Anti-Mullerian Hormone as a Marker of Oocyte Quantity ...

Anti-Mullerian Hormone as a Marker of

Oocyte Quantity, Developmental Potential, and Fetal Sex

by

Anja Stojsin Carter

A Thesis Presented to

The University of Guelph

In partial fulfillment of requirements

for the degree of

Doctor of Philosophy

in

Biomedical Sciences

Guelph, Ontario, Canada

© Anja Stojsin Carter, December 2016

ABSTRACT

ANTI-MULLERIAN HORMONE AS A MARKER OF OOCYTE QUANTITY,

DEVELOPMENTAL POTENTIAL AND FETAL SEX

Anja Stojsin Carter Advisor:

University of Guelph, 2016 Professor W. A. King

Delayed childbearing age, increased environmental pollutants accompanying modern life

style, and an increase in inbreeding due to high demand for milk and meat yield have resulted in

the decline in human and bovine reproduction respectively. Anti-Mullerian hormone (AMH) is

expressed starting from 7-8 weeks of gestation in males and 20 weeks of gestation in females, in

up to 100x higher concentration in males. AMH has been described as a non-invasive and

accurate marker of ovarian quantitative fertility parameters in both humans and cattle. However,

it is still unknown how AMH levels correlate to different fertility parameters in different cattle

breeds; can AMH levels in the mother be used as a fetal sex marker during pregnancy in cows?

In humans, can AMH collected in the single follicular fluid (mono FF), as well as granulosa cell

(GC) AMH receptor 2 (AMHR2) be used as an embryo developmental potential marker? Here

we present evidence of the higher levels of systemic and follicular AMH in Zebu compared to

European cattle, corresponding to higher levels of AFC and oocytes. Cows pregnant with a male

fetus, as compared to a female fetus, were observed to have a significantly different change in

plasma AMH between day 35 and 135 during gestation. The placenta and cotyledon were found

to express AMHR2 between day 38 and 80, however not significantly different between

pregnancies with an opposite sex fetus. In the human study, systemic and average mono FF

AMH, and average mono GC AMHR2 expression were significantly negatively correlated with

the patient’s blastocyst rate. When patients were divided into normal and high groups based on

the their systemic AMH levels, the following was observed: normal systemic AMH level patients

had a lower average FF AMH level and a higher blastocyst rate compared to the higher systemic

AMH level patients. Also, in normal systemic AMH patients, blastocysts corresponded to

follicles with a lower level of AMH, while in high systemic AMH patients blastocysts

corresponded to follicles with a higher level of AMH.

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DECLARATION OF WORK PERFORMED

I declare that, with the exception of the items indicated below, all the work reported in

the body of this thesis was performed by me.

Cattle ovaries and reproductive tracts were collected by Pradeep Blaraju, Steven Huang,

Heather Smale, Stephan Botha, and Brooklin Rushton during the course of these studies. Media

used in Canada for oocyte in vitro maturation, in vitro fertilization, and in vitro culture were

prepared by Liz St. John. Real time qPCR experiments in Chapter I were performed by Kiana

Mahboubi. Cell culture and DNA extraction were performed by Dr. Olutobi Oluwole. Antral

follicle count, ovary diameter measurements, serum collections, slaughterhouse ovary collection,

bovine anti-Mullerian hormone ELISA measurements, and fetal serum collection in Brazil were

performed with the help of Dr. Moyses Miranda, Dr. Otavio Ohashi, Dr. Nathalia Nogueira, Dr.

Tiago de Bem, Rodrigo de Morais, Cinthia Lopes, Mayra Costa, Alessandra Ximenes, Tobias

Sovernigo, and Marcus Filho. ONE Fertility patient consents were obtained by Melody

Rasmussen and Maja Smrzlic. Human anti-Mullerian hormone ELISA measurements were

performed by Alexandra Marinic-Cowden. Human follicular fluid collections were performed by

Michael Neal. Human in vitro fertilization, culture, embryo assessment and transfer were

performed by Katie Willoughby, Lisa Deys, and Lindsay Moffatt. Daniel Gillis performed most

of the statistical analysis.

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ACKNOWLEDGEMENTS

First and foremost I would like to thank my supervisor Dr. Allan King. Allan provided

me with the opportunity to work in his lab twice, doing a research project during the last year of

my undergraduate degree, and then for my PhD, for which I was able to do a project highly

relevant to my interests and goals. I was also given the opportunity to collaborate with a human

fertility clinic and stay in close contact with the field in which my findings could have an impact.

I also have to thank Allan for the opportunity to go on a research exchange to Brazil, to work

with his collaborators in Belem, Para. Last but not least, Allan has been incredibly understanding

of my personal life; I got married and had a baby after the second year of my degree. Allan

organized the baby shower and allowed me to pursue motherhood in parallel with work on my

thesis. The people Allan gathered around himself are all brilliant and I had the honor of being

part of his team.

I would like to thank Dr. Pavneesh Madan for his support throughout my project and his valuable

input on the project progression and experiment planning. Dr. Madan also helped me

troubleshoot through my immunofluorescence and confocal microscopy work, and was

encouraging throughout my manuscript writing.

I would like to thank Dr. Neil MacLusky for guidance and support during my committee

meetings and for his help with some of my statistics questions. Neil is a very sweet,

approachable and genuine person, finding time to talk to students and allowing them to feel like

one of his colleagues.

I would like to thank Mike Neal, ONE Fertility Burlington scientific director, for giving me the

opportunity to collaborate, for his enthusiasm, for help with writing the ethics protocols,

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abstracts and manuscript, and for enabling me to collect valuable sample material, attend

conferences, and extend my research opportunities by including a human study.

I would like to thank Dr. Julang Li, my external committee member, for kind words, support and

guidance.

I would like to give a special Thank You to Dr. Laura Favetta. Dr. Favetta was my advisor, my

friend, my sister, my parent. I met Laura during my undergraduate degree project and she has

provided me with infinite help since then. It was an honor knowing Dr. Favetta, with her devoted

and passionate approach to students and teaching. Dr. Favetta’s knowledge on qPCR and

endocrinology kept me going in the right direction!

I would like to thank Dr. Daniel Gillis for his immense help and patience in performing majority

of the statistical analysis in this thesis.

I would like to thank Liz St. John for her help with ovary and placenta collections, support in any

lab related issues, and who, with her kindness, never intimidated the students around her.

I would like to thank Dr. Monica Antenos for sharing her knowledge, and providing incredible

support in the lab, where she created a friendly, relaxed, but very stimulating atmosphere.

I would like to thank Ed Reyes and Allison MacKay for their technical support and patience,

dealing with ordering supplies and questions at, often, inconvenient times.

I would like to thank Helen Coates for her patience and help with confocal microcopy. I would

like to thank Dr. Tamas Ravay for his valuable input in qPCR and immunofluorescence and

molecular troubleshooting. Dr. Ravay was also more than just a colleague; he was a friend and a

support throughout this project.

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I would like to thank Kiana Mahboube, a Masters student, who worked on part of my project and

helped incredibly with qPCR work, and who has also been a close friend and support.

I would like to thank to Dr. Stalker, Kata Ozs, and Dr. Petrik for their help with troubleshooting

experiments and cell material.

I would also like to thank our collaborators and extended family in Brazil, Dr. Miranda, Dr.

Ohashi, Dr. Costa, Dr. de Bem, and many others. Without your input this project would have

been so much more boring. I loved my experience in Brazil, and thank you for providing me

with so many opportunities to examine and learn so much about your beautiful cattle: Bos taurus

indicus.

I would also like to extend my gratitude to the team at ONE Fertility, Burlington. Thank you to

the embryologists: Katie, Lindsay, and Lisa for their patience to have me in the lab during their

busy schedules, to have patients answer my questions, and to trust me to help them with some of

their media preparations and case setups. I also would like to thank the andrology team: Tiffany

and Leanne for allowing me to use some of their space to prepare research samples. I would like

to thank the staff: Melody, Maja and Alexandra for their help with patient consent forms and

running the human ELISA. Last but not least, I would like to thank Dr. Karnis, Dr. Amin, Dr.

Huges and Dr. Faghih for their trust and the opportunity to collaborate.

This research would have not been possible without the financial support from the OVC Doctoral

Scholarship, The Natural Sciences and Engineering Research Council of Canada (NSERC),

Canada Research Chair (CRC), and North/South Animal Biology and Reproductive

Biotechnology Consortium- Canada/Brazil Doctoral Student Research Exchange.

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I would now like to thank my friends and family all around the world. I would like to thank my

friends in Canada: Carolyn, Sarah, Jacky, Tobi, Kayla, Allison, Carmon, Leslie, Stewart,

Graham, Faz, Anh, Nayoung, Jyoti, Nina, Anuja, Moez, Ari and many others in the Biomedical

Sciences Department, including staff Kim Best and Frances Graziotto, for their friendship and

support. I would like to thank especially my friend Gilan Abdelaal, who was there for me

through the good, bad and the ugly. I would like to thank my former high school teacher Dragan

Gajic, for his love and passion for science that molded my undergrad and grad scientific path. I

would like to thank my family in Canada, my in-laws Ludy and Ron, who provided me with

support and kind words, lots of tasty food, and babysitting hours. I also owe a big Thank You to

Ludy who was kind enough to go through my thesis and correct all the grammar and spelling. I

would like to thank my friends and colleagues outside of Canada: Sara, Tanja, Jelena, Vera,

Christina, Magda, Nathalia, Priscila, Cinthia, and many others for being there for me. Also, I

would like to thank my past employer, Dr. Zorica Crnogorac-Ilic, for her passion in helping

patients, the opportunity to work in her team, as well as her support in my idea to peruse a

doctorate degree. I would like to thank my extended family, my aunts and uncles, my cousins,

and my dad Radomir and his family for their support.

Now I would like to thank my close family, my grandpa, Bogomir, my mom, Vera and her

partner Slobodan, my son Aleksandar and my husband Timothy for always being my rock and

my inspiration. Hvala Vam!

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TABLE OF CONTENTS

DECLARATIONOFWORKPERFORMED......................................................................................................IVACKNOWLEDGEMENTS......................................................................................................................................VLISTOFTABLES..................................................................................................................................................XILISTOFFIGURES................................................................................................................................................XIILISTOFABBREVIATIONS................................................................................................................................XVINTRODUCTION....................................................................................................................................................1LITERATUREREVIEW.........................................................................................................................................5HUMANASSISTEDREPRODUCTIONTECHNOLOGIESTODAY.............................................................................................5INVIVOREPRODUCTION.........................................................................................................................................................10ESTROUSCYCLE.......................................................................................................................................................................11ANTI-MULLERIANHORMONE..............................................................................................................................................13ANTI-MULLERIANHORMONERECEPTOR2......................................................................................................................15AMHinmales.......................................................................................................................................................................16AMHinfemales....................................................................................................................................................................17

AMHASACLINICALMARKEROFOVARIANRESERVE.......................................................................................................19AMHASANOOCYTEANDEMBRYODEVELOPMENTALPOTENTIALMARKER...............................................................21FromHumanSerum..........................................................................................................................................................21FromHumanFollicularFluid.......................................................................................................................................23

AMHASAPCOS,DORANDCANCERMARKER.................................................................................................................24COWASAMODELFORHUMANREPRODUCTION................................................................................................................25DAIRYANDBEEFCOWFERTILITY........................................................................................................................................26ANTI-MULLERIANHORMONEINCATTLE...........................................................................................................................27BOSTAURUSTAURUSVS.BOSTAURUSINDICUS..................................................................................................................28AMHASAFETALSEXMARKER............................................................................................................................................30HUMANVS.BOVINEPLACENTA............................................................................................................................................33

RATIONALE,HYPOTHESIS,ANDOBJECTIVES..........................................................................................36RATIONALE..............................................................................................................................................................................36HYPOTHESIS............................................................................................................................................................................37OBJECTIVES..............................................................................................................................................................................37

CHAPTERI...........................................................................................................................................................38SYSTEMICANDLOCALANTI-MULLERIANHORMONEREFELCTSDIFFERENCESINTHEREPORDUCTIONPOTENTIALOFZEBUANDEUROPEANCATTLE.....................................................38INTRODUCTION.................................................................................................................................................................39MATERIALANDMETHODS...........................................................................................................................................41AnimalsandExperimentalDesign..............................................................................................................................41IVF.............................................................................................................................................................................................42ELISA........................................................................................................................................................................................43RNAextractionandreversetranscription..............................................................................................................44RealTimequantitativePCR...........................................................................................................................................45Statistics.................................................................................................................................................................................46

RESULTS................................................................................................................................................................................48Studygroup1.......................................................................................................................................................................48Studygroup2.......................................................................................................................................................................48

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DISSCUSION..........................................................................................................................................................................53CHAPTERII..........................................................................................................................................................56PREGNANCYANTI-MULLERIANHORMONEASAFETALSEX-DETERMININGFACTOR...............56INTRODUCTION.................................................................................................................................................................57METHODS..............................................................................................................................................................................59AnimalsandExperimentalDesign..............................................................................................................................59DNAextractionandsexconfirmationusingTSPY...............................................................................................62RNAextractionandreversetranscription..............................................................................................................63RealtimequantitativePCR............................................................................................................................................63ELISA........................................................................................................................................................................................63Statistics.................................................................................................................................................................................64

RESULTS................................................................................................................................................................................65Studygroup1.......................................................................................................................................................................65Studygroup2.......................................................................................................................................................................66Studygroup3.......................................................................................................................................................................66

DISCUSSION..........................................................................................................................................................................69CHAPTERIII........................................................................................................................................................76HUMANMONOFOLLICULARANTI-MULLERIANHORMONEINRELATIONTOOOCYTEDEVELOPMENT..................................................................................................................................................76INTRODUCTION.................................................................................................................................................................77METHODS..............................................................................................................................................................................81PatientsandExperimentalDesign.............................................................................................................................81MonofollicularSampleCollectionandIVF..............................................................................................................82ELISA........................................................................................................................................................................................83Cellculture............................................................................................................................................................................83RNAextractionandreversetranscription..............................................................................................................84RealTimequantitativePCR...........................................................................................................................................84

RESULTS................................................................................................................................................................................86AMHperpatient:................................................................................................................................................................86AMHperindividualfollicles:..........................................................................................................................................86

DISCUSSION..........................................................................................................................................................................91GENERALDISCUSSION.....................................................................................................................................96SUMMARY,CONCLUSIONS,ANDFUTUREDIRECTIONS.......................................................................107LITERATURECITED........................................................................................................................................110APPENDIX..........................................................................................................................................................129APPENDIXI:DATAFROMCHAPTERII,STUDYGROUP1..............................................................................................129APPENDIXII:THECONSENTFORM...................................................................................................................................130APPENDIXIII:MONOFOLLICULARSAMPLECOLLECTIONINSTRUCTIONS..................................................................133APPENDIXIV:PROTOCOLFORTHEMONOFOLLICULAROOCYTECOLLECTION.........................................................135APPENDIXV:MODIFIEDCYCLESHEET...........................................................................................................................136

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LIST OF TABLES

Table 1 Real Time PCR primers………………………………………………………………...46

Table 2 Summary of antral follicle count (AFC), ovary diameter (OD), plasma anti-Mullerian hormone (Pl AMH) from Study group 1, and follicular fluid AMH (FF AMH), oocyte, cleavage and blastocyst rate mean values (± SE) from Study group 2 for European type (E), Zebu (Z) and crossbred (C) cattle and the p-values from their average value comparisons. Significant difference (p<0.05) is indicated by the symbol (*)………………………………………………50



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LIST OF FIGURES

Figure 1 Correlations between anti-Mullerian hormone (AMH) and reproductive parameters in European type (E, light gray square), Zebu (Z, black triangle) and crossbred (C, dark grey diamond) cattle. The plots show simple linear regression trend lines for each of the breeds but that they do not reflect the model that was used in the statistical analysis. A) represented Study group 1 and B) represented Study group 2. Ai) Plasma AMH (Pl AMH) vs. antral follicle count (AFC) for E (n=7), Z (n=30) and C (n=6) animals. Z correlation, ρ=0.54, p=0.002; Z to E comparison, p=0.004; C to E comparison, p=0.049. Aii) Pl AMH concentration vs. ovarian diameter (OD) in E (n=6), Z (n=26) and C (n=6) animals. Z correlation, ρ=0.36, p=0.067; Z to E comparison, p=0.009; C to E comparison, p=0.094. Bi) Pl AMH vs. average number of oocytes per pair in Z (n=12; ρ=0.818, p=0.002); Bii) Follicular fluid AMH (FF AMH) concentration vs. number of oocytes in Z (n=24), and E (n=59) cattle. E correlation, ρ=0.37, p=0.005; Z to E comparison, p<0.0001. Biii) FF AMH concentration (ng/ml) vs. AFC in E (n=56; ρ=0.35, p=0.009)………………………………………………………………………………………….51 Figure 2 A) Relative granulosa cell anti-Mullerian hormone (GC AMH) mRNA expression in low vs. high oocyte producing ovaries for European type (grey, n=56) and Zebu (black, n=10) cattle. B) Relative GC AMH and anti-Mullerian hormone receptor 2 (AMHR2) mRNA expression in low (light gray) vs. high (dark gray) oocyte producing ovaries for European type cattle (n=56) was found to be significantly different (p=0.035). Glyceraldehyde 3-phosphate dehydrogenase housekeeping gene used to determine relative expression level, error bars denote the standard error of the mean (SEM) and significant difference (p<0.05) is indicated by the symbol (*)………………………………………………………………………………………..52 Figure 3 Visual representation of the three study groups for the Chapter 2. Horizontal line represents the time line of gestation divided into the three trimesters and each trimester into three months starting with artificial insemination (AI) of the cow and ending at birth. Literature based fetal expression of AMH is represented by either blue for male at 60 days or red for female at 150 days, with large and small arrows corresponding to the level of expression. In dark red: Study group I, collections at day 0, 35, 135 and 275 and study group II collections from 85 to 155 days of gestation and study group III collections from 38 to 80 days of gestation. In yellow: (Empey et al., 2012; Fanchin et al., 2007) detected significant difference in maternal blood AMH levels between male and female fetuses in humans in between 11th and 15th week of pregnancy, approximately corresponding to 77 and 105 days of gestation……………………………………………………………………………...…………. 61 Figure 4 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in cows Bos taurus indicus during gestation at 2 time periods, between day 35 and 135 (purple), and between day 135 and 275 (orange) carrying male (M; n=5) vs. female calves (F; n=3). A) Y-axis represents change in Pl AMH between M and F at two time periods, first time period found to be significantly different between M and F (p= 0.036), indicated by the symbol (*). B) Y-axis represents relative change in Pl AMH in terms of its previous value, example: Δ Pl AMH (day x - day y) / Pl AMH (day y). Error bars denote the standard error of the mean (SEM)………………………………………………………………………………….67

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Figure 5 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in Bos taurus indicus cows (with male, n=10, in blue and with female, n=11, in red) and fetus (male, n=10, in green and female, n=11, in purple) at single time points throughout pregnancy, between day 85 and 155, fetus size from 15cm to 45 cm A) Graph represents average level of Pl AMH of pregnant cow and fetus for period from 85 to 155 days, sex denoted as male (M) and female (F). Difference between the cows was not significant (p=0.560), however differences that were significant were between the female fetuses and cows with those female fetuses (*, p<0.05), between the male fetuses and the cows with those male fetuses (**, p<0.05), and the male and female fetus (***, p<0.05). Error bars denote the standard error of the mean (SEM). B) Graph represents relationship between pregnant cow with male (green triangle) or female fetus (purple cross), or male (blue rhombus) or female fetus (red square) Pl AMH and fetus size in cm…………………………………………………………………………………...68 Figure 6 Graphs representing relative AMHR2 RNA expression from male (blue; n=6) and female (red; n=7) cotyledon (Cot.) and male (M. in blue; n=2) and female (F. in red; n=3) placenta (Plac.) during 1st trimester in Bos taurus taurus. A) Male vs. female relative AMHR2 RNA expression from cotyledon only, gestation days 38 to 76 for male, and 56 to 80 for female. B) Male vs. female cotyledon and placenta relative AMHR2 RNA expression. Gestation days from placenta samples 42 to 46 for males, and 70 to 80 for females. AMHR2 RNA was compared to two housekeeping genes Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A to determine relative expression level. Error bars denote the standard error of the mean (SEM)…………………………………………………………………………68 Figure 7 Model describing the fetal testicular AMH secretion 1000x higher than the fetal ovarian AMH secretion and 100x higher than the cow’s ovarian secretion observed between day 85 and 155 of gestation. Model proposes that male fetal AMH crosses placenta and enters maternal circulation leading to the rise in the cow’s Pl AMH compared to the cows that carry female fetuses observed between day 35 and 135 of gestation……………………………….…………75 Figure 8 Anti-Mullerian hormone (AMH) per patient based approach. Correlations between AMH level, its relative receptor transcript amount and embryo development potential in six patients. Ai) Serum AMH (SE AMH) (pmol/l) vs. Average follicular fluid (FF) AMH (pmol/l) (p=0.017). Aii) SE AMH concentration (pmol/l) vs. Average relative GC AMHR2 RNA expression. Aiii) SE AMH (pmol/l) vs. Antral follicle count (AFC); Bi) SE AMH concentration (pmol/l) vs. Blastocyst rate (blast rate) (p=0.015). Bii) Average relative GC AMHR2 RNA expression vs. blast rate p=0.036. Biii) Average FF AMH concentration (pmol/l) vs. blast rate p=0.036…………………………………………………………………………………………..88 Figure 9 Comparisons between individual follicles serum (SE) AMH (pmol/l), average follicular fluid (FF) AMH (pmol/l), relative GC AMHR2 RNA expression, oocyte number and blastocyst (blast) rate between patients (n=3; blue) with “normal” 1.93-2.62 ng/ml and patients (n=3; red) with “high” between 4.21-6.79 ng/ml (x 7.14 to be converted to pmol/l). Significant difference was observed between “normal” and “high” groups for SE AMH, FF AMH and blast rate (p=0.048, p=0.038, and p=0.038, respectively). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression

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level. Error bars denote the standard error of the mean (SEM) and significant difference (P<0.05) is indicated by the symbol (*)……………………………………………………………………89

Figure 10 Comparisons between average of individual follicles that gave rise to blastocyst (red/blue) and non blastocyst (green) for each patient being from either “high” (i) or “normal” (ii) SE AMH groups, 4.21-6.79 ng/ml or 1.93-2.62 ng/ml respectively. Ai) Average Mono follicular fluid (FF) AMH (pmol/l) in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Aii) Average Mono FF AMH (pmol/l) in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Bi) Average FF AMH/SE in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Bii) Average FF AMH/SE in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Ci) Average relative GC AMHR2 RNA expression in “high” patient group from blast vs. non blast follicles respectively, patient 2 (n=1, n=1), patient 3 (n=3, n=1); Cii) Average relative GC AMHR2 RNA expression in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=1), patient 5 (n=4, n=2). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression level, and error bars denote the standard error of the mean (SEM)…………90

Figure 11 Ovaries from high and normal SE AMH patient groups with oocytes that developed to blastocysts corresponding to high FF AMH in red or low FF AMH in blue respectively, compared to oocytes that did not develop to blastocysts corresponding to FF AMH in green for both patient groups……………………………………………………………………………….95

