New Technologies and Perinatal Medicine: Prediction and Prevention of Pregnancy Complications 1138706140, 9781138706149

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New Technologies and Perinatal Medicine Prediction and Prevention of Pregnancy Complications

Series in Maternal-Fetal Medicine About the Series Published in association with the Journal of Maternal Fetal and Neonatal Medicine, the series in Maternal Fetal Medicine keeps readers up to date with the latest clinical therapies to improve the health of pregnant patients and ensure a successful birth. Each volume in the series is prepared separately and typically focuses on a topical theme. Volumes are published on an occasional basis, depending on the emergence of new developments. Textbook of Diabetes and Pregnancy, Third Edition Moshe Hod, Lois G. Jovanovic, Gian Carlo Di Renzo, Alberto De Leiva, Oded Langer Cesarean Delivery: A Comprehensive Illustrated Practical Guide Gian Carlo Di Renzo, Antonio Malvasi Obstetric Evidence Based Guidelines, Third Edition Vincenzo Berghella Maternal-Fetal Evidence Based Guidelines, Third Edition Vincenzo Berghella Maternal-Fetal and Obstetric Evidence Based Guidelines, Two Volume Set, Third Edition Vincenzo Berghella The Long-Term Impact of Medical Complications in Pregnancy: A Window into Maternal and Fetal Future Health Eyal Sheiner Operative Obstetrics, 4E Joseph J. Apuzzio, Anthony M. Vintzileos, Vincenzo Berghella, Jesus R. Alvarez-Perez Placenta Accreta Syndrome Robert M. Silver Neurology and Pregnancy: Clinical Management Michael S. Marsh, Lina Nashef, Peter Brex Fetal Cardiology: Embryology, Genetics, Physiology, Echocardiographic Evaluation, Diagnosis, and Perinatal Management of Cardiac Diseases, Third Edition Simcha Yagel, Norman H. Silverman, Ulrich Gembruch New Technologies and Perinatal Medicine: Prediction and Prevention of Pregnancy Complications Moshe Hod, Vincenzo Berghella, Mary E. D’Alton, Gian Carlo Di Renzo, Eduard Gratacós, Vassilios Fanos For more information about this series please visit: https://www.crcpress.com/Series-in-Maternal-Fetal-Medicine/ book-series/CRCSERMATFET

New Technologies and Perinatal Medicine Prediction and Prevention of Pregnancy Complications Edited by

Moshe Hod md Director, Mor Comprehensive Women’s Health Care Center Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel Vincenzo Berghella md facog Director, Division of Maternal-Fetal Medicine Professor, Department of Obstetrics and Gynecology Sidney Kimmel Medical College of Thomas Jefferson University Philadelphia, Pennsylvania, USA Mary E. D’Alton md mb bs Chair, Department of Obstetrics & Gynecology Willard C. Rappleye Professor of Obstetrics & Gynecology Columbia University Irving Medical Center Director of Services, Sloane Hospital for Women New York-Presbyterian, New York City, New York, USA Gian Carlo Di Renzo md phd Professor and Chairman, Department of Obstetrics and Gynecology Director, Perinatal and Reproductive Medicine Center and Midwifery School, University Hospital, Perugia, Italy Director, Permanent International and European School of Perinatal and Reproductive Medicine (PREIS), Florence, Italy Eduard Gratacós md Director and Professor, BCNatal, Hospital Clínic and Hospital Sant Joan de Deu, University of Barcelona, Barcelona, Spain Vassilios Fanos md

Professor of Pediatrics Director, Neonatal Intensive Care Unit University of Cagliari, Cagliari, Italy

CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2020 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed on acid-free paper International Standard Book Number-13: 978-1-138-70614-9 (Hardback) This book contains information obtained from authentic and highly regarded sources. While all reasonable efforts have been made to publish reliable data and information, neither the author[s] nor the publisher can accept any legal responsibility or liability for any errors or omissions that may be made. The publishers wish to make clear that any views or opinions expressed in this book by individual editors, authors or contributors are personal to them and do not necessarily reflect the views/opinions of the publishers. The information or guidance contained in this book is intended for use by medical, scientific or health-care professionals and is provided strictly as a supplement to the medical or other professional’s own judgement, their knowledge of the patient’s medical history, relevant manufacturer’s instructions and the appropriate best practice guidelines. Because of the rapid advances in medical science, any information or advice on dosages, procedures or diagnoses should be independently verified. The reader is strongly urged to consult the relevant national drug formulary and the drug companies’ and device or material manufacturers’ printed instructions, and their websites, before administering or utilizing any of the drugs, devices or materials mentioned in this book. This book does not indicate whether a particular treatment is appropriate or suitable for a particular individual. Ultimately it is the sole responsibility of the medical professional to make his or her own professional judgements, so as to advise and treat patients appropriately. The authors and publishers have also attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

Contents Introduction: Why do we need omics and systems biology? Contributors

vii xi

Section I  PREGNANCY COMPLICATIONS: SETTING THE SCENE 1 2 3 4 5 6 7 8 9 10 11

The mother: Adaptation to pregnancy and normal metabolism Francesca Parisi, Alice Zavatta, Roberta Milazzo, and Irene Cetin Maternal and fetal normal and abnormal nutrition Sarah Louise Killeen, Eilleen C. O’Brien, and Fionnuala M. McAuliffe Great obstetrical syndromes: It’s all in the placenta Martin Gauster and Gernot Desoye Normal and abnormal fetal growth Javier Caradeux, Eduard Gratacós, and Francesc Figueras Preterm labor and birth Vincenzo Berghella and Eduardo da Fonseca Gestational diabetes mellitus Silvia Vannuccini and Federico Mecacci Preeclampsia Jon Hyett and Liona C. Poon Maternal obesity Tahir A. Mahmood and Rohan Chodankar Maternal health: Immediate, short-, and long-term complications following pregnancy Gil Gutvirtz, Omri Zamstein, and Eyal Sheiner The fetus and the neonate: Immediate, short-, and long-term impact Umberto Simeoni and Elie Saliba Cost of pregnancy complications related to noncommunicable diseases and cost effectiveness of interventions to address them Anil Kapur, Jon Hyett, and H. David McIntyre

2 7 12 18 23 28 34 40 46 56

60

Section II TOWARDS PREDICTION AND PREVENTION 12 13 14 15 16 17 18 19 20 21 22

Integrated system biology approaches to fetal medicine problems Jezid Miranda, Fátima Crispi, and Eduard Gratacós Omics and female reproduction Galia Oron Maternal genome and pregnancy outcomes Nagendra K. Monangi, Ge Zhang, Mikko Hallman, Kari Teramo, Bo Jacobsson, and Louis J. Muglia Placental development and omics Sylvie Hauguel-de Mouzon, Gernot Desoye, and Silvija Cvitic Placental metabolomics in obese pregnancies Irene Cetin, Chiara Novielli, and Chiara Mandò Methylome and epigenetic markers Skevi Kyriakou, Marios Ioannides, George Koumbaris, and Philippos Patsalis Microbiome and pregnancy complications Maria Carmen Collado and Omry Koren Small noncoding RNAs as biomarkers for pregnancy complications Liron Yoffe, Meitar Grad, Avital Luba Polsky, Moshe Hod, and Noam Shomron Urine metabolomics and proteomics in prenatal health Daniela Duarte, Maria do Céu Almeida, Pedro Domingues, and Ana M. Gil Metabolomics and perinatal complications Flaminia Bardanzellu, Moshe Hod, and Vassilios Fanos Metabolomics in normal and pathologic pregnancies Antonio Ragusa, Alessandro Svelato, and Sara D’Avino

74 81 85 90 95 98 102 107 112 125 133

v

vi Contents 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37

Metabolomics in amniotic fluid 139 Alexandra-Maria Michaelidou, Foteini Tsakoumaki, Maria Fotiou, Charikleia Kyrkou, and Apostolos P. Athanasiadis Omics and coagulation disorders in pregnancy 149 Sara Ornaghi and Michael J. Paidas Omics and perinatal medicine: Preeclampsia 156 Piya Chaemsaithong and Liona C. Poon Single nucleotide polymorphisms and pregnancy complications 172 Federica Tarquini, Giuliana Coata, Elena Picchiassi, and Gian Carlo Di Renzo Metabolomics and perinatal cardiology 174 Roberta Pintus, Angelica Dessì, and Vassilios Fanos Metabolomics and human breast milk: A unique and inimitable food for infants 177 Flamina Cesare Marincola, Sara Corbu, Roberta Pintus, Angelica Dessì, and Vassilios Fanos Neurodevelopment and placental omics 181 Despina D. Briana and Ariadne Malamitsi-Puchner Early life complications, placental genomics, and risk for neurodevelopmental disorders in offspring 185 Pasquale Di Carlo, Giovanna Punzi, and Gianluca Ursini Metabolomics and perinatal asphyxia 192 Ernesto d’Aloja, Emanuela Locci, Antonio Noto, Matteo Nioi, Giovanni Bazzano, and Vassilios Fanos Environment, pregnancy complications, and omics 204 Chen Ben David and Ido Solt Sleep and pregnancy complications 209 Orna Sever and Riva Tauman Maternal plasma cell-free DNA screening: Basic science and applications 214 Peter Benn and Howard Cuckle Maternal plasma cell-free DNA screening: Integration into clinical practice 218 Howard Cuckle and Peter Benn Microarrays 223 Melissa Stosic, Jessica L. Giordano, Brynn Levy, and Ronald Wapner Whole exome and whole genome sequencing 230 Mary E. Norton

Index 239

Introduction Why do we need omics and systems biology? Omics implies many different approaches are concurrently applied to a seemingly singular problem. The presumption is that the plethora of concurrent data will lead to causal elucidations and treatment of pregnant woman and fetuses not otherwise possible. Those of us who have practiced and conducted investigations for decades could be forgiven for wondering just why this unfamiliar and vastly more complex assignment has suddenly become necessary. After all, we have long been conducting randomized clinical trials (RCTs), often happy with results, regardless of whether resolution had been reached on an arguable issue. RCTs funded by the National Institutes of Health (NIH), Medical Research Council (MRC), and other agencies seemed well constructed, took into account potential confounding variables that could be adjusted (multivariate analysis), and delivered crisp conclusions on the primary outcomes. Why, then, must we current investigators embark on a much more complex strategy? The simple answer is that the disorders we once believed to be a homogenous condition are rarely so. These disorders are heterogeneous. This volume illustrates well the approaches that are thus needed. In turn, we are in need of hypotheses derived in agnostic (“out of the box”) fashion, not just derivative of our preconceived beliefs. Let us, then, briefly consider why omics and systems biology will open doors that one could say are locked at present. I. C  ommon disorders were once considered homogenous in etiology: Perusing textbooks written perhaps 30–40 years ago leaves one with the conclusion that most common perinatal diseases were of a single etiology. Phenotypes of affected patients might differ in degree of expression, as for example shown by chronological age of onset or gestational week of manifestation. However, guidelines were fundamentally predicated on the assumption that a given disorder was singular. Systemic hypertension in adults was diagnosed (then and now) if blood pressure was greater than 140/90  mm  Hg. Simply put, below that value was normal. True, professional societies frequently explored different thresholds. Yes, we knew rare causes existed, such as Cushing syndrome or adrenal biosynthetic disorders. However, these “zebras” were considered exceptional, merely to be excluded initially for completeness of our differential diagnosis. Most cases would eventually prove to be of the same etiology and, hence, treated similarly. Aggressiveness of therapy (e.g., dosage) might differ, but qualitatively the strategy would not.

  In obstetrics, the prevalence of preeclampsia is 5%–7%. We know its epidemiology (primigravid women; multiparous women with new partners). We diagnosed on the basis of elevated blood pressure, hyperreflexia, edema, and proteinuria. We knew that a woman whose pre-pregnancy blood pressure was 100/70 need not reach 140/90 to be considered to have preeclampsia. Diagnosis, prevention, and treatment have not fundamentally changed for many years— nor has progress. The current elixir—aspirin—might benefit 20% of women. This means that 80% would not be “cured.” Despite this noninfectious condition affecting 5% of the population, we persisted in thinking there was usually only one etiology. Yet, heterogeneity exists; thus, something else is necessary for progress. Omics and systems biology become candidates. II. All common disorders are etiologically heterogeneous: If  almost all noninfectious medical disorders of incidence 2%–5% are heterogeneous in etiology, what is their underlying basis? Illustrative is that medical geneticists had the advantage of knowing that heritable inborn errors of metabolism were heterogeneous. Mutations in different enzymes in a common pathway could have the same end result, for example, elevated cholesterol or decreased cortisol. This was the result of defects in one of the sequential enzymes in a single biosynthetic pathway. That each disorder was due to a different gene (etiologic heterogeneity) was evident, even if at least one component of a pleiotropic phenotype was similar. Differentiation was also possible as a result of different profiles of metabolites.   A familiar example is phenylketonuria (PKU). PKU is an autosomal recessive disorder due to deficiency of the enzyme phenylalanine hydroxylase (PAH), which is necessary to convert phenylalanine to tyrosine. Diagnosis of PKU was initially made not on the basis of directly measuring excess phenylalanine, but by detecting an increase in the by-product metabolite phenylpyruvic acid. Phenylpyruvic acid accumulated secondarily to elevated levels of phenylalanine. But even the uncommon disorder PKU is heterogeneous. Classical, variant, and benign phenotypes exist, all due to different perturbations in the PAH enzyme. Perturbations exist in still other genes—PCR and PHPR. All contribute to clinical PKU.   We in obstetrics-gynecology (OB-GYN) have lacked analogous examples like inborn errors of metabolism. Global conferences are convened to codify diagnostic criteria (e.g., Rotterdam criteria), but classifications tend to be quantitative variants on the theme of vii

