nitrogen and stored at -80oC for molecular analyses, or fixed in 4% paraformaldehyde (PFA) for histological analyses. Fetal tails were collected and snap-frozen in liquid nitrogen for genotyping. Following fetal collection, the dam was euthanized by diaphragm puncture, blood collected via cardiac puncture (see section 2.5.3) and liver collected and snap frozen in liquid nitrogen and stored at -80oC.

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A B

D E

F G

Figure 2.3 – Measurement of fetal and placental dimensions on embryonic day 20 . Measurement of fetal snout-to-rump length (A), head width (B) and hind limb length (C). A placenta separated from the fetus (D) for measurements of length (E), width (F) and depth (G).

Chapter 2 General Methods and Materials

2.4.2 Offspring cohort

Rats were anaesthetized with an i.p. injection of a mixed solution containing 50/50 Ketamine/Xylazile (Lyppard Australia Ltd., Northgate, QLD, Australia) (0.5 mL/100g body weight) between 8.00-11.00 hours, following an overnight fast. Body dimensions (head width, measured from the front of the ears across the head; hind limb, measured from the base of the left heel to the knee; crown-to-rump length, measured from the middle of the ears in the center of the head to the hair line of the tail; snout-to-rump length, measured from the tip of the nose to the hair line of the tail) were taken using digital Vernier calipers (accurate to 0.01 mm). Abdominal circumferences were determined by placing a thread around the middle of the waist and measure the length of the thread with a ruler (accurate to 1 mm). Ponderal index were later calculated by using the following formula:

��ℎ� �� = � 100 �� − �� − �� ℎ3 where weight is expressed in grams and snout-to-rump length in cm.

The rat was placed supine and the chest cavity opened. Blood was collected by cardiac puncture with a heparinized and ethylenediaminetetraacetic acid (EDTA) coated syringe (see section 2.5.3). Following blood collection, all major organs and intra-abdominal visceral fat were extracted and weighed. All tissues were either snap-frozen in liquid nitrogen and stored at -80oC for molecular analyses, or fixed in 4% PFA for histological analyses. In all cases, only one male and one female from each litter were used for each outcomes measure in all adulthood experiments.

2.4.3 Placental dry weight

Placental labyrinth and junctional zone dry weights were obtained by oven drying. For this purpose, the initial weight of labyrinth and junctional zones were recorded, the tissue placed in a weigh boat, covered with aluminum foil and dehydrated at 37oC. Tissues were weighed daily until weight did no longer change.

Chapter 2 General Methods and Materials

2.5 Blood collection

Blood sampling was performed via tail tipping on rats in the PAC cohort and on offspring at 2, 4, and 8 months of age. Offspring aged 8 months were fasted overnight prior to blood sampling. Blood sampling was performed via tail slicing for the glucose tolerance test (GTT) (following an overnight fasting period of 15 hours) and insulin tolerance test (ITT) (following a fasting period of 1 hour) on offspring aged 6 months. Blood sampling was performed via cardiac puncture on fetuses, dams and offspring on all post mortems (PM).

2.5.1 Tail tipping

An analgesic cream containing lidocaine and prilocaine was applied to the tip of the tail 5-15 minutes prior to the procedure. The rat was wrapped into a towel to restrict movements and placed in prone position with the tail exposed. Approximately 1 mm of the tip of the tail was cut of using a sterile surgical blade (Figure 2.4 A-B). A blood sample of 300-700 µL was collected into either a Microvette® lithium heparin coated tube or EDTA coated tube (1.6 mg EDTA per 1 ml blood) (Sarstedt Pty, Ltd., Technology Park, SA, Australia).

2.5.2 Tail slicing

Tail slicing was only performed for blood sampling during the GTT and ITT. All tail slicing procedures were performed in a quiet room with a temperature of 28-30oC to assist blood circulation. 10-20 minutes prior to the procedure, an analgesic cream containing lidocaine and prilocaine was applied to the tail. The rat was wrapped into a towel to restrict movements and placed in prone position with only the tail exposed. A small incision (~2 mm long and ~1 mm deep) was made with a sterile surgical blade in a lateral caudal vein to allow blood sampling. Blood samples of 200-300 µL were collected into Microvette® lithium heparin coated tube (Sarstedt, Pty, Ltd., Technology Park, SA, Australia) (Figure 2.4 C-D). For blood sampling over an extended period of time, the scab on the initial incision was removed by using a cotton bud soaked in heparinized saline. Whole blood glucose concentration was tested with Accu-Check® Performa (Roche Diagnostics, Pty, Ltd., Castle Hill, NSW, Australia) at every sampling to monitor blood glucose concentration during the procedure. Details of the GTT and ITT are described in section 2.6.

Chapter 2 General Methods and Materials

2.5.3 Cardiac puncture

During all PMs, blood was collected via cardiac puncture. With the rat placed supine, the chest cavity was opened and exposed. Blood was drawn into a heparinized syringe by inserting the syringe needle in the left ventricle and transferred to Microvette® lithium heparin coated tube (Sarstedt, Pty, Ltd., Technology Park, SA, Australia). Blood was also drawn into a non-heparinized coated syringe and transferred to EDTA coated tube (1.6 mg EDTA per 1 ml blood) (Sarstedt, Pty, Ltd., Technology Park, SA, Australia). For cardiac puncture on fetuses, the chest cavity was cut open, a small incision made in the heart and blood drawn with a hematocrit capillary (Hirschmann® Eberstads, Germany).

A B

C D

Figure 2.4 – Blood collection via tail tipping and tail slicing . . Tail tipping (A-B) was performed for all monthly blood collections and tail slicing (C-D) was performed for blood collections during the glucose- and insulin tolerance tests (GTT and ITT).

Chapter 2 General Methods and Materials

2.6 Assessment of glucose- and insulin homeostasis

2.6.1 Glucose tolerance test (GTT)

A GTT was performed on rats aged 6 months. Rats were fasted overnight (for 15 hours) and transferred to a quiet room with a temperature of 28-30oC. All GTTs were initiated between 8.00 and 9.00 hours. During the procedure, rats were housed individually in small plastic cages with a stainless steel lid and had ad libitum access to water. Following basal blood collection via tail slicing (see section 2.5.2), 1 g/kg body weight of glucose (Sigma-Aldrich, Sydney, NSW, Australia) (made up in saline) was administered via an i.p. injection. Further blood sampling took place at 5, 10, 20, 40, 60 and 90 minutes following the glucose administration. After the procedure, rats had access to standardized chow and water and were allowed to recover individually for one day, before being transferred back to their home cage.

2.6.2 Insulin tolerance test (ITT)

An insulin tolerance test was performed on a different subset of rats aged 6 months in order to avoid stressing the rats. Rats were fasted for 1 hour and transferred to a quiet room with a temperature of 28-30oC. All ITTs were initiated between 10.00 and 10.30 hours. During the procedure, rats were housed individually in small plastic cages with a stainless steel lid and had ad libitum access to water. Following basal blood collection via tail slicing (see section 2.5.2), 0.75 U/kg body weight of insulin (Actrapid, Novo Nordisk Pharmaceuticals Pty. Ltd., Baulkham Hills, NSW, Australia) made up in saline was administered via an i.p. injection. Further blood sampling took place at 5, 20, 40, 60, 90 and 120 minutes following the insulin administration. After the procedure, rats had access to standardized chow and water and were allowed to recover individually for one day, before being transferred back to their home cage.

2.6.3 Calculations for area under curves generated in the GTT and ITT

Basal glucose and insulin concentration from the GTT were used to calculate HOMA-IR (Duncan et al., 1995):

Chapter 2 General Methods and Materials

�� ( ) � �� ( ) �� − �� = �� 22.5

The HOMA-IR index is often used to estimate hepatic insulin sensitivity (Wallace et al., 2004) and although controversial, it has been shown to be a good predictor of insulin sensitivity in Sprague-Dawley rats (Cacho et al., 2008). To further validate the insulin resistance score, a quantitative insulin sensitivity check index (QUICKI) was calculated (Katz et al., 2000):

1 �� = �� log (�� (��) � log (�� ( �� )

A low QUICKI indicates low insulin sensitivity and a high QUICKI indicates high insulin sensitivity.

The area under the glucose curve (AUGC) and the area under the insulin curve (AUIC) for the IPGTT were calculated using the trapezius method with baseline defined as zero (Allison et al., 1995) using GraphPad Prism 6 Software (GraphPad Software Inc., San Diego, CA, USA). The AUGC was calculated as the incremental glucose area under the curve (AUC) from basal to 90 minutes (Figure 2.5 A). Total AUIC was calculated as the total incremental insulin AUC from basal to 120 minutes, or as first- plus second-phase insulin secretion (Figure 2.5 C-D). Before calculating AUGC following the ITT, the curves were inverted (Figure 2.5 B) and the total incremental area calculated from basal to 120 minutes. The insulin secretory response to glucose, or the ratio of AUIC to AUGC following the IPGTT, was calculated by dividing the total AUIC by the total AUGC.

Acute first-phase insulin secretion, which is indicative of acute insulin release from the pancreas in response to a glucose load (Del Prato and Tiengo, 2001, Kahn et al., 2008) was calculated as the incremental AUIC from basal to 5 minutes (Figure 2.5 C). Second-phase insulin secretion comprises a sustained, slow release of newly formed insulin from the β-cells in order to normalize the blood glucose concentration, and was calculated as the incremental AUIC from 5 to 120 minutes (Figure 2.5 D).

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A B Insulin injection

Glucose injection 0 -

C 1st phase insulin secretion D 2nd phase insulin secretion

Glucose injection Glucose injection

Figure 2.5 – Area under glucose and insulin curves ...... Area under the glucose curve (AUGC) following the IPGTT was calculated as the total incremental area from basal to 90 minutes (A). To determine the AUGC following the ITT, graphs were inverted and the total incremental area calculated from basal to 120 minutes (B). First phase-insulin secretion was calculated as the incremental AUIC from basal to 5 minutes (C) and second-phase insulin secretion as the incremental AUIC from 5 to 90 minutes (D).

2.7 Blood handling and plasma analyses

All blood samples were spun down at 3500 rpm for 15 minutes at 4oC using a refrigerating Eppendorf microcentrifuge 5417R (Quantum scientific, Eppendorf South Pacific, NSW, Australia) to allow for plasma separation. The plasma supernatant was transferred into aliquots to avoid repeated freeze thawing, and stored at -20 or -80oC depending on specific assay requirements until further analysis. Plasma used for PAC determination was stored in 0.5 mL PCR tubes, filled up to the lid to avoid evaporation, and snap-frozen in liquid nitrogen prior to being stored in -80oC until assayed.

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2.7.1 Cobas Integra analyses

A Cobas Integra 400 Plus Chemistry Analyzer system (software version 3.5) (Block Scientific, NY, USA) was used for determining plasma concentrations of enzymes and ions. Plasma glucose, TG, total cholesterol, low density lipoprotein (LDL) and high density lipoprotein (HDL) were measured in duplicates by absorbance photometry. Plasma sodium, potassium and chloride were measured in duplicates by ion-selective electrode potentiometry with assay detection. Catalogue number, detection range and sub- and main reference length for tested parameters are summarized in Table 2.2.

Table 2.2 Assay specifics for parameters analysed with Cobas Integra 400 plus Plasma parameter Instrument number Detection limit (mmol/L) Sub/main wavelength †Glucose #04404483190 0.11-41.6 700/340 †Triglycerides #20767107322 0.1-10 700/505 †Total cholesterol #03039773190 0.1-20.7 800/505 †LDL #03038866322 0.10-14.2 700/600 †HDL #04399803190 0.08-3.10 700/600 *Sodium #21029371001 N/A N/A *Potassium #21029355001 N/A N/A *Chloride #03246353001 N/A N/A

HDL, high density lipoprotein; LDL, low density lipoprotein; †tested with absorbance photometry; *tested with ion-selective electrode potentiometry.

2.7.2 Plasma alcohol determination

PAC was determined by the enzymatic colorimetric (565 nm) method using the EnzyChromTM EtOH assay kit and protocol (ECET-100) (Bio Assay Systems, Hayward, CA, USA) according to the manufacturer’s instructions. The EnzyChromTM EtOH assay kit is based on ADH catalyzed oxidation of EtOH, in which the NADH produced is coupled to the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT)/phenazine methosulfate (PMS) reagent. The color produced is proportionate to the EtOH concentration in the sample when measured at 565 nm. Briefly, 10 µL plasma sample was added to each reaction well in a clear bottom 96- well plate. 90 µL working reagent (consisting of 60 µL assay buffer, 1 µL enzyme, 10 µL NAD, 14 µL PMS and 14 µL MTT reagent) was added and solutions mixed by gently tapping the plate. Optical density (OD) was measured at time point zero (OD0) 77

Chapter 2 General Methods and Materials

and after 5 minutes incubation in room temperature (OD5). A ΔOD was calculated by subtracting OD0 from OD5 for standards and sample wells and used to determine sample EtOH concentration from the standard curve generated. All samples were tested in duplicates.

2.7.3 Hormone analyses

Plasma insulin and leptin was determined using a high sensitivity rat insulin or leptin Radioimmunoassay (RIA) kit containing the radioactive gamma isotope of iodine-125 (125I). Insulin concentrations were determined in plasma collected during the GTT at 6 months, and leptin concentration in plasma collected at PN30 and at 8 months.

The RIA assay is based on the competitive binding between unlabelled insulin/leptin antigen (in plasma samples) and radiolabelled insulin/leptin antigen to the insulin/leptin antibody. A tracer antigen, labelled with 125I-Insulin or 125I-Human-Leptin is added in a known concentration. The radiolabelled antigen tracer is incubated with a known amount of the antibody for that specific antigen, allowing for chemical binding between the two. As plasma samples with an unknown concentration (unlabelled antigen) is added, labelled antigen tracer and unlabelled antigen will compete for the limited (but constant) number of binding sites on the antibody. As the concentration of unlabelled antigen (from the test sample) increases, it displaces the amount of labelled antigen tracer that is bound to the antibody. As such the ratio of antibody bound labelled antigen to free labelled antigen decreases as the antigen concentration in the test sample increases. After separating bound antigens from unbound fractions, the bound fractions can be counted with a gamma counter and radioactivity measured. By generating a binding curve with standards provided in the kit (Figure 2.6), the amount of antigen in test samples are calculated as the inverse proportion to the amount of unlabelled insulin/leptin in the sample.

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Insulin RIA standard curve ) 0 Percentage bound (%B/B bound Percentage

Standard concentration (ng/ml)

Figure 2.6 – Insulin RIA standard curve generated with Assay Zap . .

A weighted 4-parameter curve graphing the percentage bound (%B/B0) for each standard on the y- axis versus the known concentration of each standard on the x-axis. The insulin concentrations for the test samples were determined by interpolation of the reference curve. The procedure for calculating plasma leptin concentrations is the same.

2.7.3.1 Plasma insulin determination

Insulin concentrations were determined following the manufacturers protocol, but modified by reducing all reagents and samples by half due to small sample volumes (Cat.#RI-13K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia) (Table 2.3). All samples for this assay were run in duplicates. Non-specific binding (NSB) tubes were prepared 125 by adding 100 µL assay buffer with 50 µL hydrated I-Insulin; reference (B0) tubes by adding 50 µL assay buffer with 50 µL hydrated 125I-Insulin; and insulin standards (0.16, 0.31, 0.63, 1.25, 2.5, 5.0 and 10.0 ng x mL-1) and quality controls (QCs) were prepared by adding 50 µL assay buffer, 50 µL hydrated 125I-Insulin and 50 µL insulin antibody (guinea pig anti-rat insulin serum in assay buffer) together. Plasma samples (25 µL) were diluted 1:2 or 1:4 as appropriate with assay buffer. 50 µL hydrated 125I- Insulin and 50 µL insulin antibody was added before vortexing and incubating in 4oC for 20-24 hours. Following incubation, 500 µL cold precipitating reagent (goat anti- guinea pig immunoglobulin G (IgG) serum) was added to all tubes except the total

Chapter 2 General Methods and Materials

counts tubes, samples vortexed and incubated in 4oC for another 20 minutes. Insulin 2 gamma count was performed with a 2470 Wizard TM automatic gamma counter (PerkinElmer, Inc. Massachusetts, USA) following a 45 minutes centrifugation at 3500 g at 4oC in a refrigerating Beckman C5-6R centrifuge (Beckman Coulter, Pty Ltd., Lane Cove, NSW, Australia) and decantation of supernatant. Plasma insulin concentrations were then calculated by automated data reduction procedures.

Table 2.3 Modified assay standard procedure for insulin radioimmunoassay Day 1 Day 2 Step 1 2-3 4 5 6 7 8 9-11 Set up

Tube content Assay Std/QC/test Rat insulin Precipitating 125 C I-tracer o (x2) buffer samples AB reagent

Total counts - - 50µl - rs at 4 - ou h

NSB 100µl - 50µl - 500µl 24 C - o

B0 50µl - 50µl 50µl 500µl Std 0.16 - 50µl of 0.16ng/ml 50µl 50µl 500µl , decant supernatant and and supernatant decant ,

Std 0.31 - 50µl of 0.31ng/ml 50µl 50µl 500µl Std 0.63 - 50µl of 0.63ng/ml 50µl 50µl 500µl Std 1.25 - 50µl of 1.25ng/ml 50µl 50µl 500µl

Std 2.50 - 50µl of 2.5ng/ml 50µl 50µl 500µl count perform Std 5.00 - 50µl of 5.0ng/ml 50µl 50µl 500µl Std 10.0 - 50µl of 10.0ng/ml 50µl 50µl 500µl C for 45 minutes at 3500 at minutes 45 C for o

QC1 - 50µl of QC1 50µl 50µl 500µl 4 at minutes 20 for incubate and Vortex QC2 - 50µl of QC2 50µl 50µl 500µl Test sample 1 25µl 25µl test sample 50µl 50µl 500µl Centrifuge at 4 at Centrifuge

Test sample 2 25µl 25µl test sample 50µl 50µl 20 for incubate and foil, aluminum with cover Vortex, 500µl

B0, reference tube; NSB, non-specific binding; QC, quality control; std, standard. All procedures were following the manufacturers’ protocol but modified by reducing all reagents and samples by half as shown in the table. Adapted from (Cat.#RI-13K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia).

2.7.3.2 Plasma leptin determination

Leptin concentrations were determined following the manufacturers protocol (Cat.#XL-85K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia) (Table 2.4). All samples for this assay were run in duplicates. On day one, 300 µL assay buffer were added into

NSB tubes. B0 tubes were prepared by adding 200 µL assay buffer with 100 µL leptin antibody (guinea pig anti-multi-species leptin antibody in assay buffer); and leptin standards (0.20, 0.39, 0.78, 1.56, 3.13, 6.25, 12.5, 25.0, 50.0 and 100.0 ng x mL-1)

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and QCs by adding 100 µL assay buffer with 100 µL standard/QC and 100 µL leptin antibody. Plasma collected from rats aged 8 months were run in a 1:3 dilution (50 µL sample + 150 µL assay buffer), and plasma collected at PN30 in a 3:1 dilution (150 µL sample + 50 µL assay buffer). 100 µL leptin antibody was added to test samples. Tubes were mixed by vortexing and incubated in 4oC for 20-24 hours. Following incubation, on day two, 100 µL 125I-Human-Leptin tracer was added to all tubes, and tubes were mixed again by vortexing and incubated in 4oC for 20-24 hours. On day three, 1 mL cold precipitating reagent (goat anti-guinea pig IgG serum) was added to all tubes except the total counts tubes. Tubes were gently vortexed and incubated in 4oC for another 20 minutes. Leptin gamma count was performed with a 2470 2 Wizard TM automatic gamma counter (PerkinElmer, Inc. Massachusetts, USA) following a 30 minutes centrifugation at 3000 g at 4oC in a refrigerating Beckman C5- 6R centrifuge (Beckman Coulter, Pty Ltd., Lane Cove, NSW, Australia) and decantation of supernatant. Plasma leptin concentrations were then calculated by automated data reduction procedures.

Chapter 2 General Methods and Materials

Table 2.4 Modified assay standard procedure for leptin radioimmunoassay Day 1 Day 2 Day 3 Step 1 2-3 4 5 6 7 8 8 9-11 Set up

Tube content Assay Std/QC/test Leptin Precipitating 125I-tracer (x2) buffer samples AB reagent

C C

Total counts - - - o 100µl o - NSB 300µl - - 100µl 1000µl rs at 4 rs at 4 rs at

B 200µl - 100µl ou 100µl ou 1000µl

0 h h

C 24 24 o *Std 0.20 100µl 100µl of 0.20ng/ml 100µl - 100µl - 1000µl 20 20 *Std 0.39 100µl 100µl of 0.39ng/ml 100µl 100µl 1000µl *Std 0.78 100µl 100µl of 0.78ng/ml 100µl 100µl 1000µl Std 1.56 100µl 100µl of 1.56ng/ml 100µl 100µl 1000µl , decant supernatant and perform count perform and supernatant decant ,

Std 3.13 100µl 100µl of 3.13ng/ml 100µl 100µl 1000µl g

Std 6.25 100µl 100µl of 6.25ng/ml 100µl 100µl 1000µl 00 Std 12.5 100µl 100µl of 12.5ng/ml 100µl 100µl 1000µl Std 25.0 100µl 100µl of 25.0ng/ml 100µl 100µl 1000µl luminum foil, and incubate for for incubate and foil, luminum for incubate and foil, luminum Std 50.0 100µl 100µl of 50.0ng/ml 100µl 100µl 1000µl Vortex and incubate for 20 minutes at 4 at minutes 20 for incubate and Vortex

*Std 100.0 100µl 100µl of 100ng/ml 100µl 100µl 1000µl 30 at minutes 30 for

C QC1 100µl 100µl of QC1 100µl 100µl 1000µl o QC2 100µl 100µl of QC2 100µl 100µl 1000µl Vortex, cover with a with cover Vortex, a with cover Vortex, Test sample 1 50µl 150µl test sample 100µl 100µl 1000µl

Test sample 2 50µl 150µl test sample 100µl 100µl 1000µl 4 at Centrifuge

B0, reference tube; NSB, non-specific binding; QC, quality control; std, standard. All procedures were following the manufacturers’ protocol. Standard curve was extended (*) to allow for a wider detection limit. The table is showing a 1:3 dilution of test samples. Adapted from (Cat.#XL-85K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia).

Chapter 2 General Methods and Materials

2.7.3.3 Automated data reduction procedures

For determination of plasma insulin and leptin concentrations, a weighted 4- parameter curve was generated in Assay Zap (Biosoft® version 3.2) (Figure 2.6). The average count per minute (cpm) of the NSB tubes were subtracted from the average cpm of each sample and test sample to generate a total binding counts value. This value was then used to determine the percentage of tracer bound, which was calculated by:

�� % �� = � 100 �� where the total counts are the current cpm measured from the hydrated 125I-tracer. The percentage tracer bound should be between 35-50%.

The percentage of total binding (%B/B0) for each standard and sample was the calculated by:

�� %�/� = � 100 0 ��

The %B/B0 was plotted using the standard values on the y-axis and the known concentrations of the standards on the x-axis. The insulin and leptin concentrations in the test samples and QCs were determined in ng x mL-1 by interpolation of the reference curve. Appropriate mathematical adjustment were made to accommodate for the dilution factor, in this case, the value from a 1:2 dilution was multiplied by 2, the value from a 1:3 dilution by 3, the value from a 1:4 dilution by 4 and a value from a 3:1 dilution was divided by 3.

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2.7.3.4 Plasma adiponectin determination

Plasma adiponectin was determined with enzyme-linked immunosorbent assay (ELISA) (limit of sensitivity 0.4 ng/mL) (Cat#EZRADP-62K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia) according to the manufacturers instructions (Table 2.5). Test samples were diluted to 1:500 in 1x assay buffer. The dilution was made in two steps. First, 10 µL test sample was added to 990 µL assay buffer (dilution A; 1:100), and then 100 µL of dilution A was added to 400 µL assay buffer (dilution B; 1:500). All reagents were pre-warmed to room temperature before use. Assay strips were placed in a microliter assay plate and washed three times with 300 µL provided wash buffer. Wash buffer and residual amount was decanted from the wells between every wash by inverting the plate and tapping it onto absorbent towels several times. 80 µL assay running buffer was added to each well together with 20 µL standards, QCs or test sample. The assay plate was covered with plate sealer and incubated in room temperature for 2 hours on a Heidolph Titramax 100 orbital microliter plate shaker at 500 rpm (John Morris Scientific Pty, Ltd., Chatswood, NSW, Australia). Following incubation, the plate was washed a second time (same washing procedure as the first time). 100 µL rat pre-titered bioinylated monoclonal anti-Adiponectin antibody was added to each well using a multi-channel pipette and the plate was sealed and incubated for 1 hour in room temperature at 500 rpm. The plate was then washed a third time before adding 100 µL enzyme solution (pre-titered streptavidid-horseradish peroxidase conjungate in buffer) using a multi-channel pipette. After another 30 minutes incubation in room temperature at 500 rpm, and another three washes, 100 µL substrate solution (containing 3,3’,5,5’-tetramethylbenzidine in buffer) was added to each well. The plate was placed in room temperature on the plate shaker at 500 rpm for 8-15 minutes to allow for color change (intensity proportional to increasing concentrations of the rat adiponectin standards). 100 µL of stop solution (containing 0.3 M hydrochloric acid (HCl)) was added to each well and the plate gently agitated. Absorbance was immediately read at 450 nm and 590 nm in a Tecan SunriseTM Micro plate Absorbance reader (Tecan Pty, Ltd., Port Melbourne, VIC, Australia) and the difference of absorbance units recorded.

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Table 2.5 Assay procedure for plasma adiponectin ELISA Step 1 2 3 4 5 6 7 8 9 10 11 12 Well# Running Std/QC/test Enzyme Substrate Stop µl µl

Antibody buffer samples solution solution solution Std 0 100µl - 100µl 100µl 100µl 100µl µl wash wash µl

µl wash wash µl µl wash wash µl

Std 3.1 80µl 20µl of 3.1ng/ml 300 with es 100µl 100µl 100µl 100µl

Std 6.3 80µl 20µl of 6.3ng/ml 100µl 100µl 100µl 100µl

Std 12.5 80µl 20µl of 12.5ng/ml 100µl 100µl 100µl 100µl

Std 25 80µl 20µl of 25ng/ml 100µl 100µl 100µl 100µl

µl wash buffer and remove residual residual remove and buffer wash µl 80µl 20µl of 50ng/ml 100µl 100µl 100µl 100µl

Std 50 solutions.

Std 100 80µl 20µl of 100ng/ml 100µl 100µl solutions. residual remove 100µl 100µl 25 min in RT. Wash 3 times with 300 with times 3 Wash RT. in min 25 - Std 200 80µl 20µl of 200ng/ml 100µl 100µl 100µl 100µl buffer and remove residual solutions. residual remove buffer and buffer and solutions. residual remove buffer and

QC2 80µl 20µl of QC2 100µl 100µl 100µl 100µl nm. and 590 nm 450 at Read absorbance wash buffer and remove residual solutions. residual remove and buffer wash

Sample1 80µl 20µl of sample 1 100µl 100µl 100µl 100µl Seal and incubate 1 hour in RT. Wash 3 times with 300 with 3 times Wash RT. in hour 1 incubate Seal and Seal and incubate 30 min in RT. Wash 3 times with 300 with times 3 Wash RT. in min 30 incubate Seal and Wash plate 3 times with 300 with 3 times plate Wash Sample 2 80µl 20µl of sample 2 100µl 100µl 100µl 5 incubate Seal and 100µl Seal and incubate 2 hours in RT on shaker. Wash 3 tim 3 Wash shaker. RT on in hours 2 incubate Seal and

QC, quality control; RT, room temperature; Std, standard. All procedures were following the manufacturers’ protocol. Adapted from (Cat.#EZRADP-62K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia).

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A sigmoidal 4-parameter logistic equation was generated in Assay Zap (Biosoft® version 3.2) (Figure 2.7) and the concentration of adiponectin in test samples calculated based on the values of the standards.

Adiponectin ELISA standard curve 450nm) - Log absorbance (590nm absorbance Log

Standard concentration (ng/ml)

Figure 2.7 – Standard curve generated with Assay Zap for determination of adiponectin . . . A sigmoidal 4-parameter logistic equation graphing the logarithm of the difference of absorbance units between 590 and 450 nm for each standard on the y-axis versus the known concentration of each standard on the x-axis. The adiponectin concentrations for the test samples were determined by based on the standard values.

2.7.4 Plasma osmolality determination

Plasma osmolality is a measurement of the body’s electrolyte-water balance and was determined using a Vapor Pressure Osmometer (5520 WESCOR, Helena Laboratories, Australia) (detection range 20-3200 mmol/kg).

2.8 Body composition measurements

Body composition (total fat mass (FM), total fat free mass (FFM), abdominal fat mass, bone mineral density (BMD) and bone mineral content (BMC)) were measured with a dual-energy X-ray absorptiometer (DXA; model XR36, Norland). Rats were anesthetized with an i.p. injection of a 50/50 mix of Zoletil/Xylazile (0.1 mL/100g

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body weight) and scanned in prone position. To avoid dryness of the eyes, saline was continuously applied onto the eyes with a syringe tube. Following the scan, rats received an intramuscular injection of 2-6 mL saline in the subscapular region to prevent dehydration and to facilitate recovery. Rats were allowed to recover in individual cages, with ad libitum access to tap water, hydrogels (Clear H2O, Portland, ME, USA) and moist rat chow. Scans were analysed using the manufacturer’s recommended software for use in laboratory animals (Small subject analysis software, version 2.5.3/1.3.1, Norland) (Figure 2.8).

A B C

Figure 2.8 – DXA-scan of body composition . . An anesthetized rat undergoing a DXA-scan of body composition (A), an image of a control fed (B) and WD fed (C) male rat generated for analyze of body composition and abdominal fat content (square).

2.9 Gene expression analysis

Relative mRNA expression for a range of genes of interest (GOI) was determined by quantitative real-time polymerase chain reaction (qPCR) in a variety of tissues from E20 and offspring cohorts.

2.9.1 RNA extraction

For the purpose of this thesis, RNA was extracted from liver, placental labyrinth and junctional zones, and visceral intra-abdominal mesenteric adipose tissue. Extraction of these tissues required different protocols which are described in detail in the following sections.

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2.9.1.1 RNA extraction from liver and placental compartments

Total RNA was extracted from frozen tissues (20-30 mg) using an RNeasy Mini Kit (QIAGEN, Doncaster VIC, Australia). The homogenization buffer contained 1% (v/v) of β-mercaptoethanol for every mL of RLT buffer. Frozen samples were homogenized for 45-60 seconds in 600 µL of the RLT buffer using an Ultra-Turrax T8 homogenizer (IKA, Labtek, Brendale, QLD, Australia). Between each sample, the probe was cleaned in distilled water and by 100% EtOH to prevent cross contamination. The homogenized samples were centrifuged using a refrigerating Eppendorf microcentrifuge 5417R (Quantum scientific, Eppendorf South Pacific, NSW, Australia) at 14,000 rpm for 3 minutes at room temperature to allow for separation of the RNA containing aqueous phase from the DNA/protein containing pellet. The supernatant was transferred to a sterilized 1.5 mL Eppendorf tube. One volume of 70% EtOH was added and mixed by pipetting. 600 µL aliquots were pipetted out and transferred to an RNA spin column (pre-inserted into a collection tube) and centrifuged at 14,000 rpm for 30 seconds at room temperature. This step was repeated with the remaining 600 µL of supernatant/EtOH mix. 350 µL provided wash buffer was added to the spin column and samples centrifuged again at 14,000 rpm for 30 seconds. 80 µL of deoxyribonuclease (DNase) in RDD (12.5 % (v/v)) were pipetted directly on to the membrane of the spin column and samples were rested for 15 minutes at room temperature. Spin columns were washed again in 350 µL wash buffer and two times in 500 µL provided RPE buffer. RNA was then eluted from the spin column using two aliquots of 30 µL of ribonuclease (RNase)/DNase free water (InvitrogenTM) centrifuged through the column at 14,000 rpm for 1 minute. A total of 60 µL of RNA was obtained from each sample and stored in -80oC prior to performing complementary Deoxyribonucleic acid (cDNA) synthesis.

2.9.1.2 RNA extraction from visceral abdominal adipose tissue

For adipose tissue, total RNA was extracted from frozen tissues (80-90 mg) using an RNeasy Mini Kit (QIAGEN, Doncaster VIC, Australia). Adipose tissue was homogenized in 1000 µL Trizol lysis reagent for 20-40 seconds using an Ultra-Turrax T8 homogenizer (IKA, Labtek, Brendale, QLD, Australia). The homogenate was rested in room temperature for 5 minutes. 200 µL chloroform was added to the homogenate and samples vigorously shaken for 20 seconds. Samples were

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incubated in room temperature for another 3 minutes before being centrifuged at 14,000 rpm for 15 minutes at 4oC. The chloroform allows the sample to separate into a clear upper aqueous layer (containing the RNA), an interphase, and a pink/red lower layer (containing the DNA and proteins). The upper phase was carefully transferred to a sterilized 1.5 mL Eppendorf tube and one volume (~600 µL) of 70% EtOH was added. Samples were mixed by pipetting and aliquots were transferred to a RNA spin column (pre-inserted into a collection tube) and centrifuged at 14,000 rpm for 30 seconds at room temperature. From this step onwards, the procedure followed the same protocol as described for liver and placental compartment RNA extraction (see section 2.9.1.1). However, due to very low yield of RNA, only 30 µL of RNase/DNase free water (InvitrogenTM) was added to elute the RNA from the spin column. Thus a total of 30 µL of RNA was obtained from each adipose sample and stored in -80oC prior to performing cDNA synthesis.

2.9.2 RNA concentration and purity

The concentration and purity of RNA were measured using a NanoDrop ND1000 spechtrophotometer (NanoDrop Technologies, Wilmington, DE, USA) (Figure 2.9). Calibration was performed by adding 1 µL of RNase-free water onto the measurement pedestal sensor of the NanoDrop in order to blank the system to zero. 1 µL of extracted RNA per sample was placed onto the measurement pedestal sensor to create a reading. Sample and blank intensities were used by the NanoDropto calculate the sample absorbance wavelengths at 260 nm and 280 nm (ND-1000 Data Viewer). Although we did not check the integrity of all RNA samples by running them on a gel, any samples that did not give the expected 260:280 ratio or gave a value for 18S outside the expected range was either re-extracted or excluded from the analysis.

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Figure 2.9 – Measurement of RNA concentrations using a Nanodrop spectrophotometer . . . The curve generated when measuring ribonucleic acid (RNA) concentration using a Nanodrop spectrophotometer. The concentration of RNA is calculated from the A260/A280 ratio.

The Beer-Lambert equation is used to correlate the calculated absorbance with concentration:

(� � ��) � = 260 �

Where: C = concentration of RNA (ng/µL)

A260 = absorbance at 260 nm ec = wavelength-dependent extinction coefficient (a constant: 40 ng-cm/µL for RNA) B = the path length of the NanoDrop (1 mm)

Both RNA and protein absorbs light at distinct wavelengths (i.e. 260 nm and 280 nm). Therefore, the purity was also evaluated by obtaining an A260/A280 ratio. By comparing the absorbance values at 260 nm and 280 nm, the proportion of RNA relative to protein in the sample can be calculated. Samples with A260/A280 ratio 1.8-

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2.1 μg/μL were considered as a relatively pure RNA sample and used for cDNA synthesis.

