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The prediction of preeclampsia: the way forward

Published:March 27, 2021DOI:https://doi.org/10.1016/j.ajog.2020.10.047
      Despite intensive investigation, we still cannot adequately predict, treat, or prevent preeclampsia. We have gained awareness that preeclampsia is a syndrome not a disease and is heterogeneous in its presentation and pathophysiology, which may indicate differing underlying phenotypes, and that the impact extends beyond pregnancy per se. Effects on the fetus and mother extend many years after pregnancy, as evidenced by fetal programming of adult disease and increased risk of the development of maternal cardiovascular disease. The increased occurrence of preeclampsia in women with preexisting risk factors suggests that the stress of pregnancy may expose subclinical vascular disease as opposed to preeclampsia damaging the vasculature. The heterogeneity of preeclampsia has blighted efforts to predict preeclampsia early in gestation and has thwarted success in attempts at therapy with treatments, such as low-dose aspirin or global antioxidants. There is a critical need to identify the phenotypes to enable their specific prediction and treatment. Such studies require considerably larger collections of patients than employed in past and current studies. This does not necessarily imply much larger patient numbers in single studies but can be facilitated by the ability to easily combine many smaller studies. This can be accomplished by agreeing on a priori standardized and harmonized clinical data and biospecimen collection across new studies. Such standards are being established by international groups of investigators. Leadership by international organizations, perhaps adopting a carrot and stick approach, to overcome investigator, institutional and funder reticence toward data sharing is required to ensure adoption of such standards. Future studies should include women in both low- and high-resource settings and employ social media and novel methods for data collection and analysis, including machine learning and artificial intelligence. The goal is to identify the pathophysiology underlying differing preeclampsia phenotypes, their successful prediction with the design, and the implementation of phenotype-specific therapies.

      Key words

      Click Supplemental Materials under article title in Contents at ajog.org

      Introduction

      The societal and economic costs, estimated at $2.18 billion within the first 12 months of delivery in the United States,
      • Stevens W.
      • Shih T.
      • Incerti D.
      • et al.
      Short-term costs of preeclampsia to the United States health care system.
      of preeclampsia, which is the leading cause of maternal morbidity and responsible for 75,000 maternal deaths worldwide each year,
      • Duley L.
      The global impact of pre-eclampsia and eclampsia.
      remain unabated despite a substantial and ongoing amount of work attempting to describe the mechanistic underpinnings of the disorder, prediction of its occurrence, and therapeutic approaches. Most of this work was performed in developed countries where pregnant women have good access to antenatal care and advanced healthcare facilities and where morbidity and mortality are limited by prompt delivery of women with preeclampsia, which is accompanied by iatrogenic delivery of preterm neonates. In comparison, only 1% of the perinatal research expenditure but 99% of the 600,000 annual maternal deaths occur in low- and middle-income countries,
      • Duley L.
      The global impact of pre-eclampsia and eclampsia.
      where women have limited access to healthcare. Although improved access to care is necessary for alleviating the burden of preeclampsia in developing countries, there is still a role for predicting preeclampsia in that setting and in developed countries to alleviate the consequences.

      Where are we now?

