In 2011, the American Heart Association added preeclampsia, gestational diabetes mellitus (GDM), and delivery of a growth-restricted child as pregnancy-related risk factors for cardiovascular disease (CVD).1 This move was applauded by the obstetric research community, which for some years had emphasized the importance of pregnancy as a stress test for detecting women at excessive risk for premature CVD.2–4

CVD is the leading cause of death for men and women in high-income and most low-to-middle–income countries.5 Globally, coronary artery disease kills more women than men,6 although women develop CVD 10 to 15 years later than men. Women frequently present with unrecognized CVD symptoms and are twice as likely as men to die of a first acute myocardial infarction if <50 years old.7 The preclinical stages of CVD are evident from a young age and are modifiable through control of classic risk factors (insulin resistance/diabetes mellitus, obesity, lack of exercise, tobacco smoking, hypertension, and hyperlipidemia).8,9 In this regard, pregnancy is a window of opportunity for identifying those women with perinatal complications who may benefit from early risk detection and early CVD prevention.

In this article, we summarize the associations between pregnancy, placenta-related pregnancy complications, and future maternal CVD. We present established as well as more novel hypotheses, which may explain these epidemiological associations. The interventions that potentially could reduce risks of future CVD are enumerated. To facilitate progress, we suggest methods of harmonizing study designs, long-term follow-ups of pregnancy cohorts and biobanks, and pooling of the world’s data in ways that can enhance the power of current and future research.

### Preeclampsia and Fetal Growth Restriction and Future CVD Risk

Preeclampsia is a pregnancy-specific multisystem disorder defined by new-onset hypertension and proteinuria after gestational week 20, or new onset preeclampsia-associated signs in the absence of proteinuria.8 Preeclampsia requires the presence of …

Pregnancy and Long-Term Maternal Cardiovascular Health: Progress Through Harmonization of Research Cohorts and Biobanks

The rapid expansion of sophisticated molecular biomarker data information for detecting early biological responses to chemical agents in concert with the evolution of personalized medicine databases raises a number of challenging issues for the future with regard to how to most effectively make use of this growing body of personal information for constructive public health purposes and yet protect the privacy of the individual. As discussed elsewhere in this book, the growing body of complex biomarker data require appropriate statistical analysis, reasoned digestion, and translation into terminology that is readily understood by persons with limited technical backgrounds. This chapter will attempt to address the need for translation of technical biomarker information on two levels. The first is to provide some hopefully useful insights into how currently available “omic” biomarker data could be used for risk assessment purposes in the next 10 years. The second is to consider how the merger of biomarker data with the personalized electronic medical records of individuals could be used to aid preventable chemical-induced diseases while protecting the privacy of the individuals. These are complex but achievable issues.

