Serum Hydroxysteroid (17beta) dehydrogenase 1 concentration in pregnant women correlates with pregnancy-associated plasma protein a but does not serve as an independent marker for preeclampsia.

Hydroxysteroid (17beta) dehydrogenase 1 (HSD17B1) is a steroid synthetic enzyme expressed in ovarian granulosa cells and placental syncytiotrophoblasts. Here, HSD17B1 serum concentration was measured with a validated immuno assay during pregnancy at three time points (12-14, 18-20 and 26-28 weeks of gestation). The concentration increased 2.5-fold (p < 0.0001) and 1.7-fold (p = 0.0019) during the follow-up period for control women and women who later developed preeclampsia (PE), respectively, and a significant difference was observed at weeks 26-28 (p = 0.0266). HSD17B1 concentration at all the three time points positively correlated with serum PAPPA measured at the first time point (first time point r = 0.38, p = 1.1x10-10; second time point r = 0.27, p = 5.9x10-6 and third timepoint r = 0.26, p = 2.3x10-5). No correlation was observed between HSD17B1 and placental growth factor (PLGF). Serum HSD17B1, furthermore, negatively correlated with the mother's weight and body mass index (BMI), mirroring the pattern observed for PAPPA. The univariable logistic regression identified a weak association between HSD17B1 at 26-28 weeks and later development of PE (P = 0.04). Also, the best multivariable model obtained using penalized logistic regression with stable iterative variable selection at 26-28 weeks included HSD17B1, together with PLGF, PAPPA and the mother's BMI. While the area under the ROC curve of the model was higher than that of the adjusted PLGF, the difference was not statistically significant. In summary, the serum concentration of HSD17B1 correlated with PAPPA, another protein expressed in syncytiotrophoblasts, and with mother's weight and BMI but could not be considered as an independent marker for PE.

Associations of polymetabolic risk of high maternal pre-pregnancy body mass index with pregnancy complications, birth outcomes, and early childhood neurodevelopment: findings from two pregnancy cohorts.

BACKGROUND: A substantial proportion of maternal pregnancy complications, adverse birth outcomes and neurodevelopmental delay in children may be attributable to high maternal pre-pregnancy Body Mass Index (BMI). However, BMI alone is insufficient for the identification of all at-risk mothers and children as many women with non-obesity(< 30 kg/m2) or normal weight(18.5-24.99 kg/m2) and their children may suffer from adversities. Evidence suggests that BMI-related metabolic changes during pregnancy may predict adverse mother-child outcomes better than maternal anthropometric BMI. METHODS: In a cohort of 425 mother-child dyads, we identified maternal BMI-defined metabolome based on associations of 95 metabolic measures measured three times during pregnancy with maternal pre-pregnancy BMI. We then examined whether maternal BMI-defined metabolome performed better than anthropometric BMI in predicting gestational diabetes, hypertensive disorders, gestational weight gain (GWG), Caesarian section delivery, child gestational age and weight at birth, preterm birth, admission to neonatal intensive care unit (NICU), and childhood neurodevelopment. Based on metabolic measures with the highest contributions to BMI-defined metabolome, including inflammatory and glycolysis-related measures, fatty acids, fluid balance, ketone bodies, lipids and amino acids, we created a set of maternal high BMI-related polymetabolic risk scores (PMRSs), and in an independent replication cohort of 489 mother-child dyads tested their performance in predicting the same set of mother-child outcomes in comparison to anthropometric BMI. RESULTS: BMI-defined metabolome predicted all of the studied mother-child outcomes and improved their prediction over anthropometric BMI, except for gestational hypertension and GWG. BMI-related PMRSs predicted gestational diabetes, preeclampsia, Caesarian section delivery, admission to NICU, lower gestational age at birth, lower cognitive development score of the child, and improved their prediction over anthropometric BMI. BMI-related PMRSs predicted gestational diabetes, preeclampsia, Caesarean section delivery, NICU admission and child's lower gestational age at birth even at the levels of maternal non-obesity and normal weight. CONCLUSIONS: Maternal BMI-defined metabolome improves the prediction of pregnancy complications, birth outcomes, and neurodevelopment in children over anthropometric BMI. The novel, BMI-related PMRSs generated based on the BMI-defined metabolome have the potential to become biomarkers identifying at-risk mothers and their children for timely targeted interventions even at the level of maternal non-obesity and normal weight.

