Exploring and Accounting for Genetically Driven Effect Heterogeneity in Mendelian Randomization.

Mendelian randomization (MR) is a framework to estimate the causal effect of a modifiable health exposure, drug target or pharmaceutical intervention on a downstream outcome by using genetic variants as instrumental variables. A crucial assumption allowing estimation of the average causal effect in MR, termed homogeneity, is that the causal effect does not vary across levels of any instrument used in the analysis. In contrast, the science of pharmacogenetics seeks to actively uncover and exploit genetically driven effect heterogeneity for the purposes of precision medicine. In this study, we consider a recently proposed method for performing pharmacogenetic analysis on observational data-the Triangulation WIthin a STudy (TWIST) framework-and explore how it can be combined with traditional MR approaches to properly characterise average causal effects and genetically driven effect heterogeneity. We propose two new methods which not only estimate the genetically driven effect heterogeneity but also enable the estimation of a causal effect in the genetic group with and without the risk allele separately. Both methods utilise homogeneity-respecting and homogeneity-violating genetic variants and rely on a different set of assumptions. Using data from the ALSPAC study, we apply our new methods to estimate the causal effect of smoking before and during pregnancy on offspring birth weight in mothers whose genetics mean they find it (relatively) easier or harder to quit smoking.

Exploring pleiotropy in Mendelian randomisation analyses: What are genetic variants associated with 'cigarette smoking initiation' really capturing?

Genetic variants used as instruments for exposures in Mendelian randomisation (MR) analyses may have horizontal pleiotropic effects (i.e., influence outcomes via pathways other than through the exposure), which can undermine the validity of results. We examined the extent of this using smoking behaviours as an example. We first ran a phenome-wide association study in UK Biobank, using a smoking initiation genetic instrument. From the most strongly associated phenotypes, we selected those we considered could either plausibly or not plausibly be caused by smoking. We examined associations between genetic instruments for smoking initiation, smoking heaviness and lifetime smoking and these phenotypes in UK Biobank and the Avon Longitudinal Study of Parents and Children (ALSPAC). We conducted negative control analyses among never smokers, including children. We found evidence that smoking-related genetic instruments were associated with phenotypes not plausibly caused by smoking in UK Biobank and (to a lesser extent) ALSPAC. We observed associations with phenotypes among never smokers. Our results demonstrate that smoking-related genetic risk scores are associated with unexpected phenotypes that are less plausibly downstream of smoking. This may reflect horizontal pleiotropy in these genetic risk scores, and we would encourage researchers to exercise caution this when using these and genetic risk scores for other complex behavioural exposures. We outline approaches that could be taken to consider this and overcome issues caused by potential horizontal pleiotropy, for example, in genetically informed causal inference analyses (e.g., MR) it is important to consider negative control outcomes and triangulation approaches, to avoid arriving at incorrect conclusions.

The impact of anorexia nervosa and BMI polygenic risk on childhood growth: A 20-year longitudinal population-based study.

Growth deviating from the norm during childhood has been associated with anorexia nervosa (AN) and obesity later in life. In this study, we examined whether polygenic scores (PGSs) for AN and BMI are associated with growth trajectories spanning the first two decades of life. AN PGSs and BMI PGSs were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 8,654). Using generalized (mixed) linear models, we associated PGSs with trajectories of weight, height, body mass index (BMI), fat mass index (FMI), lean mass index (LMI), and bone mineral density (BMD). Female participants with AN PGSs one standard deviation (SD) higher had, on average, 0.004% slower growth in BMI between the ages 6.5 and 24 years and a 0.4% slower gain in BMD between the ages 10 and 24 years. Higher BMI PGSs were associated with faster growth for BMI, FMI, LMI, BMD, and weight trajectories in both sexes throughout childhood. Female participants with both a high AN PGS and a low BMI PGS showed slower growth compared to those with both a low AN PGS and a low BMI PGS. We conclude that AN PGSs and BMI PGSs have detectable sex-specific effects on growth trajectories. Female participants with a high AN PGS and low BMI PGS likely constitute a high-risk group for AN, as their growth was slower compared to their peers with high PGSs on both traits. Further research is needed to better understand how the AN PGS and the BMI PGS co-influence growth during childhood and whether a high BMI PGS can mitigate the effects of a high AN PGS.

