The overall aim of the study is to characterize the development of the excessive exercise and to identify the genetic basis of this phenotype. Genetic regions have been selected on the basis of mouse genetic mapping studies revealing genetic loci for baseline physical activity levels. Specific aim 1: Validation of association between genetic candidate regions and physical activity levels. Hypothesis 1: There is a significant association between genetic variation in candidate regions and the self-reported as well as objectively measured participation in EE. Specific aim 2: Assessing the developmental trajectories of EE in females in childhood and adolescence and their relation to BMI. Hypothesis 2: Participation in EE is a phenotype developing during adolescence and associated with lowered BMI.

The ALSPAC analysis will contribute to a large-scale GWAS meta-analysis conducted within the EAGLE cohort. A case/control status of 'Urticaria ever' will be derived using the questions listed in the table above. This derived variable will then be used to conduct a case/control genome-wide association study within ALSPAC using the imputed genome-wide SNP data of the offspring. Summary results for each SNP will transferred to the meta-analysis team in Munich. No individual level data will be transferred. The team in Munich will meta-analyse the ALSPAC data along with several other cohorts from the EAGLE consortium.

Aims: Compare methylome in normal white blood cells before and after puberty.

Hypothesis: Puberty is accompanied by characteristic changes in the epigenome that mediate greater leukocyte inflammatory responses in the post-pubertal age.

Variables: Normal males and females sampled and tested for DNA methylation at pre- (e.g. ~age 7) and post- pubertal ages (e.g. ~15 +).

The question: Why do children survive when adults do not? One aspect of the puberty transition is extraordinary but neglected: pre-pubertal children show a remarkable resistance to mortality from the same severe infections, sepsis and trauma that are otherwise commonly fatal in post-pubertal individuals (adults). Studying the biology behind resistance and how it is lost in the puberty transition could provide a treasure trove of insights into basic mechanisms and new leads for drugs.

The rationale: Blood leukocytes of children consistently produce less pro-inflammatory, and more anti-inflammatory cytokines than their adult counterparts. The natural resistance of children to mortality from influenza and other infections is lost at puberty, implying a hormonally-mediated (and deleterious) 'reprogramming' of the host response. Our central hypothesis is that a specific epigenetic program in leukocytes mediates the superior resistance of children to mortality.

Analysis plan: Given the overlap with longitudinal modelling of the HM450 ARIES data set, it is proposed that data for this project will be analysed in Bristol under the supervision of Caroline Relton by a visiting researcher from HSPH.

This project aims to investigate the maternal and fetal genetic contributions to pre-eclampsia and pregancy complications, and will attempt to identify common HLA genetic variants from GWAS within ALSPAC.

Pre-eclampsia is a pregnancy-specific syndrome diagnosed by the accompanying increase in maternal blood pressure and proteinuria (Roberts and Cooper, 2001). The condition generally affects around 3-5% of pregnancies, though among women with complete obstetric data within ALSPAC , 2% had pre-eclampsia and 16% had gestational hypertension (Lawlor et al, 2011). In pre-eclampsia, endovascular invasion of the maternal spiral arteries by the cytotrophoblast is compromised and placental perfusion is weakened. It is believed that this decreased placental perfusion is in part the result of immunogenetic components of the mother and fetus.

The genetic constitution of mother and baby might be an important determinant of successful implantation and therefore pregnancy complications such as pre-eclampsia. Immune mechanisms are linked to the hypothesis that the maternal immune system is challenged by a genetically foreign fetus to different extents depending on the maternal and fetal genotypes.

According to Redman and Sargent (2010), maternal adaptation to fetal (paternal) alloantigens is crucial in the early stages of pregnancy. Observational studies support this idea and point to risk factors for pre-eclampsia such as primiparity, a short interval between first coitus and conception with the same partner, oocyte donation, artificial donor insemination and a change in partner, all of which may have an immunological basis (e.g. Dekker 2002; Dekker et al, 2011). Dekker et al (2011), predict that 35% of the variance in susceptibility to PE is attributable to maternal genetic effects; 20% to fetal genetic effects and 13% to the couple effect. Supporting this is the identification of paternal SNPs with associations with PE in the SCOPE consortium (http://www.scopestudy.net/default.aspx).