Figure 12 “Size matters concept” representation of the ovary in which the ovarian size is positively correlated to: the ovarian reserve, the ovarian function (based on the oocyte developmental potential), and the systemic AMH level. However it is negatively correlated to the ovulatory follicular AMH level………………………………………………………………...106

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LIST OF ABBREVIATIONS

AMH Anti-Mullerian Hormone

AFC Antral follicle count

IVP In vitro production

GC Granulosa cell

FF Follicular fluid

ART Assisted reproduction technologies

MOET Multiple ovulation and embryo transfer

AMHR2 Anti-Mullerian hormone receptor 2

SEF Social egg freezing

IVF In vitro fertilization

WHO World Health Organization

EDC Endocrine disrupting chemicals

HPG Hypothalamic-pituitary-gonadal axis

FSH Follicle stimulating hormone

LH Luteinizing hormone

FSHRc Follicle stimulating hormone receptor

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IGF Insulin growth factor

cAMP Cyclic adenosine monophosphate

MII Metaphase II

MIS Mullerian inhibiting substance

TF Transcription factor

SF1 Sterioidogenic factor 1

WT1 Wilms’ tumor associated protein 1

TGF-beta Transforming growth factor beta

BMP Bone morphogenic proteins

GDF Growth and differentiation factor

GDNF Glial cell-derived neurotrophic factor

SBE Smad binding element

AMHR1 Anti-Mullerian receptor 1

Alk3 Activin-like kinase 3

Bmpr1a Bone morphogenic protein receptor 1a

SRY Sex determining region of Y chromosome

MMP Metalloproteinase

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PCOS Polycystic ovarian syndrome

OHSS Ovarian hyperstimulation syndrome

OPU Ovum pick-up

DOR Diminished ovarian reserve

KGN Ovarian granulosa-like tumor cell line

AI Artificial insemination

BCS Body condition score

Taurus/ European Bos taurus taurus

Indicus/ Zebu Bos taurus indicus

CL Corpus luteum

Pl Plasma

OD Ovarian diameter

COC Cumulus oocyte complex

IVM In vitro maturation

SOF Synthetic oviductal fluid

BSA Bovine serum albumin

ELISA Enzyme linked immunosorbent assay

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dNTP Deoxyribonucleotide triphosphates

qPCR Real time quantitative PCR

GAPDH Glyceraldehyde-3-Phosphate Dehydrogenase

H2A Histone 2A

YWHAZ Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase

activation protein

HPRT1 Zeta hypoxanthine guanine phosphoribosyl transferase 1

SDHA Succinate dehydrogenase complex, subunit A

Glht General liner hypothesis test

PGD Preimplantation genetic diagnosis

AFP Alphafetoprotein

TSPY Testes-specific protein Y

PPIA Peptidylprolyl isomerase I

hCG Human chorionic gonadotropin

TLM Time-lapse microscopy

Mono FF Monofollicular

SE Serum

2PN 2 pronucleus

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REB Research Ethics Board

TESA Testicular sperm retrieval

ONE Ontario Network of Experts

FBA Fetal bovine serum

eGFP Enhanced Green Fluorescent Protein

1

INTRODUCTION

Understanding ovarian physiology has both biological and economic importance. The

ovary’s main role is to produce reproductive hormones and to house follicles, structures

enclosing oocytes. Follicle number is established during embryogenesis and rapidly decreases

towards birth and puberty. The time between puberty and menopause represents the reproductive

life during which <1% of follicles will leave their dormant state and become recruited towards

ovulation (Malek et al., 1998; Oktem and Oktay, 2008). The mechanism controlling this switch

between dormancy and activation is under strict paracrine and endocrine control. Strict paracrine

control ensures that individuals do not exhaust their ovarian reserve prematurely, allowing for

maximized propagation of genetic material and survival of the species.

Anti-Mullerian hormone (AMH) is one of the paracrine factors involved in the regulation

of follicle recruitment. In the female, AMH is secreted by the ovary and inhibits premature

primordial follicle activation. It has been shown that ablation of this hormone causes premature

menopause in mice (Durlinger et al., 1999; Pereira et al., 2013). In males, AMH is expressed

earlier during embryogenesis in almost a hundred times higher concentration than in females,

ensuring inhibition of Mullerian ducts that represent the embryological origin of the oviducts,

uterus and upper part of the vagina (Sandvig and Llorente, 2012; Teixeira et al., 2001). In

females, expression of AMH starts a few months later and in much lower concentration, reaching

its peak in puberty. The levels in the female have been shown to reflect reproductive aging,

ovarian reserve, number of growing follicles or antral follicle count (AFC), ability to respond to

superovulation drugs, and number of oocytes retrieved during in vitro production (IVP)

(Anderson et al., 2012; J. J. Ireland et al., 2011; La Marca et al., 2009; Malek et al., 1998).

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AMH function has been explored at cellular, follicular, ovarian, individual, population,

subspecies, and species level. At the cellular level, AMH has been shown to be expressed by

both Sertoli and granulosa cells (GCs) signaling in both an autocrine and paracrine fashion to

cells of near proximity. Since AMH is expressed at highly different concentrations and times

between sexes, it has been speculated that it might be utilized as a sex-determining marker

during early pregnancy (Empey et al., 2012; Malek et al., 1998). At the follicular level, AMH is

expressed by preantral growing follicles, keeping the remaining primordial follicles in a

dormancy stage, and possibly reflecting the enclosed oocyte’s developmental potential

(Brownbill et al., 1995; Takahashi et al., 2008). At the ovarian level, AMH from pooled

follicular fluid (FF) has been shown to correlate to overall pregnancy rates in humans (Duc-

Goiran et al., 2006; Wunder et al., 2008). Measured in serum and/or plasma, individual AMH

levels have been shown to be consistent between estrous cycles, independent of the

hypothalamic-pituitary-gonadal axis, and correlated to pooled FF levels (Morgan et al., 2011;

Rico et al., 2009; Wang et al., 2009; Wittmann and McLennan, 2011). When examined at the

population level, AMH displays highly variable levels among individuals with different ovarian

potential (Barker, 1944; J. L. H. Ireland et al., 2008). When examined between cattle subspecies

Bos taurus taurus and Bos taurus indicus, a specific AMH range has been shown to be

characteristic of each subspecies (Batista et al., 2014; Firoozi et al., 2009; Hocher et al., 2009;

Walsh et al., 2015). At the species level, there are species specific average serum AMH levels

(Kumar et al., 2013; Stephen et al., 2002).

Human assisted reproduction technologies (ART) and cattle industry in vitro production

(IVP) have a common problem: decreasing fertility. Two of the main factors causing infertility in

women are the increasing age of first time mothers and exposure to environmental stressors

3

related to a modern life style (Bushnik and Garner, 2008; Y. Nishi et al., 2000). As a

consequence ARTs are acquiring increasing importance in the reproductive field, resulting in 5

million babies born worldwide from 1978 until 2012 (Brodin et al., 2013; Holte et al., 2011;

Kawamura et al., 2013; Sunkara et al., 2011; van Loendersloot et al., 2014). One of the main

deficiencies of ART is the lack of markers of oocyte and embryo competence, which would

allow for more accurate and consistent selection methods and increase in success rate. The lack

of viability markers leads to problems such as multiple gestations and risk of preterm delivery,

low gestational weight and long term post natal effects on the child’s development, and ethical

issues with cryopreservation and creation of “excess” embryos (Grady et al., 2012; Keeton et al.,

1996).

Cattle industry IVP, responding to a declining fertility of 3-4% per decade, and has

produced over 500,000 embryos per year (Lucy, 2001; Mapletoft, 2005; Ramsay et al., 2005;

Royal et al., 2000; Spencer, 2013). Dairy cattle particularly have been bred towards increased

milk yield, that has been physiologically prioritized over fertility traits (Leroy et al., 2008;

Woodruff and Shea, 2010). Cattle IVP application has been improved due to the ability to

cryopreserve genetically valuable embryos and transport them around the world. IVP also

brought improvement in reproduction efficiency by retrieving up to hundred oocytes per single

retrieval procedure from cattle using Multiple Ovulation, and Embryo Transfer to multiple

recipients (MOET) (Gilchrist et al., 2008; Li and Albertini, 2013; Mapletoft, 2005). A better

understanding of ovarian physiology, known to be highly similar between human and cow, could

lead to individualized hormonal stimulation protocols and selection of the most viable oocytes

and embryos, resulting in increased safety and efficiency of ART and IVP.

4

The aim of this thesis is to evaluate the correlation between granulosa cell AMH gene

expression and plasma and follicular fluid AMH protein level on oocyte quantity, developmental

potential, and fetal sex. AFC, ovarian diameter, oocyte number, blastocyst rate, FF and plasma

AMH levels, and GC AMH and AMH receptor 2 (AMHR2) expression were assessed in two

cattle subspecies, Bos taurus taurus and Bos taurus indicus, with known fertility differences.

Secondly, pregnant maternal and fetal plasma AMH were compared in cattle carrying male vs.

female fetuses. Finally, serum and monofollicular AMH levels and expression were compared to

oocyte developmental potential in humans.

5

LITERATURE REVIEW

Human Assisted Reproduction Technologies Today

With over 5 million babies born worldwide and the imminent 40th anniversary of the

birth of Louise Brown in 1978, the field of Assisted Reproduction Technologies (ART) went

from being an experimental practice to a common clinical procedure to achieve the birth of a

healthy singleton baby. One of the main reasons for the upsurge of ART in the last 4 decades is

the increased age of first time mothers, as well as the negative influence of environmental stress

on fertility. The number of 30 and over 35 year old first time moms grew from 15% to 26% and

from 3% to 11% from 1987 to 2005 respectively (Bushnik and Garner, 2008; Norris et al., 2009;

Tsafriri et al., 1996; Webb et al., 2002). In addition, the mean of reproductive age moved from

24.6 to 29.1 between 1970 and 1999 (Berkholtz et al., 2006; Hsueh et al., 2015; Velde and

Pearson, 2002). The emancipation of women in the 1960s, leading to an increase in female

education and participation in the labor force, an increase in the rate of divorce and remarriage,

and the availability of more reliable forms of contraception contributed to a change in

reproductive behavior. It resulted in delayed childbearing and a decreased number of children per

couple in most Western-style societies (Agdi et al., 2010; Ortega-Hrepich et al., 2014; Velde and

Pearson, 2002). These sociological factors, together with a physiological decrease in female

fertility with age, are reflected in the difference in infertility rates of 6% versus more than 30%

between the 15-24 age group compared to the over 30 age group, making ART an indispensable

and viable way to have biological children. The rise of “social egg freezing” (SEF) in the last

couple of years allowed for reproductive autonomy for women and a way to arrest the biological

clock (Argyle et al., 2016; La Marca et al., 2009). To illustrate the complex social issues

surrounding the timing of conception, when companies such as Apple or Facebook took the

6

revolutionary step of offering SEF to their employees, women felt pressured to delay childbirth

(Baylis, 2015; Dunlop et al., 2016; Kawamura et al., 2013; Varghese et al., 2008; Xiao et al.,

2015).

SEF has been shown to represent 91% of non-oncological reasons for fertility

preservation, compared to repetitive surgery (1%), endometriosis (6%) and other infertility

causes (2%) (Donnez et al., 2011; Hsueh et al., 2015; Stoop et al., 2014). Using computer

simulation, it was suggested that, with help of in vitro fertilization (IVF), a woman has a 90%

chance of having a one-child family at age of 35 and a three-child family at the age of 28. If no

IVF was involved, the female age would drop to 32 and 23 respectively (Habbema et al., 2015;

Hu et al., 2014). Since 2009, the World Heath Organization (WHO) has recognized infertility as

a disease of the reproductive system, defined by the failure to achieve a clinical pregnancy after

12 months or more of regular unprotected sexual intercourse (J. Johnson et al., 2005; 2004;

World Health Organization, 2011). Infertility is ranked as the 5th highest serious global disability

of women under the age of 60, therefore deserving proper attention and treatment (Zegers-

Hochschild et al., 2009).

Besides maternal age being a contributor to infertility, environmental influences,

especially rising levels of man-made endocrine disrupting chemicals (EDC), are affecting both

humans and animals through eating, drinking, breathing, cosmetic application, and soil contact

from waste, pesticide and fertilizer application (Krisher, 2013). EDC’s are stable and lipophilic

compounds that accumulate over decades, causing both chronic and acute harm to female

fertility (Ferris et al., 2015; Krisher, 2013). The direct effects on female reproduction are seen on

oocyte maturation and blastocyst development, with Bisphenol A exposure during oocyte

maturation in vitro resulting in spindle abnormalities, chromosome misalignment, decreased

7

embryo development, skewed sex ratio, and increased apoptosis in blastocysts (Ferris et al.,

2015). BPA is one of the highest volume synthetic chemicals produced worldwide, exceeding 5.4

million tons in 2015, and present in urine, blood, FF, and tissue of 92.6% of Americans and 90%

of Canadians (Bushnik et al., 2010).

One of the major limiting factors of ART is financial. In the USA, for example, the cost

is up to $15,771 per treatment, and $55, 450 per live birth. (Scheetz et al., 2012). In some

countries, such as Canada, Belgium, the UK, Argentina, Uruguay, Israel, and Serbia, 1-3 cycles

of ART are fully funded, while in others such as Australia, Brazil, and Germany treatment is

partially funded. This assists patients to conceive without being limited by their economic status.

It has been estimated that this investment in ART by governments is highly justified in the long

term due to an eight fold return of approximately $127,000US, in net tax revenue during a

person’s lifetime (Connolly et al., 2008). There are two major ART cost factors: ovarian

stimulation drugs and in vitro media culture systems. Both of these can be reduced with more

precise patient selection, simpler patient diagnostic methods, correct ovarian stimulation,

simplified procedures and equipment in the lab, and minimized complications caused by ART

(Maheshwari and Teoh, 2014).

The main drawback of ART is that the long-term effects are unknown, since the oldest

child is not yet forty. One of the possible consequences of ART is that unfavorable reproductive

traits are being carried from one generation to the next, with increasing chances that the children

conceived by ART will also need assistance in reproducing. Regarding the effect of ART on

developmental competencies of children, a well-conducted Canadian study examined children

ages 0-5. This study provided evidence of increased risk of prenatal and birth-related risk factors

associated with being conceived by mothers aged 35 and older. It was difficult to differentiate

8

between the negative effects due to the use of ARTs versus those due to preterm birth and low

gestational weight. However, the children seemed to also have better outcomes in many of the

tested cognitive, physical, and behavioral criteria compared to children from younger moms

(Bushnik and Garner, 2008). It was found that time spent with the child, relationship factors, and

financial resources have significant impact on developmental milestones such as the age when

the child first ate solid food, sat up, said the first word, or made the first step (Bushnik and

Garner, 2008). There are other potential long term epigenetic risks following ART procedures,

such as Beckwith-Wiedemann syndrome, Angelman syndrome, and the more recently

recognized maternal hypomethylation syndrome, and neurological risks such as cerebral palsy,

that need to be evaluated further (Vulliemoz and Kurinczuk, 2012). Also, possible increased

cancer risk due to ovarian stimulation drugs is still under investigation and long term data is

necessary to remove all the confounding factors (Brinton et al., 2012).

Currently the in vitro parameters for women under 40 using ARTs are ~70% fertilization,

~30% blastocyst rate and ~20% pregnancy rate compared to ~90% fertilization and ~50%

pregnancy success rate with natural conception and timed intercourse (Grodon, 2003; Leroy et

al., 2012). One of the reasons for the lower ART pregnancy rate is the inability to select an

embryo with the highest developmental potential. To compensate for the lowered pregnancy rate,

transfer of more then one embryo is commonly performed, often resulting in multiple gestations.

Multiple gestations are associated with high rates of pregnancy-related and neonatal

complications such as preterm delivery, decreased weight for gestational age, 7.4%, 21.6%, and

50% of twin, triplet, and quadruplet pregnancies respectively, and birth of at least one child with

developmental disabilities. In addition, cost increases with multiple gestations, being 10 times

higher for a triplet vs. singleton pregnancy (Maheshwari and Teoh, 2014). In the US, from 1980

9

to 1997 the number of live birth twin deliveries rose 52%, and high order multiple gestations

increased 404% from 1,337 to 6,737 births (Hankins and Saade, 2005). It is estimated that twin

pregnancies represented 1 in 44 births but accounted for 1 in 8 perinatal deaths. In Australia, the

reduction in multiple births by half allowed for a 55% increase in availability of IVF services, by

redirection of funding and resources. (Chambers et al., 2011).

The main concerns of IVF remain: how to improve our ability to detect oocytes and

embryos with developmental potential that would lead to pregnancy and a healthy child, and how

to mimic the in vivo environment to provide the optimal conditions for the oocyte and embryo to

sustain its development in vitro (Chronopoulou and Harper, 2014)? These oocyte and embryo

selection methods need to fulfill criteria such as being simple and rapid, inexpensive, to allow for

high throughput and consistency, and, most importantly, to be non-invasive. Maybe a new hope

in the future lies in microfluid platforms in which automated robots perform the entire IVF

protocol without any human input; however these are still only a matter of science fiction

( Swain et al., 2013). Current methods of selection include the fields of transcriptomics,

proteomics, metabolomics, but the most commonly used method is still morphology combined

with kinetics-based assessment. There is a wide body of data showing that all currently existing

methods lack precision and consistency to detect oocytes and embryos with the highest

developmental potential (Balaban and Urman, 2006; Boni et al., 2002; Ebner, 2003; Maheshwari

and Teoh, 2014; Rienzi et al., 2010; Robert et al., 2001; Sinclair, 2008; Stojkovic et al., 2001).

10

In vivo reproduction

The oocyte is one of the most unique cells in the mammalian body. It meiotically divides,

resulting in cells with haploid genetic material, is able to give rise to all other cells of the body

by being totipotent, reprograms somatic nuclei, and reprograms sperm chromatin to a functional

pronucleus. It is also a cell that contains the distinctive combination of parental genes through

the process of crossing over. Oocyte importance can be evidenced by the complex endocrine

physiology that regulates its creation, storage, selection, maturation, ovulation and fertilization.

The creation of oocytes takes place during embryogenesis in which 1000-2000 primordial germ

cells migrate to the genital ridges where they can start mitotically dividing, generating around

~7x106 oogonia, and populating an area that will develop into ovaries (Velde and Pearson, 2002).

Other mesodermal somatic cells come to “help” by providing a supporting and structural role in

organ development. These cells are destined to become granulosa and theca cells, and have

important roles in hormone secretion and regulation, ensuring proper oocyte storage and

nurturing for up to 50 years in humans. The complexity and codependence of the interaction

between these two cell types, germ and somatic, is just starting to be revealed by research (Eppig

et al., 2002; Li and Albertini, 2013; Oktem and Oktay, 2008; Rodgers and Irving-Rodgers, 2010;

Webb et al., 2002).

At around 20 weeks of gestation in humans, somatic cells start to envelope oogonia and

form structures called primordial follicles (Oktem and Urman, 2010). Surrounded by somatic

cells, oogonia are ready to start their journey from the diplotene stage to the haploid oocyte. The

process at first only progresses to prophase I of the first meiotic division, and gets arrested at this

stage, mainly in the primary stage follicles that stay dormant until puberty. By the time of

puberty, the follicle number is lessened by almost 80% of its starting quantity (Erickson, 1966).

11

Only a limited number of the remaining follicles are reawakened or recruited, in a strictly timed

manner under the control of both direct paracrine and indirect endocrine factors, after having

been arrested from 13-14 years, at puberty, or for as long as 45-50 years, at menopause (Oktem

and Oktay, 2008).

Estrous cycle

Recurring time periods where the female hormone estrogen is produced by ovaries, in set

patterns during reproductive life, is called the estrous cycle. Sexual maturity starts in puberty

with the establishment of the hypothalamic-pituitary-gonadal axis (HPG). The hypothalamus

secretes gonadotropin-releasing hormone that triggers the pituitary gland to produce follicle

stimulating hormone (FSH) and luteinizing hormone (LH), that in turn leads to gonadal secretion

of steroid hormones. Establishment of HPG results in reawakening, growth, maturation and

ovulation of selected follicles, setting the stage for fertilization, implantation and pregnancy. If

fertilization, implantation and pregnancy do not occur, HPG leads to another cycle of endocrine

hormone secretion, triggering a new set of dormant follicles. Follicle number in an individual’s

lifetime is considered an ovarian reserve. This paradigm can be challenged when new oocytes

are generated from germ cells throughout an individual’s reproductive life (J. Johnson et al.,

2005; 2004). However, the vast majority of the available follicular pool comes from those

generated during embryo development. The reawakening of follicles happens in cycles or

“waves” where a group of 5-10 follicles is triggered to enter the growth phase. Usually there are

three of these waves per one estrogen cycle, and the last wave results in one ovulatory follicle

(Driancourt, 2001). The entire process of selection, growth and maturation of the follicle with

12

ovulation takes about 90 days and this process is governed by fluctuations of reproductive

hormones depending on the follicle growth stage (Webb et al., 2004). Follicle growth is

paracrine influenced stages for approximately 80 days, due to lack of presence of endocrine FSH

receptor (FSHRc) and consist of: primordial, primary, and secondary. Following paracrine, are

the endocrine influenced stages, of mainly FSH, that occur for only the next 7-9 days and consist

of antral and ovulatory (Driancourt, 2001; Oktem and Oktay, 2008; Sirard, 2001). The stage of

the follicle is defined based on the morphological appearance of the follicle and the cells

enclosed in the follicle. The oocyte goes through complex cytoplasmic changes during

maturation stages including organelle redistribution, cytoskeleton dynamics, molecular

maturation, and zona pellucida acquisition (Ferreira et al., 2009). The primordial follicle,

~0.03mm in size, is defined as one with only one arrested oocyte, with one layer of flattened GC

layer (Velde and Pearson, 2002). The primary follicle, 0.03-0.1mm in size, is one where the GCs

start changing shape from flattened to more cuboidal. The ovary is mostly populated by primary

follicles until puberty. The secondary follicle, 0.1-2mm in size, occurs when the number of GC

layers change from one to two or more. The antral follicle, 3-8mm in size, is when there is a

development of a cavity in the follicle as a result of apoptosis, and the follicular fluid (FF) fills

the cavity. At this stage, under the influence of FSH, an aromatase enzyme starts being expressed

by GCs, converting androgens produced by theca cells to estrogen. The GCs also produce

activins, inhibins, follistatins, and insulin growth factors (IGF) (Webb et al., 2007). All of these

paracrine factors have a role in proper follicle and oocyte growth. The ovulatory follicle, 8-

10mm in size, is a follicle where the membrane is thinning and GCs are starting to express LH

receptors. Pulsatile action of LH is what causes the rupture and ovulation. The follicle that first

obtains the highest number of LH receptors is the one selected for ovulation (Hamel et al., 2008).

13

The oocyte resumes meiosis approximately 24 hours prior to ovulation, initiated by a decline in

the surge of cyclic adenosine monophosphate (cAMP) through the gap junction from GCs to

oocyte. During these 24 hours, the oocyte reaches metaphase II (MII) of the second meiotic

division (Norris et al., 2009). As long as the dominant follicle is present, there is no further

recruitment. This process of dominance selection occurs randomly between the ovaries

(Driancourt, 2001). The majority of follicles are at the dormant stage with only less than 1%

becoming selected to be ovulatory in a lifetime.

