Louise C. Kenny

Higher risk of offspring schizophrenia following antenatal maternal exposure to severe adverse life events.

CONTEXT Most societies believe that a mothers psychological state can influence her unborn baby. Severe adverse life events during pregnancy have been consistently associated with an elevated risk of low birth weight and prematurity. Such events during the first trimester have also been associated with risk of congenital malformations. OBJECTIVE To assess the effect in offspring of antenatal maternal exposure to an objective measure of stress on risk of adverse neurodevelopment, specifically schizophrenia. We hypothesized that the strongest relationship would be to maternal exposures during the first trimester. DESIGN Population-based study. SETTING Denmark. PARTICIPANTS In a cohort of 1.38 million Danish births from 1973 to 1995, mothers were considered exposed if 1 (or more) of their close relatives died or was diagnosed with cancer, acute myocardial infarction, or stroke syndrome up to 6 months before conception or during pregnancy. Offspring were followed up from their 10th birthday until their death, migration, onset of schizophrenia, or June 30, 2005; admissions were identified by linkage to the Central Psychiatric Register. Main Outcome Measure Schizophrenia. RESULTS The risk of schizophrenia and related disorders was raised in offspring whose mothers were exposed to death of a relative during the first trimester (adjusted relative risk, 1.67 [95% confidence interval, 1.02-2.73]). Death of a relative during other trimesters or up to 6 months before pregnancy were not linked with a higher risk of schizophrenia. CONCLUSIONS Our population-based study suggests that severe stress to a mother during the first trimester may alter the risk of schizophrenia in offspring. This finding is consistent with ecological evidence from whole populations exposed to severe stressors and suggests that environment may influence neurodevelopment at the feto-placental-maternal interface.

Clinical risk prediction for pre-eclampsia in nulliparous women: development of model in international prospective cohort

Objectives To develop a predictive model for pre-eclampsia based on clinical risk factors for nulliparous women and to identify a subgroup at increased risk, in whom specialist referral might be indicated. Design Prospective multicentre cohort. Setting Five centres in Auckland, New Zealand; Adelaide, Australia; Manchester and London, United Kingdom; and Cork, Republic of Ireland. Participants 3572 “healthy” nulliparous women with a singleton pregnancy from a large international study; data on pregnancy outcome were available for 3529 (99%). Main outcome measure Pre-eclampsia defined as ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg, or both, on at least two occasions four hours apart after 20 weeks’ gestation but before the onset of labour, or postpartum, with either proteinuria or any multisystem complication. Preterm pre-eclampsia was defined as women with pre-eclampsia delivered before 37+0 weeks’ gestation. In the stepwise logistic regression the comparison group was women without pre-eclampsia. Results Of the 3529 women, 186 (5.3%) developed pre-eclampsia, including 47 (1.3%) with preterm pre-eclampsia. Clinical risk factors at 14-16 weeks’ gestation were age, mean arterial blood pressure, body mass index (BMI), family history of pre-eclampsia, family history of coronary heart disease, maternal birth weight, and vaginal bleeding for at least five days. Factors associated with reduced risk were a previous single miscarriage with the same partner, taking at least 12 months to conceive, high intake of fruit, cigarette smoking, and alcohol use in the first trimester. The area under the receiver operating characteristics curve (AUC), under internal validation, was 0.71. Addition of uterine artery Doppler indices did not improve performance (internal validation AUC 0.71). A framework for specialist referral was developed based on a probability of pre-eclampsia generated by the model of at least 15% or an abnormal uterine artery Doppler waveform in a subset of women with single risk factors. Nine per cent of nulliparous women would be referred for a specialist opinion, of whom 21% would develop pre-eclampsia. The relative risk for developing pre-eclampsia and preterm pre-eclampsia in women referred to a specialist compared with standard care was 5.5 and 12.2, respectively. Conclusions The ability to predict pre-eclampsia in healthy nulliparous women using clinical phenotype is modest and requires external validation in other populations. If validated, it could provide a personalised clinical risk profile for nulliparous women to which biomarkers could be added. Trial registration ACTRN12607000551493.

Advanced maternal age and adverse pregnancy outcome: evidence from a large contemporary cohort.