2.9.3 Reverse transcription of RNA to cDNA cDNA synthesis from RNA was performed using the iScriptTM Reverse Transcription Supermix for RT-qPCR (Bio-Rad). 1 µg of total RNA was combined with 2 µL of 5x iScript reverse transcription supermix and made up to 10 µL with nuclease-free water. The cDNA synthesis step also contained a No-RT control to reveal the presence of genomic DNA (gDNA). This reaction contained the same amount of RNA as the reverse transcription reaction to allow similar carryover of cDNA synthesis components in qPCR, but the 5x iScript reverse transcription supermix was replaced by a negative reverse transcriptase. Samples were incubated at 25oC for 10 minutes for enzyme activation, followed by 42oC for 30 minutes extension phase. The reaction was terminated at 85oC for 5 minutes to allow for denaturation using a PCR Express Thermal Cycler (Thermo Fisher Scientific, Wilmington, DE, USA). Samples were stored in -20oC until quantifying gene expression by qRT-PCR assay.

2.9.4 Quantifying gene expression

Gene expression was quantified via TaqMan® or SYBR® Green-based detection chemistry. As almost all genes examined in this thesis were quantified using Taqman®in the following sections, whereas the SYBR® Green-based detection chemistry is only described briefly.

2.9.4.1 TaqMan® detection chemistry mRNA expression is measured by the fluorescence emitted during the polymerase chain reaction (PCR) as an indicator of amplicon (i.e. the PCR product) production during each PCR cycle in ‘real-time’. A laser is directed to each sample well with fluorescence emission data collected once every few seconds for each sample as the PCR product is being generated. A fluorescent reporter detects and measures the amount of PCR product formation by the number of copies of the nucleic acid target. As the starting copy number is determined by when the PCR product is first detected, the higher the starting copy number, the more fluorescence will be emitted and this in turn indicates a higher gene expression of the nucleic target. The 91

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fluorescence signal, which increases exponentially, is measured by the cycle threshold (CT) (PCR cycle number at which the reporter dye fluorescence exceeds background level and is proportional to the level of gene expression in a given tissue).

Taqman® probes are oligonucleotides which contain a reporter dye at the 5’ end and a quenching dye at the 3’ end (Figure 2.10). For the purpose of this thesis, 18s ribosomal RNA (Rn18s) was used as the endogenous control (labelled at the 5′ end with VIC; 2′-chloro-7′-phenyl-1,4-dichloro-6-carboxyfluorescein). All probes were labelled at the 3’ end with the florophore FAM; V6-carboxyfluorescein (TaqMan® Ribosomal RNA Control Reagents kit, Applied Biosystems, Mulgrave, VIC, Australia). When excited by the cycler’s light source, the quenching molecule quenches the fluorescence emitted by the reporter dye via FRET (Bustin, 2000). During the extension phase, when the Taq polymerase replicates a template DNA strand on which a TaqMan® probe is bound, its 5’exonuclease activity will cleave the probe, causing the probe to cleave, and the fluorescent and quenching dyes to decouple, thus terminating the FRET. The increased fluorescence in each cycle is therefore directly proportional to the amount of probe cleaved and PCR product formed. When well designed, TaqMan® probe chemistry provides the highest level of specificity for the PCR and requires very little optimization. It is the most commonly used detection chemistry for reverse transcription polymerase chain reaction (RT-PCR). TaqMan® detection chemistry and assay on demand (AOD) (Applied Biosystems, Foster City, CA, USA) assays were used to determine relative gene expression of various genes throughout this thesis (Table 2.8).

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Figure 2.10 – The principle of Taqman® detection chemistry A schematic presentation of the principle of Taqman® polymerization, strand displacement, cleavage and completion of cycle. Adapted from (Yuan et al., 2000).

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2.9.4.2 SYBR®Green-based detection chemistry

SYBR® Green is a non-sequence specific double stranded (ds) intercalating dsDNA binding dye which fluoresces once bound to the dsDNA (Figure 2.11). The target gene is amplified using a pair of specific primers and the amount of dye incorporated is proportional to the amount of generated target. When the dye emits at 520 nm, fluorescence emitted is detected and related to the amount of target. As SYBR® Green will bind to any dsDNA, primers needs to be very specific to the target, which generally requires sufficient optimization. The specificity of the system is validated at the end of the PCR run by creating a melt curve (Figure 2.12). As every product has a specific dissociation temperature, depending on the size and base content, the melt curve is an indication of the number of products amplified. An optimized SYBR® Green reaction will produce one single unique, well defined peak on the melt curve. The first step of a SYBR® Green reaction is DNA denaturation. This is followed by primers anneal and the free SYBR® Green molecules in the reaction mix binds to the dsDNA. DNA polymerase then elongates the template during the extension phase and allows for more SYBR® Green molecules to bind to the product. Subsequently, this results in an exponential increase in the fluorescent level.

Figure 2.11 – The principle of SYBR® Green detection chemistry A schematic presentation of the principle of SYBR® Green detection chemistry. The initial annealing phase is followed by an extension phase, in which free SYBR® Green molecules bind to the dsDNA to produce an exponential increase in the fluorescence level. Adapted from (van der Velden et al., 2003).

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Figure 2.12 – A melt curve generated with SYBR® Green detection chemistry . The melt curve generated in a SYBR® Green reaction is dependent on each products’ size and base content. When optimized, the reaction produces one unique, well defined peak on the melt curve.

2.9.5 Real-time PCR

Real-time PCR was performed using a StepOne™ Real-Time PCR system (Applied Biosystems, VIC, Australia) in 10 µL reactions (2.5 µL of 1:10 dilution of cDNA (1:5 dilution for adipose tissue)) as shown in Table 2.6. Before measuring gene expression for the GOI with Taqman®, reactions were tested with (multiplex) and without 18s (singleplex) at different sample concentrations (1:10, 1:100 and 1:1000) for each primer set and tissue in duplicates. In cases were 18s did not significantly affect the amplification of the primer set, reactions were multiplexed (Figure 2.13). In all other cases, reactions were singleplexed.

All reactions were run in duplicates. The thermal cycling conditions for Taqman® consisted of: 1) an incubation step at 50oC for 2 minutes; 2) an initial denaturation stage at 95oC for 10 minutes; 3) 40 cycles of 95oC for 15 seconds to denature the cDNA into single strands; and 4) annealing/extension at 60oC for 1 minute. For SYBR® Green, the thermal cycling parameters consisted of: 1) 10 minutes at 95oC; 2) a 40 cycle denaturation stage for 15 seconds at 95oC; and 3) an annealing/extension phase at 60oC for 1 minute. The melt curve for SYBR® Green was generated at the end of the thermal cycling using the Applied Biosystems real- 95

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time PCR system. Data obtained from the RT-PCR reactions were analyzed using the StepOne™ sequence detection system (StepOne™ Software v2.2.2, Applied Biosystems, VIC, Australia). Each PCR template contained three calibration samples, one water and four negative controls prepared during the cDNA synthesis to monitor gDNA, contamination and non-specific binding.

Table 2.6 Recipe for real-time PCR reactions with Taqman® and SYBR® Green Taqman® Amount per well (µL) SYBR® Green Amount per well (µL) Mastermix 5 Mastermix 5 18s 0.1 18s 1* AOD 0.25 Probe/primer set (4ng/ml) 1* 1:10 cDNA (sample) 2.5 1:10 cDNA (sample) 2.5

Rnase free H2O 2.15 Rnase free H2O 1.5 Total 10 10

18s, 18s ribosomal ribonucleic acid; AOD, assay on demand; cDNA, complementary Deoxyribonucleic acid. Recipe for a real-time PCR reaction with Taqman® and SYBR® Green detection chemistry per reaction well. When singleplexed, reaction volume was adjusted with RNase free water (H2O). *, All SYBR® Green were singleplexed with each reaction containing either 18s or the probe/primer set.

a b

c e

Figure 2.13 – An amplification plot generated by the real-time PCR system . . . . . An amplification plot of a multiplexed reaction (left curve 18s, right curve gene of interest). The plateau phase (a), linear phase (b), exponential phase (c), background (d) and threshold (e) are indicated for the curve showing the gene of interest.

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2.9.6 Quantification of gene expression

Relative gene expression results were analyzed using the comparative CT method in which the difference between the average CT-values of the gene of interest and the endogenous control 18s ribosomal RNA was calculated for each sample (ΔCT) according to:

ΔCT = ACT(GOI) – ACT(18s)

The ΔCT for each sample was further normalized to the ΔCT of a calibrator sample

(i.e. the control group), creating a ΔΔCT value:

ΔΔCT = ΔCT (sample) - ΔCT (calibrator)

The ΔΔCT value was transformed to an absolute value that allows for gene expression levels to be represented as a fold-change relative to the calibrator used. The formula used for the comparative expression level was:

- ΔΔC 2 T

2.9.7 Fetal genotyping

Identification of DNA for the sex-determining region Y (Sry) sequence is the most accurate way to determine fetal sex as the use of this method has eliminated the possibility of contamination by maternal tissue.

At the time of PMs for the E20 cohort, fetal tails were collected and snap frozen in liquid nitrogen for determination of fetal sex. Tails were incubated in lysis buffer (Table 2.7) containing 0.2 mg/mL proteinkinase K (Promega) overnight at 55oC. Proteinkinase K was deactivated by heating at 95oC for 10 minutes followed by vortexing of tissue samples. Samples were then centrifuged at 4oC at 10 000 rpm for 10 minutes. A multiplexed RT-PCR reaction for the Sry gene (Sry, Mm00441712_s1) was performed directly on the supernatant as described in section 2.9.5 to detect gDNA.

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Table 2.7 Lysis Buffer Reagent Volume/weight KCl 1.15 g 1M TRIS-HCl pH 8.3 2 mL

1M MgCl2 0.4 mL Gelatin 20 mg Nonidet P-40 900 µL TWEEN 20 900 µL H20 200 mL

HCl, hydrogen chloride; KCl, potassium chloride; MgCl2, magnesium chloride; TRIS, tris(hydroxyl- methyl) aminomethane.

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Table 2.8 Primers and probes used in thesis AOD ID number/ AOD Name Gene name Reaction type Chapter used Rn00593696_m1 Slc38a1 Solute carrier family 38, member 1, multiplex 1 Mn00628416_m1 Slc38a2 Solute carrier family 38, member 2, multiplex 1 Rn00593742_m1 Slc38a4 Solute carrier family 38, member 4, multiplex 1 Rn1417099_m1 Slc2a1(Glut1) solute carrier family 2 (facilitated glucose transporter) member 1 multiplex 1 Rn00567331_m1 Slc2a3(Glut3) solute carrier family 2 (facilitated glucose transporter) member 3 multiplex 1 Rn00710306_m1 Igf1 Insulin-like growth factor 1 multiplex 1 Rn01454518_m1 Igf2 Insulin-like growth factor 2 multiplex 1 Rn01636937_m1 Igf2R Insulin-like growth factor 2 receptor multiplex 1 Mm00437304_m1 Vegfa Vascular endothelial growth factor A multiplex 1 Rn00492539_m1 11βHsd2 Hydroxysteroid 11-beta dehydrogenase 2 multiplex 1 Rn00585926_m1 Pgf Placental growth factor multiplex 1 Rn00570815_m1 Flt1 fms-related tyrosine kinase 1 multiplex 1 Mn01222421_m1 Kdr Kinase insert domain receptor multiplex 1 Rn01476417_m1 Gys1 Glycogen synthase 1 multiplex 1 Rn00570335_s1 Gjb3 Gap junction beta-3 protein multiplex 1 Rn00583429_m1 Gsk3β Glycogen synthase kinase 3 beta multiplex 1 Rn01529014_m1 Pck1 Phosphoenolpyruvate carboxykinase multiplex 2 Rn00561265_m1 Gck Glukokinase multiplex 2 Rn00689876_m1 G6pc Glucose 6-phosphatase multiplex 2 Rn00580241_m1 Ppargc1a Peroxisome proliferator-activated receptor gamma coactivator 1-alpha singleplex 2 Rn01193634_g1 Hdac2 Histone deacetylase 2 multiplex 2 F 5’-GATTAGGCTGCTTCAATCTC Hdac3* Histone deacetylase 3 singleplex 2 R 5’-CAGAGATGTTTCATATGTCCAG F 5’-AAACAGCTTCTGAACCTAAC Hdac4* Histone deacetylase 4 singleplex 2 R 5’-GAGTCTGTAACATCCAGGG Rn01528283_m1 Hdac6 Histone deacetylase 6 multiplex 2 F 5’-AGAGACCAGGATAAGAACG Dnmt1* Deoxyribonucleic acid methyltransferase 1 singleplex 2 R 5’-TTACTCGTTCAGGTTTCTCC F 5’-AATAGCCAAGTTCAGCAAAG Dnmt3a* Deoxyribonucleic acid methyltransferase 13A singleplex 2 R 5’-AAACACCCTTTCCATTTCAG F 5’-GATGACAAGGAGTTTGGAATA Dnmt3b* Deoxyribonucleic acid methyltransferase 13B singleplex 2 R 5’-CAGCGATCTCAGAAAACTTG

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Table 2.8 Primers and probes used in thesis (cont.) AOD ID number/ AOD Name Gene name Reaction type Chapter used Rn00565158_m1 Lep Leptin multiplex 3 F 5'-GAAACACACGAGACGCTGAA Tnf-α* Tumor necrosis factor alpha singleplex 3 R 5'-GAAAGCCCATTGGAATCCTT F 5'-ACTCATCTTGAAAGCACTTG IL-6* Interleukin 6 singleplex 3 R 5'-GTCCACAAACTGATATGCTTAG

F, forward probe; R, reverse probe; *, gene expression determined using SYBR® Green-based detection chemistry. All other genes were analysed with TaqMan® detection chemistry.

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2.10 Protein expression analysis

Protein expression was determined by Western Blotting and/or immunohistochemistry (see section 2.10.3 and 2.11.3) in placental, muscle and adipose tissue.

2.10.1 Protein extraction

Total protein was extracted from placenta (30-40 mg), visceral intra-abdominal mesenteric adipose tissue (70-90 mg) and skeletal muscle (10-15 mg). RIPA lysis buffer (Table 2.9) was added (~350-500 µL depending on tissue weight). Samples were homogenized with an Ultra-Turrax T8 homogenizer (IKA, Labtek, Brendale, QLD, Australia) for 20-30 seconds (maximum 2 bursts). Samples were centrifuged at 11,000 rpm for 30 minutes at 4oC in an Eppendorf microcentrifuge 5417R (Quantum scientific, Eppendorf South Pacific, NSW, Australia) to allow for separation of the cellular debris and supernatant.

Table 2.9 RIPA buffer recipe Reagent Concentration Volume (ml) Final Concentration

MQ H20 - 85.6 Tris-Hcl pH7.5 2 M 2.5 0.05 M NaCl 5 M 2 0.1 M EDTA pH8 0.5 M 0.4 0.002 M NaF 1 M 5 0.05 M SDS 10% 1 0.1% Deoxycholic acid 20% 2.5 0.5% Triton x 100 100% 1 1% Aprotin 2 mg/mL 0.05 Leupeptin 2 mg/mL 0.25 Pepstatin 2 mg/mL 0.035 Total volume 100.34 Add fresh - NaF 0.01 M 50 uL per 5 mL 0.01 Na Vanadate 0.01 M 50 uL per 5 mL 0.01 Na pyrophosphate 0.005 M 22.5 uL per 5 mL 0.0045

EDTA, ethylenediaminetetraacetic acid; HCl, hydrogen chloride; KCl, potassium chloride; MgCl2, magnesium chloride; MQ H20, milli-Q water; NaF, sodium fluoride; SDS, sodium dodecyl sulphate; TRIS, tris(hydroxymethyl) aminomethane.

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2.10.2 Protein concentration

The concentration of protein was determined using the Bio-Rad RC DC protein assay kit (Bio-Rad, Gladesville, NSW, Australia) which uses a colometric assay for protein quantitation. All samples were tested in triplicates and compared to a standard curve generated using bovine serum albumin. 5 µL sample/standard per well was loaded in a flat bottomed 96 well reaction plate. 75 µL provided reagent A (containing 0.02% reagent S) were added to each well followed by 200 µL reagent B. The plate was gently agitated and incubated in room temperature for 20-45 minutes to allow for color change of the standards. Absorbance was measured at 650 nm in a Tecan SunriseTM Micro plate Absorbance reader (Tecan Australia Pty, Ltd., Port Melbourne, VIC, Australia).

2.10.3 Western blotting

Following the protein concentration assay, samples were diluted in radioimmunoprecipitation (RIPA) buffer to a final concentration of 20 µL. 20% sodium dodecyl sulfate (SDS) was added to each sample before heating samples for 5 minutes at 95oC. Even concentrations of samples were then subjected to a sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) on 10-12% resolving gels (depending on the molecular weight of the protein of interest) and run at 90 V for 2-3 hours. Proteins were then transferred to an Immun-Blot® LF polyvinylidene fluoride (PVDF) membrane (Bio-Rad, Gladesville, NSW, Australia) at 30 V at 4oC overnight. Following protein transfer, the membrane was blocked for 1.5-3 hours in blocking buffer (3% fish gelatin from cold water fish (Sigma Aldrich, St Louis, MO, USA) in phosphate buffered saline (1 x PBS), using 2% horse or goat serum as appropriate. The membrane was then incubated with the first primary antibody overnight in 4oC. The antibody cocktail consisted of 3% fish gelatin in 1 x PBS, 2% horse or goat serum as appropriate, and 0.01% tween20. Following several washes in washing buffer, the membrane was incubated with an endogenous control as appropriate for 30 minutes in 4oC. After several washes, the membrane was subjected to secondary antibodies for 30-40 minutes in 4oC in a cocktail containing 3% fish gelatin in 1 x PBS, 1% horse- and 2% goat serum, 0.01% tween20 and 0.02% SDS. Membranes were washed again several times before being scanned with an Odyssey Infrared imaging system (LI-COR Biosciences, Lincoln, NE, USA)

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and densitometry performed using the Odyssey 2.0 software package (LI-COR Biosciences, Lincoln, NE, USA). All primary and secondary antibodies used in this thesis are summarized in Table 2.10.

Table 2.10 Antibodies used for western blotting and/or immunohistochemistry in this thesis MW Chapter Name company/product# Host Dilution Duration (kDa) used Anti-GLUT-1 Millipore #07-1401 Rabbit 1:1000 ON 54 1 Anti-IGF1R Santa Cruz #Sc-712 Rabbit 1:1000 ON 132 1 Anti-GSK3α/β Upstate, Millipore #05-412 Mouse 1:400 ON 46, 51 2

Anti-pGSK3α/βSer9/21 Cell signaling #9331 Rabbit 1:400 ON 46, 51 2

Anti-pAKT2(thr309) Cell signaling #9275 Rabbit 1:600 ON 60 2

Anti-pAKT2(ser474) Cell signaling #8599 Rabbit 1:800 ON 60 2 Anti-AKT2 Cell signaling #3063 Rabbit 1:1000 ON 60 2 Anti-beta actin Sigma Aldrich #A1978 Mouse 1:25000 30 min 42 1+2 Donkey-Anti-Mouse 2° Li-Cor 926-32210 Donkey 1:15000 30 min N/A Goat-Anti-Rabbit 2° Li-Cor 926-68071 Goat 1:20000 30 min N/A

AKT, v-akt murine thymoma viral oncogene homolog; GLUT1, glucose transporter 1; GSK3, glycogen synthase kinase-3; IGF1R, insulin-like growth factor receptor 1; N/A, not applicable; ON, overnight.

2.11 Histology

At the time of PMs, some tissues were fixed in 4% PFA at 4oC overnight before being prepared for paraffin sectioning. Tissues were dehydrated in 70% EtOH overnight followed by a processing procedure of 90% EtOH, 100% EtOH and xylene. Following infusion of 60oC paraffin wax under vacuum (60 psi), tissues were embedded in paraffin blocks. Blocks were sectioned at 7 µm and transferred to Superfrost Ultra Plus® (Menzel Gläser).

2.11.1 Hematoxylin and Eosin

Slides were stained with hematoxylin and eosin (H&E) for basic morphological investigation. Hematoxylin stains nucleic acids deep blue-purple whereas eosin stains protein, cytoplasm and extracellular matrix in various degrees of pink. Paraffin slides were de-waxed in a series of xylene (3 x 2 minutes), and rehydrated in a series of EtOH (2 x 2 minutes of 100% EtOH; 2 minutes of 95% EtOH; 2 min of 90% EtOH; and 2 minutes of 70% EtOH) before being stained in hematoxylin for 6 minutes. Following the stain in hematoxylin, slides were washed in running tap water for 2 minutes, placed in 90% EtOH for 2 minutes and the counterstained in eosin for

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6 minutes. Slides were then washed in 70% EtOH for 2 minutes and dehydrated through a series of EtOH (2 minutes each in 70% EtOH; 95% EtOH; and 100% EtOH). Slides were re-waxed in a new series of xylene (3 x 2 minutes), mounted with DPX mounting medium (Merck, mounting medium, Darmstadt, Germany) and cover- slipped.

For this thesis, E20 placentas were stained with H&E to allow for identification of placental compartments for cross-sectional analyses (see section 2.11.4). Livers collected at 8 months were stained with H&E to allow for pathological analyses using the Kleiner scoring system (see section 2.11.5).

2.11.2 Masson’s trichrome

Masson’s trichrome stain is commonly used to identify increases in collagenous tissue. The three dyes used in this method is selectively staining nuclei dark blue/purple-black (Weigert’s working hematoxylin), collagen blue (aniline blue) and muscle, erythrocytes and cytoplasm red (Biebrish scarlet). Paraffin slides were de- waxed and rehydrated according to the same protocol described in section 2.11.1. Slides were then mordant in Bouin’s solution at 60oC for 1 hour, followed by a 5 minutes wash in running tap water to remove picric acid. Slides were then stained in Weigert’s working hematoxylin for 5 minutes, washed in running tap water for 5 minutes and rinsed in distilled water. Slides were subjected to Bierbich scarlet stain for 5 minutes before being rinsed in distilled water again. Sections were flooded in 2.5% phosphotungstic/phosphomolybdic acid solution for 30 minutes before being stained with aniline blue for 20 minutes. The third stain was followed by a wash in distilled water, a 1 minute wash in 1% acetic acid, another wash in distilled water and slides were finally dehydrated, cleared and cover-slipped as described in section 2.11.1.

For this thesis, Masson’s trichrome stain was used to stain livers to allow for evaluation of fibrosis using the Kleiner scoring system (see section 2.11.5).

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2.11.3 Immunohistochemistry

Immunocytochemistry is a common method in biomedical research which uses antibodies to identify and localize proteins and other macromolecules in tissues and cells (Burry, 2011).

In this thesis, immunohistochemistry was used to identify GLUT1 in E20 placentas from 5 representative midline sections (7 µm). Sections were dehydrated as described in section 2.11.1, washed in distilled water for 2 minutes and placed in PBS. Endogenous peroxidase activity was blocked by placing the slides in 0.9% hydrogen peroxide (H2O2) in water for 40 minutes, followed by washes in 0.1 M phosphate buffer (PB) (3 x 5 minutes). Slides were then incubated in PB containing 10% goat serum and 2% BSA for 30 minutes to block non-specific binding. A rabbit polyclonal GLUT1 antibody (1:1000, Millipore - cat. #07-1401) was put on the sections in a mixture containing 2% BSA and 0.3% triton in PB for 1 hour before washing in 0.1 M PB (3 x 5 minutes). This was followed by a 30 minute incubation with a bioinylated goat-anti-rabbit IgG secondary antibody (1:200, VECTASTAIN Elite avidin-biotin complex (ABC) Kit, PK-6101) containing 10% goat serum and 2% BSA in PB for 1 hour at 37oC and washes in 0.1 M PB (3 x 5 minutes). Slides were then incubated in ABC reagents (10 µL of reagent A and 10 µL of reagent B per 1 mL of prep solution) at 37oC for 30 minutes, and washed again in 0.1 M PB (3 x 5 minutes). 50 µL of 3’3 diaminobenzidine tetrahydrochloride (DAB) (ImmPACT DAB Peroxidase Substrate, SK4015, Vectorlabs., USA) (made up by adding 30 µL of DAM chromagen per 1 mL of DAB substrate buffer) was added to the slides and the reaction stopped by placing the slides in distilled water once the sections turned pale brown. Slides were finally counterstained in hematoxylin for 20 seconds, dehydrated and re-waxed as described in section 2.11.1 before being cover-slipped. Negative controls were generated to show that the labelling was a result of the label added and not the result of endogenous labelling.

2.11.4 Cross-sectional area measurement

For determining the cross-sectional area of the labyrinth vs. the junctional zones in E20 placenta, slides were scanned with an Aperio Scanscope XT scanning system (Aperio Technologies, Inc., Vista, CA, USA) and visualized using the associated

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ImageScope software (version.10.2.2.2319). Thea area of each placental compartment was determined by carefully drawing around the outline of that specific zone on five different sections per placenta (Figure 2.14). The cross-sectional area of glycogen cells within the junctional layer was evaluated in the same way. All sections were assessed blinded.

1000µm

Figure 2.14 – Cross-sectional area of a placental section . . . . . The cross-sectional areas in placental sections were calculated using the ImageScope software. Drawings around each placental compartment were made at 2 x magnifications for the junctional layer (yellow) and the labyrinth layer (green) and at 5 x magnifications for glycogen cells (red). Placental section is shown at 2 x magnification.

2.11.5 Kleiner scoring system for non-alcoholic fatty liver disease

NAFLD is commonly seen together with insulin resistance. The Kleiner scoring system, developed by Kleiner and colleagues (Kleiner et al., 2005), is a commonly used semi quantitative scoring system for assessing a variety of histological features of NAFLD in slides stained with H&E and Masson’s trichrome.

Five representative liver sections (6 µm) taken from the apex of the left lateral lobe of the liver per animal were stained with H&E (see section 2.11.1), and five were 106

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stained with Masson’s trichrome (see section 2.11.2) to assess histological features of NAFLD (Figure 2.15). All sections were scored blinded. Features assessed included steatosis, microvesicular steatosis, inflammation, microgranulomas (H&E), and fibrosis (Masson’s trichrome) (Table 2.11).

Table 2.11 Kleiner scoring system Severity Score Steatosis grade <5% 0 (Low- to medium- power 5-33% 1 evaluation) >33-66% 2 >66% 3 Location of steatosis Zone 3 0 (predominant distribution Zone 1 1 pattern) Azonal 2 Panacinar 3 Microvesicular steatosis Absent 0 (contiguous patches) Present 1 Lobular inflammation (overall No foci 0 assessment of all inflammatory <2 foci per 200 x field 1 foci) 2-4 foci per 200 x field 2 >4 foci per 200 x field 3 Microgranulomas (small Absent 0 aggregates of macrophages) Present 1 Stage of fibrosis None 0 Perisinusoidal or periportal 1 Mild, zone 3, perisinusoidal 1A Moderate, zone 3, 1B perisinusoidal Portal/periportal 1C

For description of hepatic zones, refer to Figure 2.15 A.

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A B

1 2 2 3 3

C D

E F

G H I

Figure 2.15 – Traits of NAFLD assessed with the Kleiner scoring system . . . Liver section stained with H%E of a healthy liver (A) with the hepatic zones defined (1, the area around the portal vein; 2, azonal; and 3, the area around the central vein). A liver with macrovesicular steatosis in zone 1 (black arrow), zone 3 (yellow arrow) and zone 2 (green arrow) (B). Macrovesicular steatosis in zone 1 exclusively receives a score of 1 (C), and macrovesicular steatosis in zone 3 exclusively receives a score of 0 (D). (E) is showing the presence of microgranuloma (yellow arrows) and severe lobular inflammation (>4 foci x 200 field) receiving a score of 3, and (F) the presence of microvesicular steatosis. For scoring the severity of macrovesicular steatosis, sections with 5-33% steatosis at low to medium power receives a score of 1 (G), 33-66% receives a score of 2 (H), and >66% receives a score of 3. A, B and G-I are shown at 5 x magnification and C-F at 10 x magnification. All inserted bars are 200 µm. 108

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2.12 Statistical analyses

The statistical analyses for each data set are described in the relevant experimental chapters. All data are presented as mean ± standard error of the mean (SEM). The number of animals (n) used for each experiment is stated in the chapters. All graphs and statistical analyses were conducted with GraphPad Prism (v.6.0; GraphPad Software Inc., San Diego, CA, USA). Details of specific statistical analyses are found in each chapter.

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CHAPTER 3

Contributor Statement of contribution Gårdebjer, E. M. Study design (45%) Animal treatment (95%) Tissue collection (50%) Gene and protein studies (100%) Histological studies (95%) Interpretation of results (70%) Writing manuscript (70%) Cuffe, J. S. Histological studies (5%) Reviewing and editing manuscript (5%) Interpretation of results (15%) Pantaleon, M. Interpretation of results (5%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (10%) Moritz, K. M. Study design (55%) Animal treatment (5%) Tissue collection (50%) Interpretation of results (10%) Reviewing and editing manuscript (10%)

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Title: Periconceptional alcohol consumption causes fetal growth restriction and increases glycogen accumulation in the late gestation rat placenta

Running Title: Periconceptional alcohol and the placenta

Authors and affiliations: Emelie Gårdebjer1, James SM Cuffe1, Marie Pantaleon1, Mary E Wlodek2 and Karen M Moritz1.

1School of Biomedical Sciences, The University of Queensland, St Lucia, Queensland, Australia and 2The Department of Physiology, The University of Melbourne, Parkville, Victoria, Australia.

Correspondence: Associate Professor Karen Moritz, School of Biomedical Sciences, The University of Queensland, St Lucia, 4072, Australia, E-mail: [email protected], Telephone: +617 33654598, Fax: +617 33651299

Keywords: Periconceptional, preimplantation, ethanol, placenta, glycogen

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Abstract

Introduction: Alcohol consumption is a common social practice among women of childbearing age. With 50% of pregnancies being unplanned, many embryos are exposed to alcohol prior to pregnancy recognition and formation of the placenta. The effects of PC:EtOH-exposure on the placenta are unknown.

Methods: Sprague-Dawley rats were exposed to alcohol (12.5% v/v ad libitum) from 4 days prior to 4 days after conception and effects on placental growth, morphology and gene/protein expression examined at E20.

Results: PC:EtOH-exposed fetuses were growth restricted and their placental/body weight ratio and placental cross-sectional area were increased. This was associated with an increase in cross-sectional area of the junctional zone and glycogen cells, especially in PC:EtOH-exposed placentas from female fetuses. Junctional Glut1 and insulin like growth factor 2 (Igf2) mRNA levels were increased. Labyrinth insulin like growth factor 1 (Igf1) mRNA levels were decreased in placentas from both sexes, but protein IGF1R levels were decreased in placentas from male fetuses only. Labyrinth mRNA levels of Slc38a2 were decreased and Vegfa were increased in placentas following PC:EtOH-exposure but only placentas from female fetuses exhibited increased Kdr expression. Augmented expression of the protective enzyme 11-beta hydroxysteroid dehydrogenase (11βHsd2) was found in PC:EtOH- exposed labyrinth.

Discussion: These observations are consistent with a stress response, apparent well beyond the period of EtOH-exposure and demonstrate that PC:EtOH alters placental development in a sex-specific manner.

Conclusion: Public awareness should be increased to educate women about how excessive drinking even before falling pregnant may impact on placental development and fetal health.

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3.1 Introduction

It is increasingly accepted that IUGR is associated with chronic adult diseases that in many cases can be traced back to the quality of nutrition and health of the mother during pregnancy (McMillen and Robinson, 2005). A critical issue is the relative vulnerability of different stages of development to environmental insult and therefore potential developmental programming changes. Increasing evidence suggests that these programming events may be determined prior to implantation (Fleming et al., 2004). Indeed, the period surrounding conception, or the periconceptional period, has been identified as a critical window of vulnerability for the embryo in both in vitro and in vivo studies from several species (Kwong et al., 2000, Sinclair et al., 2007). Whilst previous studies have examined the impact of nutrition during the periconceptional period on development (Watkins et al., 2011, Zhang et al., 2011), little is known about the impact of maternal alcohol consumption during this period. This is of particular interest, as many women consume alcohol prior to pregnancy recognition (Edwards and Werler, 2006, Floyd et al., 1999) and both gestational (Gundogan et al., 2010) and periconceptional (Haycock and Ramsay, 2009) EtOH-exposure is known to impair placentation by inhibition of vascular transformation and by reducing invasive trophoblastic cells (Gundogan et al., 2013).

Developmental programming events are often sexually dimorphic but the mechanisms involved are poorly understood (Maloney et al., 2011). The placenta which is the major determinant of intrauterine growth (Harding and Johnston, 1995) may be a key in mediating tissue responses to a dynamic maternal environment as it forms the interface between the maternal and fetal circulation. Sex differences in how the placenta responds to the same maternal milieu may contribute to the altered susceptibility of male and female fetuses to long-term programming outcomes observed in other animal models (O'Connell et al., 2011, O'Connell et al., 2013a, Cuffe et al., 2011, Cuffe et al., 2012).

This study examined the impact of moderate alcohol exposure during the periconceptional period in the rat. This time point was selected as it is during this period that the initiation of placental formation occurs and insults that occur at this time may have long lasting effects on later stage placental morphology and function. 113

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This study also sought to establish whether changes in placental morphology and function were dependent upon fetal sex.

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3.2 Materials and methods

3.2.1 Ethics

3.2.2 Animal treatment

Outbred, nulliparous female Sprague Dawley rats were housed individually and kept under standard housing conditions, with controlled temperature, humidity and an artificial 12 hour light–dark cycle. Vaginal impedance was measured with an EC40 estrous cycle monitor (Fine Science Tools, CA, USA). When the impedance was 4.5 × 103 Ω or above, indicating estrous, dams were randomly allocated either a control liquid diet (n = 10) or a liquid diet containing 12.5% EtOH (v/v) (∼25% EtOH derived calories) (n = 11) on which they remained on during the periconceptional period (from 4 days prior to conception until 4 days after). The energy content of the EtOH diet was modified to give equal energy percentages of protein, fat and calories compared with the control diet. The dams had ad libitum access to the liquid diet 21 hours daily, with water offered during the remaining 3 hours of the day. At the initiation of the next estrus cycle (4 days), dams were mated overnight. Mating was confirmed by the presence of a seminal plug and this day was designated as E1. On E5, the liquid diet was replaced with standardized rat chow. Food, water intake and maternal weight gain was monitored daily throughout gestation. On E20, dams were deeply anesthetized following i.p. administration of a mix of 50/50 Ketamine/Xylazile (0.1 mL/100 g body weight) and maternal blood collected from a tail vein. Fetuses and placentas were removed and weighed to the nearest 0.1 μg. Placental dimensions were measured to the nearest 0.01 mm. Fetal sex was confirmed by qPCR as previously described (Cuffe et al., 2012). Placentas were immediately separated into the labyrinth and junctional zone, snap frozen in liquid nitrogen and stored at −80 °C, or left intact and fixed in 4% PFA. Placental labyrinth and junctional zone dry weights were obtained by oven drying (Cuffe et al., 2012). All analyses were carried out in placentas from both male and female fetuses.

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To avoid stressing the dams, a separate cohort of control fed dams and EtOH fed dams (n = 10 per group) where set up for determination of PAC. These dams were treated and mated in the same way as outlined previously. Blood was drawn from a tail vein into a lithium-heparinized collection tube (Sarstedt, SA, Australia), two days prior to mating (E-2) and on E2 at 0.5, 1, 3 and 5 hours after diet administration. Plasma samples were centrifuged at 3000 rpm for 10 minutes at 4°C. The plasma supernatant was collected and stored at −80 °C until assayed with an EnzyChrome EtOH kit (BioAssay Systems, CA, USA) according to manufacturer's instructions.