Anti-Mullerian Hormone

Alfred Jost in 1947 defined a second male determining factor besides testosterone, called

Mullerian Inhibiting Substance (MIS). As its name suggests, its function in the male embryo is

to inhibit the Mullerian duct development. Later, the name more commonly used became Anti-

Mullerian Hormone (AMH). The human AMH gene is located on 19p13.2-13.3. This is a

relatively short gene of 2.75kb, divided into 6 exons, giving rise to 1.7kb mRNA. Bovine and

mouse promoters are a canonical TATA box, with a single transcription start site located 10bp

upstream of the ATG. The human promotor is a degenerate TTAA motif at 26 bp, with the

functional initiator element recognized by the transcription factor (TF) II-I. The proximal

promoter displays a number of evolutionary conserved binding elements: steroidogenic factor 1

(SF1), two GATA, one SOX9, and Wilms’ tumor associated protein 1 (WT1), all indicating a

common AMH expression in mammals (Lasala et al., 2004). Main regulators of AMH

expression are Sf1, Gata4, Wt1, Dax1 and Fog2 (Salmon et al., 2004a). Without the binding of

SF1 and the pair of GATA4, no up regulation of AMH is initiated (Watanabe et al., 2000). AMH

14

mRNA is translated to a 140kDa disulfide linked glycoprotein homodimer, belonging to a

transforming growth factor (TGF)-beta family of proteins. In humans it is synthesized as 560

amino acids with a half life of 3-5 days in serum (La Marca et al., 2009; Lasala et al., 2004).

TGF-beta family is composed of 33 related polypeptides that, beside AMH, also include bone

morphogenic proteins (BMP), growth and differentiation factor (GDF), activin/inhibin subfamily,

glial cell-derived neurotrophic factor (GDNF), and nodal (Knight, 2006). All of these are

involved in injury repair, cellular proliferation, differentiation, adhesion, and immunity

(Morikawa et al., 2016). Disturbance in TGF-beta signaling leads to a variety of diseases such as

connective tissue disorders, fibrosis, and cancer (Morikawa et al., 2016). Even with TGF-beta

family being large, there are many fewer receptors and downstream intercellular effectors than

signaling molecules. They all signal through trans-membrane serine/threonine kinases,

consisting of seven type I receptors and five type II receptors, forming heteromeric type I/type II

receptor complexes. Ligand binding to a tetrameric receptor complex stabilizes and activates

their signaling capacities, further phosphorylating Smad proteins. Smads got their name from

studies in Drosoplila and C. elegans proteins, in which Sma and Mad were identified

respectively and found to be very similar to human, frog and mouse signaling molecules. The

Smad complex translocates to the nucleus where it binds to the promoter Smad Binding Element

(SBE) causing up regulation of metalloproteinases in males and down regulation of follicle

recruitment and growth factors in females (La Marca et al., 2009).

140kDa AMH undergoes posttranslational proteolytic cleavage, starting from covalently

bound prepropeptide and cleaving to become propeptide non-covalently linked between the N

and C terminal domain. Each homodimer becomes 110kDa (pro region) and 30kDa (mature

region) in size. The pro region is where main species-specific sequence differences are located,

15

and the mature region is where most biological activity resides. Unlike other TGF-beta members,

these two regions remain non-covalently associated and bind to the receptor. The pro region is

believed to be involved in proper folding and delivery of the mature region to the receptor

(Morikawa et al., 2016). The biological activity of the mature vs. combined promature version is

enhanced by almost double, indicating that mature version contains hydrophobic properties and

differential folding, decreasing its potency. The non-covalent promature complex is highly

sensitive to heat and pH stress, making it difficult to construct a bioassay that is stable and

consistent. Because the immature covalent version is non biologically active and present in a

very low amount, ~4%, of the total AMH, the proteases serve as a regulatory mechanism

reassuring the promature version is present at the site of action. After the promature complex

binds to the receptor, the two regions dissociate, with the mature region bound to the receptor,

and the pro region remaining loose in the proximity of the receptor (di Clemente et al., 2010;

Wilson et al., 1993). AMH is known to be a protein with highly conserved function throughout

mammalian kingdom with homology between 74% and 68% to bovine, rat and mouse and 27%

and 33% to chicken and alligator (Teixeira et al., 2001)

Anti-Mullerian Hormone Receptor 2

AMHR2 is a transmembrane receptor with serine/threonine kinase activity. It is highly

specific, sharing 30% overall homology with other TGF-beta family type II receptors (Teixeira et

al., 2001). It is expressed at day 15 in mouse embryo in both male and female in the

mesenchymal cells of the gonads surrounding the Mullerian ducts. AMH binds AMHR2, which

causes further phospohorilation of AMH receptor 1 (AMHR1), also known as activin-like kinase

16

3 (Alk3), or bone morphogenic protein receptor 1a (Bmpr1a). This heteromeric complex acts

downstream, phosphorylating Smad proteins within the cytoplasm. AMHR2 is thought to have

two splice variants, both with an inhibitory role on AMH (Imhoff et al., 2013). Monniaux et al.

has shown that the AMHR2 expression pattern resembles AMH transcript levels during follicular

maturation stages in the caprine species (Monniaux et al., 2011).

AMH in males

AMH was primarily discovered as a male determining factor crucial in male sex

differentiation. Knock out of this hormone in males leads to a normal male phenotype but with

Mullerian duct persistence, formation of a uterus and fallopian tubes, azoospermia due to

malformation of the ductus deferens and agenesis of epydidymus, with testes adhered to the

uterine tubes or in the abdominal and inguinal region, and normal testicular histology with

presence of spermatogonia (M. Y. Nishi et al., 2012). The internal genitalia possess the intrinsic

tendency to feminize in the absence of the Y chromosome (Kuijper et al., 2013). AMH is one of

the first genes to be expressed from the bipotential gonad, leading to differentiation of testes

under the influence of the sex determining region of Y chromosome (SRY) (La Marca et al.,

2010; Teixeira et al., 2001). In males both Sertoli and mesenchymal cells express AMH that up

regulates metalloproteinases (MMPs) in the surrounding epithelial duct cells. This leads to the

breakdown of the extracellular matrix and ultimately the disappearance of Mullerian ducts

(Visser, 2003). AMH is also known as a male determining factor in different conditions of

hermaphroditism and tumor growth. Aksglaede et al. studied the AMH serum levels and found

17

that they reach a peak of about 1082pmol/l (~150ng/ml) at 12 months after birth and then decline,

being ~20% lower at the age of 7 and a further 3-4% during adulthood (Ebner, 2006).

AMH in females

Until the 1990s, AMH function and importance was more studied in males due to the fact

that expression of AMH in the male embryo precedes that of the female embryo by ~3 months in

utero, and is expressed in concentrations a few hundred times higher compared to the female

embryo. In the female embryo AMH is secreted by GC cells and is dependent on the follicle

stage, starting with expression in primary follicles and lasting to the antral stage, being highest in

the preantral follicles (Themmen, 2005; Visser et al., 2006; Visser and Themmen, 2005). Knock

out of AMH in the female mouse embryo causes premature exhaustion of ovarian follicle reserve

and early menopause (Durlinger et al., 1999). In mono-ovular species such as the sheep, cow,

monkey and human, AMH plays a key role in modulating follicle growth and development

(Campbell et al., 2012), inhibiting follicular growth, maturation, and dominant follicle selection

during the gonadotropin responsive phase (Xu et al., 2016). In poly-ovular species, the function

of AMH is to inhibit recruitment of primordial and primary follicles (Xu et al., 2016). In

summary AMH could be defined as an intra- and inter- follicular “guardian” of follicle

recruitment and development (Salmon et al., 2004b). Additional studies using bovine, mice and

rat embryonic ovarian cortical pieces, in culture or placed in sham, or in ovariectomised chick

embryos in ovo showed evidence that AMH inhibits follicular growth (Fortune et al., 2011;

Nilsson et al., 2007; 2011). In vitro, when recombinant AMH was added to the cortical ovarian

pieces, the number of primordial follicles increased while the number of primary follicles

18

decreased with increasing AMH concentration (Fortune et al., 2011). As mentioned earlier,

dormancy is the fate of the majority of follicles throughout female life. It is believed that this

inhibition is achieved through suppression of steroidogenesis and differentiation of somatic cells

in the gonads (di Clemente et al., 2003). AMH has been shown to down regulate expression of

aromatase, LH receptor, and steroidogenic enzymes (Visser, 2003). The rate of dizygotic

twinning increases with age and chances of twinning increase with every consecutive pregnancy

(from 1.3% in the first to 2.7% in the fourth pregnancy) (Hankins and Saade, 2005), suggesting

that the decrease with age in the stringency of AMH’s ability to inhibit follicle recruitment might

result in a higher rate of dizygotic twinning. In the presence of AMH, the effect of FSH as one of

the necessary HPG factors for follicle growth is decreased. In addition, in vivo more follicles

start to grow under the influence of exogenous FSH in AMH-deficient mice compared with the

wild types (Durlinger et al., 2001). In a sheep study by Campbell et al., FSH addition caused an

increase in the proportion of small antral follicles with no changes in the pattern or intensity of

AMH expression (Campbell et al., 2004). The AMH mRNA level was significantly lower after

10 days of culture without FSH. However, this decrease was not reflected in the number of

growing follicles, which may suggest that AMH expression in vitro could be high enough to

keep control over follicle recruitment (Sadeu et al., 2008). Even with prior evidence suggesting

that FSH promotes while AMH inhibits follicular growth, in a AMH KO study FSH was shown

to be unnecessary for initial recruitment of follicles, indicating predominantly paracrine control

(Oktem and Urman, 2010). IGF-I has been proposed to have a regulating paracrine role on both

AMH and FSH via a “break free” mechanism from the inhibitory influence of AMH on the

growing follicles (Campbell et al., 2012). AMH was also reported to exhibit a dose responsive

inhibitory effect on LH-stimulated androgen production by theca cells (Campbell et al., 2012).

19

This is particularly important in pathologies such as polycystic ovarian syndrome (PCOS) where

this balance is disturbed.

AMH as a clinical marker of ovarian reserve

Being suppressive of follicle recruitment and reflecting ovarian reproductive aging, AMH

gained clinical importance as a marker of 1) ovarian follicle reserve and 2) the number of

gonadotropin sensitive follicles, also known as the antral follicle count (AFC) (J. J. Ireland et al.,

2011; Kevenaar et al., 2006). These two ovarian parameters, ovarian reserve and AFC, are

interchangeably used in a clinical ART setting as a highly individually repeatable, as well as a

non-invasive way to assess the current status and prognosis of patient outcome (Burns, 2005;

Chang et al., 1998; Sonigo et al., 2016). Ovarian reserve, estimated by AMH, in general reflects

the total quantity of oocytes available in the ovary, while AFC is a measure of the number of

growing follicles (Erickson, 1966; J. J. Ireland et al., 2011; J. L. H. Ireland et al., 2008).

Measured in serum at any stage of the estrous cycle, AMH is found not to have significant

fluctuations, irrespective of the other reproductive endocrine and paracrine hormonal

concentrations (La Marca et al., 2009). AMH is also found to be consistent in individuals and

animals from one cycle to the next, making it an excellent marker of inter- and intra- cycle

ovarian status (La Marca et al., 2006; La Marca and Volpe, 2006). This is very important when,

in comparison, the individual inter-cycle AFC variation has been demonstrated to change by a

factor of 5-7. To demonstrate the potential for AMH as a good prognostic tool for fertility, it

could be used a cattle herd setting to identify the approximately 30% of cattle that end up

producing 70% of total embryos (J. J. Ireland et al., 2007). One of the definite benefits of using

20

AMH over AFC is that it can be done offsite and it is not affected by the technical skills of

personnel. The most concrete result linking AMH, AFC and ovary size shows that ovarian size is

reflective of female fertility, a concept long known in the context of male fertility (Coulter and

Foote, 1979; J. J. Ireland et al., 2011; Keeton et al., 1996). AMH can more accurately predict

occurrence of menopause within 4 years, with 0.87 stringency, than can AFC (Visser et al.,

2006). The latest study by Sonigo et al. provides the threshold values of AMH and AFC, being

3.7ng/ml and 20 respectively, for approval for oocyte crypreservation after in vitro maturation

procedure in IVF patients (Sonigo et al., 2016).

In the ART setting, the number of growing follicles is an important estimate, since those

follicles are sensitive to ovarian superovulation drugs, allowing for growth of more than one

follicle and more than one mature oocyte. An incorrect estimate of the patient’s response can

lead to ovarian hyperstimulation syndrome (OHSS), one of the major risks in ART. OHSS

occurs when a patient is overdosed on gonadotropins, leading to ovarian hyper response and

possibly resulting in: enlargement of the ovaries, abdominal pain, nausea, diarrhea, dehydration,

rise in blood pressure, and even in rare cases: thrombosis, distention, oliguria, pleural effusion,

and respiratory distress. This condition is considered life threating and it often requires

hospitalization. Therefore, correct ovarian stimulation needs to be a balance between achieving

an adequate oocyte yield without causing adverse effects. Current stimulation procedures are

based on the monitoring of follicular growth using ultrasound and biochemical hormonal

analysis. However these are still considered “without the predictive value of individual ovarian

potential …. over simplistic and dangerous” (Maheshwari and Teoh, 2014).

Proper reserve assessment using AMH or AFC has the potential to improve type, dosage,

and duration of ovarian stimulation to maximize the clinical goals of IVF treatment. It also

21

improves cost-effectiveness, considering that ovarian stimulation is the major cost of the IVF

treatment (Maheshwari and Teoh, 2014). Recently, the literature has been defining and

interpreting the cutoff and extreme levels of clinical AMH values: “more invasive or time-

consuming methods of fertility preservation being appropriate for women with a low AMH”

(Anderson et al., 2012), or: “AMH measurement may be useful in the prediction of poor

response and cycle cancellation and also of hyper-response and ovarian hyperstimulation

syndrome” (La Marca et al., 2010). OHSS and multiple pregnancies are the two most common

adverse effects of IVF and AMH has a potential to reduce both in its role of clinical marker at

systemic and local levels.

AMH as an oocyte and embryo developmental potential marker

From Human Serum

AMH correlation to oocyte quantity is well established, and there is now evidence to

suggest AMH levels could be a marker of oocyte quality. This has been investigated in both

humans and bovines, and only a few human clinical studies have established a correlation.

Confounding variables in these studies could be the aging process which links decreasing quality

of oocytes with lower AMH levels, or embryo numbers which could be an extrapolation of

retrieved oocyte number (Fanchin, 2003). A study conducted on 141 patients, divided into three

groups based on 25th and 75th percentile of day 3 serum AMH, showed that 50% of normal

morphological oocytes were derived from the “normal” serum AMH patient group (1.66 and

4.52ng/ml), compared to 30% of normal morphological oocytes derived from the lower or higher

serum AMH groups (Ebner, 2006). Silberstein et al., on the other hand, showed evidence that

22

serum AMH ≥2.7ng/ml measured on the hCG administration day could be correlated with

embryo morphology and cleavage rate (Silberstein, 2005). EldarGeva et al. showed a correlation

between serum AMH of 2.52ng/ml and ongoing pregnancy rates (Eldar-Geva, 2005). Further

studies suggested that 0.69ng/ml could be a cut off between the ovum pick-up (OPU) procedure

cancellation (Penarrubia et al., 2005), while 1.13ng/ml might be an indicator of poor ovarian

reserve, with a specificity of 85% and a sensitivity of 80% (Tremellen et al., 2005). Another

study by Nelson et al. showed the positive correlation between AMH values and live birth rate,

as well as a correlation between AFC and AMH, when AFC values are between 15 and 25

(Nelson et al., 2007). Lakamge et al. defined 14pmol/l or 1.96ng/ml as the cut off for the

cumulative pregnancy rates per cycle (Lakamge, 2007). Majumder et al. showed that serum

AMH and AFC predict oocyte and embryo potential, but both are better in predicting negative

live birth outcome, with AMH being 84% specific (Majumder et al., 2010). LaMarca et al.

showed that serum AMH (prior to gonadotropin stimulation) and age are predictors of live birth,

with a sensitivity of 79.2% and a specificity of 44.2% (La Marca et al., 2011). AMH

concentrations of below 0.4 and between 0.4 and 2.8ng/ml have a 44% and 86% live birth

chance respectively. Even with the moderate ability to predict live birth, AMH was found

superior to age, day 3 FSH, oestradiol, or inhibin B levels and similar to AFC (Hazout et al.,

2004). Brodin et al. provided evidence and set a foundation, supported by Sunkara et al.,

showing that AMH is positively correlated to both oocyte quantity and quality independent of

age and number of oocytes retrieved (Brodin et al., 2013; Sunkara et al., 2011).

23

From Human Follicular Fluid

More recently, a few research groups have become interested in follicular AMH levels

and have shown similar results as seen in serum. Fanchin et al. showed that ovarian preovulatory

FF AMH is correlated to serum AMH, and both are predictive of the implantation potential of

embryos (Fanchin et al., 2007). In this study AMH concentration was adjusted to the total protein

content of the FF, due to variability in the follicular size. FF AMH was stratified as low (up to

1ng/ml), average (1.1-2ng/ml) and high (above 2ng/ml). The prevoulatory FF AMH was

approximately 2.5 times as concentrated compared to serum levels of AMH. This study used

only one retrieved oocyte and one embryo per transfer. Another study successfully compared and

correlated the pooled FF AMH to the maturation status of the oocyte (Cupisti et al., 2007).

Takahashi et al. explored the largest preovulatory FF and found a positive association to oocyte

fertilization, showing that AMH was 3.42 times higher in the fertilized vs. non fertilized groups

(Takahashi et al., 2008). Wunder et al. showed evidence that pooled FF and serum AMH on the

day of oocyte retrieval correlated to the pregnancy outcome (Wunder et al., 2008). There is a

body of evidence showing the effect of other follicular components secreted by GCs that have an

effect on oocyte competence (Mendoza et al., 2002), as well as research by Salmon et al.

showing the effect of the oocyte on AMH expression in GC (Salmon et al., 2004b). These results

clearly point to the fact that ovarian reserve, of which AMH is an obvious marker, is associated

to the oocyte quality, independently of age and oocyte quantity.

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AMH as a PCOS, DOR and cancer marker

By being representative of ovarian status, AMH has become a marker of ovarian

pathologies such as PCOS, diminished ovarian reserve (DOR), and granulosa cell tumors. PCOS

is caused by insensitivity of the follicular pool to signals that direct selection for dominance and

inhibition of further recruitment and growth. The proportion of growing follicles is increased and

the proportion of atretic follicles is decreased due to the lack of an ovulatory follicle that would

otherwise act as inhibitory signal towards new recruitment. In addition, the number of androgen

receptors in the follicle is increased resulting in constant initiation of growth. Imbalance in AMH,

androgen receptors, FSHRc, estrogen, and progesterone causes the follicular cycle to be “frozen”,

resulting in disruption of follicular maturation and ovulation, decreased oocyte quality, and

infertility (Rice et al., 2006). AMH levels were found to be 3 times higher in PCOS patients than

in controls and were significantly associated with AFC. Diagnostic predictability of AMH was

found to be 0.851, with a threshold of 60pmol/l (8.4ng/ml), and with a specificity of 92% and a

sensitivity of 67% (Pigny, 2005). AMH, AMHRc, FSHR, androgen receptors were all increased

in PCOS patients (Catteau-Jonard et al., 2008). Stimulation response could not be predicted with

AMH in PCOS patients (Kim et al., 2013). Promising treatment lies in the use of suppressors or

inhibitors of AMH to remove the block of the ovulatory signal, and allowing for a selection of a

single ovulatory follicle. This principle extends to patients with DOR or poor responders to

gonadotropin treatment, where AMH activity is insufficient, and where the addition of

recombinant AMH could potentially have a therapeutic value (Campbell et al., 2012).

Levels of AMH in GC tumors were found to precede clinical detection by 16 months (La

Marca and Volpe, 2006). In experiments by Stephen et al., addition of 10g of recombinant AMH

per day for 3 weeks caused inhibition of human cancer cell lines in vivo, under renal capsules

25

(Stephen et al., 2002). The AMH caused decreased neovascularization, necrosis, inflammation,

and tumor size. The TGF-beta family has been shown to have an anti-proliferative response in

different cell types. Inhibition of TGF-beta has been linked to enhanced tumorogenicity in vivo,

and different types of mutations of TGF-beta have also been found in cancers (Morikawa et al.,

2016). Often a same protein can display suppressor properties in the initial stages of tumor

growth, but switches to a pro-onco gene in the later stages (Tang et al., 2003). Anttonen et al.

explored tumor growth using the ovarian granulosa-like cell line (KGN) developed by Nishi et al.

and showed that AMH expression varies depending on the tumor size, while AMHR2 was

unaffected. In addition, increasing levels of exogenous AMH in vivo and in vitro tumor cell

number decreased by mean of apoptosis (Anttonen et al., 2011; Y. Nishi et al., 2000).

Cow as a model for human reproduction

The bovine model in studying human reproduction became popular with the realization

that cattle have a very similar gestation length, endocrine hormone status and regulation, are

monoovulatory, have a similar estrous cycle length, with 2-3 follicular waves, have individually

repeatable AFC, and have similar pathologies such as PCOS and tumors. Because they are large

animals, it is easier to assess the ovary in terms of ultrasound measurements and sampling,

compared to rodents. Ovaries are readily available from slaughtered animals. AFC has been

shown to impact fertility in cattle to the same extent as in human. Variation of AFC has been

shown to differ 7 fold among animals, ranging from 8-56 follicles, but it is highly reproducible

per animal (with an accuracy of 0.85-0.95), regardless of the breed, age, season, or management

conditions. An AFC below 15 was correlated to an 80% smaller ovarian reserve, dramatically

26

different to cattle with an AFC above 25 (J. L. H. Ireland et al., 2008). In 12 month old heifers,

80% of their original oocyte reserve has been normally lost and the average conception rate after

artificial insemination (AI) was found to decline from 56% at 15-16 months of age to 42% at 26-

27 months of age (Kuhn et al., 2006).

Dairy and beef cow fertility

The dairy and beef industries are of tremendous economic importance, and ART is

immensely valuable tool to sustain production. Serious problems have been observed with

decreasing fertility of up to 3-4% per decade (Spencer, 2013). To achieve a pregnancy rate of

40%, usually requires two AIs. The UK dairy industry defined its main problems in dairy and

beef production as subfertility, mastitis, and lameness, with subfertility being the one with the

highest economic impact and the most difficult to solve. The dairy industry is under constant

selective pressure for high milk production (Royal et al., 2000). Several studies have been

conducted on the effect of energy utilization towards increased milk production against body

condition score (BCS) and the effect of prolactin on reproduction efficiency. It has been shown

that fertility traits such as luteal activity postpartum are heritable, while calving interval and BCS

heritability are under investigation (Leroy et al., 2008). Increasing milk yield has been shown to

negatively impact the ART, as the oocyte number and embryo quality decreases. Up to 50% of

modern dairy cows present abnormal estrous cycles postpartum, leading to prolonged calving to

first insemination intervals (Opsomer et al., 2000), low conception rates, and high early

embryonic mortality (Leroy et al., 2012). Luteal activity postpartum has been also shown to

negatively correlate with milk yield, with estimates that lactation uses 75% of the cow’s

27

metabolic capacity. One of the ways to overcome this decreasing fertility issue is to utilize the

IVP or MOET method that includes in vivo fertilization (Mapletoft, 2005). It was found that IVP

produces higher number of oocytes and embryos, 9.4 vs. 6.7, but that the pregnancy rates are

lower, 33.5% vs. 41.5% respectively. After considering the efficiency of IVP over MOET, it was

found that in a 15 day interval, IVP produced more pregnancies even with lower pregnancy rates

(Pontes et al., 2009).