      Over the past 30 years, there has been a general acceptance that preeclampsia is a syndrome and not a disease
      • Myatt L.
      • Roberts J.M.
      Preeclampsia: syndrome or disease?.
      and that preeclampsia presents with different phenotypes. These can be described clinically as mild vs severe and early- vs late-onset preeclampsia, although these are not dichotomous variables but rather continuous variables with arbitrary but clinically relevant definitions. Further clinical phenotypes include the presence or absence of growth restriction and variants, such as the HELLP (hemolysis, elevated liver enzymes, and low platelet count) syndrome and superimposition of preeclampsia on chronic hypertension. The knowledge that there is varying involvement of different organ systems in the clinical presentation of preeclampsia,
      • Myatt L.
      • Carpenter L.
      Prediction of preeclampsia.
      ,
      • Myatt L.
      • Miodovnik M.
      Prediction of preeclampsia.
      together with the large number of cross-sectional studies measuring different analytes in women with preeclampsia and the growing number of discovery-type “omics” studies,
      • Leavey K.
      • Bainbridge S.A.
      • Cox B.J.
      Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.
      • Leavey K.
      • Benton S.J.
      • Grynspan D.
      • Kingdom J.C.
      • Bainbridge S.A.
      • Cox B.J.
      Unsupervised placental gene expression profiling identifies clinically relevant subclasses of human preeclampsia.
      • Kenny L.C.
      • Broadhurst D.I.
      • Dunn W.
      • et al.
      Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers.
      • Austdal M.
      • Thomsen L.C.
      • Tangerås L.H.
      • et al.
      Metabolic profiles of placenta in preeclampsia using HR-MAS MRS metabolomics.
      has supported the concept of different biochemical phenotypes.
      • Myatt L.
      • Carpenter L.
      Prediction of preeclampsia.
      ,
      • Myatt L.
      • Miodovnik M.
      Prediction of preeclampsia.
      ,
      • Thomsen L.C.
      • Melton P.E.
      • Tollaksen K.
      • et al.
      Refined phenotyping identifies links between preeclampsia and related diseases in a Norwegian preeclampsia family cohort.
      This concept was instrumental in the design of the Combined Antioxidant and Preeclampsia Prediction Studies (CAPPS)
      • Myatt L.
      • Clifton R.G.
      • Roberts J.M.
      • et al.
      First-trimester prediction of preeclampsia in nulliparous women at low risk.
      and the Screening for Pregnancy Endpoints (SCOPE)
      • Kenny L.C.
      • Black M.A.
      • Poston L.
      • et al.
      Early pregnancy prediction of preeclampsia in nulliparous women, combining clinical risk and biomarkers: the Screening for Pregnancy Endpoints (SCOPE) international cohort study.
      studies, which both measured a range of biomarkers longitudinally across gestations in what were thought at the time to be relatively large numbers (2500 and 5623, respectively) of low-risk nulliparous women. Disappointingly, neither of these studies could identify early pregnancy predictors of preeclampsia; however, both studies made a point that the heterogeneity of preeclampsia contributed to the failure to identify early predictors with clinical utility. However, as these were studies of low-risk nulliparous women, most of those who developed preeclampsia developed late-onset preeclampsia, a condition alleviated by prompt delivery of the patient with relatively low fetal morbidity and mortality. There was also growing acceptance of the concept that early-onset preeclampsia is primarily related to failure of trophoblast invasion and adaptation of uterine spiral arteries
      • Robertson W.B.
      • Brosens I.
      • Dixon G.
      Maternal uterine vascular lesions in the hypertensive complications of pregnancy.
      leading to a relative placental ischemia and that late-onset preeclampsia, in which two-thirds of women do not display increased uterine artery vascular impedance,
      • Li H.
      • Gudnason H.
      • Olofsson P.
      • Dubiel M.
      • Gudmundsson S.
      Increased uterine artery vascular impedance is related to adverse outcome of pregnancy but is present in only one-third of late third-trimester pre-eclamptic women.
      is related to increased maternal susceptibility to the vascular and metabolic stress of pregnancy
      • Roberts J.M.
      • Hubel C.A.
      The two stage model of preeclampsia: variations on the theme.
      or to advancing placental senescence
      • Redman C.W.
      • Staff A.C.
      Preeclampsia, biomarkers, syncytiotrophoblast stress, and placental capacity.
      that releases damaging vasoactive factors into the maternal circulation.
      An important finding from both CAPPS and SCOPE was that although they could not identify the biomarkers with clinical utility for first-trimester prediction of preeclampsia, measurement of changes in biomarkers from first to early or late second trimester of pregnancy
      • Myatt L.
      • Clifton R.G.
      • Roberts J.M.
      • et al.
      Can changes in angiogenic biomarkers between the first and second trimesters of pregnancy predict development of pre-eclampsia in a low-risk nulliparous patient population?.
      increased the sensitivity for detecting preeclampsia, that is, the later in gestation, the better the ability to predict. Subsequently, these findings have been capitalized on with second
      • Agrawal S.
      • Cerdeira A.S.
      • Redman C.
      • Vatish M.
      Meta-analysis and systematic review to assess the role of soluble FMS-like tyrosine kinase-1 and placenta growth factor ratio in prediction of preeclampsia: the SaPPPhirE study.
      and third trimesters
      • Duhig K.E.
      • Myers J.
      • Seed P.T.
      • et al.
      Placental growth factor testing to assess women with suspected pre-eclampsia: a multicentre, pragmatic, stepped-wedge cluster-randomised controlled trial.
      measurement of angiogenic factors being shown to have high diagnostic accuracy for predicting subsequent development of preeclampsia and other adverse outcomes and assignment of women to appropriate clinical care pathways, indeed being introduced into routine clinical practice in the United Kingdom.
      National Institute for Health and Care Excellence
      PlGF-based testing to help diagnose suspected pre-eclampsia (Triage PlGF test, Elecsys immunoassay sFlt-1/PlGF ratio, DELFIA Xpress PlGF 1-2-3 test, and BRAHMS sFlt-1 Kryptor/BRAHMS PlGF plus Kryptor PE ratio).
      First-trimester screening using a combination of ultrasound measurement of uterine artery pulsatility index, maternal risk factors, mean arterial pressure, and placental growth factor has now been recommended for predicting early-onset preeclampsia,
      • Poon L.C.
      • Shennan A.
      • Hyett J.A.
      • et al.
      The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre-eclampsia: a pragmatic guide for first-trimester screening and prevention.
      that is, the placental disease. It is recommended that low-dose aspirin be administered to these women before 16 weeks’ gestation, reducing the incidence of early-onset preeclampsia by more than 60%.
      • Rolnik D.L.
      • Nicolaides K.H.
      • Poon L.C.
      Prevention of preeclampsia with aspirin.
      Although this is a significant step forward, early-onset preeclampsia only affects <1% of the pregnant population with up to 80% of preeclampsia being late onset where both mother and fetus are still at risk of adverse outcomes with only increased surveillance and delivery available to prevent adverse events. We are now aware that exposure to an adverse intrauterine environment, such as that presented by growth restriction or preeclampsia, results in fetal programming of adult diseases, including cardiovascular, metabolic, and neurodevelopmental disorders
      • Bale T.L.
      • Baram T.Z.
      • Brown A.S.
      • et al.
      Early life programming and neurodevelopmental disorders.
      ,
      • Godfrey K.M.
      • Barker D.J.
      Fetal programming and adult health.
      ; hence, instead of leaving the fetus exposed throughout gestation, early prediction of the potential development of preeclampsia and implementation of a therapy could prevent these programming effects. Similarly, there is now increasing awareness of the association of adverse pregnancy outcomes, including preeclampsia, with the development of long-term cardiovascular and metabolic diseases in women.
      • Staff A.C.
      • Redman C.W.
      • Williams D.
      • et al.
      Pregnancy and long-term maternal cardiovascular health: progress through harmonization of research cohorts and biobanks.
      Whether this is the result of preeclampsia damaging the maternal vasculature or whether the stress of pregnancy exposes women with preexisting subclinical vascular disease is currently being investigated. However, early prediction and institution of a prophylactic therapy to prevent the development of preeclampsia may be beneficial in preventing long-term consequences.