3.2.3 Gene analyses

RNA from each placental region was extracted separately using the RNeasy Mini-Kit (Qiagen, VIC, Australia), reverse transcribed into cDNA and gene expression assayed using qPCR with the following Assays-on-Demand primer/probe sets (Applied Biosystems., CA, USA): 11βHsd2 (Rn00492539_m1); Slc2a1 (Rn1411 7099_m1); Slc2a3 (Rn00567331); Igf1 (Rn00710306_m1); Igf2 (Rn0145518 _m1); Igf1R (Rn01636937_m1); Slc38a1 (Rn00593696_m1); Slc38a2 (Mn00628416 _m1); Slc38a (Rn00593742_m1); Pgf (Rn00585926_m1); Flt1 (Rn00570815_m1); Vegfa (Mm00437304_m1); Kdr (Mn01222421_m1); Gsk3β (Rn00583429_m1); Gys1 (Rn01476417_m1) and Gjb3 (Rn00570335_s1). qPCR results were analyzed using the ΔΔCT method, Rn18s as the endogenous control and did not differ between groups. All groups were compared with the average of the male control group (Cuffe et al., 2011). qPCR results were analyzed using the ΔΔCT method. Rn18s was used as the endogenous control because initial studies demonstrated the expression of the gene did not differ between groups.

3.2.4 Protein analyses

Total protein was extracted from placental labyrinth tissue (n = 5–6 per sex and treatment group) and subjected to SDS-PAGE and western blotting as described previously (Cuffe et al., 2011) to detect the expression of IGFR1 (Anti-IGF1R 1:1000, Santa Cruz – cat#Sc-712).

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3.2.5 Immunohistochemistry

Fixed placentas were processed to paraffin and 5 representative midline sections (7 μm) were taken from each placenta. Sections were stained with H&E, cover- slipped and imaged using the ScanScope system (Aperio Technologies, USA). Cross-sectional areas of junctional zone, labyrinth and glycogen cells were measured using imagescope software (version.10.2.2.2319). Additional sections were used for immunohistochemical staining of GLUT1. Sections were dehydrated, blocked in BSA/goat serum and incubated with a rabbit polyclonal GLUT1 antibody for 1 hour (1:1000, Millipore – cat. #07-1401). This was followed by 30 minute incubation with anti-rabbit secondary antibody (ABC Vectastain Elite KIT, Vectorlabs, USA) and staining with Diaminobenzidine tetrahydrochloride (ImmPACT DAB Peroxidase Substrate, SK4015, Vectorlabs, USA).

3.2.6 Plasma analyses

Maternal and fetal plasma electrolytes were analyzed with a Cobas Integra 400 Chemistry Analyzer (Block Scientific, NY, USA). Osmolality was determined using a Vapor Pressure Osmometer (5520 WESCOR, Helena Laboratories, Australia).

3.2.7 Statistical analyses

All results are presented as mean ± SEM. Fetal body and placenta weights were calculated as litter averages by sex. qPCR data represent 7–11 fetuses of each sex, collected from different litters. Statistical analyses were conducted with GraphPad Prism 5 software (GraphPad Software, CA, USA). Maternal measurements during pregnancy were analysed with a repeated measures analysis of variance (ANOVA) or with an unpaired student's t-test. All fetal/placental data were analyzed with a two- way ANOVA for treatment (Ptrt) and sex (Psex) using Bonferroni's post hoc test as appropriate.

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3.3 Results

3.3.1 Maternal parameters and plasma alcohol levels

There was no difference in maternal caloric intake or weight gain at any time during gestation, but EtOH-exposed dams consumed more water during exposure to the liquid diet (Table 3.1). The peak PAC was reached 30 minutes after provision of the EtOH containing diet on E-2 (0.18 ± 0.04%) and E2 (0.25 ± 0.04%). Levels thereafter declined and at 3 hours were ∼0.07 ± 0.02% and at 5 hours, 0.05 ± 0.02% (data not shown). Plasma osmolality and electrolyte concentration of sodium, potassium and chloride did not differ between groups on either E-2 or E2 (Table 3.1). The number of fetuses and the fetal sex ratio (data not shown) was similar between treatment groups, but EtOH-exposed dams had a higher rate of unviable fetuses (Table 3.1).

Table 3.1. Maternal parameters Variables Control EtOH Calorie intake (liquid diet), cal/gbw/d (E-4-mating) 0.20 ± 0.01 0.18 ± 0.01 Calorie intake (liquid diet), cal/gbw/d (mating-E4) 0.23 ± 0.01 0.21 ± 0.01 Calorie intake (chow), cal/gbw/d (E5-E20) 0.27 ± 0.01 0.27 ± 0.00 Water intake, ml/gbw/d (E-4-mating) 0.010 ± 0.002 0.015 ± 0.002* Water intake, ml/gbw/d (mating-E4) 0.010 ± 0.002 0.023 ± 0.003* Water intake, ml/gbw/d (E5-E20) 0.110 ± 0.003 0.120 ± 0.005 Peak plasma alcohol level (%) (E-2) 0 0.18 ± 0.04 Osmolality (mmol/kg) (E-2) 302 ± 4 300 ± 5 Plasma sodium (mmol/L) (E-2) 136.8 ± 1.9 140.4 ± 1.2 Plasma potassium (mmol/L) (E-2) 5.17 ± 0.16 5.37 ± 0.63 Plasma chloride (mmol/L) (E-2) 101.2 ± 1.7 102.3 ± 1.8 Peak plasma alcohol level (%) (E2) 0 0.25 ± 0.04 Osmolality (mmol/kg) (E2) 292 ± 4 297 ± 1 Plasma sodium (mmol/L) (E2) 136.9 ± 1.1 137.8 ± 1.3 Plasma potassium (mmol/L) (E2) 6.62 ± 0.78 5.28 ± 0.31 Plasma chloride (mmol/L) (E2) 101.1 ± 1.1 100.4 ± 1.1 Body weight on (g) E0 254 ± 6 262 ± 8 Total weight gain (g) 144.8 ± 8.6 141.2 ± 6.0 Litter size (number) 15 ± 1 14 ± 1 Number of pregnancies with at least one unviable fetus 1 of 9 6 of 11

Bw, body weight; E, embryonic day, EtOH, ethanol; d, day. All data are presented as mean ± SEM and n(control) = 9, n(EtOH) = 11. *,P < 0.05 by unpaired t-test (P < 0.05).

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3.3.2 Fetal weight, placental ratio and placental cross-sectional area

At E20, the body weight of PC:EtOH-exposed fetuses was reduced (Ptrt < 0.009) and females of both treatment groups were lighter than their males counterparts

(Psex < 0.04, Table 3.2). PC:EtOH-exposed fetuses were also shorter than controls

(Ptrt < 0.004, Table 3.2). There was no difference in absolute placenta (Table 3.2), labyrinth or junctional zone wet weight (data not shown), but placenta-to-body weight-ratio was increased following PC:EtOH-exposure (Ptrt < 0.004, Table 3.2). Labyrinth zone dry weights were unaffected by PC:EtOH-exposure while junctional dry weight was increased (Ptrt < 0.002, Table 3.2). Placental depth was not different following PC:EtOH-exposure but length (Ptrt < 0.05) and width (Ptrt < 0.03) were increased (Table 3.2).

H&E staining showed no gross morphological abnormalities in response to PC:EtOH-exposure, however there was an increase in junctional zone due to glycogen accumulation (Figure 3.1). Analysis of the cross-sectional areas of each placental zone in proportion to whole placenta showed a decrease in labyrinth

(Ptrt < 0.03, Figure 3.1 A) and an increase in junctional (Ptrt < 0.03, Figure 3.1 B) region following PC:EtOH-exposure. In addition, the cross-sectional area of glycogen cells, both as a percentage of total placenta (Ptrt < 0.002; Psex < 0.01, Figure 3.1 C) and as absolute cross-sectional area (Ptrt < 0.009; Psex < 0.007, Figure 3.1 D) were greater following PC:EtOH-exposure. Post hoc analyses showed that the cross- sectional area of glycogen cells were greater in PC:EtOH-exposed placentas from females compared with their control counterparts (P < 0.01).

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Table 3.2 Fetal and placental weights and dimensions at E20 Variables Male control Male EtOH Female Control Female EtOH Statistics Fetal weight and dimensions

P(trt) < 0.002 Body weight, g 2.65 ± 0.05 2.45 ± 0.08 2.50 ± 0.05 2.33 ± 0.07 P(sex) < 0.04 P(trt x sex) = NS P(trt) < 0.004 Snout-rump length, mm 40.37 ± 0.23 38.58 ± 0.76 39.55 ± 0.13 37.85 ± 0.68 P(sex) = NS P(trt x sex) = NS

Placental weights and dimensions

P(trt) = NS Absolute placenta wet weight, g 0.56 ± 0.02 0.55 ± 0.02 0.55 ± 0.01 0.55 ± 0.02 P(sex) = NS P(trt x sex) = NS

P(trt) < 0.004 Placenta:Body weight ratio, g/gbw 0.21 ± 0.01 0.23 ± 0.01 0.22 ± 0.01 0.24 ± 0.01 P(sex) = NS P(trt x sex) = NS P(trt) = NS Absolute Labyrinth zone (dry), g 0.057 ± 0.011 0.065 ± 0.012 0.054 ± 0.005 0.057 ± 0.004 P(sex) = NS P(trt x sex) = NS P(trt) < 0.002 Absolute Junctional zone (dry), g 0.033 ± 0.003 0.042 ± 0.002 0.033 ± 0.003 0.045 ± 0.004* P(sex) = NS P(trt x sex) = NS

P(trt) < 0.05 Placental length, mm 13.55 ± 0.21 13.95 ± 0.20 13.54 ± 0.16 13.94 ± 0.18 P(sex) = NS P(trt x sex) = NS P(trt) < 0.03 Placental width, mm 12.18 ± 0.14 12.42 ± 0.18 12.02 ± 0.14 12.60 ± 0.19 P(sex) = NS P(trt x sex) = NS

P(trt) = NS Placental depth, mm 4.20 ± 0.10 4.22 ± 0.12 4.14 ± 0.09 4.18 ± 0.13 P(sex) = NS P(trt x sex) = NS

Bw, body weight; EtOH, ethanol; NS, not significantly different; trt, treatment. All data are presented as mean ± SEM and n = 9-11 for each group. *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex. 120

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Figure 3.1 – Placental morphology following periconceptional alcohol exposure . Effects of PC:EtOH-exposure (black bars) on cross-sectional area of labyrinth zone (A), junctional zone (B), glycogen cells (C) as a percentage of total placenta, and absolute cross-sectional area of glycogen cells (D) in placentas from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means ± SEM, n = 9–11 per group, **, P < 0.01 for Bonferroni post hoc compared with untreated controls of same sex. Representative sections of untreated control (E) and PC:EtOH-exposed (F) placenta from female fetuses ×1 (scale bars 1000 μm) with glycogen stores (appears white) shown in ×20 magnification (scale bars 100 μm).

3.3.3 Placental gene and protein expression

PC:EtOH-exposure did not alter mRNA levels of Glut1 in the labyrinth (Figure 3.2 A) but increased the expression in the junctional zone of the placenta (Ptrt < 0.05, Figure

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3.2 B). This was confirmed by immunohistochemistry staining of GLUT1 in the junctional zone (Figure 3.2 E & F). There was a significant interaction between

PC:EtOH and sex on the gene expression of Glut3 in both the labyrinth (Ptrt x sex < 0.02, Figure 3.2 C) and junctional zone (Ptrt x sex < 0.04, Figure 3.2 D).

Figure 3.2 – The effect of periconceptional alcohol exposure on glucose transporters in the placenta Effects of PC:EtOH-exposure (black bars) on Glut1 gene expression in the labyrinth (A) and junctional (B) zone; and on Glut3 gene expression in the labyrinth (C) and junctional (D) zone of placenta from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means ± SEM, n = 9–11 per group, *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex. Representative sections of untreated control (E) and PC:EtOH- exposed (F) placenta from female fetuses shown in ×20 magnification (scale bars 100 μm) quantitatively confirmed that the increase in Glut1 mRNA in the junctional zone also were translated into increases in GLUT1 protein levels (dark brown staining). Inserts shows sections stained with the appropriate sense probe as a control (×20 magnification, scale bars 100 μm). 122

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PC:EtOH-exposure suppressed Igf1 gene expression in the labyrinth

(Ptrt < 0.001, Figure 3.3 A), whereas the gene expression of Igf1 in the junctional zone was unaffected (Figure 3.3 B). Igf2 mRNA was not altered in the labyrinth (Figure 3.3 C) but increased in the junctional zone of PC:EtOH-exposed placentas

(Ptrt < 0.03, Figure 3.3 D). mRNA levels of the insulin like growth factor 2 receptor (Igf2R) were similar between treatment groups (Figure 3.3 F). Relative protein expression of IGF1R was lower in PC:EtOH-exposed placenta from males, but not females, when compared with untreated controls (P < 0.01, Figure 3.3 E).

PC:EtOH-exposure did not affect junctional mRNA levels of gap junction beta-3 protein (Gjb3) and Gys1 but mRNA levels of Gsk3β were higher in PC:EtOH- exposed placenta from females but not males (P < 0.05, Table 3.3). In addition, PC:EtOH caused multiple changes in mRNA expression in the labyrinth: increased mRNA levels of 11βHsd2 in both sexes (Ptrt < 0.0001, Table 3.3), increased mRNA levels of Slc38a1 in placentas from females fetuses regardless of treatment group (Psex < 0.03, Table 3.3) and decreased mRNA levels of Slc38a2 in placentas from both sexes (Ptrt < 0.003, Table 3.3), while Slc38a4 was unaffected (Table 3.3). Vegfa mRNA levels were higher in PC:EtOH-exposed placentas

(Ptrt < 0.03, Table 3.3) and in placentas from female fetuses (Psex < 0.03, Table 3.3), but there was no difference in mRNA levels of Pgf (Table 3.3). While Flt1 gene expression was higher in placentas from female fetuses (Psex < 0.02, Table 3.3), mRNA levels of Kdr were only increased in placentas from females following PC:EtOH-exposure (P < 0.05, Table 3.3).

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Figure 3.3 – The effect of periconceptional alcohol exposure on gene and protein expression of placental insulin like growth factors . Effects of PC:EtOH-exposure (black bars) on Igf1 gene expression in the labyrinth (A) and junctional (B) zone; on Igf2 gene expression in the labyrinth (C) and junctional (D) zone, on relative protein expression in the labyrinth zone (E), and on relative gene expression of Igf2R (F) of placenta from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means ± SEM, mRNA expression: *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex, n = 9–11 per group. Protein expression: *, P < 0.05 by unpaired t-test comparing untreated controls and PC:EtOH-exposed placenta of the same sex, n = 5 per group. 124

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Table 3.3 Relative gene expression Male control Male EtOH Female Control Female EtOH Statistics Labyrinth zone

P(trt) = NS Slc38a1 1.03 ± 0.07 0.91 ± 0.08 1.06 ± 0.10 1.28 ± 0.14 P(sex) < 0.04 P(trt x sex) = NS

P(trt) < 0.003 Slc38a2 1.01 ± 0.06 0.76 ±0.06 0.92 ± 0.05 0.83 ± 0.04 P(sex) = NS P(trt x sex) = NS

P(trt) = NS Slc38a4 1.11 ± 0.13 1.06 ± 0.10 0.90 ± 0.05 1.11 ± 0.12 P(sex) = NS P(trt x sex) = NS

P(trt) < 0.03 Vegfa 1.03 ± 0.09 1.23 ±0.11 1.23 ± 0.11 1.55 ± 0.13 P(sex) < 0.03 P(trt x sex) = NS

P(trt) = NS Kdr 1.07 ± 0.14 0.97 ± 0.07 0.87 ± 0.05 1.39 ± 0.16* P(sex) = NS P(trt x sex) < 0.01

P(trt) = NS Pgf 1.03 ± 0.09 0.97 ± 0.08 1.01 ± 0.08 1.15 ± 0.08 P(sex) = NS P(trt x sex) = NS

P(trt) = NS Flt1 1.02 ± 0.08 0.91 ± 0.10 1.14 ± 0.10 1.25 ± 0.09 P(sex) < 0.02 P(trt x sex) = NS P < 0.0001 11βHsd2 1.06 ± 0.14 2.03 ±0.21 1.38 ± 0.20 2.51 ± 0.29 (trt) P(sex) = NS P(trt x sex) = NS Junctional zone Glycogen cell markers

P(trt) = NS Gys1 1.03 ± 0.09 0.98 ± 0.09 1.00 ± 0.11 1.11 ± 0.13 P(sex) = NS P(trt x sex) = NS

P(trt) = NS

Gsk3β 1.02 ± 0.09 0.84 ± 0.04 0.82 ± 0.05 1.07 ± 0.09* P(sex) = NS P(trt x sex) < 0.006

P(trt) = NS Gjb3 1.13 ± 0.20 1.09 ± 0.15 0.87 ± 0.09 1.15 ± 0.14 P(sex) = NS P(trt x sex) = NS

11βHsd2, 11-beta hydroxysteroid dehydrogenase; Flt1, fms-related tyrosine kinase 1; Gjb3, gap junction beta-3 protein; Gsk3β, glycogen synthase kinase 3 beta; Gys1, Glycogen synthase 1; Kdr, kinase insert domain receptor; NS, not significantly different; Pgf, placental growth factor; Slc38a, sodium-coupled neutral amino acid transporter; Vegfa, vascular endothelial growth factor A. All data are presented as mean ± SEM and n = 9-11 for each group. *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex.

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3.4 Discussion

Our study shows for the first time that exposure of the rat to moderate levels of alcohol exclusively during the periconceptional period is sufficient to program growth restriction in both male and female fetuses in late gestation and cause significant changes in placental structure, morphology and gene expression. Whilst the primary stimulus was PC:EtOH-exposure, elevated levels of placental 11βHsd2 (Cuffe et al., 2011) and (Cuffe et al., 2012) and GLUT1 (Langdown and Sugden, 2001) suggest a long-lasting stress response may be involved. Sex-specific differences such as the size of placental junctional zone in females, along with an increase in Glut3 mRNA levels, indicate dissimilar mechanisms of action. The observations from this study are consistent with other models of periconceptional perturbations, mainly focusing on maternal nutritional status (Kwong et al., 2000, Sinclair et al., 2007, Watkins et al., 2011, Zhang et al., 2011, Ikeda et al., 2012), in that it highlights the importance of the period around the time of conception as a critical window of development. These results are therefore of high clinical importance as they suggest that a woman's drinking habits, even prior to conception and preimplantation can have implications on the growth and development of the placenta and thus, the fetus.

PC:EtOH-exposure results in fetal growth restriction

It is well established that prenatal alcohol exposure causes fetal growth restriction (Chen and Nyomba, 2003b, Lopez-Tejero et al., 1989) Many studies of in utero EtOH-exposure are however confounded by a modified energy intake (Chen and Nyomba, 2003a). Both maternal over- (Jones et al., 2009) and undernutrition (Vickers et al., 2000) causes alterations in fetal growth ultimately resulting in early onset of adult diseases (Vickers et al., 2000, Langley-Evans and Nwagwu, 1998, Barker et al., 1990). Our model is not complicated by caloric restriction or overnutrition as energy intake was equivalent in both EtOH and control fed dams throughout preimplantation and later periods of gestation, as was maternal weight gain. Moreover EtOH-exposed dams drank more water, allowing maintenance of plasma osmolality and electrolytes. The PAC reported may appear high as they were determined following the period of maximal ingestion. The PAC generated is comparable with other models of EtOH exposure, which generally administer EtOH

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via gavage (Chen and Nyomba, 2003a) (Gray et al., 2010). Importantly, these levels are only marginally higher than levels found in occasional alcohol users (Touquet et al., 2008) and as rats metabolize alcohol faster than humans (Zorzano and Herrera, 1990), they should be considered clinically relevant.

PC:EtOH-exposure introduced a long-lasting stress response in placentas from both sexes

EtOH appeared to induce a long-lasting stress response in placentas from both sexes, as evidenced by increased expression of the gene 11βHsd2 in the labyrinth zone. Placental 11βHSD2 protects the fetus from maternally circulating glucocorticoids (cortisol or corticosterone) by enzymatic inactivation (Murphy et al., 2007). Previous studies performed by our laboratory in the mouse (Cuffe et al., 2011, Cuffe et al., 2012) and others in the human (Clifton et al., 2006) have shown that the placenta can mediate a temporary increase in the expression level of 11βHsd2 in response to elevations in circulating maternal glucocorticoids. Although corticosterone levels were not measured in this model, other studies in rats have shown that chronic alcohol consumption throughout pregnancy does indeed increase maternal corticosterone concentrations (Wilcoxon and Redei, 2004). Furthermore, increases in placental Glut1 gene expression, similar to those measured in this study, have been observed in rats following maternal glucocorticoid administration (Langdown and Sugden, 2001). GLUT1 is a ubiquitous stress and growth factor responsive transporter that is expressed throughout preimplantation development (Pantaleon and Kaye, 1998). We therefore suggest the increased Glut1 expression in PC:EtOH-exposed placentas to be supportive for a role of stress and/or glucocorticoids in PC:EtOH-exposure.

PC:EtOH-exposure caused sex-specific alterations in placental morphology and gene expression

Abnormal placental weight, both absolute and as a ratio of fetal weight, are independently associated with adult disease (Barker et al., 1990). Although absolute placental weight was unchanged by PC:EtOH-exposure, there were changes in shape and an increase in body/placental ratio and junctional zone cross-sectional area. The increase in junctional cross-sectional area was due to an increase in the 127

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area of apparent glycogen and this was more pronounced in placentas from females. This suggests a sexually dimorphic chance which ultimately may have contributed to other sex-specific alterations, as differences in placental shape and morphology affects transplacental transfer of nutrients, oxygen and hormones (Burton and Fowden, 2012).

Neither IGF1 nor 2 can cross the placental barrier and are exclusively produced by the feto-placental unit to maintain fetal and placental growth (Lopez et al., 1996). As IGF1 deletion is known to cause fetal growth restriction (Fowden, 2003), we suggest that the lower labyrinth Igf1 mRNA levels in PC:EtOH-exposed placentas may have impacted on fetal growth. Junctional Igf2 mRNA levels on the other hand were elevated, whilst labyrinth mRNA levels of IGF2R were maintained. Given that the IGF2R predominantly acts to limit IGF2 action by internalization and degradation of the ligand (Baker et al., 1993), we suggest this may have contributed to the greater proportion of junctional zone area observed in PC:EtOH-exposed placentas from females.

PC:EtOH-exposure also increased levels of labyrinth Vegfa gene expression. Numerous studies have previously shown that prenatal EtOH-exposure alters normal vascular adaptation during pregnancy (for review see (Ramadoss and Magness, 2012)). Whilst the increase in Vegfa gene expression may appear to be inconsistent with the apparent growth restriction, similar results have been observed in placentas of mouse fetuses following prenatal dexamethasone administration (Cuffe et al., 2011). As mRNA levels of Flt1 were higher in placentas from female fetuses regardless of treatment group and mRNA levels of Kdr were increased in placentas from PC:EtOH-exposed females only, it is likely that placentas from female fetuses are attempting to increase vasculogenesis to ensure adequate fetal nutrient supply.

PC:EtOH-exposure and alterations in glycogen cross-sectional area

Glycogen cross-sectional area was increased in placentas from female fetuses following PC:EtOH-exposure. Although the role of glycogen in the placenta is unclear we attempted to further approach this by investigating the levels of specific glycogen cell markers. Interestingly, whilst Igf2, a key regulator of placental glycogen

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synthesis (Lopez et al., 1996, Esquiliano et al., 2009) was elevated in PC:EtOH- exposed female placentas, mRNA levels of Gjb3 and Gys1 was unchanged. Gjb3 encodes a gap junction protein which is exclusively expressed in the membrane of vacuolated glycogen cells in mid to late gestation placenta (Coan et al., 2006) whilst Gys1 is the rate limiting enzyme involved in glycogen synthesis (Bevan, 2001). Intriguingly, mRNA levels of Gsk3β, a negative regulator of GYS1 activity (Ludwig et al., 1996), was only elevated in placentas from females, perhaps to limit further glycogen deposition. Furthermore, PC:EtOH-exposure increased junctional Glut3 mRNA levels in female placenta, which together with glycogen accumulation has also has been observed in placentas of diabetic rats (Boileau et al., 1995). While GLUT3 is involved in glucose delivery to the fetus (Boileau et al., 1995), it also transports glucose from the fetal circulation back into the placenta, as the placenta is the only tissue capable of storing excess fetal glucose (Schneider et al., 2003). In contrast, placentas from male fetuses expressed less Glut3 following PC:EtOH-exposure but also had a smaller placental area occupied by glycogen cells. Our data may suggest an early EtOH induced change in metabolism to favor glycogen accumulation. We propose that placentas, particularly from females, either have a reduced capacity for transplacental glucose transfer from mother to fetus and/or an augmented backflow of glucose from the fetal circulation to the placenta, which again is the case seen in placentas of diabetic rats (Thomas et al., 1990).

PC:EtOH-exposure altered amino acid transporter abundance

The decreased labyrinth expression of Slc38a2 following PC:EtOH-exposure seen in this study may have contributed to fetal growth restriction as seen in other models with changes in placental Na+-dependent system A transporters (Sinclair et al., 2007, Maloney et al., 2011). The system A amino acid transporters accept a wide range of amino acids, however only Slc38a2 transports the essential amino acid methionine (Mackenzie and Erickson, 2004). As methionine is involved in DNA and histone methylation it has been suggested to play an important role in epigenetic regulation of genes (Sinclair et al., 2007, Ikeda et al., 2012). The preimplantation embryo is very susceptible to epigenetic perturbations (Ikeda et al., 2012) and we cannot preclude the possibility of the alterations in Slc38a2 gene expression

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contributing to faults in programming events involving epigenetic change.

Conclusion

Our study has for the first time shown that maternal alcohol intake exclusively around the time of conception alters placental weight and morphology and causes growth restriction in the late gestation fetus. Particularly interesting was the programmed stress response, indicated by the increase in placental 11βHsd2 and Glut1 gene expression. Our results suggest that the placenta exerts sex-specific mechanisms of actions, both structurally and functionally, with females perhaps being more protected. Future studies that determine postnatal sex-specific contributions to adult onset of programmed disease following PC:EtOH-exposure need to be carried out to establish this hypothesis. As alcohol consumption is common amongst women of childbearing age (Floyd et al., 1999) and half of all pregnancies are unplanned (Colvin et al., 2007) it is important to address this by increasing public awareness about the implication of alcohol consumption even before becoming pregnant.

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CHAPTER 4

GARDEBJER, E. M., ANDERSON, S., PANTALEON, M., WLODEK, M. E., & MORITZ, K. M. 2015. Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring which is exacerbated by a postnatal high-fat diet. FASEB. J, (fj.14-268979).

Contributor Statement of contribution Gårdebjer, E. M. Study design (50%) Animal treatment* (80%) Tissue collection† (60%) Glucose/Insulin tolerance testing (100%) Plasma assays (100%) Gene and protein studies (100%) Interpreting results (65%) Writing manuscript (75%) Anderson, S. Interpretation of results (15%) Reviewing and editing manuscript (10%) Pantaleon, M. Tissue collection† (5%) Interpretation of results (10%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (5%) Moritz, K. M. Study design (50%) Animal treatment* (5%) Tissue collection† (20%) Interpretation of results (10%) Reviewing and editing manuscript (5%)

*, Remaining 15% performed by Kalisch-Smith, J; †, remaining 15% contributed to by other members of Moritz’s lab

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Title: Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring which is exacerbated by a postnatal high-fat diet

Running Title: Programming effects of periconceptional alcohol

Authors and affiliations: Emelie M Gårdebjer1, Stephen T Anderson1, Marie Pantaleon1, Mary E Wlodek2 and Karen M Moritz1.

Schools of 1Biomedical Sciences, The University of Queensland, St Lucia, Queensland, Australia and 2The Department of Physiology, The University of Melbourne, Parkville, Victoria, Australia.

Correspondence: Associate Professor Karen Moritz, School of Biomedical Sciences, The University of Queensland, St Lucia, 4072, Australia, e-mail: [email protected], Telephone: +617 33654598, Fax: +617 33651299

Keywords: Developmental programming, metabolic pathways, diabetes, gene expression, gluconeogenesis

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Abstract

Introduction: Alcohol consumption throughout pregnancy can cause metabolic dysregulation, including glucose intolerance in progeny. This study determined if alcohol consumed exclusively around conception caused similar outcomes.

Methods and results: Periconceptional maternal alcohol intake (12% v/v in a liquid diet, PC:EtOH), from 4 days prior to conception until day 4 of gestation in the Sprague-Dawley rat, resulted in offspring with elevated fasting plasma glucose (~10- 25%, P < 0.05), impaired glucose tolerance (P < 0.05) and decreased insulin sensitivity (P < 0.01) at 6 months of age. This was associated with increased hepatic gluconeogenesis and sex-specific alterations in peripheral protein kinase B (AKT) signaling. These changes were accompanied by increased mRNA expression of DNA methyltransferases 1, 3a and 3b (1.5-1.9 fold, P < 0.05) in fetal liver in late gestation, suggesting that PC:EtOH may cause epigenetic changes that predispose offspring to metabolic dysfunction. Exposure to a postnatal high-fat diet (HFD) from 3 months of age caused hyperinsulineamia (~2 fold increase, P < 0.001) and exacerbated the metabolic dysfunction in male offspring exposed to PC:EtOH but had no additive effects in females. Control rats were given a liquid diet containing no alcohol but matched to ensure equal caloric intake.

Discussion and conclusion: Given many women may drink alcohol whilst planning a pregnancy, it is crucial to increase public awareness regarding the effects of alcohol conception.

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4.1 Introduction

Increasing evidence implicates the intrauterine environment in the development of chronic adult disease propensity and metabolic disorders (Godfrey and Barker, 2000). Indeed, fetuses exposed to a range of adverse intrauterine environments including malnutrition (Ravelli et al., 1999), placental insufficiency (Siebel et al., 2008), and alcohol (Chen and Nyomba, 2003b, Lopez-Tejero et al., 1989, Yao et al., 2006, Probyn et al., 2013c) have an increased risk of adult onset metabolic dysfunction. Low birth weight, insulin resistance, and altered regulation of hepatic glucose output are commonly demonstrated in these models (Chen and Nyomba, 2003b, Lopez-Tejero et al., 1989, Yao et al., 2006, Probyn et al., 2013c, Devaskar and Thamotharan, 2007, Chen and Nyomba, 2004). Intriguingly, these effects are often programmed in a sex-specific manner, with males consistently more adversely affected than females (Probyn et al., 2013c). The periconceptional period appears to be a particularly susceptible developmental window for programming of disease (McMillen et al., 2008). Given >50% of women consume alcohol prior to pregnancy (Colvin et al., 2007) and half of all pregnancies are reported to be unplanned (Colvin et al., 2007, Naimi et al., 2003), many embryos are potentially exposed to alcohol prior to pregnancy recognition. Despite recommendations of alcohol abstinence for women who are pregnant, or planning a pregnancy, a recent study reported that 32% of women claim they would continue to drink despite trying to conceive (Peadon et al., 2011).

We have previously shown that PC:EtOH-exposure causes fetal growth restriction and sex-specific placental abnormalities in late pregnancy in the rat (Gardebjer et al., 2014). Both are risk factors for adult onset disease (Varvarigou, 2010, D J Barker, 1990). Here, we examined the hypothesis that PC:EtOH-exposure programs glucose intolerance and insulin resistance in offspring. In addition, we explored the influence of a postnatal HFD as it has been suggested that lifestyle/dietary factors can unmask and/or exacerbate pre-programmed adult disease propensity (Chen and Nyomba, 2003b). In order to elucidate potential mechanisms contributing to disease, we examined the effect of PC:EtOH-exposure on gluconeogenic genes in the liver and AKT-signaling in peripheral tissues in postnatal offspring (Yao et al., 2006, Devaskar and Thamotharan, 2007, Thompson et al., 2007). Additionally, we assessed

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expression levels of key chromatin modifiers in fetal life since epigenetic changes are implicated in metabolic programming of adult disease following periconceptional perturbation (Sinclair et al., 2007). Specifically, we examined expression levels of histone deactylases (HDACs) and DNA methyltrasferases (DNMTs) in fetal liver as alterations in both these modifications are associated with metabolic disease.

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4.2 Materials and methods

4.2.1 Ethics

All animal experimentation was approved by The University of Queensland Anatomical Bioscience Animal Ethics Committee (SBS/022/12/NHMRC) prior to commencement of the study.

4.2.2 Rats and treatment

Outbred nulliparous Sprague-Dawley rats were individually housed under an artificial 12 hour light-dark cycle and treated as previously described (Gardebjer et al., 2014). Briefly, 12-13-week-old dams were randomly allocated to a liquid diet containing either 12.5% v/v (PC:EtOH) or an equal-caloric 0% EtOH diet (untreated, U) (n = 22 per treatment group) for one full estrus cycle (4 days), prior to overnight mating. Animals that did not mate on the 4th or 5th day after being offered the diet were removed from the protocol. The liquid diet was composed of Sustagen® hospital formula (Mead Johnson® Nutritionals), reduced fat milk, corn flour and essential minerals (ferric citrate, copper II sulphate, selenium and magnesium sulphate. In preliminary experiments, we had identified that the EtOH-exposed dams consumed a lesser amount of the liquid diet, hence the energy density of the EtOH-diet was increased and the ingredients were modified to ensure an equal amount of macro- and micronutrients: (control diet composition: 11.3% fat, 17.0% protein, 68.2% carbohydrates, 7.7 MJ/kg; EtOH-diet: 11.9% fat, 13.6% protein, 50.7% carbohydrates, 11.8 MJ/kg). Dams had access to the liquid diet 21 hours daily ad libitum until E4, with water offered during the remaining 3 hours of the day. Liquid diets were replaced by standardized rat chow and water on E5 (4.0% fat, 13.6% protein 64.3% carbohydrates; 15.5 MJ/kg) (SF-08-020 Specialty feeds, Glenforrest, WA, Australia). One subset of dams (n = 10 per group) was killed on E20 for collection of fetal liver, whereas one subset (n = 12 per group) littered down naturally. Offspring were weighed daily until weaning on PN day 28. At 3 months, one subset of offspring was randomly assigned to a modified diet that contained increased fat and cholesterol (HFD: 21% fat, 0.15% cholesterol, 19% protein, 59.9% carbohydrates; 19.4MJ/kg) (SF00-219 Specialty feeds, Glenforrest, WA, Australia) whilst remaining animals were supplied with the same standardized chow as the 136

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dams consumed (C). These diets are matched for micronutrient composition. This resulted in the generation of 8 treatment groups: U:C; U:HFD; PC:EtOH:C and PC:EtOH:HFD for both male and female offspring. Both the HFD and C diet were based on similar base ingredients for protein and carbohydrates (casein; and wheat starch, sucrose and cellulose); but the fat source was canola oil in the C-diet and clarified butter in the HFD. All groups had ad libitum access to allocated diet and water until the end of the study.

4.2.3 Glucose and insulin tolerance test

Glucose (1g/kg body weight) and insulin (0.75 U/kg body weight) tolerance tests (GTT & ITT) were performed at 6 months (n = 10-11 per group) as described previously (Probyn et al., 2013c). Plasma glucose levels were determined using a Cobas Integra 400 Plus Chemistry Analyzer and insulin concentrations by rat insulin RIA kit (Cat#RI-13K, Millipore Australia, Kilsyth, VIC, AUS). Insulin samples were run in duplicates, at 1:2 dilutions. Assay sensitivity was 28.0 pmol/L whilst inter- and intra-assay coefficients of variation were 14.9% and 9.9% respectively.