Anti-Mullerian Hormone in cattle

The size of ovaries, ovarian reserve, and AFC have been shown to be highly similar in

both humans and cattle, therefore AMH has also been a candidate parameter to identify cattle

reproduction outcome and fertility (Erickson, 1966). AMH was defined as “an endocrine marker

of gonadotropin responsive follicles” (Rico et al., 2009). Ireland et al. has shown, using the three

largest follicles in low vs. high AFC groups of animals, that intrafollicular estradiol and mRNA

for aromatase in GCs were greater and mRNA for AMH was lower respectively (J. J. Ireland et

al., 2009). Serum AMH was found to be highly individually reproducible and variable between

animals, corresponding to high variation of the number of oocytes in new born calves (10,000-

350,000) and 12 month old heifers (1,920- 40,960) (J. L. H. Ireland et al., 2008; Lo et al., 1998).

AMH half-life in the bovine is 2 days, with levels being static during the estrous cycle. It is

believed that AMH has the ability to inhibit FSH dependent aromatase expression, resulting in an

inverse AMH and estradiol17beta relationship, while AMH production is enhanced by BMP

(Novembri et al., 2015). AMH is regulated at the follicular, ovarian, and endocrine levels. At the

follicular level it is regulated by the stage of follicle, at the ovarian level it is regulated by the

28

pool of small antral follicles, and at the endocrine level it is regulated by the effects of other

endocrine hormones (Rico et al., 2011).

Bos taurus taurus vs. Bos taurus indicus

All domestic cattle belong to the family Bovidae, subfamily Bovinae. The subspecies

studied here belong to two subspecies Bos taurus taurus (taurus) and Bos taurus indicus

(indicus). In Tibetan “Zen” or “Zeba” is the word for hump, which is one of the main physical

features of indicus cattle. The common ancestor originated in Western Asia around 4500 BC.

Zebu cattle comprise more than half of the world’s cattle due to their multipurpose and hardy

features. In the 1800’s, indicus was introduced to the American continent as Brangus, a cross

between the Brahma and Angus breeds. Breeding is known to increase phenotypic superiority, or

hybrid vigor, carrying better-adapted traits from both parents. However, the heritability of these

traits is not linear and is easily influenced by environmental factors (Abeygunawardena and

Dematawewa, 2004). These different subspecies have adapted to diverse environmental

conditions, which impacted overall reproduction physiology (Beatty et al., 2006; Driancourt,

2001). For example, Brahma (Bos taurus indicus) and Senepol (tropical Bos taurus taurus) have

greater numbers of follicles in all size categories than Angus (temperate Bos taurus taurus)

(Alvarez et al., 2000). Bo et al. has described indicus as superior to taurus in terms of calving

rates if both are kept in tropical or subtropical environments (Bó et al., 2003). Indicus has

adapted to hot temperatures, humidity, parasites, and low quality forages. However, indicus

reproduction is characterized by: 6-12 months delayed puberty until 60% of body weight is

reached (compared to 30-55% in taurus); 2-4 follicular waves; lower LH secretion; estrous

29

length on average 20.9 days; smaller duration of estrous (10 hours, compared to 16.3 hours in

taurus); decreased estrous intensity; smaller interval from estrous to ovulation; longer gestation

length; extended post partum period of 17 months (compared to 12 months in taurus); higher

number of AFC (41.5 vs. 21 in taurus); lower number of dominant follicles; smaller max

diameter of dominant follicle (10-12mm vs. 16-20mm in taurus), smaller CL (24mm vs. 28mm

in taurus); and lower twining rate (Sartori and Barros, 2011). Indicus cattle take 3 years to reach

puberty and produce only a few liters of milk over a short lactation period, after which there is an

extended postpartum anestrous. Variability to superovulation treatments and difficulty detecting

estrous causes decreased efficiency in indicus ART. The dose for super ovulation drugs of

indicus vs. taurus is usually reduced by 30% for gonadotropins, by 50% for progesterone, and by

40% for estradiol. The calving interval in the dry vs. wet season differs, from 19.9 months to

14.5 months. There is evidence that for every hour of daylight there is 0.5mm increase of the

dominant follicle diameter, relating seasonal changes to fertility parameters. Baruselli et al.

reported that follicular deviation of the ovulatory follicle is smaller in indicus breeds, and that

estrous occurs more often during the night (Baruselli et al., 2006). Pontes et al. found that there

is no difference in the number of primordial, primary, or secondary follicles in the ovaries of

fetuses or heifers in both subspecies, therefore the initial number is not the reason for the

difference in oocyte and embryo yield (Pontes et al., 2011). It is believed that the mechanism

controlling the follicle development differs in each of the subspecies (Silva-Santos et al., 2011).

Therefore five main problems with ART in indicus were defined: 1) necessity to detect estrous;

2) necessity to start gonadotropin at the correct time; 3) necessity to perform AI at the correct

time; 4) high variability of embryo production per donor; 5) high proportion of unresponsive

donors. Pontes et al. examined a large number of animals belonging to three breeds, Gir,

30

Holstein, and Girolanda (Gir and Holstein in varying percentages of crossbreeding: ¼ Holstein

and ¾ Gir and ½ Holstein Gir mix) (Pontes et al., 2010). It was found that pregnancy rates were

40%, 36%, 37%, and 37% respectively. However, there was a large variation in viable oocytes

per retrieval 12.1, 8.0, 16.8 and 24.3, as well as in pregnancy per retrieval 1.2, 0.7, 1.3, 1.7

respectively.

Batista et al. examined AFC in Nelore and Holstein cattle at 3 different time points, 120

days, 60 days and 0 days before plasma AMH determination and found that at all time points

AFC correlated with AMH (Batista et al., 2014). Nelore heifers had overall higher AFC and

AMH compared to Holstein (Baldrighi et al., 2014; Batista et al., 2014). These authors defined

serum AMH as a reliable phenotypic marker to predict relative number of follicles at any point

of the cycle irrespective of genetic group. Guerreiro et al. also came to a similar conclusion,

defining AMH as an accurate endocrine marker for the in vitro embryo yield but not for

blastocyst yield (Guerreiro et al., 2014).

AMH as a fetal sex marker

AMH has been proposed as a potential sex-determining factor in early pregnancy, but

current studies present contradictory findings. AMH is expressed at different sex specific time

points during pregnancy (7 weeks for males and 20 weeks for females), but is an order of

magnitude more concentrated in male fetal circulation. In male cord blood AMH levels are

around 64 to 92ng/ml in the second trimester, while still undetectable in female fetus cord blood.

Lee and colleagues, in 1996, defined AMH as a “testis specific marker during infancy and early

childhood” (Lee et al., 1996). A human clinical study by Empey et al. included over 100 women

31

carrying either male and female fetuses, and revealed a significant sex specific difference in

maternal serum in the time period between 11 and 15 weeks of pregnancy, with the average male

concentration being 2.0 ± 0.03ng/ml and the average female concentration being 0.94 ± 0.2ng/ml

(Empey et al., 2012). However, a study by LaMarca et al. showed an increase of maternal serum

AMH levels during second semester, but this increase was not found significant (La Marca,

2005). A study by Nelson et al. also examined serum AMH levels across trimesters, and found

AMH levels were significantly decreasing across trimesters (Nelson et al., 2010). Interestingly,

pre-pregnancy and post-pregnancy serum AMH levels were found not to differ. Studies about the

ability of AMH to cross the placenta have not yet been published. Studies on other proteins, such

as alphafetoprotein (AFP), 70kDa in size, crossing from the fetal to the maternal circulation by

passive transport through placental “leaks” have provided evidence of the ability of large

proteins to cross the placenta (Malek et al., 1998). A recent study examined AMH and AMHR2

expression in the placenta and fetal membranes and found no difference in expression levels

using qPCR in either the placenta or fetal membranes between male and female fetuses.

However the study did show significantly higher AMH antibody staining intensity of male fetal

membranes vs. female fetal membranes (Novembri et al., 2015).

The effect of fetal AMH is illustrated in opposite fetal sex twins in the hermaphrodite

condition in cattle called Free-Martin. First described in 1917, it was not until 1991 that AMH

was proposed as a possible cause of Free-Martinism (Komisarek and Dorynek, 2002). This

condition occurs in twin pregnancies with opposite sex fetuses that share circulation with

vascular anastomoses, and results in a disturbed development of the female reproductive tract

due to high male fetal AMH expression. It is the most common type of disorders of sex

development in cattle and occurs in up to 90% of the female fetuses of surviving opposite sex

32

twin sets (Padula, 2005). These animals are described as having morphologically both female

and male external genitalia, both Wolffian and Mullerian ducts, an enlarged clitoris, a shorter

vagina length, an increased ano-vaginal distance, the presence of ovotestes, and the absence of a

cervix (Hwang et al., 2001; Roberts and Greenwood, 1928). Newborn Free-Martin calf AMH

levels were found to be similar to that of a new born male calf, >700ng/ml, compared to the

normal female, <120ng/ml. However a decrease to female levels is observed in the Free-Martin

calf after 2 weeks after birth, while in a normal male the decrease would occur over the first 5

months of life (Padula, 2005). Testosterone levels in the Free-Martin calf are similar to male

levels, but other steroid hormones and gonadotropin levels are much lower, and they also have a

heavier birth weight and higher marbling score. A similar condition was described in the sheep,

deer, pig and horse by the same authors. It is interesting to observe that sheep and deer also

belong to ruminant groups and share the same placenta type as cows, while the pig and horse

placenta is of diffuse type. Another study looked at the effect of hormonal therapy on a Free-

Martin heifer, twin to a bull, and found that the heifer started lactating 9 days after the treatment

and continued for one month, but the milk had low butterfat content. This animal was not able to

conceive, but resumed a normal oestrual cycle after treatments with 20mg of diethylstilbestrol

dipropionate (synthetic estrogen) over 22 days 8 injections (Barker, 1944). Both of these studies

were unable to genotype the Free-Martin animals due to unavailable resources and knowledge at

the time, therefore the sex was not determined with certainty. A more current case study in a

human with a rare type of monochorionic dizygotic twinning with opposite sex twins described a

healthy boy (XY) and girl (XX) born with no sign of hermaphroditism (Souter et al., 2003). In

this study the placental barrier was not present and there was still no effect of male AMH on the

female twin. Other human studies of similar pregnancies did see differences in length of

33

gestation, female behavior, and IQ (Derom et al., 2005; Luke et al., 2005). Other types of

hermaphroditism have been discovered, however the etiologies of the condition are diverse. The

most common condition is a true hemaphroditism due to chimerism or mix of male and female

cells in the gonads during embryo development (Souter et al., 2006).

The newest data has shown that AMH expression is not only limited to the ovary and

placenta but it is also expressed in the liver and brain (Novembri et al., 2015). Brain studies have

shown differential expression between male and female mice and possible differential brain

development and function leading to sex specific behavior (Wang et al., 2009; Wittmann and

McLennan, 2013).

Human vs. bovine placenta

In order to explore levels of fetal AMH in maternal circulation during pregnancy, the

placenta has to be considered, as it is the main barrier between maternal and fetal circulation.

The placenta’s main function is to nurture the fetus and allow for selective transport of nutrients

without compromising the mother’s survival. Simultaneously, fetal secretions, cells, proteins and

DNA are transported and diffused through the placenta to the maternal circulation (Lo et al.,

1998). The placenta produces AMH but with no difference in levels between the male and

female fetus (Novembri et al., 2015).

Bovine placenta differs from the human placenta in morphology. It is epitheliochorial

with cotyledonary morphology, while in the human it is hemochorial with discoid morphology

(Rawn and Cross, 2008). The epitheliochorial placenta is evolutionarily conserved among large

species with increased gestation length, singleton pregnancies, and immature young, while the

34

hemochorial placenta is mostly found in smaller mammals, often with multiple offspring, among

which the human is the largest example (Enders and Carter, 2004). Cotyledons, 100-140 in

number, are the main sites of oxygen, nutrient, and CO2 exchange. In the discoid placenta,

exchange is focused at the disk-specific area where the placenta attaches to the endometrium. In

the epitheliochorial placenta, maternal and fetal vascular systems remain completely separated

by intact epithelial cells with basal laminae and connective tissue on each side, causing minimal

trauma to the uterus. In the hemochorial placenta, fetal chorionic epithelium is bathed in

maternal blood, because chorionic villi erode through the maternal endothelium (Barreto et al.,

2011). This feature of the primate placenta, of being more invasive than in the ruminant placenta,

possibly allows for a more facilitated nutrient transport and more rapid growth within a shorter

gestation length. However, there is also an increased risk of microchimerism, immunological

response, and excessive bleeding at parturition (Barreto et al., 2011; Enders and Carter, 2004;

Nelson et al., 2010).

The placenta is important not just as a barrier, but as an active “nutrient sensing” dynamic

organ, allowing for constant adaptation to the continuously changing environment (Diaz et al.,

2014). For example, oxygen diffusion ability varies across species with different placenta

thicknesses (6um in the cow compared to 1um in the pig and 3um in the horse) (Carter and

Enders, 2013; Kuijper et al., 2013). Another adaptation is the development of endocytosis,

pinocytosis, and trinucleate cells to overcome the lack of direct maternal blood access. Interferon

tau, placental lactogens, pregnancy associated glycoproteins, and growth hormones are a few of

the many endocrine hormones produced by the ruminant placenta. AMH is a 140kDa

glycoprotein dimer, quite a large protein, which needs to be transported across multiple cell

membranes. Means of transport could potentially be either by a slow diffusion process of similar

35

size proteins (Malek et al., 1998) and/or by means of cytoplasmic vesicles such as exosomes

(Pereira et al., 2013; Rong et al., 2015; Sandvig and Llorente, 2012; Vargas et al., 2014).

Differing placenta structure and morphology could be the potential reason why the condition of

Free-Martinism does not occur in human dizygotic monochorionic twin pregnancies. High AMH

levels could possibly move through the discoid placenta in human in a more localized fashion

and not affect the second fetus of opposite sex to the extent that it happens in bovine

cotyledonary placenta (Chen et al., 2013; Derom et al., 2005). In addition, it was interestingly

observed that in humans, female fetuses have a slower rate of growth more in concert with the

growth of the placenta, while male fetuses have a higher tendency to outgrow the capacity of the

placenta to maintain their viability, described as “boys live dangerously in the womb” (Brett et

al., 2014; Eriksson et al., 2009).

36

RATIONALE, HYPOTHESIS, AND OBJECTIVES

Rationale

There is an evident fall in human and bovine fertility in the last few decades. Assisted

reproduction technologies (ART) and in-vitro production (IVP) have been employed to over

come these raising issues. In order to provide safe and efficient ART and IVP there are many

areas that are still in need of significant improvement. One main area in need of a better

understanding is the endocrine and paracrine ovarian function behind creation, storage, selection

and maturation of oocytes. These processes are all crucial in establishment of maximized oocyte

yield and development potential. Anti-Mullerian hormone (AMH) has been established as a

clinical marker of oocyte quantity and ovarian reserve however few studies presented evidence

that these properties seem to be subspecies specific when measured systemically reflecting cattle

fertility characteristics. There has also been some conflicting evidence on early pregnancy

maternal circulation AMH in human as a possible be determinant of the fetal sex due to its

differential expression between male and female fetus and its placenta. AMH has also been

speculated to reflect oocyte quality measured from a single largest ovulatory follicle or pooled

follicular fluid in human. We are interested to expand the evidence on AMH in different cattle

subspecies by including local, granulosa cell and follicular fluid, AMH measurements and AMH

results from their crossbreed. We are interested to see if the difference in AMH expression

detected in early pregnant maternal and male/female fetal circulation; and placenta expression in

order to use AMH as an early fetal sex-determining marker in cattle. Last but not least, we are

interested to utilize human single follicular aspirates, monofollicular samples, and look at the

correlation to oocyte developmental potential.

37

Hypothesis

The hypothesis of this study is as follows: AMH and AMHR2 gene expression and

plasma and follicular fluid AMH protein level correlate with the oocyte quantity, developmental

potential and fetal sex.

Objectives

To test this hypothesis, the following objectives were addressed:

Objective 1: Determine if AMH and granulosa cell AMHR2 mRNA content reflect Nelore (Bos

taurus indicus) breed fertility in terms of oocyte and antral follicle number that differs compared

to Angus and Holstein breeds (Bos taurus taurus).

Objective 2: Determine if plasma AMH, and placental and cotyledonary AMHR2 mRNA

content, differ in pregnant cows carrying male vs. female fetuses.

Objective 3: Determine if monofollicular AMH protein and granulosa cell AMHR2 mRNA

content correlates to oocyte developmental potential in human.

38

CHAPTER I

SYSTEMIC AND LOCAL ANTI-MULLERIAN HORMONE REFELCTS

DIFFERENCES IN THE REPORDUCTION POTENTIAL OF ZEBU AND EUROPEAN

CATTLE

* A portion of the material in this chapter has been published in Animal Reproduction Science (Stojsin-Carter et al., 2016)

39

INTRODUCTION

The genetic background of cattle significantly impacts their reproductive performance. It

is believed that increased inbreeding to achieve maximal milk yield has negatively impacted

reproductive efficiency in temperate, Bos taurus taurus (European type cattle) animals (Bachelot

and Binart, 2007; Leroy et al., 2015). By comparison, the tropical and subtropical subspecies of

cattle, Bos taurus indicus (Zebu), generally found in India and South America, are known for

lower milk yields, but greater reproductive efficiency (Bó et al., 2003). In a direct in vitro

production (IVP) comparison with European type cattle vs. Zebu cattle reported blastocyst rate

was 25.6% and 32.1% respectively, which ultimately gave rise to two thirds more pregnancies

(Viana et al., 2010). However, Zebu were found to have lower breeding capacity due to delayed

puberty, decreased estrous duration and intensity, longer gestation length and postpartum period,

and lower twinning rate compared to European type cattle (Abeygunawardena and Dematawewa,

2004; Bó et al., 2003; Silva-Santos et al., 2011). Taken together, the greater embryo and

pregnancy rate but lower breeding capacity make Zebu cattle an ideal candidate for in vitro

embryo production (IVP). To date, there is an incomplete understanding of the underlying

endocrine, molecular and physiological factors necessary to achieve optimal IVP protocols in

Zebu and European type cattle.

Anti-Mullerian hormone (AMH) is a 140kDa glycoprotein dimer member of the TGF-

beta protein subfamily secreted by Sertoli cells in testes, and by granulosa cells (GC) in the

ovary reviewed by (di Clemente et al., 2003). In females AMH is believed to inhibit premature

follicular growth and maturation, making it the ovarian reserve “guardian” (Visser et al., 2006).

Its minimal intra and inter estrous variability makes it a useful predictor of ovarian reserve

(Fanchin, 2003; Ireland et al., 2007). The exact mechanism by which AMH acts in the ovary is

40

not certain, but it is believed to be through decreasing GC sensitivity to luteinizing hormone

(LH) and follicle stimulating hormone (FSH) (Visser and Themmen, 2005). Due to its link with

ovarian reserve, AMH is used extensively as a quantitative marker of fertility in humans, and is

also being increasingly examined as a potential biomarker of reproductive efficiency in other

species, including cattle (Ireland et al., 2011; Monniaux et al., 2011; Rico et al., 2011). Various

human studies have reported correlation of AMH concentration to a number of qualitative

reproductive parameters, such as fertilization, implantation and pregnancy rates, however, this

has not been previously shown in cattle (Fanchin et al., 2007; Majumder et al., 2010; Takahashi

et al., 2008). In addition to several reports of AMH in European type cattle (Ireland et al., 2009;

Ireland et al., 2008) there are three published investigations involving Zebu cattle (Baldrighi et

al., 2014; Batista et al., 2014; Guerreiro et al., 2014). These studies focused on comparing

plasma AMH (Pl AMH) concentration between Zebu and European type cattle and correlating to

the number of antral follicles (AFC) as a quantitative reproductive parameter. The findings of

these studies provide evidence for plasma (Pl) AMH to AFC correlation with Zebu animals

displaying greater AMH values for the same AFC compared to European type animals.

The aim of the current study was to investigate and compare the relationship between

both systemic and local AMH and reproductive parameters: AFC, ovary diameter (OD), oocyte

number, cleavage and blastocyst rate in both Zebu and European type cattle, as well as a small

cohort of crossbred animals. It was hypothesized that irrespective of its source, AMH correlated

to reproductive parameters with Zebu having greater AMH value compared to European type

cattle.

41

MATERIAL AND METHODS

Animals and Experimental Design

Study group 1

Bos taurus indicus or Zebu (Nelore breed, n=30), Bos taurus taurus or European type

cattle (Red Angus breed, n=10), and crossbred Bos taurus taurus × Bos taurus indicus (Brangus

breed, n=10) cows of average reproductive age (mean ages 8.6, 7.8 and 7.1 years respectively)

raised on pasture in Paraná state, Brazil were subjected to ovarian examination of AFC and OD

with the 2-D trans-rectal Mindray adapted with a linear transductor ultrasound, and peripheral

blood collection via puncture of the tail vein. Blood was collected in EDTA tubes (BD

Vacutaner®, BD Franklin Lakes NJ, USA) to allow for more consistent AMH ELISA

measurement. The Bovine AMH ELISA kit AL-114 (Ansh Labs, Texas, USA) was used

according to the manufacturer’s protocol with the exception of an overnight separation of plasma

at room temperature following the MOFA® Minitube Canada protocol for AMH testing.

Samples were frozen at -20°C following collection until ELISA measurement was performed.

Study group 2

Post-mortem collection of ovaries from unsynchronized, non pregnant pasture raised

Zebu (Nelore breed, n=12) and European type cattle (Holstein breed, n=56) raised under

standard dairy farming conditions, was performed in government-approved slaughterhouses in

Belem, Pará state, Brazil and Guelph, Ontario, Canada, respectively. For the Zebu cattle, each

animal had a matching blood sample as well as a pair of ovaries. Blood was collected during

exsanguination at the time of slaughter and was left overnight in EDTA tubes for separation of

plasma from blood cells at room temperature. For European type cattle, AFC was determined by

visual counting of the antral follicles per ovary. For both cattle subspecies, antral follicles, 5-

42

8mm in diameter, for each ovary were aspirated and pooled. After collection, pooled supernatant

FF was carefully removed without disturbing the cell pellet that has settled and frozen at -20°C

until AMH ELISA measurement. The pooled pellet was re-suspended with HEPES-buffered

Ham's F-10 plus 2% steer serum (Cansera; Rexdale, ON, Canada). The cumulus-oocyte

complexes (COC) were collected, counted and put into in vitro culture, while the rest of the cells

were frozen for qPCR analysis.