Comparison of the stability of glycoprotein acetyls and high sensitivity C-reactive protein as markers of chronic inflammation.

It has been suggested that glycoprotein acetyls (GlycA) better reflects chronic inflammation than high sensitivity C-reactive protein (hsCRP), but paediatric/life-course data are sparse. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank, we compared short- (over weeks) and long-term (over years) correlations of GlycA and hsCRP, cross-sectional correlations between GlycA and hsCRP, and associations of pro-inflammatory risk factors with GlycA and hsCRP across the life-course. GlycA showed high short-term (weeks) stability at 15 years (r = 0.75; 95% CI = 0.56, 0.94), 18 years (r = 0.74; 0.64, 0.85), 24 years (r = 0.74; 0.51, 0.98) and 48 years (r = 0.82 0.76, 0.86) and this was comparable to the short-term stability of hsCRP at 24 years. GlycA stability was moderate over the long-term, for example between 15 and 18 years r = 0.52; 0.47, 0.56 and between 15 and 24 years r = 0.37; 0.31, 0.44. These were larger than equivalent correlations of hsCRP. GlycA and concurrently measured hsCRP were moderately correlated at all ages, for example at 15 years (r = 0.44; 0.40, 0.48) and at 18 years (r = 0.55; 0.51, 0.59). We found similar associations of known proinflammatory factors and inflammatory diseases with GlycA and hsCRP. For example, BMI was positively associated with GlycA (mean difference in GlycA per standard deviation change in BMI = 0.08; 95% CI = 0.07, 0.10) and hsCRP (0.10; 0.08, 0.11). This study showed that GlycA has greater long-term stability than hsCRP, however associations of proinflammatory factors with GlycA and hsCRP were broadly similar.

An Examination of Sleep as a Protective Factor for Depression and Anxiety in the Perinatal Period: Novel Causal Analyses in a Prospective Pregnancy Cohort.

Sleep problems are common in the perinatal period. But the effects of sleep health on long-term postpartum depression and anxiety are underexamined. Using marginal structural models, we estimated the effect of sustained restful sleep quality, or adequate sleep quantity, or both, on clinically significant depression and anxiety at 23- and 32-weeks gestation, and 8-weeks, 8-, and 21-months postpartum. Women (n = 9,211) in the Avon Longitudinal Study of Parents and Children cohort reported on sleep quality (difficulty falling asleep, and early morning awakening), sleep quantity (< or > 5 hours and perceived sleep adequacy), depression (Edinburgh Postnatal Depression Scale), and anxiety (Crown-Crisp Experiential Index). Analyses adjusted for fixed (maternal education, age, body mass index, parity, marital status, smoking) and time varying (alcohol use, psychosocial adversities, depression, anxiety or sleep problems at prior time periods) covariates. Descriptive analyses suggest that sleep alterations persist beyond the immediate postpartum period. Estimates of counterfactual prevalences of outcomes under restful sleep quality and adequate sleep suggest a reduction of the population burden of clinically significant depression between 2.4% - 5.9%, and anxiety by 3.4% - 8.0% for the time points assessed. Interventions for perinatal sleep problems may reduce clinically significant depression and anxiety.

Analyses Using Multiple Imputation Need to Consider Missing Data in Auxiliary Variables.

Auxiliary variables are used in multiple imputation (MI) to reduce bias and increase efficiency. These variables may often themselves be incomplete. We explored how missing data in auxiliary variables influenced estimates obtained from MI. We implemented a simulation study with three different missing data mechanisms for the outcome. We then examined the impact of increasing proportions of missing data and different missingness mechanisms for the auxiliary variable on bias of an unadjusted linear regression coefficient and the fraction of missing information. We illustrate our findings with an applied example in the Avon Longitudinal Study of Parents and Children. We found that where complete records analyses were biased, increasing proportions of missing data in auxiliary variables, under any missing data mechanism, reduced the ability of MI including the auxiliary variable to mitigate this bias. Where there was no bias in the complete records analysis, inclusion of a missing not at random auxiliary variable in MI introduced bias of potentially important magnitude (up to 17% of the effect size in our simulation). Careful consideration of the quantity and nature of missing data in auxiliary variables needs to be made when selecting them for use in MI models.

