Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study.

BACKGROUND: The timing of puberty may have an important impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Previous research suggests that this relationship may be causal, but replication and an investigation of whether this effect extends to other mental health domains is warranted. METHODS: In this Registered Report, we triangulated evidence from different causal inference methods using a new wave of data (N = 13,398) from the Norwegian Mother, Father, and Child Cohort Study. We combined multiple regression, one- and two-sample Mendelian randomisation (MR), and negative control analyses (using pre-pubertal symptoms as outcomes) to assess the causal links between age at menarche and different domains of adolescent mental health. RESULTS: Our results supported the hypothesis that earlier age at menarche is associated with elevated depressive symptoms in early adolescence based on multiple regression (ß = - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (ß = - 0.07, 95% CI [- 0.13, 0.00], pone-tailed = 0.03), but the effect was small, corresponding to just a 0.06 standard deviation increase in depressive symptoms with each earlier year of menarche. There was also some evidence of a causal relationship with depression diagnoses during adolescence based on one-sample MR (OR = 0.74, 95% CI [0.54, 1.01], pone-tailed = 0.03), corresponding to a 29% increase in the odds of receiving a depression diagnosis with each earlier year of menarche. Negative control and two-sample MR sensitivity analyses were broadly consistent with this pattern of results. Multivariable MR analyses accounting for the genetic overlap between age at menarche and childhood body size provided some evidence of confounding. Meanwhile, we found little consistent evidence of effects on other domains of mental health after accounting for co-occurring depression and other confounding. CONCLUSIONS: We found evidence that age at menarche affected diagnoses of adolescent depression, but not other domains of mental health. Our findings suggest that earlier age at menarche is linked to problems in specific domains rather than adolescent mental health in general.

Stability selection enhances feature selection and enables accurate prediction of gestational age using only five DNA methylation sites.

BACKGROUND: DNA methylation (DNAm) is robustly associated with chronological age in children and adults, and gestational age (GA) in newborns. This property has enabled the development of several epigenetic clocks that can accurately predict chronological age and GA. However, the lack of overlap in predictive CpGs across different epigenetic clocks remains elusive. Our main aim was therefore to identify and characterize CpGs that are stably predictive of GA. RESULTS: We applied a statistical approach called 'stability selection' to DNAm data from 2138 newborns in the Norwegian Mother, Father, and Child Cohort study. Stability selection combines subsampling with variable selection to restrict the number of false discoveries in the set of selected variables. Twenty-four CpGs were identified as being stably predictive of GA. Intriguingly, only up to 10% of the CpGs in previous GA clocks were found to be stably selected. Based on these results, we used generalized additive model regression to develop a new GA clock consisting of only five CpGs, which showed a similar predictive performance as previous GA clocks (R2 = 0.674, median absolute deviation = 4.4 days). These CpGs were in or near genes and regulatory regions involved in immune responses, metabolism, and developmental processes. Furthermore, accounting for nonlinear associations improved prediction performance in preterm newborns. CONCLUSION: We present a methodological framework for feature selection that is broadly applicable to any trait that can be predicted from DNAm data. We demonstrate its utility by identifying CpGs that are highly predictive of GA and present a new and highly performant GA clock based on only five CpGs that is more amenable to a clinical setting.

Do environmental effects indexed by parental genetic variation influence common psychiatric symptoms in childhood?

Parental genes may indirectly influence offspring psychiatric outcomes through the environment that parents create for their children. These indirect genetic effects, also known as genetic nurture, could explain individual differences in common internalising and externalising psychiatric symptoms during childhood. Advanced statistical genetic methods leverage data from families to estimate the overall contribution of parental genetic nurture effects. This study included up to 10,499 children, 5990 mother-child pairs, and 6,222 father-child pairs from the Norwegian Mother Father and Child Study. Genome-based restricted maximum likelihood (GREML) models were applied using software packages GCTA and M-GCTA to estimate variance in maternally reported depressive, disruptive, and attention-deficit hyperactivity disorder (ADHD) symptoms in 8-year-olds that was explained by direct offspring genetic effects and maternal or paternal genetic nurture. There was no strong evidence of genetic nurture in this sample, although a suggestive paternal genetic nurture effect on offspring depressive symptoms (variance explained (V) = 0.098, standard error (SE) = 0.057) and a suggestive maternal genetic nurture effect on ADHD symptoms (V = 0.084, SE = 0.058) was observed. The results indicate that parental genetic nurture effects could be of some relevance in explaining individual differences in childhood psychiatric symptoms. However, robustly estimating their contribution is a challenge for researchers given the current paucity of large-scale samples of genotyped families with information on childhood psychiatric outcomes.

Nucleated red blood cells explain most of the association between DNA methylation and gestational age.

Determining if specific cell type(s) are responsible for an association between DNA methylation (DNAm) and a given phenotype is important for understanding the biological mechanisms underlying the association. Our EWAS of gestational age (GA) in 953 newborns from the Norwegian MoBa study identified 13,660 CpGs significantly associated with GA (pBonferroni<0.05) after adjustment for cell type composition. When the CellDMC algorithm was applied to explore cell-type specific effects, 2,330 CpGs were significantly associated with GA, mostly in nucleated red blood cells [nRBCs; n = 2,030 (87%)]. Similar patterns were found in another dataset based on a different array and when applying an alternative algorithm to CellDMC called Tensor Composition Analysis (TCA). Our findings point to nRBCs as the main cell type driving the DNAm-GA association, implicating an epigenetic signature of erythropoiesis as a likely mechanism. They also explain the poor correlation observed between epigenetic age clocks for newborns and those for adults.