For investigations into mRNA expression, the total number of oocytes per ovary or ovary

pair was counted. Samples were grouped into “low” or “high” oocyte producing ovary if they

contained less than 9 or more than 19 oocytes per ovary, respectively. These cut offs were

determined by using 25th and 75th percentiles of the ovary that contained the highest number of

oocytes in order to choose the samples with the potentially most obvious difference in AMH

expression.

IVF

Bovine ovaries from the local abattoir were transported to the laboratory in a 0.9% saline

solution at 33 to 37°C. IVP was preformed as described by Ashkar et al. for samples obtained in

Canada and by Costa et al. for samples obtained in Brazil with the exception that cumulus-oocyte

complexes (COCs) were kept separate per each ovary (Ashkar et al., 2010; Costa et al., 2013). In

brief, cumulus oocyte complexes (COCs) were aspirated from ovarian follicles for collection into

HEPES buffered Ham’s F-10 plus 2% steer serum (Cansera, Rexdale, ON, Canada). COCs were

collected and in groups of 10 were matured in 80uL drops for in vitro maturation under mineral

oil (Paisley Products, Toronto), for 22-24 hours at 38.5°C in 5% CO2. The in vtiro maturation

(IVM) drops consist of TCM199 medium + 2% FBS supplemented with 1µg/mL of E2,

43

0.5µg/mL of FSH and 1µg/mL of LH (NIH, Washington, DC, USA). Frozen-thawed Bos Taurus

semen (EastGen, Guelph On) was used for in vitro fertilization. Semen was placed in 1.5mL of

HEPES Sperm TALP for 45 minutes at 38.5°C in 5% CO2 in order for swim up to occur. The

swim up product (upper layer) was then centrifuged at 2000rpm for 7 minutes. Mature oocytes

were washed twice in HEPES Sperm TALP, and twice in IVF TALP with 20µg/mL heparin, and

transferred into 80µL IVF TALP droplets under mineral oil. Sperm was added to the oocytes and

oocytes were incubated overnight with motile sperm at 38.5°C in 5% CO2. The next day

presumptive zygotes were stripped using pipette-vortexing in a HEPES Sperm TALP wash.

Zygotes were then washed in HEPES Sperm TALP twice and then transferred to synthetic

oviductal fluid (SOF) media supplemented with sodium pyruvate, non-essential and essential

amino acids, gentamicin, 15% bovine serum albumin (BSA), and Cansera. They were then

transferred to 30µL drops of SOF media under mineral oil and incubated at 38.5°C in 5% CO2. A

maximum of 10 oocytes were matured, fertilized and cultured per medium drop. Number of

oocytes was assessed at the time of collection, cleavage rate was assessed on Day 2, and

blastocyst rate on Day 8.

ELISA

AMH was measured using the Bovine AMH enzyme linked immunosorbent assay

(ELISA) kit AL-114 (Ansh Labs, Texas, USA) according to the manufacturer’s protocol. Before

measurement, FF was first diluted between 1:500 and 1:10,000 times using the supplied diluent

and placed in EDTA tubes at 4°C overnight. AMH was measured using 50µL of Pl or diluted FF

sample. The provided analytical range of the assay was 0.156 - 10ng/mL, and the analytical

44

sensitivity 0.011ng/mL. The intra-assay coefficients of variation were 2.92%, 2.54% and 3.65%

for quality control plasma samples containing 0.611, 1.259 and 2.56ng/mL AMH, respectively.

RNA extraction and reverse transcription

RNA was extracted from the GC pellets using a TRIzol reagent (Invitrogen, Cincinnati,

OH, USA) according to the manufacturer’s instructions and previous publications (Favetta et al.,

2004; Scheetz et al., 2012). In brief, each pellet was homogenized in 0.5mL of TRIzol Reagent.

Phase separation was achieved by adding chloroform, and RNA was precipitated from the

aqueous phase with isopropanol. Samples were incubated at -20°C overnight and centrifuged at

10,000g at 4°C. The RNA pellet was washed with 75% ethanol and dissolved in 20µL of sterile

RNase-free water. Contaminants were removed with DNase I treatment (Ambion, Huston, TX,

USA) and total RNA concentration was measured with a spectrophotometer. RNA samples were

stored at -80°C until further use. Reverse transcription PCR was performed using the high-

capacity complementary DNA (cDNA) reverse transcription kit (Applied Biosystems, Auckland,

New Zealand) following manufacturer’s protocol. Briefly, 500ng of oligo(dT) was first added to

each RNA sample and incubated at 70°C for 2 minutes. A mixture of 4µL of RT buffer, 1µL of

0.1M dithiothreitol, 1µL of 10mM deoxyribonucleotide triphosphates (dNTPs) mix, 0.5µL of

RNasin (40U/µL; Promega, Madison, WI, USA), and 1µL of Superscript II (200U/µL;

Invitrogen) was then added and the reaction was incubated further at 42°C for 1 hour, followed

by a final incubation at 70°C for 30 minutes. cDNA samples were stored at -20°C until further

use.

45

Real Time quantitative PCR

Real-time quantitative PCR (RT-qPCR) was carried out to determine AMH and AMHR2

transcript levels using the BIO-RAD CFX96TM Real-Time PCR System and SsoFastTM

EvaGreen Supermix (Bio-Rad Laboratories, Hercules, CA, USA) according to a standard

protocol that had been temperature optimized for the AMH, Glyceraldehyde-3-Phosphate

Dehydrogenase (GAPDH) and AMHR2 primers (Table 1). Prior to quantification, optimization

procedures were performed by running qPCRs with and without the purified template to identify

the melting temperatures of the primer dimers and specific product. Each reaction contained 5µL

of SsoFastTM EvaGreen Supermix reaction mix, 1µL of a mix of the forward and reverse

primers at a concentration of 5µmol, 2µL of the cDNA of interest and was adjusted to a total

volume of 10µL using H2O. The standard curve was established using ovarian tissue cDNA

template in five serial dilutions ranging from 1µg/µL to 0.03125µg/µL of cDNA. The

amplification program was as follows: 95°C for 10 minutes, followed by 50 amplification cycles

of 95°C for 10 seconds, 65°C for 10 seconds, 72°C for 10 seconds and acquisition of

fluorescence for 10 seconds. After the end of the last cycle, a melting curve was generated by

taking measurements every 0.5°C from 72°C to 95°C. GAPDH transcript was selected as the

housekeeping gene, as it showed the most consistent levels of mRNA expression among the

samples tested using geNorm software (Vandesompele et al., 2002). Other housekeeping genes

tested were histone (H2A), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation

protein, zeta (YWHAZ), hypoxanthine guanine phosphoribosyl transferase 1 (HPRT1) and

succinate dehydrogenase complex, subunit A (SDHA). Relative quantification of the transcripts

of interest (Table 1) was calculated between two subspecies and between the low and high

oocyte producing ovaries.

46

Table 1 Real Time PCR primers

Gene GenBank

accession

number

Sequence Reference Size (bp)

AMH NM_173890.1 F-5’-CAGGGAAGAAGTCTTCAGCA-3’

R-5’-AAGGTGGTCAAGTCACTCAG-3’

(Ireland et

al., 2009;

Scheetz et

al., 2012)

270

GAPDH NM_001034034.2 F-5’-TTCCT GGTACGACAATGAATTTG-3’

R-5’-GGAGATGGGG CAGGACTC-3’

(Hamilton

et al.,

2011)

153

AMHR2 NM_001205328.1 F-5’-GTGCTTCTCCCAGGTCATAC-3’

R-5’-AATGTGGTCATGCTGTAGGC-3’

(Monniau

x et al.,

2011)

163

Statistics

For statistical investigation Student’s t-test was used to compare parameters between the

subspecies, while Spearman correlation, and multivariable linear models were used to compare

parameters within the subspecies with p<0.05 considered statistically significant. For example,

referring to Figure 1 Part Ai which outlines the relationship between Plasma AMH and the AFC,

the following linear model was considered: Pl AMH = Intercept + AFC + Breed. Here the Breed

is a categorical variable. This allows us to model the Pl AMH for each breed, and compare the

differences between them. To compare differences between breeds, we use a Tukey test that is an

option within the general linear hypothesis test (glht) from the multcomp package in R (Team,

2009). The test allows us to estimate the differences in intercepts between the breeds, assuming

47

that the slope (related to the AFC) is constant for all breeds. This was done due to the available

sample size. A similar modeling exercise was performed comparing Pl AMH to OD (Aii), and

FF AMH to oocyte # (Bii). Pl AMH numbers were calculated using GraphPad Prism (GraphPad

Software, San Diego, CA, USA).

48

RESULTS

Study group 1

Zebu and crossbred animals had significantly greater mean Pl AMH concentration than

their European counterparts (p=0.010, p=0.018 respectively; Table 2). The Pl AMH mean

concentration for Zebu, European type cattle and crossbred cattle were 0.77±0.09, 0.33±0.24 and

0.63±0.07ng/ml respectively (Table 2). The correlation between Pl AMH and AFC was

significantly different when comparing either Zebu or crossbred to European type cattle

(p=0.004 and p=0.049 respectively; Figure 1Ai); the same result was observed for Pl AMH and

OD between Zebu and European type cattle (p=0.009; Figure 1Aii). The correlation between Pl

AMH and AFC in Zebu was significantly positive (p=0.002; Figure 1Ai). The European type

cattle had significantly lower AFC compared to Zebu and crossbreed (p=0.006, p=0.027

respectively; Table 2) and larger OD (p=0.008; Table 2) compared to Zebu animals.

Study group 2

In a subset of Zebu animals, matched plasma samples and ovary samples were available

and it was possible to observe a significant and positive correlation between Pl AMH and

number of oocytes per ovary pair (p=0.002; Figure 1Bi), with the Pl AMH mean value and the

mean oocyte number of 1.15±0.27ng/ml and 11.58±1.83, respectively.

Mean FF AMH concentration was found to be significantly greater in Zebu compared to

European type cattle (p<0.0001; Table 2). The FF AMH mean for Zebu and European type cattle

was 4934.3±568.5ng/ml and 2977.9±214.1ng/ml respectively (Table 2). The correlation between

FF AMH and oocyte number per ovary was significantly different between Zebu and European

type cattle (p<0.0001; Figure 1Bii), and only European type showed significantly positive

49

correlation (p=0.005; Figure 1Bii). A positive correlation was not observed between FF AMH

and cleavage rate, however the mean cleavage rate of 70.92±4.55 for European and 76.77±5.99

for Zebu cattle (Table 2). A positive correlation was not observed between FF AMH and

blastocyst rate, however the mean blastocyst rate of 18.94±2.96 for European and 25.05±6.34 for

Zebu cattle (Table 2). In a subset of European type animals where ovaries were collected post

mortem, it was also possible to compare FF AMH concentration to AFC, and a significant

positive correlation was observed (p=0.009; Figure 1Biii).

The expression of AMH GC mRNA was not found to be significantly different between

either low or high oocyte producing ovary groups, or between European type and Zebu cattle

(Figure 2A). The expression of AMHR2 mRNA was found to be significantly different between

low and high group for European type cattle (p=0.035; Figure 2B) and positively correlated to

oocyte number in this subspecies (p=0.01).

50

Table 2 Summary of antral follicle count (AFC), ovary diameter (OD), plasma anti-Mullerian hormone (Pl AMH) from Study group 1, and follicular fluid AMH (FF AMH), oocyte, cleavage and blastocyst rate mean values (± SE) from Study group 2 for European type (E), Zebu (Z) and crossbred (C) cattle and the p-values from their average value comparisons. Significant difference (p<0.05) is indicated by the symbol (*).

Study group 1 Study group 2

AFC OD (mm) Pl AMH (ng/mL)

FF AMH (ng/mL)

Oocyte #/ovary

Cleavage rate/ovary

Blastocyst rate/ovary

European (E)

17.14 ± 1.82 (n=7)

66.20 ± 3.50 (n=7)

0.33 ± 0.24 (n=8)

2977.9 ± 214.1 (n=56)

17.5 ± 1.60 (n=56)

70.92 ± 4.55 (n=32)

18.94 ± 2.96 (n=32)

Zebu (Z)

27.37 ± 1.83 (n=30)

57.66 ± 1.17 (n=30)

0.77 ± 0.09 (n=30)

4934.3 ± 568.5 (n=24)

11.58 ± 1.83 (n=24)

76.77 ± 5.99 (n=24)

25.05 ± 6.34 (n=24)

Crossbred (C)

25.83 ± 10.55 (n=6)

59.03 ± 3.45 (n=6)

0.63 ± 0.07 (n=10)

P-values

E vs. Z *0.006 *0.008 *0.010 *<0.0001 0.064

E vs. C *0.027 0.138 *0.018

Z vs. C 0.782 0.581 0.532

51

Figure 1 Correlations between anti-Mullerian hormone (AMH) and reproductive parameters in European type (E, light gray square), Zebu (Z, black triangle) and crossbred (C, dark grey diamond) cattle. The plots show simple linear regression trend lines for each of the breeds but that they do not reflect the model that was used in the statistical analysis. A) represented Study group 1 and B) represented Study group 2. Ai) Plasma AMH (Pl AMH) vs. antral follicle count (AFC) for E (n=7), Z (n=30) and C (n=6) animals. Z correlation, ρ=0.54, p=0.002; Z to E comparison, p=0.004; C to E comparison, p=0.049. Aii) Pl AMH concentration vs. ovarian diameter (OD) in E (n=6), Z (n=26) and C (n=6) animals. Z correlation, ρ=0.36, p=0.067; Z to E comparison, p=0.009; C to E comparison, p=0.094. Bi) Pl AMH vs. average number of oocytes per pair in Z (n=12; ρ=0.818, p=0.002); Bii) Follicular fluid AMH (FF AMH) concentration vs. number of oocytes in Z (n=24), and E (n=59) cattle. E correlation, ρ=0.37, p=0.005; Z to E comparison, p<0.0001. Biii) FF AMH concentration (ng/ml) vs. AFC in E (n=56; ρ=0.35, p=0.009).

52

Figure 2 A) Relative granulosa cell anti-Mullerian hormone (GC AMH) mRNA expression in low vs. high oocyte producing ovaries for European type (grey, n=56) and Zebu (black, n=10) cattle. B) Relative GC AMH and anti-Mullerian hormone receptor 2 (AMHR2) mRNA expression in low (light gray) vs. high (dark gray) oocyte producing ovaries for European type cattle (n=56) was found to be significantly different (p=0.035). Glyceraldehyde 3-phosphate dehydrogenase housekeeping gene used to determine relative expression level, error bars denote the standard error of the mean (SEM) and significant difference (p<0.05) is indicated by the symbol (*).

*

53

DISSCUSION

The aim of the current study was to investigate and compare the relationship between

both systemic and local AMH and reproductive parameters: antral follicle count, ovary diameter,

oocyte number, cleavage and blastocyst rate in both Zebu and European type cattle, as well as a

small cohort of crossbred animals. Preliminary research published by Batista et al. and Baldrighi

et al. examined and revealed for the first time that plasma AMH and AFC relationship is greater

in Zebu compared to European type cattle (Baldrighi et al., 2014; Batista et al., 2014). The

current report expands their preliminary research by providing evidence that AMH, from both

sources Pl and FF, is significantly different between Zebu and European type cattle for all

examined parameters with Zebu displaying greater AMH values. Plasma and FF AMH was

found correlated with two of the reproductive parameters examined, AFC and oocyte number.

Additionally for the first time in European type cattle GC AMHR2 RNA expression was

examined and found positively correlated to oocyte number. The sequencing of the AMHR2

cDNA product was performed and confirmed 100% homology to the bovine AMHR2 (GenBank

accession number NM_001205328.1). Plasma AMH concentration was also measured in

crossbred cattle and found to more closely mirror their maternal Zebu concentration.

The European type cattle FF AMH concentration displayed a significant positive

correlation to the quantitative reproductive markers: AFC and number of oocytes. A positive

trend yet non-significant was also observed when comparing Pl AMH to AFC. Our results for

AMH in European type cattle are in general agreement with the current literature, however none

of the published work to our knowledge directly compared AMH from both Pl and FF between

two subspecies of cattle. In the current study, FF AMH in bovine subspecies was not found to

have a significant correlation with cleavage nor blastocyst rate, which is in agreement with

54

previous bovine studies correlating reproductive parameters to oocyte quality (Guerreiro et al.,

2014; Ireland et al., 2007). Nevertheless in human studies, AMH from both FF and serum has

been found to correlate to qualitative oocyte markers such as fertilization and implantation rates

(Fanchin et al., 2007; Majumder et al., 2010; Takahashi et al., 2008). The study by Kawamura et

al. speculated that AFC as a quantitative marker has a direct effect on the ovarian structure and

morphology and therefore should have an effect on the quality of oocytes within the ovary.

Further study looking at the oocyte quality parameters would be required to determine if the

absence of the relationship between the quantitative and qualitative markers is the result of

inherent species differences or factors related to in vitro culture conditions.

Granulosa expression measurements were performed in the low and high oocyte yielding

ovaries where the difference in the protein and transcript amounts would be expected to be the

greatest. GC AMH RNA expression measurements from low and high oocyte yielding ovaries

did not appear to differ in the current study. Previously it has been demonstrated that even a

1mm size change in follicle is associated with an exponential expression difference in AMH

level due to its crucial role in follicle growth and maturation (Rico et al., 2011). This would lead

to variability of the AMH GC expression data within both high and low yielding groups, and

possibly result in the absence of the expected difference. It could be speculated that other

determinants beside follicle size also need to be measured and considered during comparison.

Significant positive correlation was observed between GC AMHR2 RNA levels and number of

oocytes, as well as significant difference in levels between the low and high oocyte producing

ovaries. The measured levels of AMHR2 transcript reported here are in accordance with

previously published results in goat GCs (Monniaux et al., 2011).

55

Zebu cattle are known for their greater in vitro embryo and pregnancy rate but lower

breeding capacity. Beyond their different IVP rates and estrous cycle characteristics, the

underlying physiological and endocrine basis for their different reproductive potential is not clear.

In this study, Zebu Pl AMH concentration was significantly positively correlated with

reproductive parameters: AFC and average number of oocytes per pair of ovaries, as well as FF

AMH and number of oocytes, which indicates that AMH irrespective of being systemic or local

can be used as a quantitative reproductive marker. Overall this is in general agreement with the

current AMH model and patterns reported in previous human, European type cattle and Zebu

experiments by Baldraghi et al. and Batista et al. (Baldrighi et al., 2014; Batista et al., 2014;

Stojsin- Carter et al., 2016). Importantly, although Zebu and European type cattle appear to

follow the same patterns of positive correlation, the AMH values and correlated parameters were

significantly different in every case, with Zebu expressing significantly greater AMH

concentrations compared to European type cattle at matched parameter values. This result

demonstrates the importance of species and subspecies when interpreting AMH data.

The crossbred cattle included in this study appeared to be intermediate between the two

subspecies, but more comparable to their Zebu counterparts. The crossbred cows were created

using semen from European bulls to inseminate the Zebu cows despite being considered a 3/8

Zebu, 5/8 European type cattle cross on a genetic level. This also underscores the importance of

considering the genetic background of animals when conducting and interpreting bovine AMH

studies.

56

CHAPTER II

PREGNANCY ANTI-MULLERIAN HORMONE AS A FETAL SEX-DETERMINING

FACTOR

57

INTRODUCTION

In the bovine industry, the ability to influence and determine fetal sex enhances

management of herd breeding, allows for faster genetic progress, has implications in sex-linked

diseases, and improves conservation of superior and endangered animals. Preconception sex

selection by means of sperm sex sorting, or pre-implantation genetic diagnosis (PGD) coupled

with IVF, has been employed since late 1980’s (Andrabi and Maxwell, 2007; Bodo et al., 2001;

Choudhary et al., 2016). Even before 2005, over 30,000 cattle offspring had been produced using

sexed spermatozoa, obtained mostly by flow cytometric sperm sorting (Armstrong et al., 2015; L.

A. Johnson et al., 2005). PGD has been shown to be highly accurate and efficient in sex selection

even in field conditions, however, a major problem for PGD remains its dependence on the use

of IVF (Lopes et al., 2001; Majumder et al., 2010; Nelson et al., 2007; Penarrubia et al., 2005;

Silberstein, 2005; Takahashi et al., 2008; Tremellen et al., 2005; Wunder et al., 2008).

At present, ultrasound starting from 8th week of pregnancy is the most widespread

prenatal sex determination method in bovine industry, as it’s readily available and non-invasive

(Stroud, 2005). However most accurate results are achieved after 10th week of gestation (Ali and

Fahmy, 2008; Stroud, 2005). The downside of this diagnostic method is the lack of consistency

due to variability in both technician skills and in the position of the fetus.

Although usually investigated as a marker for fertility and ovarian reserve, and as an

infancy marker for testicular function, AMH has recently gained attention as a potential early

pregnancy sex-determining marker due to its few hundred-fold concentration difference in

expression by male vs. female fetuses. The increased rate of AMH expression by males starts

from as early as the 7th week of gestation, which could theoretically place it as one of the earliest

58

measurable molecular markers for determining bovine fetal sex (Vigier et al., 1984). Despite this

potential, only a few studies to date have investigated human maternal levels of AMH during

gestation, without reference to fetal sex (La Marca, 2005; Nelson et al., 2010) or with reference

to fetal sex (Empey et al., 2012). All of these studies showed a decline of maternal AMH levels

during pregnancy, presumably due to inactivated follicle growth (Kuijper et al., 2013). The

single study that considered the impact of fetal sex on maternal AMH did reveal a significant

higher Pl AMH levels in mothers carrying a female vs. male fetus (Empey et al., 2012). An

additional recent article by Novembri et al. investigated the placenta of fetuses of both sexes as a

potential source of AMH at birth (Novembri et al., 2015). The authors reported that AMH

expression was not different between the sexes, however the staining intensity of the AMH

antibody appeared higher in the placenta of male pregnancies. These initial studies show the

potential impact of pregnancy on maternal AMH biology, the possibility of AMH representing

an actual marker of fetal sex and the need to consider the potential role of the placenta in the

current and future studies.

The aim of this chapter is to investigate the association between the levels of plasma

AMH in cows carrying female and cows carrying male fetuses at four different time points,

gestation day 0, 35, 135 and 275, for each animal. Also, plasma AMH was measured in single

time points in cows carrying female and cows carrying male fetuses in the period between 85 and

155 days of gestation. Lastly, expression of AMHR2 was measured in the placenta and cotyledon

of male and female fetus pregnancies between 38 and 80 days of gestation to determine if there

is a placental derived sex linked difference. It was hypothesized that levels of plasma AMH

between cows carrying a male vs. cows carrying a female fetus would differ, being higher in the

cows carrying a male fetus, with neither the placenta or cotyledon having an additive effect.

59

METHODS

Animals and Experimental Design

Study group 1

B. taurus indicus or Zebu (n=13) cows of average reproductive age raised on the pasture

in São Paulo state, Brazil were subjected to artificial insemination (AI) and peripheral blood

collection via puncture of the tail vein at day 0 (AI), 35, 135 and 275 of gestation (Figure 3). Out

of 13 animals, 4 animals aborted, 1 animal sample got damaged, and in 8 animals (n=8)

pregnancy resulted in a birth of a healthy singleton calf with all samples successfully retrieved.