      Caveats for prediction studies and therapeutic trials

      If we accept that early prediction of late-onset (and early-onset) preeclampsia may be of benefit for both the mother and offspring, how do we achieve it against the background of heterogeneity of the syndrome that has blighted previous efforts? The overall incidence of preeclampsia and the incidence of severe preeclampsia are increased in certain high-risk groups of patients, for example, multifetal gestation, previous preeclampsia, chronic hypertension, and pregestational diabetes,
      • Caritis S.
      • Sibai B.
      • Hauth J.
      • et al.
      Low-dose aspirin to prevent preeclampsia in women at high risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units.
      which may point to different underlying causes, for example, placental or endothelial dysfunction. These patient groups may present enriched populations for study, but most preeclampsia cases in developed countries occur in clinical practice in low-risk nulliparous women, leading to this group being selected in many studies, for example, CAPPS and SCOPE. However, among nulliparous women, up to 5% will have chronic hypertension, multifetal gestation, or pregestational diabetes, and the increased incidence of preeclampsia associated with these high-risk conditions means that up to 14% of preeclampsia in nulliparous women will be associated with these conditions (Levine and Myatt unpublished). Similarly, in multiparous women, a group also including those with previous preeclampsia, up to 9% will have a high-risk condition, and close to 100% of their preeclampsia will be associated with these preexisting high-risk conditions. The association of preeclampsia with high-risk conditions and the mendelian pattern of inheritance in some families suggest that preeclampsia is a complex genetic disorder occurring as a result of numerous common variants at different loci that contribute to an individual’s susceptibility to the disease.
      • Williams P.J.
      • Broughton Pipkin F.
      The genetics of pre-eclampsia and other hypertensive disorders of pregnancy.
      Because no single cause or genetic variant will account for all preeclampsia cases, large patient numbers across many different populations are required to unravel this complexity.
      • Jebbink J.
      • Wolters A.
      • Fernando F.
      • Afink G.
      • van der Post J.
      • Ris-Stalpers C.
      Molecular genetics of preeclampsia and HELLP syndrome—a review.
      ,
      • Triche E.W.
      • Uzun A.
      • DeWan A.T.
      • et al.
      Bioinformatic approach to the genetics of preeclampsia.
      Beyond predicting which women are likely to develop preeclampsia, prediction studies would be useful for identifying women who might benefit from some sort of therapy if it was available. Although the deviation in biomarker levels or profiles from those seen in normotensive patients with good outcomes is used to identify those developing preeclampsia and indicate potential pathophysiologic pathways, we have to be cautious as the placenta and maternal systems may adapt to the pathophysiologic insult and display this adaptive response rather than display the evidence of the causative pathway. A therapeutic action targeted at these pathways may worsen the condition and threaten maternal and fetal well-being by ameliorating the adaptive response rather than inhibiting a causative pathway.

      What lessons have we learned?