Background Recent decades have witnessed an increase in mean maternal age at childbirth in most high-resourced countries. Advanced maternal age has been associated with several adverse maternal and perinatal outcomes. Although there are many studies on this topic, data from large contemporary population-based cohorts that controls for demographic variables known to influence perinatal outcomes is limited. Methods We performed a population-based cohort study using data on all singleton births in 2004–2008 from the North Western Perinatal Survey based at The University of Manchester, UK. We compared pregnancy outcomes in women aged 30–34, 35–39 and ≥40 years with women aged 20–29 years using log-linear binomial regression. Models were adjusted for parity, ethnicity, social deprivation score and body mass index. Results The final study cohort consisted of 215,344 births; 122,307 mothers (54.19%) were aged 20–29 years, 62,371(27.63%) were aged 30–34 years, 33,966(15.05%) were aged 35–39 years and 7,066(3.13%) were aged ≥40 years. Women aged 40+ at delivery were at increased risk of stillbirth (RR = 1.83, [95% CI 1.37–2.43]), pre-term (RR = 1.25, [95% CI: 1.14–1.36]) and very pre-term birth (RR = 1.29, [95% CI:1.08–1.55]), Macrosomia (RR = 1.31, [95% CI: 1.12–1.54]), extremely large for gestational age (RR = 1.40, [95% CI: 1.25–1.58]) and Caesarean delivery (RR = 1.83, [95% CI: 1.77–1.90]). Conclusions Advanced maternal age is associated with a range of adverse pregnancy outcomes. These risks are independent of parity and remain after adjusting for the ameliorating effects of higher socioeconomic status. The data from this large contemporary cohort will be of interest to healthcare providers and women and will facilitate evidence based counselling of older expectant mothers.

Metabolic profiling of serum using Ultra Performance Liquid Chromatography and the LTQ-Orbitrap mass spectrometry system

Advances in analytical instrumentation can provide significant advantages to the volume and quality of biological knowledge acquired in metabolomic investigations. The interfacing of sub-2 microm liquid chromatography (UPLC ACQUITY) and LTQ-Orbitrap mass spectrometry systems provides many theoretical advantages. The applicability of the interfaced systems was investigated using a simple 11-component metabolite mix and a complex mammalian biofluid, serum. Metabolites were detected in the metabolite mix with signals that were linear with their concentration over 2.5-3.5 orders of magnitude, with correlation coefficients greater than 0.993 and limits of detection less than 1 micromol L(-1). Reproducibility of retention time (RSD<3%) and chromatographic peak area (RSD<15%) and a high mass accuracy (<2 ppm) were observed for 14 QC serum samples interdispersed with other serum samples, analysed over a period of 40 h. The evaluation of a single deconvolution software package (XCMS) was performed and showed that two parameters (snthresh and bw) provided significant changes to the number of peaks detected and the peak area reproducibility for the dataset used. The data were used to indicate possible biomarkers of pre-eclampsia and showed both the instruments and XCMS to be applicable to the reproducible and valid detection of disease biomarkers present in serum.

Diagnostic Accuracy of Placental Growth Factor in Women With Suspected Preeclampsia A Prospective Multicenter Study

Background— Hypertensive disorders of pregnancy are a major contributor to death and disability for pregnant women and their infants. The diagnosis of preeclampsia by using blood pressure and proteinuria is of limited use because they are tertiary, downstream features of the disease. Placental growth factor (PlGF) is an angiogenic factor, a secondary marker of associated placental dysfunction in preeclampsia, with known low plasma concentrations in the disease. Methods and Results— In a prospective multicenter study, we studied the diagnostic accuracy of low plasma PlGF concentration (<5th centile for gestation, Alere Triage assay) in women presenting with suspected preeclampsia between 20 and 35 weeks’ gestation (and up to 41 weeks’ gestation as a secondary analysis). The outcome was delivery for confirmed preeclampsia within 14 days. Of 625 women, 346 (55%) developed confirmed preeclampsia. In 287 women enrolled before 35 weeks’ gestation, PlGF <5th centile had high sensitivity (0.96; 95% confidence interval, 0.89–0.99) and negative predictive value (0.98; 0.93–0.995) for preeclampsia within 14 days; specificity was lower (0.55; 0.48–0.61). Area under the receiver operating characteristic curve for low PlGF (0.87, standard error 0.03) for predicting preeclampsia within 14 days was greater than all other commonly used tests, singly or in combination (range, 0.58–0.76), in women presenting with suspected preeclampsia (P<0.001 for all comparisons). Conclusions— In women presenting before 35 weeks’ gestation with suspected preeclampsia, low PlGF has high sensitivity and negative predictive value for preeclampsia within 14 days, is better than other currently used tests, and presents an innovative adjunct to management of such women.