Fetal sex determination was assessed using 2-D trans-rectal Mindray adapted with a liner

transductor ultrasound during the 2nd trimester and then was confirmed at birth. Out of 8 animals,

3 carried a female and 5 carried a male fetus. All blood sampling was done by the same person

and blood was collected in EDTA tubes (BD Vacutaner®, BD Franklin Lakes NJ, USA). Plasma

was centrifuged at 1.400rpm and the top layer was aspirated to a new 1.5ml tube and frozen at -

80°C. Samples were shipped on dry ice to the Pará state, Brazil for the ELISA measurements.

The Bovine AMH ELISA kit AL-114 (Ansh Labs, Texas, USA) was used according to the

manufacturer’s protocol.

Study group 2

Post-mortem blood collection of singleton pregnant pasture raised B. taurus indicus or

Zebu cows (n=21) carrying 10 male and 11 female fetuses, was performed in a Para State

Surveillance Agency approved slaughterhouse located in Castanhal, Brazil (Figure 3). The cows’

ages were variable, however they were estimated to be between 6 and 10 years old. Cow’s blood

was collected during exsanguination at the time of slaughter in EDTA tubes. Matching fetal

60

blood was collected in EDTA tubes via heart puncture with a 23-gauge butterfly infusion set

attached to a 5mL syringe and 10ml syringe. Fetal crown to rump length was from 15 to 43 cm,

estimated to represent a 2nd trimester, more specifically 85-155 days old (~3-5 month) fetus.

Fetal sex was determined visually based on the presence or absence of a scrotum and annogenital

distance. Plasma samples were centrifuged at 3000rpm and the top layer was aspirated to a

new 1.5ml tube and frozen at -20°C until the AMH ELISA measurements.

Study group 3

Post-mortem reproductive tracts of singleton pregnant B. taurus taurus of average

reproductive age were collected from the government-approved slaughterhouses in Guelph,

Ontario Canada (Figure 3). Reproductive tracts were transported on ice and sampling was

performed at the University of Guelph. Samples from 13 fetuses, 13 cotyledon and 13 non-

cotyledon from each placenta were obtained and snap frozen in liquid nitrogen. Fetus age was

determined based on the crown to rump length representing 1st trimester, specifically 3-4.5

months of pregnancy, 38 to 73 days for 7 male (2.2-12.5cm) and 56-80 days for 6 female (5.3-

14.5cm). Anogenital distance was used for sex determination. In order to confirm the sex of the

fetus, DNA extraction and quantitative PCR using GAPDH and testes-specific protein Y

encoded (TSPY) primers from Table 3 was performed from the epithelial fetus tissue samples.

Placenta samples were used to measure quantity of AMHR2 RNA expression via quantitative

PCR described in Chapter 1, using GAPDH and Peptidylprolyl Isomerase A (PPIA) as

housekeeping genes, Table 3.

61

Figure 3 Visual representation of the three study groups for the Chapter 2. Horizontal line represents the time line of gestation divided into the three trimesters and each trimester into three months starting with artificial insemination (AI) of the cow and ending at birth. Literature based fetal expression of AMH is represented by either blue for male at 60 days or red for female at 150 days, with large and small arrows corresponding to the level of expression. In dark red: Study group I, collections at day 0, 35, 135 and 275 and study group II collections from 85 to 155 days of gestation and study group III collections from 38 to 80 days of gestation. In yellow: (Empey et al., 2012; Fanchin et al., 2007) detected significant difference in maternal blood AMH levels between male and female fetuses in humans in between 11th and 15th week of pregnancy, approximately corresponding to 77 and 105 days of gestation.


Gene GenBank

accession

number

Sequence Reference Size

(bp)

GAPDH NM_001034034.2 F-5’-TTCCTGGTACGACAATGAATTTG-3’

R-5’-GGAGATGGGGCAGGACTC-3’

(Hamilton et al.,

2011)

153

TSPY NM_001244608.1 F-5’- CCCAGAATCGAACAGGATTG-3’

R-5’- TTGTCTCTCACGGACGAACC-3’

(Hamilton et al.,

2009)

215

AMHR2 NM_001205328.1 F-5’-GTGCTTCTCCCAGGTCATAC-3’

R-5’-AATGTGGTCATGCTGTAGGC-3’

(Monniaux et

al., 2011)

163

PPIA NM_178320.2 F-5’- TCTTGTCCATGGCAAATGCTG -3’

R-5’- TTTCACCTTGCCAAAGTACCAC -3’

(Ferris et al.,

2016)

111

62

DNA extraction and sex confirmation using TSPY

Each epithelial tissue sample was taken out of the liquid nitrogen and homogenized using

a pestle. Homogenized tissue samples were immediately transferred to a tube containing 4ml of

digestion buffer and vortexed to dissolve any clumps. Homogenized tissues were incubated in a

water bath at 50°C for 5 hours. Samples were vortexed every hour for 10 seconds. After

incubation, DNA was extracted using a phenol/savage solution (2ml sample: 1ml phenol: 1ml

savage) and precipitated using ammonium acetate (4M) and isopropanol. The strands of DNA

were scooped out of the solution with a sterile glass hook, washed with 70% alcohol, air dried

for 30 sec to 1 min. The DNA obtained from each sample was resuspended in 100ul of nuclease

free water and kept in the refrigerator overnight. After extraction was completed, DNA obtained

from each tissue was quantified using a NanoDrop spectrophotometer. The TSPY primers (Table

3) amplified a 215bp product from genomic DNA. A 10ul reaction contained 5mM primers, 6ng

of genomic DNA and 1X SsoFast EvaGreen Supermix (Bio-Rad) was carried out in a CFX96

Touch™ Real Time–PCR Detection System (Bio-Rad) with denaturation at 98°C for 2 minutes,

followed by 50 cycles of 98°C for 5 seconds, 60°C for 5 seconds and 95°C for 10 seconds.

Melting curve was obtained starting at 72°C with measurements taken every 0.2°C until 95°C.

All biological replicates were run in triplicates. Since TSPY was used for male or female

confirmation and not quantitative measurements, standard curve was not necessary. Male were

identified as TSPY positive while female were TSPY negative samples.

63


RNA extraction was performed as described in Chapter 1 except the reverse transcription

that was performed using qScriptTM cDNA SuperMix (Quanta Biosciences, Canada) according to

the manufacturer’s instructions.

Real time quantitative PCR

Real time quantitative PCR was performed as described in Chapter 1 using primers from

Table 3. The amplification program was as follows: 95°C for 10 minutes, followed by 50

amplification cycles of 95°C for 10 seconds, 60°C for 10 second (and not 65°C as in Chapter 1),

72°C for 10 seconds and acquisition of fluorescence for 10 seconds. Standard curves for GAPDH

and PPIA primers were generated using pooled male and female fetal placenta cotyledon and

non-cotyledon cDNA samples in six serial dilutions ranging from 12.5 to 0.781ng/ul, while

standard curve for the AMHR2 primers were generated using bovine adult testes cDNA sample

in six serial dilutions ranging from 50 to 3.125ng/ul. Calibrator sample used to avoid inter plate

variation was bovine adult testes.

ELISA

Procedure for AMH measurement using the ELISA kit are described in Chapter 1 and

apply to Study group 1 and 2 from this chapter. Novel for the AMH ELISA kit in this Chapter is

use of provided controls, Low and High, specific for each plate and AMH units were pg/ml and

not ng/ml. Specific to Study group 1 and this Chapter is that all the samples from each animal

were all sampled on the same ELISA plate and were done in triplicates. A few of the samples

64

were run more than once across all the plates and shown to be within allowed levels of variation.

Male fetal samples were diluted 100 times.

Statistics

Wilcoxon rank sum test was used to check statistical significance in the patterns of male

vs. female AMH levels throughout pregnancy. Wilcoxon test and Spearman correlation test was

performed to test difference and correlation between serum AMH levels of male fetus to cow and

female fetus to cow during 2nd trimester of pregnancy, as well as AMHR RNA expression

between female and male cotyledon and placenta samples during 1st trimester.

65

RESULTS

Study group 1

Based on the raw data was presented in Appendix I, the difference between day 35 and

135 in Pl AMH was found significant between cows Bos taurus indicus carrying a male, n=5,

and a female fetus, n=3 (p=0.036; Figure 4A). The average change in the level of Pl AMH

between these two time points for cows carrying a male fetus was 255.4±178.5pg/ml, while for

cows carrying a female fetus was -181.3±146.1pg/ml. The difference between day 275 and 135

in Pl AMH were found not significant between cows carrying a male or a female fetus (p=0.786;

Figure 4A). The average change in the level of Pl AMH between these two time points for cows

carrying a male fetus was 87.6±161.2pg/ml, while for cows carrying a female fetus was

59.5±54.3pg/ml.

The relative difference between day 35 and 135 in terms of the level at day 35 in Pl AMH

was found not significant between cows carrying a male or female fetus (p=0.571; Figure 4B).

The average relative change in the level of Pl AMH between these two time points for cows

carrying a male fetus was 0.432±0.260, while for cows carrying a female fetus was 0.160±0.067.

The relative difference between day 275 and 135 in terms of the level at day 135 in Pl AMH was

found not significant between cows carrying a male or female fetus (p=0.549; Figure 4B). The

average relative change in the level of Pl AMH between these two time points for cows carrying

a male fetus was 0.294±0.062, while for cows carrying a female fetus was 0.220±0.190.

66

Study group 2

Pregnant cow Pl AMH for the period of 85 to 155 days of gestation in cows carrying a

male or female fetus was not found significantly different (p=0.557; Figure 5A). The average Pl

AMH for the same period for a cow carrying a male fetus was 947.3±146.6pg/ml, and for a cow

carrying a female fetus was 809.4±180.5pg/ml. The average fetus Pl AMH for males (n=10) was

175,309.9±16,903.7pg/ml and for females (n=11) was 154.1±22.3pg/ml. There was a significant

difference between the levels of male and female fetuses Pl AMH (p<0.05); male fetus and cow

pregnant with the male fetus (p<0.05); and female fetus and cow pregnant with the female fetus

(p<0.05) Figure 5A. The correlation between Bos taurus indicus pregnant cow Pl AMH and fetus

size was not found significant for male fetus carrying cows (n=10; ρ=-0.16; p=0.650; Figure 5B)

nor for female fetus carrying cows (n=11; ρ=-0.21; p=0.523; Figure 5B).

Study group 3

The correlation between days in utero and relative AMHR2 RNA expression from the

cotyledon of Bos taurus taurus was not found significant in cows carrying a male (n= 6, ρ=-0.09,

p=0.870; Figure 6A) or a female fetus (n=7, ρ=0.66, p=0.102; Figure 6A). Cotyledon and

placenta samples were evaluated based on the fetal sex male vs. female and AMHR2 RNA

expression and found not to be significantly different for the cotyledon (p=0.553; Figure 6B) and

for the placenta (n=3 vs. n=4 respectively, p=0.660; Figure 6B). When comparing within each

sex, cotyledon vs. placenta, results were found also not to be significant for the male samples

(p=0.381; Figure 6B), and for the female samples (p=0.927; Figure 6B). The average male

cotyledon relative AMHR2 RNA expression was 0.015±0.004, and female was 0.017±0.001.

67

The average male placenta relative AMHR2 RNA expression was 0.050±0.030, and female was

0.081±0.060.

Figure 4 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in cows Bos taurus indicus during gestation at 2 time periods, between day 35 and 135 (purple), and between day 135 and 275 (orange) carrying male (M; n=5) vs. female calves (F; n=3). A) Y-axis represents change in Pl AMH between M and F at two time periods, first time period found to be significantly different between M and F (p= 0.036), indicated by the symbol (*). B) Y-axis represents relative change in Pl AMH in terms of its previous value, example: Δ Pl AMH (day x - day y) / Pl AMH (day y). Error bars denote the standard error of the mean (SEM).

68

Figure 5 Graphs representing plasma AMH (Pl AMH) values (pg/ml) measured using Ansh ELISA kit in Bos taurus indicus cows (with male, n=10, in blue and with female, n=11, in red) and fetus (male, n=10, in green and female, n=11, in purple) at single time points throughout pregnancy, between day 85 and 155, fetus size from 15cm to 45 cm A) Graph represents average level of Pl AMH of pregnant cow and fetus for period from 85 to 155 days, sex denoted as male (M) and female (F). Difference between the cows was not significant (p=0.560), however differences that were significant were between the female fetuses and cows with those female fetuses (*, p<0.05), between the male fetuses and the cows with those male fetuses (**, p<0.05), and the male and female fetus (***, p<0.05). Error bars denote the standard error of the mean (SEM). B) Graph represents relationship between pregnant cow with male (green triangle) or female fetus (purple cross), or male (blue rhombus) or female fetus (red square) Pl AMH and fetus size in cm.

Figure 6 Graphs representing relative AMHR2 RNA expression from male (blue; n=6) and female (red; n=7) cotyledon (Cot.) and male (M. in blue; n=2) and female (F. in red; n=3) placenta (Plac.) during 1st trimester in Bos taurus taurus. A) Male vs. female relative AMHR2 RNA expression from cotyledon only, gestation days 38 to 76 for male, and 56 to 80 for female. B) Male vs. female cotyledon and placenta relative AMHR2 RNA expression. Gestation days from placenta samples 42 to 46 for males, and 70 to 80 for females. AMHR2 RNA was compared to two housekeeping genes Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A to determine relative expression level. Error bars denote the standard error of the mean (SEM).

69

DISCUSSION

The aim of the current objective was to investigate the levels of Pl AMH in cows carrying

female vs. cows carrying male fetuses at four different time points for each animal: gestation day

0, 35, 135 and 275. Additionally, Pl AMH levels were measured at time of slaughter in a

separate cohort of cows and their respective female or male fetuses in the period between 85 and

155 days of gestation. Lastly, expression of AMHR2 was measured in the placenta and cotyledon

of male and female pregnancies between 38 and 80 days of gestation to investigate possible sex

differences in its expression. It was hypothesized that levels of Pl AMH between cows carrying a

male fetus vs. cows carrying a female fetus would differ, being higher in the cows carrying a

male fetus, and that the placenta and cotyledon would express AMHR2 at a comparable level in

pregnancies of both sexes.

Here, for the first time in a bovine study, we present evidence that cows carrying a male

fetus have significantly higher difference in Pl AMH levels than cows carrying a female fetus.

This observation is in general agreement with the previous humans studies (Empey et al., 2012;

La Marca, 2005). Beginning with Ebner et al. who characterized the range of non-pregnant

systemic AMH level in humans associated with the optimal fertility (Ebner, 2006), Empey et al.

observed women carrying a female fetus show a drop in systemic AMH levels and that those

carrying a male fetus showed levels that were closer to those of the non-pregnant state. In the

current study, we present evidence that in cows carrying a female fetus Pl AMH dropped by

approximately 20% compared to the non-pregnant Pl AMH value, while in cows carrying a male

fetus it increased by about 30%. The overall difference of approximately 50% is comparable to

the findings in humans, which showed a doubling of Pl AMH levels of mothers carrying a fetus

of the opposite sex (Empey et al., 2012). The range, defined by Empey et al., where the influence

70

of fetal sex can be observed on the maternal systemic AMH levels was between 11th and 15th

week of gestation, which falls within the range identified by our current results. Although it did

not consider fetal sex, the previous human study by LaMarca at al. presented evidence of

increased levels of systemic AMH in the 2nd trimester, which can be seen to parallel our current

findings in cattle (La Marca, 2005). The close overall agreement between the current bovine

study and previous human results demonstrates the strong reproductive similarity between these

two species.

Importantly, the observation of significant fetal sex influence on maternal difference in Pl

AMH levels in the current study provides additional evidence that it represents a potential

marker for fetal sex during early pregnancy. As discussed in the Introduction, accurate detection

of the fetus sex in the first trimester of pregnancy could facilitate planning for herd management

and breeding programs. Interestingly, AMH receptors were shown not only expressed in the

ovary, but also brain, lung and adrenal tissue (Imhoff et al., 2013). This opens the possibility that

fetal sex could potentially influence broader aspects of maternal physiology or even mental state

via AMH signaling pathways. Looking at previous reports, when they are carrying fetuses of the

opposite sex, mothers with chronic health conditions have been shown to respond differently to

medical treatment, implying that fetal sex does in some way have an impact on the mother

(Firoozi et al., 2009; Hocher et al., 2009; Walsh et al., 2015). Recognizing the small sample size

of the current study, the future experiments with larger animal numbers and additional sampling

times should be completed to confirm these results and further assess the utility, accuracy and

feasibility of maternal AMH levels as a fetal sex marker.

While the current study found a significant difference in Pl AMH levels between cows

carrying a female or male fetus when multiple measurements were made and considered for each

71

individual cow, a separate cohort consisting of animals that were sampled at only a single time

point did not show a significant difference for the same variable. This can be explained by the

large individual variation in baseline AMH levels shown in Chapter I and the fact that the single

time point sampling, used for the second cohort, did not allow this variation to be normalized for

or considered during analysis (Anderson et al., 2012; J. J. Ireland et al., 2011). Larger animal

numbers are believed to reveal a significant difference even with the single time point

measurements. However, in the current study, technical limitations did not allow for either the

collection of multiple measurements or the inclusion of additional animals in the second cohort.

In addition to maternal Pl AMH, the current study also directly sampled fetuses to

determine fetal Pl AMH levels. To our knowledge, this represents the first report of fetal Pl

AMH levels in cattle. The fetal samples were taken at between day 85 and 155 of gestation and

the observed AMH levels were found to be significantly different compared to those of the

carrying cow. Further, male fetal Pl AMH was found to be approximately 1000x higher than

female fetal levels, and approximately 100x higher than in the Pl AMH levels of the carrying

cows. Although novel as fetal measurements, the relationships and levels observed in each fetal

sex agree with interpolations of published calf Pl AMH levels (Kitahara et al., 2012b; 2012a;

Rota et al., 2002). The current results also fit within previous literature describing a rise in male

bovine and human fetal AMH expression at around 7 and 8 weeks of pregnancy respectively, and

the suspected onset of female human fetal ovarian AMH expression at approximately 140 days

of gestation (Matzuk and Lamb, 2002; Teixeira et al., 2001; Vigier et al., 1984).

Considering the above results and previous reports in combination, specifically the

observations that cows carrying a female pregnancy show decreased Pl AMH compared to a non-

pregnant state, and that male fetal Pl AMH levels were significantly higher than both female fetal

72

and maternal levels, suggests that fetal sex is a significant determinant of maternal AMH levels.

On this basis, we propose a working model of maternal and fetal AMH biology during pregnancy

(Figure 7). In this model, maternal ovarian AMH production decreases during pregnancy and this

decrease is either compensated for, or not compensated for, by AMH produced by a male or

female fetus respectively. The following three assumptions were made within this model and are

considered further below: 1) maternal AMH production decreases during pregnancy; 2) the

placenta, as the other major feature additional to the fetus during pregnancy, is neither a

significant contributor to AMH levels nor complete barrier to fetal-maternal AMH transmission;

3) fetal AMH production falls within the necessary ranges to explain the observed maternal Pl

AMH values.

Both the current experiments and previous studies in humans also show decrease in

maternal Pl AMH during pregnancy, which suggests AMH production by the maternal ovaries is

affected by the pregnant state (La Marca, 2005; Nelson et al., 2010). Considering the physiology

of pregnancy and our understanding of ovarian AMH biogenesis, this is not surprising. During

pregnancy, high progesterone and human chorionic gonadotropin (hCG) values act to inhibit

gonadotropins expressed by the pituitary, which in turn inhibits stimulation of the ovary and

follicular development and cycling. This difference in the ovary between the pregnant compared

to the non-pregnant state in the human and bovine species can be directly observed, with the

pregnant-state ovary showing smaller follicular number and size, and premature follicular atresia

(Guilbault et al., 1986; 2012a; Pierson and Ginther, 1986; Westergaard, 1985). As AMH

production in the ovary is directly tied to follicular development and ovarian cycling, the

quieting of the ovary during pregnancy can be strongly linked to a decline in maternal AMH

production (Kuijper et al., 2013).

73

The role of the placenta in AMH biology has not been extensively explored. A previous

human study by Novembri et al. examined placenta and fetal membranes at birth and detected

expression of both AMH and AMHR2 that did not differ between opposite sex fetuses

(Novembri et al., 2015). The current study is in agreement with their findings in terms of

AMHR2 expression, however, using the same technique we were unable to detect AMH

expression in bovine cotyledon and placenta samples between gestation day 38 and 80 (data not

shown). From these two studies, it can be proposed that placental differences between the species

of each study, as well as time of sampling could be all possible reasons why AMH expression in

the bovine placenta and cotyledon was not detected. Therefore, until additional studies are

conducted, the possibility remains that placental AMH production may be contributing to

maternal AMH levels; however, the results of this current study support the alternative

hypothesis that the placenta expresses AMHR2, but not AMH itself. Although the observations

of the current study are unlikely to represent subspecies differences, it is important to note that Pl

AMH levels in the current study were all measured in Bos taurus indicus, while the placenta and

cotyledon samples were obtained from Bos taurus taurus.

In order to speculate about the increases in maternal Pl AMH due to fetal AMH

production, one has to explore the ability of fetal AMH to cross the placenta and enter the

maternal circulation. Larger charged molecules, such as peptide hormones like AMH, can move

across the bovine placenta by means of active transport by either specialized receptor molecules

within microvesicles (receptor mediated endocytosis) (Pereira et al., 2013; Sandvig and Llorente,

2012), or by pinocytosis of syncytiotrophoblast cells (Palmeira et al., 2012), or by passive

transport at a very slow rate (Malek et al., 1998). Although the ability of AMH to cross the

placenta by these methods has not been directly investigated, previous reports on molecules with

74

similar characteristics, such as IgG and alpha fetal protein (AFP) in human, and enhanced Green

Fluorescent Protein (eGFP) in cattle support the possibility (Brownbill et al., 1995; Duc-Goiran

et al., 2006; Malek et al., 1998; Pereira et al., 2013; Sandvig and Llorente, 2012).

Lastly, assuming fetal AMH can cross through the placenta, the remaining question is

whether this difference would be detectable in the mother, due to its dilution in the larger blood

volume of the mother compared to the fetus. It was determined previously that the first trimester

fetal blood volume in cattle is around 10 000 times lower (~4ml) than the mother (~40 000ml)

(Reynolds, 1953). We have presented evidence that in cattle, the male fetal plasma AMH is up to

500x more concentrated than in the maternal plasma. Considering these values, the overall rise of

maternal AMH levels following dilution of male fetal AMH levels in the maternal blood volume

could be expected to fall between 0.05 to 0.5ng/ml. In our study, we found the rise to be

approximately 0.2ng/ml, which is in line with this rough prediction. Further, maternal Pl AMH in

non-pregnant cows is on average only 0.33ng/ml, meaning this increase represents a significant

proportion of their baseline values (Stojsin- Carter et al., 2016).

In summary, the current study provides evidence of fetal-sex linked differences in

maternal AMH levels and proposes a model where they are driven by a decreases in maternal

AMH production coupled with sex-dependent fetal AMH production. The importance of these

findings lies in their demonstration of the need to consider the potential impact of pregnancy and

fetal sex in future studies of AMH, the potential to use maternal Pl AMH levels as a marker of

fetal sex during early pregnancy and their contribution to our broader knowledge of AMH

biology and ovarian function during pregnancy.