      The rate of occurrence of preeclampsia (5%–7%) means that even in large studies, such as CAPPS (n=2500) and SCOPE (n=5623), only relatively small numbers of patients actually develop preeclampsia with most cases being late-onset mild preeclampsia and a proportion of these cases associated with preexisting conditions. Obviously, a larger number of patients have to be enrolled to achieve meaningful numbers of women with preeclampsia to allow the dissection of biomarker profiles, risk factors, etc., necessary to reveal different known, suspected, and unknown phenotypes of preeclampsia. This may be beyond the resources of single centers or even networks. It is not surprising that many current studies still employ small patient numbers and are cross-sectional in nature, limiting the utility and knowledge gained. The differences in study design, patient selection, and clinical data collection make it extremely difficult to combine these studies even in meta-analyses.
      • Wu P.
      • van den Berg C.
      • Alfirevic Z.
      • et al.
      Early pregnancy biomarkers in pre-eclampsia: a systematic review and meta-analysis.
      A major failure is poor definition and clinical phenotyping of patients, leading to the concept of the 1 million dollar test but the 5 cent diagnosis.
      • Roberts J.M.
      Preeclampsia: new approaches but the same old problems.
      Although useful in clinical practice, where the objective is not to miss patients at high risk of adverse outcome, use of the recently more inclusive clinical diagnosis
      American College of Obstetricians and Gynecologists
      Gestational hypertension and preeclampsia: ACOG Practice Bulletin Summary, number 222.
      for research studies may include many patients with weak phenotypes. What strategy can then be employed? Regardless of their size, studies must collect sufficient clinical data (not just blood pressure and proteinuria) to enable adequate phenotyping of patients. The data should be compatible with data collected from other studies, allowing them to be easily compared and combined if necessary. The need for data standardization and harmonization across studies has been clearly recognized and operative in, for example, the cancer field for many years and has been clearly mentioned as advantageous in study of preeclampsia.
      • Myatt L.
      • Redman C.W.
      • Staff A.C.
      • et al.
      Strategy for standardization of preeclampsia research study design.
      Collection of data across many studies into a database with a priori agreed data fields will allow easy combination of large numbers of smaller studies to quickly achieve the patient numbers needed to encompass the different phenotypes of preeclampsia each in adequate numbers.
      • Myers J.E.
      • Myatt L.
      • Roberts J.M.
      • Redman C.
      Global Pregnancy Collaboration (CoLab)
      COLLECT, a collaborative database for pregnancy and placental research studies worldwide.
      The patient numbers have to be large enough to achieve statistical power necessary to define the contribution of factors, such as ethnicity, geography and environmental exposures, genetics, preexisting conditions, and confounders, such as obesity and fetal gender. It is realized that the collection of extensive and detailed clinical data is difficult in resource-poor areas; however, in this case, all efforts should be made to collect at least a minimal agreed standardized data set
      • Myatt L.
      • Redman C.W.
      • Staff A.C.
      • et al.
      Strategy for standardization of preeclampsia research study design.
      (Supplemental Table 1) compatible with data that are collected in resource-rich areas.

      What data to collect to really understand preeclampsia

      Traditionally, preeclampsia studies have collected data in cross-sectional studies from patients diagnosed with preeclampsia, and these have been the basis for our current understanding of the pathophysiology and therapeutic approaches. Recently, a few longitudinal sample and data collections have been made, with both their expense and the incidence of preeclampsia (5%–7%) ultimately limiting the numbers of women in such studies who will develop preeclampsia. Our realization of the long-term consequences of adverse pregnancy outcome on the mother and offspring now indicates that we should collect pregnancy and postpregnancy data in the same women. Deep phenotyping of women during pregnancy has recently been suggested to offer an opportunity to not only improve pregnancy outcomes but also define the antecedents of lifelong health and wellness.
      • Paquette A.G.
      • Hood L.
      • Price N.D.
      • Sadovsky Y.
      Deep phenotyping during pregnancy for predictive and preventive medicine.
      The understanding that preexisting risk factors, exposed by pregnancy and leading to preeclampsia, may play a major role in the pathophysiology suggests that prepregnancy studies are also important. Hence, comprehensive studies of the reproductive life course may need to be undertaken to truly understand the antecedents, incidence, and consequences of preeclampsia. This Herculean long-term undertaking is perhaps beyond the capacity of even major philanthropic organizations but can be aided by agreed upon types and standards for data collection. Leadership to encourage adoption of such standards should perhaps come from authoritative international organizations; a top-down approach linked to grant support may aid in the adoption of standards. This does not mandate large multicenter international studies; individual investigator-initiated studies can still occur, but adoption of data collection standards allows the facility to easily aggregate data if desired and overcome the previously mentioned issues of data combination.
      • Wu P.
      • van den Berg C.
      • Alfirevic Z.
      • et al.
      Early pregnancy biomarkers in pre-eclampsia: a systematic review and meta-analysis.
      Where will such data come from? Obviously, medical records are a major source but standards and ease of access vary across the globe. Efforts must be made to again standardize and get ease of access. Furthermore, in the United States, the major driver of electronic medical record design was for accurate billing with little attention to accumulating data to understand diseases. There is also an abundance of data generated and gathered on social media, through patient advocacy sites and via commercial tests, for example, genetic ancestry, that can be incorporated into preeclampsia studies. Again, the quality and disease identification from such data are of widely varying quality. A similar concern related to the variation in the collection of clinical data applies to the collection of biospecimens into biobanks. Various organizations have presented standardized methods for the collection and storage of materials, for example, the placenta;
      • Burton G.J.
      • Sebire N.J.
      • Myatt L.
      • et al.
      Optimising sample collection for placental research.
      however, these need to be widely adopted to ensure consistency across studies.
      Research studies will usually have high-quality clinical data and associated biomaterials that are carefully collected but are limited by the number of subjects in any study. This raises the issue of data sharing, in which investigators can combine many such studies to achieve a large data set. However, data sharing is currently associated with several challenges. These include the mindset of investigators, academic institutions, and funders for whom sharing has not been of high priority. Furthermore, collecting necessary data and identifying and including relevant outcomes sufficient for sharing and data formats and dictionaries that do not impede sharing present major problems.
      • Roberts J.M.
      • Mascalzoni D.
      • Ness R.B.
      • Poston L.
      Global Pregnancy Collaboration
      Collaboration to understand complex diseases: preeclampsia and adverse pregnancy outcomes.
      It is encouraging that funders, academic institutions, and individual investigators are beginning to recognize the importance of sharing. For preeclampsia, the Global Pregnancy Collaboration (CoLab) has presented data fields that are necessary to collect data for preeclampsia research, including a minimal and an optimal set of variables
      • Myatt L.
      • Redman C.W.
      • Staff A.C.
      • et al.
      Strategy for standardization of preeclampsia research study design.
      (Supplemental Table 1, Supplemental Table 2), whereas the International Collaboration to Harmonize Outcomes in Pre-eclampsia (iHOPE) is attempting to standardize outcomes collected in preeclampsia studies.
      • Duffy J.
      • Rolph R.
      • Gale C.
      • et al.
      Core outcome sets in women’s and newborn health: a systematic review.
      The iHOPE initiative builds on the efforts of 80 journals participating in the Core Outcomes in Women’s and Newborn Health (CROWN) initiative, which encourages researchers to develop core outcome sets, that is, minimum collections of outcomes with standardized measurement and prioritized reporting in clinical trials to facilitate synthesis and dissemination of results in systematic reviews. The CoLab has also prepared a harmonized preeclampsia database available to all investigators at nominal or no charge in which data can be securely stored with access only to the investigator (https://pregnancycolab.tghn.org/collect/).
      • Myers J.E.
      • Myatt L.
      • Roberts J.M.
      • Redman C.
      Global Pregnancy Collaboration (CoLab)
      COLLECT, a collaborative database for pregnancy and placental research studies worldwide.
      However, if sharing is chosen, data are easily shared with others who are using this database.