4.2.4 Tissue collection

Rats were euthanized at 8 months by i.p. administration of a 50/50 Ketamine/Xylazile mix (0.5 mL/100 g body weight) after a 15 hour fasting period. Tissues were snap- frozen in liquid nitrogen and stored at -80oC (gastrocnemius muscle, white intra- abdominal adipose tissue, and liver). Fetal liver was collected as previously described on E20 (Gardebjer et al., 2014).

4.2.5 qPCR and Western blotting

RNA from the left lateral lobe of the liver was extracted using RNeasy Mini-Kit and reversed transcribed into cDNA. Gene expression was analyzed using qPCR with the following Assay-on-Demand primer/probe sets (Applied Biosystems, CA, USA) Pck1, (Rn01529014_m1), Gck, Rn00561265_m1), G6pc, (Rn00689876_m1), Ppargc1a, (Rn00580241_m1), Hdac2 (Rn01193634_g1) and Hdac6 (Rn01528 283_m1), or SYBR® Green detection chemistry using the following primers for: Hdac3 (F;5'-GATTAGGCTGCTTCAATCTC; R;5'-CAGAGATGTTTCATATGTCCAG),

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Hdac4 (F;5'-AAACAGCTTCTGAACCTAAC; R;5'-GAGTCTGTAACATCCA-GGG), Dnmt1 (F;5'-AGAGACCAGGATAAGAACG; R;5'-TTACTCGTTCAGGTTT-CTCC), Dnmt3a (F;5'-AATAGCCAAGTTCAGCAAAG; R;5'-AAACACCCTTTCCATT-TCAG) and Dnmt3b (F;5'-GATGACAAGGAGTTTGGAATA; R;5'-CAGCGATCTCAGAAAA

CTTG). qPCR results were analyzed with the ΔΔCT method. Rn18s, which did not differ between groups, was used as the endogenous control. All groups were compared with the average of the untreated control group (Gardebjer et al., 2014).

Total protein was extracted from 80 mg abdominal adipose tissue and 15 mg gastrocnemius muscle. Tissues were homogenized in 0.4 mL RIPA buffer for 20 seconds using an Ultra-Turrax T8 homogeniser (Labtek). Homogenates were centrifuged (11,000 rpm, 20 minutes, 4 °C) and resultant supernatant assayed using the Bio-Rad (Hercules, CA, USA) reducing agent and detergent compatible protein assay kit. Total protein (20 µg per sample; n = 5–6 per sex and PC-treatment) was subjected to SDS-PAGE on 12% gels and subsequently transferred to Immobilon® FL PVDF membranes (Millipore). Membranes were incubated overnight with one of the following polyclonal rabbit antibodies (all from Cell Signaling,

Danvers, MA, USA); anti-total-AKT2 (1:1000, cat#3063), anti-phospho-AKT(Thr309)

(1:600, cat#9275), anti-phospho-AKTSer474 (1:800, cat#8599), anti-phospho-

GSK3α/β(Ser21/9) (1:600, cat#9331), or a mouse monoclonal anti-GSK3α/β (1:600, cat#05-412, Upstate Biotechnology, Lake Placid, NY, USA). β-actin immunoreactivity was used for ratiometric purposes (1:25000, #A1978; Sigma Aldrich, St. Louis, MO). Protein expression was assayed using a LI-COR Odyssey infrared imaging system (LICOR Biosciences, Lincoln, NE, USA) following exposure to LI-COR IRDye 680 goat anti-rabbit and IRDye 800CW goat anti-mouse secondary antibodies (Millennium Science, Mulgrave, Australia).

4.2.6 Calculations and statistical analyses

AUGC and AUIC concentration curves were calculated using the trapezius method with baseline defined as zero (Allison et al., 1995). AUGC following the GTT was calculated defining the baseline as zero and the positive incremental area (AUC of positive peaks) (Wolever and Jenkins, 1986). The ITT curves were inverted before calculating AUGC. Acute first-phase insulin secretion was calculated as the

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incremental AUIC from basal to 5 minutes and second-phase insulin secretion as the incremental AUIC from 5 to 120 minutes. QUICKI was calculated as 1/[log(fasting insulin (μU/mL)) × log(fasting glucose (mg/dL))] (Katz et al., 2000). HOMA-IR was calculated using [fasting insulin (μU/mL) × fasting glucose (mmol/L)]/22.5 (Duncan et al., 1995).

Three-way ANOVA analysis was conducted with IBM® SPSS® Statistics (version 20.0) with main effects being PC-treatment, sex and diet. For most parameters there were significant (P < 0.05) main effects of PC-treatment, but also significant interactions with postnatal diet. Therefore, data was first analysed by two-way ANOVA examining the effects of PC-treatment between sexes [main effects of PC- treatment (PPC:EtOH) and sex (PSex)]. Subsequently, the effect of HFD and PC:EtOH within each sex [main effects of PC-treatment (PPC:EtOH) and postnatal diet (PHFD)] was also assessed. Data were log transferred to remove heterogeneity of variance prior to performing ANOVA as required (Bartlett’s test). Means were further compared using a Tukey’s multiple comparison post-hoc test. Plasma glucose- and insulin concentrations over time were analysed with a two-way ANOVA repeated measurements [effects of PC-treatment (PPC:EtOH) and time (Ptime)]. Protein immunoblots were compared by Students t-test. P < 0.05 was considered statistically significant. Statistical analyses other than three-way ANOVAs were conducted with GraphPad Prism 6 software for Windows (GraphPad Software, San Diego, CA, USA). Results are presented as mean ± SEM.

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4.3 Results

4.3.1 Maternal parameters and postnatal growth

Dams were of similar age (U: 87 ± 3 vs. PC:EtOH: 85 ± 3 days) and weight (U: 262 ± 7 vs. PC:EtOH: 258 ± 7 g) at the start of the experimental protocol. There was no difference in caloric intake at any time during pregnancy as reported previously (Gardebjer et al., 2014). Gestational weight gain was similar between treatment groups (data not shown). The average and the peak PAC two days prior to mating was 0.07 ± 0.01% and 0.18 ± 0.04% respectively, and the peak PAC on E2 was 0.25 ± 0.04% (Gardebjer et al., 2014). There were no differences in gestational length (22 days), litter size (15 ± 1 pups), or the male:female ratio (U: 1.13 vs. PC:EtOH: 1.17) between treatment groups. Body weight at weaning (PN28) was also similar between treatment groups (Table 4.1) with no apparent differences in body weight prior to initiation of the HFD at 3 months (Table 4.1). Whilst consumption of a HFD significantly increased weight gain between weeks 17-24 and weeks 25-32 in both male and female offspring of both treatment groups (P < 0.0001, Table 4.1), PC:EtOH-exposure alone or in conjunction with HFD did not significantly affect growth (Table 4.1).

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Table 4.1 Offspring weights and weight gain of untreated (U) and PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD) Treatment group Statistics (P values) U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction Male Body weight at weaning, g 75 ± 4 74 ± 3 N/A N/A NS N/A N/A Body weight at 16 weeks, g 475 ± 8 479 ± 8 490 ± 11 480 ± 14 NS NS NS Weight gain (week 17-24), g 104 ± 7 108 ± 4 156 ± 16 169 ± 8 NS <0.0001 NS Weight gain (week 25-32), g 54 ± 5 57 ± 4 105 ± 10 94 ± 9 NS <0.0001 NS Body weight at PM, (week 32) g 606 ± 16 607 ± 13 681 ± 22 727 ± 45 NS <0.001 NS Snout-rump length at PM, cm 28.5 ± 0.2 28.1 ± 0.3 28.8 ± 0.3 28.8 ± 0.5 NS NS NS

Female

Body weight at weaning, g 72 ± 3 66 ± 2 N/A N/A 0.06 N/A N/A

Body weight at 16 weeks, g 283 ± 6 283 ± 4 286 ± 3 287 ± 6 NS NS NS Female Weight gain (week 17-24), g 47 ± 3 43 ± 3 73 ± 6 71 ± 8 NS <0.0001 NS Weight gain (week 25-32), g 20 ± 2 18 ± 2 47 ± 4 40 ± 6 NS <0.0001 NS Body weight at PM, (week 32) g 315 ± 16 309 ± 14 387 ± 20 354 ± 18 NS <0.01 NS Snout-rump length at PM, cm 23.8 ± 0.3 23.0 ± 0.3 24.2 ± 0.4 23.8 ± 0.3 0.06 <0.05 NS

HFD, high-fat diet; N/A, no data available; NS, not statistically significant; PC:EtOH, periconceptional alcohol; PM, post mortem. Body weight at weaning was analyzed with an unpaired t-test. All other data was analyzed with a two-way-ANOVA within each sex with main effects of PC:EtOH and HFD. Data are represented as mean ± SEM.

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4.3.2 GTT and ITT at 6 months

Primarily we examined the effects of the periconceptional alcohol exposure on glucose tolerance and insulin sensitivity in animals on the control diet in male and female offspring. We found that PC:EtOH-exposure increased fasting glucose concentrations (P < 0.05), although this was significantly greater in males than females (Figure 4.1 A). This effect was associated with a non-significant increase in fasting insulin concentrations (PPC:EtOH < 0.07, Figure 4.1 B), and significantly altered

HOMA-IR and QUICKI indices (PPC:EtOH < 0.05, Figure 4.1 C & D). However, there were significant sex differences, with females exhibiting lower fasting insulin concentrations than males, and correspondingly lower HOMA-IR and higher QUICKI indices (Psex < 0.05, Figure 4.1 B-D). In the GTT, glucose clearance was inhibited in both sexes by PC:EtOH-exposure, as indicated by increased AUGC (PPC:EtOH < 0.01, Figure 4.2 A & B). Furthermore, both sexes displayed increased pancreatic insulin output (AUIC) during the GTT (PPC:EtOH < 0.01, Figure 4.2 C & D). The increased insulin response was both acute first-phase (PPC:EtOH < 0.05, Figure 4.2 E) and second-phase (PPC:EtOH < 0.001, Figure 4.2 F). Correspondingly, the AUIC:AUGC- ratio was increased by PC:EtOH-exposure (PPC:EtOH < 0.05, Table 4.2). In the ITT, glucose clearance from circulation in response to exogenous insulin was decreased by PC:EtOH in both sexes (PPC:EtOH < 0.01, Figure 4.2 G & H).

Second, we ascertained whether there was an interaction between PC:EtOH and a PN HFD in metabolic outcomes. To examine this interaction, we analysed males and females separately. In males, consumption of a HFD augmented fasting glucose concentrations, to a similar degree in both untreated and PC:EtOH (PHFD < 0.001, Table 4.2). Similarly, fasting insulin concentrations were also increased following

HFD exposure (PHFD < 0.001, Table 4.2). However, PC:EtOH-exposed males that consumed a HFD had 2-fold higher fasting insulin concentration compared with males of other treatment groups (Pinteraction < 0.01, Table 4.2). This interaction of HFD with PC:EtOH resulted in a marked increase in the HOMA-IR index. In the GTT, consumption of the HFD did not affect the overall glucose (AUGC) or insulin (AUIC) response, but the HFD diet did increase acute first-phase insulin secretion (PHFD < 0.01), and further exacerbated (P < 0.05) the response to PC:EtOH-exposure (Table

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4.2). In the ITT, the HFD did not affect the glucose clearance in response to exogenous insulin beyond the effect of PC:EtOH.

In females, there were generally significant effects of consuming a postnatal HFD in the absence of outcomes following PC:EtOH-exposure (Table 4.2). The HFD had no effect on fasting glucose concentrations, but increased fasting insulin concentrations

(PHFD < 0.01, Table 4.2). This was associated with altered HOMA-IR and QUICKI indices (PHFD < 0.01, Table 4.2). Similarly in the GTT, the AUGC, AUIC, AUIC:AUGC-ratio, and acute first-phase and second-phase insulin secretion, and the AUGC in the ITT were all increased by the HFD (PHFD < 0.05; < 0.01; < 0.01; < 0.01; < 0.01, < 0.05 respectively), but there were no significant interactions between PC:EtOH and HFD in females for any of these measures (Table 4.2).

A B

C D

Figure 4.1 – The effect of periconceptional alcohol exposure on fasting plasma glucose and insulin, HOMA-IR and QUICKI scores .. Effects of PC:EtOH-exposure (black bars) on (A) fasting plasma glucose and (B) insulin concentration in male and female offspring at 6 months of age. Corresponding homeostatic model assessment (HOMA) of insulin resistance (C) and quantitative insulin sensitivity check index (QUICKI) (D) compared with U:C (white bars). Data is represented as mean ± SEM and compared with the untreated male group. n = 8-12 per group. NS, not statistically significant. 143

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Figure 4.2 – The effect of periconceptional alcohol exposure on glucose and insulin homeostasis Plasma glucose clearance following a glucose tolerance test (GTT) (A), area under the glucose curve (AUGC) generated from the GTT (B), plasma insulin secretion following a GTT (C), total area under the insulin curve (AUIC) generated from the GTT (D) with acute first- and second-phase insulin secretion shown in (E & F). Plasma glucose concentration following an insulin tolerance test (ITT) (G) and the inverted AUGC generated from the ITT (H). All experiments were performed on male and female offspring at 6 months of age. n = 8-12 for PC:EtOH (black bars) and untreated (white bars) groups. For curves: untreated males (white circles), PC:EtOH males (black circles), untreated females (white squares) and PC:EtOH females (black squares). Data is represented as mean ± SEM and compared with the untreated male group. NS, not statistically significant. 144

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Table 4.2 Plasma glucose and insulin chemistry of untreated (U) and PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD) Treatment group Statistics (P values) U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction Male Fasting glucose (mmol/L) 7.0 ± 0.1 7.6 ± 0.2 7.8 ± 0.2 8.2 ± 0.2 <0.01 <0.001 NS Fasting insulin (pmol/L) 315.0 ± 70.0a 437.5 ± 70.0a 367.5 ± 52.5a 892.5 ± 105.0b <0.0001 <0.001 <0.01 HOMA-IR index 0.57 ± 0.12a 0.86 ± 0.15a 0.75 ± 0.12a 1.92 ± 0.25b <0.0001 <0.001 <0.01 QUICKI index 0.45 ± 0.03 0.40 ± 0.01 0.41 ± 0.01 0.35 ± 0.01 <0.01 <0.05 NS AUGC (GTT) 1020 ± 46 1206 ± 47 1054 ± 55 1217 ± 48 <0.01 NS NS Total AUIC (GTT) 238 ± 59 493 ± 86 285 ± 39 695 ± 88 <0.0001 NS NS AUIC (first-phase) (GTT) 26 ± 5a 40 ± 8a 30 ± 5a 78 ± 11b <0.001 <0.01 <0.05 AUIC (second-phase) (GTT) 194 ± 51 422 ± 73 235 ± 34 565 ± 71 <0.0001 NS NS AUIC/AUGC 0.23 ± 0.05 0.41 ± 0.07 0.26 ± 0.04 0.55 ± 0.07 <0.001 NS NS AUGC (ITT) 1521 ± 57 1280 ± 94 1316 ± 58 1308 ± 63 <0.05 NS NS

Female Fasting glucose (mmol/L) 6.9 ± 0.2 7.0 ± 0.2 7.5 ± 0.3 7.4 ± 0.4 NS NS NS Fasting insulin (pmol/L) 175.0 ± 35.0 227.5 ± 35.0 402.5 ± 87.5 455.0 ± 87.5 NS <0.01 NS HOMA-IR index 0.31 ± 0.07 0.42 ± 0.09 0.82 ± 0.18 0.93 ± 0.20 NS <0.01 NS QUICKI index 0.51 ± 0.03 0.46 ± 0.02 0.41 ± 0.05 0.42 ± 0.03 NS <0.01 NS AUGC (GTT) 1023 ± 21 1115 ± 57 1211 ± 65 1191 ± 57 NS <0.05 NS Total AUIC (GTT) 190 ± 39 277 ± 25 466 ± 94 502 ± 99 NS <0.01 NS AUIC (first-phase) (GTT) 17 ± 2 25 ± 4 42 ± 8 45 ± 9 NS <0.01 NS AUIC (second-phase) (GTT) 160 ± 37 231 ± 21 392 ± 85 424 ± 85 NS <0.01 NS AUIC/AUGC 0.20 ± 0.04 0.26 ± 0.03 0.37 ± 0.06 0.41 ± 0.07 NS <0.01 NS AUGC (ITT) 1544 ± 49 1357 ± 69 1263 ± 52 1168 ± 40 <0.01 <0.001 NS

AUGC, area under the glucose curve; AUIC, area under the insulin curve; HOMA-IR, homeostatic model for assessment of insulin resistance; NS, not statistically significant; QUICKI, quantitative insulin sensitivity check index. Fasting glucose and insulin concentrations were prior to glucose tolerance test (GTT); basal glucose concentrations were prior to insulin tolerance test (ITT). Data was analysed with a two-way-ANOVA with post-hoc Tukey’s multiple comparison test. Values with different superscript letters are significantly different (P < 0.05).

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4.3.4 Hepatic gluconeogenesis

Having established that PC:EtOH-exposure resulted in metabolic dysfunction, we sought to determine if this was associated with changes in expression of genes regulating hepatic gluconeogenesis. We found that PC:EtOH-exposure increased mRNA-expression of G6pc (PPC:EtOH < 0.01, Figure 4.3 A), Pck1 (PPC:EtOH < 0.05, Figure 4.3 C), peroxisome proliferator-activated receptor gamma, coactivator 1α

(Ppargc1a) (PPC:EtOH < 0.05, Figure 4.3 D) and decreased expression of Gck

(PPC:EtOH < 0.01, Figure 4.3 B) in both sexes. Overall mRNA-expression of Ppargc1a was higher in females compared with males (Psex < 0.001, Figure 4.3 D), whereas

Gck was expressed at lower levels in females than males (Psex < 0.01, Figure 4.3 B).

The HFD did not affect the gene expression of G6pc, Pck1, or Ppargc1a in males

(Table 4.3). HFD-fed males had increased gene expression of Gck (PHFD < 0.01), but there was no significant interaction of a HFD with PC:EtOH (Table 4.3). In females, the HFD had no effect on G6pc, Ppargc1a or Gck (Table 4.3). However the HFD decreased gene expression of Pck1 (PHFD < 0.01) and this decrease was greater in females exposed to PC:EtOH compared with control-fed females (PInteraction < 0.01, Table 4.3).

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Figure 4.3 – The effect of periconceptional alcohol exposure on hepatic mRNA levels . The effect of PC:EtOH-exposure (black bars) on hepatic mRNA levels of glucose-6-phosphatase (G6pc) (A), glucokinase (Gck) (B), phosphoenolpyruvate carboxykinase (Pck1) (C), and peroxisomeproliferator-activated receptor-gamma co-activator alpha (Ppargc1a) (D) compared with U:C (white bars) in male and female offspring at 8 months of age, n = 6-8 per group. Values are expressed as relative gene expression levels normalized to endogenous control ribosomal 18s. Data is represented as mean ± SEM and compared with the untreated male group. NS, not statistically significant.

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Table 4.3 Relative mRNA levels of hepatic genes of untreated (U) and PC:EtOH-exposed offspring fed a control (C) or a high-fat diet (HFD)

Treatment group Statistics (P values)

U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction Male G6pc 1.09 ± 0.19 1.62 ± 0.39 1.15 ± 0.21 1.40 ± 0.28 NS NS NS Gck 1.08 ± 0.17 0.80 ± 0.34 1.82 ± 0.19 1.58 ± 0.37 NS <0.01 NS Pck1 1.08 ± 0.17 1.52 ± 0.18 1.05 ± 0.21 1.34 ± 0.21 0.07 NS NS Ppargc1a 1.29 ± 0.30 1.66 ± 0.34 1.78 ± 0.55 2.23 ± 0.56 NS NS NS

Female G6pc 1.07 ± 0.13 2.08 ± 0.42 2.06 ± 0.40 1.48 ± 0.39 NS NS <0.05 Gck 1.17 ± 0.24 0.72 ± 0.18 1.11 ± 0.25 0.86 ± 0.18 NS NS NS Pck1 1.07 ± 0.13ab 1.60 ± 0.20b 1.07 ± 0.15ab 0.80 ± 0.10a NS <0.01 <0.01 Ppargc1a 1.14 ± 0.19 1.80 ± 0.22 0.84 ± 0.15 1.34 ± 0.22 <0.01 0.06 NS

G6pc, glucose-6-phosphatase; Gck, glucokinase; Pck1, phosphoenolpyruvate carboxykinasel; Ppargc1a, peroxisome proliferator-activated receptor gamma, coactivator 1α; NS, not statistically significant. All data were analyzed with a two-way-ANOVA compared with the U/C group for each sex. Data are represented as mean ± SEM. Mean values with different superscript letters are significantly different with post-hoc Tukey’s multiple comparison test. Values with different superscript letters are significantly different (P < 0.05).

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4.3.5 Peripheral insulin signaling

As peripheral insulin insensitivity is often due to altered insulin signaling, we examined protein expression of AKT2 and GSK3β and their basal serine/threonine phosphorylation states in adipose tissue and skeletal muscle in control-fed offspring.

PC:EtOH-exposed males had higher protein levels of tAKT2 (PPC:EtOH < 0.05, Figure

4.4 A), basal pAKTThr309 (U: 0.71 ± 0.34 vs. PC:EtOH: 5.27 ± 0.90, P < 0.01), and pAKTThr309/tAKT ratio (PPC:EtOH < 0.05, Figure 4.4 A) in adipose tissue compared with untreated males. Neither pAKTSer474 (U: 1.00 ± 0.29 vs. PC:EtOH: 1.11 ± 0.31) or the pAKTSer474/tAKT ratio (Figure 4.4 A) were different in adipose tissue between untreated and PC:EtOH-exposed males. In skeletal muscle, there was no significant difference in tAKT2 (U: 1.00 ± 0.32 vs. PC:EtOH: 0.77 ± 0.11), pAKTSer474 (U: 1.00 ±

0.27 vs. PC:EtOH: 0.70 ± 0.17) or the pAKTSer474/tAKT ratio (U: 1.00 ± 0.20 vs. PC:EtOH: 0.86 ± 0.19) between untreated and PC:EtOH-exposed males respectively (data not shown).

In control-fed female offspring, protein levels of tAKT2 in adipose tissue were similar in PC:EtOH-exposed and untreated groups (Figure 4.4 B), but pAKTThr309 (U: 1.00 ±

0.12 vs. PC:EtOH: 0.26 ± 0.16, P < 0.01), the pAKTThr309/tAKT ratio (P < 0.01, Fig.

4B), pAKTSer474 (U: 1.00 ± 0.12 vs. PC:EtOH: 0.33 ± 0.08, P < 0.001), and the pAKTSer474/tAKT ratio (P < 0.001, Figure 4.4 B) were all significantly lower following PC:EtOH. In skeletal muscle, PC:EtOH-exposed females had higher protein levels of tAKT (U: 1.00 ± 0.19 vs. PC:EtOH: 1.49 ± 0.08, P < 0.05). Both pAKTSer474 (U: 1.00 ±

0.24 vs. PC:EtOH: 0.58 ± 0.18) and the pAKTSer474/tAKT ratio (U: 1.00 ± 0.25 vs. PC:EtOH: 0.50 ± 0.30) lower following PC:EtOH-exposure but this did not reach statistical significance (P < 0.11) (data not shown).

Protein levels of tGSK3β and pGSK3βSer9/tGSK3β in adipose tissue were similar between all control-fed groups (Figure 4.4 C & D). Similar results for GSK3β were found in skeletal muscle of both sexes (data not shown).

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Figure 4.4 – The effect of periconceptional alcohol exposure on AKT and GSK3β-protein in adipose tissue The effect of PC:EtOH-exposure (black bars) on protein levels in white intra-abdominal adipose tissue in male and female offspring at 8 months of age compared with U:C (white bars), n = 4-6 per group. Total (t)AKT2 levels, phosphorylated (p)AKTThr309/tAKT ratio and the pAKTSer474/tAKT ratio in males (A) and females (B). tGSK3β and the pGSK3βSer9/tGSK3β ratio in males (C) and females (D). Values for the protein levels are normalised to β-Actin. Data is represented as mean ± SEM. * P < 0.05; * P < 0.01; * P < 0.001 by Students t-test.

. . . .

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4.3.6 Fetal liver expression of chromatin modifiers

An adverse environment during the periconceptional period may result in epigenetic changes and thus long-term alterations in gene expression, which have been implicated as an underlying mechanism in the development of metabolic disease (McMillen et al., 2008, Sinclair et al., 2007, Maloney et al., 2011). We therefore examined expression levels of key chromatin modifiers, namely HDACs and DNA DNMTs in fetal liver following periconceptional alcohol exposure. PC:EtOH-exposure increased mRNA- expression of Dnmt1, Dnmt3a and Dnmt3b in liver from fetuses on E20 (PPC:EtOH < 0.05, Figure 4.5 A-C) but had no effect on Hdac2, Hdac3, Hdac4 or Hdac6 mRNA levels (data not shown).

Figure 4.5 – The effect of periconceptional alcohol exposure on the expression of hepatic DNA methyltransferases on E20 . The effect of PC:EtOH-exposure (black bars) on fetal hepatic mRNA levels of DNA methyltransferase (Dnmt)1 (A), Dnmt3a (B) and Dnmt3b (C) compared with untreated offspring (white bars) in males and females on E20, n = 9-11 per group. Values are expressed as relative gene expression levels normalized to endogenous control ribosomal 18s. Data is represented as mean ± SEM and compared with the untreated male group. NS, 151 not statistically significant.

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4.4 Discussion

Our data demonstrate for the first time that maternal alcohol consumption for a short period exclusively during the periconceptional period impairs glucose tolerance and decreases insulin sensitivity in both male and female adult offspring at 6 months of age. This metabolic phenotype was associated with increased hepatic gluconeogenesis in both sexes, indicated by increased levels of G6pc, Pck1 and Ppargc1a, and decreased levels of Gck mRNA, although increased fasting glucose concentrations was only apparent in males. Furthermore, sex-specific alterations in AKT2 signaling were observed in peripheral tissues. Importantly, consumption of a postnatal HFD exacerbated both fasting insulin concentrations and acute first-phase insulin secretion during the GTT more than 2-fold in PC:EtOH-exposed male offspring relative to PC:EtOH-exposure or a HFD alone. Our data demonstrate that PC:EtOH-exposure around the time of conception is sufficient to cause a prediabetic insulin insensitive state in both male and female offspring, with significant interactive effects of HFD and PC:EtOH in male, but not female offspring. Analysis of fetal liver mRNA in late gestation demonstrated altered expression of multiple DNA methyltransferases, suggesting that long term metabolic outcomes following PC:EtOH may partly derive from changes in methylation status.

Several animal studies have previously linked maternal alcohol consumption during pregnancy to insulin resistance and glucose intolerance in offspring postnatally (Chen and Nyomba, 2003b, Chen and Nyomba, 2003a, Lopez-Tejero et al., 1989). Maternal EtOH-exposure throughout pregnancy (gavage of 2 g/kg EtOH twice daily, or ~13E% daily) impairs glucose tolerance in rat offspring at 3 months of age, despite hyperinsulinemia (Chen and Nyomba, 2003a). Indeed, persistent hyperinsulinemia is reported to occur from the first day of postnatal life in the rat following maternal EtOH-exposure throughout pregnancy (25% in drinking water, >30E%) (Lopez-Tejero et al., 1989). This is consistent with our own data that more moderate maternal alcohol consumption (6% v/v via a liquid diet, ~15E% daily) throughout pregnancy results in hyperinsulinemia in male, but not female rat offspring at 4 months of age (Probyn et al., 2013c). Collectively, these studies highlight that maternal alcohol consumption during pregnancy can alter glucose metabolism in offspring. Here for the first time, we report that alcohol consumption

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(12.5% v/v, or ~22E%) solely during the periconceptional period (4 days prior to conception until day 4 of gestation) is sufficient to program similar metabolic responses in offspring later in postnatal life.

Although insulin directly inhibits de novo glucose output from the liver to the bloodstream by supressing gluconeogenesis (Huang, 2009), it is well characterized that hepatic glucose output remains high in an insulin resistant state (Mitrakou et al., 1992). Intriguingly, in our study, fasting plasma glucose concentrations were increased, especially in males following PC:EtOH-exposure, indicating increased hepatic gluconeogenesis (DeFronzo et al., 1981). In contrast, PC:EtOH-treated females were euglycaemic and exhibited better insulin sensitivity (lower HOMA-IR and higher QUICKI indices) than males. To further examine gluconeogenesis in our animals, we investigated alterations in hepatic gene expression. We found that PC:EtOH-exposure increased the relative gene expression of the rate-limiting gluconeogenic enzyme Pck1 (Rognstad, 1979). Relatively small increases in Pck1 gene expression are known to be sufficient to increase hepatic gluconeogenesis and impair glucose tolerance (Sun et al., 2002). Interestingly, glucose intolerance associated with increased hepatic Pck1 expression has also been demonstrated in offspring following prenatal protein restriction (Desai et al., 1997) and maternal glucocorticoid administration (Drake et al., 2005). Levels of Ppargc1a mRNA, a transcription factor which stimulates the expression of Pck1 and G6pc (Yoon et al., 2001), were also increased following PC:EtOH-exposure as were levels of G6pc mRNA, despite hyperinsulinemia. Increased gluconeogenesis associated with increased basal gene expression of both Pck1 and Ppargc1a has previously been demonstrated in rats prenatally exposed to alcohol throughout pregnancy (Yao et al., 2013). Furthermore, Gck gene expression was decreased in PC:EtOH-exposed offspring, consistent with an insulin resistant phenotype (Caro et al., 1995). Collectively, our data suggest that increased hepatic glucose output contributes to the insulin insensitive phenotype in both PC:EtOH-exposed male and female offspring.

Although debatable, insulin resistance often precedes any impairment of β-cell function (Warram et al., 1990). Blood glucose levels can be normal or near normal as the β-cells hypersecrete insulin to compensate for the developing insulin

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resistance (Kasuga, 2006). In our study, PC:EtOH-exposed offspring displayed only minor increases in fasting insulin and no loss of either first- or second-phase insulin secretion during the GTT. Instead, hypersecretion of insulin in response to a glucose load was observed, indicative of β-cell compensation. Furthermore, reduced responsiveness of PC:EtOH-exposed offspring to exogenous insulin (ITT) confirmed an insulin insensitive phenotype. Our results therefore support the notion that the effect of PC:EtOH-exposure is most likely due to dysregulation in tissue-specific insulin signaling (insulin insensitivity) and resultant pancreatic β-cell compensation, rather than PC:EtOH-exposure causing a direct pancreatic defect, like β-cell failure (Thompson et al., 2007, Devaskar and Thamotharan, 2007).

We consequently investigated AKT2 activation in adipose tissue and skeletal muscle, which is necessary for GLUT4 translocation and insulin-mediated glucose uptake (Huang, 2009, Devaskar and Thamotharan, 2007). Since consumption of the HFD did not exacerbate the already impaired insulin sensitivity, we quantified AKT2 levels only in untreated and PC:EtOH-exposed control-fed offspring. Given the phenotypes of impaired glucose tolerance and insulin insensitivity in PC:EtOH offspring, we expected AKT2 activity to be decreased in peripheral tissues. Indeed, female offspring exposed to EtOH during the periconceptional period had decreased AKT2 phosphorylation in adipose tissue (Ser474 and Thr309), whilst in skeletal muscle Ser474 phosphorylation tended to be decreased. Such decreases in phosphorylation of AKT2 are consistent with lower basal kinase activity (Thr309) and reduced “full” kinase activity in response to insulin (Ser474) (Schultze et al., 2011). Paradoxically, in PC:EtOH-exposed male offspring, there was an increase in tAKT2 in adipose tissue, which might improve insulin sensitivity (Bae et al., 2003). Similar increases in tAKT2 have been demonstrated in skeletal muscle of twin sheep offspring exposed to periconceptional undernutrition (Lie et al., 2014), and in male, but not female offspring of obese mice (Shelley et al., 2009). Such up-regulation of tAKT2 levels is possibly a compensatory mechanism, and may be a direct result of increased basal insulin levels (40% higher in PC:EtOH-exposed males). Moreover the ratio of Thr309 phosphorylation to total AKT2 was also increased in adipose tissue of PC:EtOH-exposed male offspring, affirming the idea of increased insulin signaling in this tissue. These apparently disparate results in adipose tissue of male PC:EtOH-exposed offspring require further investigation as increased phosphor- 154

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ylation at Thr309 together with tAKT2 may be related to signaling pathways mediating adipogenesis and/or angiogenesis (He et al., 2010, Shiojima and Walsh, 2002). Notwithstanding these sex-specific effects on insulin signaling in peripheral tissues, our data suggest maternal alcohol consumption during the periconceptional period programs a phenotype that is consistent with metabolic dysfunction and insulin resistance.

There is growing evidence that perturbations around periconception can result in epigenetic modifications such as DNA methylation or histone acetylation, which have been implicated as an underlying mechanism in the development of metabolic disease (McMillen et al., 2008, Sinclair et al., 2007, Maloney et al., 2011). Key effectors are DNMTs, histone acetyltransferases (HATs), and HDAC proteins, respectively. Maternal alcohol consumption (E1-E7) has previously been linked to increased adult hepatic gluconeogenesis in association with increased class II HDAC protein activity (Yao et al., 2013). Although we did not observe changes in fetal liver Hdac mRNA expression, we cannot rule out the possibility that protein activity of these chromatin modifiers is altered in our model to impact on chromatin accessibility. Levels of expression of Dnmt genes however, were significantly increased in the fetal liver at E20 suggesting long-term alterations in methylation status. This is consistent with other recently published data showing dysregulation of hippocampal DNMT activity without changes in HDAC activity in a rat model of early life alcohol exposure (Perkins et al., 2013). It is tempting to speculate that increased Dnmt expression and consequent hypermethylation may provide the link between PC:EtOH and alterations in gene expression associated with the metabolic phenotype observed. Consistent with our data, Ppargc1a expression is reduced by hypermethylation of the PPARGC1A-promoter in diabetic patients (Barres et al., 2009), and correlates positively with fasting plasma insulin levels and HOMA-IR (Sookoian et al., 2010).

Other studies have demonstrated altered insulin and glucose dynamics following maternal periconceptional methionine deficiency in sheep (Sinclair et al., 2007) and rats (Maloney et al., 2011). Methionine provides methyl groups for the production of S-adenosyl methionine, a substrate for DNMTs. Significantly, we have previously demonstrated decreased expression of the major methionine transporter, Slc38a2, in

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the placenta following PC:EtOH (Gardebjer et al., 2014). Intriguingly, global DNA methylation is increased in response to either methionine or choline deficiency through pregnancy (Sinclair et al., 2007, Kovacheva et al., 2007) and this is associated with increased expression of Dnmts, which is driven by hypomethylation of the Dnmt1 promoter (Kovacheva et al., 2007). Data from mice suggest that a perturbed preimplantation environment can also alter levels of the de novo DNA methyl transferase Dnmt3l (Kafer et al., 2011). This potentially impacts on de novo genome-wide methylation following resetting of epigenetic marks that occurs during this stage are also consistent with our data. Early embryonic alcohol exposure has also been demonstrated to result in allele specific changes in methylation patterns of the H19/Igf2 domain in the placenta of mice which may contribute to growth restriction (Haycock and Ramsay, 2009).