Technical Translational Analysis of Molecular Biomarker Data

BACKGROUND Stillbirth affects 2.6 million pregnancies worldwide each year. Whilst the majority of cases occur in low- and middle-income countries, stillbirth remains an important clinical issue for high-income countries (HICs) - with both the UK and the USA reporting rates above the mean for HICs. In HICs, the most frequently reported association with stillbirth is placental dysfunction. Placental dysfunction may be evident clinically as fetal growth restriction (FGR) and small-for-dates infants. It can be caused by placental abruption or hypertensive disorders of pregnancy and many other disorders and factorsPlacental abnormalities are noted in 11% to 65% of stillbirths. Identification of FGA is difficult in utero. Small-for-gestational age (SGA), as assessed after birth, is the most commonly used surrogate measure for this outcome. The degree of SGA is associated with the likelihood of FGR; 30% of infants with a birthweight < 10th centile are thought to be FGR, while 70% of infants with a birthweight < 3rd centile are thought to be FGR. Critically, SGA is the most significant antenatal risk factor for a stillborn infant. Correct identification of SGA infants is associated with a reduction in the perinatal mortality rate. However, currently used tests, such as measurement of symphysis-fundal height, have a low reported sensitivity and specificity for the identification of SGA infants. OBJECTIVES The primary objective was to assess and compare the diagnostic accuracy of ultrasound assessment of fetal growth by estimated fetal weight (EFW) and placental biomarkers alone and in any combination used after 24 weeks of pregnancy in the identification of placental dysfunction as evidenced by either stillbirth, or birth of a SGA infant. Secondary objectives were to investigate the effect of clinical and methodological factors on test performance. SEARCH METHODS We developed full search strategies with no language or date restrictions. The following sources were searched: MEDLINE, MEDLINE In Process and Embase via Ovid, Cochrane (Wiley) CENTRAL, Science Citation Index (Web of Science), CINAHL (EBSCO) with search strategies adapted for each database as required; ISRCTN Registry, UK Clinical Trials Gateway, WHO International Clinical Trials Portal and ClinicalTrials.gov for ongoing studies; specialist abstract and conference proceeding resources (British Library's ZETOC and Web of Science Conference Proceedings Citation Index). Search last conducted in Ocober 2016. SELECTION CRITERIA We included studies of pregnant women of any age with a gestation of at least 24 weeks if relevant outcomes of pregnancy (live birth/stillbirth; SGA infant) were assessed. Studies were included irrespective of whether pregnant women were deemed to be low or high risk for complications or were of mixed populations (low and high risk). Pregnancies complicated by fetal abnormalities and multi-fetal pregnancies were excluded as they have a higher risk of stillbirth from non-placental causes. With regard to biochemical tests, we included assays performed using any technique and at any threshold used to determine test positivity. DATA COLLECTION AND ANALYSIS We extracted the numbers of true positive, false positive, false negative, and true negative test results from each study. We assessed risk of bias and applicability using the QUADAS-2 tool. Meta-analyses were performed using the hierarchical summary ROC model to estimate and compare test accuracy. MAIN RESULTS We included 91 studies that evaluated seven tests - blood tests for human placental lactogen (hPL), oestriol, placental growth factor (PlGF) and uric acid, ultrasound EFW and placental grading and urinary oestriol - in a total of 175,426 pregnant women, in which 15,471 pregnancies ended in the birth of a small baby and 740 pregnancies which ended in stillbirth. The quality of included studies was variable with most domains at low risk of bias although 59% of studies were deemed to be of unclear risk of bias for the reference standard domain. Fifty-three per cent of studies were of high concern for applicability due to inclusion of only high- or low-risk women.Using all available data for SGA (86 studies; 159,490 pregnancies involving 15,471 SGA infants), there was evidence of a difference in accuracy (P < 0.0001) between the seven tests for detecting pregnancies that are SGA at birth. Ultrasound EFW was the most accurate test for detecting SGA at birth with a diagnostic odds ratio (DOR) of 21.3 (95% CI 13.1 to 34.6); hPL was the most accurate biochemical test with a DOR of 4.78 (95% CI 3.21 to 7.13). In a hypothetical cohort of 1000 pregnant women, at the median specificity of 0.88 and median prevalence of 19%, EFW, hPL, oestriol, urinary oestriol, uric acid, PlGF and placental grading will miss 50 (95% CI 32 to 68), 116 (97 to 133), 124 (108 to 137), 127 (95 to 152), 139 (118 to 154), 144 (118 to 161), and 144 (122 to 161) SGA infants, respectively. For the detection of pregnancies ending in stillbirth (21 studies; 100,687 pregnancies involving 740 stillbirths), in an indirect comparison of the four biochemical tests, PlGF was the most accurate test with a DOR of 49.2 (95% CI 12.7 to 191). In a hypothetical cohort of 1000 pregnant women, at the median specificity of 0.78 and median prevalence of 1.7%, PlGF, hPL, urinary oestriol and uric acid will miss 2 (95% CI 0 to 4), 4 (2 to 8), 6 (6 to 7) and 8 (3 to 13) stillbirths, respectively. No studies assessed the accuracy of ultrasound EFW for detection of pregnancy ending in stillbirth. AUTHORS' CONCLUSIONS Biochemical markers of placental dysfunction used alone have insufficient accuracy to identify pregnancies ending in SGA or stillbirth. Studies combining U and placental biomarkers are needed to determine whether this approach improves diagnostic accuracy over the use of ultrasound estimation of fetal size or biochemical markers of placental dysfunction used alone. Many of the studies included in this review were carried out between 1974 and 2016. Studies of placental substances were mostly carried out before 1991 and after 2013; earlier studies may not reflect developments in test technology.

/pdf/biochemical-tests-of-placental-function-versus-ultrasound-1i6a333yak.pdf

Biochemical tests of placental function versus ultrasound assessment of fetal size for stillbirth and small-for-gestational-age infants

The strategy of intellectual collaboration has accelerated modern research and research success. Identified by Professor Robert Adams in 2013 as the Fourth Age of Research collaboration is evident through ever increasing numbers of international multicenter publications. These tend to provide positive benefits in terms of citation; indeed Universities with a lower percentage of home grown papers have higher research incomes.1 The European Commission has placed collaboration at the heart of its research strategy and reported on the economic benefits. Emerging economies such as those of South America have also recognized the benefit of international collaboration.2 Much of the effort has been bottom up, that is, through researcher led collaborations, such as in the field of genetics, for example, genomics. Cancer, diabetes mellitus, and Alzheimer disease research3 have all benefited through extensive collaborative efforts.

We have developed a consortium to emulate the best of this collaborative spirit, known as Global Pregnancy Collaboration (CoLab). CoLab, from its inception in 2010 has focused on adverse pregnancy outcomes and achieving a better understanding of their causes (online-only Data Supplement). Here, we review the pathologies we seek to understand and explain why better understanding mandates a global network of scientific and clinical experience. We present preeclampsia as a prototypical disorder but similar networks and collaboration are mandatory for understanding all human disease and, in particular, rare disorders. We highlight some of the challenges to collaborative studies, despite the overarching view, with supporting evidence, that this approach benefits all, and is to be encouraged. These challenges are not isolated to our discipline. We seek to bring attention to common hindrances, drawn from experiences within the CoLab consortium and suggest possible solutions.

### Preeclampsia: Potential for Gain From Collaboration

Adverse pregnancy outcomes such as preeclampsia, preterm labor, stillbirth, and fetal growth restriction continue to be major causes of morbidity and mortality …

Collaboration to Understand Complex Diseases: Preeclampsia and Adverse Pregnancy Outcomes.

[94-OR]: Extending the scope of individual patient data meta-analyses: Merging algorithms for biomarker measurements from heterogeneous laboratory platforms. The CoLAB Preeclampsia angiogenic factor study.

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[94-OR]: Extending the scope of individual patient data meta-analyses: Merging algorithms for biomarker measurements from heterogeneous laboratory platforms. The CoLAB Preeclampsia angiogenic factor study.