However, pre-eclampsia is proposed to be a two-step disorder, with the first step relating to poor endovascular invasion (placental pre-eclampsia) and the second relating to maternal constitutional factors that might increase sensitivity to placental ishaemia and increased oxidative stress (maternal pre-eclampsia). In this study, we are investigating the immunogenetic components of the mother and fetus in particular, and therefore will attempt to separate any common variants which relate to maternal constitution. This will be done by focusing in particular on the Human Leukocyte Antigen (HLA) system related to immunotolerance.

In terms of previous successes at identifying genetic loci predisposing to pre-eclampsia, numerous candidate gene studies and linkage studies have been performed, and various alleles have been identified, includes human leukocyte antigen variants. For example, pre-eclampsia is more frequent in women who are homozygous for inhibitory A haplotypes (AA) of KIR, especially if the fetus is homozygous for the HLA-C2 genotype (Hiby et al, 2004). However, there has been limited success at identifying common variants through GWAS studies, such as GOPEC (http://www.gopec.org/) and GENPE (http://www.genpe.org/). We propose that this limited success is due to the fact that only the maternal genome has been considered in these association studies, and we would like to investigate the contribution of both maternal and fetal genomes, and in particular the HLA variants.

Gestational hypertension may also be considered as an outcome in our search for HLA variants as it has been proposed that pre-eclampsia is at the upper range of a normal distribution in blood pressure and maternal vascular stress during pregnancy. Intra-uterine growth restrictuion and pre-term birth may also be associated with similar abnormal physiological changes during placentation, and therefore potentially to immunogenetic processes. In addition, inclusion of gestational hypertension, pre-term births and low birth weight would provide a higher sample size of cases for genotyping.

AIMS:

- To genotype and impute variants within the HLA region in both mothers and children in ALSPAC.

- To investigate associations between:

- Maternal HLA types and maternal phenotypes (pre-eclampsia, gestational hypertension)

- Maternal HLA types and child phenotypes (gestational age and birthweight)

- Child HLA types and maternal phenotypes (pre-eclampsia, gestational hypertension)

- Child HLA types and child phenotypes (gestational age and birthweight)

- HLA discordance between mother and child and maternal/child phenotypes (pre-eclampsia, gestational hypertension, gestational age, birthweight)

HYPOTHESES:

- The limited success of previous GWAS's investigating pre-eclampsia is due to the fact that only the maternal genome has been considered. This study will therefore investigate both the maternal and fetal HLA genotypes using HLA imputation of GWAS data in ALSPAC.

- Hypotheses to be considered during this task are:

- Specific maternal or child HLA variants are related to immuno-incompetence in pregnancy and the onset of pre-eclampsia and other pregnancy complications.

- The immune/immunogenetic maladaptation hypothesis (Dekker and, 1988)

- Parental sharing of human leukocyte antigens (HLA) may be associated with adverse pregnancy outcome (Ober, 1998)

-Mismatch of certain maternal and fetal HLA alleles may be associated with adverse pregnancy outcome.

EXPOSURE VARIABLES:

- HLA variants (those expressed by the trophoblast HLA-E and HLA-F, HLA-G and HLA-C; those not expression by the trophoblast e.g. HLA-A, HLA-B HLA-DR1/DR2, soluble class I antigens which may interact with HLA-G (Hvid et al, 2005) ) in mother and child.

OUTCOME VARIABLES:

- pre-eclampsia

- maternal hypertension

- pre-term birth

- low birth weight

CONFOUNDING VARIABLES:

No confounders, but potential mediators e.g. maternal BMI, previous history of hypertension and diabetes, parity, age of mother.

BIBLIOGRAPHY

Roberts, JM, Cooper, DW. Pathogenesis and genetics of pre-eclampsia. Lancet. 2001. 357:53-56.