      Data Analysis

      A powerful illustration of the heterogeneity of preeclampsia is the wide scatter seen in data presented from studies of biomarkers. Often, this is presented as mean and standard deviation and hides the considerable overlap between patients with and without preeclampsia; furthermore, patients with preeclampsia often have analyte values similar to patients without preeclampsia.
      • Weissgerber T.L.
      • Milic N.M.
      • Winham S.J.
      • Garovic V.D.
      Beyond bar and line graphs: time for a new data presentation paradigm.
      ,
      • Powers R.W.
      • Roberts J.M.
      • Cooper K.M.
      • et al.
      Maternal serum soluble fms-like tyrosine kinase 1 concentrations are not increased in early pregnancy and decrease more slowly postpartum in women who develop preeclampsia.
      Beyond this, data analyses have been routine and depend on receiver operating characteristic curve analysis to identify the predictors. The recent interest in the use of dynamical modeling, machine learning, and artificial intelligence that more comprehensively studies the interaction of various factors offers some hope in studying the interaction of clinical and biochemical factors and may also be useful in being applied retrospectively to previous data sets.

      Therapeutic approaches

      In retrospect, it is perhaps easy to determine why previous therapeutic trials with low-dose aspirin
      • Caritis S.
      • Sibai B.
      • Hauth J.
      • et al.
      Low-dose aspirin to prevent preeclampsia in women at high risk. National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units.
      ,
      • Sibai B.M.
      • Caritis S.N.
      • Thom E.
      • et al.
      Prevention of preeclampsia with low-dose aspirin in healthy, nulliparous pregnant women. The National Institute of Child Health and Human Development Network of Maternal-Fetal Medicine Units.
      or antioxidants
      • Roberts J.M.
      • Myatt L.
      • Spong C.Y.
      • et al.
      Vitamins C and E to prevent complications of pregnancy-associated hypertension.
      aimed at reduction in overall preeclampsia have failed in large-scale trials. Given the heterogeneity of preeclampsia, any beneficial effect on 1 or more phenotypes of patients may have been obscured by the lack of effect on other phenotypes within the population. Furthermore, these treatments were chosen on the basis of empirical observations in cross-sectional studies of women with established disease. So were deficiencies in antioxidant defenses seen as a cause or consequence of preeclampsia? We now have more knowledge of the cell and subcellular specific sites of synthesis and action of different pro- and antioxidants
      • Myatt L.
      • Cui X.
      Oxidative stress in the placenta.
      ,
      • Kurutas E.B.
      The importance of antioxidants which play the role in cellular response against oxidative/nitrosative stress: current state.
      that it is not surprising that a global antioxidant did not work. The use of low-dose aspirin in women who are predicted to be at high risk of early-onset preeclampsia
      • Poon L.C.
      • Shennan A.
      • Hyett J.A.
      • et al.
      The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre-eclampsia: a pragmatic guide for first-trimester screening and prevention.
      where large numbers of women need to be treated to prevent 1 case of preeclampsia
      • Rolnik D.L.
      • Nicolaides K.H.
      • Poon L.C.
      Prevention of preeclampsia with aspirin.
      is defended by the low-risk profile of low-dose aspirin, although recently aspirin use in pregnancy has been associated with increased postpartum bleeding and hematoma.
      • Hastie R.
      • Tong S.
      • Wikström A.K.
      • Sandström A.
      • Hesselman S.
      • Bergman L.
      Aspirin use during pregnancy and the risk of bleeding complications: a Swedish population-based cohort study.
      Novel therapeutic approaches currently being investigated include targeting the complement system,
      • Regal J.F.
      • Burwick R.M.
      • Fleming S.D.
      The complement system and preeclampsia.
      proangiogenesis,
      • Eddy A.C.
      • Bidwell 3rd, G.L.
      • George E.M.
      Pro-angiogenic therapeutics for preeclampsia.
      and the use of pravastatin, metformin, proton-pump inhibitors, and micronutrients.
      • Tong S.
      • Kaitu’U-Lino T.J.
      • Hastie R.
      • Brownfoot F.
      • Cluver C.
      • Hannan N.
      Pravastatin, proton-pump inhibitors, metformin, micronutrients, and biologics: new horizons for the prevention or treatment of preeclampsia.
      These trials may suffer the same consequences as previous ones related to the heterogeneity of preeclampsia. Obviously, the identification of different phenotypes of preeclampsia and application of therapies specific to that phenotype are the way forward.