viii Introduction

follicles, hirsutism, and anovulation. Yet over a dozen different genes are associated with polycystic ovarian syndrome (PCOS) and characterized by robust statistical significance (1,2).   Fortunately, increased appreciation of genetic and etiological heterogeneity is occurring in many common obstetrical conditions. Progress in differentiating hyperglycemias is an example. Once, only binary stratification into childhood (insulin-dependent) and adult-onset (insulin resistant) diabetes mellitus (DM) existed. This categorization later became disrupted with the recognition of maturity onset diabetes of youth (MODY). Its age of onset (late teens; early third decade) was different. Heritability was different (often a single gene). Later, MODY began to be stratified into different types on the basis of genes and mode of inheritance. III. Phenotypically similar but etiologically distinct disorders require different diagnostic criteria and different treatments: Adrenal hyperplasia is the result of one of a series of enzyme defects in the biosynthetic path that results in cortisol. Negative feedback inhibition based on cortisol levels modulates rate of synthesis. If an enzyme block exists in the pathway, precursors accumulate prior to the block, leading secondarily to excesses of other steroids. A dozen distinct defects exist. Many differ considerably from one another in phenotype, but others show only nuanced differences.   The adrenal biosynthetic pathway includes the enzymes 21-hydroxylase and 11-β-hydroxylase. 21-Hydroxylase is required to convert 17α-OH progesterone to 11-deoxycortisol, a penultimate step in the synthesis of cortisol. Genital ambiguity occurs in affected females because when 17α-OH progesterone accumulates, conversion to androgens occurs. Salt wasting also occurs because 11-deoxycortisol, which facilitates salt retention, is not synthesized in normal amounts. The situation differs in part with the next enzyme in the adrenal biosynthetic pathway: 11-β-hydroxylase, whose deficiency results in excess 11-deoxycortisol that again leads to deficiencies in cortisol. Like 21-hydroxylase, genital ambiguity occurs as a result of accumulation of excess androgens. However, no longer does salt retention occur. Instead, the salt-retaining steroid 11-deoxycortisol accumulates, resulting in hypertension due to hypervolemia. Thus, salt wasting occurs in 21-hydroxylase deficiency, whereas salt retention occurs in 11β-hydroxylase deficiency. Treatment with cortisol abrogates genital ambiguity in both. Were genital ambiguity the only feature, phenotypic differences would not be so well appreciated.   Differentially treating phenotypically similar but actually nonidentical conditions is a major principle underlying improvement in oncology treatment. Genetic testing often reveals a series of different mutations in histologically similar tumors in different

individuals. Let us assume that any of a set of genes (A, B, C, D, or E) could if perturbed produce a histologically identical cancer. Assume further that three different chemotherapeutic agents confer benefit in patients having a tumor of common histologic type. Yet no drug alone is universally efficacious. Chemotherapeutic agents 1 and 3 might be efficacious in certain patients, whereas only agent 2 might provide benefit in other patients. Higher doses of agent 2 could be delivered if 1 and 3 are not concurrently administered. The converse also is applicable. We can predict that analogous strategies will evolve for detecting and treating preeclampsia and preterm birth. IV. Precision medicine integrates omics, clinical data, environmental exposures, and social determinants: Marketing teams often tout an institution for its “precision medicine.” Applicability to obstetrics is not a new idea (3). However, do we in 2019 offer “precision medicine in obstetrics”? Not really. To date, only limited diagnostic options exist for women with obstetrical disorders. We can measure the presence or absence of an associated protein (recall that enzymes are gene products) or metabolites indicative of an altered pathway. But usually this information overlaps with those characteristics of other conditions thus not being qualitatively unique. By contrast, a novel footprint might exist if we interrogated DNA sequences in a targeted region from among the 21,000 protein-coding genes. We can compare a promising sequence in a patient-derived sample to the normal reference genome. Sequencing is no longer difficult, expensive, or time-consuming. Benign variants can be distinguished readily from pathogenic variants.   Imagine the power of expanding and applying our nascent genomic knowledge to obstetrical conditions. Of the protein-coding genes, function is known in only one-third. A portion of the remaining two-thirds can be expected to play pivotal roles in embryonic/ fetal differentiations or placentation. The sentinel genomewide association study (GWAS) by Zhang, Muglia, and colleagues is a shining example (4). A total of 43,568 women of European ancestry had self-reported their experience with preterm birth. This discovery group was compared to replicates of three Nordic data sets comprising 8,643 women. Six significant sequences were found. Their contiguous genes were thus associated with preterm birth, gestational length, or both. Several genes had not been appreciated or received attention previously. Hallman, Zhang, Muglia, and colleagues further describe how GWAS is only the start (5).   Protein-coding genes (exome) constitute only 1.5% of DNA; 98.5% of the human genome is not proteincoding genes, carrying out regulatory functions. Regulatory regions govern the degree of gene expression. Expression of a given gene is not necessarily on or off, but quantifiable in degree. Imagine a

Introduction ix

temperature thermostat, in which a single setting is not expected and does not need to be constant. Gene expression can be increased, decreased, or turned off without altering the DNA sequence. The mechanism is presumed to involve DNA methylation. One can thus track gene expression by RNA expression (transcription) or by DNA suppression (methylome). If a gene ordinarily not expressed (imprinted) suddenly becomes expressed, its regulatory sequence might have become demethylated and, hence, transcribed (transcriptome).   From study of the genome, transcriptome, and methylome, one can concurrently study proteins (proteome) and metabolites (metabolome). This approach is well illustrated by the integrated system biology approach of Than et al. (6) on preeclampsia. An integrated approach was applied by Tsang et al. (7) to determine DNA or RNA in individual placental cells, correlating with histology, metabolic information, and single cell function and morphology via cell separation. There was shown to be 18 different types of placental cells. In addition, one can incorporate information on environment and interaction with genome (epigenome), measures of social determination (e.g., nutrition), and clinical status. Examples of the latter are clinical risk factors and sociodemographic findings gathered from individual patient data on 4.1 million women in four countries and California (8). These data were used to generate population-based odds ratios (ORs) for risk factors. These differ from ORs for an individual’s risk factor. A high OR (e.g., 6.0) for a woman having had a prior preterm birth (PTB) would be good counsel, but because PTB occurs only in 8%–10% of deliveries the population-attributable risks would not be great. By contrast, a lower OR (OR 1.3) would confer a greater attributable risk for the general population if the frequency of a risk factor were more than 8%–10%. Thus, nulliparity and male sex actually confer a greater overall (population) effect than preeclampsia or PTB. In aggregate, both nature and nurture can be concurrently assessed. V. Data interrogation and clinical conclusion: Accumulating an enormous amount of data is attractive but presents a problem. Data accumulation and ongoing monitoring are necessary. The integrated repository being created for the March of Dimes Prematurity Research Centers is exemplary (9). How, then, can one utilize these data to determine causative significance and therapy? How can one extract truly novel information? There are two conceptual approaches for data exploration and mining: (1) machine learning and (2) artificial intelligence (AI). Tools are similar and overlap, but expectations differ.   Machine learning implies brute-force iterative queries, using computers and bioinformatics to accomplish such searches. The underlying hypothesis

might be traditional, or a novel idea hypothesized by an investigator. Despite immense software and computer prowess needed, recall that this approach fundamentally requires a human. Computers are very efficient at processing massive data sets to recognize patterns; however, someone must program the endpoint or threshold that justifies an algorithmic response. To illustrate, let us fancifully try to identify members of a terrorist cell. As the investigator, one might enumerate a plethora of nefarious characteristics hypothesized to distinguish terrorist from nonterrorist. This list would doubtless be based on our prior assumption of behavior expected by a terrorist. For example, one might predict gun purchase, proclivity for fast cars, and social isolation. A machine learning approach could thus sort through massive data in hopes of identifying recurring patterns indicative of suspect individuals. Law enforcement could then focus on individuals identified. In medicine, we can apply machine learning to fine-tune disease predictions or stratify given a known set of associated characteristics.   AI is agnostic. There is no a priori hypothesis. The principle involves interrogating all relationships, not just those logically deduced by humans but those seemingly illogical. AI would thus explore all hypotheses. In fact, we already use agnostic approaches to locate geneassociated sequences. Zhang et al. (4) had no restrictions on genes likely to be associated with gestational length or preterm birth, but found six associated proteincoding genes. Not all were anticipated. A humanderived hypothesis might have been restrictive and perhaps counterproductive; humans can imagine only so much, and in doing so subliminally filter out the implausible. Unimaginable relationships would never be explored. Let us return to our search for terrorists. AI can proceed agnostically without prior hypotheses and without unwitting restriction of a hypothesis. Perhaps attending a certain movie theater on the Saturday before a planned terrorist action will unwittingly pinpoint terrorist members. Perhaps the members also frequent a particular ice cream parlor and eat pistachio ice cream. Perhaps members unexpectedly enjoy a television show of unexpected motif—not an action movie but a fashion show. AI can interrogate and correlate all this, without bias. A set of characteristics could evolve that would not be imaginable by us.   Machine learning and AI are being utilized for system biology, and “multiomic” approaches have resulted in novel observations, especially relating to adaptations during pregnancies using patterns of fetal gene expression. Predictions can be made on gestational length—not by ultrasound but by analysis of maternal blood. Maternal (and fetal) cell free DNA correlated with gestational age predicts gestational age within 2 weeks (10). A Stanford team is pursuing the concept of gestational clocks: immunologic (11), proteomic (12), and a truly agnostic “multiomic” (13).

x Introduction

Conclusion Genetic heterogeneity is ubiquitous among the major obstetrical syndromes. Contemporary investigators must adjust to this reality and make appropriate changes in our experimental designs. Enumerating all possible hypotheses is mathematically impractical and no longer possible. Even if practical, such an approach would be presumptuous because our enumerating all possible relationships of causative value cannot escape intrinsic bias and expectation. Omics and systems biology will reveal new avenues for elucidating etiology and, hence, new pathways to novel treatment. Joe Leigh Simpson Department of Obstetrics and Gynecology Department of Molecular and Human Genetics Herbert Wertheim College of Medicine Florida International University, Miami, Florida Moshe Hod Mor Comprehensive Women’s Health Care Center, Sackler Faculty of Medicine Tel Aviv University, Tel Aviv, Israel

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1. Chen ZJ, Zhao H, He L et al. Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2-21 and 9q33.3. Nat Genet. 2011;43:55–59. 2. Shi Y, Zhao H, Shi Y et al. Genome-wide association study identifies eight new risks loci for polycystic ovary syndrome. Nat Genet. 2012;44:1020–1025. 3. Romero R, Tromp G. High-dimensional biology in obstetrics and gynecology: Functional genomics in microarray studies. Am J Obstet Gynecol. 2006;195:360–363.

4. Zhang G, Feenstra B, Bacelis J et  al. Genetic associations with gestational length and spontaneous preterm birth. New Eng Med. 2017;337:1156–1167. 5. Hallman M, Haapalainen A, Huusko JM et  al. Spontaneous premature birth as a target of genomic research. Pediatr Res. 2019;85:422–431. 6. Than NG, Romero R, Tarca AL et  al. Integrated systems biology approach identifies novel maternal and placental pathways of preeclampsia. Front Immunol. 2018;9:1–41; Article 1661. 7. Tsang JCH, Vong JSL, Ji L et al. Integrative singlecell and cell-free RNA analysis. PNAS. 2017;114(37): e7786–e7795. 8. Ferrero DM, Larson J, Jacobsson B et  al. Crosscountry individual participant analysis of 4.1 million singleton births in 5 countries with very high human development index confirms known associations but provides no biologic explanation for 2/3 of all preterm births. PLOS ONE. 2016;11:e0162506. 9. Sirota M, Thomas CG, Liu R et al. Author correction: Enabling precision medicine in neonatology, an integrated repository for preterm birth research. Sci Data. 2018;5(1):3. 10. Ngo TTM, Moufarrej MN, Rasmussen MLH et  al. Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Science. 2018;360(6393):1133–1136. 11. Aghaeepour N, Ganio EA, Mcilwain D et  al. An immune clock of human pregnancy. Sci Immunol. 2017;2(15), pii: eaan2946. doi:10.1126/sciimmunol. aan2946 12. Aghaeepour N, Lehallier B, Baca Q et al. A proteomic clock of human pregnancy. Am J Obstet Gynecol. 2018;218(3):347.e1–347.e14. 13. Ghaemi MS, DiGiulio DB, Contrepois K et al. Multiomics modeling of the immunome, transcriptome, microbiome, proteome, and metabolome adaptations during human pregnancy. Bioinformatics. 2019;35:​ 95–103.

Contributors Maria do Céu Almeida Maternidade Bissaya Barreto Centro Hospitalar e Universitário Coimbra Coimbra, Portugal and Department of Chemistry and QOPNA CICECO–Aveiro Institute of Materials University of Aveiro, Campus Universitario de Santiago Aveiro, Portugal Apostolos P. Athanasiadis Department of Obstetrics and Gynecology School of Medicine Aristotle University of Thessaloniki Thessaloniki, Greece Flaminia Bardanzellu Neonatal Intensive Care Unit AOU University of Cagliari Cagliari, Italy Giovanni Bazzano Department of Medical Sciences and Public Health University of Cagliari Cagliari, Italy Peter Benn Department of Genetics and Genome Sciences University of Connecticut Health Center Farmington, Connecticut Vincenzo Berghella Professor, Ob-Gyn Director, MFM Division and Fellowship Thomas Jefferson University Philadelphia, Pennsylvania

Irene Cetin Department of Woman, Child and Neonate V. Buzzi Children Hospital ASST Fatebenefratelli Sacco and Department of Biomedical and Clinical Sciences University of Milan Milan, Italy Piya Chaemsaithong Department of Obstetrics and Gynaecology Prince of Wales Hospital The Chinese University of Hong Kong Shatin, Hong Kong SAR, China Rohan Chodankar MRC Centre for Reproductive Health Queens Medical Research Institute University of Edinburgh Edinburgh, Scotland Giuliana Coata Laboratory of Prenatal Biochemistry and Molecular Biology Department of Biomedical and Surgical Sciences University of Perugia Perugia, Italy Maria Carmen Collado Institute of Agrochemistry and Food Technology National Research Council (IATA-CSIC) Valencia, Spain Sara Corbu Department of Chemical and Geological Sciences University of Cagliari Cagliari, Italy

Despina D. Briana Department of Neonatology National and Kapodistrian University of Athens Medical School Athens, Greece

Fátima Crispi Fetal i+D Fetal Medicine Research Center BCNatal–Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu) ICGON, IDIBAPS University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER) Barcelona, Spain