In conclusion, our data establish that maternal consumption of alcohol during the periconceptional period programs impaired glucose tolerance and insulin insensitivity in offspring, which was associated with altered expression of key modifiers of fetal methylation status. Whilst these conditions are evident in both males and females, dysregulation of peripheral insulin signaling appeared to be sexually dimorphic with male offspring being more susceptible to a combination of PC:EtOH-exposure and a postnatal high-fat diet than females. These novel findings have important clinical implications for women wanting to conceive and bear healthy children.

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CHAPTER 5

Contributor Statement of contribution Gårdebjer, E. M. Study design (50%) Animal treatment* (80%) Tissue collection† (65%) DXA-scan (60%) Plasma assays (100%) Gene and protein studies (100%) Histological studies (80%) Interpreting results (65%) Writing manuscript (70%) Ward, S. DXA-scan (40%) Interpretation of results (10%) Reviewing and editing manuscript (10%) Biefeldt-Ohmann, H. Histological studies (20%) Interpretation of results (10%) Reviewing and editing manuscript (5%) Wlodek, M. E. Reviewing and editing manuscript (5%) Moritz, K. M. Study design (50%) Animal treatment* (5%) Tissue collection† (20%) Interpretation of results (15%) Reviewing and editing manuscript (10%)

*, Remaining 15% performed by Kalisch-Smith, J; †, remaining 15% contributed to by other members of Moritz’s lab

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Title: The effects of maternal alcohol intake around conception and a postnatal high-fat diet on adiposity in male and female rat offspring

Running Title: Adult obesity following periconceptional alcohol

Authors and affiliations: Emelie M Gårdebjer1, Leigh C Ward2, Helle Bielfeldt- Ohmann3, Mary E Wlodek2 and Karen M Moritz1.

Schools of 1Biomedical Sciences and 2Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia; School of Veterinary Sciences, The University of Queensland, Gatton, Queensland, Australia; and 3The Department of Physiology, The University of Melbourne, Parkville, Victoria, Australia.

Keywords: Developmental programming, obesity, steatosis, inflammation, adult onset disease

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Abstract

Introduction: The effects of maternal alcohol consumption around the time of conception – a critical window of development – on adult onset obesity are largely unknown. We examined if PC:EtOH affected the development of obesity and/or NAFLD in adult offspring. We also studied the interaction of PC:EtOH with a postnatal HFD.

Methods: Female Sprague-Dawley rats were fed a control or EtOH-containing liquid diet (0% or 12.5% EtOH v/v) from 4 days prior to mating until 4 days of gestation (n = 12 per group). A subset of offspring was fed a HFD between 3-8 months of age, resulting in 8 groups for analysis. Body composition was assessed with DXA at 7 months. Plasma was collected at PN30 and at 8 months when animals were killed for tissue collection. Results were analyzed separately for each sex.

Results: Both PC:EtOH and HFD increased total fat mass in males (PPC:EtOH < 0.05;

PHFD < 0.0001); but only HFD increased fat mass in females (PHFD < 0.0001). PC:EtOH increased the incidence of microvesicular steatosis and hepatic inflammation in male offspring only. At PN30, plasma leptin was increased in male and triglycerides decreased in female PC:EtOH-exposed offspring (PPC:EtOH < 0.05). At 8 months, PC:EtOH-exposure increased plasma triglycerides, HDL and cholesterol in male offspring (PPC:EtOH < 0.05); and LDL, cholesterol and leptin in female offspring (PPC:EtOH < 0.05). HFD increased HDL (PHFD < 0.05) and leptin (PHFD

< 0.01) in males and triglycerides, cholesterol and leptin (PHFD < 0.05) in females. mRNA levels of Tnf-α and Leptin in visceral adipose were increased in both sexes

(PPC:EtOH < 0.05) following PC:EtOH-exposure.

Discussion and conclusion: Consuming alcohol around conception increases the risk of obesity, alters the plasma lipid profile and induces adult steatosis in a sex-specific manner. PC:EtOH-programmed phenotypes were similar to those caused by consumption of a postnatal HFD, particularly in male offspring. These results have important implications for women who have consumed alcohol around the time of conception.

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5.1 Introduction

Accumulating evidence suggests that exposure to a suboptimal environment in utero, including maternal alcohol intake (Shen et al., 2014), can impact on fetal development and offspring health, and therefore partially explain the rapid increase in disorders such as obesity and NAFLD (McMillen and Robinson, 2005). The timing of exposure may be important in determining the severity of the outcome (Fleming et al., 2004). Most developmental programming studies have focused on maternal insults when present throughout gestation; but the time shortly prior to conception until embryonic implantation (the periconceptional period) may be equally important (Lie et al., 2014, Maloney et al., 2011, Zhang et al., 2011). Very little, however, is known about how alcohol intake during this period – when women are most likely to drink (Floyd et al., 1999, Mullally et al., 2011) – impacts on the long-term health of the offspring, as previous studies have focused on the effects of alcohol when consumed throughout gestation (Chen and Nyomba, 2003a, Chen and Nyomba, 2004, Elton et al., 2002, Lopez-Tejero et al., 1989).

Human data from the Dutch Famine have demonstrated the possibility of obesity to be programmed in utero (de Rooij et al., 2006, Ravelli et al., 1999). Animal models of undernutrition (Jaquiery et al., 2012), low protein diet (Bol et al., 2009) and uteroplacental insufficiency (Joss-Moore et al., 2010) in various species have confirmed this. Prenatal alcohol exposure has been extensively investigated in relation to alterations in glucose and insulin metabolism (Probyn et al., 2013c, Chen and Nyomba, 2003a, Chen et al., 2004). Considering the strong links between insulin resistance, obesity and inflammation (Peraldi and Spiegelman, 1998, Fantuzzi, 2005), relatively less is known about the consequences of maternal alcohol consumption on adult obesity (Dobson et al., 2012), especially when consumed around conception only. In some cases, a mismatch between the pre- and postnatal environment can reveal or exacerbate an in utero-programmed phenotype (Chen and Nyomba, 2003b, Rueda-Clausen et al., 2011). This is particularly important as developmental programming generally affects male and female offspring differently. Neglecting the sex of the offspring in the analyses may therefore confound conclusions to be drawn, especially in cases where such mismatch occurs (Vickers et al., 2000).

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We have recently shown that maternal alcohol intake when limited to the time of conception (PC:EtOH-exposure) restricts fetal growth (Gardebjer et al., 2014) – a strong indicator of adult onset disease (Floyd et al., 1999) – and induces a prediabetic state in adult offspring (Gardebjer et al., 2015). Here, using the same model, we aimed to determine: 1) if PC:EtOH-exposure contributes to obesity in the adult offspring; 2) if a postnatal HFD interacts with PC:EtOH to exacerbate the phenotype; and 3) to establish whether male and female offspring are affected differently. Our study has important clinical implications as it can provide evidence to the current recommendations given to women concerning alcohol and pregnancy and ultimately secure the future health of the baby.

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5.2 Materials and methods

5.2.1 Ethics

All animal experimentation was approved by The University of Queensland Anatomical Bioscience Animal Ethics Committee (SBS/022/12/NHMRC) prior to commencement of the study.

5.2.2 Animal treatment

Nulliparous Sprague-Dawley rats (n = 12 per treatment group) were treated as described in detail previously (Gardebjer et al., 2015). Briefly, dams were given a liquid diet containing either 0% or 12.5% EtOH (v/v) with similar energy composition from 4 days prior to mating until 4 days of gestation (control diet composition: 11.3% fat, 17.0% protein, 68.2% carbohydrates, 7.7MJ/kg; EtOH-diet: 11.9% fat, 13.6% protein, 50.7% carbohydrates, 11.8MJ/kg). Standard chow was offered from day 5. At PN30 blood samples were collected from a subset of offspring. At 3 months of age, a subset of offspring were randomly assigned a HFD (21% fat, 0.15% cholesterol, 19% protein, 59.9% carbohydrates; 19.4 MJ/kg) while one remained on standardized chow (C; 4.0% fat, 13.6% protein 64.3% carbohydrates; 15.5 MJ/kg), generating four treatment groups: untreated U:C; U:HFD; PC:EtOH:C and PC:EtOH:HFD for both male and female offspring.

5.2.3 Body composition measurements

A dual-energy X-ray absorptiometer (DXA; model XR36, Norland Corp., Fort Atkinson, USA) was used to determine body composition total FM, total FFM, abdominal fat mass, BMD and BMC) at 7 months (n = 10-11/group). Rats were anesthetized with an i.p. injection of a 50/50 mix of Zoletil/Xylazile (0.1 mL/100 g body weight). Scan images were analysed using the manufacturer’s recommended software for use in laboratory animals (small subject analysis software, version 2.5.3/1.3.1, Norland Corp., Fort Atkinson, USA).

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5.2.4 Tissue collection

Offspring (n = 12 per group) were sacrificed at 8 months following an overnight fasting period, with an i.p. administration of a mix of 50/50 Ketamine/Xylazile (0.5 mL/100 g body weight). Snout-rump length and abdominal girth were measured. Liver and visceral abdominal adipose tissue were snap frozen in liquid nitrogen and stored in -80oC, and the apexes of the left lateral lobe of the liver were collected in 4% PFA for histological analyses.

5.2.5 Blood sampling and plasma chemistry

Blood was collected via cardiac puncture on PN30 and at 8 months, immediately spun (3000 rpm, 15 minutes, 4oC) and plasma stored at -80oC. Triglycerides, HDL, LDL, total cholesterol and electrolytes were analysed with a Cobas Integra 400 Plus Chemistry Analyzer (Block Scientific, NY, USA). Leptin was analysed with a multi- species leptin radioimmunoassay kit with an assay sensitivity of 0.2 ng/mL (Cat.# XL-85K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia). The between and within assay CVs were <6% for two leptin quality controls samples at concentrations 3.3 and 15.9 ng/mL. Adiponectin was analyzed by an enzyme-linked immunosorbent assay with an assay sensitivity of 0.4 ng/mL (Cat#EZRADP-62K, Millipore, Pty. Ltd., Kilsyth, VIC, Australia).

5.2.6 Gene analyses

RNA from the apex of the left lateral lobe of the liver was extracted using an RNeasy Mini-Kit and visceral adipose tissue was extracted using an RNeasy Lipid Tissue Mini Kit (Qiagen, VIC, Australia) and reversed transcribed into cDNA. Gene expression analyses were conducted via qPCR with the Taqman Assay-on-Demand primer/probe set for Leptin (Rn00565158_m1) (Applied Biosystems, CA, USA), or SYBR® Green detection chemistry using the following primers for Tnf-α (F, 5'- GAAACACACGAGACGCTGAA; R, 5'-GAAAGCCCATTGGAATCCTT), and IL-6 (F, 5'-ACTCATCTTGAAAGCACTTG; R, 5'-GTCCACAAACTGATATGCTTAG) (Sigma

Aldrich). mRNA expression was calculated with the ΔΔCT method. Rn18s, which did not differ between groups, was used as the endogenous control (Gardebjer et al., 2014).

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5.2.7 Histological analyses

One section of the left lateral lobe of the liver were processed to paraffin and sectioned at 6 µm. Five representative sections per liver (n = 8 animals/group) were stained with H&E and scored for steatosis, microvesicular steatosis, inflammation and microgranulomas; and five were stained with Masson’s trichrome for evaluation of fibrosis according to the semi-quantitative Kleiner scoring system for non-alcoholic steatohepatitis (NASH) (Kleiner et al., 2005). All scores were performed blinded.

5.2.8 Statistical analyses

Statistical analyses were conducted with GraphPad Prism 6 software for Windows (GraphPad Software, San Diego, CA, USA). PN30 data were analysed by a students t-test for males and females separately. Data for U:C, U:HFD, PC:EtOH:C and PC:EtOH:HFD were analysed by two-way ANOVAs for main effects of PC-treatment

(PPC:EtOH) and postnatal diet (PHFD) with males and females being analysed in separate ANOVAs. Data were log transferred to remove heterogeneity of variance prior to performing the ANOVA analyses as appropriate (Bartlett’s test). In cases where interaction and/or either treatment effect were significant, means were compared using a Tukey’s multiple comparison post-hoc test to look at statistical differences within variables. P < 0.05 was considered statistically significant. All results are presented as mean ± SEM.

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5.3 Results

5.3.1 Animal model

As previously reported, there were no differences in maternal weight, initial age, caloric intake, gestational length, weight gain or litter sizes between PC:EtOH- exposed and untreated dams (Gardebjer et al., 2014).

5.3.2 PN30 outcomes

Body weight, abdominal circumference, ponderal index and liver:body weight-ratio were similar between treatment groups of both male and female offspring; however PC:EtOH-exposed offspring tended to weigh less than their untreated counterparts

(PPC:EtOH = 0.06, Table 5.1). PC:EtOH-exposed male offspring had higher plasma leptin levels (PPC:EtOH < 0.05), and tended to have elevated plasma triglyceride levels

(PPC:EtOH = 0.09) compared with untreated controls on PN30, but plasma cholesterol and HDL were similar between treatment groups (Table 5.1). Females had similar plasma levels of leptin, cholesterol and HDL, but but plasma triglyceride levels were lower following PC:EtOH-exposure (PPC:EtOH < 0.05, Table 5.1).

5.3.3 Adult offspring outcomes

5.3.3.1 Offspring body composition

Figure 5.1 shows that HFD-fed offspring weighed more than control-fed offspring for both sexes at 7 months (PHFD < 0.001, Figure 5.1 A & B), but PC:EtOH-exposure did not affect body weight. At the time of tissue collection at 8 months, similar differences in body weight were observed (PHFD < 0.001 vs 0.01 for males and females respectively, Table 5.2). PC:EtOH-exposed males had lower % fat-free mass and higher % total- and abdominal fat mass compared with untreated groups

(PPC:EtOH < 0.05, Figure 5.1 C, E & G). The weight of intra-abdominal fat pads as a proportion of body weight at the time of tissue collection also tended to be higher following PC:EtOH-exposure (PPC:EtOH = 0.06, Table 5.2). PC:EtOH-exposed males had a larger abdominal circumference compared with untreated males at 8 months

(PHFD < 0.05, Table 5.2), despite a similar ponderal index (Table 5.2). Both PC:EtOH- exposed and untreated males that were fed a postnatal HFD had lower percentage 165

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FFM, and higher total- and abdominal FM (PHFD < 0.0001, Figure 5.1 C, E & G) and a larger amount of intra-abdominal fat per gram body weight (PHFD < 0.0001, Table 5.2) compared with those fed a control diet. HFD-fed male offspring also had a larger abdominal circumference (PHFD < 0.001) and ponderal index (PHFD < 0.01) (Table 5.2) but a HFD did not potentiate the effects of PC:EtOH-exposure.

The body composition of female offspring was unaffected by PC:EtOH, but HFD-fed females had a lower % FFM, higher total- and abdominal FM (PHFD < 0.0001, Figure

5.1 D, F & H), and a larger amount of intra-abdominal fat per gram body weight (PHFD

< 0.001, Table 5.2). Both abdominal circumference (PHFD < 0.001) and ponderal index (PHFD < 0.01) were higher in HFD-fed females (Table 5.2). Similar to male offspring, % BMC and BMD were unaffected by both PC:EtOH-exposure and HFD.

Table 5.1. Body weight and plasma parameters at postnatal day 30 Variables Untreated PC:EtOH Male Body weight (g) 76.5 ± 3.5 73.8 ± 2.2 Abdominal circumference (cm) 11.2 ± 0.2 10.8 ± 0.2 Ponderal index (g/(100xcm3)) 30.4 ± 1.4 28.9 ± 2.6 Liver weight (g/gbw) 0.04 ± 0.001 0.04 ± 0.001 Triglycerides (mmol/L) 0.7 ± 0.1 0.9 ± 0.1 HDL (mmol/L) 1.49 ± 0.05 1.53 ± 0.07 Cholesterol (mmol/L) 2.4 ± 0.1 2.5 ± 0.1 Leptin (ng/mL) 1.68 ± 0.23 2.47 ± 0.31*

Female Body weight (g) 71.8 ± 2.3 65.4 ± 2.2 Abdominal circumference (cm) 10.6 ± 0.4 10.6 ± 0.2 Ponderal index (g/(100xcm3)) 31.0 ± 1.8 30.3 ± 1.5 Liver weight (g/gbw) 0.04 ± 0.001 0.04 ± 0.001 Triglycerides (mmol/L) 1.0 ± 0.1 0.6 ± 0.1* HDL (mmol/L) 1.57 ± 0.08 1.58 ± 0.14 Cholesterol (mmol/L) 2.6 ± 0.1 2.5 ± 0.2 Leptin (ng/mL) 1.75 ± 0.18 1.70 ± 0.21

C, control; HDL, high density lipoprotein; PC:EtOH, periconceptional alcohol; U, untreated. Data are presented as mean ± SEM and n(untreated) = 9, n(EtOH) = 11. *,P < 0.05 by unpaired t-test (P < 0.05).

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A B

C D

E F

G H

Figure 5.1 – Effects of periconceptional alcohol and high-fat diet on adult offspring weight and body composition . . . . . Body weight for male (A) and female offspring (B); % fat-free mass for male (C) and female offspring (D); % of total body fat mass for male (E) and female offspring (F); and % abdominal fat mass for male (G) and female offspring (H) exposed to PC:EtOH (black bars) and/or a high-fat diet (HFD) at 7 months compared with untreated offspring (white bars) on a control diet. n = 10-11 per group. Data were analysed with two-way ANOVAs and is represented as mean ± SEM. NS, not significant. 167

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Table 5.2 Body and organ measurements at tissue collection and during X-ray absorptiometry scan of body composition in male and female offspring aged 7-8 months

Treatment group Statistics (P values) Variable U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction Male Body weight at PM (g) 606 ± 16 607 ± 13 681 ± 22 727 ± 45 NS <0.001 NS Abdominal circumference (cm) 22.0 ± 0.5 22.4 ± 0.3 23.4 ± 0.6 25.9 ± 1.1 <0.05 <0.001 NS Ponderal index (g/(100xcm3)) 2.6 ± 0.1 2.7 ± 0.1 2.8 ± 0.1 3.0 ± 0.1 0.08 <0.01 NS Liver weight (g/gbw) 0.02 ± 0.01 0.02 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 NS NS NS Intra-abdominal fat weight (g/g bw) 0.04 ± 0.01 0.05 ± 0.01 0.06 ± 0.01 0.08 ± 0.01 0.06 <0.0001 NS Tibial length (mm) 51.1 ± 1.0 52.0 ± 1.2 50.6 ± 1.1 51.1 ± 1.2 NS NS NS BMC (%) 2.85 ± 0.05 2.93 ± 0.07 2.88 ± 0.05 2.85 ± 0.05 NS NS NS BMD (g/cm2) 0.19 ± 0.01 0.19 ± 0.01 0.19 ± 0.01 0.19 ± 0.01 NS NS NS

Female Body weight at PM (g) 315 ± 16 309 ± 14 387 ± 20 354 ± 18 NS <0.01 NS Abdominal circumference (cm) 17.3 ± 0.6 17.1 ± 0.3 19.1 ± 0.7 19.3 ± 0.4 NS <0.001 NS Ponderal index (g/(100xcm3)) 2.3 ± 0.1 2.5 ± 0.08 2.7 ± 0.07 2.7 ± 0.1 NS <0.01 NS Liver weight (g/gbw) 0.03 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 0.03 ± 0.01 NS NS NS Intra-abdominal fat weight (g/g bw) 0.05 ± 0.01 0.05 ± 0.01 0.07 ± 0.01 0.09 ± 0.01 NS <0.001 NS Tibial length (mm) 46.4 ± 1.1 43.9 ± 1.1 45.9 ± 1.2 45.7 ± 1.0 NS NS NS BMC (%) 3.42 ± 0.09 3.25 ± 0.08 3.27 ± 0.12 3.38 ± 0.08 NS NS NS BMD (g/cm2) 0.16 ± 0.01 0.17 ± 0.01 0.16 ± 0.01 0.17 ± 0.01 NS NS NS

BMC, bone mineral content; BMD, bone mineral density; C, control; DXA, dual X-ray absorptiometry; HFD, high-fat diet; NS, not statistically significant; PC:EtOH, periconceptional alcohol; U, untreated. All data were analysed with a two-way-ANOVA for each sex.Data is represented as mean ± SEM, n = 10-11 per treatment group.

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5.3.3.2 Plasma biochemistry at 8 months

Table 5.3 shows that PC:EtOH-exposed male offspring aged 8 months – regardless of postnatal diet – had increased plasma levels of triglycerides (PPC:EtOH < 0.05), HDL

(PPC:EtOH < 0.05), and cholesterol (PPC:EtOH < 0.01). HFD-fed males had lower HDL

(PHFD < 0.05, Table 5.3) and higher leptin levels (PHFD < 0.01, Figure 5.2 A) compared with control-fed males. PC:EtOH-exposed female offspring aged 8 months had higher plasma levels of LDL and cholesterol (PPC:EtOH < 0.05) as shown in table

2. PC:EtOH-exposed females also had increased fasting leptin (PPC:EtOH < 0.05,

Figure 5.2 B. Leptin (PHFD < 0.01, Figure 5.2 B) and triglycerides (PHFD < 0.01, Table 5.3) were also increased in females fed HFD whereas HDL levels were decreased

(PHFD < 0.05, Table 5.3). Adiponectin (Figure 5.2 C & D) and plasma electrolytes (data not shown) were not affected by either PC:EtOH-exposure or HFD in either sex.

A B

C D

Figure 5.2 – Effects of periconceptional alcohol and high-fat diet on plasma leptin and adiponectin Circulating levels of fasting plasma adipokines following PC:EtOH-exposure (black bars) or untreated (white bars) offspring on a control or high-fat diet (HFD) at 8 months; n = 8-10 per group. Leptin (A) and adiponectin (C) plasma levels in male offspring and leptin (B) and adiponectin (D) plasma levels in female offspring. Data were analysed with two-way ANOVAs and represented as mean ± SEM.

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Table 5.3 Fasting plasma profile of 8 months old male and female offspring

Treatment group Statistics (P values)

Variable U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction Male Triglycerides 0.9 ± 0.2 1.1 ± 0.1 0.9 ± 0.1 1.3 ± 0.1 <0.05 NS NS HDL 1.68 ± 0.12 1.81 ± 0.07 1.21 ± 0.14 1.6 ± 0.1 <0.05 <0.05 NS LDL 0.09 ± 0.03 0.10 ± 0.02 0.13 ± 0.04 0.16 ± 0.05 NS NS NS Cholesterol 1.7 ± 0.1 1.9 ± 0.1 1.5 ± 0.2 2.00 ± 0.1 <0.01 NS NS

Female Triglycerides 0.5 ± 0.1 0.6 ± 0.1 1.2 ± 0.3 1.5 ± 0.3 NS <0.05 NS HDL 1.94 ± 0.15 2.01 ± 0.14 1.53 ± 0.16 1.72 ± 0.09 NS <0.05 NS LDL 0.10 ± 0.03 0.17 ± 0.05 0.09 ± 0.02 0.19 ± 0.03 <0.05 NS NS Cholesterol 2.0 ± 0.2 2.2 ± 0.2 1.9 ± 0.2 2.4 ± 0.4 <0.05 NS NS

C, control; HDL, high density lipoprotein; HFD, high-fat diet; LDL, low density lipoprotein; NS, not significant; PC:EtOH, periconceptional alcohol; U, untreated. Data were analysed with a two-way- ANOVA for each sex. Data is represented as mean ± SEM, n = 8-12 per treatment group.

5.3.3.3 Adipose tissue gene expression

PC:EtOH significantly increased mRNA-levels of Tnf-α, IL-6, and Leptin in abdominal adipose tissue in male offspring at 8 months (PPC:EtOH < 0.01, 0.05 and 0.05, Figure 5.3 A, C & E). In females, PC:EtOH-exposure only increased mRNA-levels of Tnf-α and Leptin in abdominal abdominal tissue (PPC:EtOH < 0.05, Figure 5.3 B & E) whereas IL-6 was not different (Figure 5.3 D). The HFD had no effect on mRNA- levels of Tnf-α, IL-6 or Leptin in adipose tissue.

PC:EtOH did not affect the hepatic gene expression of Tnf-α in neither male of female offspring, however the HFD increased Tnf-α mRNA-levels in male (U:C 1.23

± 0.13; EtOH:C 1.08 ± 0.13; U:HFD 3.22 ± 0.53; EtOH:HFD 2.28 ± 0.46, PHFD < 0.001) but not female liver (data not shown). Hepatic mRNA-levels of IL-6 was unaffected by both PC:EtOH and HFD.

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A B

C D

E F

Figure 5.3 – Effects of periconceptional alcohol and high-fat diet on gene expression in visceral abdominal adipose tissue . . Relative gene expression of Tnf-α (A), IL-6 (C), and Leptin (Lep) (E) in male offspring; and Tnf-α (B), IL- 6 (D), and Lep (F) in female offspring exposed to PC:EtOH (black bars) and/or a high-fat diet (HFD) on gene expression in visceral abdominal adipose tissue at 8 months, compared with untreated (white bars) offspring on a control diet. n = 7-8 per group. Data were analysed with two-way ANOVAs and represented as mean ± SEM.

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5.3.3.4 Assessment of non-alcoholic fatty liver disease

PC:EtOH-exposure did not grossly affect hepatic morphology (Figure 5.4). Signs of macrovesicular steatosis were absent in control-fed offspring of both sexes. The HFD increased the prevalence of macrovesicular steatosis in both sexes, although male offspring were more affected than females. The macrovesicular steatosis was more likely to be located around the central vein (zone 3) in untreated males fed HFD, whereas PC:EtOH-exposed males consuming HFD had a greater percentage panacinar steatosis compared with any other treatment group. Signs of microvesicular steatosis were present in livers of both male and female offspring following both PC:EtOH and HFD, whereas this was not seen in control-fed untreated offspring. All PC:EtOH-exposed males had lobular inflammation when fed a control diet compared with only 50% of untreated (U:C) and HFD-fed (U:HFD) males. Although not all HFD-fed animals had lobular inflammation, in male offspring, the severity of this condition was worsened regardless of PC-treatment. Microgranulomas were present in all groups, however this was more frequent following PC:EtOH and/or HFD. There were no signs of hepatic fibrosis in liver sections from any treatment group.

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A B

C D

Male Female U:C EtOH:C U:HFD EtOH:HFD U:C EtOH:C U:HFD EtOH:HFD <5 % 100 100 10 0 100 100 71 86 Steatosis 5-33 % 0 0 50 60 0 0 29 0 grade >33-66 % 0 0 20 20 0 0 0 0 >66 % 0 0 20 20 0 0 0 14 Absent 100 100 10 0 100 100 71 86 Central 0 0 40 40 0 0 14.5 0 Location of Portal 0 0 10 0 0 0 0 0 steatosis Azonal 0 0 20 10 0 0 0 0 Panacinar 0 0 20 50 0 0 14.5 14 Micro- Absent 100 67 20 0 100 71 0 29 vesicular Present steatosis 0 33 80 100 0 29 100 71 Absent 50 0 30 20 14 43 14 0 Lobular Grade 1 50 100 50 60 86 43 86 100 inflammation Grade 2 0 0 20 20 0 14 0 0 Absent Micro- 50 17 30 30 57 29 43 14 granulomas Present 50 83 70 70 43 71 57 86 Stage of None 100 100 100 100 100 100 100 100 fibrosis

Figure 5.4 – Effects of periconceptional alcohol and high-fat diet on the development of hepatic steatosis Representative H&E liver histology images from male untreated (A) and PC:EtOH-exposed (B) on a control diet, and for male untreated (C) and PC:EtOH-exposed (D) on a high-fat diet (HFD) at 8 months, with quantification of non-alcoholic fatty liver disease according to the Kleiner-scoring system (panel E). Scale bars are 100 μm for inserts and 200 μm for large images, n = 8 per group.

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5.4 Discussion

Although total fat mass is strongly associated with morbidity and correlates with coronary artery disease and diabetes, visceral distribution of fat is an even stronger predictor of adverse health outcomes (Montague and O'Rahilly, 2000). This study demonstrates that alcohol, when consumed only around the time of conception, predisposes male offspring to visceral adiposity, associated with altered plasma biochemistry and increased gene expression of cytokines and leptin. PC:EtOH- exposed female offspring also had altered plasma biochemistry and increased gene expression of inflammatory markers, despite no changes in body composition. PC:EtOH offspring of both sexes were more likely to exhibit signs of microvesicular steatosis, but overall the development of NAFLD was not severely affected by PC:EtOH. Although a postnatal HFD also significantly affected both body composition, plasma chemistry, gene expression and NAFLD, it did generally not exacerbate the effects of PC:EtOH. However, the zonal distribution of hepatic steatosis was more likely to be panacinar in PC:EtOH-exposed male offspring consuming HFD compared with either one treatment, suggesting that PC:EtOH had a more deleterious effect on NAFLD progression when male offspring were submitted to a mismatch in pre- and postnatal nutrition. The phenotype displayed by male offspring following PC:EtOH was often comparable to the one seen after consuming HFD for the major part of adult life (U:HFD-group). Contradictorily, female offspring were vulnerable to a postnatal HFD, but not to PC:EtOH-exposure.

The increase in body fat seen in males at 8 months corroborates a previous study, in which ewes were periconceptionally undernourished from either 61 days before until the time of mating, from 61 days prior to mating until 30 days gestation, or from 2 days before mating to 30 days gestation. Offspring were studied at 3-4 years of age, and it was shown that males, but not females of all groups exhibited increased %FM and a tendency to decreased % lean mass, despite similar body weights (Jaquiery et al., 2012). Similarly, mice fed a low-protein diet during gestation produced offspring with increased total and %FM at 9 months, and this was exacerbated in males that were fed a hypercaloric diet from weaning. Females were not studied (Bol et al., 2009). The ability of prenatal alcohol (30% v/v in tap water) to increase visceral and subcutaneous adipose tissue in adult offspring has been demonstrated in guinea pig

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(Dobson et al., 2012), although studies in rat have not shown any effect of prenatal alcohol consumption on offspring adipose tissue (Chen and Nyomba, 2003a). Human studies have demonstrated increased % body fat in intrauterine growth restricted males (Kensara et al., 2005). An increase in body fat, despite normal BMI (or ponderal index), is referred to as ‘normal weight obesity’ and is associated with cardiometabolic dysregulation and metabolic syndrome in humans (Romero-Corral et al., 2010).

Adipocytes, were long considered as energy storage only, whereas now it is widely understood they play a role in endocrine functions. Adipose tissue secretes both hormones and inflammatory cytokines and adipokines, many of which have been implicated in the development of insulin resistance and obesity (Greenberg and Obin, 2006, Fantuzzi, 2005). TNF-α, when shown to be overexpressed in obese rodents, was the first molecular link between obesity and inflammation (Sethi and Hotamisligil, 1999, Hotamisligil et al., 1993). Since then, evidence has accumulated to suggest that inflammatory pathways – which recently have been shown to be affected in offspring following maternal perturbations (Alfaradhi et al., 2014, Pruis et al., 2014) – are critical in the mechanism underlying insulin resistance and adiposity (Weisberg et al., 2003, Uysal et al., 1997). TNF-α expression, which is increased in adiposity (Fantuzzi, 2005), increases plasma levels of TG, VLDL (Peraldi and Spiegelman, 1998) and is therefore a likely mediator to insulin resistance. Indeed, mice lacking TNF-α or its receptors exhibit improved insulin sensitivity compared with wild-type mice (Hotamisligil et al., 1993, Uysal et al., 1997). Increased levels of IL-6, which are induced by TNF-α (Kern et al., 1995), correlate with the prospect risk of developing type 2 diabetes – irrespective of amount body fat in undiagnosed subjects (Pradhan et al., 2001); and adipose gene expression of IL-6 is increased in obese and diabetic subjects compared with lean subjects (Fried et al., 1998). However, although the expression and circulating levels of cytokines correlates with obesity and diabetes (Fantuzzi, 2005), it is also established that inflammation can predict future adiposity (Engstrom et al., 2003) suggesting the early presence of inflammatory markers can also be the cause of obesity. Hence the increased levels of Tnf-α in females exposed to PC:EtOH, despite unaffected adiposity, may suggest that they are more likely to gain adipose tissue or weight compared with untreated females; a proposal that could be tested if DXA scans were repeated at a later age. 175

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Both TNF-α and IL-6 reduces adiponectin secretion from adipocytes (Rotter et al., 2003). Although high circulating adiponectin levels are associated with a relatively lower risk of type two diabetes (Spranger et al., 2003), it was not surprising that plasma levels of adiponectin were comparable between all groups in our study. Models of fetal programming often produce inconsistent results of adiponectin levels in metabolic phenotypes, and others have failed to correlate prenatal alcohol exposure with circulating adiponectin levels (Chen et al., 2004). Instead, we found plasma leptin levels to be increased in male but not female offspring on PN30, and in female but not male offspring at 8 months following PC:EtOH. Free plasma leptin generally positively correlates with adipose tissue mass (Maffei et al., 1995, Brabant et al., 2000) and therefore it is possible that PC:EtOH-exposed males had more adipose tissue on PN30 – or that they were resistant to leptin (Friedman, 2002). Without closer examination of body composition on PN30 and/or examination of the leptin receptor, we can only speculate about this. Although the mechanisms are still unclear, increased plasma leptin has previously been found in 4 months old females, but not male offspring of periconceptionally undernourished sheep (-15 days to +30 days gestation), but fat content was not assessed in this study (Debus et al., 2012). Owing to the close relationship between leptin levels and fat mass, it was expected to see increased plasma leptin levels in HDF-fed offspring – however surprisingly, adipose Leptin mRNA was only increased following PC:EtOH. The fact that we only examined gene expression in one fat depot may explain this, as this may not be representative of the level of Leptin expression across all fat cells. It is also possible that the plasma leptin levels found in the HFD-fed animals reflects the increased amount of total body fat, without affecting leptin mRNA.

In addition to regulation of insulin, increased circulating leptin levels are associated with NAFLD in children (Nobili et al., 2006), and an increased susceptibility to NAFLD following intrauterine growth restriction has recently been demonstrated (Alisi et al., 2012). The prevalence of NAFLD is, just as obesity, increasing at an alarming rate and is closely associated with obesity and insulin resistance (Alisi et al., 2012). Steatosis, or accumulation of triglycerides in hepatocytes, is considered the “first hit” in NAFLD, which increases the susceptibility to “second hits” cell injury, fibrosis and inflammation, subsequently leading to NASH (Carter-Kent et al., 2011). Histological examination is the accepted standard for diagnosis of NAFLD. Maternal 176

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obesity is known to cause NAFLD in offspring, despite no differences in body weight or adiposity (Alfaradhi et al., 2014). Shen et al (2014) demonstrated increased hepatic steatosis in female rat offspring when exposed to high doses of alcohol prenatally (E11-E20, dams reaching 87 mM (0.40% BAC)). Males were not examined in this study. The lower doses of alcohol used in this study (0.18-0.25% PAC) did not severely affect liver histology. The combination of PC:EtOH and HFD was however the more likely to, apart from steatosis around the central vein, cause a panacinar distribution of steatosis; whereas HFD alone did not induce panacinar steatosis (males only). Although we did not observe any major differences in other liver features between treatment groups, the presence of panacinar steatosis has been associated with a greater likelihood to cause ballooning injury and fibrosis, compared to when steatosis is present around the central and/or portal vein, which show no correlation with an early degree of fibrosis (Chalasani et al., 2008). We therefore suggest that the combination of PC:EtOH and a postnatal HFD has a more profound effect on the development of NAFLD.