Positive maternal mental health during pregnancy and psychiatric problems in children from early childhood to late childhood.

Negative maternal mental health during pregnancy increases the risk of psychiatric problems in children, but research on the potential benefits of positive maternal mental health during pregnancy is scarce. We investigated associations between positive maternal mental health composite score, based on reports of maternal positive affect, curiosity, and social support during pregnancy, and children's psychiatric problems (Child Behavior Checklist) at ages 1.9-5.9 and 7.1-12.1 years among 2636 mother-child dyads of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study. For each standard deviation higher positive maternal mental health score during pregnancy, total psychiatric problems were 1.37 (95% confidence interval (CI) -1.79,-0.95) t-scores lower in early childhood and 1.75 (95% CI -2.24,-1.26) t-scores lower in late childhood. These associations were independent of covariates and of negative maternal mental health. Total psychiatric problems remained stably lower from early childhood to late childhood in children of mothers with higher positive mental health during pregnancy, whereas they increased in children of mothers with lower positive mental health. Positive maternal mental health in child's late childhood partially mediated the effects of positive maternal mental health during pregnancy on children's psychiatric problems. Supporting positive maternal mental health may benefit mothers and children.

Metabolomic Profiles of Nonobese and Obese Women With Gestational Diabetes.

CONTEXT: In non-pregnant population, nonobese individuals with obesity-related metabolome have increased risk for type 2 diabetes and cardiovascular diseases. The risk of these diseases is also increased after gestational diabetes. OBJECTIVE: This work aimed to examine whether nonobese (body mass index [BMI] < 30) and obese (BMI ≥ 30) women with gestational diabetes mellitus (GDM) and obese non-GDM women differ in metabolomic profiles from nonobese non-GDM controls. METHODS: Levels of 66 metabolic measures were assessed in early (median 13, IQR 12.4-13.7 gestation weeks), and across early, mid (20, 19.3-23.0), and late (28, 27.0-35.0) pregnancy blood samples in 755 pregnant women from the PREDO and RADIEL studies. The independent replication cohort comprised 490 pregnant women. RESULTS: Nonobese and obese GDM, and obese non-GDM women differed similarly from the controls across early, mid, and late pregnancy in 13 measures, including very low-density lipoprotein-related measures, and fatty acids. In 6 measures, including fatty acid (FA) ratios, glycolysis-related measures, valine, and 3-hydroxybutyrate, the differences between obese GDM women and controls were more pronounced than the differences between nonobese GDM or obese non-GDM women and controls. In 16 measures, including HDL-related measures, FA ratios, amino acids, and inflammation, differences between obese GDM or obese non-GDM women and controls were more pronounced than the differences between nonobese GDM women and controls. Most differences were evident in early pregnancy, and in the replication cohort were more often in the same direction than would be expected by chance alone. CONCLUSION: Differences between nonobese and obese GDM, or obese non-GDM women and controls in metabolomic profiles may allow detection of high-risk women for timely targeted preventive interventions.

Positive maternal mental health during pregnancy and mental and behavioral disorders in children: A prospective pregnancy cohort study.

BACKGROUND: The role of positive maternal mental health during pregnancy in child mental health remains largely unknown. We investigated whether positive maternal mental health during pregnancy is associated with lower hazards of mental and behavioral disorders in children and mitigates the adverse effects of negative maternal mental health. METHODS: Among 3,378 mother-child dyads of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study, mothers reported their positive mental health biweekly throughout pregnancy with the Positive and Negative Affect Schedule, the Spielberger State Anxiety Inventory Curiosity scale, and a visual analogue scale for social support, and negative mental health with the Center for Epidemiologic Studies Depression Scale. We extracted data on their mental and behavioral disorder diagnoses from a nationwide medical register. This register provided data on their children's mental and behavioral disorder diagnoses as well, from birth until 8.4-12.8 (Median = 10.2, Interquartile Range 9.7-10.8) years of age. RESULTS: A positive maternal mental health composite score during pregnancy was associated with a lower hazard of any mental and behavioral disorder among all children [Hazard Ratio (HR) = 0.79, 95% Confidence Interval (CI) 0.71 - 0.87] and among children of mothers experiencing clinically relevant depressive symptoms during pregnancy [HR = 0.80, 95%CI 0.64 - 1.00] and/or mental and behavioral disorders before or during pregnancy [HR = 0.69, 95%CI 0.55-0.86]. These associations were independent of covariates. CONCLUSIONS: Children whose mothers had more positive mental health during pregnancy were less likely to develop mental and behavioral disorders. Protective effects were seen also among children of mothers facing mental health adversities before or during pregnancy.