Javier Caradeux Fetal Medicine Unit Clínica Dávila Santiago, Chile

Howard Cuckle Department of Obstetrics and Gynecology Columbia University Medical Center New York City, New York

xi

xii Contributors Silvija Cvitic Department of Obstetrics and Gynaecology Medical University of Graz Graz, Austria Eduardo da Fonseca Division of Obstetrics and Gynecology Federal University of Paraíba Paraíba, Brazil Ernesto d’Aloja Department of Medical Sciences and Public Health University of Cagliari Cagliari, Italy Chen Ben David Feto-Maternal Medicine Division Rambam Health Care Campus and Technion Faculty of Medicine Haifa, Israel Sara D’Avino Department of Obstetrics and Gynecology Massa Carrara General Hospital Massa Carrara, Italy and Lieber Institute for Brain Development Johns Hopkins Medical Campus Baltimore, Maryland Gernot Desoye Department of Obstetrics and Gynaecology Medical University of Graz Graz, Austria Angelica Dessì Neonatal Intensive Care Unit AOU Policlinico di Monserrato University of Cagliari Cagliari, Italy Pasquale Di Carlo Group of Psychiatric Neuroscience Department of Basic Medical Sciences Neuroscience and Sense Organs University of Bari Aldo Moro Bari, Italy Gian Carlo Di Renzo Department of Obstetrics and Gynecology Perinatal and Reproductive Medicine Center and Midwifery School University Hospital Perugia, Italy and Permanent International and European School of Perinatal and Reproductive Medicine (PREIS) Florence, Italy

Pedro Domingues Department of Chemistry and QOPNA CICECO–Aveiro Institute of Materials University of Aveiro Aveiro, Portugal Daniela Duarte Department of Chemistry CICECO–Aveiro Institute of Materials University of Aveiro Aveiro, Portugal Vassilios Fanos Neonatal Intensive Care Unit AOU Policlinico di Monserrato and Department of Surgical Sciences University of Cagliari Cagliari, Italy Francesc Figueras Fetal i+D Fetal Medicine Research Center BCNatal–Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), ICGON Barcelona, Spain Maria Fotiou Department of Food Science and Technology School of Agriculture Aristotle University of Thessaloniki Thessaloniki, Greece Martin Gauster Division of Cell Biology, Histology, and Embryology Gottfried Schatz Research Centre for Cell Signaling, Metabolism and Ageing Medical University of Graz Graz, Austria Ana M. Gil CICECO–Aveiro Institute of Materials Department of Chemistry University of Aveiro Aveiro, Portugal Jessica L. Giordano Department of Obstetrics and Gynecology Columbia University Irving Medical Center New York City, New York Meitar Grad Faculty of Medicine Tel Aviv University Tel Aviv, Israel

Contributors xiii Eduard Gratacós Department of Obstetrics and Gynaecology Medical University of Graz Graz, Austria and Fetal i+D Fetal Medicine Research Center BCNatal–Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu) ICGON, IDIBAPS University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER) Barcelona, Spain Gil Gutvirtz Department of Obstetrics and Gynecology Soroka University Medical Center Ben-Gurion University of the Negev Beer-Sheva, Israel and Department of Chemistry CICECO–Aveiro Institute of Materials University of Aveiro Aveiro, Portugal Mikko Hallman The PEDEGO Research Unit and Medical Research Center Oulu University of Oulu and Department of Children and Adolescents Oulu University Hospital Oulu, Finland Sylvie Hauguel-de Mouzon Department of Reproductive Biology Case Western Reserve University Cleveland, Ohio Moshe Hod Mor Comprehensive Women’s Health Care Center Sackler Faculty of Medicine Tel Aviv University Tel Aviv, Israel Jon Hyett Sydney Institute for Women Children and their Families Sydney Local Health District and Discipline of Obstetrics, Gynaecology, and Neonatology Faculty of Medicine University of Sydney Sydney, Australia

Marios Ioannides NIPD Genetics Nicosia, Cyprus Bo Jacobsson Department of Obstetrics and Gynecology Sahlgrenska Academy University of Gothenburg Gothenburg, Sweden and Department of Genetics and Bioinformatics Area of Health Data and Digitalization Norwegian Institute of Public Health Oslo, Norway Anil Kapur World Diabetes Foundation Bagsvaerd, Denmark Sarah Louise Killeen UCD Perinatal Research Centre UCD School of Medicine National Maternity Hospital Dublin, Ireland Omry Koren The Azrieli Faculty of Medicine Bar Ilan University Safed, Israel George Koumbaris NIPD Genetics Nicosia, Cyprus Skevi Kyriakou NIPD Genetics Nicosia, Cyprus Charikleia Kyrkou Department of Food Science and Technology School of Agriculture Aristotle University of Thessaloniki Thessaloniki, Greece Brynn Levy Department of Pathology and Cell Biology Columbia University Irving Medical Center New York, New York Emanuela Locci Department of Medical Sciences and Public Health University of Cagliari Cagliari, Italy Tahir A. Mahmood Consultant Obstetrician and Gynaecologist Victoria Hospital Kirkcaldy, Scotland

xiv Contributors Ariadne Malamitsi-Puchner National and Kapodistrian University of Athens Medical School Athens, Greece Chiara Mandò Department of Biomedical and Clinical Sciences “Luigi Sacco” Università degli Studi di Milano Milan, Italy Flamina Cesare Marincola Department of Chemical and Geological Sciences University of Cagliari Cagliari, Italy Fionnuala M. McAuliffe UCD Perinatal Research Centre UCD School of Medicine National Maternity Hospital Dublin, Ireland H. David McIntyre Conjoint Head, Mater Clinical Unit University of Queensland Mater Clinical School Brisbane, Australia Federico Mecacci Department of Experimental Clinical and Biomedical Sciences University of Florence Careggi University Hospital Florence, Italy Alexandra-Maria Michaelidou Department of Food Science and Technology School of Agriculture Aristotle University of Thessaloniki Thessaloniki, Greece Roberta Milazzo Department of Woman, Child and Neonate V. Buzzi Children Hospital ASST Fatebenefratelli Sacco and Department of Biomedical and Clinical Sciences University of Milan Milan, Italy Jezid Miranda Fetal i+D Fetal Medicine Research Center BCNatal–Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), ICGON, IDIBAPS University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER) Barcelona, Spain

Nagendra K. Monangi Division of Neonatology Perinatal Institute Cincinnati Children’s Hospital Medical Center and Department of Pediatrics University of Cincinnati College of Medicine Cincinnati, Ohio Louis J. Muglia Department of Pediatrics University of Cincinnati College of Medicine and Division of Human Genetics The Center for Prevention of Preterm Birth Perinatal Institute Cincinnati Children’s Hospital Medical Center Cincinnati, Ohio Matteo Nioi Department of Medical Sciences and Public Health University of Cagliari Cagliari, Italy Mary E. Norton Department of Obstetrics, Gynecology, and Reproductive Sciences University of California, San Francisco San Francisco, California Antonio Noto Department of Surgical Sciences University of Cagliari Cagliari, Italy Chiara Novielli Department of Biomedical and Clinical Sciences “Luigi Sacco” Università degli Studi di Milano Milan, Italy Eilleen C. O’Brien UCD Perinatal Research Centre UCD School of Medicine National Maternity Hospital Dublin, Ireland Sara Ornaghi Department of Obstetrics and Gynecology Foundation MBBM University of Milan-Bicocca School of Medicine and Surgery Monza, Italy

Contributors xv Galia Oron IVF and Infertility Unit Helen Schneider Hospital for Women Rabin Medical Center Petach-Tikva, Israel and Sackler Faculty of Medicine Tel Aviv University Tel Aviv, Israel Michael J. Paidas Department of Obstetrics and Gynecology University of Miami Miller School of Medicine Miami, Florida Francesca Parisi Department of Woman, Child and Neonate V. Buzzi Children Hospital ASST Fatebenefratelli Sacco Milan, Italy

Antonio Ragusa Department of Obstetrics and Gynecology Massa Carrara General Hospital Massa Carrara, Italy Elie Saliba Division of Neonatology Tours University Hospital and University Tours, France Orna Sever Sleep Disorders Center Tel Aviv Souraski Medical Center Sackler School of Medicine Tel Aviv University Tel Aviv, Israel Eyal Sheiner Department of Obstetrics and Gynecology Soroka University Medical Center Ben-Gurion University of the Negev Beer-Sheva, Israel

Philippos Patsalis NIPD Genetics Nicosia, Cyprus

Noam Shomron Faculty of Medicine Tel Aviv University Tel Aviv, Israel

Elena Picchiassi Laboratory of Prenatal Biochemistry and Molecular Biology Department of Biomedical and Surgical Sciences University of Perugia Perugia, Italy

Umberto Simeoni Division of Pediatrics Département Femme-Mère-Enfant Centre Hospitalier Universitaire Vaudois University of Lausanne Lausanne, Switzerland

Roberta Pintus Neonatal Intensive Care Unit Azienda Ospedaliero-Universitaria Cagliari University of Cagliari Cagliari, Italy

Ido Solt Feto-Maternal Medicine Division Rambam Health Care Campus and Technion Faculty of Medicine Haifa, Israel

Avital Luba Polsky Faculty of Medicine Tel Aviv University Tel Aviv, Israel Liona C. Poon Department of Obstetrics and Gynaecology Prince of Wales Hospital The Chinese University of Hong Kong Shatin, Hong Kong SAR, China Giovanna Punzi Lieber Institute for Brain Development Johns Hopkins Medical Campus Baltimore, Maryland

Melissa Stosic Department of Obstetrics and Gynecology Columbia University Irving Medical Center New York City, New York Alessandro Svelato Department of Obstetrics and Gynecology Massa Carrara General Hospital Massa Carrara, Italy Federica Tarquini Laboratory of Prenatal Biochemistry and Molecular Biology Department of Biomedical and Surgical Sciences University of Perugia Perugia, Italy

xvi Contributors Riva Tauman Sleep Disorders Center Tel Aviv Souraski Medical Center Sackler School of Medicine Tel Aviv University Tel Aviv, Israel Kari Teramo Department of Obstetrics and Gynecology University of Helsinki and Helsinki University Hospital Helsinki, Finland Foteini Tsakoumaki Department of Food Science and Technology School of Agriculture Aristotle University of Thessaloniki Thessaloniki, Greece Gianluca Ursini Lieber Institute for Brain Development Johns Hopkins Medical Campus and Department of Psychiatry and Behavioral Sciences Johns Hopkins School of Medicine Baltimore, Maryland Silvia Vannuccini Department of Neuroscience, Psychology, Pharmacology and Child Health University of Florence Careggi University Hospital Florence, Italy and Department of Molecular and Developmental Medicine Obstetrics and Gynecology University Hospital of Siena Siena, Italy

Ronald Wapner Department of Obstetrics and Gynecology Columbia University Irving Medical Center New York City, New York Liron Yoffe Faculty of Medicine Tel Aviv University Tel Aviv, Israel Omri Zamstein Department of Obstetrics and Gynecology Soroka University Medical Center Ben-Gurion University of the Negev Beer-Sheva, Israel Alice Zavatta Department of Woman, Child and Neonate V. Buzzi Children Hospital ASST Fatebenefratelli Sacco and Department of Biomedical and Clinical Sciences University of Milan Milan, Italy Ge Zhang Department of Pediatrics University of Cincinnati College of Medicine and Division of Human Genetics The Center for Prevention of Preterm Birth Cincinnati Children’s Hospital Medical Center Cincinnati, Ohio

I

Section   

Pregnancy Complications: Setting the Scene

1

The mother Adaptation to pregnancy and normal metabolism FRANCESCA PARISI, ALICE ZAVATTA, ROBERTA MILAZZO, and IRENE CETIN

INTRODUCTION

During pregnancy, several maternal anatomical and physiological changes occur in order to ensure proper development of the growing fetus and to prepare the mother for labor and delivery. In this context, maternal adaptation to pregnancy includes numerous cardiovascular, renal, hematologic, respiratory, and metabolic changes that finally lead to increased oxygen and nutrient supply to the fetoplacental unit and to enhanced protection against postpartum hemorrhage for the mother. Table 1.1 summarizes the main mechanisms of maternal adaptation to pregnancy with a systems approach. Moreover, an evolutionary revolution occurred over the last decades: the intrauterine period of development has been shown to permanently shape the adult life, mainly through epigenetic modifications that affect the postnatal phenotype of the offspring in later life (1). This concept has given a new pivotal role to obstetric care also for improving the health status and the risk of chronic disease of future generations. In this context, maternal maladaptation to pregnancy may lead to short-term derangements in intrauterine development, with abnormal fetal growth, birth weight, and morphological development, and may finally shape the risk of chronic diseases of the child and the adult as a long-term effect. PERICONCEPTIONAL PERIOD

Despite the great attention given to the second half of pregnancy, the research focus has recently moved to the first trimester and the time around conception (the “periconceptional period”) in order to grant early screening and diagnosis of subsequent adverse pregnancy outcomes with long-term health effects (Figure 1.1). The periconceptional period represents a chaotic time window from a biological point of view, starting with gamete maturation, going through the events of fertilization and implantation, and ending with the development of the embryonic structures and the first stages of placentation. This period is crucial for a normal adaptation to pregnancy, and any pathological deviation in this time window may finally lead to overt diseases in the second half of pregnancy and to larger shifts in the adult phenotype than the second half of pregnancy. In fact, if it is true that perinatal morbidity and mortality and the risk of noncommunicable diseases are mainly related to complications diagnosed during the second part of pregnancy (e.g., hypertensive 2

disorders, intrauterine growth restriction, preterm birth), it is also evident that these conditions originate during the very first stages of pregnancy and even before, thus involving the most important stages of gamete, placenta, and embryo development (2). MATERNAL ADAPTATIONS

Maternal immune and cardiovascular adaptations, including early endometrium decidualization, subsequent trophoblast implantation and invasion, and transformation of the uterine circulation into low-resistance vessels, are all periconceptional events necessary for successful placental development, with short- and long-term effects during the second half of pregnancy onward. All of these processes are orchestrated by several placental molecules and proteases, including the endothelial and placental growth factors (vascular endothelial growth factor [VEGF], placental growth factor [PlGF]) and vasoactive mediators (e.g., nitric oxide, transforming growth factor [TGF]-ß, and endothelial prostacyclin). Together with decreased systemic vascular reactivity to angiotensin II and norepinephrine, these early local events together with the systemic release of placental mediators lead to peripheral vasodilatation and the drop of systemic vascular resistances (3). As a consequence, both systolic and diastolic pressures decrease to a nadir at 24–26 weeks. In the meanwhile, the expansion of blood volume, starting around 12 weeks of gestation, represents a cardinal change in order to support the increased metabolic requests of the fetoplacental unit and to protect the mother against hypotension and postpartum blood loss (4). More specifically, the plasma expansion overcomes the increment of cellular components, with consequent hemodilution and physiologic gestational anemia, adequate uteroplacental perfusion, and lower cardiac work. Hypervolemia is the result of different mechanisms primarily due to estrogenic stimulation, including renin-angiotensin axis activation, higher levels of aldosterone, and reduction of atrial natriuretic peptide. Plasma volume expansion is known to be lower in pregnancies complicated by hypertension, preeclampsia, and fetal growth restriction, although it is not clear if these women already have a lower pre-pregnancy volume or if this is a consequence of a hemodynamic maladaptation (5). On the other side, decreased peripheral vascular resistances also result in increasing heart rate, as an effect of sympathetic nervous system activation (6). Therefore,