The available literature generally focuses on recognition of the problem and lifestyle interventions, including medication, dietary modifications and exercise to improve outcomes such as obesity or ‘normal weight obesity’. However, we and others have shown that adiposity and associated disorders are just as likely a result of unfavorable periconceptional and prenatal events. It is therefore essential to spread knowledge about the consequences alcohol consumption around conception may have on the future heath of the baby to women planning a pregnancy.

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CHAPTER 6

General discussion

6.1 Thesis summary

The primary focuses of this thesis were to identify the long-term metabolic consequences of maternal periconceptional alcohol exposure; and to determine if a postnatal western diet impacted on the in utero programmed phenotype. Secondly, this thesis investigated if the adult phenotype correlated with early changes in the placenta, including biochemistry, size, and morphology. The significant findings were that male and female fetuses of dams that consumed alcohol exclusively around the time of conception were growth restricted and had a relatively larger placenta – changes that have been strongly associated with adult onset disease in many other programming models. Indeed, adult offspring in our study became insulin insensitive, experienced glucose intolerance and increased adiposity (males only). Importantly the degree of disease was often equivalent to that seen after consuming a western diet for the major part of adult life. These changes are summarized in Table 6.1. Although we suggest the long-term metabolic dysfunction to have arisen via compromised placental function, and alterations in molecular and endocrine pathways, it should be emphasized that the alcohol may have induced epigenetic changes during the preimplantation development. It was beyond the scope of this thesis to investigate such changes but some primarily results including changes in DNMTs indicate the importance of pursuing this idea in future studies. This chapter summarizes the findings and conclusions drawn from the studies in this thesis and puts them into a broader context in view of the general literature.

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Table 6.1 Summary of the major findings in fetuses and adult offspring following periconceptional alcohol exposure and a postnatal western diet Male Female Area of Measure PEtOH PWD PEtOH+WD PEtOH PWD PEtOH+WD investigation Litter size ↔ ↔

Fetal Body weight ↓ ↓ Body length ↓ ↓ Placenta:bw-ratio ↑ ↑ Weight and dimensions

Placenta wet weight ↔ L, S ↔ L, S

Placenta dry weight ↔L ↑S ↔L ↑S Depth ↔ ↔ Width ↑ ↑ Length ↑ ↑ Cross-sectional area Glycogen cells ↑ ↑ Labyrinth zone ↓ ↓ Spongio zone ↑ ↑ Gene and protein expression

11βHsd2 ↑L ↑L

Igf1 ↓L ↔S ↓L ↔S

Igf2 ↔L ↑S ↔L ↑S Placental Igf2R ↔L ↔L

IGF1R *↓L *↔L

Glut1 ↔L ↑S ↔L ↑S

Glut3 ↔L ↓S ↑L ↑S

Slc38a1 ↔L ↔L

Slc38a2 ↓L ↓L

Slc38a4 ↔L ↔L

Vegfa ↑L ↑L

Kdr ↔L ↔L

Pgf ↔L ↔L

Flt1 ↔L ↔L

Gys1 ↔S ↔S

Gsk3β ↔S ↑S

Gjb3 ↔S ↔S Demethyltransferases (mRNA) Dnmt1 ↑ ↑ Hepatic Dnmt3a ↑ ↑ Dnmt3b ↑ ↑ *, compared to the same sex only; L, placental labyrinth zone; S, placental spongiotrophoblast zone.

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Table 6.1 Summary of the major findings in fetuses and adult offspring following periconceptional ethanol exposure and a postnatal western diet (cont.) Male Female Area of Measure PEtOH PWD PEtOH+WD PEtOH PWD PEtOH+WD investigation Glucose and insulin tolerance tests (6 months) Fasting glucose ↑ ↑ ↔ ↑ ↔ ↔ Fasting insulin ↔ ↑ ↑ ↔ ↑ ↔ HOMA-IR ↑ ↑ ↑ ↑ ↑ ↔ QUICKI ↓ ↓ ↔ ↓ ↓ ↔ Glucose intolerance (AUGC) ↑ ↔ ↔ ↑ ↑ ↔ (AUIC) Endogenous insulin ↑ ↔ ↔ ↑ ↑ ↔ insensitivity (AUIC) first-phase ↑ ↑ ↑ ↑ ↑ ↔ Glucose and (AUIC) second-phase ↑ ↔ ↔ ↑ ↑ ↔ insulin (AUGC) Exogenous insulin ↑ ↔ ↔ ↑ ↑ ↔ homeostasis insensitivity Hepatic gluconeogenesis (mRNA) G6pase ↑ ↔ ↔ ↑ ↔ ↔ Pepck ↑ ↔ ↔ ↑ ↓ ↓ Pcg-1α ↑ ↔ ↔ ↑ ↔ ↔ Gk ↓ ↑ ↑ ↓ ↔ ↔ AKT2 signaling (protein expression) *tAKT2 ↑A ↔M ↔A↑M *pAKT2Thr/tAKT2 ↑A↔M ↓A↔M *pAKT2Ser/tAKT2 ↔A↔M ↓A↔M Body composition (7 months) % fat free mass ↓ ↓ ↔ ↔ ↓ ↔ % fat mass ↑ ↑ ↔ ↔ ↑ ↔ Abdominal circumference ↑ ↑ ↔ ↔ ↑ ↔ Plasma profile Triglycerides ↑ ↔ ↔ ↔ ↑ ↔ Total cholesterol ↑ ↔ ↔ ↑ ↔ ↔ LDL ↔ ↔ ↔ ↑ ↔ ↔ Obesity HDL ↑ ↓ ↔ ↔ ↓ ↔ Leptin ↔ ↑ ↔ ↑ ↑ ↔ Adiponectin ↔ ↔ ↔ ↔ ↔ ↔ Inflammation and other mRNA expression

Tnf-α (visceral adipose) ↑ ↔ ↔ ↑ ↔ ↔ IL-6 (visceral adipose) ↑ ↔ ↔ ↑ ↔ ↔ Leptin ↑ ↔ ↔ ↑ ↔ ↔ Tnf-α (hepatic) ↔ ↑ ↑ ↔ ↔ ↔ IL-6 (hepatic) ↔ ↔ ↔ ↔ ↔ ↔

*, compared to the same sex only; A, adipose tissue; M, skeletal muscle. Differences between sex are not shown in this table.

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6.2 Relevance of animal model, dietary Intervention and study design

The rat is a good animal model to study the effects of the early maternal environment

We sought to mimic maternal alcohol consumption around the time of conception (prior to embryonic implantation) using a rat model. As demonstrated in Figure 6.1, the preimplantation development more or less overlaps in rat and human until E4 – hence the rat is a suitable species to study impacts from the early in utero environment.

Fertilization 1-cell 2-cell Early blastocyst Implantation 0 1 2 3 4 5 6 7 8 9 10 Fertilization 1-cell 2-cell Early blastocyst Implantation

Human preimplantation development

Rat preimplantation development

Figure 6.1 – A comparison between the human and rat preimplantation development . . Rat (blue) and human (pink) embryonic development overlaps from fertilization until early blastocyst stage. The rat embryo implants between E5-E7 whereas the human embryo implants between E7- E10.

Importantly, our model does not aim to differentiate between pre-conception and preimplantation effects, but covers the periconceptional period as a whole. Others have demonstrated the significance of both periods in programming of adult disease (Watkins et al., 2010, Watkins et al., 2011, Watkins et al., 2008), demonstrating that the underlying mechanisms may vary as such the pre-conception period is more likely to affect the developing follicle in the ovary, whereas the post-conception period has a greater effect on the uterus and is likely to induce epigenetic changes in the blastocyst. In order to identify such differences in our study, future studies should compare the two periods separately by administering alcohol either exclusively 181

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during oocyte maturation (4 days prior to until conception) and exclusively during preimplantation development (until 4 days post conception).

Administration of alcohol via a liquid diet is the best available method to study alcohol in animal models

To study the effects of early alcohol consumption, Sprague-Dawley rats were offered an EtOH containing (12% v/v, ~22E%) nutritionally complete Sustagen based liquid diet. Untreated dams were given a similar diet in which the ingredients had been modified to give an equal amount of calories and similar E% of micro- and macronutrients. As a part of this thesis, I comprehensively developed this diet based on dietary data collected by others from a smaller pilot study of PC:EtOH-exposure in the Moritz’s lab. In the pilot study, control and EtOH-exposed dams consumed different volumes of the liquid diet (thereby receiving diets with different nutritional composition). Using this data, I was able to calculate how much of each ingredient that was needed to create a similar nutrient and caloric intake in both treatment groups. The procedure was however complicated by the fact that each modification made to the ingredients changed the viscosity and palatability of the diets, and therefore also the amount the dams consumed. Eventually, during a series of preliminary dietary experiments, I managed to produce an EtOH-diet, which compared to the control diet was less palatable (dams drank a smaller volume) but had higher energy density and a different ingredient composition (dams received the same amount of micro- and macronutrients) on average. Naturally, the dams did not drink an identical amount of diet (and therefore absolute EtOH); however this reflects the real life situation better as also women drink variable amounts.

We choose to administer the alcohol via a liquid diet in order to limit confounding factors, and to secure the intake of vitamins and minerals. The alternatives would have been to give EtOH via drinking water (which rats have a natural aversion to); via gavage (which causes a lot of unnecessary stress); or intravenously via a pump (which apart from causing stress is unnatural as the EtOH skips the gastrointestinal system and goes straight out in the blood). In addition, when EtOH is given via drinking water or gavage, the EtOH-derived calories could create a surplus of calories (when added in addition to a normal diet) and compromise the results as they could arise from either EtOH, or overfeeding. The above models could also

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reduce the daily calorie intake as a result of imposed stress or aversion, creating a similar problem. As we wanted to examine the effects of EtOH in vivo, without substituting other nutrients or calories, the liquid diet was the best available choice, and has previously been compared with a pair-fed control group (Lieber and DeCarli, 1982).

Our model created high – but realistic plasma alcohol levels

The dams in our study reached PACs of 0.18 ± 0.04% 2 days before mating and 0.25 ± 0.04% 2 days after (30 minutes after offering the diet). These levels of alcohol may be considered as fairly high but are only marginally higher than levels found in occasional alcohol users who undergo a drinking “binge” (Touquet et al., 2008). Rats also metabolize alcohol much faster than humans (Zorzano and Herrera, 1990) and indeed, the PAC in the dams in our model quickly declined and measured only 0.07 ± 0.02% 3 hours after; and 0.05 ± 0.02% 5 hours after diet administration. Furthermore, the E% alcohol derived calories (22E%) are quite similar to other alcohol studies in rat, ranging between 13-25E% (Chen and Nyomba, 2003a, Lopez-

Tejero et al., 1989, Probyn et al., 2012).

6.3 Fetal weight and offspring growth

PC:EtOH-exposure affected fetal weight but did not impact on offspring growth

Chapter 3 demonstrated both male and female fetuses were growth restricted on E20 (8 and 9% lighter than their sex controls respectively), but were of similar weights to untreated offspring already at PN1. PC:EtOH-exposed female offspring tended to weigh less compared with untreated controls at weaning (P = 0.06) but thereafter, PC:EtOH had no effect on weight gain (Table 4.1). This is similar to a previous study by the Moritz’s lab in which dams were exposed to a low-moderate dose of alcohol (6% v/v) throughout pregnancy. In this study, EtOH-exposed females were 3% lighter and males 8% lighter compared with controls on E20, but the weight difference was no longer seen on PN1 (Probyn et al., 2012). This could either reflect a quick catch-up growth between E20 and PN1; or be due to subtle differences between different study cohorts. Interestingly, although offspring weight up until 8 months were unaffected by PC:EtOH, PC:EtOH-exposed male offspring displayed increased abdominal circumference and increased weight of intra-abdominal fat

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pads (Chapter 5), suggesting that PC:EtOH affected body composition in males. This is highly relevant as an abdominal distribution of fat is more harmful than for example total fat mass or absolute body weight (discussed in section 6.5). In contrast to our results, the low-moderate alcohol slowed growth in male offspring between 7-12 month of age (Probyn et al., 2012) but did not affect body composition (Probyn et al., 2013c). These dissimilar results are likely to recede in differences in the exposure periods and dosages used. As expected, WD-fed offspring weight more than control- fed offspring at all times.

6.4 The effects of periconceptional ethanol exposure on the placenta

PC:EtOH-exposure affected placental weight and morphology

Over the past decade, there has been a lot of attention on the placenta in developmental programming, as it shows strong correlations with adult disease. In this thesis, I examined the placenta to gain insight into the potential mechanisms which may have contributed to the programming of adult onset metabolic dysfunction. PC:EtOH-exposed male and female fetuses had a relatively larger placenta (specifically the spongiotrophoblast layer and glycogen cells) on E20 compared with untreated controls. This finding is consistent with more recent data from others (O'Connell et al., 2013b), and from the Moritz’s lab, in which changes in glycogen cells have been identified following maternal hypoxia, glucocorticoids, and magnesium deficiency (unpublished data), suggesting that changes in glycogen cell content in the placenta may be indicative of fetal programming. Although the role of glycogen cells in placental development are still largely unknown, ALDH1A3 has recently been identified as a marker of glycogen trophoblast cells in the placenta in vitro (Outhwaite et al., 2014). ALDH1A3 is apart from detoxification of aldehydes in alcohol metabolism involved in oxidation of retinal to retinoic acid (Muzio et al., 2012) – which is essential for fetal and placental development (Kastner et al., 1995). As the early ectoplacental cone and later glycogen cells express Aldh1a3, it is possible that they can regulate early differentiation of junctional zone cell types, and provide the fetus with retinoic acid during development (Outhwaite et al., 2014). It is therefore tempting to speculate that increased glycogen cells in the placenta may serve as a protective mechanism by securing sufficient retinoic acid (and/or to protect the fetus from glucose toxicity as discussed in Chapter 3) during development. It would be

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informative to elucidate retinoic acid signaling further in developmental programming models demonstrating altered placental glycogen content.

PC:EtOH-exposure impaired the placental glucocorticoid barrier

Another key finding in the placenta was the 2-fold increase in mRNA-levels of 11βHsd2 in placentas from PC:EtOH-exposed fetsuses – something that also was demonstrated in a mouse model of endogenous glucocorticoid infusion (E14.5) by other members of Moritz’s lab (Cuffe et al., 2012). Alcohol is known to increase maternal levels of glucocorticoids (Liang et al., 2011, Weinberg et al., 2008) and have previously been shown to decrease placental mRNA levels of 11βHsd2 in mice (Liang et al., 2011). While contradictory to our findings, the mRNAs in the study of Liang et al (2011) were analysed in animals receiving very high doses of alcohol administration (40% EtOH v/v). The increased 11βHsd2 levels in our model were observed after the exposure period, and may therefore, as speculated in Chapter 3 be an attempt to increase the placental barrier to protect the developing fetus. To confirm this, 11βHSD2 protein levels and maternal and fetal plasma levels of glucocorticoids would have to be measured. An earlier examination of the placenta (eg E10-15) may also provide insight. Some preliminary results from our lab do suggest that 11βHSD2 levels are reduced in the labyrinth zone of the (female) placenta on E20, where they were only 32% (P = 0.0013) of those in placenta from untreated females. While this would strengthen the argument, these analyses need to be repeated with a higher n-number and validated with better antibodies.

6.5 Long-term consequences of periconceptional alcohol exposure and a western diet

An abundance of studies have demonstrated that alcohol has the potential to affect different organs and organ systems in the body. Due to alcohols well known teratogenic effects, the brain has been extensively investigated, both in humans and animals (Jones et al., 1973, Clarren et al., 1978, Abel and Dintcheff, 1978, Maier and West, 2001). Over time however, evidence have accumulated to also suggest a strong correlation between prenatal alcohol and future risk for metabolic disorders. In agreement with the studies in this thesis, many other animal studies have demonstrated glucose intolerance and/or insulin insensitivity (Villarroya and Mampel,

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1985, Elton et al., 2002, Chen and Nyomba, 2003b, Chen and Nyomba, 2003a, Chen and Nyomba, 2004, Chen et al., 2004, Yao et al., 2006, Yao et al., 2013, Probyn et al., 2013c); and a few have demonstrated increased adiposity (Dobson et al., 2012) in offspring following prenatal alcohol exposure (see Table 1.2 for further details). Our lab has previously contributed to the body of evidence suggesting that prenatal alcohol affects other organ systems, both when administered in a binge-like pattern; and when kept low-moderate throughout gestation. Primarily, these models have shown that alcohol decreases nephron endowment and consequently increases blood pressure in the offspring following binge (Gray et al., 2010). Our low- moderate model (6% EtOH v/v) showed that prenatal alcohol at these levels altered protein composition in the breast milk without affecting the mammary gland (Probyn et al., 2013b). Additionally, offspring exposed to a low-moderate dose of alcohol prenatally developed pulmonary fibrosis over time (8-19 months old males), which would compromise respiratory lung capacity (Probyn et al., 2013a); exhibited left ventricular hypertrophy and fibrosis associated with decreased maximal aortic flow velocity (8 months) (Nguyen et al., 2014); and induced anxiety-like behaviour via structural changes in the basolateral amygdala (8 and 15 months) (Cullen et al., 2013).

Hence similar to our other alcohol models, the findings from this thesis should be seen as a part of a much larger picture. We are currently investigating the effects of PC:EtOH-exposure on cardiovascular and renal health, as well as the brain and behaviour. Many of the studies are ongoing but unpublished results suggest that also PC:EtOH-exposure compromise nephron number (PN30) and impair renal function. Adult PC:EtOH-exposed females (12 months) exhibit increased left ventricular internal diameter during systole and decreased cardiac output without any apparent blood pressure changes. This suggests that alcohol, also when periconceptionally administered has the potential to impair kidney development and influence renal and cardiovascular functions in adulthood. Other preliminary results indicate that PC:EtOH-exposed offspring may be neophobic, and the brain and other behavioural outcomes is currently under investigation.

Bearing in mind potential changes in multiple organs and systems, it is difficult to elucidate which condition appears first as all the aforementioned diseases can be

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programmed in utero; be epigenetically modified; and also affect the development of one another. Explicably, the development of diabetes and obesity as researched in this thesis is complexly intertwined with each other, as well as other metabolic outcomes. Obesity for example, is a major risk factor for both type 2 diabetes and CVD (Kopelman, 2007). In the same way, diabetes is a risk factor for obesity. The connection between the two is insulin resistance, and insulin resistance is characterized by chronic inflammation (Yu et al., 2002). To bring yet another dimension into consideration, interactions with the postnatal environment, in this case a WD (known to contribute to diabetes, obesity and CVD by itself) also causes inflammation (Manzel et al., 2014). The outcomes in Chapter 4 and Chapter 5 of this thesis are therefore strongly related not only to each other, but to other outcomes in this model. These interactions are summarized in Figure 6.2.

Cleary, this figure is quite simplistic and only indicates associations between different parameters without explaining the mechanisms (which are discussed in section 1.7.2.2.1). It should also be noted that some aspects of the disease picture are missing, limiting the conclusions we can draw from this data. For example, it would have been informative to histologically determine the size and number of adipocytes in adipose tissue in relation to closer examination of fat metabolism. In addition, data of the weight of subcutaneous fat pads would have been extremely valuable as it perhaps would explain some of the sex difference regarding the degree of insulin insensitivity, inflammation and hepatic steatosis. Obesity could be seen as a healthy response to high blood sugar (which is toxic). Storing glucose as fat in adipose tissue therefore protects other organs against glucose toxicity. Importantly, the capacity of subcutaneous fat to convert glucose to fat is larger compared with visceral fat (mainly because of the larger size and wider distribution); and visceral fat – apart from providing a smaller storage depot – also produce more pro- inflammatory cytokines (Hamdy et al., 2006, van Harmelen et al., 2002); and are more susceptible to rupture which in turn causes inflammation (and therefore contributes to insulin resistance) (Monteiro and Azevedo, 2010).

Chapter 4 provides a solid explanation to the insulin insensitivity seen in female offspring exposed to PC:EtOH. However, the same explanation did not apply to PC:EtOH-exposed male offspring, leaving room for speculation. It was clear that

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insulin insensitivity did not arise from the same mechanism in both sexes. Perhaps in females it arose from dysfunctions in peripheral insulin signaling; but in males, the increase in visceral adiposity (that was not seen in females) (see Chapter 5) was a major cause of insulin insensitivity (i.e obesity preceded insulin insensitivity in males). This may also explain the faster progress of hepatic steatosis in males. When the adipocytes are unable to store more fat, other organs (in this case the liver) are likely to be affected. Because females generally have more subcutaneous fat and males more visceral fat (Hamdy et al., 2006), females are more ‘protected’ from metabolic outcomes caused by obesity. It is tempting to speculate that perhaps PC:EtOH-exposed female offspring could in a compensatory mechanism distribute more fat subcutaneously and thereby protect themselves, or at least postpone the development of steatosis. Although the percentage of total fat mass in females exposed to PC:EtOH speaks against this, it should be highlighted that: 1) the DXA scan did not consider the distribution of fat pads (other than an indication of abdominal fat); and 2) the argument still holds up for WD-fed females which despite of being fat (including more viscerally distributed fat) had milder signs of steatosis compared with WD-fed males. It is however important to remember that the lack of obesity in PC:EtOH-exposed females is no indication these animals are metabolically healthy, they still have increased levels of cholesterol, LDL and leptin in plasma. It should be noted however that the dissimilarities between rat and human lipid metabolism do complicate the comparison between rat and human lipid disorders. Therefore the altered plasma lipid profile in the PC:EtOH-exposed rats can only be compared with the plasma lipid profile of the untreated control rats – and not with humans. Additionally, we can not rule out the possibility of female offspring developing/exhibiting a stronger phenotype later in life (beyond this experimental protocol) as signs of metabolic syndrome and obesity tend to appear later in females, and because females live longer than males. Another important aspect to consider is the influence of the WD on the long-term disease picture. We introduced this ‘second hit’ when the offspring were 3 months old (corresponding to young people moving out of home) to mimic a realistic scenario during which many people change and establish their adult lifestyle. It is possible that introducing the WD earlier, perhaps after weaning as made by a number of other studies, may have influenced the severity and the type of the outcomes.

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Postnatal WD restriction Fetal growth growth Fetal Inflammation TNFa IL-6 Epigenetics

Obesity Diabetes CVD Uteroplacental Periconceptional alcohol Periconceptional Adiponectin Leptin Brain Adipokines

Figure 6.2 – A simplistic presentation of the relationship between periconceptional alcohol and its early and long- term metabolic consequences. . Solid (black) arrows indicate a relationship/association that we have demonstrated within this model. Dashed arrows indicate that there is a relationship between the two parameters that has been shown in other models. It does not Maternal stress Maternal indicate in which order parameters arise.

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6.6 Proposed mechanism – epigenetic modifications and initial development

Having established a significant metabolic phenotype following PC:EtOH, it is important to consider the underlying mechanisms. The metabolic consequences in offspring exposed to alcohol periconceptionally are likely to arise from multifactorial mechanisms. The contribution of the placenta and our proposed ‘stress hypothesis’ has already been discussed in section 6.4. The primary research question of this thesis was to establish if PC:EtOH-exposure increases the susceptibility of adult metabolic disease; rather than elucidating how it occurred. Chapter 3 started to investigate the placenta’s role in programming of disease, and chapter 4 & 5 sought to explain the phenotype by examining programmed alterations in molecular pathways (gluconeogenesis, peripheral insulin signaling, and inflammation). Importantly, some initial investigation on the gene expression of Dnmt’s and Hdac’s, special targets for these genes (PGC-1α), and imprinted genes (Igf1) have provided us with some plausible indications of other underlying mechanisms that should be further addressed in future studies. Some of these are discussed in the following sections.

Direct effects of alcohol via epigenetic regulation

It is unlikely that alcohol directly impacted on organ development as it was administered prior to organogenesis; and teratogenic effects of alcohol consumption are generally only seen following excess alcohol consumption throughout gestation. The metabolites from alcohol can however influence on one-carbon metabolism and the methyl donor pathway, and thereby serve as a mediator of epigenetic modifications (El Hajj et al., 2014). For example, EtOH selectively acetylates histone H3 at lysine residue 9 (H3Ack9) (via an alcohol metabolism dependent process) in both cultured rat hepatocytes (Martus et al., 2005) and in vivo (Powles et al., 2013, Muzio et al., 2012). As a consequence, Adh1 gene expression increases (Martus et al., 2005); EtOH metabolism increases, and this in turn intensifies this cycle (Yan et al., 2014). Although maternal livers were not collected during the exposure period, unpublished data from our lab demonstrate such increase by which dams consuming EtOH had a ~40% increase in hepatic Adh1 gene expression on E20 compared with untreated dams (P < 0.05). This suggests that if Adh1 was increased as a consequence of increased H3 acetylation, the hepatic metabolism of EtOH may have

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contributed to epigenetic responses in the dams in our study. This would need to be confirmed by chromatin immunoprecipitation assays as well as measurements of H3 acetylation activity in maternal liver, preferably both on E20, and simultaneously with the exposure period.

Epigenetic modifications of the placenta

The first indication of epigenetic programming following PC:EtOH-exposure in fetal tissue was decreased gene expression of the methionine transporter Slc38a2 in the labyrinth zone of the late gestation placenta (Chapter 3). We speculated that PC:EtOH-exposed fetuses may have an aberrant methionine system, which in turn would influence on one-carbon metabolism, as methionine provides methyl groups for S-adenosyl methionine (SAM) production. Interestingly, SAM is a substrate for DNMTs (Kovacheva et al., 2007), and global DNA methylation is often increased in response to methionine (or choline), and associated with hypomethylation of the Dnmt1 promotor (Kovacheva et al., 2007). Intragrastric EtOH feeding in rat has been shown to cause hepatic methionine deficiency, reduced SAM activity and reduced DNA methylation (Outhwaite et al., 2014); and also we were able to link the reduced Slc38a2 expression to increased gene expression of hepatic Dnmts in the fetuses in Chapter 4. That PC:EtOH-exposure could induce epigenetic modifications is also supported by the fact that oxidative stress – a known consequence of alcohol consumption (Agudelo et al., 2011) – also alters DNA methylation (Lertratanangkoon et al., 1997). Our findings so far are only sufficient for speculations; however they opened up for new questions and ideas that are currently being investigated in this model: 1) if the adult phenotype is partly a result of early epigenetic dysregulation, how does EtOH affect the preimplantation embryo, early trophoblast stem cell differentiation, and the allocation of placental linages? (discussed in the following sections); and 2) if one-carbon metabolism is affected, could the phenotype be reversed by an intervention of a methyl donor such as folate or choline administration? (discussed in section 6.7).

Direct effects of periconceptional alcohol on the developing embryo

As discussed in section 1.3.1.1, the preimplantation embryo is highly responsive to its surrounding environment because of the rapid development it is undergoing,

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which includes a genome-wide demethylation, zygotic genome activation, and morphologic and metabolic differentiation (Fleming et al., 2004). These events all occurs during alcohol administration in our PC:EtOH model, and therefore it is plausible that both the uterus and the early blastocyst development are affected. We have recently started to examine how PC:EtOH affects the maternal uterine environment by isolating endometrial stromal cells from untreated and PC:EtOH- exposed dams on E5. Following culture (in conditions inducing decidualization), we found that two key markers of decidualization, insulin like growth factor binding protein 1 (Igfbp1) and prolactin (Prl) were considerable reduced, being expressed at only ~5% and ~25% respectively compared with control levels (P < 0.05). This suggest that PC:EtOH directly affects the uterus and perhaps impacts on the ability of stromal cells to decidualize. Furthermore, we have preliminary results demonstrating that alcohol directly impacts on the trophoblast cells in vitro by reducing gene expression of Prl7b1, Prl7a2, and syncytin a (Syna) (P < 0.05) (trophoblast subtype-specific markers), suggesting EtOH could cause a delay in TS differentiation or alter cell allocation to specific lineages. Clearly, we have strong indications that EtOH has the ability to induce changes in both the uterine environment and the early blastocyst. This part of the study is under extensive investigation and we are planning to conduct embryo transfer studies to further determine the relative role of the maternal environment and the blastocyst, as faults in this early development are likely to contribute to the placental and fetal organ deficits observed from E20 and onwards. Data supporting this comes from human studies, demonstrating that children born following in vitro fertilization have higher blood pressure and fasting blood glucose levels (Ceelen et al., 2008).

6.7 Limitations and future directions

The studies in this thesis have provided novel, valuable insights regarding the consequences of periconceptional maternal alcohol consumption, but have also raised many new questions which remain to be answered. Some of these questions and ideas have already been covered previously whereas some others are discussed in the following paragraphs.

Firstly, this study was set up to cover the periconceptional period in full. Therefore, it is difficult to recognize what day/process during this window that is the most critical

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to in utero perturbations, as the consequences may have arisen from alcohol’s effect on the maternal ovaries and/or alcohol’s effect on the uterus/preimplantation environment. Hence future studies should consider separating the pre- versus post conception period. Additionally, one should attempt to measure the concentration of alcohol and the composition of nutrients in the uterine fluid to confirm a direct effect of alcohol on preimplantation development, something that we did not have the technical capability of doing during the course of this thesis. It is possible, as suggested section 6.6, that alcohol (and/or secondary factors) may have compromised the embryonic development directly and/or indirectly (epigenetic modifications) which may contribute to the adult phenotype. Apart from the ongoing studies determining EtOH’s effect on blastocyst development, it would be informative to separate embryos by sex to elucidate if later sex differences could origin already in embryonic development.

Choline as an intervention to reverse the effects from periconceptional alcohol

The primary research question in this thesis was to establish if periconceptional alcohol consumption impacts on the future disease picture, which my studies have clearly demonstrated. Naturally, the next question would be to establish if these diseases are reversible or preventable. Our current hypothesis that choline supplementation may reverse the phenotypes programmed by PC:EtOH arose from several observations from this thesis.

The pregnant woman has an increased demand of choline; however alcohol is known to reduce plasma choline. Some preliminary data from our lab have confirmed this for our model, demonstrated that maternal choline levels on E5 are ~50% reduced (P < 0.05). In addition, a human study demonstrated that choline supplementation during the third trimester of pregnancy decreased cortisol by 33% (Jiang et al., 2012), which would be an attractive outcome in our model considering the clear indications of maternal stress (see section 6.4). Additionally, choline deficiency has been demonstrated to induce alterations in the fetal epigenetic marks (Waterland et al., 2008, Jiang et al., 2012), and affect the function and vascularization in cultured placental trophoblast cells from human (Jiang et al., 2014). Again, considering the changes in placental Slc38a2 (and thereby possibly one-carbon metabolism); changes in Dnmts; the lower maternal choline levels on E5; 193

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and the indications that EtOH may delay TS differentiation and/or alter cell allocation to specific lineages in the embryo, supplementing with choline is an attractive intervention which could potentially reverse the adult metabolic phenotype.

Paternal periconceptional alcohol consumption

Finally, this project has only investigated the effects of maternal periconceptional alcohol consumption, although the scenario which this model aims to mimic is likely to include paternal drinking as well. Of interest would be to compare the effects of maternal vs. paternal periconceptional alcohol exposure individually as well as examining the combined outcome. Alcohol is known to impact on both sperm mobility and morphology (Langley-Evans and McMullen, 2010), and paternal alcohol consumption in mouse (5.92 g EtOH per kg body weight for 5 weeks by gavage) generated offspring with a compromised growth post weaning, associated with reduced DNA methylation at the H19 paternally imprinted control region (Knezovich and Ramsay, 2012). Paternal drinking has also been associated with congenital malformations, low birth weight and neonatal mortality (Friedler, 1996, Passaro et al., 1998) but metabolic effects in the offspring following paternal periconceptional alcohol consumption remain to be explored.

194

Chapter 6 General Discussion

6.8 Conclusion and clinical implications

Overall, my PhD studies have developed and optimized a rat model of PC:EtOH- exposure and used this to demonstrate that PC:EtOH causes fetal growth restriction and impacts on the late gestation placenta. In addition, I have shown that these early effects of PC:EtOH are associated with an adult diseased phenotype, including glucose intolerance, insulin insensitivity, adiposity and hepatic steatosis. These findings are of particular significance because they are the first to show that maternal drinking; limited to the time of conception can induce long-lasting metabolic outcomes in the offspring – often similar to those seen after consuming a western diet for major part of adult life. Hence this supports an underlying genetic factor to obesity and insulin resistance. Given the high number of women consuming alcohol during pregnancy planning, and the rapid rise in metabolic type disorders, it is plausible that alcohol is a contributing factor to this. It is therefore crucial to increase knowledge and awareness regarding the potential harm alcohol – when consumed around the time of conception – has on the health of the future baby.

