The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits

BACKGROUND

The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD).

METHODS

We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models.

RESULTS

Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity.

CONCLUSIONS

The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.

The Born in Guangzhou Cohort Study enables generational genetic discoveries

Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.

Maternal type 1 diabetes and relative protection against offspring transmission

Type 1 diabetes is around twice as common in the offspring of men with type 1 diabetes than in the offspring of women with type 1 diabetes, but the reasons for this difference are unclear. This Review summarises the evidence on the rate of transmission of type 1 diabetes to the offspring of affected fathers compared with affected mothers. The findings of nine major studies are presented, describing the magnitude of the effect observed and the relative strengths and weaknesses of these studies. This Review also explores possible underlying mechanisms for this effect, such as genetic mechanisms (eg, the selective loss of fetuses with high-risk genes in mothers with type 1 diabetes, preferential transmission of susceptibility genes from fathers, and parent-of-origin effects influencing gene expression), environmental exposures (eg, exposure to maternal hyperglycaemia, exogenous insulin exposure, and transplacental antibody transfer), and maternal microchimerism. Understanding why type 1 diabetes is more common in the offspring of men versus women with type 1 diabetes will help in the identification of individuals at high risk of the disease and can pave the way in the development of interventions that mimic the protective elements of maternal type 1 diabetes to reduce the risk of disease in individuals at high risk.

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

OBJECTIVE

To investigate the genetic architecture of internalizing symptoms in childhood and adolescence.

METHOD

In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.

RESULTS

The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.

CONCLUSION

Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Overview of CAPICE-Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Skłodowska-Curie International Training Network

The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).

Placental genomics mediates genetic associations with complex health traits and disease

As the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we perform distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At $$P \; < \; 2.5\times {10}^{-6}$$ P < 2.5 × 10 − 6 , we detect 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explain 4 early-life traits but no later-in-life traits. 89 GTAs show significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells reveal that knockdown of mediator gene EPS15 upregulates predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course.

Systematic Review: Molecular Studies of Common Genetic Variation in Child and Adolescent Psychiatric Disorders

OBJECTIVE

A systematic review of studies using molecular genetics and statistical approaches to investigate the role of common genetic variation in the development, persistence, and comorbidity of childhood psychiatric traits was conducted.

METHOD

A literature review was performed using the PubMed database, following PRISMA guidelines. There were 131 studies meeting inclusion criteria, having investigated at least one type of childhood-onset or childhood-measured psychiatric disorder or trait with the aim of identifying trait-associated common genetic variants, estimating the contribution of single nucleotide polymorphisms (SNPs) to the amount of variance explained (SNP-based heritability), investigating genetic overlap between psychiatric traits, or investigating whether the stability in traits or the association with adult traits is explained by genetic factors.

RESULTS

The first robustly associated genetic variants have started to be identified for childhood psychiatric traits. There were substantial contributions of common genetic variants to many traits, with variation in single nucleotide polymorphism heritability estimates depending on age and raters. Moreover, genetic variants also appeared to explain comorbidity as well as stability across a range of psychiatric traits in childhood and across the life span.

CONCLUSION

Common genetic variation plays a substantial role in childhood psychiatric traits. Increased sample sizes will lead to increased power to identify genetic variants and to understand genetic architecture, which will ultimately be beneficial to targeted and prevention strategies. This can be achieved by harmonizing phenotype measurements, as is already proposed by large international consortia and by including the collection of genetic material in every study.

Cohort profile: InTraUterine sampling in early pregnancy (ITU), a prospective pregnancy cohort study in Finland: study design and baseline characteristics

PURPOSE

The InTraUterine sampling in early pregnancy (ITU) is a prospective pregnancy cohort study. The overarching aim of ITU is to unravel genomic, epigenomic, transcriptomic, endocrine, inflammatory and metabolic maternal-placental-fetal mechanisms involved in the programming of health and disease after exposure to prenatal environmental adversity, such as maternal malnutrition, cardiometabolic disorders, infections, medical interventions, mental disorders and psychosocial stress. This paper describes the study protocol, design and baseline characteristics of the cohort.