Metabolic changes during pregnancy  3

Table 1.1  Maternal adaptation to pregnancy System Cardiovascular

Hematologic

Renal

Respiratory

Gastrointestinal

Metabolism

Immunity

Increase

Decrease

Heart rate Blood volume Cardiac output Venous stasis Plasma volume Red blood cell mass Fibrinogen, factors II, VII, VIII, X, XII, XIII Thrombin activatable fibrinolytic inhibitor, PAI-1, PAI-2 D-dimer Resistance to activated protein C Organ volume Renal blood flow GFR Urinary frequency and nocturia Dilatation of the ureters and renal pelvis Proteinuria and glucosuria Excretion of HCO3− Minute ventilation PO2 Slight alkalosis Oxygen consumption Gastroesophageal reflux Lithogenicity of bile Serum alkaline phosphatase Insulin resistance Postprandial glycemia FFA concentration Cholesterol and triglyceride concentrations Leukocytes count Th2 response CRP and ESR

Systemic vascular resistance Systemic blood pressure Blood viscosity (Hct and Hb) Protein S activity Prothrombin time (slightly) Hemoglobin concentration Platelet count (slightly)

Creatinine Natremia

Functional residual capacity PCO2

Intestinal peristalsis Gallbladder motility Serum level of AST, ALT, γ-GT Albumin concentration Starving glycemia

Leukocytes function Th1 response Immunoglobulin titles

Abbreviations: CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; FFA, free fatty acid; Hb, hemoglobin; Hct, hematocrit; GFR, glomerular filtration rate; PAI, plasminogen activator inhibitor; PCO2, partial pressure of carbon dioxide; PO2, partial pressure of oxygen; Th, T-helper lymphocytes.

the cardiac output elevation of pregnancy is caused by preload increment (blood volume expansion), afterload reduction (drop in peripheral vascular resistances), and increased maternal heart rate. Nevertheless, the ejection fraction remains constant, representing a reliable marker of left ventricular function (7). Pregnancies complicated by hypertensive disorders and fetal growth restriction typically show hemodynamic dysfunctional adaptation: low cardiac output and high total vascular resistance (8). Moreover, the increased afterload of hypertensive conditions leads to compensatory left ventricular remodeling, necessary to reduce wall stress and to balance myocardial oxygen demand and supply (9). It is clear that if the first periconceptional step of adequate trophoblast invasion and spiral artery remodeling fails to build a proper placental circulation, the resulting ischemic placenta and the local oxidative stress lead to systemic endothelial

dysfunction, greater release of antiangiogenic factors (e.g.,  sFlt-1, endoglin) and pro-inflammatory cytokines (e.g., tumor necrosis factor [TNF]-α) (3), finally resulting in cardiovascular maternal maladaptation, hypertensive disorders, and fetal growth restriction in the second half of pregnancy (3). METABOLIC CHANGES DURING PREGNANCY

The periconceptional period represents the starting point of all metabolic adaptations that lead to proper placental development, adequate nutrient delivery, and normal prenatal growth trajectory. From a metabolic point of view, the first half of pregnancy is physiologically characterized by anabolic processes aiming to store energy in the maternal adipose tissue (12). In this period and under the direct effect of pregnancy-related hormones that increase both insulin release and sensitivity (e.g., estrogens, progesterone,

4  The mother

Gamete maturation

Implantation placentation embryo development

Fertilization

Adaptation to pregnancy and long-term health outcomes

Figure 1.1  The periconceptional period (14 weeks before to 10 weeks after conception). The periconceptional period includes a series of complex events starting from male and female gamete maturation, going through conception, implantation, placentation, and finally to embryogenesis in the first trimester of pregnancy. Such a chaotic period is vulnerable to external parental environment and exposures. But more important, parental exposures in the periconceptional period have been shown to permanently modify the development of the gamete/placenta/embryo, finally impacting on pregnancy outcome and further programming the future health of the offspring.

placental lactogen, and growth hormones), maternal hunger sensation and lipogenic processes are progressively enhanced (13). In turn, the second half of pregnancy shows a switch toward a catabolic state essential for increasing the delivery of nutrients to the exponentially growing fetus. In this context, maternal insulin resistance represents the key physiological mechanism leading to intensified endogenous glucose production, lipolytic activity, and finally increased maternal glucose and free fatty acid (FFA) delivery to the fetoplacental unit (6,14–18). Derangements in metabolic adaptations can lead to pathological insulin resistance, chronic hyperglycemia, and hyperinsulinemia characterizing gestational diabetes mellitus (GDM). As a multifactorial syndrome, GDM is characterized by ß-cell dysfunction resulting in excessive insulin production, and peripheral insulin resistance, both leading to reduced glucose uptake, adipocyte differentiation, and gene expression of insulin signaling regulators (19–23). Maternal adipose tissue, as an endocrine organ together with the placenta, represents the main mediator of early abnormal metabolic adaptations, with effects on metabolic, vascular, and inflammatory pathways that eventually shape several adverse obstetric outcomes in the setting of maternal obesity, including GDM and hypertensive disorders (24,25). In obese pregnancies, maternal lipid profile shifts, increasing triglycerides and decreasing high-density lipoproteins concentrations, and placental expression of fatty acid binding proteins are stimulated (26,27). This will finally lead to increased nutrient delivery to the fetus with resulting prenatal overgrowth. Moreover, long-chain polyunsaturated fatty acids biomagnification is disrupted, leading to decreased availability of arachidonic acid and DHA for the fetus and increased risk of a number of chronic diseases throughout postnatal life.

NUTRITION AND LIFESTYLE

Unhealthy maternal lifestyle and nutritional factors represent all modifiable risk factors impacting early maternal adaptations and leading to abnormal placentation, adverse pregnancy outcomes, and chronic diseases in future life. In this context, periconceptional maternal smoking was significantly associated with intrauterine growth restriction and preterm delivery (10), likely as a consequence of hypoxia, excessive oxidative stress, and the proangiogenic role of nicotine, that eventually alter early placental vasculogenesis, villous development, and function (2). Even qualitative or quantitative maternal malnutrition negatively impacts several pathways of embryonic and placental development. Periconceptional folic acid supplementation and adherence to a Mediterranean diet have been associated with uteroplacental Doppler indices during the second half of pregnancy and placental weight. These associations are mainly explained by deranged intake of nutrients acting as cofactors in the one-carbon metabolism during the periconception period (1). This pathway is essential for cellular biosynthesis and DNA repair and methylation, and any disturbance results in overwhelming oxidative stress, inflammation, apoptosis, and abnormal chromatin methylation. In this context, early one-carbon derangements, objectified by increased maternal plasma total homocysteine and decreased red blood cell folate and serum vitamin B12 concentrations, has been related to decreased trajectories of embryonic growth and morphological development, increased incidence of congenital anomalies and abnormal placentation, with evident placental insufficiency in the second half of pregnancy (2,11). All of these events finally lead to increased risks of hypertensive disorders, intrauterine growth restriction, and preterm birth, with cardiovascular and metabolic effects in childhood and adult life. These studies also underline

Summary 5 Periconceptional maternal environment Age Gender male Folic acid (RBC, tablet) Black ethnic origin High fish and olive oil, low meat DP High vitamin B12

Alcohol use Smoking CV risk profile High Hb/Hct High tHcy

First trimester growth trajectories

Pregnancy outcome

Non-communicable disease

Fetal growth-SGA preterm birth

Figure 1.2  Maternal exposures and characteristics associated with first trimester embryonic growth. The red and green arrows, respectively, indicate maternal exposures and characteristics negatively and positively associated with first trimester crown-rump length. Reduced embryonic growth has been further associated with the risk of small for gestational age (SGA) and preterm birth and with increased risk of chronic diseases in later life. (CV, cardiovascular; Hb, hemoglobin; Hct, hematocrit; RBC, red blood cell; tHcy, total homocysteine; DP, dietary pattern.) another crucial achievement of recent research: although the reproductive outcome of the periconceptional period (e.g., fertility, miscarriage, congenital malformations) is universally known to be strongly associated with maternal environment and exposures (e.g., folic acid supplementation, smoking habit, alcohol use), further strong associations have been recently detected between maternal nutrition, lifestyle, and first trimester embryonic growth, reversing the idea that embryonic development must be independent on external stimuli and constant in every woman and in every pregnancy (Figure 1.2). Moreover, impaired first trimester embryonic growth has been associated with increased risks of adverse pregnancy outcome and noncommunicable disease in later life, further underlining the importance of periconceptional care and early interventions. PLACENTAL ROLE

The placenta is a unique organ that represents an indispensable link between the mother and the fetus. How the human placenta and the fetus can lead to the maternal adaptation to pregnancy as described is still an open question. Recently, the release of membrane vesicles has been given a crucial role as an important mediator of intercellular communication. With regard to pregnancy, several studies showed that the placenta can release extracellular vesicles into maternal circulation as early as 6 weeks of gestation (28,29). Circulating vesicles, classified as microvesicles and exosomes, contain signaling molecules (RNAs and proteins) that are representative of the placental origin. Due to the capability of transferring their contents to specific target cells, placental exosomes can finally modulate the biological function of the target tissue leading to maternal (mal)adaptation during pregnancy (29). In normal pregnancies, embryonic and placental exosomes

were shown to induce maternal immunotolerance by enhancing T-cell apoptosis and reducing effector T cells (30). Moreover, exosomes released from metabolically active tissues, including the placenta, could finally initiate metabolic reprogramming in the end target tissue. This represents a potential platform for maternal metabolic modifications eventually leading to disease if disrupted (e.g., gestational diabetes mellitus) (Figure 1.3). Although exosomes are constitutively produced from cells, pathological conditions and the microenvironment of the parent placental cell (e.g., hypoxic or lipogenic) can modulate exosome biogenesis, molecule content, and release. Furthermore, a strong association between the concentration of placental exosomes in maternal blood and the incidence of pregnancy complication, such as gestational diabetes mellitus or preeclampsia, has been detected. As most pregnancy complications seem to originate from the very first stages of pregnancy, during the periconceptional period, then becoming evident only in the second half of pregnancy when usually no or few therapies—except delivery—are available, a growing body of studies is now focusing on the research of early markers of embryo-placental dysfunction, in order to develop successful prevention strategies. If this is the case, early modifications in the profile of placentaderived biomarkers could represent a useful instrument to identify early maladaptation in asymptomatic women and patients at risk of pregnancy complications. SUMMARY

The periconceptional period is pivotal for a healthy start of pregnancy. Maternal adaptations begin at conception and determine changes that lead to appropriate placenta development and availability of nutrients to the fetus. When these changes are not adequate, both hypertensive

6  The mother Microvescicles CCV

RNA and proteins

Early endosome

Golgi MVE

ER

Exosomes

Lysosome MVE

Metabolic reprogramming

Figure 1.3  Placenta-maternal intercommunication for maternal adaptation and metabolic reprogramming. Placental role on physiological and pathological maternal adaptations to pregnancy. Starting as early as the periconceptional period, the placenta releases microvesicles and exosomes, containing RNA and proteins, into the maternal circulation. Such molecules finally modulate DNA expression of target tissues, supporting organic and functional maternal changes (e.g., immunotolerance, metabolic or cardiovascular changing).

disorders as well as gestational diabetes may occur in the second half of pregnancy. Long-term effects in the offspring have been associated with inappropriate maternal adaptation to pregnancy. REFERENCES

1. Steegers-Theunissen RP et al. Hum Reprod Update. 2013;19(6):640–655. 2. Reijnders IF et al. Hum Reprod Update. 2019;25(1):​ 72–94. 3. Armaly Z et al. Front Physiol. 2018;9:973. 4. Troiano NH. AACN Adv Crit Care. 2018;29(3):273–283. 5. De Haas S et  al. Ultrasound Obstet Gynecol. 2017;50(6):683–696. 6. Meah VL et al. Heart. 2016;102:518. 7. Lang RM, Borow KM. Heart disease. In: Barron WM, Lindheimer MD, eds. Medical Disorders During Pregnancy. St. Louis MO: Mosby Year Book; 1991:184. 8. Ferrazzi E et  al. Am J Obstet Gynecol. 2018;218: 124.e1–124.e11. 9. Melchiorre K et al. BJOG. 2013;120:496–504. 10. Jauniaux E, Burton GJ. Early Hum Dev. 2007;83:699–706. 11. Parisi F et al. Fertil Steril. 2017;107(3):691–698.e1.

12. Di Cianni G et  al. Diabetes Metab Res Rev. 2003;19:259–270. 13. Murphy SP, Abrams BF. Am J Public Health. 1993;83:1161–1163. 14. Sitruk-Ware R. Steroids. 2000;65:651–658. 15. Catalano PM et  al. Am  J Obstet Gynecol. 1991;165:1667–1672. 16. Phelps RL et al. Am J Obstet Gynecol. 1981;140:730–736. 17. Freinkel N. Diabetes. 1980;29(12):1023–1035. 18. Zhandong Z et al. Ann Nutr Metab. 2017;70:59–65. 19. Weir GC et al. Diabetes. 2001;50(suppl 1):S154–159. 20. Lappas M. Metabolism. 2014;63:250–262. 21. Ashcroft FM et al. Cell Metab. 2017;26:17–23. 22. Kautzky-Willer A et al. Diabetes. 2003;52:244–251. 23. Forbes S et al. Diabetologia. 2011;54:641–647. 24. Ramsay JE et al. J Clin Endocrinol Metab. 2002;87:4231. 25. Delhaes F et al. Placenta. 2018;69:118. 26. Cetin I et al. J Dev Orig Health Dis. 2012;3:409–414. 27. Scifres CM et  al. J Clin Endocrinol Metab. 2011;96(7):E1083–E1091. 28. Gangoda L et al. Proteomics. 2015;15:260–271. 29. Salomon C, Rice GE. Prog Mol Biol Transl Sci. 2017;145:163–179. 30. Gercel-Taylor C et  al. J Reprod Immunol. 2002;56:​ 29–44.