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Placenta 35 (2014) 50e57

Contents lists available at ScienceDirect

Placenta

journal homepage: www.elsevier.com/locate/placenta

Periconceptional alcohol consumption causes fetal growth restriction and increases glycogen accumulation in the late gestation rat placenta

E.M. Gårdebjer a, J.S.M. Cuffe a, M. Pantaleon a, M.E. Wlodek b, K.M. Moritz a,* a School of Biomedical Sciences, The University of Queensland, St Lucia, Queensland 4072, Australia b The Department of Physiology, The University of Melbourne, Parkville, Victoria 3010, Australia article info abstract

Article history: Introduction: Alcohol consumption is a common social practice among women of childbearing age. With Accepted 18 October 2013 50% of pregnancies being unplanned, many embryos are exposed to alcohol prior to pregnancy recognition and formation of the placenta. The effects of periconceptional (PC) alcohol exposure on the Keywords: placenta are unknown. Periconceptional Methods: Sprague-Dawley rats were exposed to alcohol (12.5% v/v ad libitum) from 4 days prior to 4 days Preimplantation after conception and effects on placental growth, morphology and gene/protein expression examined at Ethanol embryonic day (E) 20. Placenta Results: Glycogen PC ethanol (EtOH)-exposed fetuses were growth restricted and their placental/body weight ratio and placental cross-sectional area were increased. This was associated with an increase in cross-sectional area of the junctional zone and glycogen cells, especially in PC EtOH-exposed placentas from female fetuses. Junctional Glut1 and Igf2 mRNA levels were increased. Labyrinth Igf1 mRNA levels were decreased in placentas from both sexes, but protein IGF1R levels were decreased in placentas from male fetuses only. Labyrinth mRNA levels of Slc38a2 were decreased and Vegfa were increased in placentas following PC EtOH-exposure but only placentas from female fetuses exhibited increased Kdr expression. Augmented expression of the protective enzyme 11bHsd2 was found in PC EtOH-exposed labyrinth. Discussion: These observations are consistent with a stress response, apparent well beyond the period of EtOH-exposure and demonstrate that PC EtOH alters placental development in a sex speciﬁc manner. Conclusion: Public awareness should be increased to educate women about how excessive drinking even before falling pregnant may impact on placental development and fetal health. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction particular interest, as many women consume alcohol prior to pregnancy recognition [7,8] and both gestational [9] and PC [10] It is increasingly accepted that intrauterine growth restriction is EtOH exposure is known to impair placentation by inhibition of associated with chronic adult diseases that in many cases can be vascular transformation and by reducing invasive trophoblastic traced back to the quality of nutrition and health of the mother cells [11]. during pregnancy [1]. A critical issue is the relative vulnerability of Developmental programming events are often sexually dimor- different stages of development to environmental insult and phic but the mechanisms involved are poorly understood [12]. The therefore potential developmental programming changes. placenta which is the major determinant of intrauterine growth Increasing evidence suggests that these programming events may [13] may be a key in mediating tissue responses to a dynamic be determined prior to implantation [2]. Indeed, the period sur- maternal environment as it forms the interface between the rounding conception, or the periconceptional (PC) period, has been maternal and fetal circulation. Sex differences in how the placenta identiﬁed as a critical window of vulnerability for the embryo in responds to the same maternal milieu may contribute to the altered both in vitro and in vivo studies from several species [3,4]. Whilst susceptibility of male and female fetuses to long-term program- previous studies have examined the impact of nutrition during the ming outcomes observed in other animal models [14e17]. PC period on development [5,6], little is known about the impact of This study examined the impact of moderate alcohol exposure maternal alcohol consumption during this period. This is of during the PC period in the rat. This time point was selected as it is during this period that the initiation of placental formation occurs * Corresponding author. Tel.: 61 7 33654598; fax: 61 7 33651299. and insults that occur at this time may have long lasting effects on þ þ E-mail address: [email protected] (K.M. Moritz). later stage placental morphology and function. This study also

0143-4004/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.placenta.2013.10.008 E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57 51 sought to establish whether changes in placental morphology and 2.6. Plasma analyses function were dependent upon fetal sex. Maternal and fetal plasma electrolytes were analyzed with a Cobas Integra 400 Chemistry Analyzer (Block Scientific, NY, USA). Osmolality was determined using a 2. Materials and methods Vapor Pressure Osmometer (5520 WESCOR, Helena Laboratories, Australia). 2.1. Ethics 2.7. Statistical analyses All animal experiments and procedures were approved by The University of All results are presented as mean SEM. Fetal body and placenta weights were Queensland Anatomical Bioscience Animal Ethics Committee (AEC approval number Æ calculated as litter averages by sex. qPCR data represent 7e11 fetuses of each sex, SBS/022/12/NHMRC) prior to commencement of this study. collected from different litters. Statistical analyses were conducted with GraphPad Prism 5 software (GraphPad Software, CA, USA). Maternal measurements during 2.2. Animal treatment pregnancy were analysed with a repeated measures ANOVA or with an unpaired Outbred, nulliparous female Sprague Dawley rats were housed individually and student’s t test. All fetal/placental data were analyzed with a two-way ANOVA for kept under standard housing conditions, with controlled temperature, humidity and an treatment (Ptrt) and sex (Psex) using Bonferroni’s post hoc testing as appropriate. artificial 12 h lightedark cycle. Vaginal impedance was measured with an EC40 estrous cycle monitor (Fine Science Tools, CA, USA). When the impedance was 4.5 103 U or Â 3. Results above, indicating estrous, dams were randomly allocated either a control liquid diet (n 10) or a liquid diet containing 12.5% EtOH (v/v) (w25% EtOH derived calories) ¼ (n 11) on which they remained on during the PC period (from 4 days prior to 3.1. Maternal parameters and plasma alcohol levels ¼ conception until 4 days after). The energy content of the EtOH diet was modified to give equal energy percentages of protein, fat and calories compared to the control diet. The There was no difference in maternal caloric intake or weight dams had ad libitum access to the liquid diet 21 h daily, with water offered during the gain at any time during gestation, but EtOH-exposed dams remaining 3 h of the day. At the initiation of the next estrus cycle (4 days), dams were mated overnight. Mating was confirmed by the presence of a seminal plug and this day consumed more water during exposure to the liquid diet (Table 1). was designated as E1. On E5, the liquid diet was replaced with standardized rat chow. The peak PAC was reached 30 min after provision of the EtOH Food, water intake and maternal weight gainwas monitoreddaily throughout gestation. containing diet on E-2 (0.18 0.04%) and E2 (0.25 0.04%). Levels Æ Æ On E20, dams were deeply anesthetized following i.p. administration of a mix of 50/50 thereafter declined and at 3 h were w0.07 0.02% and at 5 h, ketamine/xylazile (0.1ml/100 g body weight) (Lyppard Australia Ltd,QLD,Australia) and Æ 0.05 0.02% (data not shown). Plasma osmolality and electrolyte maternal blood collected from a tail vein. Fetuses and placentas were removed and Æ weighed to the nearest 0.1 mg. Placental dimensions were measured to the nearest concentration of sodium, potassium and chloride did not differ 0.01 mm. Fetal sex was confirmed by real time polymerase chain reaction (qPCR) as between groups on either E-2 or E2 (Table 1). The number of fetuses previously described [17]. Placentas were immediately separated into the labyrinth and and the fetal sex ratio (data not shown) was similar between junctional zone, snap frozen in liquid nitrogen and stored at 80 C, or left intact and À treatment groups, but EtOH-exposed dams had a higher rate of fixed in 4% paraformaldehyde (PFA). Placental labyrinth and junctional zone dry weights were obtained by oven drying [17]. All analyses were carried out in placentas from both unviable fetuses (Table 1). male and female fetuses. To avoid stressing the dams, a separate cohort of control fed dams and EtOH fed 3.2. Fetal weight, placental ratio and placental cross-sectional area dams (n 10 per group) where set up for determination of plasma alcohol con- ¼ centrations (PAC). These dams were treated and mated in the same way as outlined above. Blood was drawn from a tail vein into a lithium-heparinized collection tube At E20, the body weight of PC EtOH-exposed fetuses was (Sarstedt, SA, Australia), two days prior to mating (E-2) and on E2 at 0.5, 1, 3 and reduced (Ptrt < 0.009) and females of both treatment groups were 5 h after diet administration. Plasma samples were centrifuged at 3000 rpm for lighter than their males counterparts (Psex < 0.04, Table 2). PC 10 min at 4 C. The plasma supernatant was collected and stored at 80 C until À EtOH-exposed fetuses were also shorter than controls (Ptrt < 0.004, assayed with an EnzyChrome EtOH kit (BioAssay Systems, CA, USA) according to manufacturer’s instructions. Table 2). There was no difference in absolute placenta (Table 2), labyrinth or junctional zone wet weight (data not shown), but 2.3. Gene analyses placenta to body weight ratio was increased following PC EtOH- RNA from each placental region was extracted separately using the RNeasy Mini- Kit (Qiagen, VIC, Australia), reverse transcribed into cDNA and gene expression assayed using qPCR with the following Assays-on-Demand primer/probe sets Table 1 (Applied Biosystems., CA, USA);Hsd11b2 (Rn00492539_m1), Slc2a1 (Rn1417099_m1), Maternal parameters. Slc2a3 (Rn00567331), Igf1(Rn00710306_m1), Igf2 (Rn01454518_m1), Igf2R Variables Control EtOH (Rn01636937_m1), Slc38a1 (Rn00593696_m1), Slc38a2 (Mn00628416_m1), Slc38a4 Calorie intake (liquid diet), cal/gbw/d 0.20 0.01 0.18 0.01 (Rn00593742_m1), Pgf (Rn00585926_m1), Flt1 (Rn00570815_m1), Vegfa Æ Æ (Mm00437304_m1), Kdr (Mn01222421_m1), Gsk3b (Rn00583429_m1), Gys1 (E-4-mating) Calorie intake (liquid diet), cal/gbw/d 0.23 0.01 0.21 0.01 (Rn01476417_m1) and Gjb3(Rn00570335_s1). qPCR results were analyzed using the Æ Æ DDc(t) method, with Rn18s as the endogenous control. All groups were compared (mating-E4) Calorie intake (chow), cal/gbw/d (E5-E20) 0.27 0.01 0.27 0.00 with the average of the male control group [16]. Æ Æ Water intake, ml/gbw/d (E-4-mating) 0.010 0.002 0.015 0.002* Æ Æ Water intake, ml/gbw/d (mating-E4) 0.010 0.002 0.023 0.003* 2.4. Protein analyses Æ Æ Water intake, ml/gbw/d (E5-E20) 0.110 0.003 0.120 0.005 Æ Æ Total protein was extracted from placental labyrinth tissue (n 5e6 per sex and Peak plasma alcohol level (%) (E-2) 0 0.18 0.04 ¼ Æ treatment group) and subjected to SDS-PAGE and western blotting as described Osmolality (mmol/kg) (E-2) 302 4 300 5 Æ Æ previously [16] to detect the expression of IGFR1(Anti-IGF1R 1:1000, Santa Cruz e Plasma sodium (mmol/L) (E-2) 136.8 1.9 140.4 1.2 Æ Æ cat#Sc-712). Plasma potassium (mmol/L) (E-2) 5.17 0.16 5.37 0.63 Æ Æ Plasma chloride (mmol/L) (E-2) 101.2 1.7 102.3 1.8 Æ Æ 2.5. Immunohistochemistry Peak plasma alcohol level (%) (E2) 0 0.25 0.04 Æ Osmolality (mmol/kg) (E2) 292 4 297 1 Fixed placenta were processed to paraffin and 5 representative midline sections Æ Æ Plasma sodium (mmol/L) (E2) 136.9 1.1 137.8 1.3 (7 mm) were taken from each placenta. Sections were stained with hematoxylin and Æ Æ Plasma potassium (mmol/L) (E2) 6.62 0.78 5.28 0.31 eosin (H&E), coverslipped and imaged using the ScanScope system (Aperio Tech- Æ Æ Plasma chloride (mmol/L) (E2) 101.1 1.1 100.4 1.1 nologies, USA). Cross sectional areas of junctional zone, labyrinth and glycogen cells Æ Æ Body weight on E0 (g) 254 6 262 8 were measured using imagescope software (version.10.2.2.2319). Additional sec- Æ Æ Total weight gain (g) 144.8 8.6 141.2 6.0 tions were used for immunohistochemical staining of GLUT1. Sections were dehy- Æ Æ Litter size (number) 15 1 14 1 drated, blocked in BSA/goat serum and incubated with a rabbit polyclonal GLUT1 Æ Æ Number of pregnancies with at least 1 of 9 6 of 11 antibody for 1 h (1:1000, Millipore e cat. #07-1401). This was followed by 30 min one unviable fetus incubation with anti-rabbit secondary antibody (ABC Vectastain Elite KIT, Vector- labs, USA) and staining with Diaminobenzidine tetrahydrochloride (ImmPACT DAB All data are presented as mean SEM and n(control) 9, n(EtOH) 11. Æ ¼ ¼ Peroxidase Substrate, SK4015, Vectorlabs, USA). E embryonic day. *, P < 0.05 by unpaired t -test (P < 0.05). ¼ 52 E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57

Table 2 Fetal and placental weights and dimensions at E20.

Variables Male control Male EtOH Female control Female EtOH Statistics

Fetal weight and dimensions Body weight, g 2.65 0.05 2.45 0.08 2.50 0.05 2.33 0.07 P < 0.002 Æ Æ Æ Æ (trt) P(sex) < 0.04 P(trt sex) NS Â ¼ Snout-rump length, mm 40.37 0.23 38.58 0.76 39.55 0.13 37.85 0.68 P < 0.004 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Placental weights and dimensions Absolute placenta wet weight, g 0.56 0.02 0.55 0.02 0.55 0.01 0.55 0.02 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ Placenta:body weight ratio, g/gbw 0.21 0.01 0.23 0.01 0.22 0.01 0.24 0.01 P < 0.004 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Absolute labyrinth zone (dry), g 0.057 0.011 0.065 0.012 0.054 0.005 0.057 0.004 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ Absolute junctional zone (dry), g 0.033 0.003 0.042 0.002 0.033 0.003 0.045 0.004* P < 0.002 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Placental length, mm 13.55 0.21 13.95 0.20 13.54 0.16 13.94 0.18 P < 0.05 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Placental width, mm 12.18 0.14 12.42 0.18 12.02 0.14 12.60 0.19 P < 0.03 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Placental depth, mm 4.20 0.10 4.22 0.12 4.14 0.09 4.18 0.13 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ All data are presented as mean SEM and n 9e11 for each group. *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex. NS not signiﬁcantly Æ ¼ ¼ different.

exposure (Ptrt < 0.004, Table 2). Labyrinth zone dry weights were placenta from males, but not females, when compared to untreated unaffected by PC EtOH-exposure while junctional dry weight was controls (P < 0.01, Fig. 3E). increased (Ptrt < 0.002, Table 2). Placental depth was not different PC EtOH-exposure did not affect junctional mRNA levels of Gjb3 following PC EtOH-exposure but length (Ptrt < 0.05) and width and Gys1 but mRNA levels of Gsk3b were higher in PC EtOH- (Ptrt < 0.03) were increased (Table 2). exposed placenta from females but not males (P < 0.05, Table 3). H&E staining showed no gross morphological abnormalities in In addition, PC-EtOH caused multiple changes in mRNA expression response to PC EtOH-exposure, however there was an increase in in the labyrinth: increased mRNA levels of 11bHsd2 in both sexes junctional zone due to glycogen accumulation (Fig. 1). Analysis of (Ptrt < 0.0001, Table 3), increased mRNA levels of Slc38a1 in pla- the cross-sectional areas of each placental zone in proportion to centas from females fetuses regardless of treatment group whole placenta showed a decrease in labyrinth (Ptrt < 0.03, Fig. 1A) (Psex < 0.03, Table 3) and decreased mRNA levels of Slc38a2 in and an increase in junctional (Ptrt < 0.03, Fig. 1B) region following placentas from both sexes (Ptrt < 0.003, Table 3), while Slc38a4 was PC EtOH-exposure. In addition, the cross-sectional area of glycogen unaffected (Table 3). Vegfa mRNA levels were higher in PC EtOH- cells, both as a percentage of total placenta (Ptrt < 0.002, Psex < 0.01, exposed placentas (Ptrt < 0.03, Table 3) and in placentas from fe- Fig. 1C) and as absolute cross sectional area (Ptrt < 0.009, male fetuses (Psex < 0.03, Table 3), but there was no difference in Psex < 0.007, Fig. 1D) were greater following PC EtOH-exposure. mRNA levels of Pgf (Table 3). While Flt1 gene expression was higher Post hoc analyses showed that the cross-sectional area of in placentas from female fetuses (Psex < 0.02, Table 3), mRNA levels glycogen cells were greater in PC EtOH-exposed placentas from of Kdr were only increased in placentas from females following PC females compared to their control counterparts (P < 0.01). EtOH-exposure (P < 0.05, Table 3).

3.3. Placental gene and protein expression 4. Discussion

PC EtOH-exposure did not alter mRNA levels of Glut1 in the Our study shows for the first time that exposure of the rat to labyrinth (Fig. 2A) but increased the expression in the junctional moderate levels of alcohol exclusively during the PC period is suf- zone of the placenta (Ptrt < 0.05, Fig. 2B). This was confirmed by ficient to program growth restriction in both male and female fe- immunohistochemistry staining of GLUT1 in the junctional zone tuses in late gestation and cause significant changes in placental (Fig. 2E and F). The relative gene expression of Glut3 was unaffected structure, morphology and gene expression. Whilst the primary by PC EtOH-exposure (Fig. 2C and D). stimulus was PC EtOH-exposure, elevated levels of placental PC EtOH-exposure suppressed Igf1 gene expression in the lab- 11bHsd2 [16,17] and GLUT1 [18] suggest a long-lasting stress yrinth (Ptrt < 0.001, Fig. 3A), whereas the gene expression of Igf1 in response may be involved. Sex-specific differences such as the size the junctional zone was unaffected (Fig. 3B). Igf2 mRNA was not of placental junctional zone in females, along with an increase in altered in the labyrinth (Fig. 3C) but increased in the junctional Glut3 mRNA levels, indicate dissimilar mechanisms of action. The zone of PC EtOH-exposed placentas (Ptrt < 0.03, Fig. 3D). mRNA observations from this study are consistent with other models of PC levels of the Igf2R were similar between treatment groups (Fig. 3F). perturbations, mainly focusing on maternal nutritional status [3e Relative protein expression of IGF1R was lower in PC EtOH-exposed 6,19], in that it highlights the importance of the period around E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57 53

Fig. 1. Effects of PC EtOH-exposure (black bars) on cross-sectional area of labyrinth zone (A), junctional zone (B), glycogen cells (C) as a percentage of total placenta, and absolute cross-sectional area of glycogen cells (D) in placentas from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means SEM, n 9e11 per group, **, P < 0.01 for Bonferroni post hoc compared with untreated controls of same sex. Representative sections of untreated control (E) and PC EtOH- Æ ¼ exposed (F) placenta from female fetuses 1 (scale bars 1000 mm) with glycogen stores (appears white) shown in 20 magniﬁcation (scale bars 100 mm). Â Â the time of conception as a critical window of development. These occasional alcohol users [28] and as rats metabolize alcohol faster results are therefore of high clinical importance as they suggest that than humans [29], they should be considered clinically relevant. a woman’s drinking habits, even prior to conception and preimplantation can have implications on the growth and development 4.2. PC EtOH-exposure introduced a long-lasting stress response in of the placenta and thus, the fetus. placentas from both sexes

4.1. PC-EtOH exposure results in fetal growth restriction EtOH appeared to induce a long-lasting stress response in placentas from both sexes, as evidenced by increased expression of the It is well established that prenatal alcohol exposure causes fetal gene 11bHsd2 in the labyrinth zone. Placental 11bHSD2 protects the growth restriction [20,21]. Many studies of in utero EtOH-exposure fetus from maternally circulating glucocorticoids (cortisol or are however confounded by a modiﬁed energy intake [22]. Both corticosterone) by enzymatic inactivation [30]. Previous studies maternal over [23] and under nutrition [24] causes alterations in performed by our laboratory in the mouse [16,17] and others in the fetal growth ultimately resulting in early onset of adult diseases human [31] have shown that the placenta can mediate a temporary [24e26]. Our model is not complicated by caloric restriction or increase in the expression level of 11bHsd2 in response to eleva- overnutrition as energy intake was equivalent in both EtOH and tions in circulating maternal glucocorticoids. Although corticoste- control fed dams throughout preimplantation and later periods of rone levels were not measured in this model, other studies in rats gestation, as was maternal weight gain. Moreover EtOH-exposed have shown that chronic alcohol consumption throughout preg- dams drank more water allowing maintenance of plasma osmo- nancy does indeed increase maternal corticosterone concentrations lality and electrolytes. The PAC reported may appear high as they [32]. Furthermore, increases in placental Glut1 gene expression, were determined following the period of maximal ingestion. The similar to those measured in this study, have been observed in rats PAC generated is comparable with other models of EtOH exposure, following maternal glucocorticoid administration [18]. GLUT1 is a which generally administer EtOH via gavage [22,27]. Importantly, ubiquitous stress and growth factor responsive transporter that is these levels are only marginally higher than levels found in expressed throughout preimplantation development [33].We 54 E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57

Fig. 2. Effects of PC EtOH-exposure (black bars) on Glut1 gene expression in the labyrinth (A) and junctional (B) zone; and on Glut3 gene expression in the labyrinth (C) and junctional (D) zone of placenta from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means SEM, n 9e11 per Æ ¼ group, *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex. Representative sections of untreated control (E) and PC EtOH-exposed (F) placenta from female fetuses shown in 20 magnification (scale bars 100 mm) quantitatively confirmed that the increase in Glut1 mRNA in the junctional zone also were translated into increases Â in GLUT1 protein levels (dark brown staining). Inserts shows sections stained with the appropriate sense probe as a control ( 20 magnification, scale bars 100 mm). Â therefore suggest the increased Glut1 expression in PC EtOH- fetal growth restriction [36] we suggest that the lower labyrinth exposed placentas to be supportive for a role of stress and/or glu- Igf1 mRNA levels in PC EtOH-exposed placentas may have cocorticoids in PC EtOH-exposure. impacted on fetal growth. Junctional Igf2 mRNA levels on the other hand were elevated, whilst labyrinth mRNA levels of Igf2R 4.3. PC EtOH-exposure caused sex specific alterations in placental were maintained. Given that the IGF2R predominantly acts to morphology and gene expression limit IGF2 action by internalization and degradation of the ligand [37], we suggest this may have contributed to the greater pro- Abnormal placental weight, both absolute and as a ratio of fetal portion of junctional zone area observed in PC EtOH-exposed weight, are independently associated with adult disease [26]. placentas from females. Although absolute placental weight was unchanged by PC EtOH- PC EtOH-exposure also increased levels of labyrinth Vegfa gene exposure, there were changes in shape and an increase in body/ expression. Numerous studies have previously shown that pre- placental ratio and junctional zone cross-sectional area. The in- natal EtOH-exposure alters normal vascular adaptation during crease in junctional cross-sectional area was due to an increase in pregnancy (for review see [38]). Whilst the increase in Vegfa gene the area of apparent glycogen and this was more pronounced in expression may appear to be inconsistent with the apparent placentas from females. This suggests a sexually dimorphic growth restriction, similar results have been observed in placentas chance which ultimately may have contributed to other sex- of mouse fetuses following prenatal dexamethasone administra- specific alterations, as differences in placental shape and tion [16]. As mRNA levels of Flt1 were higher in placentas from morphology affects transplacental transfer of nutrients, oxygen female fetuses regardless of treatment group and mRNA levels of and hormones [34]. Kdr were increased in placentas from PC EtOH-exposed females Neither IGF1 nor 2 can cross the placental barrier and are only, it is likely that placentas from female fetuses are attempting exclusively produced by the feto-placental unit to maintain fetal to increase vasculogenesis to ensure adequate fetal nutrient and placental growth [35]. As IGF1 deletion is known to cause supply. E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57 55

Fig. 3. Effects of PC EtOH-exposure (black bars) on Igf1 gene expression in the labyrinth (A) and junctional (B) zone; on Igf2 gene expression in the labyrinth (C) and junctional (D) zone, on relative protein expression in the labyrinth zone (E), and on relative gene expression of Igf2R (F) of placenta from male and female fetuses on E20 compared with untreated controls (white bars). Data are represented as litter means SEM, mRNA expression: *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex, n 9e11 per Æ ¼ group. Protein expression: *, P < 0.05 by unpaired t-test comparing untreated controls and PC EtOH-exposed placenta of the same sex, n 5 per group. ¼

4.4. PC EtOH-exposure and alterations in glycogen cross-sectional glycogen synthesis [41]. Intriguingly, mRNA levels of Gsk3b,a area negative regulator of GYS1 activity [42], was only elevated in placentas from females, perhaps to limit further glycogen deposition. Glycogen cross-sectional area was increased in placentas from Furthermore, PC EtOH-exposure increased junctional Glut3 female fetuses following PC EtOH-exposure. Although the role of mRNA levels in female placenta, which together with glycogen glycogen in the placenta is unclear we attempted to further accumulation has also has been observed in placentas of diabetic approach this by investigating the levels of speciﬁc glycogen cell rats [43]. While GLUT3 is involved in glucose delivery to the fetus markers. Interestingly, whilst Igf2, a key regulator of placental [43], it also transports glucose from the fetal circulation back into glycogen synthesis [35,39], was elevated in PC EtOH-exposed fe- the placenta, as the placenta is the only tissue capable of storing male placentas, mRNA levels of Gjb3 and Gys1 was unchanged. Gjb3 excess fetal glucose [44]. In contrast, placentas from male fetuses encodes a gap junction protein which is exclusively expressed in expressed less Glut3 following PC EtOH-exposure but also had a the membrane of vacuolated glycogen cells in mid to late gestation smaller placental area occupied by glycogen cells. Our data may placenta [40] whilst Gys1 is the rate limiting enzyme involved in suggest an early EtOH induced change in metabolism to favor 56 E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57

Table 3 Relative gene expression.

Male control Male EtOH Female control Female EtOH Statistics

Labyrinth zone Slc38a1 1.03 0.07 0.91 0.08 1.06 0.10 1.28 0.14 P NS Æ Æ Æ Æ (trt) ¼ P(sex) < 0.04 P(trt sex) NS Â ¼ Slc38a2 1.01 0.06 0.76 0.06 0.92 0.05 0.83 0.04 P < 0.003 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Slc38a4 1.11 0.13 1.06 0.10 0.90 0.05 1.11 0.12 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ Vegfa 1.03 0.09 1.23 0.11 1.23 0.11 1.55 0.13 P < 0.03 Æ Æ Æ Æ (trt) P(sex) < 0.03 P(trt sex) NS Â ¼ Kdr 1.07 0.14 0.97 0.07 0.87 0.05 1.39 0.16* P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) < 0.01 Â Pgf 1.03 0.09 0.97 0.08 1.01 0.08 1.15 0.08 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ Flt1 1.02 0.08 0.91 0.10 1.14 0.10 1.25 0.09 P NS Æ Æ Æ Æ (trt) ¼ P(sex) < 0.02 P(trt sex) NS Â ¼ 11bHsd2 1.06 0.14 2.03 0.21* 1.38 0.20 2.51 0.29* P < 0.0001 Æ Æ Æ Æ (trt) P NS (sex) ¼ P(trt sex) NS Â ¼ Junctional zone Glycogen cell markers Gys1 1.03 0.09 0.98 0.09 1.00 0.11 1.11 0.13 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ Gsk3b 1.02 0.09 0.84 0.04 0.82 0.05 1.07 0.09* P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) < 0.006 Â Gjb3 1.13 0.20 1.09 0.15 0.87 0.09 1.15 0.14 P NS Æ Æ Æ Æ (trt) ¼ P NS (sex) ¼ P(trt sex) NS Â ¼ All data are presented as mean SEM and n 9e11 for each group. *, P < 0.05 for Bonferroni post hoc compared with untreated controls of same sex. NS not significantly Æ ¼ ¼ different. glycogen accumulation. We propose that placentas, particularly programmed disease following PC EtOH-exposure need to be car- from females, either have a reduced capacity for transplacental ried out to establish this hypothesis. As alcohol consumption is glucose transfer from mother to fetus and/or an augmented back- common amongst women of childbearing age [8] and half of all flow of glucose from the fetal circulation to the placenta, which pregnancies are unplanned [47] it is important to address this by again is the case seen in placentas of diabetic rats [45]. increasing public awareness about the implication of alcohol consumption even before becoming pregnant. 4.5. PC EtOH-exposure altered amino acid transporter abundance Acknowledgments The decreased labyrinth expression of Slc38a2 following PC EtOH-exposure seen in this study may have contributed to fetal The authors would like to acknowledge the funding provided by growth restriction as seen in other models with changes in placental the National Health and Medical Research Council of Australia Na -dependent system A transporters [4,12]. The system A amino þ (1046137) and David Simmons for assistance with the placental acid transporters accept a wide range of amino acids, however only morphology. Slc38a2 transports the essential amino acid methionine [46]. As methionine is involved in DNA and histone methylation it has been suggested to play an important role in epigenetic regulation of genes References [4,19]. The preimplantation embryo is very susceptible to epigenetic [1] McMillen IC, Robinson JS. Developmental origins of the metabolic syndrome: perturbations [19] and we cannot preclude the possibility of the al- prediction, plasticity, and programming. Physiol Rev 2005;85(2):571e633. terations in Slc38a2 gene expression contributing to faults in pro- [2] Fleming TP, Kwong WY, Porter R, Ursell E, Fesenko I, Wilkins A, et al. The gramming events involving epigenetic change. embryo and its future. Biol Reprod 2004;71(4):1046e54. Our study has for the first time shown that maternal alcohol [3] Kwong WY, Wild AE, Roberts P, Willis AC, Fleming TP. Maternal undernutrition during the preimplantation period of rat development causes blastocyst intake exclusively around the time of conception alters placental abnormalities and programming of postnatal hypertension. Development weight and morphology and causes growth restriction in the late 2000;127(19):4195e202. gestation fetus. Particularly interesting was the programmed stress [4] Sinclair KD, Allegrucci C, Singh R, Gardner DS, Sebastian S, Bispham J, et al. DNA methylation, insulin resistance, and blood pressure in offspring deter- response, indicated by the increase in placental 11bHsd2 and Glut1 mined by maternal periconceptional B vitamin and methionine status. Proc gene expression. Our results suggest that the placenta exerts sex- Natl Acad Sci U S A 2007;104(49):19351e6. specific mechanisms of actions, both structurally and functionally, [5] Watkins AJ, Lucas ES, Wilkins A, Cagampang FR, Fleming TP. Maternal periconceptional and gestational low protein diet affects mouse offspring growth, with females perhaps being more protected. Future studies that cardiovascular and adipose phenotype at 1 year of age. PLoS One 2011;6(12): determine postnatal sex-specific contributions to adult onset of e28745. E.M. Gårdebjer et al. / Placenta 35 (2014) 50e57 57

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Maternal alcohol intake around the time of conception causes glucose intolerance and insulin insensitivity in rat offspring, which is exacerbated by a postnatal high-fat diet

Emelie M. Gardebjer,*˚ Stephen T. Anderson,* Marie Pantaleon,* Mary E. Wlodek,† and Karen M. Moritz*,1 *Biomedical Sciences, The University of Queensland, St. Lucia, Queensland, Australia; and †The Department of Physiology, The University of Melbourne, Parkville, Victoria, Australia

ABSTRACT Alcohol consumption throughout preg- Key Words: developmental programming • metabolic path- nancy can cause metabolic dysregulation, including ways • diabetes • gluconeogenesis • gene expression glucose intolerance in progeny. This study determined if periconceptional (PC) alcohol (12% v/v in a liquid INCREASING EVIDENCE IMPLICATES the intrauterine environ- diet) (PC:EtOH) consumed exclusively around con- ment in the development of chronic adult disease ception results in similar outcomes in Sprague-Dawley propensity and metabolic disorders (1). Indeed, fetuses rats. Control (C) rats were given a liquid diet contain- exposed to a range of adverse intrauterine environments ing no alcohol but matched to ensure equal caloric in- including malnutrition (2), placental insufficiency (3), and take. PC maternal alcohol intake (from 4 days before alcohol (4–7) have an increased risk of adult onset meta- conception until day 4 of gestation), resulted in off- bolic dysfunction. Low birth weight, insulin resistance, and spring with elevated fasting plasma glucose (∼10–25%, altered regulation of hepatic glucose output are commonly P < 0.05), impaired glucose tolerance (P < 0.05), and demonstrated in these models (4–9). Intriguingly, these decreased insulin sensitivity (P < 0.01) at 6 months of effects are often programmed in a sex-specificmanner, age. This was associated with increased hepatic glu- with males consistently more adversely affected than coneogenesis and sex-specificalterationsinperipheral females (7). The PC period appears to be a particularly protein kinase B (AKT) signaling. These changes were susceptible developmental window for programming of accompanied by increased mRNA expression of DNA disease (10). Given that .50% of women consume alcohol methyltransferases (DNMTs) 1, 3a, and 3b (1.5- to 1.9-fold, before pregnancy (11) and half of all pregnancies are P < 0.05) in fetal liver in late gestation, suggesting PC:EtOH reported to be unplanned (11, 12), many embryos are may cause epigenetic changes that predispose offspring to potentially exposed to alcohol before pregnancy recogni- metabolic dysfunction. Exposure to a postnatal (PN) high- tion. Despite recommendationsofalcoholabstinencefor fat and cholesterol diet (HFD) from 3 months of age women who are pregnant, or planning a pregnancy, a re- caused hyperinsulinemia (∼2-fold increase, P < 0.001) and cent study reported that 32% of women claim that they exacerbated the metabolic dysfunction in male offspring would continue to drink despite trying to conceive (13). exposed to PC:EtOH but had no additive effects in We have previously shown that PC:EtOH-exposure females. Given many women may drink alcohol while causes fetal growth restriction and sex-specific placental planning a pregnancy, it is crucial to increase public abnormalities in late pregnancy in the rat (14). Both awareness regarding the effects of alcohol consumption are risk factors for adult-onset disease (15, 16). Here, around conception on offspring health.—Gardebjer,˚ we examined the hypothesis that PC:EtOH-exposure E. M., Anderson, S. T., Pantaleon, M., Wlodek, M. E., programs glucose intolerance and insulin resistance in Moritz, K. M. Maternal alcohol intake around the time of offspring. In addition, we explored the influence of a PN conception causes glucose intolerance and insulin in- HFD as it has been suggested that lifestyle/dietary factors sensitivity in rat offspring, which is exacerbated by can unmask and/or exacerbate preprogrammed adult a postnatal high-fat diet. FASEB J. 29, 000–000 (2015). disease propensity (4). To elucidate potential mecha- www.fasebj.org nisms contributing to disease, we examined the effect of PC:EtOH-exposure on gluconeogenic genes in the liver and AKT signaling in peripheral tissues in adult offspring Abbreviations: AKT, protein kinase B; AUGC, area under the (5, 8, 17). Additionally, we assessed expression levels of glucose curve; AUIC, area under the insulin curve; bw, body weight; C, control; DNMT, DNA methyltransferases; E%, energy percentage; E, embryonic day; EtOH, ethanol; G6pc,glucose-6- 1 Correspondence: School of Biomedical Sciences, The phosphatase; Gck,glucokinase;GSK3,glycogensynthasekinase University of Queensland, St Lucia, 4072, Australia. E-mail: 3; GTT, glucose tolerance test;HDAC,histonedeactylases; [email protected] (continued on next page) doi: 10.1096/fj.14-268979

0892-6638/15/0029-0001 © FASEB 1 key chromatin modifiers in fetal life because epigenetic was canola oil in the C-diet and clarified butter in the HFD. All changes are implicated in metabolic programming of groups had ad libitum access to allocated diet and water until the adult disease following PC perturbation (18). Specifi- end of the study. cally, we examined expression levels of histone deactylases (HDACs) and DNA methyltransferases (DNMTs) in Glucose and insulin tolerance tests fetal liver as alterations in both these modifications are associated with metabolic disease. Glucose [1g/kg body weight (bw)] tolerance test (GTT) and insulin (0.75 U/kg bw) tolerance test (ITT) were performed at 6 months (n = 10–11 per group) as described previously (7). MATERIALS AND METHODS Plasma glucose levels were determined using a Cobas Integra 400 Plus Chemistry Analyzer and insulin concentrations by rat insulin radioimmunoassay kit (catalog no.RI-13K, Millipore Australia, Ethics Kilsyth, Victoria, Australia). Insulin samples were run in duplicates, at 1:2 dilutions. Assay sensitivity was 0.16 ng/mL, and inter- All animal experimentation was approved by The University of and intra-assay coefficients of variation were 14.9% and 9.9%, Queensland Anatomic Bioscience Animal Ethics Committee respectively. (SBS/022/12/NHMRC) before the commencement of the study.

