The overall objective of the proposal is to exploit information held within existing cohorts and their population-based biobanks to improve understanding of the determinants of and risk factors for low lung function , respiratory disability and the development of a major cause of disease, disability and death in European adults, namely chronic obstructive lung disease (COPD). Lung function in adult life is a critical objective marker of good lung health, strongly associated with other major chronic diseases (for example cardiovascular disease) and is a major independent determinant of overall health status (physical and mental health, quality of life, exercise capacity, independent living).

We will

1. identify determinants and risk factors (behavioural, environmental, occupational, nutritional, other modifiable lifestyle, genetic) of poor lung growth, excess lung function decline and occurrence of low lung function, respiratory disability and COPD within existing child and adult cohorts

2. validate the role of risk factors for poor lung growth, excess lung function decline and occurrence of low lung function, respiratory disability and COPD through a) integration of data from relevant disciplines (clinical, epidemiological, molecular, genetics, epigenetics) and b) valorisation of knowledge gained from the cohort-related population-based biobanks

3. generate and integrate information on change in DNA methylation patterns with ageing to identify risk factors and validate the role of these risk factors

4. generate a predictive risk score that takes account of the combined effects of factors that cause poor lung growth and lung function decline and lead to low lung function, respiratory disability, and COPD in older adults

This work will provide an evidence base for risk identification that can underpin future preventive and therapeutic strategies and policies.

AIMS:

Health risk behaviors related to substance (ab)use and externalizing problem behavior threaten the healthy development of children and adolescents. Specifically, early onset substance use and conduct problems are key predictors of later addiction and clinical-level antisocial personality disorder. These are greatly debilitating conditions for any individual, but also the societal costs associated with these conditions are enormous. Harsh or inconsequent discipline, lack of warmth and sensitivity, abuse by parents, and parents' dependence on substance use are among the strongest predictors of substance (ab)use and conduct problems in childhood and adolescence.

Previous research over the past decade has indicated that family risks may have a particularly detrimental effect in children carrying specific genotypes, that regulate the activity within dopaminergic, serotonergic, GABAergic, and cholinergic pathways. In our proposal, we aim to identify gene-environment interactions that predict health risk behaviors in childhood and adolescence - focusing on genetic risk on the one hand, and on specific family and parenting risks on the other hand. Although the field of GxE research holds great promise, until now it has proven difficult to replicate GxE findings. This has two main causes: first of all, a lack of statistical power in most correlational studies focusing on GxE (e.g., Duncan & Keller, 2011) and secondly, a lacking specification of possible explanatory mechanisms underlying GxE (Dodge, 2010; Weeland, Overbeek, Orobio de Castro, & Matthys, 2014).

Thus, our overall aim is to 1) conduct cross-validated tests of gene-environment interactions related to the development of common addictive behaviors (smoking, alcohol, marijuana) and conduct problems or antisocial behavior in childhood and adolescence, and 2) to test possible mechanisms underlying this gene-environment interplay. With regard to this latter aim, we aim to examine specficially whether children's temperamental traits, such as for instance (but not limited to) levels of (dis)inhibiton and reward and punishment sensitivity, can be identified as explanatory factors underlying the gene-environment interactions that lead up to the development of health risk behaviors.

Hypotheses

The major hypothesis is that there are environmental factors, hitherto unsuspected, that have an effect on the risk of preterm delivery. It is anticipated that such environmental effects may interact with the genetic markers of mother and/or fetus, or work through DNA methylation.

Specific aims will determine, using a hypothesis free approach, whether any of the following are associated independently with preterm delivery: lifestyle of parents and grandparents (including smoking, alcohol, drug abuse, caffeine and activity levels); other physical exposures (medications, diet, work-based chemicals, noise, radiation); psychosocial features of parents and grandparents (including stressors based on life events, social circumstances, financial difficulties, domestic abuse, abuse of the parents in childhood); and mental and physical health of parents and grandparents. For all relationships identified, assessments will be made concerning relevant genetic and epigenetic associations, and their interaction with the exposures.

OBJECTIVES (note these will be achieved within the collaboration; ALSPAC will contribute to some but not all and for each objective more than one study will always contribute)

1a. To determine how metabolomic profiles change with age from birth through to old age.