Maternal early-pregnancy body mass index-associated metabolomic component and mental and behavioral disorders in children.

Maternal pre-pregnancy obesity and/or higher body mass index (BMI) have been associated with neurodevelopmental and mental health adversities in children. While maternal metabolomic perturbations during pregnancy may underpin these associations, the existing evidence is limited to studying individual metabolites, not capturing metabolic variation specific to maternal BMI, and not accounting for the correlated nature of the metabolomic measures. By using multivariate supervised analytical methods, we first identified maternal early-pregnancy BMI-associated metabolomic component during pregnancy. We then examined whether this component was associated with mental and behavioral disorders in children, improved the prediction of the child outcomes over maternal BMI, and what proportion of the effect of maternal BMI on the child outcomes this component mediated. Early-pregnancy BMI of 425 mothers participating in the PREDO study was extracted from the national Medical Birth Register. During pregnancy, mothers donated up to three blood samples, from which a targeted panel of 68 metabolites were measured. Mental and behavioral disorders in children followed-up from birth until 8.4-12.8 years came from the Care Register for Health Care. Of the 68 metabolites averaged across the three sampling points, 43 associated significantly with maternal early-pregnancy BMI yielding a maternal early-pregnancy BMI-associated metabolomic component (total variance explained, 55.4%; predictive ability, 52.0%). This metabolomic component was significantly associated with higher hazard of any mental and behavioral disorder [HR 1.45, 95%CI(1.15, 1.84)] and relative risk of having a higher number of co-morbid disorders [RR 1.43, 95%CI(1.12, 1.69)] in children. It improved the goodness-of-model-fit over maternal BMI by 37.7-65.6%, and hence the predictive significance of the model, and mediated 60.8-75.8% of the effect of maternal BMI on the child outcomes. Maternal BMI-related metabolomic perturbations during pregnancy are associated with a higher risk of mental and behavioral disorders in children. These findings may allow identifying metabolomic targets for personalized interventions.

Reliability of a novel approach for reference-based cell type estimation in human placental DNA methylation studies.

The placenta is a central organ during early development, influencing trajectories of health and disease. DNA methylation (DNAm) studies of human placenta improve our understanding of how its function relates to disease risk. However, DNAm studies can be biased by cell type heterogeneity, so it is essential to control for this in order to reduce confounding and increase precision. Computational cell type deconvolution approaches have proven to be very useful for this purpose. For human placenta, however, an assessment of the performance of these estimation methods is still lacking. Here, we examine the performance of a newly available reference-based cell type estimation approach and compare it to an often-used reference-free cell type estimation approach, namely RefFreeEWAS, in placental genome-wide DNAm samples taken at birth and from chorionic villus biopsies early in pregnancy using three independent studies comprising over 1000 samples. We found both reference-free and reference-based estimated cell type proportions to have predictive value for DNAm, however, reference-based cell type estimation outperformed reference-free estimation for the majority of data sets. Reference-based cell type estimations mirror previous histological knowledge on changes in cell type proportions through gestation. Further, CpGs whose variation in DNAm was largely explained by reference-based estimated cell type proportions were in the proximity of genes that are highly tissue-specific for placenta. This was not the case for reference-free estimated cell type proportions. We provide a list of these CpGs as a resource to help researchers to interpret results of existing studies and improve future DNAm studies of human placenta.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Maternal postpartum depressive symptoms partially mediate the association between preterm birth and mental and behavioral disorders in children.