75

Figure 7 Model describing the fetal testicular AMH secretion 1000x higher than the fetal ovarian AMH secretion and 100x higher than the cow’s ovarian secretion observed between day 85 and 155 of gestation. Model proposes that male fetal AMH crosses placenta and enters maternal circulation leading to the rise in the cow’s Pl AMH compared to the cows that carry female fetuses observed between day 35 and 135 of gestation.

76

CHAPTER III

HUMAN MONOFOLLICULAR ANTI-MULLERIAN HORMONE IN RELATION TO

OOCYTE DEVELOPMENT

77

INTRODUCTION

Genomics, transcriptomics, proteomics and metabolomics based methods have all been

employed in an attempt to determine what factors have the most influence on oocyte

developmental potential. However, most of their currently proposed implementations failed to

show sufficient non-invasiveness, consistency, reliability and cost effectiveness in order to be

widely accepted and used. The gold standard in most of human and bovine IVF is still the

morphokinetics approach. This is the morphological examination of the gamete and embryo,

coupled with the monitoring of the speed of embryo development. If performed visually by

individuals, it is found to be subjective and inconsistent (Bols et al., 2012). Standardizing the

evaluation of embryos using morphokinetics has been employed using time-lapse microscopy

(TLM), which captures images of the developing embryo within the incubator and uses an

algorithm to determine its viability. However, recently the Cochrane Database of Systematic

Reviews examined 3 randomized control trials, including 994 women and their IVF success rate

based on use of time-lapse microscopy, and found that there is no difference in the rates of

clinical pregnancy, live birth, miscarriage, and still birth, with or without the use of TLM

(Armstrong et al., 2015; Kaser and Racowsky, 2014). In summary, despite advances into new

areas and the further development of existing methods, there is still a clear need for novel

markers to help determine oocyte developmental potential and guide decision making during

assisted reproduction.

In the scope of ovarian and follicular physiology, AMH has been proposed to have

multiple important functions. In a clinical setting, the most commonly considered role of AMH is

its function as the “guardian” of the ovarian reserve. In brief, AMH is expressed from the

granulosa cells (GC) of preantral follicles and is recognized as being crucial for controlling

78

follicle recruitment towards growth and ovulation, as well as preventing premature ovarian

depletion. As a result, AMH levels are now commonly measured to give potential insight into

current and future ovarian status or fertility. Although less commonly considered in comparison,

the expression of AMH by developing follicles and the critical role it plays in follicular

recruitment and development suggests AMH levels may be reflective, and therefore also a

prospective biomarker, of follicle health and oocyte developmental potential. To date, this

concept of AMH as an oocyte quality biomarker has been mostly explored in human fertility

clinics by examining AMH levels in serum or in single or pooled ovulatory follicular fluid, and

comparing it to overall or specific oocyte and embryo development, pregnancy, and live birth

rates (Cupisti et al., 2007; Ebner, 2006; Eldar-Geva, 2005; Hazout et al., 2004; La Marca et al.,

2011; Lakamge, 2007; Majumder et al., 2010; Nelson et al., 2007; Penarrubia et al., 2005;

Silberstein, 2005; Takahashi et al., 2008; Tremellen et al., 2005; Wunder et al., 2008). Evidence

of a broader link or dual relationship between AMH at the levels of both individual fertility,

represented by oocyte quantity, and individual oocyte quality can also be seen in studies by

Sunkara et al. and Brodin et al.; after controlling for both age and oocyte yield in 892 patients

undergoing 1230 ART cycles, they observed that aspects of oocyte quantity and quality are

codependent, due to their positive correlation to serum (SE) AMH as a common parameter

(Brodin et al., 2013; Sunkara et al., 2011). As the authors explained, “If age and oocyte yield

would be the same, a patient with a high AMH level would have a greater likelihood of having a

euploid oocyte retrieved than would a woman with a low AMH level”.

Despite its promise, so far the use of AMH as a marker of oocyte developmental potential

has had mixed success. Looking at the designs of the past studies, they can generally be

considered to be incomplete because they usually do not sufficiently consider the large variation

79

in AMH levels between separate follicles or the need to directly link primary and outcome

measurements between each follicle and its oocyte. Although the specific compromises they

make, like pooled follicular fluid, simplify and therefore facilitate study completion, their

associated loss in study detail is likely hiding important links between AMH levels and oocyte

potential and contributing to the inconclusive or negative study results. For example, extreme

AMH values in the fluid of only a few follicles may be averaged out in a pooled follicular fluid

sample, and therefore would not be linked to an associated outcome in the matched oocyte

during analysis. In short, without individually measuring each follicle and individually tracking

each oocyte to allow pairing during analysis, it quickly becomes difficult or impossible to link

specific characteristics, such as AMH level, between a given follicle and its oocyte.

Only one study to our knowledge has focused on examining each follicle individually,

using monofollicular sampling (mono FF) and linking the observed status of the follicle to the

outcomes of its oocyte (Hamel et al., 2008). This study considered ovulatory stage follicles in

humans and tested the oocytes by a microarray assay. Although this study did not consider AMH

directly, its results did suggest ties between AMH and individual oocyte quality. One of the

factors differentially expressed between follicles that produced an oocyte that lead to pregnancy

vs. one that did not was aromatase, which has been linked to AMH (Hamel et al., 2008). Also in

this study, follicles selected for dominance were shown to be those that enter the luteinization

process first, by having more LH receptors (Hamel et al., 2008). Durlinger et al., Themmen et al.,

and Scheetz et al. presented evidence of opposing concentrations between LH receptors and

AMH, so it could be speculated that a decrease in AMH might be associated with follicular

dominance (Durlinger et al., 2001; Scheetz et al., 2012; Themmen, 2005).

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Given this background, the aim of the current study was to evaluate SE and mono FF

AMH levels, as well as mono FF AMH receptor 2 (AMHR2) RNA expression at the ovulatory

follicular stage, and to compare the ability of each corresponding oocyte to reach metaphase II

(MII) stage, the zygote to reach 2 pronucleus (2PN) stage, and embryo to reach blastocyst stage,

in patients of similar age and non-AMH related causes of infertility. It was hypothesized that

both SE, pooled average mono FF AMH, and pooled average mono FF AMHR2 RNA

expression would positively correlate to the AFC, oocyte number, and overall blastocyst rates. At

the mono FF level, it was also hypothesized both AMH level and AMHR2 receptor expression

would positively correlate with the oocyte’s and embryo’s ability to reach MII, 2PN, and

blastocyst stage respectively.

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METHODS

Patients and Experimental Design

Patients (n=6) from age of 27 to 36 admitted to ONE Fertility, Burlington for infertility

treatment by means of IVF. Causes of infertility were same sex couples, male factor, and

increased BMI. All patients from which the samples were collected signed a Participation in

Research consent form outlining the purpose of the study, procedures necessary to obtain

samples, potential risks and discomforts, potential benefits to participants and/or society,

payment for participation, confidentiality, participation and withdrawal, and rights of research

participants. The consent form (Appendix II) was approved by the University of Guelph

Research Ethics Board (REB) under number 13SE007. The title of the project was: “Molecular

Markers of Oocyte Health and Quality”. 16 patients signed the consent form, but patients number

ended up being 6 due to the following research based exclusion criteria: 1) negative for all of the

regular patient screening procedures; 2) screened for serum AMH; 3) not having any of the

following: PCOS, ovarian insufficiency/low reserve, testicular sperm retrieval (TESA) (partner),

a history of ovarian cancer. Logistics exclusion based criteria included: 1) at least 2

embryologists working; 2) use of the single lumen needle for aspiration; 3) not scheduled on the

weekend; 4) not be scheduled with more than 2 other IVF cases; 5) flushing, if necessary,

performed in a separate tube; 6) all the staff involved informed about modifications of the

procedure.

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Monofollicular Sample Collection and IVF

There was significant organization necessary to perform sample collection in order to

minimize time of the IVF procedure. One day before the collection, IVF lab staff had to prepare

media following “Monofollicular sample collection instructions” (Appendix III) in order to

perform the collection of the oocytes in a single follicle fashion, being able to trace each oocyte

to the follicle data, and without dilution of the follicular fluid with the flush media. “Protocol for

the monofolliclular oocyte collection” (Appendix IV) was used to help the staff go through the

preparation in a stepwise process. “Modified Cycle Sheet” (Appendix V) was used to record

coded details on the number of follicles, volume, number of oocytes, and details about each

sample and patient. IVF procedure, unless specified by the consent form, was performed in the

same fashion as established by the Ontario Network of Experts (ONE) Fertility protocols for the

IVF procedure. Simplified modifications allowing for collection of the research material

included: the gynecologist would have to aspirate each follicle separately instead of continuously

going from one to the other. That would allow the embryologist to obtain a single follicle

aspirate, search for the oocyte, and place the oocyte in the specifically prepared in vitro culture

system. Therefore, the next modification was that the culture system allowed only a single

oocyte, instead of multiple oocytes, to be placed per drop of culture media, in order to be able to

trace which oocyte belonged to each follicle. The next modification was that one of the

researchers would be present to obtain the monofollicular (mono FF) aspirate and place it in the -

20°C until all of the follicles were collected. After collection, aspirates would be spun in the

centrifuge, on 1.400rpm, volume would be recorded, and top layer, at least 100ul, of follicular

fluid would be removed and placed in the separate tube and frozen at -20°C for the AMH ELISA

measurements. Pallets were resuspended in 10% PBS and frozen in liquid N2 until transportation

83

to the University of Guelph. Blastocyst rate per patient was determined based on the total

number of blastocysts at day 5 divided by the total number of oocytes collected.

ELISA

AMH was measured in ONE Fertility, Burlington, using Automated Roche AMH assay

on the cobas e electrochemiluminescence immunoassay platform for AMH, using Beckman

Coulter Gen II assay antibodies (Roche Diagnostics International Ltd, Rotkreuz, Switzerland)

according to the manufacture’s instructions. 50ul of serum samples from each follicle were

measured undiluted, in replicates of two. Each plate was checked against provided controls. The

provided analytical range of the assay was 0.01-23ng/ml, with an analytical sensitivity of

0.01ng/ml. Repeatability and intermediate precision calculated on 14 serum samples ranged from

1.0 to 2.2% and 1.5 to 2.8% respectively.

Cell culture

Human Granulosa-Like Tumor Cell Line (KGN) were obtained from Queen’s University

and used as a positive control. It has been shown that AMH and AMHR2 are both expressed in

KGN cells (Anttonen et al., 2011). The cells were cultured in Dulbecco’s Modified Eagle

Medium (DMEM)/F12, 10% fetal bovine serum (FBS) with a doubling time ~46 hours (Y. Nishi

et al., 2000). They were frozen in FBS containing 10% DMSO at passage 4 and 5 and shipped to

the University of Guelph where they were thawed and cultured until passage 8, followed by

RNA extraction as described in Chapter 1.

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The same protocol was followed as described in Chapter 1 for KGN RNA extraction,

while mono FF cell pellets RNA extraction was done using AllPrepTM DNA/RNA Micro Kit

(QIAGEN, Inc., Burlington, ON) following the manufacture’s protocol. Reverse transcription for

both was performed using qScriptTM cDNA SuperMix (Quanta Biosciences, Canada) according

to the manufacturer’s instructions.

Real Time quantitative PCR

The same protocol was followed as described in Chapter 1, except for the use of primers

from Table 4. All RNA samples were normalized against GAPDH and PPIA. The amplification

program was as follows: 95°C for 10 minutes, followed by 50 amplification cycles of 95°C for

10 seconds, 60°C for 10 seconds (and not 65°C as in Chapter 1), 72°C for 10 seconds, and

acquisition of fluorescence for 10 seconds. Standard curves for all primers were generated using

pooled pellet cDNA samples from a unrelated patient with a signed consent form in six serial

dilutions ranging from 12.5 to 0.781ng/ul, The calibrator sample used to avoid inter plate

variation was KGN cDNA.

85


Gene GenBank

accession

number

Sequence Reference Size

(bp)

hAMH NM_000479.3 F-5’- CGCCTGGTGGTCCTACAC-3’

R-5’-AAGGTGGTCAAGTCACTCAG-3’

(Anttonen et al.,

2011; Catteau-

Jonard et al.,

2008)

60

hGAPDH NM_001256799.2 F-5’- GAAGGTGAAGGTCGGAGTC -3’

R-5’- GAAGATGGTGATGGGATTTC-3’

(Le et al., 2008;

Yoshimura et al.,

2003)

226

PPIA NM_178320.2 F-5’- TCTTGTCCATGGCAAATGCTG -3’

R-5’- TTTCACCTTGCCAAAGTACCAC -

3’

(Ferris et al.,

2016)

111

hAMHR2 NM_001164690.1 F-5’-TGTGTTTCTCCCAGGTAATCCG-3’

R-5’-AATGTGGTCGTGCTGTAGGC-3’

(Anttonen et al.,

2011; Catteau-

Jonard et al.,

2008)

164

86

RESULTS

AMH per patient:

Average FF AMH per patient was positively correlated to SE AMH levels (n=6; ρ=0.94,

p=0.017; Figure 8Ai). There was also a positive trend between SE AMH and relative AMHR2

RNA expression (ρ=0.60, p=0.242; Figure 8Aii), oocyte number (ρ=0.35, p=0.492) and AFC

(ρ=0.09, p=0.870; Figure 8Aiii). Average SE AMH, FF AMH, and relative AMHR2 RNA

expression were all negatively correlated with the rate of blastocyst development (ρ=-0.90,

p=0.015; Figure 8Bi; ρ=-0.84, p=0.036 Figure 8Bii and, ρ=-0.84, p=0.036; Figure 8Biii

respectively) for individual patients. In all six patients transfer of embryos resulted in clinical

pregnancy.

AMH per individual follicles:

Individually collected and grouped for all patients FF AMH was not found different

between M2 oocytes and non M2 oocytes (n=41 vs. n=28, p=0.350), 2PN zygotes and non 2PN

zygotes (n=30 vs. n=11, p=0.940) and blastocyst and non blastocyst group (n=17 vs. n=13,

p=0.563). The average FF AMH for M2 was 34.08±6.66pmol/l vs. non M2 was

35.77±9.99pmol/l. The average FF AMH for 2PN was 36.13±8.29pmol/l vs. non 2PN was

28.50±10.67pmol/l. The average FF for blastocyst was 30.49±11.10pmol/l vs. non blastocyst

was 27.87±7.64pmol/l. When the data was divided based on SE AMH level into two groups,

“normal” group being 1.93 to 2.62ng/ml and “high” group being 4.21 to 6.79ng/ml, each with

n=3, SE AMH level and FF AMH level were found significantly lower in the first group vs. the

second group (p=0.048, p=0.038, respectively). The blastocyst rate was found significantly

higher in the first group vs. the second group (p=0.038) Figure 9. Average relative GC AMHR2

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RNA expression and oocyte number were not found significantly different between the groups

(p=0.700, p=0.369) respectively. The average value of the SE AMH was 16.83±1.52pmol/l for

the “normal” group 38.4±5.39pmol/l and for “high” group. The average value for the FF AMH

was 10.89±2.62 pmol/l for the “normal” group, and 64.80±11.68pmol/l for the “high” group. The

average relative GC AMHR2 RNA expression for the “normal” group was 0.18±0.04 and for the

“high” group was 0.20±0.03. The oocyte number for the “normal” group was 8.67±0.88 and for

the “high” group was 11.34±1.86. The average blastocyst rate was 0.39±0.05 for the “normal”

group, and 0.25±0.07 for the “high” group. If data between blastocyst and non blastocyst

producing FF AMH (pmol/l) (n=6), FF AMH/SE AMH (n=6) and relative AMHR2 RNA

expression (n=4) was examined per patient in “high” (i) and “normal” (ii) SE AMH groups, in

“high” patients follicles with higher values produced blastocyst while in “normal” patients

follicles with lower values produced blastocyst, Figure 10.

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Figure 8 Anti-Mullerian hormone (AMH) per patient based approach. Correlations between AMH level, its relative receptor transcript amount and embryo development potential in six patients. Ai) Serum AMH (SE AMH) (pmol/l) vs. Average follicular fluid (FF) AMH (pmol/l) (p=0.017). Aii) SE AMH concentration (pmol/l) vs. Average relative GC AMHR2 RNA expression. Aiii) SE AMH (pmol/l) vs. Antral follicle count (AFC); Bi) SE AMH concentration (pmol/l) vs. Blastocyst rate (blast rate) (p=0.015). Bii) Average relative GC AMHR2 RNA expression vs. blast rate p=0.036. Biii) Average FF AMH concentration (pmol/l) vs. blast rate p=0.036.

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Figure 9 Comparisons between individual follicles serum (SE) AMH (pmol/l), average follicular fluid (FF) AMH (pmol/l), relative GC AMHR2 RNA expression, oocyte number and blastocyst (blast) rate between patients (n=3; blue) with “normal” 1.93-2.62 ng/ml and patients (n=3; red) with “high” between 4.21-6.79 ng/ml (x 7.14 to be converted to pmol/l). Significant difference was observed between “normal” and “high” groups for SE AMH, FF AMH and blast rate (p=0.048, p=0.038, and p=0.038, respectively). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression level. Error bars denote the standard error of the mean (SEM) and significant difference (P<0.05) is indicated by the symbol (*).

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Figure 10 Comparisons between average of individual follicles that gave rise to blastocyst (red/blue) and non blastocyst (green) for each patient being from either “high” (i) or “normal” (ii) SE AMH groups, 4.21-6.79 ng/ml or 1.93-2.62 ng/ml respectively. Ai) Average Mono follicular fluid (FF) AMH (pmol/l) in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Aii) Average Mono FF AMH (pmol/l) in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Bi) Average FF AMH/SE in “high” patient group from blast vs. non blast follicles respectively, patient 1 (n=1, n=2), patient 2 (n=2, n=3), patient 3 (n=5, n=2); Bii) Average FF AMH/SE in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=4), patient 5 (n=3, n=2), patient 6 (n=2, n=2). Ci) Average relative GC AMHR2 RNA expression in “high” patient group from blast vs. non blast follicles respectively, patient 2 (n=1, n=1), patient 3 (n=3, n=1); Cii) Average relative GC AMHR2 RNA expression in “normal” patient group from blast vs. non blast follicles respectively, patient 4 (n=3, n=1), patient 5 (n=4, n=2). Glyceraldehyde 3-phosphate dehydrogenase and Peptidylprolyl isomerase A were used as housekeeping genes to determine relative expression level, and error bars denote the standard error of the mean (SEM).

91

DISCUSSION

The aim of the current study was to investigate and compare potential relationships

between both systemic, and mono FF AMH protein level, as well as mono FF GC AMHR2 RNA

expression and the following human reproductive parameters: antral follicle count, oocyte

number, oocyte maturity, zygote and blastocyst rate. The broader goal was to assess the utility of

AMH as a marker of oocyte developmental potential in assisted reproduction. To date, only one

preliminary study published by Hamel et al., used a similar mono FF sampling and analysis

method. Although it did not consider AMH levels, it used a microarray approach, and was

successful in identifying a number of differentially expressed factors in relation to pregnancy

outcome, some of which are known to be part of AMH regulatory function (Hamel et al., 2008).

The current study provides evidence in support of a significant positive correlation

between SE AMH and average mono FF AMH, and a positive trend between SE AMH and

average mono FF GC AMHR2 RNA expression when examined on a per patient basis. This

finding is in agreement with previous studies showing a correlation between average FF and SE

AMH (Fanchin et al., 2007), including our own previous bovine study, which showed average

FF AMH and GC AMHR2 RNA expression to have a significantly positively correlation to SE

AMH (Stojsin- Carter et al., 2016). A positive correlation was not observed between AMH and

AFC or AMH and oocyte number, however this may also be due to the low patient numbers

available for the current study.

Examined on a per patient bases, we found a significant negative correlation between SE

AMH, average FF AMH, average relative GC AMHR2 RNA expression and blastocyst rate. This

finding is contrary to the three previous reports reporting a positive correlation between AMH

and embryo developmental potential (Fanchin et al., 2007; Majumder et al., 2010; Takahashi et

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al., 2008). However, looking closer, all of these previous studies only measured and considered

the AMH level of single largest ovulatory follicle and did not examine all subsequent follicles

per patient. In contrast, the negative correlation observed in the current study includes these

additional values in the analysis and therefore reaches a separate conclusion. In general, the

interpretation of studies relying on single largest follicle values are problematic due to the strong

impact between absolute follicle size and AMH levels, and the fact that the characteristic of

largest follicle is not standardized across all patients, but rather may vary significantly from one

patient to the next. Additionally, there is evidence the largest or dominant follicle is unique

compared to the other follicles with respect to multiple factors related to development, such as

AMH (Scheetz et al., 2012). Considering this trend, where a developing follicle becomes

depleted in factors involved in dormancy, a negative relationship between localized or follicle

specific AMH and blastocyst rate becomes justified.

In order to further explore the observed negative relationship between AMH and embryo

developmental outcome, patients were divided into two groups based on their SE AMH levels.

These levels were drawn from previous literature that defined the normal human SE AMH range

as being 1.66-4.52ng/ml which is the 25th to 75th percentile of the population (Ebner, 2006).

Additionally, we considered reports describing levels of 2.52 and 2.7 to be correlated with a

positive developmental outcome, and that 1.96ng/ml represents a lower limit associated with

negative developmental outcomes (Eldar-Geva, 2005; La Marca et al., 2011; Lakamge, 2007;

Silberstein, 2005). In this context, the SE AMH level of or two patient groups were 1.93-

2.62ng/ml for the first group, which we considered to fall into the normal AMH range, and 4.21-

6.79ng/ml for the second group, which we considered to represent a higher than normal AMH

range. In addition to the statistically significant difference in both SE and average FF AMH

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levels, the blastocyst rate was also significantly different with higher levels in the “normal”

group compared to the “high” group. These finding provides evidence, to our knowledge for the

first time, of a potential association between negative blastocyst outcomes in patients with higher

AMH levels, excluding those linked to an identified and specific ovarian pathology such PCOS

(Pigny, 2005). While the specific definition of the “high” SE AMH range used in this analysis

has not been explicitly defined previously in the literature, it falls above 75% of the normal range

(>4.52ng/ml) and bellow the values associated with ovarian dysfunction or defined pathologies

(<8.40ng/ml) (Pigny, 2005). Based on our observations, the possibility of a threshold beyond

which increasing levels of systemic and follicular AMH are no longer associated with a good

IVF prognosis should be considered, even in the absence of an identified ovarian pathology. A

potential mechanism associates increased levels of AMH to decreased oocyte quality and poor

reproductive outcomes due to the lack of follicular selection and maturation. This is a novel

concept and requires further verification.

Looking further using the greater detail provided by the use of a mono FF approach,

reveals an additional relationship. Oocytes showing increased developmental potential in “high”

SE AMH patients were associated with higher AMH and GC AMHR2 RNA expression, while

the opposite relationship was observed in the “normal” SE AMH group with oocytes showing

increased developmental potential were associated with lower AMH and GC AMHR2 RNA

expression (Figure 11). If it is assumed local AMH levels need to drop to a critical point to

allow for the follicle to be recruited and matured properly allowing for increased stereogenic

synthesis and gonadotropin receptor expression as seen in normal SE AMH patient on the local

level (Visser, 2003), it is unclear how can this opposing trend be explained in the high SE AMH

patients. It might be speculated that alterations in the local AMH level in the high SE AMH

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group remaining high at the ovulatory level could be a reason why the overall blastocyst rate in

the high SE AMH patients is lower compared to the normal SE AMH patients. However,

understanding how few of these follicles still progress and mature producing a blastocyst is

unclear, the current result clearly demonstrates the utility and importance of using paired mono

FF and serum measurements when investigating follicular level AMH biology.