Lawlor, DA, Macdonald-Wallis, C, Fraser, A, Nelson, SM., Hingorani, A, Davey Smith, G, Sattar, N and Deanfield, J (2012) Cardiovascular biomarkers and vascular function during childhood in the offspring of mothers with hypertensive disorders of pregnancy: findings from the Avon Longitudinal Study of Parents and Children. Eur. Heart J. 33, 335-345

Redman CW, Sargent IL. Immunology of pre-eclampsia. Am J Reprod Immunol. 2010;63:534 -543.

Dekker, G, 2002. The partner's role in the etiology of preeclampsia. J. Reprod. Immunol. 57, 203-215.

Dekker G, Robillard PY, Roberts C. The etiology of preeclampsia: the

role of the father. J Reprod Immunol. 2011;89(2):126-132.

Dekker, G, Robillard, PY, Hulsey, TC. Immune maladaptation in the etiology of preeclampsia: a review of corroborative epidemiologic studies. Obstet Gynecol Surv 1998. 53:377-382.

Ober, C, 1998. HLA and pregnancy: the paradox of the fetal allograft. Am. J. Hum. Genet. 62, 1-5.

Infants showing slow growth in infancy compared to their peers have been identified in ALSPAC and their growth followed up to 13 years of age. This work has shown that if they grew slowly between birth and 8 weeks they then grew very fast between 8 weeks and 2 years with their growth in weight outstripping their growth in height. By 13 years they were very close in weight and height to their normal growing peers. A second group who grew slowly between 8 weeks and 9 months were very slow in catching up with their normal peers and remained much lighter and shorter at 13 years.ALSPAC has collected data on feeding behaviours, difficulties and foods and drinks consumed by these children at 4 weeks, 6 months, 15 months, 2 years and so on. These include breast and formula feeding as well as age of introduction of solid foods and other drinks. There are also questions about parental feeding practices including feeding on demand or by schedule, use of food as rewards and attitudes to feeding. On a 10% subsample of the children there are detailed diet diaries at 4, 8 and 18 months these give a great deal more information about types of foods fed and timing of meals and drinks. Two investigations will be carried out one into the early slow growing group and the other into the late slow growing group using the rest of the cohort as a comparison group. The reason for the division is that we have previously shown very different recovery growth patterns in these two groups and it important to determine if nutritional or behaviour differences are determining these differences in growth trajectory.

The prevalence of childhood overweight and obesity is increasing around the world. Childhood obesity has been shown to be related to adult obesity and other health related problems. Studies have reported that a high intake of protein in early life is related to rapid early growth which may be a risk factor for obesity in later childhood. In ALSPAC dietary information has been collected repeatedly from a 10% sub-sample of the ALSPAC cohort (around 1000 children) at the following ages: 8 months, 1 1/2 years, 3 1/2 years, 5, 7 & 10 years. All the dietary data have been coded and prepared and are ready for use. Children will be allocated to quintiles according to their protein intake at 8 months of age in the first instant. Foods will be investigated to ascertain the sources of the protein in the diet at 8 months and the degree of tracking of protein intakes will be assessed at 1.5, 3.5, 5.0, 7.5 & 10 years. The tracking of protein intakes from one age to the next will be assessed using a multinomial logistic regression to estimate the odds ratio for being in the highest quintile for protein at the each sequential

In collaboration with Professor John Henderson, the Cardiff group has focused on the preterm and intrauterine growth retardation (IUGR) populations of the ALSPAC cohort to assess their cardiorespiratory outcomes. The data show deficits in lung function that are significant in both populations at 8 years of age but seem to improve later at 15 years of age. However, it is unclear if these deficits are related to clinical outcomes. Thus we wish to extend the studies to investigate if these deficits in both groups, i.e. children who were born preterm or with IUGR, have clinical implications due to the lung function decrements. Recent publications on the cohort associate lower levels of physical activity with increased adiposity and blood pressure- both risk factors for cardiovascular disease later in life but we wish to extend our studies with John Lowe who will register for a higher degree (PhD) with Professors Kotecha and Henderson acting as supervisors for this natural extension to our collaborative efforts. The specific aim of the projects would be to: Investigate the relationship between prematurity and IUGR with physical activity in the cohort and to assess the relationship of physical activity with pulmonary function measurements, cardiovascular outcomes and body composition (which we are investigating at present).