Preschool Mathematics and Literacy Skills and Educational Attainment in Adolescents Born Preterm and Full Term.

OBJECTIVES: To test whether preschool academic skills were associated with educational attainment in adolescence and whether associations differed between individuals born preterm and at full term. STUDY DESIGN: This prospective cohort study comprised 6924 individuals, including n = 444 (6.4%) adolescents born preterm (<37 weeks of gestation) from the Avon Longitudinal Study of Parents and Children. Preschool academic (mathematics and literacy) skills were rated by teachers at 4-5 years. Educational attainment at 16 years was informed by attaining a General Certificate of Secondary Education (GCSE) in key subjects mathematics and English. Logistic regressions assessed the association between preterm birth, preschool mathematics, and GCSE Mathematics and between preterm birth, preschool literacy, and GCSE English. RESULTS: Similar numbers of adolescents born preterm and at term achieved a GCSE in mathematics and English (53.6 % vs 57.4% and 59.5% vs 63.9%, respectively; P values > .05). Higher preschool academic skill scores in mathematics were associated with greater odds of attaining GCSE Mathematics and preschool literacy skills were associated with GCSE English. Adolescents born preterm with higher preschool mathematics (OR: 1.51, CI: 1.14, 2.00) and literacy skills (OR: 1.57, CI: 1.10, 2.25) were more likely to attain GCSEs in the respective subject than their term-born counterparts with equal levels of preschool skills. CONCLUSIONS: Preschool academic skills in mathematics and literacy are associated with educational attainment of preterm and term-born individuals in adolescence. Children born prematurely may benefit more from preschool mathematics and literacy skills for academic and educational success into adolescence than term-born individuals.

Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study.

INTRODUCTION: Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these. OBJECTIVE: To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD. METHODS: We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling. RESULTS: 499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides. CONCLUSIONS: Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.

Depressive symptoms in adolescence and adult educational and employment outcomes: a structured life course analysis.

BACKGROUND: Depression is a common mental health disorder that often starts during adolescence, with potentially important future consequences including 'Not in Education, Employment or Training' (NEET) status. METHODS: We took a structured life course modeling approach to examine how depressive symptoms during adolescence might be associated with later NEET status, using a high-quality longitudinal data resource. We considered four plausible life course models: (1) an early adolescent sensitive period model where depressive symptoms in early adolescence are more associated with later NEET status relative to exposure at other stages; (2) a mid adolescent sensitive period model where depressive symptoms during the transition from compulsory education to adult life might be more deleterious regarding NEET status; (3) a late adolescent sensitive period model, meaning that depressive symptoms around the time when most adults have completed their education and started their careers are the most strongly associated with NEET status; and (4) an accumulation of risk model which highlights the importance of chronicity of symptoms. RESULTS: Our analysis sample included participants with full information on NEET status (N = 3951), and the results supported the accumulation of risk model, showing that the odds of NEET increase by 1.015 (95% CI 1.012-1.019) for an increase of 1 unit in depression at any age between 11 and 24 years. CONCLUSIONS: Given the adverse implications of NEET status, our results emphasize the importance of supporting mental health during adolescence and early adulthood, as well as considering specific needs of young people with re-occurring depressed mood.

Childhood correlates and young adult outcomes of trajectories of emotional problems from childhood to adolescence.