Early pregnancy prediction of preeclampsia in nulliparous women, combining clinical risk and biomarkers: the Screening for Pregnancy Endpoints (SCOPE) international cohort study

More than half of all cases of preeclampsia occur in healthy first-time pregnant women. Our aim was to develop a method to predict those at risk by combining clinical factors and measurements of biomarkers in women recruited to the Screening for Pregnancy Endpoints (SCOPE) study of low-risk nulliparous women. Forty-seven biomarkers identified on the basis of (1) association with preeclampsia, (2) a biological role in placentation, or (3) a role in cellular mechanisms involved in the pathogenesis of preeclampsia were measured in plasma sampled at 14 to 16 weeks’ gestation from 5623 women. The cohort was randomly divided into training (n=3747) and validation (n=1876) cohorts. Preeclampsia developed in 278 (4.9%) women, of whom 28 (0.5%) developed early-onset preeclampsia. The final model for the prediction of preeclampsia included placental growth factor, mean arterial pressure, and body mass index at 14 to 16 weeks’ gestation, the consumption of ≥3 pieces of fruit per day, and mean uterine artery resistance index. The area under the receiver operator curve (95% confidence interval) for this model in training and validation cohorts was 0.73 (0.70–0.77) and 0.68 (0.63–0.74), respectively. A predictive model of early-onset preeclampsia included angiogenin/placental growth factor as a ratio, mean arterial pressure, any pregnancy loss <10 weeks, and mean uterine artery resistance index (area under the receiver operator curve [95% confidence interval] in training and validation cohorts, 0.89 [0.78–1.0] and 0.78 [0.58–0.99], respectively). Neither model included pregnancy-associated plasma protein A, previously reported to predict preeclampsia in populations of mixed parity and risk. In nulliparous women, combining multiple biomarkers and clinical data provided modest prediction of preeclampsia. # Novelty and Significance {#article-title-41}More than half of all cases of preeclampsia occur in healthy first-time pregnant women. Our aim was to develop a method to predict those at risk by combining clinical factors and measurements of biomarkers in women recruited to the Screening for Pregnancy Endpoints (SCOPE) study of low-risk nulliparous women. Forty-seven biomarkers identified on the basis of (1) association with preeclampsia, (2) a biological role in placentation, or (3) a role in cellular mechanisms involved in the pathogenesis of preeclampsia were measured in plasma sampled at 14 to 16 weeks’ gestation from 5623 women. The cohort was randomly divided into training (n=3747) and validation (n=1876) cohorts. Preeclampsia developed in 278 (4.9%) women, of whom 28 (0.5%) developed early-onset preeclampsia. The final model for the prediction of preeclampsia included placental growth factor, mean arterial pressure, and body mass index at 14 to 16 weeks’ gestation, the consumption of ≥3 pieces of fruit per day, and mean uterine artery resistance index. The area under the receiver operator curve (95% confidence interval) for this model in training and validation cohorts was 0.73 (0.70–0.77) and 0.68 (0.63–0.74), respectively. A predictive model of early-onset preeclampsia included angiogenin/placental growth factor as a ratio, mean arterial pressure, any pregnancy loss <10 weeks, and mean uterine artery resistance index (area under the receiver operator curve [95% confidence interval] in training and validation cohorts, 0.89 [0.78–1.0] and 0.78 [0.58–0.99], respectively). Neither model included pregnancy-associated plasma protein A, previously reported to predict preeclampsia in populations of mixed parity and risk. In nulliparous women, combining multiple biomarkers and clinical data provided modest prediction of preeclampsia.

Reduced infant birthweight consequent upon maternal exposure to severe life events.