PARTICIPANTS

We included 944 pregnant Finnish women, their partners and children born alive between April 2012 and December 2017. The women were recruited through the national, voluntary trisomy 21 screening between 9⁺⁰ and 21⁺⁶ gestational weeks. Of the participating women, 543 were screen positive and underwent fetal chromosomal testing. Test result of these women suggested no fetal chromosomal abnormality. Further, we recruited 401 women who were screen negative and who did not undergo fetal chromosomal testing.

FINDINGS TO DATE

We have collected chorionic villi and amniotic fluid from the screen-positive women; blood, urine, buccal swabs and diurnal salivary samples from all women; blood and buccal swabs from all partners; and placenta, cord blood and buccal swabs from all newborns for analyses of the genome, epigenome, transcriptome, and endocrine, inflammatory and metabolic markers. These data are coupled with comprehensive phenotypes, including questions on demographic characteristics, health and well-being of the women and their partners during pregnancy and of the women and their children at the child's age of 1.7 and 3 years. Data also come from patient records and nationwide registers covering health, lifestyle and medication data.

FUTURE PLANS

Multiple layers of ITU data allow integrative data analyses, which translate to biomarker identification and allow risk stratification and understanding of the biological mechanisms involved in prenatal programming of health and disease.

Sleep-related traits and attention-deficit/hyperactivity disorder comorbidity: Shared genetic risk factors, molecular mechanisms, and causal effects

OBJECTIVES

To evaluate the shared genetic components, common pathways and causal relationship between ADHD and sleep-related phenotypes.

METHODS

We used the largest genome-wide association summary statistics available for attention-deficit/hyperactivity disorder (ADHD) and various sleep-related phenotypes (insomnia, napping, daytime dozing, snoring, ease getting up, daytime sleepiness, sleep duration and chronotype). We estimated the genomic correlation using cross-trait linkage disequilibrium score regression (LDSR) and investigated the potential common mechanisms using gene-based cross-trait metanalyses and functional enrichment analyses. The causal effect was estimated using two-sample Mendelian randomisation (TSMR), using the inverse variance weighted method as the main estimator.

RESULTS

A positive genomic correlation between insomnia, daytime napping, daytime dozing, snoring, daytime sleepiness, short and long sleep duration, and ADHD was observed. Insomnia, daytime sleepiness, and snoring shared genes with ADHD, that are involved in neurobiological functions and regulatory signalling pathways. The TSMR supported a causal effect of insomnia, daytime napping, and short sleep duration on ADHD, and of ADHD on long sleep duration and chronotype.

CONCLUSION

Comorbidity between sleep phenotypes and ADHD may be mediated by common genetic factors that play an important role in neuronal signalling pathways. A causal effect of sleep disturbances and short sleep duration on ADHD reinforced their role as predictors of ADHD.

Editorial: The Value of Genetically Informative Designs to Understand Pathways of Intergenerational Transmission and Direction of Causality

One of the greatest challenges in the social, behavioral, and medical sciences is to determine the causality underlying associations between risk factors and behavioral or disease outcomes. An area in which insight into causality, and especially direction of causation of possible risk factors and outcomes, could have enormous (clinical) impact is the field of childhood and adolescent psychiatry. Abundant evidence shows that psychopathology runs in families, but the pathways underlying shared family risk are unclear. Large twin family studies provide robust estimates for the heritability of childhood and adolescent behavioral and emotional problems, but direct non-genetic effects from parent to offspring or vice versa cannot be excluded. Question remains as to whether there is a direct causal effect of parental mental health status on the mental health and well-being of their offspring above and beyond the transmission of genetic susceptibility. Genetically informed methods provide opportunities to tackle this causality challenge.¹.