      Summary: How to Move Forward

      Despite preeclampsia being described over 15 centuries ago and with tremendous energy and resources being expended in the second half of the 20th century in attempting to define the underlying pathophysiology and limited success in predicting and preventing the less frequently occurring early-onset form we still, in the 21st century, lack the overall ability to predict, prevent other than by delivery, or effectively treat preeclampsia. The impact of preeclampsia extends beyond risks to the mother and fetus in pregnancy per se, as the adverse intrauterine environment programs the fetus for disease in adult life and women with preeclamptic pregnancy are at increased risk of cardiovascular disease in later life. The prepregnancy antecedents of preeclampsia may also contribute to its development, illustrating that the condition is related to health across the lifespan. We now accept that preeclampsia is a syndrome and not a disease and that the considerable heterogeneity in its presentation and associated pathology implies that the condition has several phenotypes that has yet to be clearly defined beyond their associated temporal or clinical appearance. This heterogeneity has blighted our attempts to predict who will develop preeclampsia at a time when intervention may be useful to prevent adverse outcomes and has shown that global therapeutic approaches do not work and therapies tailored for individual phenotypes may be necessary. Hence, there is a need to identify the different phenotypes of preeclampsia, develop methods for their prediction, and design and test phenotype-specific interventions. The burden of overall maternal morbidity and mortality and of preeclampsia in low-resource settings mandates that increasing attention is paid to the study of preeclampsia in those countries where currently only 1% of research occurs and the antecedents, development, and consequences may differ. To define the phenotypes of preeclampsia, a much larger number of patients than have been employed in studies to date is needed. This does not necessarily imply that larger single studies, the use of agreed upon standardized and harmonized clinical data, and biospecimen collection will allow aggregation of many small studies to achieve large numbers by overcoming previous barriers to data combination. Novel methods of data collection emerging in the digital age and on social media should be incorporated together with machine learning and artificial intelligence in data analysis. These efforts have to be led by international organizations and may need to involve a “carrot and stick” approach to overcome investigator, institutional, and funder resistance to collaboration. Such collaborative investigator-led efforts are emergent but need the support of funding bodies to achieve their potential. If we can define the differing underlying phenotypes of preeclampsia and hence identify phenotype-specific predictors, we can then start phenotype-specific therapies rather than continue the one-size-fits-all approach previously adopted where any potential success is obscured by the background of nonresponders.