Preterm birth has been linked with postpartum depressive (PPD) disorders and high symptom levels, but evidence remains conflicting and limited in quality. It remains unclear whether PPD symptoms of mothers with preterm babies were already elevated before childbirth, and whether PPD symptoms mediate/aggravate the effect of preterm birth on child mental disorders. We examined whether preterm birth associated with maternal PPD symptoms, depressive symptoms trajectories from antenatal to postpartum stage, and whether PPD symptoms mediated/aggravated associations between preterm birth and child mental disorders. Mothers of preterm (n = 125) and term-born (n = 3033) children of the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study reported depressive symptoms four times within 8 weeks before and twice within 12 months after childbirth. Child mental and behavioral disorder diagnoses until age 8.4-12.8 years came from medical register. Preterm birth associated with higher PPD symptoms (mean difference = 0.19 SD, 95% CI 0.01, 0.37, p = 0.04), and higher odds (odds ratio = 2.23, 95% CI 1.22, 4.09, p = 0.009) of the mother to belong to a group that had consistently high depressive symptoms levels trajectory from antenatal to postpartum stage. PPD symptoms partially mediated and aggravated the association between preterm birth and child mental disorders. Preterm birth, maternal PPD symptoms and child mental disorders are associated, calling for timely prevention interventions.

Longitudinal Metabolic Profiling of Maternal Obesity, Gestational Diabetes, and Hypertensive Pregnancy Disorders.

CONTEXT: Comprehensive assessment of metabolism in maternal obesity and pregnancy disorders can provide information about the shared maternal-fetal milieu and give insight into both maternal long-term health and intergenerational transmission of disease burden. OBJECTIVE: To assess levels, profiles, and change in the levels of metabolic measures during pregnancies complicated by obesity, gestational diabetes (GDM), or hypertensive disorders. DESIGN, SETTING AND PARTICIPANTS: A secondary analysis of 2 study cohorts, PREDO and RADIEL, including 741 pregnant women. MAIN OUTCOME MEASURES: We assessed 225 metabolic measures by nuclear magnetic resonance in blood samples collected at median 13 [interquartile range (IQR) 12.4-13.7], 20 (IQR 19.3-23.0), and 28 (27.0-35.0) weeks of gestation. RESULTS: Across all 3 time points women with obesity [body mass index (BMI) ≥ 30kg/m2] in comparison to normal weight (BMI 18.5-24.99 kg/m2) had significantly higher levels of most very-low-density lipoprotein-related measures, many fatty and most amino acids, and more adverse metabolic profiles. The change in the levels of most metabolic measures during pregnancy was smaller in obese than in normal weight women. GDM, preeclampsia, and chronic hypertension were associated with metabolic alterations similar to obesity. The associations of obesity held after adjustment for GDM and hypertensive disorders, but many of the associations with GDM and hypertensive disorders were rendered nonsignificant after adjustment for BMI and the other pregnancy disorders. CONCLUSIONS: This study shows that the pregnancy-related metabolic change is smaller in women with obesity, who display metabolic perturbations already in early pregnancy. Metabolic alterations of obesity and pregnancy disorders resembled each other suggesting a shared metabolic origin.

Serum Inhibin-A and PAPP-A2 in the prediction of pre-eclampsia during the first and second trimesters in high-risk women.

OBJECTIVES: Maternal serum inhibin-A, pregnancy associated plasma protein-A (PAPP-A) and PAPP-A2 together with placental growth factor (PlGF), maternal risk factors and uterine artery pulsatility index (UtA PI) were analysed to study their ability to predict pre-eclampsia (PE). STUDY DESIGN: Serial serum samples for the nested case-control study were collected prospectively at 12-14, 18-20 and 26-28 weeks of gestation from 11 women who later developed early-onset PE (EO PE, diagnosis < 34 + 0 weeks of gestation), 34 women who developed late-onset PE (LO PE, diagnosis ≥ 34 + 0 weeks) and 89 controls. MAIN OUTCOME MEASURES: Gestational age -adjusted multiples of the median (MoM) values were calculated for biomarker concentrations. Multivariate regression analyses were performed to combine first trimester biomarkers, previously reported results on PlGF, maternal risk factors and UtA PI. Area under curve (AUC) values and 95% confidence intervals (CIs) for the prediction of PE and its subtypes were calculated. RESULTS: A high first trimester inhibin-A predicted PE (AUC 0.618, 95%CI, 0.513-0.724), whereas PAPP-A and PlGF predicted only EO PE (0.701, 0.562-0.840 and 0.798, 0.686-0.909, respectively). At 26-28 weeks PAPP-A2 and inhibin-A predicted all PE subtypes. In the multivariate setting inhibin-A combined with maternal pre-pregnancy body mass index, prior PE and mean UtA PI predicted PE (0.811,0.726-0.896) and LO PE (0.824, 0.733-0.914). CONCLUSIONS: At first trimester inhibin-A show potential ability to predict not only EO PE but also LO PE whereas PlGF and PAPP-A predict only EO PE. At late second trimester inhibin-A and PAPP-A2 might be useful for short-term prediction of PE.