1b. To explore the extent to which markers of reproductive health (age at menarche, age at first birth, parity, age at menopause, transition through menopausal transition) alter general age related trajectories

1c. To explore the associations of adiposity and change in adiposity with change in metabolomic profiles with increasing age.

1d. To explore the associaitons of reproductive hormones and change in reproductive hormones with change in metabolomic profiles with increasing age.

2a. To determine the extent to which blood-based metabolic profiles (assessed at different ages), in addition to clinical characteristics, improve stratification of women into different levels of risk for infertility

2b. To determine the extent to which blood-based metabolic profiles improve risk prediction of live birth obtained from IVFpredict.

2c.To determine the extent to which blood-based metabolic profiles (assessed at different pre-pregnancy and gestational ages), in addition to clinical characteristics, improve stratification of women who become pregnant into different levels of risk for hypertensive disorder of pregnancy, gestational diabetes, preterm birth, large for gestational age and small for gestational age.

2d. To develop the best prediction tools for single and combined adverse pregnancy/perinatal outcomes

3a. To determine the role of blood-based metabolic profiles (assessed at different ages) in the causal pathway between greater adiposity and subsequent reproductive and perinatal outcomes

3b. To determine the role of maternal gestational and fetal (assessed in cord-blood) blood-based metabolomics in the causal pathway between maternal gestational adiposity and weight gain and subsequent offspring (and the next generation - grandchildren) adiposity and cardiometabolic health

4a. To determine the extent to which metabolic profiles change as women go throug the menopausal transition and determine whether any change is independent of age related change

4b. To determine the extent to which reproductive hormone changes as women go through the perimenopausal transition are related to menopausal transition changes in metabolic profiles

4c. To determine the extent to which any menopausal transition changes in metabolic profiles result in future cardiometabolic diseases.

We have investigated BMI in childhood using different time points in genome-wide association settings. Our results suggest that the genomic profile differs according to the nature of the phenotype being investigated; optimising BMI appropriattely for each age group, so that the correlation of BMI with height is removed, resulted in SNPs in ADCY3 being genome-wide significant while this was not the case when BMI was used without this adjustment (Stergiakouli et al under review).

As an extension of this project we would like to perform a genome-wide association study of body shape perceptions using data from the "Growing up" questionnaire. This questionnaire was completed by the children when they were ~ 77 months and asked them to choose one from a series of pictures which best reflected how they thought their body looked.

We are interested in comparing the results from our previous GWAS of BMI in childhood with a GWAS of body perception. We would also test if top hits from published GWAS on BMI in childhood and adulthood can be replicated using body perception data.

Aims

To extend the investigation of the relationship of maternal iodine status in pregnancy with child neurocognitive outcomes. To explore the relationship between repeated iodine measures during pregnancy and child neurocognitive outcomes.

Aims:

1. Assess elastic nets, random forests and support vector machine regression models for their applicability to the outlined problem.

2. Identify sets of genes that contribute to each metabolic phenotype.

3. Carry out functional analyses on identified gene sets.

4. Compare gene sets between time points and between similar metabolite measures.

The overall aim of this proposal is to develop statistical methods and paradigms to better leverage the considerable amount of peripheral blood DNA methylation data that has been (and will be) collected from large scale epidemiological studies. In particular, our focus is on developing and optimizing statistical methods of using DNA methylation profiles to "tag" environmental exposures, so that this information can be better utilized to investigate the genetic and environmental basis of complex traits and diseases.

The specific aims of the proposal are:

Aim 1: To assess the degree to which medically relevant environmental exposures can be tagged by DNA methylation profiles from peripheral blood and to investigate the ability of different statistical approaches to tag these exposures.

Aim 2: To investigate the degree to which "DeMendelization" of methylation profiles (i.e removing the effect of genetic variants) can improve tagging of environmental exposures.

Aim 3: To investigate whether genome-wide association meta-analyses of methylation profiles that index environmental exposures could be used to identify genetic variants underlying medically relevant exposures known to have a heritable component.

Aims

To explore the distribution and correlations of school exclusion in children and young people in ALSPAC, with particular focus on early risk markers, concurrent needs, developmental trajectories and later outcomes.