Tissue collection Rats and treatment Rats were euthanized at 8 months by intraperitoneal adminis- Outbred nulliparous Sprague-Dawley rats were housed in- tration of a 50/50 ketamine/xylazine mix (0.5 ml/100g bw) after dividually under an artificial 12-hour light-dark cycle and treated a 15 h fast. Tissues were snap-frozen in liquid nitrogen and stored as described previously (14). In brief, 12- to 13-week-old dams at 280°C (gastrocnemius muscle, white intra-abdominal adipose were randomly allocated to a liquid diet containing either 12.5% tissue, and liver). Fetal liver was collected as described previously v/v (PC:EtOH) or an equal-caloric 0% EtOH diet (untreated, U) on E20 (14). (n =22pertreatmentgroup)for1fullestruscycle(4days)before fi overnight mating. Animals that did not mate on thefourth or fth Quantitative PCR and Western blotting day after being offered the diet were removed from the protocol. The liquid diet was composed of Sustagen hospital formula (Mead Johnson Nutritionals, Auckland, New Zealand), reduced RNA from the left lateral lobe of the liver was extracted using fat milk, corn flour, and essential minerals (ferric citrate, copper RNeasy Mini-Kit and reversed transcribed into cDNA. Gene ex- II sulfate, selenium, and magnesium sulfate). In preliminary pression was analyzed using quantitative PCR (qPCR) with the fol- experiments, we had identified that the EtOH-exposed dams lowing Assay-on-Demand primer/probe sets (Applied Biosystems, consumed a lesser amount of the liquid diet, hence the energy Foster City, CA, USA) phosphoenolpyruvate carboxykinase (Pck1) density of the EtOH-diet was increased and the ingredients were (Rn01529014_m1), glucokinase (Gck)(Rn00561265_m1),glucose- modified to ensure an equal amount of macro- and micro- 6-phosphatase (G6pc)(Rn00689876_m1),peroxisomeproliferator- g a nutrients (C diet composition: 11.3% fat, 17.0% protein, 68.2% activated receptor coactivator 1- (Ppargc1a) (Rn00580241_m1), carbohydrates, 7.7 MJ/kg; EtOH diet: 11.9% fat, 13.6% protein, Hdac2 (Rn01193634-g1), and Hdac6 (Rn01528283_m1), or SYBR 50.7% carbohydrates, 11.8 MJ/kg). Dams had access to the liquid Green detection chemistry using the following primers for: Hdac3 9 9 diet 21 hours daily ad libitum until embryonic day (E)4, with water (F: 5 -GATTAGGCTGCTTCAATCTC; R: 5 -CAGAGATGTTTCA- 9 offered during the remaining 3 h of the day. Liquid diets were TATGTCCAG), Hdac4 (F: 5 -AAACAGCTTCTGAACCTAAC; R: 9 9 replaced by standardized rat chow and water on E5 (4.0% fat, 5 -GAGTCTGTAACATCCAGGG), Dnmt1 (F: 5 -AGAGACCAGG- 9 13.6% protein 64.3% carbohydrates; 15.5 MJ/kg) (SF-08-020 ATAAGAACG; R: 5 -TTACTCGTTCAGGTTTCTCC), Dnmt3a (F: 9 9 Specialty feeds, Glenforrest, WA, Australia). One subset of dams 5 -AATAGCCAAGTTCAGCAAAG; R:5 -AAACACCCTTTCCATTT- 9 (n = 10 per group) were killed on E20 for collection of fetal liver, CAG), and Dnmt3b (F:5 -GATGACAAGGAGTTTGGAATA; 9 whereas one subset (n = 12 per group) littered down naturally. R:5 -CAGCGATCTCAGAAAACTTG). qPCR results were analyzed DD Offspring were weighed daily until weaning on PN day 28. At with the c(t)method,usingRn18s as the endogenous control. 3 months, one subset of offspring was randomly assigned to All groups were compared to the average of the U:C group (14). a modified diet that contained increased fat and cholesterol Total protein was extracted from 80 mg abdominal adipose (21% fat, 0.15% cholesterol, 19% protein, 59.9% carbohydrates; tissue and 15 mg skeletal muscle. Tissues were homogenized in 19.4 MJ/kg) (SF00-219 Specialty feeds) and the remaining ani- 0.4 ml RIPA buffer for 20 seconds using an Ultra-Turrax T8 mals were supplied with the same standardized chow as the dams homogenizer (Labtek, Brendale, Australia). Homogenates consumed (C). These diets are matched for micronutrient were centrifuged (11,000 rpm, 20 min, 4°C) and resultant composition. This resulted in the generation of 8 treatment supernatant assayed using the Bio-Rad (Hercules, CA, USA) groups: U:C; U:HFD; PC:EtOH:C; and PC:EtOH:HFD for both reducing agent and detergent compatible protein assay kit. male and female offspring. Both the HFD and C diet were based Total protein (20 mgpersample;n =5–6persexandPC on similarbase ingredients for protein andcarbohydrates (casein; treatment) was subjected to SDS-PAGE on 12% gels and sub- and wheat starch, sucrose, and cellulose); but the fat source sequently transferred to Immobilon FL PVDF membranes (Millipore). Membranes were incubated overnight with one of the following polyclonal rabbit antibodies (all from Cell Sig- (continued from previous page) naling, Danvers, MA, USA); anti-total-AKT2 (1:1000, catalog HFD, high-fat and cholesterol diet; HOMA-IR, homeostasis no. 3063), anti-phospho-AKTThr309 (1:600, catalog no. 9275), model assessment-estimated insulin resistance; ITT, insulin tol- anti-phospho-AKTSer474 (1:800, catalog no. 8599), anti-phospho- erance test; PC, periconceptional; Pck1,phosphoenolpyruvate glycogen synthase kinase 3 (GSK3)a/bSer21/9 (1:600, catalog no. carboxykinase; Ppargc1a,peroxisomeproliferator-activatedre- 9331), or a mouse monoclonal anti-GSK3a/b (1:600, catalog no. ceptor g coactivator 1-a; PN, postnatal; qPCR, quantitative 05-412, Upstate Biotechnology, Lake Placid, NY, USA). b-Actin PCR; QUICKI, quantitative insulin sensitivity check index; immunoreactivity was used for ratiometric purposes (1:25000, U, untreated #A1978; Sigma-Aldrich, St. Louis, MO). Protein expression was

2 Vol. 29 June 2015 The FASEB Journal x www.fasebj.org GARDEBJER˚ ET AL. assayed using a LI-COR Odyssey infrared imaging system (LI- RESULTS COR Biosciences, Lincoln, NE, USA) following exposure to LI-COR IRDye 680 goat anti-rabbit and IRDye 800CW goat Maternal parameters and PN growth anti-mouse secondary antibodies (Millennium Science, Mul- grave, Australia). Dams were of similar age (U: 87 6 3 vs. PC:EtOH: 85 6 3 d) and weight (U: 262 6 7 vs. PC:EtOH: 258 6 7g)atthestart of the experimental protocol. There was no difference in Calculations and statistical analyses caloric intake at any time during pregnancy as reported previously (14). Gestational weight gain was similar be- Area under glucose (AUGC) and insulin (AUIC) concentra- tween treatment groups (data not shown). The average tion curves were calculated using the trapezius method with fi and the peak plasma alcohol concentration 2 days before baseline de ned as 0 (19). AUGC following the GTT was cal- mating was 0.07 6 0.01% and 0.18 6 0.04%, respectively, culated defining the baseline as 0 and the positive incremental area (AUC of positive peaks) (20). The ITT curves were inverted and the peak plasma alcohol concentration on E2 was before calculating AUGC. Acute first-phase insulin secretion 0.25 6 0.04% (14). There were no differences in gesta- was calculated as the incremental AUIC from basal to 5 min and tional length (22 d), litter size (15 6 1 pups), or the male: second-phase insulin secretion as the incremental AUIC female ratio (U: 1.13 vs. PC:EtOH: 1.17) between treat- from 5 to 120 min. Quantitative insulin sensitivity check index ment groups. Body weight at weaning (PN28) was also (QUICKI) was calculated as 1/{log[fasting insulin (mU/ml)] 3 similar between treatment groups (Table 1) with no ap- log[fasting glucose (mg/dl)]} (21). The homeostasis model parent differences in body weight before initiation of the assessment-estimated insulin resistance (HOMA-IR) was HFD at 3 months (Table 1). Although consumption of an calculated using [fasting insulin (mU/ml) 3 fasting glucose HFD significantly increased weight gain between weeks 17 (mmol/L)]/22.5 (22). and 24 and weeks 25 and 32 in both male and female Three-way ANOVA analysis was conducted with IBM SPSS offspring of both treatment groups (P , 0.0001, Table 1), (Chicago, IL, USA) Statistics (version 20.0) with main effects PC:EtOH-exposure alone or in conjunction with HFD did being PC treatment, sex, and diet. For most parameters, there fi were significant (P , 0.05) main effects of PC treatment, but not signi cantly affect growth (Table 1). also significant interactions with PN diet. Therefore, data were first analyzed by 2-way ANOVA examining the effects of PC treatment between sexes [main effects of PC treatment GTT and ITT at 6 months (PPC:EtOH) and sex (PSex)]. Subsequently, the effect of HFD and PC:EtOH within each sex [main effects of PC treatment Primarily we examined the effects of the PC:EtOH- (PPC:EtOH)andPNdiet(PHFD)] was also assessed. Data were exposure on glucose tolerance and insulin sensitivity in log transferred to remove heterogeneity of variance before animals on the C diet in male and female offspring. We performing ANOVA as required (Bartlett’s test). Means were found that PC:EtOH-exposure increased fasting glucose further compared using a Tukey’smultiplecomparisonpost hoc concentrations (P , 0.05), although this was significantly test. Plasma glucose and insulin concentrations over time were greater in males than females (Fig. 1A). This effect analyzed with a 2-way ANOVA repeated measurements [effects of was associated with a nonsignificant increase in fasting PC treatment (PPC:EtOH)andtime(Ptime)]. Protein immunoblots were compared by Student’s t test. P , 0.05 was considered insulin concentrations (PPC:EtOH , 0.07, Fig. 1B) and fi significantly altered HOMA-IR and QUICKI indices statistically signi cant. Statistical analyses other than 3-way fi ANOVAs were conducted with GraphPad Prism 6 software for (PPC:EtOH , 0.05, Fig. 1C, D). However, there were signi - Windows (GraphPad Software, San Diego, CA, USA). Results cant sex differences, with females exhibiting lower fasting are presented as mean 6 SEM. insulin concentrations than males, and correspondingly

TABLE 1. Offspring weights and weight gain of U and PC:EtOH-exposed offspring fed a C diet or a HFD

Treatment group Statistics (P values) U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction

Male Body weight at weaning (g) 75 6 4 74 6 3 N/A N/A NS N/A N/A Body weight at 16 wk (g) 475 6 8 479 6 8 490 6 11 480 6 14 NS NS NS Weight gain wk 17–24 (g) 104 6 7 108 6 4 156 6 16 169 6 8 NS ,0.0001 NS Weight gain wk 25–32 (g) 54 6 5 57 6 4 105 6 10 94 6 9 NS ,0.0001 NS Body weight at PM, wk 32 (g) 606 6 16 607 6 13 681 6 22 727 6 45 NS ,0.001 NS Snout-rump length at PM (cm) 28.5 6 0.2 28.1 6 0.3 28.8 6 0.3 28.8 6 0.5 NS NS NS Female Body weight at weaning (g) 72 6 3 66 6 2 N/A N/A 0.06 N/A N/A Body weight at 16 wk (g) 283 6 6 283 6 4 286 6 3 287 6 6 NS NS NS Weight gain wk 17–24 (g) 47 6 3 43 6 3 73 6 6 71 6 8 NS ,0.0001 NS Weight gain wk 25–32 (g) 20 6 2 18 6 2 47 6 4 40 6 6 NS ,0.0001 NS Body weight at PM, wk 32 (g) 315 6 16 309 6 14 387 6 20 354 6 18 NS ,0.01 NS Snout-rump length at PM (cm) 23.8 6 0.3 23.0 6 0.3 24.2 6 0.4 23.8 6 0.3 0.06 ,0.05 NS

Body weight at weaning was analyzed with an unpaired t test. All other data was analyzed with a 2-way-ANOVA within each sex with main effects of PC:EtOH and HFD. Data are represented as mean 6 SEM. PM, postmortem; N/A, no data available; NS, not statistically signiﬁcant.

PROGRAMMING EFFECTS OF PERICONCEPTIONAL ALCOHOL 3 Figure 1. Effects of PC:EtOH-exposure (black bars) on (A) fasting plasma glucose and (B) insulin concentration in male and female offspring at 6 months of age. Corresponding homeostatic model assessment (HOMA) of insulin resistance (C) and QUICKI (D) compared to U:C (white bars). n =8–12 per group. Data are represented as mean 6 SEM and compared with the U male group. NS, not signiﬁcant.

lower HOMA-IR and higher QUICKI indices (Psex , 0.05, the HFD did not affect the overall glucose (AUGC) or in- Fig. 1B–D). In the GTT, glucose clearance was inhibited in sulin (AUIC) response, but the HFD diet did increase acute fi both sexes by PC:EtOH exposure, as indicated by in- rst-phase insulin secretion (PHFD , 0.01), and further creased AUGC (PPC:EtOH , 0.01, Fig. 2A, B). Furthermore, exacerbated (P , 0.05) the response to PC:EtOH exposure both sexes displayed increased pancreatic insulin output (Table 2). In the ITT, the HFD did not affect the glucose (AUIC) during the GTT (PPC:EtOH , 0.01, Fig. 2C, D). The clearance in response to exogenous insulin beyond the increased insulin response was both acute first-phase effect of PC:EtOH. fi (PPC:EtOH , 0.05, Fig. 2E) and second phase (PPC:EtOH , In females, there were generally signi cant effects of 0.001, Fig. 2F). Correspondingly, the AUIC:AUGC ratio consuming a PN HFD in the absence of outcomes follow- was increased by PC:EtOH exposure (PPC:EtOH , 0.05, ing PC:EtOH exposure (Table 2). The HFD had no effect Table 2). In the ITT, glucose clearance from circulation in on fasting glucose concentrations, but increased fasting response to exogenous insulin was decreased by PC:EtOH insulin concentrations (PHFD , 0.01, Table 2). This was in both sexes (PPC:EtOH , 0.01, Fig. 2G, H). associated with altered HOMA-IR and QUICKI indices Second, we ascertained whether there was an interaction (PHFD , 0.01, Table 2). Similarly in the GTT, the AUGC, between PC:EtOH and a PN HFD in metabolic outcomes. AUIC, AUIC:AUGC ratio, and acute first-phase and To examine this interaction, we analyzed males and females second-phase insulin secretion, and the AUGC in the ITT separately. In males, consumption of a HFD augmented were all increased by the HFD (PHFD , 0.05; , 0.01; , 0.01; fasting glucose concentrations, to a similar degree in both U , 0.01; , 0.01, , 0.05, respectively), but there were no fi and PC:EtOH (PHFD , 0.001, Table 2). Similarly, fasting signi cant interactions between PC:EtOH and HFD in insulin concentrations were also increased following HFD females for any of these measures (Table 2). exposure (PHFD , 0.001, Table 2). However, PC:EtOH- exposed males that consumed a HFD had 2-fold higher Hepatic gluconeogenesis fasting insulin concentration compared with males of other treatment groups (Pinteraction , 0.01, Table 2). This in- Having established that PC:EtOH exposure resulted in teraction of HFD with PC:EtOH resulted in a marked in- metabolic dysfunction, we sought to determine whether crease in the HOMA-IR index. In the GTT, consumption of this was associated with changes in expression of genes

4 Vol. 29 June 2015 The FASEB Journal x www.fasebj.org GARDEBJER˚ ET AL. Figure 2. Plasma glucose clearance following a GTT (A), AUGC generated from the GTT (B), plasma insulin secretion following a GTT (C), total AUIC generated from the GTT (D) with acute ﬁrst- and second-phase insulin secretion (E and F). Plasma glucose concentration following an ITT (G) and the inverted AUGC generated from the ITT (H). All experiments were performed on male and female offspring at 6 months of age. n =8–12 for PC:EtOH (black bars) and U (white bars) groups. For curves: U males (white circles), PC:EtOH males (black circles), U females (white squares) and PC:EtOH females (black squares). Data are represented as mean 6 SEM and compared with the U male group. NS, not signiﬁcant.

PROGRAMMING EFFECTS OF PERICONCEPTIONAL ALCOHOL 5 TABLE 2. Plasma glucose and insulin chemistry of U and PC:EtOH-exposed offspring fed a C diet or a HFD

Treatment group Statistics (P values) U:C PC:EtOH:C U:HFD PC:EtOH:HFD PC:EtOH HFD Interaction

Male Fasting glucose (mmol/L) 7.0 6 0.1 7.6 6 0.2 7.8 6 0.2 8.2 6 0.2 ,0.01 ,0.001 NS Fasting insulin (pmol/L) 315.0 6 70.0a 437.5 6 70.0a 367.5 6 52.5a 892.5 6 105.0b ,0.0001 ,0.001 ,0.01 HOMA-IR index 0.57 6 0.12a 0.86 6 0.15a 0.75 6 0.12a 1.92 6 0.25b ,0.0001 ,0.001 ,0.01 QUICKI index 0.45 6 0.03 0.40 6 0.01 0.41 6 0.01 0.35 6 0.01 ,0.01 ,0.05 NS AUGC (GTT) 1020 6 46 1206 6 47 1054 6 55 1217 6 48 ,0.01 NS NS Total AUIC (GTT) 238 6 59 493 6 86 285 6 39 695 6 88 ,0.0001 NS NS AUIC (ﬁrst phase) (GTT) 26 6 5a 40 6 8a 30 6 5a 78 6 11b ,0.001 ,0.01 ,0.05 AUIC (second phase) (GTT) 194 6 51 422 6 73 235 6 34 565 6 71 ,0.0001 NS NS AUIC/AUGC 0.23 6 0.05 0.41 6 0.07 0.26 6 0.04 0.55 6 0.07 ,0.001 NS NS AUGC (ITT) 1521 6 57 1280 6 94 1316 6 58 1308 6 63 ,0.05 NS NS Female Fasting glucose (mmol/L) 6.9 6 0.2 7.0 6 0.2 7.5 6 0.3 7.4 6 0.4 NS NS NS Fasting insulin (pmol/L) 175.0 6 35.0 227.5 6 35.0 402.5 6 87.5 455.0 6 87.5 NS ,0.01 NS HOMA-IR index 0.31 6 0.07 0.42 6 0.09 0.82 6 0.18 0.93 6 0.20 NS ,0.01 NS QUICKI index 0.51 6 0.03 0.46 6 0.02 0.41 6 0.05 0.42 6 0.03 NS ,0.01 NS AUGC (GTT) 1023 6 21 1115 6 57 1211 6 65 1191 6 57 NS ,0.05 NS Total AUIC (GTT) 190 6 39 277 6 25 466 6 94 502 6 99 NS ,0.01 NS AUIC (ﬁrst phase) (GTT) 17 6 2 25 6 4 42 6 8 45 6 9 NS ,0.01 NS AUIC (second phase) (GTT) 160 6 37 231 6 21 392 6 85 424 6 85 NS ,0.01 NS AUIC/AUGC 0.20 6 0.04 0.26 6 0.03 0.37 6 0.06 0.41 6 0.07 NS ,0.01 NS AUGC (ITT) 1544 6 49 1357 6 69 1263 6 52 1168 6 40 ,0.01 ,0.001 NS

Fasting glucose and insulin concentrations were before GTT, and basal glucose concentrations were before ITT. Data were analyzed with a 2-way ANOVA with post hoc Tukey’s multiple comparison test. NS, not statistically significant. a,bValues with different superscript letters are significantly different from each other (P , 0.05). regulating hepatic gluconeogenesis. We found that PC: adipose tissue between U and PC:EtOH-exposed males. EtOH exposure increased mRNA expression of G6pc In skeletal muscle, there was no significant difference in (PPC:EtOH , 0.01, Fig. 3A), Pck1 (PPC:EtOH , 0.05, Fig. 3C), tAKT2 (U: 1.00 6 0.32 vs. PC:EtOH: 0.77 6 0.11), Ppargc1a (PPC:EtOH , 0.05, Fig. 3D), and decreased ex- pAKTSer474 (U: 1.00 6 0.27 vs. PC:EtOH: 0.70 6 0.17), pression of Gck (PPC:EtOH , 0.01, Fig. 3B) in both sexes. or the pAKTSer474/tAKT ratio (U: 1.00 6 0.20 vs. PC: Overall mRNA expression of Ppargc1a was higher in EtOH: 0.86 6 0.19) between U and PC:EtOH-exposed females compared with males (Psex , 0.001, Fig. 3D), males, respectively (data not shown). whereas Gck was expressed at lower levels in females In C-fed female offspring, protein levels of tAKT2 in ad- than males (Psex , 0.01, Fig. 3B). ipose tissue were similar in PC:EtOH-exposed and U groups The HFD did not affect the gene expression of G6pc, (Fig. 4B), but pAKTThr309 (U: 1.00 6 0.12 vs. PC:EtOH: Pck1,orPpargc1a in males (Table 3). HFD-fed males had 0.26 6 0.16, P , 0.01), the pAKTThr309/tAKT ratio increased gene expression of Gck (PHFD , 0.01), but there (P , 0.01, Fig. 4B), pAKTSer474 (U: 1.00 6 0.12 vs. PC: fi was no signi cant interaction of a HFD with PC:EtOH EtOH: 0.33 6 0.08, P , 0.001), and the pAKTSer474/ (Table 3). In females, the HFD had no effect on G6pc, tAKT ratio (P , 0.001, Fig. 4B) were all significantly Ppargc1a,orGck (Table 3). However, the HFD decreased lower following PC:EtOH. In skeletal muscle, PC:EtOH- gene expression of Pck1 (PHFD , 0.01), and this decrease exposed females had higher protein levels of tAKT was greater in females exposed to PC:EtOH compared with (U: 1.00 6 0.19 vs. PC:EtOH: 1.49 6 0.08, P , 0.05). Both C-fed females (PInteraction , 0.01, Table 3). pAKTSer474 (U: 1.00 6 0.24 vs. PC:EtOH: 0.58 6 0.18) and the pAKTSer474/tAKT ratio (U: 1.00 6 0.25 vs. PC:EtOH: Peripheral insulin signaling 0.50 6 0.30) were lower following PC:EtOH exposure but this did not reach statistical significance (P , 0.11) (data As peripheral insulin insensitivity is often due to altered not shown). insulin signaling, we examined protein expression of AKT2 Protein levels of tGSK3b and pGSK3bSer9/tGSK3b in and GSK3b and their basal serine/threonine phosphory- adipose tissue were similar between all C-fed groups (Fig. lation states in adipose tissue and skeletal muscle in C-fed 4C, D). Similar results for GSK3b were found in skeletal offspring. PC:EtOH-exposed males had higher protein muscle of both sexes (data not shown). levels of tAKT2 (PPC:EtOH , 0.05, Fig. 4A), basal pAKTThr309 (U: 0.71 6 0.34 vs. PC:EtOH: 5.27 6 0.90, P , 0.01), and pAKTThr309/tAKT ratio (PPC:EtOH , 0.05, Fig. 4A) in adi- Fetal liver expression of chromatin modifiers pose tissue compared with U males. Neither pAKTSer474 (U: 1.00 6 0.29 vs. PC:EtOH: 1.11 6 0.31) or the An adverse environment during the PC period may result pAKTSer474/tAKT ratio (Fig. 4A)weredifferentin in epigenetic changes and thus long-term alterations

6 Vol. 29 June 2015 The FASEB Journal x www.fasebj.org GARDEBJER˚ ET AL. Figure 3. The effect of PC:EtOH-exposure (black bars) on hepatic mRNA levels of G6pc (A), Gck (B), Pck1 (C) and peroxisome proliferator-activated receptor-g coactivator a (Ppargc1a)(D) compared with U:C (white bars) in male and female offspring at 8 months of age, n =6–8 per group. Values are expressed as relative gene expression levels normalized to endogenous control ribosomal 18s. Data are represented as mean 6 SEM and compared with the U male group. NS, not signiﬁcant.

in gene expression, which have been implicated as an consumption of a PN HFD exacerbated both fasting underlying mechanism in the development of meta- insulin concentrations and acute first-phase insulin bolic disease (10, 18). We therefore examined expres- secretionduring theGTTmorethan2-foldinPC:EtOH- sion levels of key chromatin modifiers, namely HDACs exposed male offspring relative to PC:EtOH exposure and DNMTs in fetal liver following PC:EtOH exposure. or a HFD alone. Our data demonstrate that PC:EtOH PC:EtOH exposure increased mRNA expression of exposure around the time of conception is sufficient to Dnmt1, Dnmt3a,andDnmt3b in liver from fetuses on cause a prediabetic insulin insensitive state in both male fi E20 (PPC:EtOH , 0.05, Fig. 5A–C)buthadnoeffect and female offspring, with signi cant interactive effects on Hdac2, Hdac3, Hdac4,orHdac6 mRNA levels (data of HFD and PC:EtOH in male but not female offspring. not shown). Analysis of fetal liver mRNA in late gestation demonstrated altered expression of multiple DNMT, suggesting that long-term metabolic outcomes following DISCUSSION PC:EtOH may partly derive from changes in methylation status. Our data demonstrate for the first time that maternal al- Several animal studies have previously linked mater- cohol consumption for a short period exclusively during nal alcohol consumption during pregnancy to insulin the PC period impairs glucose tolerance and decreases resistance and glucose intolerance in offspring post- insulin sensitivity in both male and female adult offspring natally (4, 6, 23). Maternal EtOH exposure throughout at 6 months of age. This metabolic phenotype was associ- pregnancy [gavage of 2g/kg EtOH twice daily, or ;13% ated with increased hepatic gluconeogenesis in both sexes, of energy as EtOH (E%) daily] impairs glucose toler- indicated by increased levels of G6pc, Pck1,andPpargc1a ance in rat offspring at 3 months of age, despite hyper- and decreased levels of Gck mRNA, although increased insulinemia (23). Indeed, persistent hyperinsulinemia fasting glucose concentrations was only apparent in is reported to occur from the first day of PN life in the males. Furthermore, sex-specific alterations in AKT2 sig- rat following maternal EtOH exposure throughout naling were observed in peripheral tissues. Importantly, pregnancy (25% in drinking water, .30E%) (6). This is

PROGRAMMING EFFECTS OF PERICONCEPTIONAL ALCOHOL 7 TABLE 3. Relative mRNA levels of hepatic genes of U and PC:EtOH-exposed offspring fed a C or a HFD

Treatment group Statistics (P values) PC-EtOH: PC- U:C PC-EtOH:C U:HFD HFD EtOH HFD Interaction

Male G6pc 1.09 6 0.19 1.62 6 0.39 1.15 6 0.21 1.40 6 0.28 NS NS NS Gck 1.08 6 0.17 0.80 6 0.34 1.82 6 0.19 1.58 6 0.37 NS ,0.01 NS Pck1 1.08 6 0.17 1.52 6 0.18 1.05 6 0.21 1.34 6 0.21 0.07 NS NS Ppargc1a 1.29 6 0.30 1.66 6 0.34 1.78 6 0.55 2.23 6 0.56 NS NS NS Female G6pc 1.07 6 0.13 2.08 6 0.42 2.06 6 0.40 1.48 6 0.39 NS NS ,0.05 Gck 1.17 6 0.24 0.72 6 0.18 1.11 6 0.25 0.86 6 0.18 NS NS NS Pck1 1.07 6 0.13a,b 1.60 6 0.20b 1.07 6 0.15a,b 0.80 6 0.10a NS ,0.01 ,0.01 Ppargc1a 1.14 6 0.19 1.80 6 0.22 0.84 6 0.15 1.34 6 0.22 ,0.01 0.06 NS

All data were analyzed with a 2-way-ANOVA compared with the U:C group for each sex. Data are a,b represented as mean 6 SEM. NS, not statistically significant. Mean values with different superscript letters are significantly different with post hoc Tukey’s multiple comparison test. Values with different superscript letters are significantly different to each other (P , 0.05).

consistent with our own data that more moderate ma- demonstrated in rats prenatally exposed to alcohol ternal alcohol consumption (6% v/v via aliquiddiet, throughout pregnancy (5). Furthermore, Gck gene ex- ;15E% daily) throughout pregnancy results in hyper- pression was decreased in PC:EtOH-exposed offspring, insulinemia in male but not female rat offspring at consistent with an insulin-resistant phenotype (32). 4 months of age (7). Collectively, these studies highlight Collectively, our data suggest that increased hepatic that maternal alcohol consumption during pregnancy glucose output contributes to the insulin insensitive can alter glucose metabolism in offspring. Here for the phenotype in both PC:EtOH-exposed male and female first time, we report that alcohol consumption (12.5% v/v, offspring. or ;22E%) solely during the PC period (4 days before Although debatable, insulin resistance often preconception until day 4 of gestation) is sufficient to cedes any impairment of b-cell function (33). Blood program similar metabolic responses in offspring later glucose levels can be normal or near normal as the b in PN life. cells hypersecrete insulin to compensate for the de- Although insulin directly inhibits de novo glucose veloping insulin resistance (34). In our study, PC:EtOH- output from the liver to the bloodstream by suppressing exposed offspring displayedonlyminorincreasesin gluconeogenesis (24), it is well characterized that he- fasting insulin and no loss of either first- or second- patic glucose output remains high in an insulin-resistant phase insulin secretion during the GTT. Instead, hy- state (25). Intriguingly, in our study, fasting plasma persecretion of insulin in response to a glucose load was glucose concentrations were increased, especially in observed, indicative of b-cell compensation. Further- males following PC:EtOH exposure, indicating in- more, reduced responsiveness of PC:EtOH-exposed creased hepatic gluconeogenesis (26). In contrast, PC: offspring to exogenous insulin (ITT) confirmed an EtOH-treated females were euglycemic and exhibited insulin-insensitive phenotype. Therefore, our results better insulin sensitivity (lower HOMA-IR and higher support the notion that the effect of PC:EtOH exposure QUICKI indices) than males. To further examine glu- is most probably attributed to dysregulation in tissue- coneogenesis in our animals, we investigated alterations specificinsulinsignaling(insulininsensitivity)andre- in hepatic gene expression. We found that PC:EtOH sultant pancreatic b-cell compensation, rather than PC: exposure increased the relative gene expression of the EtOH exposure causing a direct pancreatic defect, such rate-limiting gluconeogenic enzyme Pck1 (27). Rela- as b-cell failure (8, 17). tively small increases in Pck1 gene expression are known We consequently investigated AKT2 activation in to be sufficient to increase hepatic gluconeogenesis and adipose tissue and skeletal muscle, which is necessary impair glucose tolerance (28). Interestingly, glucose for GLUT4 translocation and insulin-mediated glucose intolerance associated with increased hepatic Pck1 ex- uptake (8, 24). Because consumption of the HFD did pression has also been demonstrated in offspring fol- not exacerbate the already impaired insulin sensitivity, lowing prenatal protein restriction (29) and maternal we quantified AKT2 levels only in U and PC:EtOH- glucocorticoid administration (30). Levels of Ppargc1a exposed C-fed offspring. Given the phenotypes of im- mRNA, a transcription factorthatstimulatestheex- paired glucose tolerance and insulin insensitivity in pression of Pck1 and G6pc (31), were also increased PC:EtOH offspring, we expected AKT2 activity to be following PC:EtOH exposure as were levels of G6pc decreased in peripheral tissues. Indeed, female off- mRNA, despite hyperinsulinemia. Increased gluconeo- spring exposed to EtOH during the PC period had genesis associated with increased basal gene expres- decreased AKT2 phosphorylation in adipose tissue sion of both Pck1 and Ppargc1a has previously been (Ser474 and Thr309), and in skeletal muscle Ser474

8 Vol. 29 June 2015 The FASEB Journal x www.fasebj.org GARDEBJER˚ ET AL. Figure 4. The effect of PC:EtOH exposure (black bars) on protein levels in white intra-abdominal adipose tissue in male and female offspring at 8 months of age compared to U:C (white bars), n =4–6 per group. Total (t)AKT2 levels, phosphorylated (p) AKTThr309/tAKT ratio and the pAKTSer474/tAKT ratio in males (A) and females (B). tGSK3b and the pGSK3bSer9/tGSK3b ratio in males (C) and females (D). Values for the protein levels are normalized to b-actin. Data are represented as mean 6 SEM. *P , 0.05; **P , 0.01; ***P , 0.001 by Student’s t test.

phosphorylation tended to be decreased. Such de- and may be a direct result of increased basal insulin creases in phosphorylation of AKT2 are consistent levels (40% higher in PC:EtOH-exposed males). with lower basal kinase activity (Thr309) and reduced Moreover, the ratio of Thr309 phosphorylation to total “full” kinase activity in response to insulin (Ser474) AKT2 was also increased in adipose tissue of PC:EtOH- (35). Paradoxically, in PC:EtOH-exposed male off- exposed male offspring, afﬁrming the idea of increased spring, there was an increase in tAKT2 in adipose tis- insulin signaling in this tissue. These apparently disparate sue, which might improve insulin sensitivity (36). results in adipose tissue of male PC:EtOH-exposed off- Similar increases in tAKT2 have been demonstrated spring require further investigation as increased phos- in skeletal muscle of twin sheep offspring exposed to phorylation at Thr309 together with tAKT2 may be PC undernutrition (37), and in male but not female related to signaling pathways mediating adipogenesis offspring of obese mice (38). Such up-regulation of and/or angiogenesis (39, 40). Notwithstanding these sex- tAKT2 levels is possibly a compensatory mechanism speciﬁc effects on insulin signaling in peripheral tissues,

PROGRAMMING EFFECTS OF PERICONCEPTIONAL ALCOHOL 9 proteins, respectively. Maternal alcohol consumption (E1–E7) has previously been linked to increased adult hepatic gluconeogenesis in association with increased class II HDAC protein activity (42). Although we did not observe changes in fetal liver Hdac mRNA expression, we cannot rule out the possibility that protein activity of these chromatin modifiers is altered in our model to impact on chromatin accessibility. Levels of expression of Dnmt genes, however, were significantly increased in the fetal liver at E20 suggesting long-term alterations in methylation status. This is consistent with other recently published datashowingdysregulationof hippocampal DNMT activity without changes in HDAC activity in a rat model of early life alcohol exposure (43). It is tempting to speculate that increased Dnmt expression and consequent hypermethylation may provide the link between PC:EtOH and alterations in gene expression associated with the metabolic phenotype observed. Consistent with our data, Ppargc1a expression is reduced by hypermethylation of the PPARGC1A promoter in patients with diabetes (44) and correlates positively with fasting plasma insulin levels and HOMA-IR (45). Other studies have demonstrated altered insulin and glucose dynamics following maternal PC methionine deficiency in sheep (18) and rats (41). Methionine provides methyl groups for the production of S-adenosyl methionine, a substrate for DNMTs. Significantly, we have previously demonstrated decreased expression of the major methionine transporter, Slc38a2, in the placenta following PC:EtOH (14). Intriguingly, global DNA methylation is increased in response to either methionine or choline deficiency through pregnancy (18, 46), and this is associated with increased expression of Dnmts, which is driven by hypomethylation of the Dnmt1 promoter (46). Data from mice suggest that a perturbed preimplantation environment can also alter levels of the de novo Dnmt3l (47). This potentially impacts on de novo genomewide methylation following resetting of epigenetic marks that occurs during this stage are also consistent with our data. Early embryonic alcohol exposure has also been demonstrated to result in allele-specific changes in methylation patterns of the H19/Igf2 domain Figure 5. The effect of PC:EtOH exposure (black bars) on in the placenta of mice, which may contribute to growth fetal hepatic mRNA levels of DNA methyltransferase (Dnmt)1 restriction (48). (A), Dnmt3a (B), and Dnmt3b (C) compared with U offspring (white bars) in males and females on E20, n =9–11 per group. In conclusion, our data establish that maternal con- Values are expressed as relative gene expression levels normal- sumption of alcohol during the PC period programs ized to endogenous control ribosomal 18s.Dataarerepresented impaired glucose tolerance and insulin insensitivity in as mean 6 SEM and compared with the U male group. NS, not offspring, which was associated with altered expression of significant. key modifiers of fetal methylation status. Although these conditions are evident in both males and females, dysregulation of peripheral insulin signaling appeared to be sexually dimorphic with male offspring being more sus- our data suggest maternal alcohol consumption during ceptible than female offspring to a combination of PC: the PC period programs a phenotype that is consistent EtOH exposure and a PN HFD. These novel findings have with metabolic dysfunction and insulin resistance. important clinical implications for women wanting to There is growing evidence that perturbations conceive and bear healthy children. around periconception can result in epigenetic mod- fi i cations such as DNA methylation or histone acetyla- The authors acknowledge the funding provided by the tion, which have been implicated as an underlying National Health and Medical Research Council of Australia mechanism in the development of metabolic dis- (1046137), and thank Kerri Tyrell, School of Biomedical ease (10, 18, 41). Key effectors are DNMTs, histone Sciences, The University of Queensland, for expert assistance acetyltransferases, and histone deacetylase (HDAC) with the insulin assay.

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12 Vol. 29 June 2015 The FASEB Journal x www.fasebj.org GARDEBJER˚ ET AL.