Characteristics of epigenetic aging across gestational and perinatal tissues.

BACKGROUND: Epigenetic clocks have been used to indicate differences in biological states between individuals of same chronological age. However, so far, only few studies have examined epigenetic aging in newborns-especially regarding different gestational or perinatal tissues. In this study, we investigated which birth- and pregnancy-related variables are most important in predicting gestational epigenetic age acceleration or deceleration (i.e., the deviation between gestational epigenetic age estimated from the DNA methylome and chronological gestational age) in chorionic villus, placenta and cord blood tissues from two independent study cohorts (ITU, n = 639 and PREDO, n = 966). We further characterized the correspondence of epigenetic age deviations between these tissues. RESULTS: Among the most predictive factors of epigenetic age deviations in single tissues were child sex, birth length, maternal smoking during pregnancy, maternal mental disorders until childbirth, delivery mode and parity. However, the specific factors related to epigenetic age deviation and the direction of association differed across tissues. In individuals with samples available from more than one tissue, relative epigenetic age deviations were not correlated across tissues. CONCLUSION: Gestational epigenetic age acceleration or deceleration was not related to more favorable or unfavorable factors in one direction in the investigated tissues, and the relative epigenetic age differed between tissues of the same person. This indicates that epigenetic age deviations associate with distinct, tissue specific, factors during the gestational and perinatal period. Our findings suggest that the epigenetic age of the newborn should be seen as a characteristic of a specific tissue, and less as a general characteristic of the child itself.

Maternal antenatal stress and mental and behavioral disorders in their children.

BACKGROUND: Maternal antenatal stress, including symptoms of depression, anxiety and perceived stress, is associated with mental and behavioral problems in children. Whether it is associated with child mental and behavioral disorders remains uncertain. We examined if maternal antenatal symptoms of depression, anxiety and perceived stress were associated with mental and behavioral disorders in their children, if the associations varied according to gestational week, stress type, fluctuating or consistently high symptoms, and if they were driven by maternal or paternal lifetime mood or anxiety disorders. METHODS: 3365 mothers participating in the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study completed the Center for Epidemiologic Studies Depression Scale, the State Anxiety Inventory and the Perceived Stress Scale up to 14 times throughout pregnancy. The Care Register for Health Care provided data on mental and behavioral (including neurodevelopmental) disorders for their children from birth (11/07/2006-07/24/2010) until 12/31/2016 and for parental lifetime mood and anxiety disorders until 12/31/2016. RESULTS: The hazard of any childhood mental and behavioral disorder (HR=1.91, 95% CI: 1.39-2.51) was significantly higher for children whose mothers reported consistently high in comparison to consistently low levels of all types of stress throughout pregnancy. The associations remained significant when adjusted for maternal and paternal lifetime mood and anxiety disorders (and their comorbidity and timing and mood disorder type). CONCLUSION: Maternal antenatal stress is associated with higher risk of childhood mental and behavioral disorders. Efforts to reduce maternal antenatal stress should be given a high priority to improve child mental health.

A polyepigenetic glucocorticoid exposure score at birth and childhood mental and behavioral disorders.