Maternal and fetal normal and abnormal nutrition

2

SARAH LOUISE KILLEEN, EILLEEN C. O’BRIEN, and FIONNUALA M. McAULIFFE

INTRODUCTION

Good maternal nutrition throughout pregnancy provides a supportive environment for fetal growth and development. Maternal dietary intake is a modifiable risk factor for pregnancy-related complications and is therefore an important consideration in the management of pregnant women. In addition to pregnancy and infant outcomes, maternal nutrition can influence the health and development of offspring from childhood into adulthood, as well as the future health of the mother (­1­–5). Good maternal nutrition can be defined as a diet that meets macronutrient and micronutrient requirements in pregnancy through the consumption of high-quality/ bioavailable foods in the right proportions. DIETARY REQUIREMENTS

Macronutrients Macronutrient requirements increase in pregnancy to support fetal development and tissue deposition. In the first trimester, this increase is only marginal, and during this time, pregnant women should focus on following general healthy eating guidelines (6). Sufficient, but not excessive, energy intake is essential for a healthy pregnancy and appropriate gestational weight gain (GWG). Basal metabolic rate has been shown to increase by 5%, 11%, and 25% in trimesters 1, 2, and 3, respectively (7). This increases energy requirements by approximately 85, 285, and 475 kcal/day during the first, second, and third trimesters, respectively; however, this will depend on individual factors, including pre-pregnancy weight, age, and physical activity (8,9). Women carrying twins or adolescent mothers may have even greater energy requirements (10,11). The ratio of macronutrients contributing to total energy intake should not change in pregnancy, except in the case of an unbalanced pre-pregnancy diet. There is a moderate increase in carbohydrate requirements in pregnancy of approximately 45 g per day (6). Protein requirements are increased by approximately 1, 9, and 31 g per day for the first, second, and third trimesters (8). While the recommendations for dietary fat are unchanged in pregnancy compared to healthy eating guidelines, the importance of polyunsaturated fatty acids (PUFAs) should be highlighted as PUFA status declines during pregnancy and is essential for fetal neurological and eye development (6). Adequate intake can be achieved through the consumption of oily fish once to twice a week. More frequent consumption should be avoided to limit methyl mercury and polychlorinated biphenyls that

may harm fetal development. Despite this, women should be discouraged from avoiding fish altogether as non– fish eaters may have increased risk of low birth weight (LBW) infants, and intake of fish once to twice a week has been shown to be safe (6,13). In fact, omega-3 PUFA supplementation has been shown to reduce the incidence of preterm birth, although it may increase the incidence of postterm pregnancies (14). An unbalanced diet can be characterized by inadequate or excessive intakes of different nutrients that may have negative impacts on health. This may be of concern among women with obesity, who may be paradoxically malnourished in the context of overnutrition due to the consumption of energy-dense but nutrient-poor diets (15). Obesity has also been shown to be negatively associated with maternal iron, vitamin B12, and folate status (16,17). In addition, obesity negatively impacts on circulating vitamin D levels as vitamin D is a fat-soluble vitamin and is sequestered by adipose tissue. This means that pregnant women with obesity may have lower vitamin D status despite higher dietary intakes. Micronutrients While there is some physiological adaption that occurs in pregnancy to maintain nutritional status (e.g., increased intestinal absorption of nutrients), inadequate dietary intake during pregnancy may lead to inadequate nutrient provision to the growing fetus as micronutrients are transferred across the placenta. Alternatively, maternal nutrient stores may be depleted to ensure adequacy for the growing fetus, which negatively impacts on maternal health. Certain nutrients are at greater risk of this due to variance in transfer mechanisms. Micronutrients of concern in pregnancy include iron, folic acid, iodine, vitamin B12, vitamin D, calcium, and zinc (6). It is thus not surprising that multiple micronutrient supplements, which provide a variety of key nutrients at the Recommended Dietary Allowance (RDA) level, have been shown to be superior to single-nutrient supplements in the prevention of pregnancy-related complications (18). Table 2.1 gives details of recommended nutrient intakes for pregnant women (19,20). Iron requirements increase during pregnancy by up to 50%, and despite physiological adaptations to maintain iron status, iron deficiency is common, with 38% of pregnant women affected worldwide (6,21). Cessation of menstruation helps maintain iron stores during the first trimester of pregnancy; however, blood volume and red blood cell mass increase from mid-pregnancy to 7

8  Maternal and fetal normal and abnormal nutrition

Table 2.1  Recommended micronutrient intakes for pregnant women Micronutrient

Amount/day

Vitamin A Thiamine Riboflavin Niacin Vitamin B6 Biotin Folate Vitamin B12 Vitamin C Vitamin D Vitamin E Calcium Choline Copper Iodine Iron Selenium Zinc

750–800 µg 1.4 mg 1.4 mg 18 mg 1.9 mg 30 µg 400–600 µg 2.6 µg 55 mg 5–15 µg 15 mg 1000–1300 mg 450 mg 1–1.15 mg 220–250 µg 27 mg 30–60 µg 10–12 mg

Source: Refs. 19, 20.

provide sufficient oxygen to support fetal growth, and this increases iron requirements (21). Insufficient intake can lead to maternal anemia that in severe cases can increase the risk of mortality during childbirth (22). Women who have low habitual intake of bioavailable heme dietary sources (red meat, oily fish, and dark poultry meat) may benefit from supplementation with low-dose iron (e.g., 16–20 mg/day); in the case of maternal anemia, high-dose supplementation will be essential to replete iron stores (e.g., 100–200 mg elemental iron per day) (23). Calcium is integral to bone and teeth and account for 99% of total calcium stores. Approximately 30 g of calcium is accreted by the fetus during pregnancy, mostly during the third trimester. Due to physiological adaptations in intestinal absorption, calcium requirements are not increased in pregnancy; however, in the event of inadequate dietary intake, maternal bone mineral will be resorbed so that fetal calcium requirements are met (24). Therefore, adequate daily intake should be encouraged in all pregnant women, which can be achieved through dairy products or fortified alternatives. Calcium intake is also inversely related to blood pressure in pregnancy as it is involved in vasoconstriction and dilation. Therefore, calcium supplementation in pregnant women with habitually low calcium intakes may reduce the risk of hypertensive disorders of pregnancy and associated conditions. This, however, may have negative impacts on maternal bone mineral content (6,25). In addition, vitamin D is essential for calcium absorption (26). Maternal vitamin D deficiency may lead to abnormal bone health in the newborn, LBW, hypocalcemia, and potentially, cardiac failure (6,27). Dietary sources of vitamin D are limited to oily fish, meat,

eggs, dairy products, and fortified foods. Inadequate dietary intake is common in pregnancy (28). This means that routine supplementation to avoid deficiency is advisable, especially for women who are not exposed to sufficient ultraviolet (UV) rays to support endogenous production (6). Maternal folate deficiency can have detrimental effects on fetal development, increasing the risk of neural tube defects (NTDs), including spina bifida and anencephaly (29). An adequate intake of folic acid successfully prevents NTDs; however, as pregnant women are unlikely to meet their folic acid requirements through diet alone, supplementation of 400 µg per day is recommended for all women preconception and in their first 12 weeks of pregnancy (30). Maternal obesity is a risk factor for NTDs, and as obese women may have lower serum vitamin B12 and folate levels during pregnancy compared to mothers with a healthy weight, they may need even greater folic acid supplementation as well as vitamin B12 (16,31). In addition, megaloblastic anemia can occur because of prolonged inadequate folic acid or vitamin B12 intake (32). Women who enter pregnancy with low iodine stores are at risk of hypothyroidism that is associated with neurodevelopmental delay in offspring (6). Insufficient intakes have been reported in pregnant populations (33–35). Therefore, the need for supplementation should be assessed early in pregnancy, especially in areas where noniodized salt is consumed, where there is low intake of seafood or dairy products, or in locations where there is known iodine deficiency (6). In addition, selenium is essential for fetal growth, thyroid metabolism, and the prevention of oxidative stress. Insufficiency may be associated with preeclampsia and gestational diabetes mellitus (GDM) as well as loss of pregnancy (36). Women with protein-energy malnutrition or poor dietary quality may be at risk of zinc deficiency, and zinc requirements increase by up to 40% in pregnancy. Zinc is essential for fetal growth, immune function, and neurological development. Supplementation in highrisk populations has been shown to reduce the risk of preterm birth and increase birth weight (37). In certain countries, vitamin A deficiency affects pregnant women and is associated with abnormal fetal development, preterm birth, and maternal mortality, among other outcomes. Conversely, vitamin A is teratogenic (e.g., increasing risk of craniofacial and heart defects), and in areas where vitamin A deficiency is uncommon, excessive consumption should be avoided through limiting rich sources such as liver and using pregnancy-specific micronutrient supplements (6). MATERNAL WEIGHT AND GESTATIONAL WEIGHT GAIN

Body mass index (BMI) during early pregnancy can be used to identify women who are at increased risk of pregnancy complications such as GDM, preeclampsia, and cesarean section. Maternal BMI is closely associated with intrauterine growth and birth weight. Up to a quarter of pregnant

Other nutritional considerations  9

women in the United Kingdom are obese at conception, and the prevalence of obesity is rising worldwide (6,38). Obesity and excessive GWG increase the risk of delivering large for gestational age infants, which increases the risk of delivery complications (39). In addition to macrosomia, maternal obesity increases the risk of adverse outcomes for the fetus, including congenital abnormalities and preterm birth. Conversely, women who are undernourished during pregnancy have an increased risk of delivering a small for gestational age infant. They also have diminished energy reserves and may have suboptimal status of one or more key micronutrients needed to support healthy fetal development (6). In fact, women who enter pregnancy with an underweight or overweight BMI have higher incidence of spontaneous abortion (40). Therefore, women should have their BMI calculated at their first antenatal visit and be provided with advice on appropriate GWG rather than weight loss. While there is no international consensus on appropriate GWG, the Institute of Medicine guidelines are commonly used; however, these are based on prospective studies in high-income countries, so they may not be applicable to all women (6). In the first trimester of pregnancy, very modest weight gain is expected, which may range between 1 and 3 kg for all women except those who are obese, in which case a smaller weight gain of 0.2–2 kg is recommended (41). As outlined in Table 2.2, the bulk of GWG is expected in the second and third trimesters, and levels of GWG vary depending on maternal pre-pregnancy BMI. Women who gain weight within these ranges have better pregnancy outcomes; however, most women gain weight outside of these recommendations (42). A recent Cochrane review found high-quality evidence that dietary intervention (with or without exercise) can reduce the risk of excessive GWG. Dietary interventions include low glycemic index diet, energy restriction, or reducing fat (43). Alternatively, to encourage sufficient weight gain in mothers who are malnourished, antenatal nutritional education to increase energy and protein intake can be provided and has been shown to reduce the risk of preterm birth and LBW (44).

Table 2.2  Institute of Medicine guidelines for gestational weight gain Pre-pregnancy nutritional status (body mass index [kg/m2]) Underweight (200 mg/day) should be avoided in pregnancy as it may have teratogenic effects and has been associated with adverse birth outcomes (12). CONCLUSION

Maternal nutrition is a modifiable risk factor for both immediate and long-term health outcomes and is an important consideration in the management of pregnant women. As many nutritional requirements increase during pregnancy, mothers are at risk of deficiencies. Equally, excess of certain nutrients should be avoided due to potential teratogenic effects, dietary imbalance, and excess GWG. Therefore, maternal nutrition should be assessed in all pregnant women and appropriate interventions employed to promote the health of the mother and offspring and prevent pregnancy-associated complications. REFERENCES

1. Grandy M et  al. J Matern Fetal Neonatal Med. 2018;31(12):1613–1619. 2. Geraghty AA et al. Br J Nutr. 2018;120(11):1252–1261. 3. Mandy M, Nyirenda M. Int Health. 2018;10(2):66–70. 4. Barker DJ, Thornburg KL. Clin Obstet Gynecol. 2013;56(3):511–519. 5. O’Brien EC et  al. BJOG. 2018;126(4). https://doi. org/10.1111/1471-0528.15500 6. Hanson MA et  al. Int J Gynaecol Obstet. 2015;​ 131(suppl 4):​S213–S253. 7. Butte NF, King JC. Public Health Nutr. 2005;8(7A):​ 1010–1027. 8. Joint WHO/FAO/UNU Expert Consultation. World Health Organ Tech Rep Ser. 2007;(935):1–265, back cover. 9. Butte NF et  al. Am J Clin Nutr. 2004 Jun;79(6):​ 1078–1087. 10. Gandhi M et al. Am J Clin Nutr. 2018;108(4):775–783. 11. Sally EOF et al. Clin Nutr ESPEN. 2018;27:134–136. 12. Chen LW et al. Am J Clin Nutr. 2018;108(6):1301–1308. 13. Taylor CM et  al. Int J Hyg Environ Health. 2016;​ 219(6):513–520. 14. Middleton P et  al. Cochrane Database Syst Rev. 2018;11:CD003402. 15. Dubois L et al. Br J Nutr. 2018;120(3):335–344.