Overweight, obesity, and thinness among a nationally representative sample of Norwegian adolescents and changes from childhood: Associations with sex, region, and population density.

OBJECTIVE: To estimate the prevalence of overweight, obesity, and thinness among Norwegian 13-year-olds and the changes from childhood (age 8 years) to adolescence (age 13 years); and to explore associations with sex, region, and population density from childhood to adolescence. DESIGN: We used longitudinal, anthropometric data collected by school health nurses conducted in Norway. Weight status was classified according to the International Obesity Task Force cut-offs for overweight, obesity, and thinness, and according to mean body mass index (kg/m2). PARTICIPANTS: The Norwegian Youth Growth Study, consisting of a nationally representative sample of Norwegian 13-year-olds (n = 1852; 50.7% girls), which is a part of The Norwegian Growth Cohort. RESULTS: Among 13-year-old Norwegians, the prevalence of overweight (including obesity), obesity, and thinness was 15.8%, 2.5%, and 7.3%, respectively. There was little evidence that these had changed from 8 to 13 years. From 8 to 13 years, the odds of obesity was highest in the Northern region of Norway compared to the South-East (odds ratio (OR): 3.78 (95% confidence interval (CI): 1.13, 12.65; p = 0.036) and in rural areas (OR: 4.76 (95% CI: 1.52, 14.90; p = 0.027). Over the same age period, girls had a trend towards a higher odds of thinness compared to boys (OR: 1.65 (95% CI: 0.98, 2.78; p = 0.057). CONCLUSIONS: In Norway, the prevalence of overweight, obesity, and thinness among 13-year-olds seem to be established by age 8 years. The prevalence of obesity was higher in the North and in rural areas. The results indicate the continued need for early prevention and treatment, and targeted interventions to certain areas.

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.

Stumped by the Hump: The Curious Rise and Fall of Norwegian Birthweights, 1991-2007.

BACKGROUND: There was a distinct rise in mean birthweights in Norway starting in 1991 that plateaued in 1996-2002 and then declined to previous levels. We investigated whether these changes corresponded to trends in neonatal mortality or other birthweight-associated pregnancy outcomes. We also explored known predictors of birthweight and examined whether these could explain the birthweight trends. METHODS: We calculated mean birthweight for all live births in Norway in each year from 1982 to 2016, together with annual neonatal mortality and proportion of infants born preterm, or with low Apgar score. We stratified mean birthweight over time by factors including parity, gestational age, and Scandinavian versus non-Scandinavian origin of mother, to test robustness of the pattern. In addition, we used multivariable linear regression to obtain adjusted estimates for mean birthweight per year. RESULTS: A 50-g rise and fall of mean birthweights during a 25-year period was not accompanied by corresponding changes in neonatal mortality, preterm births, or Apgar scores. The distinct hump pattern was restricted to term births and was not apparent among infants of mothers born outside Scandinavia. We saw a similar pattern for Sweden but not Finland. Known predictors of birthweight (such as parity, mode of onset of delivery, and marital status) did not explain the hump. CONCLUSIONS: A distinct temporal hump in mean birthweight among Norwegian term births had no obvious explanations. Furthermore, these fluctuations in birthweight were not associated indirectly with adverse outcomes in measures of infant health.

Pregnancy-Related Risk Factors Are Associated With a Significant Burden of Treated Hypertension Within 10 Years of Delivery: Findings From a Population-Based Norwegian Cohort.

BACKGROUND: The association between pregnancy complications and women's later cardiovascular disease has, primarily, been evaluated in studies lacking information on important covariates. This report evaluates the prospective associations between pregnancy-related risk factors (preeclampsia/eclampsia, gestational hypertension, pregestational and gestational diabetes mellitus, preterm delivery, and fetal growth restriction) and pharmacologically treated hypertension within 10 years after pregnancy, while adjusting for a wide range of covariates. METHODS AND RESULTS: Prepregnancy normotensive women participating in the MoBa (Norwegian Mother and Child Cohort Study) from January 2004 through July 2009 were linked to the Norwegian Prescription Database to identify women with pharmacologically treated hypertension beyond the postpartum period of 3 months. The burden of hypertension associated with pregnancy-related risk factors was evaluated using an attributable fraction method. A total of 1480 women developed pharmacologically treated hypertension within the follow-up among 60 027 women (rate of hypertension, 3.6/1000 person-years). The proportion of hypertension associated with a history of preeclampsia/eclampsia, gestational hypertension, preterm delivery, and pregestational or gestational diabetes mellitus was 28.6% (95% confidence interval, 25.5%-31.6%) on the basis of multivariable analyses adjusting for numerous covariates. The proportion was similar for women with a healthy prepregnancy body mass index (18.5-24.9 kg/m2; attributable fraction (AF)% 25.9%; 95% confidence interval, 21.3%-30.3%), but considerably higher for nulliparous women at baseline within the first 5 years of follow-up. Small-for-gestational age, however, did not increase subsequent hypertension risk in multivariable analyses. CONCLUSIONS: A structured postpartum follow-up of high-risk women identified through pregnancy-related risk factors would facilitate personalized preventive strategies to postpone or avoid onset of premature cardiovascular events.