BACKGROUND: Maternal depression and anxiety during pregnancy may enhance fetal exposure to glucocorticoids (GCs) and harm neurodevelopment. We tested whether a novel cross-tissue polyepigenetic biomarker indicative of in utero exposure to GC is associated with mental and behavioral disorders and their severity in children, possibly mediating the associations between maternal prenatal depressive and anxiety symptoms and these child outcomes. METHODS: Children (n = 814) from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study were followed-up from birth to age 7.1-10.7 years. A weighted polyepigenetic GC exposure score was calculated based on the methylation profile of 24 CpGs from umbilical cord blood. Child diagnosis of mental and behavioral disorder (n = 99) and its severity, defined as the number of days the child had received treatment (all 99 had received outpatient treatment and 8 had been additionally in inpatient treatment) for mental or behavioral disorder as the primary diagnosis, came from the Care Register for Health Care. Mothers (n = 408) reported on child total behavior problems at child's age of 2.3-5.8 years and their own depressive and anxiety symptoms during pregnancy (n = 583). RESULTS: The fetal polyepigenetic GC exposure score at birth was not associated with child hazard of mental and behavioral disorder (HR = 0.82, 95% CI 0.54; 1.24, p = 0.35) or total behavior problems (unstandardized beta = -0.10, 95% CI -0.31; 0.10, p = 0.33). However, for one standard deviation decrease in the polyepigenetic score, the child had spent 2.94 (95%CI 1.59; 5.45, p < 0.001) more days in inpatient or outpatient treatment with any mental and behavioral disorder as the primary diagnosis. Criteria for mediation tests were not met. CONCLUSIONS: These findings suggest that fetal polyepigenetic GC exposure score at birth was not associated with any mental or behavioral disorder diagnosis or mother-rated total behavior problems, but it may contribute to identifying children at birth who are at risk for more severe mental or behavioral disorders.

Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. OBJECTIVES: To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. DESIGN: This was an individual participant data meta-analysis of cohort studies. SETTING: Source data from secondary and tertiary care. PREDICTORS: We identified predictors from systematic reviews, and prioritised for importance in an international survey. PRIMARY OUTCOMES: Early-onset (delivery at < 34 weeks' gestation), late-onset (delivery at ≥ 34 weeks' gestation) and any-onset pre-eclampsia. ANALYSIS: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I2 and τ2. A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. RESULTS: The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia. LIMITATIONS: Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data. CONCLUSION: For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. FUTURE WORK: Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate. STUDY REGISTRATION: This study is registered as PROSPERO CRD42015029349. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 72. See the NIHR Journals Library website for further project information.

WHAT IS THE PROBLEM?: Pre-eclampsia, a condition in pregnancy that results in raised blood pressure and protein in the urine, is a major cause of complications for the mother and baby. WHAT IS NEEDED?: A way of accurately identifying women at high risk of pre-eclampsia to allow clinicians to start preventative interventions such as administering aspirin or frequently monitoring women during pregnancy. WHERE ARE THE RESEARCH GAPS?: Although over 100 tools (models) have been reported worldwide to predict pre-eclampsia, to date their performance in women managed in the UK NHS is unknown. WHAT DID WE PLAN TO DO?: We planned to comprehensively identify all published models that predict the risk of pre-eclampsia occurring at any time during pregnancy and to assess if this prediction is accurate in the UK population. If the existing models did not perform satisfactorily, we aimed to develop new prediction models. WHAT DID WE FIND?: We formed the International Prediction of Pregnancy Complications network, which provided data from a large number of studies (78 studies, 25 countries, 125 researchers, 3,570,993 singleton pregnancies). We were able to assess the performance of 24 out of the 131 models published to predict pre-eclampsia in 11 UK data sets. The models did not accurately predict the risk of pre-eclampsia across all UK data sets, and their performance varied within individual data sets. We developed new prediction models that showed promising performance on average across all data sets, but their ability to correctly identify women who develop pre-eclampsia varied between populations. The models were more clinically useful when used in the care of first-time mothers pregnant with one child, compared to a strategy of treating them all as if they were at high-risk of pre-eclampsia. WHAT DOES THIS MEAN?: Before using the International Prediction of Pregnancy Complications models in various populations, they need to be adjusted for characteristics of the particular population and the setting of application.

External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. CONCLUSIONS: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice. TRIAL REGISTRATION: PROSPERO ID: CRD42015029349 .

Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis.

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is unknown. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school age. We examined associations of both DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age 4-15 years) in 2477 children from 5 cohorts and of DNA methylation at school age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from 9 cohorts, with 3 cohorts participating at both timepoints. CpGs identified with nominal significance (p < 0.05) in either of the EWAS were correlated between timepoints (ρ = 0.30), suggesting overlap in associations; however, top signals were very different. At birth, we identified nine CpGs that predicted later ADHD symptoms (p < 1 × 10-7), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 in the promoter region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which previously was associated with neurite outgrowth and an ADHD diagnosis. In contrast, at school age, no CpGs were associated with ADHD with p < 1 × 10-7. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

Polygenic prediction of the risk of perinatal depressive symptoms.