16. O’Malley EG et al. Eur J Obstet Gynecol Reprod Biol. 2018;231:80–84. 17. Flynn AC et al. Nutrients. 2018;10(8). 18. Haider BA, Bhutta ZA. Cochrane Database Syst Rev. 2017;4:CD004905. 19. Institute of Medicine. Dietary Reference Intakes: The Essential Guide to Nutrient Requirements. Washington, DC: National Academies Press; 2006. 20. WHO Guidelines Approved by the Guidelines Review Committee. Essential Nutrition Actions: Improving Maternal, Newborn, Infant and Young Child Health and Nutrition. Geneva, Switzerland: World Health Organization; 2013. 21. Bothwell TH. Am J Clin Nutr. 2000;72(suppl 1):​ 257S–264S. 22. Daru J et al. Lancet Glob Health. 2018;6(5):e548–e554. 23. Pavord S et al. Br J Haematol. 2012;156(5):588–600. 24. Kovacs CS. Physiol Rev. 2016;96(2):449–547. 25. Hofmeyr GJ et  al. Cochrane Database Syst Rev. 2018;10:CD001059. 26. Rosen CJ et al. Endocr Rev 2012;33(3):456–492. 27. Maiya S et al. Heart 2008;94(5):581–584. 28. McGowan CA et  al. Eur J Clin Nutr 2011;65(9):​ 1076–1078. 29. Greene ND, Copp AJ. Annu Rev Neurosci. 2014;​ 37:221–242. 30. Liu J et al. Nutr J. 2018;17(1):115. 31. McMahon DM et  al. Birth Defects Res A Clin Mol Teratol. 2013;97(2):115–122. 32. Rae PG, Robb PM. J Clin Pathol. 1970;23(5):379–391. 33. Brantsæter AL et al. Nutrients. 2013;5(2):424–440. 34. Pettigrew-Porter A et al. Aust NZ J Obstet Gynaecol. 2011;51(5):464–467. 35. Limbert E et al. Eur J Endocrinol. 2010;163(4):631–635. 36. Mistry HD et  al. Am J Obstet Gynecol 2012;​ 206(1):21–30. 37. Ota E et  al. Cochrane Database Syst Rev. 2015;(2):​ CD000230. 38. Devlieger R et al. Eur J Obstet Gynecol Reprod Biol. 2016;201:203–208. 39. Walsh JM, McAuliffe FM. Best Pract Res Clin Obstet Gynaecol. 2015;29(1):63–78. 40. Pan Y et al. BMJ Open. 2016;6(6):e011227. 41. Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines; Rasmussen KM, Yaktine AL. Weight Gain During Pregnancy: Reexamining the Guidelines. The National Academies Collection: Reports funded by National Institutes of  Health. Washington, DC: National Academies Press; 2009. 42. Siega-Riz AM et  al. Am J Obstet Gynecol. 2009;​ 201(4):339.e1–14. 43. Muktabhant B et al. Cochrane Database System Rev 2015;(6):CD007145. 44. Ota E et  al. Cochrane Database Syst Rev. 2015;​ (6):CD000032.

References 11

45. Hay WW Jr. Trans Am Clin Climatol Assoc. 2006;117:321–339; discussion 339–340. 46. Metzger BE et al. (HAPO Study Cooperative Research Group). N Engl J Med. 2008;358(19):1991–2002. 47. Riskin-Mashiah S et  al. Diabetes Care. 2009;32(9):​ 1639–1643. 48. Gadgil MD et  al. J Womens Health (Larchmt). 2018;28(2):178–184. 49. Walsh JM et al. BMJ. 2012;345:e5605. 50. Walsh JM et al. Reprod Sci. 2014;21(11):1378–1381. 51. Tieu J et  al. Cochrane Database System Rev 2017;​ (1):CD006674.

52. Guo XY et al. BJOG. 2019;126(3):311–320. 53. Kennelly MA et al. Obstet Gynecol. 2018;131(5):818–826. 54. Han S et  al. Cochrane  Database System Rev 2017;(2):CD009275. 55. Hernandez TL et  al. Diabetes Res Clin Pract. 2018;145:39–50. 56. Bustos M et al. Auton Neurosci. 2017;202:62–72. 57. Yoon CK et  al. Korean J Ophthalmol. 2005;19(3):​ 239–242. 58. London V et al. Pharmacology. 2017;100(34):161–171. 59. Lumish RA et al. J Nutr. 2014;144(10):1533–1539. 60. Roy A et al. Appetite. 2018;120:163–170.

Great obstetrical syndromes It’s all in the placenta

3

MARTIN GAUSTER and GERNOT DESOYE

INTRODUCTION

The term “great obstetrical syndromes” was coined about a decade ago (1). It describes conditions that have multiple etiologies and result from maternal-fetal interactions involving the genome and the environment. The most frequent obstetrical syndromes as they were understood earlier are fetal growth restriction and preeclampsia, both rooted in problems with placentation and trophoblast invasion, biological processes mainly of the first trimester of pregnancy (2). Less common are preterm labor and preterm rupture of membranes as well as stillbirth. Later on, gestational diabetes mellitus (GDM) was also added to this list (3) because of the placental contribution to both the etiology of the maternal condition and fetal phenotype (4). Development of the fetoplacental unit in the first trimester of pregnancy has received attention because early placental changes may also have an effect on placental development later in pregnancy (5). In recent years, studies into the origins of these conditions have received attention, and attempts have been made to predict them and prevent them from occurring (6). Identification of early biomarkers has become one focus of clinical research (7,8). In this chapter, we discuss the biological processes involved in anchoring the fetoplacental unit in the uterus, the changes in the decidual arteries, and how a defect in any of these processes may lead to fetal growth restriction and preeclampsia. We further describe how the placenta may contribute to maternal metabolic changes underlying GDM and the placental involvement in phenotypic changes in the fetus. Implantation and trophoblast invasion In human pregnancy, embryo implantation is initiated by apposition of the blastocyst with its embryonic pole, bearing the inner cell mass, to the endometrial epithelium. While the inner cell mass gives rise to the embryo, the outer cell mass—referred to as trophoblast cells—forms the wall of the blastocyst, thus mediating initial adherence to the uterine wall and later forming the placenta. Apposition and adherence of the blastocyst are followed by intercellular fusion of trophoblasts that are in contact with the endometrial epithelium, to form the multinucleated syncytiotrophoblast (9). At that very early stage of embryo implantation, the syncytiotrophoblast is equipped with an enzymatic endowment that enables crossing of the endometrial epithelium and penetration of the underlying stroma. The endometrium from now on may be referred

12

to as decidua, which provides the breeding ground for the growing embryo and the developing placenta. Once the blastocyst has completely penetrated the decidua, the mass of syncytiotrophoblast rapidly increases by ongoing proliferation and fusion of underlying cytotrophoblasts. The syncytiotrophoblast forms a complete layer over the surface of the blastocyst, whereas the site at the implantation pole achieves considerable thickness and develops extensions that deeply invade the decidua. After implantation, primary placental villi, composed of a cytotrophoblast core with a covering of syncytiotrophoblast, are being developed (10). At the distal ends of the developing villi, cytotrophoblasts penetrate the syncytiotrophoblast and form cell columns, which attach the developing placenta to the decidua. With ongoing placentation, trophoblasts detach from cell columns, adopt an invasive phenotype, and invade as “extravillous trophoblasts” (EVTs), the decidual interstitium up to the first third of the myometrium. Previous, rather simplified dogmas suggest that EVTs invade the decidual interstitium with the aim to accumulate and form cellular plugs in decidual spiral arteries, where they obstruct the maternal arterial blood flow into the intervillous space until the end of the first trimester of pregnancy. With disaggregation of trophoblast plugs at the end of the first trimester, maternal blood flow is initiated into the intervillous space. Recent microanatomical surveys on first trimester decidua basalis sections challenged this doctrine and extended the current view by showing extravillous trophoblast subpopulations in several luminal structures, including uterine spiral arteries, veins, glands, and to a minor extent, uterine lymphatic vessels (10–12). While the functional significance for invasion into lymphatic vessels remains unclear, arteries, veins, and glands have to be connected to the intervillous space to guarantee successful placentation. However, the type of invasion into arteries may differ compared to invasion into uterine veins and glands. According to a recent opinion, uterine veins and glands are invaded to be connected to the intervillous space of the placenta without a massive remodeling of their vessel walls (13). In contrast, spiral arteries are remarkably converted by EVTs, leading to depletion of smooth muscle cells in their walls and loss of their elastic lamina. The consequence of the spiral artery conversion is that distal segments of the vessels dilate and are converted into flaccid conduits (Figure 3.1a), enabling reduction of the velocity of incoming maternal blood and thereby preventing damage to delicate villous trees (14–16).

Introduction 13 (a)

(b)

Villous trees Intervillous space Maternal blood

Decidua Spiral artery

Remodeled spiral artery

Inadequate remodeled spiral artery

Figure 3.1  Consequences of inadequate spiral artery remodeling. In normal pregnancy, trophoblast invasion into the maternal decidua gives rise to conversion of distal segments of spiral arteries into widened conduits (a) Aberrant trophoblast invasion and inadequate spiral artery remodeling, with absence of any dilation at the distal ends of the arteries, leads to high-speed jets that enter the intervillous space (b). Consequences of inadequate invasion and spiral artery remodeling Many placenta-associated pregnancy complications, such as recurrent pregnancy loss, intrauterine growth restriction (IUGR), and preeclampsia, have been associated with aberrant conversion of the spiral arteries in the placental bed, which is the part of the uterine wall underlying the placenta. Recent computational modeling of flow in spiral arteries suggests that inadequate spiral artery remodeling and the absence of any dilation at the distal ends of the arteries gives rise to turbulent, very high speed jets that enter the intervillous space, which surrounds the chorionic placental villi (Figure 3.1b) (14). While these high-speed jets can nowadays be visualized reliably using pulsed-wave Doppler ultrasonography, computational models of blood flow from spiral artery openings suggest that jets of flow observed by ultrasound are likely correlated with increased porosity of the intervillous space near the opening of the spiral arteries (15). Accordingly, mega-jets, which penetrate more than half the placental thickness, may only be possible when spiral arteries open to regions of the placenta with very sparse villous structures (15). This assumption further suggests that the velocity of the incoming blood flow from converted spiral arteries influences development and architecture of villous trees. The turbulent blood flow, including high-velocity jets and vortices combined with elevated blood pressure in the proximal intervillous space may contribute to an increased wall shear stress at the villous surface. Increased shear stress at the villous surface has been associated with elevated trophoblast shedding, as observed in an in toto embedded IUGR placenta. Histological examinations revealed potential villous damage, which appeared as cytokeratinpositive particles in the intervillous space, but in a more

pronounced way in veins of intercotyledonary septa that drain the intervillous space (16). Inadequate spiral artery remodeling may be the result of both shallow invasion and a reduced number of invaded trophoblasts. This assumption is based on numerous histological surveys on hysterectomy and postmortem specimens of uteri with in situ placentas as well as placental bed biopsies, consisting of both decidual and myometrial tissue. Among such studies, severely impaired trophoblast invasion has been shown in fullthickness uterine wall samples obtained from early onset preeclamptic pregnancies combined with intrauterine growth restriction (17). However, the detailed underlying mechanisms, regulating EVT invasion in vivo and how EVTs enable the extensive remodeling of the, in total, approximately 30–60 spiral arteries of the placental bed, remain largely unknown. In recent years, maternal immune cells such as uterine natural killer cells and macrophages have been suggested as key regulators of both EVT invasion and spiral artery remodeling in the placental bed (18,19). A plethora of soluble factors, including cytokines, chemokines, and growth factors, is secreted from decidual macrophages and stromal cells, as well as uterine natural killer cells and even uterine glandular epithelial cells. A balanced cocktail of these factors may drive initial proliferation of trophoblast cell columns and subsequent detachment and invasion of EVTs into the placental bed (20). Moreover, these factors could regulate recruitment of macrophages and natural killer cells as well as other less abundant immune cells into the placental bed. At the same time, decidual stroma cells are suggested to secrete some anti-invasive factors that might be essential to counteract the effects

14  Great obstetrical syndromes

of invasion-promoting factors and restrain exaggerated invasion. Thus, the decidua may provide a timely, balanced production of invasion promoting and inhibiting factors enabling a well-coordinated EVT invasion (21). Beside high-velocity jets, fluctuations in placental oxygen concentrations resulting from intermittent perfusion of the intervillous space are currently discussed as a consequence of inadequate spiral artery remodeling (22). While fluctuations in intervillous blood flow can be explained by periodic vasoconstriction of spiral arteries that might even occur during normal human pregnancies, it seems reasonable that such events occur more frequently and more pronounced in placental beds with less remodeled spiral arteries, due to the preservation of smooth muscle within their distal ends. The consequence of such fluctuations may be a decreased oxygen tension within the affected area, which probably could not be compensated by supply from adjacent spiral arteries. However, when vasoconstriction of spiral arteries declines, inflow in the intervillous space is restored, and the local oxygen tension steeply rises. Importantly, such fluctuations in oxygen tension are associated with an ischemia-reperfusion type of injury, which is well documented for other organs such as heart and brain (22). Ischemia-reperfusion generates high concentrations of reactive oxygen species (ROS), which in turn exert cytotoxic effects on the exposed syncytiotrophoblast, giving rise to placenta-associated pregnancy pathologies. In line with this assumption, recent analysis of stress-signaling pathways in placental tissues from complicated pregnancies together with in  vitro experiments with trophoblasts suggest that placental oxidative stress may contribute to the pathophysiology of early onset preeclampsia and IUGR (23). GESTATIONAL DIABETES MELLITUS: ROLE OF THE PLACENTA

GDM is a condition of hyperglycemia in the mother because of maternal ß-cell failure to compensate insulin resistance. Insulin resistance is a physiological condition in the second

half of pregnancy in order to facilitate maternal catabolism to provide macronutrients for the fetus to sustain its growth. In normal pregnancies, this is accompanied by an increase in fasting insulin levels rising between weeks 25 and 33 of pregnancy (24), a result of structural, i.e., increasing ß-cell mass with progressing gestation (25), and functional changes of the pancreatic islets (26). If the degree of insulin resistance exceeds ß-cell capacity to mount adequate responses, i.e., release more and enough insulin to achieve the same effect as in the absence of insulin resistance, then GDM ensues (27). In many instances, the ß-cell defect is already present before pregnancy (28), and pregnancy only unmasks this defect. However, in a subgroup of GDM women, mostly obese women, ß-cell function is inadequate only temporarily during pregnancy. Insulin resistance can already be present early in gestation. If associated with hyperglycemia, then maternal risk for later GDM development increases (29). In obese women, a considerable proportion (23%) is already insulin resistant around week 15 of pregnancy (30). This requires ß-cell adaptation beyond that of a pregnancy that begins without insulin resistance. Both insulin resistance and ß-cell adaptation in pregnancy are, among others, determined by placental hormones (31). Among these, human placental lactogen (hPL), the placental variant of human growth factor (hGH-V), and human chorionic gonadotropin (hCG) have received the most attention, although others such as hepatic growth factor, leptin, and kisspeptin may also play a role (32) (Figure 3.2). Many of the studies have been conducted in rodent models and may have limited validity for humans because of distinct species differences in islets and ß-cells (33) as well as in lactogenic hormones and their receptors (34). Evidence in humans is less convincing, but recent studies using human material have also supported the role of placental peptides and hormones to facilitate islet and ß-cell adaptation to pregnancy (32,35,36). Placental lactogen was among the first candidate regulators of islet adaptation in pregnancy (37). In vitro experiments using human pancreatic ductal cells and

Placental hormones

hGH-V Leptin

hPL HGF

Maternal changes

Insulin resistance

β-cell expansion

hCG Kisspeptin Leptin

Pancreas Insulin release

Metabolic (glucose) homeostasis

Figure 3.2  Hypothesized role of placental hormones in regulating maternal (glucose) homeostasis. Several placental hormones and peptides are involved in establishing physiologic maternal insulin resistance and pancreatic changes characteristic of the catabolic phase in the second half of pregnancy. Any homeostatic dysregulation reflected by augmented insulin resistance vis-à-vis inadequate pancreatic adaptation or ß-cell compensation, respectively, contributes to GDM.