The role of genetics in fetal programming of adult cardiometabolic disease

Disturbances affecting early development have broad repercussions on the individual's health during infancy and adulthood. Multiple observational studies throughout the years have shown that alterations of fetal growth are associated with increased cardiometabolic disease risks. However, the genetic component of this association only started to be investigated in the last 40 years, when single genes with distinct effects were investigated. Birth weight (BW), commonly reported as the outcome of developmental growth, has been estimated to be 20% to 60% heritable. Through Genome-Wide Association (GWA) meta-analyses, 190 different loci have been identified being associated with BW, and while many of these loci designate genes involved in glucose and lipid metabolism, with clear ties to fetal development, the role of others is not yet understood. In addition, due to its influence over the intrauterine environment, the maternal genotype also plays an important part in the determination of offspring BW, with the same loci having independent effects of different magnitude or even direction. There is still much to uncover regarding the genetic determinants of BW and the interactions between maternal, offspring, and even paternal genotype. To fully understand these, diverse and novel cohorts from multiple ancestries collecting extensive neonatal phenotype will be needed. This review compiles, chronologically, the main findings in the investigation of the genetics of BW.

Novel loci and Mapuche genetic ancestry are associated with pubertal growth traits in Chilean boys

Puberty is a complex developmental process that varies considerably among individuals and populations. Genetic factors explain a large proportion of the variability of several pubertal traits. Recent genome-wide association studies (GWAS) have identified hundreds of variants involved in traits that result from body growth, like adult height. However, they do not capture many genetic loci involved in growth changes over distinct growth phases. Further, such GWAS have been mostly performed in Europeans, but it is unknown how these findings relate to other continental populations. In this study, we analyzed the genetic basis of three pubertal traits; namely, peak height velocity (PV), age at PV (APV) and height at APV (HAPV). We analyzed a cohort of 904 admixed Chilean children and adolescents with European and Mapuche Native American ancestries. Height was measured on roughly a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$6-$$\end{document}6-month basis from childhood to adolescence between 2006 and 2019. We predict that, in average, HAPV is 4.3 cm higher in European than in Mapuche adolescents (P = 0.042), and APV is 0.73 years later in European compared with Mapuche adolescents (P = 0.023). Further, by performing a GWAS on 774, 433 single-nucleotide polymorphisms, we identified a genetic signal harboring 3 linked variants significantly associated with PV in boys (P\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$< 5 \times 10^{-8}$$\end{document}<5×10-8). This signal has never been associated with growth-related traits.

The EU Child Cohort Network's core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variables

The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.

Genetics of early growth traits

In recent years, genome-wide association studies have shed light on the genetics of early growth and its links with later-life health outcomes. Large-scale datasets and meta-analyses, combined with recently developed analytical methods, have enabled dissection of the maternal and fetal genetic contributions to variation in birth weight. Additionally, longitudinal approaches have shown differences between the genetic contributions to infant, childhood and adult adiposity. In contrast, studies of adult height loci have shown strong associations with early body length and childhood height. Early growth-associated loci provide useful tools for causal analyses: Mendelian randomization (MR) studies have provided evidence that early BMI and height are causally related to a number of adult health outcomes. We advise caution in the design and interpretation of MR studies of birth weight investigating effects of fetal growth on later-life cardiometabolic disease because birth weight is only a crude indicator of fetal growth, and the choice of genetic instrument (maternal or fetal) will greatly influence the interpretation of the results. Most genetic studies of early growth have to date centered on European-ancestry participants and outcomes measured at a single time-point, so key priorities for future studies of early growth genetics are aggregation of large samples of diverse ancestries and longitudinal studies of growth trajectories.

The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.

Objectives, design and main findings until 2020 from the Rotterdam Study

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies

To identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic heterogeneity through selecting more homogenous MDD subtypes. The value of these strategies has been debated. In this review, we summarize the most recent findings of large genomic studies that applied these approaches, and we highlight the merits and pitfalls of both approaches with particular attention to methodological and psychometric issues. We also discuss the results of analyses that investigated the heterogeneity of MDD. We conclude that both study designs are essential for further research. So far, increasing sample size has led to the identification of a relatively high number of genomic loci linked to depression. However, part of the identified variants may be related to a phenotype common to internalizing disorders and related traits. As such, samples containing detailed clinical information are needed to dissect depression heterogeneity and enable the potential identification of variants specific to a more restricted MDD phenotype. A balanced portfolio reconciling both study design approaches is the optimal approach to progress further in unraveling the genetic architecture of depression.