BACKGROUND: Emotional problems, especially anxiety, have become increasingly common in recent generations. Few population-based studies have examined trajectories of emotional problems from early childhood to late adolescence or investigated differences in psychiatric and functional outcomes. METHODS: Using the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 8286, 50.4% male), we modeled latent class growth trajectories of emotional problems, using the parent-reported Strength and Difficulties Questionnaire emotional scale (SDQ-E) on seven occasions (4-17 years). Psychiatric outcomes in young adulthood (21-25 years) were major depressive disorder (MDD), generalized anxiety disorder (GAD), and self-harm. Functional outcomes were exam attainment, educational/occupational status, and social relationship quality. RESULTS: We identified four classes of emotional problems: low (67.0%), decreasing (18.4%), increasing (8.9%), and persistent (5.7%) problems. Compared to those in the low class, individuals with decreasing emotional problems were not at elevated risk of any poor adult outcome. Individuals in the increasing and persistent classes had a greater risk of adult MDD (RR: 1.59 95% CI 1.13-2.26 and RR: 2.25 95% CI 1.49-3.41) and self-harm (RR: 2.37 95% CI 1.91-2.94 and RR: 1.87 95% CI 1.41-2.48), and of impairment in functional domains. Childhood sleep difficulties, irritability, conduct and neurodevelopmental problems, and family adversity were associated with a persistent course of emotional problems. CONCLUSIONS: Childhood emotional problems were common, but those whose symptoms improved over time were not at increased risk for adverse adult outcomes. In contrast, individuals with persistent or adolescent-increasing emotional problems had a higher risk of mental ill-health and social impairment in young adulthood which was especially pronounced for those with persistent emotional problems.

Prenatal exposure to common infections and newborn DNA methylation: A prospective, population-based study.

BACKGROUND: Infections during pregnancy have been robustly associated with adverse mental and physical health outcomes in offspring, yet the underlying molecular pathways remain largely unknown. Here, we examined whether exposure to common infections in utero associates with DNA methylation (DNAm) patterns at birth and whether this in turn relates to offspring health outcomes in the general population. METHODS: Using data from 2,367 children from the Dutch population-based Generation R Study, we first performed an epigenome-wide association study to identify differentially methylated sites and regions at birth associated with prenatal infection exposure. We also examined the influence of infection timing by using self-reported cumulative infection scores for each trimester. Second, we sought to develop an aggregate methylation profile score (MPS) based on cord blood DNAm as an epigenetic proxy of prenatal infection exposure and tested whether this MPS prospectively associates with offspring health outcomes, including psychiatric symptoms, BMI, and asthma at ages 13-16 years. Third, we investigated whether prenatal infection exposure associates with offspring epigenetic age acceleration - a marker of biological aging. Across all analysis steps, we tested whether our findings replicate in 864 participants from an independent population-based cohort (ALSPAC, UK). RESULTS: We observed no differentially methylated sites or regions in cord blood in relation to prenatal infection exposure, after multiple testing correction. 33 DNAm sites showed suggestive associations (p < 5e10 - 5; of which one was also nominally associated in ALSPAC), indicating potential links to genes associated with immune, neurodevelopmental, and cardiovascular pathways. While the MPS of prenatal infections associated with maternal reports of infections in the internal hold out sample in the Generation R Study (R2incremental = 0.049), it did not replicate in ALSPAC (R2incremental = 0.001), and it did not prospectively associate with offspring health outcomes in either cohort. Moreover, we observed no association between prenatal exposure to infections and epigenetic age acceleration across cohorts and clocks. CONCLUSION: In contrast to prior studies, which reported DNAm differences in offspring exposed to severe infections in utero, we do not find evidence for associations between self-reported clinically evident common infections during pregnancy and DNAm or epigenetic aging in cord blood within the general pediatric population. Future studies are needed to establish whether associations exist but are too subtle to be statistically meaningful with present sample sizes, whether they replicate in a cohort with a more similar infection score as our discovery cohort, whether they occur in different tissues than cord blood, and whether other biological pathways may be more relevant for mediating the effect of prenatal common infection exposure on downstream offspring health outcomes.

Interactions Between Genetic, Prenatal Substance Use, Puberty, and Parenting are Less Important for Understanding Adolescents' Internalizing, Externalizing, and Substance Use than Developmental Cascades in Multifactorial Models.