Fetus in GDM: Role of the placenta  15

islets demonstrated the potency of hPLs in stimulating dedifferentiation of ductal cells into pancreatic islets, to promote ß-cell survival, and to potentiate glucosestimulated insulin secretion (35,36). Most clinical studies have failed to associate hPL levels with GDM risk, although the placenta produces more hPL mRNA in more severe forms of GDM, i.e., those requiring management by medication (38). However, serum levels of hPL were not different between GDM and controls (39). Leptin transcriptionally represses insulin in human pancreatic islets outside pregnancy (40). It is produced and secreted not only by adipose tissue, but also by the placenta, contributing to increasing leptin levels in pregnancy (41), which is a state of maternal hyperleptinemia (42), and also to the higher circulating levels in GDM pregnancies (43). Although its main function is to regulate appetite/ satiety, leptin may also contribute to reducing pancreatic synthesis of insulin, although ß-cell leptin resistance has been proposed. Rather, leptin levels associate with insulin sensitivity indices (44). Recently, hCG has been demonstrated to regulate insulin release through hCG receptors on the ß-cells (45). hCG levels are routinely measured for aneuploidy screening in the late first trimester. In a recent meta-analysis of nine studies, first trimester multiples of median levels of the free hCG ß-subunit were lower in women later developing GDM (46). Hepatocyte growth factor is a cytokine produced by the human placenta in both trophoblast and endothelial compartments (47). Its higher placental levels in obesity (48) may have a positive effect on islet development, regeneration, and ß-cell expansion, on which its signaling receptor is located. The role of hepatocyte growth factor in human GDM pregnancies remains to be determined (32). Outside pregnancy, kisspeptin is a hypothalamic peptide and increases glucose-stimulated insulin secretion (49). During pregnancy, its circulating levels increase by 1000-fold, likely because of placental production (50,51). Kisspeptin levels are decreased in GDM (52), but its consequences for ß-cell function in GDM await clarification. Placental peptides and hormones not only affect the maternal pancreas but have also been implicated in the physiological changes of insulin resistance. Mouse studies have suggested a pronounced role of growth hormones. The pituitary is the prominent site of growth hormone production outside pregnancy. In pregnancy, the circulating levels of pituitary growth hormone (GHN) decline until mid-pregnancy. At the same time, concentrations of the growth hormone variant produced by the placenta (HG-V) begin to rise (53). Mice transgenic for HG-V show severe insulin resistance, and continuous GH-V administration of higher HG-V doses reduced insulin sensitivity (54,55). In in vitro studies using human placental models, both glucose as well as insulin inhibited HG-V secretion and production, respectively, suggesting a maternal-placental regulatory loop (56,57). Although GH-V levels are associated with maternal glycemia in type 1 and type 2 diabetes mellitus (58), no such associations

were found in GDM (53). Also, placental GH-V expression was not affected by GDM (59). There may be several reasons for the discrepancy between in vitro effects of single hormones and the results of clinical studies: (1) conditions and designs of the in vitro experiments do not reflect the in vivo situation; (2) in vivo effects comprise the whole endocrine/paracrine system, and effects of each hormone may not be additive, but competitive; and (3) pancreatic function is already impaired before pregnancy and cannot be adequately changed for the benefit of maintaining homeostasis within pregnancy. FETUS IN GDM: ROLE OF THE PLACENTA

The main feature of neonates born to GDM pregnancies is their higher adiposity. Many decades ago, Jorgen Pedersen put forward his hyperglycemia-hyperinsulinemia concept (60), which posits maternal glucose and, subsequently, fetal insulin as main determinants of neonatal adiposity in GDM. Recently, a large cohort study including more than 23,000 pregnancies confirmed this concept and expanded it to a range of hyperglycemia short of GDM diagnosis (61). Fetal adiposity in GDM not only may be found at the end of gestation, but excess growth of fetal fat deposits may begin as early as at around week 17, when abdominal circumference is already higher in fetuses whose mothers will be diagnosed later with GDM (62). This suggests fetal hyperinsulinemia may already occur early on in pregnancy. If this were correct, then any derangement of maternal glucose homeostasis early in pregnancy may have consequences for fetal growth and development through the fetal glucose steal phenomenon (63). The early pregnancy period is also a key period for placental development (compare also the previous and [64]). Any alteration in trophoblast and placental growth as well as cellular differentiation may track until the end of pregnancy and contribute to excess neonatal adiposity (65,66). It is pertinent that in early pregnancy, maternal insulin may have a stimulatory role on placental growth (66), but this will be an indirect rather than a direct effect (67). At this time of gestation, placental insulin receptors are mainly located on the microvillous membrane of the syncytiotrophoblast exposing it to maternal insulin, whereas the proliferating cytotrophoblast is located subjacent to the syncytiotrophoblast and expresses very few, if any, insulin receptors. As gestation advances, the insulin receptor location shifts to become more prominent on the fetoplacental endothelium (68). This endothelium responds not only to insulin but also to other fetal signals that in their totality serve to facilitate placental adaptation to protect fetal development. Other examples of fetal signals are oxysterols, which result from oxidative cholesterol modification (69). The fetal signals for these responses may be generated before week 32 in pregnancy, at least for the often-found placental hypervascularization, as the placental surface area correlates with the day-to-day variation in maternal blood glucose levels only between weeks 12 and 32 of gestation and not thereafter (70).

16  Great obstetrical syndromes

The myriad of placental changes that have been found at the end of GDM pregnancies (71) mostly reflect these adaptive responses. A recently proposed concept posits that the protective role of the placenta will only be overwhelmed in more extreme conditions of metabolic perturbation and not in those seen in GDM, in which the mothers receive some form of management, either by advice for lifestyle changes or by medication (67).

In the years ahead, more information will be collected to help understand the specific mechanisms underlying GDM. Targeting placental hormones and peptides combined with early risk detection may offer an opportunity to prevent GDM. It is not difficult to predict that the first trimester of pregnancy will more and more become the focus of research (77).

OUTLOOK

1. Di Renzo GC. J  Matern Fetal Neonatal Med. 2009;22(8):633–635. 2. Brosens I et  al. Am J Obstet Gynecol. 2011;204(3):​ 193–201. 3. Gabbay-Benziv R, Baschat AA. Best Pract Res Clin Obstet Gynaecol. 2015;29(2):150–155. 4. Desoye G, van Poppel M. Best Pract Res Clin Obstet Gynaecol. 2015;29(1):15–23. 5. Desoye G, Hauguel-de Mouzon S. Diabetes Care. 2007;30(suppl 2):S120–S126. 6. Sweeting A et al. Best Pract Res Clin Obstet Gynaecol. 2015;29(2):183–193. 7. Sweeting AN et al. Diabetes Res Clin Pract. 2017;127:​ 44–50. 8. De Magistris A et al. Pediatr Endocrinol Rev. 2015;​ 13(2):546–558. 9. Benirschke K et al. Pathology of the Human Placenta. Heidelberg: Springer; 2012. 10. Moser G et al. Hum Reprod. 2015;30(12):2747–2757. 11. Moser G et al. Histochem Cell Biol. 2017;147(3):353–366. 12. Windsperger K et  al. Hum Reprod. 2017;32(6):​ 1208–1217. 13. Moser G et  al. Histochem Cell Biol. 2018;150(4):​ 361–370. 14. Burton GJ et al. Placenta. 2009;30(6):473–482. 15. Saghian R et al. J Biomech Eng. 2017;139(5):051001. 16. Roth CJ et al. Sci Rep. 2017;7:40771. 17. Kadyrov M et al. Am J Obstet Gynecol. 2006;194(2):​ 557–563. 18. Smith SD et al. Am J Pathol. 2009;174(5):1959–1971. 19. Veerbeek JH et al. Placenta. 2015;36(8):775–782. 20. Pollheimer J et al. Front Immunol. 2018;9:2597. 21. Sharma S et  al. Am J Reprod Immunol. 2016;75(3):​ 341–350. 22. Hung TH, Burton GJ. Taiwan J Obstet Gynecol. 2006;45(3):​189–200. 23. Yung HW et al. J Pathol. 2014;234(2):​262–276. 24. Desoye G et al. J Clin Endocrinol Metab. 1987;64(4):​ 704–712. 25. Hill DJ. Placenta. 2018;69:162–168. 26. Moyce BL, Dolinsky VW. Int J Mol Sci. 2018;19(11). 27. Buchanan TA, Xiang AH. J Clin Invest. 2005;115(3):​ 485–491. 28. Buchanan TA et  al. Nat Rev Endocrinol. 2012;​ 8(11):639–649. 29. Riskin-Mashiah S et  al. Diabetes Care. 2009;32(9):​ 1639–1643. 30. Harreiter J et al. Diabetes Care. 2016;39(7):​e90–e92.

In recent years, immense effort has been put into preeclampsia screening tests, which now are reported to predict the risk of the development of preeclampsia from as early as 11 weeks of gestation. On the basis of an algorithm, which incorporates maternal history, mean arterial blood pressure, uterine artery Doppler pulsatility index, and placental biomarkers, preeclampsia can be detected with 54% and early onset preeclampsia even with 96%, at a false-positive rate of 10% (72,73). While induction of labor and hence removal of the placenta seem to be the only way to treat preeclamptic symptoms at the moment, many trials have been conducted to test the effectiveness of cost-effective drugs such as heparin, vitamin D, or aspirin. Low-dose aspirin (4000  g (1,23), is also present in more than 10% of gestations (3), and it is associated with several delivery complications including birth trauma, shoulder dystocia, and perinatal asphyxia (3,24). Since a clear weight cut-off definition has not yet been established, a value independent of gestational age, such as LGA, has been proposed to define a birth weight associated with increased complications (3,25,26). However, both groups barely overlap, as LGA threshold falls far below the 4000 g depending on the gestational age selected. While this could lead to an increase in sensitivity, it also could be associated with a lower specificity and an increase in false-positive rates. Figure 4.2 illustrates the concept of macrosomia and LGA. Regarding management, once fetal macrosomia is suspected, an elective cesarean section can be done to avoid complications related to vaginal delivery. However, the number of interventions needed to prevent one complication makes this approach clinically and economically unsound (27). Recently, induction of labor for impending macrosomia has been proposed to prevent complications, without increasing the cesarean section and instrumental delivery rates (23). This has put the spotlight on improving prediction of excessive fetal weight or macrosomia before labor onset for proper counseling and decision-making.

Current screening strategies  19 6% SGA?

3

FGR 20

25

35

30

0 40

32w @diagnosis

Figure 4.1  Prevalence changes across pregnancy of early and late fetal growth restriction. Table 4.1  Differential features of early and late fetal growth restriction (FGR) Early FGR

Late FGR

Prevalence Challenge Clinical impact

0.5%–1% Management (gestational age at delivery) High mortality and morbidity

Evidence of placental disease

High 70% abnormal umbilical Doppler 60% association with preeclampsia Severe angiogenic disbalance Hypoxia ++ Systemic cardiovascular adaptation Low cardiac output High vascular resistance

Fetal hemodynamics Maternal hemodynamics

4500 4250 4000 3750 3500 Macrosomia

3250 LGA

3000 2750 2500

35

36

90th percentile

37

38

39

97th percentile

40 Macrosomia

Figure 4.2  Macrosomia and largeness for gestational age. FETAL GROWTH: A DYNAMIC PROCESS

Fetal growth is a complex and dynamic process that is heavily modulated by placental function, with the placenta serving the critical respiratory, hepatic, and renal functions of the fetus (1). As gestation advances, the capacity of the uteroplacental system to meet fetal demands gradually declines (28); in early stages, this dysfunction could not be enough to be reflected by Doppler parameters (29,30). However, mainly near term, it could be enough

5%–10% Detection and diagnosis Low mortality/morbidity + high prevalence = large etiological % of the adverse outcomes Low 32 weeks and a total of 6,835 SGA babies. Reported modeled sensitivities of AC and EFW 4000 g), including 63 diagnostic studies and a total of 19,117 women. It reported a summary receiver operating characteristic (sROC) curve with an area under the curve (AUC) of 87% and a detection rate of ∼60% for a 10% fixed rate of false positives (42,43). UNIVERSAL SCAN VERSUS SELECTIVE SCAN (BASED ON RISK FACTORS AND FUNDAL HEIGHT MEASUREMENT)

In the last years, several guidelines recommended against routine scan in the last third of pregnancy, mainly based on the results of a meta-analysis that showed no clear evidence of benefit (44). However, it could be argued that this conclusion is based on studies from almost 20 years ago, when expertise and technology were not valid in contemporary practice. Furthermore, many of the studies involved no change in management if a diagnosis of abnormal fetal growth was made, which again does not reflect current practice. Finally, almost 12% of the pregnancies were scanned before 34 weeks, when the diagnostic performance is poorer (45). More recently, a large prospective study (35) was published involving 3,977 nulliparous women, in which serial scanning was performed at 28, 32, and 36 weeks, and the results were concealed to participants and treating clinicians. This series reported that universal screening triples the detection rate of SGA as compared with screening based on clinical risk factors (from 69 [20%] of 352, to 199 [57%] of 352). Regarding LGA, results from the same study group (46) report that universal ultrasonography increased the detection of LGA infants (from 47 [27%] of 177, to 67 [38%] of 177). The importance of diagnosing late SGA relies on the fact that most instances of avoidable stillbirth and neonatal death are linked to failures in antenatal SGA detection (47,48). Thus, if nondetection of FGR carries an increased risk (21), and the best (yet with limitations) way to detect FGR is universal screening (35), it follows by syllogistic thinking that the best way to prevent adverse outcomes is universal screening. On the other side, induction of labor for suspected fetal macrosomia results in a lower birth weight and fewer birth

fractures and shoulder dystocia, without increasing the cesarean section and instrumental delivery rates (23). LONGITUDINAL VERSUS CROSS-SECTIONAL ULTRASOUND AS A SCREENING TOOL