BACKGROUND: Perinatal depression carries adverse effects on maternal health and child development, but genetic underpinnings remain unclear. We investigated the polygenic risk of perinatal depressive symptoms. METHODS: About 742 women from the prospective Prediction and Prevention of Pre-eclampsia and Intrauterine Growth Restriction cohort were genotyped and completed the Center for Epidemiologic Studies Depression scale 14 times during the prenatal period and twice up to 12 months postpartum. Polygenic risk scores for major depressive disorder, bipolar disorder, schizophrenia, and cross-disorder were calculated using multiple p-value thresholds. RESULTS: Polygenic risk scores for major depressive disorder, schizophrenia, and cross-disorder, but not bipolar disorder, were associated with higher prenatal and postpartum depressive symptoms (0.8%-1% increase per one standard deviation increase in polygenic risk scores). Prenatal depressive symptoms accounted for and mediated the associations between the polygenic risk scores and postpartum depressive symptoms (effect size proportions-mediated: 52.2%-88.0%). Further, the polygenic risk scores were associated with 1.24-1.45-fold odds to belong to the group displaying consistently high compared with consistently low depressive symptoms through out the prenatal and postpartum periods. CONCLUSIONS: Polygenic risk scores for major depressive disorder, schizophrenia, and cross-disorder in non-perinatal populations generalize to perinatal depressive symptoms and may afford to identify women for timely preventive interventions.

Predisposition to superimposed preeclampsia in women with chronic hypertension: endothelial, renal, cardiac, and placental factors in a prospective longitudinal cohort.

OBJECTIVE: To assess the contribution of maternal and placental factors to the development of superimposed preeclampsia in women with chronic hypertension. METHODS: Endothelial and renal function markers were serially assessed in 90 pregnant women with chronic hypertension and controls. RESULTS: Syndecan-1 concentrations were lower at 26-27+6 weeks in women with chronic hypertension who subsequently developed superimposed preeclampsia compared with those who did not. Decreased PlGF and raised urine albumin:creatinine ratio were also associated with development of superimposed preeclampsia. CONCLUSION: Decreased syndecan-1 and PlGF concentrations implicate endothelial glycocalyx disturbance and reduced placental angiogenic capacity, respectively, in the pathophysiology of superimposed preeclampsia.

Maternal Hypertensive Pregnancy Disorders and Mental Disorders in Children.

The associations of maternal hypertensive pregnancy disorders with offspring mental disorders remain unclear. We examined whether maternal hypertensive disorders and maximum blood pressure during pregnancy predict offspring childhood mental disorders, whether the associations are independent of maternal and paternal mental disorders and paternal hypertensive disorders, independent of or additive with maternal early pregnancy overweight/obesity and diabetes mellitus disorders, and mediated or moderated by preterm birth, small-for-gestational-age birth and neonatal intensive care unit admission. Our prospective study comprised 4743 mother-child dyads of Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction study. Women were recruited to the study in early pregnancy at Finnish maternity hospitals. Children were born 2006 to 2010 and followed-up until December 31, 2016, to ages 6.4 to 10.8 years. Hypertensive pregnancy disorders were identified from medical records, Medical Birth Register, and Care Register for Health Care. Systolic and diastolic blood pressure were measured at antenatal clinics and hospital visits. Mental disorder diagnoses were identified from Care Register for Health Care. Maternal gestational and chronic hypertension, preeclampsia and its severity increased offspring hazard of any childhood mental disorder. The associations of preeclampsia (hazard ratio=1.66 [95% CI, 1.14-2.42]) and severe preeclampsia (hazard ratio=2.01 [95% CI, 1.08-3.73]) were independent of all covariates. Maternal hypertensive and diabetes mellitus disorders and overweight/obesity also additively increased offspring hazard of mental disorders. Preterm and small-for-gestational-age births and neonatal intensive care unit admission partially mediated the effects of any and severe preeclampsia on offspring mental disorders. To conclude, maternal hypertensive pregnancy disorders carry adverse consequences for offspring mental health.