This study tested interactions among puberty-related genetic risk, prenatal substance use, harsh discipline, and pubertal timing for the severity and directionality (i.e., differentiation) of externalizing and internalizing problems and adolescent substance use. This is a companion paper to Marceau et al. (2021) which examined the same influences in developmental cascade models. Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (n = 4504 White boys, n = 4287 White girls assessed from the prenatal period through 18.5 years). We hypothesized generally that later predictors would strengthen the influence of puberty-related genetic risk, prenatal substance use exposure, and pubertal risk on psychopathology and substance use (two-way interactions), and that later predictors would strengthen the interactions of earlier influences on psychopathology and substance use (three-way interactions). Interactions were sparse. Although all fourteen interactions showed that later influences can exacerbate or trigger the effects of earlier ones, they often were not in the expected direction. The most robust moderator was parental discipline, and differing and synergistic effects of biological and socially-relevant aspects of puberty were found. In all, the influences examined here operate more robustly in developmental cascades than in interaction with each other for the development of psychopathology and transitions to substance use.

A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency.

Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n = 1,118, early adulthood n = 2,762, adulthood n = 5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n = 3,089, early adulthood n = 3,993, adulthood n = 5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n = 5,382, early adulthood n = 3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.

Shorter night-time sleep duration and later sleep timing from infancy to adolescence.

BACKGROUND: Here, we (a) examined the trajectories of night-time sleep duration, bedtime and midpoint of night-time sleep (MPS) from infancy to adolescence, and (b) explored perinatal risk factors for persistent poor sleep health. METHODS: This study used data from 12,962 participants in the Avon Longitudinal Study of Parents and Children (ALSPAC). Parent or self-reported night-time sleep duration, bedtime and wake-up time were collected from questionnaires at 6, 18 and 30 months, and at 3.5, 4-5, 5-6, 6-7, 9, 11 and 15-16 years. Child's sex, birth weight, gestational age, health and temperament, together with mother's family adversity index (FAI), age at birth, prenatal socioeconomic status and postnatal anxiety and depression, were included as risk factors for persistent poor sleep health. Latent class growth analyses were applied first to detect trajectories of night-time sleep duration, bedtime and MPS, and we then applied logistic regressions for the longitudinal associations between risk factors and persistent poor sleep health domains. RESULTS: We obtained four trajectories for each of the three sleep domains. In particular, we identified a trajectory characterized by persistent shorter sleep, a trajectory of persistent later bedtime and a trajectory of persistent later MPS. Two risk factors were associated with the three poor sleep health domains: higher FAI with increased risk of persistent shorter sleep (OR = 1.20, 95% CI = 1.11-1.30, p < .001), persistent later bedtime (OR = 1.28, 95% CI = 1.19-1.39, p < .001) and persistent later MPS (OR = 1.30, 95% CI = 1.22-1.38, p < .001); and higher maternal socioeconomic status with reduced risk of persistent shorter sleep (OR = 0.99, 95% CI = 0.98-1.00, p = .048), persistent later bedtime (OR = 0.98, 95% CI = 0.97-0.99, p < .001) and persistent later MPS (OR = 0.99, 95% CI = 0.98-0.99, p < .001). CONCLUSIONS: We detected trajectories of persistent poor sleep health (i.e. shorter sleep duration, later bedtime and later MPS) from infancy to adolescence, and specific perinatal risk factors linked to persistent poor sleep health domains.

Mapping associations of polygenic scores with autistic and ADHD traits in a single city region.

BACKGROUND: The genetic and environmental aetiology of autistic and Attention Deficit Hyperactivity Disorder (ADHD) traits is known to vary spatially, but does this translate into variation in the association of specific common genetic variants? METHODS: We mapped associations between polygenic scores for autism and ADHD and their respective traits in the Avon Longitudinal Study of Parents and Children (N = 4,255-6,165) across the area surrounding Bristol, UK, and compared them to maps of environments associated with the prevalence of autism and ADHD. RESULTS: Our results suggest genetic associations vary spatially, with consistent patterns for autistic traits across polygenic scores constructed at different p-value thresholds. Patterns for ADHD traits were more variable across thresholds. We found that the spatial distributions often correlated with known environmental influences. CONCLUSIONS: These findings shed light on the factors that contribute to the complex interplay between the environment and genetic influences in autistic and ADHD traits.