We would primarily want to collect dietary data in the YPs but also hope with this proposal you will consider inclusion of dietary questions in the next Mother and Father questionnaires.

We have previously sought funding to collect new dietary data in both YPs and Mums but have not been successsful to date. We will continue to seek funds that would contribute to the data collection costs that we are poroposing and would provide nutrition support to derive nutrient intakes (if the full FFQs are included).

Ideally we would like to include a full Food Frequency Questionnaire (FFQ) similar to that used in the mothers previously. However we understand that the current YP Q being prepared is likely to be full and therefore a complete FFQ may not be considered this time around. We have therefore suggested in the QPF (attached) a considerably shortened version based on results we have obtained from dietary pattern analyses focussing on the most important foods that describe differents in dietary intake. Using this would mean we could obtain some vital dietary information but this would not be sufficient to derive any nutrient intakes; however, we could still create dietary patterns.

In addition (or possibly in the case of YPs, instead of any FFQ) we request the inclusion of a series of food behaviour questions which we feel will be really important in examining the reasons why people eat the way they do and may therefore be contributing factors to health outcomes such as obesity and other CVD risk factors for example.

Aims

The aims of this project are to assess the long-term effects that technology consumption may (or may not) have on an individual's development. Previous research into this area tends to look at specific subtypes of video games, or else categorise technology using terms which are too broad (e.g. 'internet use'). Moreover, such studies tend to use small populations of undergraduate students. This project would address these shortcomings by assessing long-term social and cognitive development in children who have be exposed to various, complex and interacting forms of technology. Very broadly, the project will look at how usage behaviour from an early age (9-12 years) predicts social behaviour and mental health at a later age (15-18 years).

Research Questions

1) How does 'screen time' (i.e. the amount of time that an individual spends per day or per week using some form of screen-based technology) result in positive or negative effects on the individual's prosocial behaviour? Does the context in which the technology is used (i.e. work vs leisure) matter?

2) How does the type of video game being played (e.g. aggressive vs non-aggressive), and the manner in which is it played (i.e. single vs. multiplayer) impact upon behaviour?

3) How does the use of social media affect an individual's ability to empathise with others?

Exploratory analyses will be used to determine what sort of effects light or heavy video game or technology usage (taking into consideration the types of video games being played and technology being used) have on an individual's ability to function normally in social settings later in life.

Exposure variables

1) Screen time. This is a broad measure that takes into account all instances of an individual's use of screen-based technology, and will include computer/internet usage, mobile phone usage, and console-based video game usage.

2) Video game usage. This measure will be broken down into three subcomponents; content (i.e. whether the video game could be primarily classed as aggressive or non-aggressive), context (i.e. whether the game is played online, played with others who are physically present in the room, or played with others who are not physically present in the room), and time spent playing.

3) Social media usage. This measure will attempt to assess the proportion of time that individuals spend on the internet whilst engaging in some form of social media, in particular Facebook and Twitter.

Additional factors that will be taken into account will be the proportion of time that computer use is for work or for pleasure, the amount of time socialising with peers, and the amount of time spent playing (both indoors and outdoors).

Outcome variables

1) Psychopathological factors. These mesaures will include assessments of aggression, depression, and anxiety in the individual.

2) Behavioural factors. These measures will include levels of conduct disorder reported at school, and the individual's ability to empathise with others.

3) Academic performance.

Confounding variables

1) Sex and socioeconomic status will likely impact upon access to, and desire to engage in, specific types of technology use.

2) Mental health and relationship status of parents may also impact upon the desire to engage with different types of technology, as well as predisposing individuals to depressive or anxious behaviour. As such, these factors will also be taken into consideration.

3) Parental monitoring will likely impact upon amount and type of aggressive behaviour.