Objective: To investigate the association between maternal exposure to severe life events and fetal growth (birthweight and small for gestational age). Stress has been associated with adverse pregnancy outcome. Methods: Mothers of 1.38 million singleton live births in Denmark between January 1, 1979 and December 31, 2002 were linked to information on their spouses, parents, siblings, and older children. Exposure was defined as death or serious illness in a relative during pregnancy or in the 6 months before conception. Linear regression was used to examine the effect of exposure on birthweight. Log-linear binomial regression was used to assess the effect of exposure on small for gestational age. Results: Death of a relative during pregnancy or in the 6 months before conception reduced birthweight by 27 g (adjusted estimate −27 g, 95% Confidence Interval (CI) = −33, −22). There was a significant association between maternal exposure to death of a relative and risk of a baby weighing below the 10th percentile (adjusted relative risk (RR) = 1.17, 95% CI = 1.13, 1.22) and 5th percentile (adjusted RR = 1.22, 95% CI = 1.15, 1.29). Conclusions: Mothers exposed to severe life events before conception or during pregnancy have babies with significantly lower birthweight. If this association is causal, the potential mechanisms of stress-related effects on birthweight include changes in lifestyle due to the exposure and stress-related dysregulation of the hypothalamic-pituitary-adrenal axis during pregnancy. IUGR = intrauterine growth restriction; CVA = cerebrovascular accident; AMI = acute myocardial infarction; SGA = small for gestational age; VSGA = very small for gestational age; GHQ = general health questionnaire; SES = socioeconomic status.

Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning

Pre-eclampsia is a multi-system disorder of pregnancy with major maternal and perinatal implications. Emerging therapeutic strategies are most likely to be maximally effective if commenced weeks or even months prior to the clinical presentation of the disease. Although widespread plasma alterations precede the clinical onset of pre-eclampsia, no single plasma constituent has emerged as a sensitive or specific predictor of risk. Consequently, currently available methods of identifying the condition prior to clinical presentation are of limited clinical use. We have exploited genetic programming, a powerful data mining method, to identify patterns of metabolites that distinguish plasma from patients with pre-eclampsia from that taken from healthy, matched controls. High-resolution gas chromatography time-of-flight mass spectrometry (GC-tof-MS) was performed on 87 plasma samples from women with pre-eclampsia and 87 matched controls. Normalised peak intensity data were fed into the Genetic Programming (GP) system which was set up to produce a model that gave an output of 1 for patients and 0 for controls. The model was trained on 50% of the data generated and tested on a separate hold-out set of 50%. The model generated by GP from the GC-tof-MS data identified a metabolomic pattern that could be used to produce two simple rules that together discriminate pre-eclampsia from normal pregnant controls using just 3 of the metabolite peak variables, with a sensitivity of 100% and a specificity of 98%. Thus, pre-eclampsia can be diagnosed at the level of small-molecule metabolism in blood plasma. These findings justify a prospective assessment of metabolomic technology as a screening tool for pre-eclampsia, while identification of the metabolites involved may lead to an improved understanding of the aetiological basis of pre-eclampsia and thus the development of targeted therapies.

Risk factors for small-for-gestational-age infants by customised birthweight centiles: data from an international prospective cohort study

Please cite this paper as: McCowan L, Roberts C, Dekker G, Taylor R, Chan E, Kenny L, Baker P, Moss‐Morris R, Chappell L, North R on behalf of the SCOPE consortium. Risk factors for small‐for‐gestational‐age infants by customised birthweight centiles: data from an international prospective cohort study. BJOG 2010;117:1599–1607.

Animal models of preeclampsia; uses and limitations

Preeclampsia remains a leading cause of maternal and fetal morbidity and mortality and has an unknown etiology. The limited progress made regarding new treatments to reduce the incidence and severity of preeclampsia has been attributed to the difficulties faced in the development of suitable animal models for the mechanistic research of this disease. In addition, animal models need hypotheses on which to be based and the slow development of testable hypotheses has also contributed to this poor progress. The past decade has seen significant advances in our understanding of preeclampsia and the development of viable reproducible animal models has contributed significantly to these advances. Although many of these models have features of preeclampsia, they are still poor overall models of the human disease and limited due to lack of reproducibility and because they do not include the complete spectrum of pathophysiological changes associated with preeclampsia. This review aims to provide a succinct and comprehensive assessment of current animal models of preeclampsia, their uses and limitations with particular attention paid to the best validated and most comprehensive models, in addition to those models which have been utilized to investigate potential therapeutic interventions for the treatment or prevention of preeclampsia.