Genetic influences on sibling bullying and mental health difficulties.

BACKGROUND: Sibling bullying is associated with mental health difficulties; both in the short and long term. It is commonly assumed that sibling bullying leads to mental health difficulties but additional explanations for the relationship between the two are seldom investigated. METHODS: To address this gap in knowledge, we used a genetically sensitive design with data from the Avon Longitudinal Study of Parents and Children (maximum N = 3,959, 53% female). At ages 11-13 years, individuals self-reported their involvement in sibling bullying, as a victim and perpetrator, and parents reported on their child's mental health difficulties. Polygenic scores, indices of genetic risk for psychiatric disorders (major depressive disorder and attention deficit hyperactivity disorder) were computed using children's genetic data. Regression and structural equation models were fitted to the data. RESULTS: Sibling bullying, victimisation and perpetration, and polygenic scores both predicted mental health difficulties in an additive manner but there was no interaction between them. Polygenic scores for mental health difficulties were also associated with sibling bullying. CONCLUSIONS: These findings suggest that sibling bullying, victimisation and perpetration, is associated with mental health difficulties, even after accounting for some genetic effects. Additionally, the relationship between sibling bullying and mental health difficulties may be, at least partly, due to shared genetic aetiology. One possibility is that genetic risk for mental health difficulties influences the onset of mental health difficulties which in turn make children more susceptible to sibling bullying.

DNA methylation at birth and lateral ventricular volume in childhood: a neuroimaging epigenetics study.

BACKGROUND: Lateral ventricular volume (LVV) enlargement has been repeatedly linked to schizophrenia; yet, what biological factors shape LVV during early development remain unclear. DNA methylation (DNAm), an essential process for neurodevelopment that is altered in schizophrenia, is a key molecular system of interest. METHODS: In this study, we conducted the first epigenome-wide association study of neonatal DNAm in cord blood with LVV in childhood (measured using T1-weighted brain scans at 10 years), based on data from a large population-based birth cohort, the Generation R Study (N = 840). Employing both probe-level and methylation profile score (MPS) approaches, we further examined whether epigenetic modifications identified at birth in cord blood are: (a) also observed cross-sectionally in childhood using peripheral blood DNAm at age of 10 years (Generation R, N = 370) and (b) prospectively associated with LVV measured in young adulthood in an all-male sample from the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 114). RESULTS: At birth, DNAm levels at four CpGs (annotated to potassium channel tetramerization domain containing 3, KCTD3; SHH signaling and ciliogenesis regulator, SDCCAG8; glutaredoxin, GLRX) prospectively associated with childhood LVV after genome-wide correction; these genes have been implicated in brain development and psychiatric traits including schizophrenia. An MPS capturing a broader epigenetic profile of LVV - but not individual top hits - showed significant cross-sectional associations with LVV in childhood in Generation R and prospectively associated with LVV in early adulthood within ALSPAC. CONCLUSIONS: This study finds suggestive evidence that DNAm at birth prospectively associates with LVV at different life stages, albeit with small effect sizes. The prediction of MPS on LVV in a childhood sample and an independent male adult sample further underscores the stability and reproducibility of DNAm as a potential marker for LVV. Future studies with larger samples and comparable time points across development are needed to further elucidate how DNAm associates with this clinically relevant brain structure and risk for neuropsychiatric disorders, and what factors explain the identified DNAm profile of LVV at birth.

The relationship between type, timing and duration of exposure to adverse childhood experiences and adolescent self-harm and depression: findings from three UK prospective population-based cohorts.