In summary, the findings of the current study provide strong evidence that AMH biology

is not as simple as one measurement or interpretation. Specifically, this study identified two

groups of individuals on the basis of different SE AMH levels that had apparently contrasting

physiology and observed further differences and alternative trends within these groups when

considering AMH measurements of individual follicles and oocytes. These observations suggest

potential relationships between AMH values and reproductive outcomes and parameters should

be investigated at the organism, ovary and individual follicle level. As a general recommendation,

systemic AMH should be considered to provide an overall indication of ovarian function and

context for the interpretation of local AMH values, while the local AMH levels should be

considered reflective of their specific follicular environment and the associated oocyte.

Additionally, although it may be possible to find associations between the AMH level of the

largest follicle and outcomes within a given study or a defined clinical setting extrapolation of

these findings is not recommended. Instead, there should be more investigations exploring the

follicular AMH effects and outcomes such as the current experiment method, but including

larger number of patients, where individual follicles and their oocytes are measured and can be

compared directly to rule out potential confounding variables, such as absolute follicle size.

Further research and implementation of these concepts has the potential to increase the utility

95

AMH in a clinical setting by allowing it to not only serve as an established marker of general

fertility, but also a novel potential marker for in vitro embryo selection.

Figure 11 Ovaries from high and normal SE AMH patient groups with oocytes that developed to blastocysts corresponding to high FF AMH in red or low FF AMH in blue respectively, compared to oocytes that did not develop to blastocysts corresponding to FF AMH in green for both patient groups.

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GENERAL DISCUSSION

The main objective of this thesis was to examine the correlation between systemic and

ovarian AMH levels and various parameters of fertility in the bovine and human species, as well

as a possible association between the cow’s systemic AMH levels and fetal sex during pregnancy.

AMH was proposed to be a marker of ovarian function in both non-pregnant bovine and human,

as well as in a pregnant bovine model.

Rising levels of infertility have a large impact on the bovine industry and human

reproduction. However, our understanding of ovarian function and biology, which should be

thorough in order to overcome this issue, is still vastly lacking. AMH has been used as a marker

of quantitative ovarian parameters such as AFC and oocyte number in humans and European

cattle. In the Zebu cattle breeds, which occupies a majority of the tropical and subtropical areas

of the planet, and therefore also has great economic importance, AMH has not been extensively

studied. The ability to identify fetal sex in early pregnancy based on the differentially expressed

fetal sex factors and/or their effects on the mother and her ovary is unknown. Only three human

studies have looked at AMH during pregnancy, and only one of those has studied higher levels

of AMH in mothers carrying a male vs. female fetus. The link between AMH and quantitative

fertility parameters has been established in both species, but only a few human IVF studies and

no bovine ones have made the link between AMH and qualitative fertility parameters, such as

successful fertilization and pregnancy rate. In this thesis, it was hypothesized that 1) Zebu cattle

would have higher systemic and ovarian AMH levels compared to European cattle, and in both

breeds AMH levels would be correlated to fertility parameters; that 2) cows carrying a male fetus

would have higher Pl AMH compared to cows carrying a female fetus; and that, 3) in women

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undergoing IVF, systemic and ovarian AMH would positively correlate with the oocyte

developmental potential outcome.

Species or breed adaptation to various environmental conditions arises though the

combination of genetic differences and evolutionary or breeding pressures. Here we provide

evidence that two cattle breeds with differing reproductive abilities also have underlying

physiological difference in terms of levels of AMH in serum, and follicular fluid. These

observations possibly represent specific adaptations to their environments, as Zebu and European

cattle have been bred for generations to adapt to a more tropical/subtropical vs. a more temperate

climate respectively. Zebu has adapted to using its energy primarily to overcome heat, humidity,

disease, and scarce nutrient availability. In comparison, European cattle have been grown in

optimal surroundings, without heat and nutrient stressors, but with added stress caused by

artificially induced human inbreeding methods for increasing milk and meat yield (Leroy et al.,

2008). These differing environments and pressures may also have resulted in the characteristics

of their reproduction to also differ. In Zebu, reproduction is more “inaccessible”, characterized

by delayed puberty, shorter and more “quiet” estrous, longer gestation, and lengthier postpartum

anestrous, but higher ovarian reserve and AMH. European cattle exhibit more “accessible”

reproduction, characterized by shorter puberty, easier estrous detection and monitoring, shorter

gestation and postpartum anestrous, but lower ovarian reserve and AMH (Butler, 2003;

Koufariotis et al., 2014; O'Brien et al., 2014). Findings from our experiments have came to the

similar conclusion where Zebu has been found to have superior fertility parameters, such as AFC

and oocyte number, that correlated to their systemic and follicular AMH compared to the

European cattle (Stojsin- Carter et al., 2016). Interestingly, Silva-Santos et al. has shown similar

fetal ovarian reserves between the two breeds in terms of primordial follicles, with higher rates

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of follicular depletion in European cows, which leads to lower reserve in the adult females

compared to Zebu (Silva-Santos et al., 2011). It could be speculated that the slower rate of

follicular depletion and higher AMH levels in Zebu are a consequence of seasonal pressure on

ovarian function. In a broader context, the associated fertility, milk production and genetic

characteristics of European versus Zebu cattle can also be interpreted as a potential cautionary

example of a failure to consider the links and potential trade-offs between traits during long-term

and high pressure animal selection and breeding. Specifically, an overly strong selective focus on

milk production has been implicated as a major source of the growing infertility problems

observed in European cattle. Recognizing the Zebu breed is currently less inbred and does not

yet appear to suffer from infertility traits, Zebu breeders and husbandry programs may wish to

try to avoid a similar limitation and take a more holistic or multi-trait approach during animal

selection. If this action is taken now before the species is further bred out and genetic variability

lost it may preserve the genetics necessary to achieve a more optimal balance between fertility

and production outcomes.

Besides exploring ovarian state of non-pregnant cows and how it relates to their systemic

and follicular AMH levels, this thesis also explored plasma AMH of pregnant cows and how it

relates to their fetal sex and their fetal plasma AMH levels (Chapter 2). Building on what has

already been discussed, additional details related to male fetal AMH expression, maternal ovary

status and potential AMH production, AMH crossing the placental barrier and the potential

effects of increased AMH levels in developing fetuses on the maternal organism were also

considered. The male fetal Pl AMH, not previously published to our knowledge, was in our study

found to be 1000x higher than female fetal Pl AMH levels, and 100x higher than the Pl AMH

levels of pregnant cows. Previous bovine studies showed afterbirth AMH levels up to a hundred

99

times higher in the of male vs. female calves (Kitahara et al., 2012b; 2012a; Rota et al., 2002).

Matzuk et al. and Teixeira et al. also described a higher AMH expression in the human male

fetus at around 8 weeks of pregnancy relating it to its role in development of the male

reproductive system (Matzuk and Lamb, 2002; Teixeira et al., 2001).

Evidence of a maternal ovarian AMH contribution as a response to the pregnancy seems

unlikely based on the following literature findings. The ovary is known to enter a partly

quiescent state during pregnancy in terms of folliculogenesis, due to the lack of gonadotropin

signals from the pituitary gland, which is inhibited by: progesterone, estradiol, and relaxin,

secreted from the corpus luteum; and by hCG, relaxin, prolactin, and progesterone, secreted from

the placenta. Some follicular growth and recruitment still occurs, but follicles do not reach an

ovulatory size and number, and have an increased amount of atresia (Guilbault et al., 1986;

Pierson and Ginther, 1986; Westergaard, 1985). Govan et al. described stunted follicular

development during pregnancy, where follicles would reach a preantral stage, with a size of up to

6mm, and not progress further (Govan, 1968). They proposed that the action of progesterone,

indirectly through inhibition of gonadotropin, is responsible for the inability of follicles to

continue further development. Driancourt et al. presented evidence of follicular cycling during

the first 7 months of pregnancy, but none of the follicles reached an ovulatory state (Driancourt,

2001). Ovarian production of progesterone is crucial in the first two months of gestation. It has

been shown that oophorectomy after 9th week of gestation does not have an effect on pregnancy,

while any disturbance prior to 9th week leads to pregnancy loss (Villaseca, 2004). Also, the urine

of pregnant women was shown to able induce luteinization in the ovaries of hypophysectomized

rats (Leonard and Smith, 1934). Overall, the ovary might be important due to progesterone

100

synthesis, however dormant in terms of folliculogenesis, and therefore an unlikely contributor of

maternal systemic AMH during pregnancy.

Considering the possible contribution of fetal AMH to maternal Pl AMH levels, one has

to explore the potential ability of fetal AMH to cross the placenta and enter the maternal

circulation. There are four anatomical barriers between maternal and fetal circulation:

syncytiotrophoblast, trophoblastic and capillary basement membranes, and fetal capillary

endothelium. It is known that CO2 and steroid compounds move by passive diffusion in the

direction of the equilibration of the concentration gradient. Larger charged molecules, such as

peptide hormones, move across the placenta by means of: active transport by either specialized

receptor molecules within microvesicles (receptor mediated endocytosis) (Pereira et al., 2013;

Sandvig and Llorente, 2012), or by pinocytosis of syncitiothrophoblast cells (Palmeira et al.,

2012); and passive transport at a very slow rate (Malek et al., 1998). Examples of maternal to

fetal active transfer via receptor molecules on the membrane are IgGs, 160kDa in size, which

ensure that her passive immunity is transferred to the fetus towards the end of pregnancy.

Another protein, transferrin, 80kDa in size, is transferred by means of pinocytosis, which ensures

proper supply of oxygen to the fetus. Examples of fetal to maternal active transfer via

microvesicles in a cloned cattle model are transgenic enhanced Green Fluorescent Protein

(eGFP), 32kDa in size, and fetal DNA (Pereira et al., 2013), with an upper limit for a

microvesicle transfer defined as 150kDa (Sandvig and Llorente, 2012). Alpha fetal protein (AFP),

70kDa in size, is an example of a protein transferred by means of diffusion from the fetus to the

mother. AFP is found at a 100x smaller concentration in the mother compared to the fetus, the

levels correlating to placental size and week of pregnancy, starting from the end of the first

trimester (Malek et al., 1998). It is speculated that this passive diffusion occurs not directly

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through the membranes but through placental “leaks” or defects, as occurs with the fetal cells

found in the maternal circulation (Malek et al., 1998). It is was found that AFP passes through

“the villous core ross the fibrinoid deposits at sites of discontinuity of the syncytiotrophoblast or

from decidua basalis by entering the vessels that traverse the basal plate” without passing

through the cytoplasm (Brownbill et al., 1995). The author argued that, in normal pregnancies,

even with the much higher concentration of AFP in fetal blood, it is difficult to detect evidence

of AFP transfer to the mother due to dilution of AFP in the much higher volume of maternal

blood. This is probably similar to what we observed with AMH. AFP and its receptor have been

shown to be expressed by the placenta (Duc-Goiran et al., 2006), similar to AMH. Therefore,

based on the examples of IgG, eGFP and AFP it could be speculated that AMH could pass

through the placenta from the fetus to the mother, utilizing both passive and active transport.

Further studies are necessary to confirm these speculations.

The potential effects of increased AMH levels during pregnancy, such as those possibly

produced and transferred from the male fetus, may possibly manifest in differences in

developmental between male vs. female brains and associated behaviors, the Free-Martin effect

being one such example, the response of pregnant mothers to chronic illness, and in oncogenesis.

The effect of the absence of AMH on brain and motor development can be seen in the KO mice

studies. AMHR2 is shown to be expressed differently in the brains of male and female mice,

leading to higher levels of motor neuron development and increased novelty preference in the

male mice (Morgan et al., 2011; Wang et al., 2009; Wittmann and McLennan, 2011). Increased

levels of AMH in bovine twin pregnancies with fetuses of opposite sex led to increased levels of

aggression and masculinization of the reproductive tract in the female twin, called a Free-Martin,

due to high levels of male AMH from the male twin (Barker, 1944). It has been shown that

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mothers carrying a male fetus differ by have a higher risk of needing acute care and medication

if diagnosed with chronic asthma, have decreased blood pressure, and have increased insulin

resistance (Firoozi et al., 2009; Hocher et al., 2009; Walsh et al., 2015). The effect of excess

AMH has been explored in experiments by Stephen et al., where the addition of 10g of

recombinant AMH per day for 3 weeks caused an inhibition of human cancer cell lines in vivo,

and decreased neovascularization, necrosis, inflammation and tumor size (Stephen et al., 2002).

Nishi et al. showed that AMH expression varied depending on the tumor size, while AMHR2 is

unaffected. They also showed that, with increasing levels of exogenous AMH, there was a tumor

cell number decrease, by means of apoptosis, in vivo and in vitro (Y. Nishi et al., 2000). It can

also be speculated that women who carry a male fetus might have delayed subsequent ovulation,

could exhibit more masculine behaviors, and could have a decreased risk of oncogenesis due to

the additive AMH effect.

In this thesis the monofollicular collection (mono FF) method was used to closely

examine and investigate links between AMH and reproductive outcomes in an IVF patient

population. Importantly, this detailed approach allowed for the novel identification of a number

of potential unexpected trends in subsets of individuals or follicles that appear to display

opposing relationships between AMH levels and outcomes. These results show that only

understanding both systemic and follicular levels of AMH, is possible to correctly predict the

capacity of the entire ovary, as well as the potential of the individual follicle. The ovarian

capacity as a whole, and the follicle as a localized environment both have an effect on the

developing oocyte. Fertility, in general, is a property of codependent quantitative and qualitative

parameters, with the ultimate goal of having both a large and healthy oocyte reserve (Brodin et

al., 2013; Holte et al., 2011; Kawamura et al., 2013; Sunkara et al., 2011). This thesis begins to

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look beyond AMH as either a qualitative or quantitative marker alone and on towards a scenario

where it can be seen to represents both these parameters together. In a general sense, Chapter 1

represents and demonstrates clear evidence AMH is a marker of quantity, and Chapter 3

represents and demonstrates clear evidence AMH is a marker of quality. Perhaps the most

obvious way to begin to tie these two characteristics together is through the “size matters”

concept, where the organ’s size and the quantity of cells positively correlates to its function,

Figure 12. For example, smaller ovarian reserve could directly imply lowered oocyte quality

within the reserve, and vice versa, irrespective of the age. This relationship can also be seen and

has been assessed in other organs such as testes, where size was found to be proportional to the

amount of Sertoli cells, which further correlated to male fertility (Keeton et al., 1996; Velde and

Pearson, 2002). Unlike testes, mammaries and their size were not correlated to the ability of the

secretory cells to produce milk (Ramsay et al., 2005).

On the tissue level, this relationship of quantity and quality codependence is

demonstrated by the complex interplay between cellular interactions. How structure or size can

affect the function or the quality can be seen in the ovarian morphology and factors that disrupt

this equilibrium within the tissue. The ovary has a firm cortex on the outer layer, where the

follicles enclosing the oocytes reside, and a softer medulla in the inner layer. As they mature,

follicles move from the outer firm layers of the ovary towards the inner softer layers. This “out to

in” direction of follicular growth is a fairly novel concept, and provides the link to the

codependence between the physical characteristics of the ovarian reserve and its functional

property, which is to produce a healthy oocyte (Woodruff and Shea, 2010). The physical

interactions between the supporting cells in the follicle (granulosa) with the oocytes, which are

facilitated through the gap and adherent junctions between the cells, ensure follicular arrest and

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dormancy in the outer layer, or detachment, growth, and proper maturation in the inner layers of

the ovary (Gilchrist et al., 2008; Li and Albertini, 2013). Detachment of these two cell types is

dependent on the decreased amount of cAMP, Ca2+, and AMH, allowing for the increased

expression of gonadotropin receptors, and stereogenesis (Norris et al., 2009; Tsafriri et al., 1996;

Webb et al., 2002). Also, during the follicular recruitment process, physical changes are

evidenced by perturbation in the extracellular matrix and cytoskeleton of the oocyte and

granulosa cells (Berkholtz et al., 2006; Hsueh et al., 2015). Another proof of the codependence

between structure and function are ovarian pathologies and their treatment methods, with AMH

being an indicator of both, as presented in all chapters. One treatment method is ovarian drilling,

where an ovarian injury is deliberately induced, leading to increased ovarian function due to the

disturbance in the ovarian structure (Ortega-Hrepich et al., 2014). A small inaccessible reserve of

follicles unresponsive to gonadotropins is thus reawakened by the structural disturbance. Women

who specifically benefit from this method are those with diminished ovarian reserve (DOR), or

polycystic ovarian syndrome (PCOS) patients both known to have lowered and increased

systemic AMH respectively (La Marca et al., 2009). Second method where ovarian structural

integrity is disturbed is ovarian fragmentation, coupled with oocyte maturation in vitro, or with

crypreservation of the ovarian pieces and in vivo oocyte maturation (Dunlop et al., 2016;

Kawamura et al., 2013; Varghese et al., 2008; Xiao et al., 2015). Patients benefiting are those

with premature ovarian failure (POF), due to cancer diagnosis, who need their gametes preserved

prior to cytotoxic therapy. In both of these methods, the birth of healthy children was achieved

by the disturbance of ovarian structure, leading to a decrease in the paracrine signals that inhibit

follicular recruitment (Donnez et al., 2011; Hsueh et al., 2015). It could be speculated that

ovarian injury may be associated with the lowering of local AMH, and that both may increase

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the ovarian ability to reacquire its “stemness” or capacity to regenerate ovarian reserve,

supported by Hu et al. (Hu et al., 2014). This concept challenges the dogma that a fixed germ cell

population is determined in utero for the female lifetime (J. Johnson et al., 2005; 2004). A

balance between renewal capacity and dormancy of follicles throughout the reproductive years is

crucial for proper species reproduction and propagation of its genetic material.

The broader importance of these findings lies in strengthening of evidence that AMH

represents consistent, reliable, and inexpensive ovarian function marker during non-pregnant and

pregnant state. In this way, it can provide key insights into fertility potential and be used to

improve ovarian stimulation protocols, breeding program efficiency, determination of fetal sex,

and ovarian pathologies. In specific relation to human ART, development of AMH as a marker

will continue to facilitate individualized ovarian reserve estimates and optimized stimulation

protocols and treatments that increase the safety of patients.

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Figure 12 “Size matters concept” representation of the ovary in which the ovarian size is positively correlated to: the ovarian reserve, the ovarian function (based on the oocyte developmental potential), and the systemic AMH level. However it is negatively correlated to the ovulatory follicular AMH level.

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SUMMARY, CONCLUSIONS, AND FUTURE DIRECTIONS

AMH measured from serum/plasma, from pooled or averaged follicular fluid, or as its

receptor RNA transcript from granulosa cells were correlated to the number of antral follicles,

number of oocytes and blastocyst rate. Zebu cattle were found to have a higher level of plasma

and follicular AMH. Crossbred animals were found to more closely mirror Zebu cattle in their

fertility parameters. Differences in AMH, if measured in the serum of pregnant cows between

day 35 and 135 of gestation, were found to reflect the sex of the fetus, with cows carrying a male

fetus having higher AMH level difference compared to cows carrying a female fetus. AMHR2

RNA expression measured in the placenta and cotyledon in pregnancies with male and female

fetuses was not found to be different. AMH levels measured from human serum, averaged

follicular fluid, and AMHR2 transcript levels from averaged pooled granulosa cells showed a

negative correlation to blastocyst rate. If patients were divided into two groups based on their

serum AMH, the group with normal levels was found to have a significantly higher blastocyst

rate compared to the group with a higher serum AMH. When measured in single follicles in high

and normal serum AMH patients, blastocysts developed from follicles with higher AMH levels

in high serum AMH patients, and from follicles with lower AMH levels in normal serum AMH

patients, compared to the AMH levels in follicles of arrested embryos. Therefore, high systemic

and low ovulatory follicular AMH might indicate high ovarian reserve, AFC, and oocyte

numbers, and a good prognosis in infertility treatment; however, if it leaves the realm of

biologically optimal values it might become a marker of a poor prognosis, or lose its value as a

marker.

From the current studies, we can say that AMH is a valid indicator of ovarian structure

and function, being a marker of oocyte number and AFC in cattle, and being a marker of

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blastocyst rate in humans. We can also say that through measured from serum/plasma, follicular

fluid or granulosa cell transcript levels, it can also represent ovarian activity. These correlations

and relationships can be highly dependent on: species, human or bovine; stage of follicles, antral

or ovulatory; the way follicles are collected, by pooling the follicular fluid or by measuring each

follicle separately and then averaging the value for all; ovarian status; current serum or plasma

and these factors should be considered in investigations and data interpretation. During

pregnancy AMH levels appear to be impacted by the fetal sex in the bovine species and therefore

have a potential use in early sex detection.

Future studies should continue to build on the present results to further increase our

understanding of AMH biology and the potential power and utility of AMH as a marker of

ovarian function. Improved characterization of AMH use within assisted reproduction assays

could be accomplished by including larger number of patients in studies and further exploring

the relationship between AMH and oocyte developmental potential, and other factors involved in

AMH signaling and their transcripts. Also the specific inclusion of patients with different

diagnoses of infertility should be included in future studies to explore changes in AMH biology

or prognostic value in these conditions. In cattle studies, AMH levels should be further explored

at additional time points throughout pregnancy, on a larger sample number, and whenever

possible include corresponding fetus plasma AMH values. Also, specific experiments exploring

the potential transport of AMH across the placenta are important in explaining the relationship

between fetal and maternal AMH levels during pregnancy. Similarly, the possible effects of

increased AMH on mothers carrying a male fetus should be directly investigated. In bovine

experiments, it would be beneficial when possible to control for genetic variability of an oocyte

donor and embryo recipient, in order to more accurately follow up on the pregnancy outcomes of

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all the oocytes from each animal. Last but not least, our understanding of the specific

mechanisms behind AMH’s ability to arrest follicular selection and maturation remains

incomplete and achieving a greater understanding of these pathways would certainly be useful in

understanding infertility and its treatment.

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APPENDIX

Appendix I: Data from Chapter II, study group 1

Plasma AMH (Pl AMH) values (pg/ml), y-axis, measured using Ansh ELISA kit in cows Bos taurus indicus during gestation at 4 time points, x-axis, day of artificial insemination (day 0), day 35, day 135, day 275 and approximately one month after calving (last point). Red lines represent samples taken from animals carrying female calf (n=3) while blue lines represent animals carrying male calf (n=5), verified by ultrasound and confirmed at birth. A) Raw data of Pl AMH in pregnant cows. B) Change in Pl AMH (Δ) between time points. C) Relative change in Pl AMH in terms of its previous value, example: Δ Pl AMH (day x - day y) / Pl AMH (day y).

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Appendix II: The consent form

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Appendix III: Monofollicular sample collection instructions

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Appendix IV: Protocol for the monofollicular oocyte collection

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Appendix V: Modified Cycle Sheet

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