A longitudinal approach has been proposed to be more appropriate because the progressive and dynamic nature of the condition is likely to be more amenable to be detected by serial assessments than by cross-sectional evaluation (49). To date, few studies have evaluated in the general population whether longitudinal assessment improves the identification of fetuses at risk for late-onset growth abnormalities and their related morbidity (50–54), reporting conflicting results. More recently, two studies conducted by our group focused on the performance of longitudinal growth assessment for the prediction of abnormal fetal growth in the general population. They showed that neither for SGA nor for LGA was the predictive performance of longitudinal assessment superior to a single cross-sectional evaluation at 32 weeks. Besides methodological issues, biologically, it could be speculated that although it seems intuitive that longitudinal assessment is more suitable to capture the dynamic nature of growth problems, what really determines the performance in predicting birth weight is the size achieved by the fetuses at term. Indeed, for clinically based outcomes (such as longterm cardiac [55–57] and neurological [58–62] outcomes or metabolic syndrome in childhood, linked to neonatal catch-up growth [63] and fetal overgrowth [10,64]) perhaps longitudinal growth assessment rather than size would have better performance. Moreover, taking into account that the mechanisms involved and conditions associated to FGR differ significantly from those involved in fetal overgrowth (i.e., macrosomia) (1), it could be proposed that a different approach should be considered for each outcome, perhaps through the combination of ultrasonic assessment of fetal growth with blood-specific biomarkers. NEONATAL VERSUS FETAL STANDARDS

When assessment of fetal growth is performed, there is wide consensus that the curves used must be fetal and not neonatal. This is especially true before 34 weeks, since the population of fetuses and neonates is very different, and it occurs because FGR is precisely a recognized risk factor of premature birth (even spontaneous) (65); therefore, pathologic conditions are overrepresented. It is known that the use of fetal versus neonatal curves allows the association between growth restriction and neonatal complications (66) to emerge clearly, as well as the association with longterm neurological sequelae (67). POPULATION-BASED VERSUS UNIVERSAL STANDARDS VERSUS CUSTOMIZED GROWTH ASSESSMENT

There is an ongoing controversy regarding the correct choice of fetal biometry chart for the assessment of fetal growth (14). On one hand, population-based fetal size references are created mainly from retrospective data sets and by nature are

References 21

descriptive; in other words, they show how the fetuses in the observed population grow. This could lead to confusion as different reference charts may report different percentiles for the same fetal measurement by differences in baseline risk between populations. Moreover, these references are skewed at the extremes of gestation where pathological conditions are concentrated, therefore rendering poor performance. In order to account for these limitations, prescriptive standards have been proposed, whereby only healthy fetuses (from uncomplicated pregnancies) are included, thus showing how a fetus should grow under optimal conditions. Under this assumption (endorsed by the World Health Organization for infant growth assessment), two different and mutually excluding premises could be followed: either we assume that one standard fits all pregnancies (i.e., the INTERGROWH21st premise) or we assume that one single standard does not fit all individuals or populations. This former concept has been challenged by recent series showing that it may misclassify a fraction of cases (68–73). Other studies, however, do support their assumptions and the validity of their approach (74–76). The latter is the main support of the concept of customization (77), which upholds that normal ranges of fetal weight are affected by constitutional variation and this needs to be adjusted for to improve the association between physiological and pathological variation. Compared with populationbased noncustomized reference charts, a customized chart will identify a different proportion of fetuses with abnormal growth at birth. This may be relevant by better capturing fetuses at risk of perinatal complications (78,79), but the benefit of such approaches over population-based charts has not been demonstrated in prospective studies. A NEW STRATEGY TO SCREEN?

Fetal size currently serves as a common clinical proxy for placental dysfunction and its assessment is an established part of antenatal care. Nonetheless, emerging data show consistently and convincingly that fetal arterial redistribution is associated more strongly than is fetal size with perinatal death at term. In that sense, cerebroplacental ratio (CPR) has been suggested as an independent indicator of significant growth restriction. However, it has been claimed that, even if CPR can be demonstrated to be a marker of placental insufficiency independent of size, the effectiveness of a strategy based on CPR assessment in the overall population is still to be proven (14). REFERENCES

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7. Chavkin U et al. J Matern Fetal Neonatal Med. 2019; 32(2):198–202. 8. Lindström L et al. Horm Res Paediatr. 2017;88(3–4):​ 215–223. 9. Katanoda K et al. J Epidemiol. 2017;27(9):428–434. 10. Boney CM. Pediatrics. 2005;115(3):e290–296. 11. Zhang J et  al. Am J Obstet Gynecol. 2010;202(6):​ 522–528. 12. World Health Organization. WHO Child Growth Standards and the Identification of Severe Acute Malnutrition in Infants and Children. Geneva, Switzerland: WHO; 2014. 13. Kuczmarski RJ et al. Adv Data. 2000;(314):1–27. 14. Ganzevoort W et al. Am J Obstet Gynecol. 2019;220(1):​ 74–82. 15. Figueras F et  al. Ultrasound Obs Gynecol. 2015;45:279–285. 16. Barker DJ. Clin Sci (Lond). 1998;95(2):115–128. 17. Godfrey KM, Barker DJ. Public Health Nutr. 2001;4(2B):611–624. 18. Figueras F, Gratacos E. Prenat Diagn. 2014;34(7):​ 655–659. 19. Barker ED et  al. Obstet Gynecol. 2013;122​(2 Pt  1):​ 248–254. 20. Lindqvist PG, Molin J. Ultrasound Obstet Gynecol. 2005;25(3):258–264. 21. Gardosi J et al. BMJ. 2013;346(January):f108. 22. Alfirevic Z, Neilson JP. Am J Obstet Gynecol. 1995;172(5):​1379–1387. 23. Boulvain M et  al. Cochrane Database Syst Rev. 2016;(5):CD000938. 24. Campbell S. Ultrasound Obstet Gynecol. 2014;43(1):​ 3–10. 25. Pasupathy D et  al. Paediatr Perinat Epidemiol. 2012;26(6):543–552. 26. Buck Louis GM et  al. Am J Obstet Gynecol. 2015;​ 213(4):449.e1–449.e41. 27. Rouse DJ et al. JAMA. 1996;276(18):1480–1486. 28. Cox LS, Redman C. Placenta. 2017;52:139–145. 29. Parra-Saavedra M et al. Placenta. 2013;34(12):​1136–1141. 30. Khalil A et al. Ultrasound Obstet Gynecol. 2016;47(1):​ 74–80. 31. Smith R et al. Placenta. 2013;34(4):310–313. 32. Tenenbaum-Gavish K, Hod M. Fetal Diagn Ther. 2013;34(1):1–7. 33. Bhattacharya S et al. BMC Public Health. 2007;7(1):​ 168. 34. Metzger BE et al. N Engl J Med. 2008;358(1533–4406):​ 1991–2002. 35. Sovio U et al. Lancet. 2015;386(10008):2089–2097. 36. Pedersen NG et  al. Obstet Gynecol. 2008;112(4):​ 765–771. 37. Grantz KL et al. Am J Obstet Gynecol. 2018;219:285. e1–285.e36. 38. Caradeux J et  al. Ultrasound Obstet Gynecol. 2018;52(3):​325–331. 39. Cavallaro A et  al. Ultrasound Obstet Gynecol. 2018;52(4):​494–500.

22  Normal and abnormal fetal growth

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60. Korzeniewski SJ et  al. Pediatrics. 2017;140(5):​ e20170697. 61. Muñoz-Moreno E et al. Front Neurosci. 2016;10:560. 62. Tanis JC et al. J Pediatr. 2015;166(3):552–558.e1. 63. Morrison JL et  al. Pediatr Nephrol. 2010;25(4):​ 669–677. 64. Gillman MW et al. Pediatrics. 2003;111(3):e221–e226. 65. Gardosi JO. Early Hum Dev. 2005;81(1):43–49. 66. Zaw W et al. Pediatrics. 2003;111(6 Pt 1):1273–1277. 67. Charkaluk M-L et al. J Pediatr. 2012;161(6):1053–1058. 68. Francis A et  al. Am J Obstet Gynecol. 2018;218(2):​ S692–S699. 69. Anderson NH et al. Am J Obstet Gynecol. 2016;214(4):​ 509.e1–509.e7. 70. Sletner L et al. Acta Obstet Gynecol Scand. 2018;97(2):​ 168–179. 71. Poon LCY et  al. Ultrasound Obstet Gynecol. 2016;48(5):​602–606. 72. Cheng Y et  al. BJOG An Int J Obstet Gynaecol. 2016;123:48–55. 73. Liu S et al. PLOS ONE. 2017;12(3):e0172910. 74. Stirnemann JJ et  al. Ultrasound Obstet Gynecol. 2017;49(4):487–492. 75. Bellussi F et al. Fetal Diagn Ther. 2017;42(3):198–203. 76. Villar J et  al. Am J Obstet Gynecol. 2018;218(2):​ S841–S854.e2. Available from: http://www.ncbi.nlm. nih.gov/pubmed/29273309 77. Gardosi J et  al. Am J Obstet Gynecol. 2018;218(2):​ S609–618. 78. Mikolajczyk RT et  al. Lancet. 2011;377(9780):​ 1855–1861. 79. De Jong CL et  al. Ultrasound Obstet Gynecol. 2000;15(1):36–40.

Preterm labor and birth VINCENZO BERGHELLA and EDUARDO DA FONSECA

DEFINITION, IMPACT, AND INCIDENCE

Every 30 seconds a baby dies from being born too soon. The definition of preterm birth (PTB) is birth before 37 weeks. Usually this implies a birth ≥20 weeks, but the earlier cutoff in gestational age varies by countries. This leads to an effect on incidences of PTB in different countries. The World Health Organization (WHO) estimates that there are about 15 million annually in the world, and that over 1 million babies die of PTB (1). In fact, in terms of yearsof-life lost, as PTB “kills” the youngest humans, it might represent the deadliest of all diseases. PREDICTION OF PRETERM BIRTH

To prevent PTB, prediction is most important. Prediction is best accomplished by review of risk factors for PTB. A list of risk factors is shown in Table 5.1 (2). We advocate that all of these risk factors be reviewed with the patient, preferably before conception, as many (e.g., smoking, diabetes, etc.) should be managed aggressively pre-pregnancy. In bold in Table 5.1 are the three risk factors that are currently most used for clinical management: prior PTB, multiple gestations, and short cervical length (CL). GENETICS AND PRETERM BIRTH

There are several recent studies and reviews on possible genetic etiologies, or at least associations, with PTB (3–5). These in general confirm the different pathways associated so far with PTB and risk factors. For example, a recent review highlighted genetic variants detected by whole exome (or genome in some cases) sequencing (WES) pointing to the negative regulation (dampening) of the innate immune response (e.g., CARD6, CARD8, NLRP10, NLRP12, NOD2, TLR10) and antimicrobial peptide/ proteins (e.g., DEFB1, MBL2) associated with PTB (3). These genetic associations support the concept that PTB, at least in part, has an inflammatory etiology, which can be induced either by pathogens (i.e., intra-amniotic infection) or “danger signals” (e.g., alarmins) released during cellular stress or necrosis (i.e., sterile intra-amniotic inflammation) (3). PTB has a polygenic basis that involves mutations or damaging variants in multiple genes involved in innate immunity and host defense mechanisms against microbes and their noxious products. WES is the most promising approach for the identification of functionally significant genetic variants responsible for spontaneous PTB (3). Another association is with genetic issues related to hormones as estrogen and progesterone, or other pathways

5

for PTB, such as variants at the EBF1, EEFSEC, AGTR2, WNT4, ADCY5, and RAP2C loci, which are associated with gestational duration, and variants at the EBF1, EEFSEC, and AGTR2 loci, associated with PTB (4). Genetics and genomics also have a role in pharmacogenomics, e.g., how a pregnant woman “reacts” to a certain pharmacologic intervention, such as progesterone for prevention of PTB, for example. Genotype may influence the response to commonly used therapeutics administered for PTB prevention and treatment (5). PREVENTION OF PRETERM BIRTH

Prevention of PTB can be divided into primary, secondary, or tertiary prevention. Primary prevention involves interventions that can be applied to all women. Table 5.2 lists some selected examples of prevention strategies tentatively aimed at primary prevention of preterm birth in the general population. These are extremely important and are best implemented though a preconception visit (2). Table 5.3 lists some examples of secondary prevention screening strategies and interventions for women for whom screening reveals them to be at higher risk for preterm birth (2). While many of these screening and intervention strategies are applied widely to many women, it is best currently, especially for transvaginal ultrasound (TVU) cervical length (CL) screening, to divide women in three broad categories based on some of the strongest risk factors as previously highlighted:

• Singletons without a prior spontaneous preterm birth (SPTB) • Singletons with a prior SPTB • Twins Singletons without a prior spontaneous preterm birth

In this population, TVU CL screening can be done at the time of the anatomy scan, around 20 weeks. If the CL is ≤25 mm (which occurs in about 1%–2% of these women) before 24 weeks, vaginal progesterone (either 200 mg suppositories, or 90 mg gel) should be recommended for prevention of PTB, as this intervention has been associated with an approximate 35% reduction in PTB (6). There are some data that show that if the CL is ≤10 mm or it shortens later to ≤10 mm, a cerclage may be helpful (7). A pessary has not yet been shown to be beneficial when the cumulative data to date are formally reviewed (8).

23

24  Preterm labor and birth

Table 5.1  Risk factors for preterm birth (PTB) • Prior obstetrics/gynecological history • Prior PTB • Cervical surgery (e.g., cone biopsy, loop electrosurgical excision procedure [LEEP], etc.) • Multiple dilations and evacuations (D&Es) • Uterine anomalies • Maternal demographics • 35 years of age • Less education (e.g.,