      Supplemental Material

      Supplemental Table 1Minimal data set for studies on preeclampsia
      Maternal data
      Physical, anthropologic, and ethnographic data
       Age
       Self-described ethnicity (white, black, Asian, Hispanic, unknown, or other [mixed])
       Country of birth
       Parents’ country of birth
       Parity
       Gravidity
       Measured height, measured weight (prepregnancy or before 14 wk) and BMI
       Years of schooling or other indicator of socioeconomic status
      Smoking history
       Cigarette or cigar smoker
       Snuff user
       Chews tobacco or takes nicotine
       For each choice, check ≥1 of the following:
      Never used
      Irregularly used
      Regularly used
      Gave up before pregnancy
      Gave up during pregnancy
      Uses currently in this pregnancy
      Medical history (reported)
       Hypertension
       Renal disease
       Diabetes mellitus (type I or type II)
       Collagen vascular disease (eg, Sjogren, antiphospholipid syndrome, systemic lupus erythematosus)
       Previous preeclampsia
       Previous gestational diabetes
       Obstetrical history (indicate numbers and gestational age at occurrence)
       Miscarriage
       Stillbirth
       Induced abortion
       Gestational hypertension
       Preeclampsia
       Eclampsia
       HELLP
       SGA and IUGR
       Gestational diabetes mellitus requiring treatment with insulin or oral hypoglycemic agents
       Preterm delivery (<37 wk)
       Neonatal death
      Present pregnancy
       BP at first visit (booking)
       Singleton or multifetal pregnancy
       Hydatidiform mole
       Hydropic placenta
      Antihypertensive use in this pregnancy
       For preeclampsia
       For essential hypertension
      Other medications
       Magnesium sulfate
       Corticosteroids for lung maturation
       Low-dose aspirin
       Thyroid supplements
       Antithyroid treatment for thyrotoxicosis
       Other (list)
      Diagnosis of preeclampsia
       Highest recorded systolic and diastolic BPs within 2 wk of delivery (do not use values during labor)
       Choose available or not available
       Highest intrapartum BP
       Highest BP within 48 h after delivery
       Proteinuria (dipstick/24 h urine/PC ratio)
      Choose available or not available
       Multisystem involvement (platelets, liver enzymes, serum creatinine, seizures, indicated preterm birth, IUGR, fetal, or neonatal death)
      Choose yes, no, or unavailable
      Maternal outcome
       Length of stay in hospital predelivery (d)
       Mode of delivery (vaginal and cesarean deliveries with or without labor or with or without induction)
       MgSO4 use in this pregnancy (before, during, or after delivery)
       Maternal outcome (healthy, PIH, preeclampsia, eclampsia, abruption, HELLP, GDM, death)
      Infant data
       Survival (yes or no)
       Intrauterine fetal death (before admission or after admission)
       Neonatal death
       Gestational age at delivery in completed wk and d (if possible; calculated using LMP and ultrasound)
       Sex
       Newborn weight
      BMI, body mass index; BP, blood pressure; GDM, gestational diabetes mellitus; HELLP syndrome, hemolysis, elevated liver enzymes, and low platelet count; IUGR, intrauterine growth restriction; LMP, last menstrual period; PC, protein-creatinine; PIH, pregnancy-induced hypertension; SGA, small for gestational age.
      Reproduced, with permission, from Myatt et al.
      • Myatt L.
      • Redman C.W.
      • Staff A.C.
      • et al.
      Strategy for standardization of preeclampsia research study design.
      Myatt. The prediction of preeclampsia. Am J Obstet Gynecol 2022.
      Supplemental Table 2Optimal data set for studies on preeclampsia
      Reproduced, with permission, from Myatt et al.
      • Myatt L.
      • Redman C.W.
      • Staff A.C.
      • et al.
      Strategy for standardization of preeclampsia research study design.
      Maternal data (data from minimal data set plus the following)
      Clinical history
       Gestational age at start of documented maternity care
       Number of prenatal visits (doctor, midwife, or hospital in present pregnancy)
       Blood transfusions
      In life time
      In present pregnancy
       Fertility history
      Assisted reproductive technology
      Present pregnancy
      Any previous attempted pregnancy
      IVF
      ICSI
      Artificial insemination
      Partner or donor sperm
      Egg recipient
      Embryo recipient
       Age at menarche
       Birthweight of the pregnant woman
       Duration of preconception sexual intercourse with biologic father of child (months [list as zero if donor semen])
      Previous pregnancy outcomes (indicate numbers, and if with same partner or a previous partner and gestational age at occurrence)
       Miscarriage
       Stillbirth
       Induced abortion
       Recurrent spontaneous pregnancy loss
       Gestational hypertension
       Preeclampsia
       Eclampsia
       HELLP
       SGA and IUGR
       Gestational diabetes mellitus requiring treatment with insulin or oral hypoglycemic agents
       Preterm delivery (<37 wk)
       Neonatal death
      Relevant maternal family history
       Mother, sister, or cousin with preeclampsia
      Validated or self-reported
       Family history (siblings, parents, and grandparents) of cardiovascular disease (none, hypertension, CHD, stroke, and actual age [y] at occurrence)
       Family history (siblings, parents, and grandparents) of diabetes mellitus
      Relevant paternal family history
       Has he fathered a preeclamptic pregnancy? (This mother or other mother)
       Mother, sister, or cousin with preeclampsia
       Validated or self-reported
       Family history (siblings, parents, and grandparents) of cardiovascular disease (none, hypertension, CHD, stroke, and actual age [y] at occurrence)
      Nicotine history
       Cigarette or cigar smoker
       Snuff user
       Chews tobacco or takes nicotine
       None of above used ever
       Used irregularly or regularly only before pregnancy
       Continues (number of cigarettes/d: 1–10, 11–20, >20; number of cigars/d: 1, 2–5, >5)
       In the third trimester of pregnancy (28–36 wk), stopped since early pregnancy, restarted since early or before pregnancy, continued to smoke [number])
      Alcohol use
       At baseline (never or gave up before pregnancy or gave up during pregnancy or this pregnancy)

      Number of units/wk
       In the third trimester of pregnancy (stopped since early pregnancy, restarted since early or before pregnancy, continued to drink)