BACKGROUND: Adverse childhood experiences (ACEs) are well-established risk factors for self-harm and depression. However, despite their high comorbidity, there has been little focus on the impact of developmental timing and the duration of exposure to ACEs on co-occurring self-harm and depression. METHODS: Data were utilised from over 22,000 children and adolescents participating in three UK cohorts, followed up longitudinally for 14-18 years: the Avon Longitudinal Study of Parents and Children (ALSPAC), the Millennium Cohort Study (MCS) and the Environmental Risk (E-Risk) Longitudinal Twin Study. Multinomial logistic regression models estimated associations between each ACE type and a four-category outcome: no self-harm or depression, self-harm alone, depression alone and self-harm with co-occurring depression. A structured life course modelling approach was used to examine whether the accumulation (duration) of exposure to each ACE, or a critical period (timing of ACEs) had the strongest effects on self-harm and depression in adolescence. RESULTS: The majority of ACEs were associated with co-occurring self-harm and depression, with consistent findings across cohorts. The importance of timing and duration of ACEs differed across ACEs and across cohorts. For parental mental health problems, longer duration of exposure was strongly associated with co-occurring self-harm and depression in both ALSPAC (adjusted OR: 1.18, 95% CI: 1.10-1.25) and MCS (1.18, 1.11-1.26) cohorts. For other ACEs in ALSPAC, exposure in middle childhood was most strongly associated with co-occurring self-harm and depression, and ACE occurrence in early childhood and adolescence was more important in the MCS. CONCLUSIONS: Efforts to mitigate the impact of ACEs should start in early life with continued support throughout childhood, to prevent long-term exposure to ACEs contributing to risk of self-harm and depression in adolescence.

Using instruments for selection to adjust for selection bias in Mendelian randomization.

Selection bias is a common concern in epidemiologic studies. In the literature, selection bias is often viewed as a missing data problem. Popular approaches to adjust for bias due to missing data, such as inverse probability weighting, rely on the assumption that data are missing at random and can yield biased results if this assumption is violated. In observational studies with outcome data missing not at random, Heckman's sample selection model can be used to adjust for bias due to missing data. In this paper, we review Heckman's method and a similar approach proposed by Tchetgen Tchetgen and Wirth (2017). We then discuss how to apply these methods to Mendelian randomization analyses using individual-level data, with missing data for either the exposure or outcome or both. We explore whether genetic variants associated with participation can be used as instruments for selection. We then describe how to obtain missingness-adjusted Wald ratio, two-stage least squares and inverse variance weighted estimates. The two methods are evaluated and compared in simulations, with results suggesting that they can both mitigate selection bias but may yield parameter estimates with large standard errors in some settings. In an illustrative real-data application, we investigate the effects of body mass index on smoking using data from the Avon Longitudinal Study of Parents and Children.

Associations of childhood diet quality scores with arterial stiffness and carotid artery intima-media thickness in adolescence/early adulthood: findings from the ALSPAC cohort.

This study examined the relationship between childhood diet quality and arterial stiffness and thickness during adolescence/early adulthood. Participants were from the Avon Longitudinal Study of Parents and Children (ALSPAC) with dietary data at ages 7, 10 and 13 years and pulse wave velocity (PWV) and carotid intima-media thickness (cIMT) at ages 17 and/or 24 years. Diet quality (DQ) was assessed using five scores: a children's Mediterranean-style diet (C-rMED) Z-score, a children's Dietary Inflammatory Z-score (C-DIS), a DASH diet Z-score, a children's Eatwell Guide (C-EWG) Z-score reflecting UK dietary guidelines and a data-driven obesogenic Z-score. Adjusted regression models examined the associations between DQ scores at 7-13 years and PWV and cIMT at 17 and 24 years. In adjusted models, a high v. low Obesogenic Z-score at 7 and 10 years was associated with higher PWV at 17: ß 0.07 (95 % CI 0.01, 0.13) and ß 0.10 (95 % CI 0.04, 0.16), respectively. A high v. low C-rMED Z-score at 7 years was associated with lower PWV at 17 (ß -0.07; 95 % CI -0.14, -0.01). A high (more anti-inflammatory) vs low C-DIS Z-score at 10 years was associated with a lower PWV at 17 years: ß -0.06 (95 % CI -0.12, -0.01). No other associations were observed. In conclusion, an Obesogenic dietary pattern in childhood (7-10 years) was related to increased arterial stiffness, while Mediterranean-style and anti-inflammatory diets were related to decreased arterial stiffness in adolescence. This highlights the importance of establishing healthy dietary habits early in life to protect against vascular damage.