      Number of units/wk
      Recreational drugs or drug abuse (yes or no)
       Cannabis (yes or no)
       Cocaine (yes or no)
       Opiates (heroin, morphine, codeine, or methadone; yes or no)
       Methamphetamine
       Ecstasy or other central stimulating drugs? (Specify)
       At baseline (never, gave up before pregnancy, gave up during pregnancy, or this pregnancy)
       In the third trimester of pregnancy (stopped since early pregnancy, restarted since early or before pregnancy, continued to use)
      Clinical data
       Blood pressures
      First blood pressure (and gestational age)
      Two highest systolic and diastolic blood pressures at each visit (can be at different times) or each wk if visit lasts >1 wk)
      At diagnosis of preeclampsia
      2 highest systolic blood pressures within 2 wk of delivery
      2 highest diastolic blood pressures within 2 wk of delivery
       Urine protein values (at each visit)
      First urinalysis (and gestational age)
      24 h or timed collections
      Protein-to-creatinine ratio
       Weight gain during pregnancy
       Weight gain since last delivery
       Growth by ultrasound
      Constant (above, below, or on curve)
      Falling off with increasing gestation
      Macrosomia
       Uteroplacental blood flow indices at midgestation (16–25 wk), performed or not performed
      Notching (yes or no)
      Unilateral (yes or no)
      Bilateral (yes or no)
      Pulsatility index (mean of bilateral measurements)
       Umbilical blood flow indices if clinical suspicion of FGR or documented FGR (done or not done)
      Gestational age at which performed
      Pulsatility index (value) and resistance index (value)
      Absent end diastolic flow (yes or no)
      Reversed end diastolic flow (yes or no)
       Fetal growth ultrasound
      12 wk
      18–20 wk
      28 wk
      36 wk
      If clinical indication of FGR or documented FGR
      Labor (active phase, yes or no; labor defined as uterine contractions, which result in cervical dilatation and effacement)
       Spontaneous (yes or no)
       Induced (yes or no)
       Induction indicated for hypertensive disorder (yes or no)
       Cesarean delivery (yes or no)
       Cesarean delivery indicated for hypertensive disorder (yes or no)
      Medical conditions before pregnancy (in addition to those in minimal data set)
       Select either
      In pregnancy alone
      Before pregnancy
      Before and continuing during pregnancy
       Other endocrine disease
       Thyroid disease
       Adrenal disease
       Liver disease
       Hematologic disorder, including alloimmune or isoimmune
       Epilepsy or seizure disorder
       Heart disease
       Cancer
       Metabolic syndrome (any 3 of the 5 criteria described in Alberti et al
      • Alberti K.G.
      • Eckel R.H.
      • Grundy S.M.
      • et al.
      Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity.
      are present before pregnancy)
       PCOS (≥2 of the following 3 features are present)
      Oligo- and anovulation
      Clinical and biochemical signs of hyperandrogenism
      Polycystic ovaries and exclusion of other pathogeneses (congenital adrenal hyperplasia, androgen-secreting tumors, Cushing syndrome)
       Infectious disease
      Malaria
      Placental (yes or no), laboratory diagnosis (yes or no)
      HIV
      CD4 count
      TB
      Active or inactive
      Schistosomiasis
      Hepatitis B
      STD
      Gonorrhea
      Syphilis
      Chlamydia
      Herpes
      Trichomoniasis
      Genital warts
      Other
      Urinary tract infection
      Antibiotics (yes or no)
       Other infectious disease
      Medications before and during pregnancy
       Select either
      In pregnancy alone (Which wk started?)
      Before pregnancy
      Before and continuing during pregnancy
       Vitamins
      Vitamin C
      Vitamin D
       Vitamin E
       Other
       Multivitamins
       Folate
       Fortified foods available in country of residence (yes or no)
      List additives used for fortification
      Aspirin
      Platelet-active drugs
       Antioxidants
      High dosages of vitamin C (>500 mg)
      High dosages of vitamin E (>400 IU)
      β-carotene
      Resveratrol
      Selenium
      Coenzyme Q10
      Other (specify)
       Fish oil
       Calcium (specify amount)
       Iron supplements (specify)
       Diuretics (specify)
       Antihypertensive agents (specify)
       Antibiotics (specify)
       Anticoagulants (specify)
       Anticonvulsants
       MgSO4
      Other (specify)
       Antidepressants (SSRIs; specify)
       Antiglycemic agents
      Insulin
      Metformin
      Other (specify)
       Long-term immunosuppressants
       Thyroid supplements
       Antithyroid treatment for thyrotoxicosis
       Other (specify)
      Postnatal maternal care
       Length of stay in hospital (d)
      Infant data (data from the minimal data set plus the following)
       Length
       APGAR scores (1, 5, and 10 min if recorded)
       Umbilical cord gases
       Admitted to NICU (yes or no)
       Length of stay in NICU (d)
       Outcome at discharge from the NICU
      IVH
      BPD
      RDS
      NEC
      Hypoxic-ischemic encephalopathy
      Convulsions
      Placenta data
       Weight
       Cord insertion
       Number of vessels in cord
       Pathology report (if sent for pathology)
       Photograph against a scale bar
      Appendix for other important information is presented.
      BPD, bronchopulmonary dysplasia; CD4, cluster of differentiation 4; CHD, coronary heart disease; FGR, fetal growth restriction; HELLP syndrome, hemolysis, elevated liver enzymes, and low platelet count; ICSI, intracytoplasmic sperm injection; IUGR, intrauterine growth restriction; IVF, in vitro fertilization; IVH, intraventricular hemorrhage; NEC, necrotizing enterocolitis; NICU, neonatal intensive care unit; PCOS, polycystic ovary syndrome; RDS, respiratory distress syndrome; SGA, small for gestational age; SSRI, selective serotonin reuptake inhibitor; STD, sexually transmitted disease; TB, tuberculosis.
      Myatt. The prediction of preeclampsia. Am J Obstet Gynecol 2022.

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