Overarching aim The aim is to clarify finer clinical differences, their aetiology and the long-term outcomes, within the subgroup of autism with IQ greater than 70. Specific Objectives 1. To investigate heterogeneity within a group of children with high-functioning autism by assessing within-group differences on language and communication abilities at the age of 2-3 years, 5-6 years and 8-10 years. 2. To assess longitudinal association between the three components of language: pragmatics, grammatical and syntactical; at three time periods: Time 1: 2-3 years; Time 2: 5-6 years; Time 3: 8-10 years

Aims: 1. To measure and report the lifetime experience of manic symptoms within the ALSPAC cohort at age 21+ using the Hypomania Checklist 32 (HCL-32), a well validated self-report questionnaire for the identification of manic symptoms. 2. To use existing data on the cohort to identify risk factors for the experience of significant manic symptoms by age 21+. 3. To use existing prospective data on the cohort to 'map out' the trajectory of symptoms in individuals who appear to either have bipolar disorder or be at very high risk of developing bipolar disorder.

Hypotheses: In order to address Aim 3 of this study (mapping the 'bipolar prodrome'), we will use existing prospective measurements of cognitive function, anxiety symptoms, depressive symptoms and psychosis-like experiences to assess whether there exists an identifiable trajectory of symptoms which predicts the experience in late adolescence/early adulthood of manic symptoms.

The Personality Consortium is a large-scale collaborative effort to conduct a genome-wide association meta-analysis on all GWAS datasets with personality data. A challenge is that a variety of instruments have been used to assess multiple aspects of personality and also that the same construct, e.g. Neuroticism, has been assessed with different instruments. These instruments include Costa and McCrae's revised NEO Personality Inventory, Eysenck's Personality Questionnaire, Cloninger's Temperament and Character Inventory, the Amsterdamse Biografische Vragenlijst, the Minnesota Multiphasic Personality Inventory, the International Personality Item Pool and others.

We propose to use Item Response Theory (IRT) analysis to map the personality data from the different questionnaires to the same constructs. The advantages of this approach include increased statistical power because of increased sample size and enhanced precision in measuring personality traits by taking a latent variable approach. Currently, several cohorts, with a total sample size of ~150,000 subjects (of which ~60.000 have GWAS data), have expressed an interest in taking part and sharing data.

Aims and Hypotheses: This study will examine whether altered methylation status of regulatory genes involved in adaptive immunity contributes to the initiation and/or persistence of RA, by aiming to identify DMRs using the following strategies:-1.Whether DMRs can be identified which are related to the presence of active RA will be investigated. 2.Whether a subset of DMRs are associated with predisposition to/initiation of RA will be investigated, by comparing methylation patterns in blood samples obtained from ALSPAC maternal controls during pregnancy, with those from those participants who were disease free at the time, but went on to develop RA. 3.Whether genetic risk factors for RA act by predisposing to altered methylation will be addressed by examining whether methylation differences identified above as being associated with RA, are related to specific single nucleotide polymorphisms.

Outcomes: Genome-wide methylation will be analysed in early and late blood samples from 1000 ALSPAC maternal controls using the 450k illumina methylation platform as part of the ARIES study. The same method will be used to analyse early and late blood samples from ALSPAC mothers found to have RA, and blood samples from local RA cases. Genome-wide SNPs will be available, imputed to the latest version of hapmap, in ALSPAC cases and controls.

The aim of the study is to examine the association between prenatal alcohol exposure and criminal activities and/or proxies of criminal behaviour. We hypothesis that offsprings of mothers who drank during pregnancy especially heavy drinking of greater than 21 units a week, will be at an increased risk for adolescents antisocial activities and conversely criminal activities in adulthood. We further hypothesize that a graded risk-response outcome will emerge with a relationship between the quantity of alcohol being correlated with the number and intensity of antisocial activities and criminal activities.

The risk for youth criminal or antisocial activity will be modeled using logistic regression with PAE as predictor and controlling for the confounding variables listed previously. Additionally, the dose-response relationship between alcohol ingested in pregnancy and number of antisocial or criminal activities will be modeled using Poisson regression. This will take into account the low numbers of pregnant women with excessive alcohol use. The paternal use of substances will help control for the maternal use during pregnancy including a comparison with the maternal use of substances outside of the period of pregnancy. The results have implications for both preventative endeavors and service planning.

Aims:

To examine the impact of newly developed methods for missing data.

Methods:

In particular, new methods have been developed to maximise efficiency when covariate data are MNAR (and therefore complete case unbiased and MI biased). In the first instance, we would like to analyse a sample of 2000 women from ALSPAC, modelling birthweight (outcome) on weight before pregnancy (self-report), adjusting for maternal age, parity, education and smoking and sex of offspring. Data on estimated pre-pregnancy weight (from GWG models) will be used to show that data on pre-pregnancy weight are MNAR.

AIMS

The aim of this project is to test and develop a proof of principle for a molecular-based bioinformatics approach to phenotype prediction.

HYPOTHESIS

The hypothesis is that single nucleotide variations in humans leading to non-synonymous changes in protein coding genes will affect the phenotype of the individual and that it is possible to predict this from knowledge of the protein.

METHODOLOGY

We are already able to predict with a reasonable degree of success whether a mutation is likely to have a phenotypic impact using bioinformatic techniques to compare the non-synonymous mutation to the wild-type using hidden Markov models trained on all proteins of known structure. Basically we compare the emission probability from the hidden Markov model of the wild-type and mutated amino acids; a big difference indicates that the change will not be well supported by the structure and function of the protein. In addition to this, independent work has shown that we are able to predict the function of an unkown protein in most cases (this is the field of protein function prediction). As well as gene function we are able to associate phenotypic outcomes from, e.g. knockouts in mice or known disease-causing mutations in humans, with many proteins. The approach which we wish to test on the ALSPAC data is the combination of the likelihood of a phenotypic impact of a mutation with phenotype and gene function associations. We wish not only to consider single point mutation outcomes but also multi-loci variations which, although individually may not have a significant predicted phenotypic outcome, when taken together across the genome could have a summed effect which is measurable in the phenotype.

DATA

The object of this is not to detect new associations but to seek a proof of principle that some phenotypic information may be inferred from molecular data alone. As such we require the genome sequence information for as many indivuals as possible, with all associated phenotype data for the purpose of validating predictions.

Aims: To examine the relationship between length of the preceding birth interval and neurodevelopmental outcomes in childhood in a birth cohort study from a high-income country (ALSPAC ) and in two birth cohorts from a middle income country (the 1993 and 2004 Pelotas birth cohort studies, from Brazil).

These studies were chosen to reflect populations with different levels of wealth and of socioeconomic inequalities, as well as their similarities in variable definitions and the availability of comparable questionnaires and follow-ups done at similar ages.

Hypotheses: Previous studies have shown the association between short inter-pregnancy intervals (especially those shorter than 12 months) and several maternal and perinatal adverse outcomes. Recently short inter-pregnancy intervals have also been associated with an increased risk of developing autism and schizophrenia. It is hypothesised that the risk of adverse neurodevelopment outcomes may be high among children that are conceived following a short inter-pregnancy internal, when maternal folate stores are still being replenished. The period immediately following the birth of a preceding pregnancy may be a particular period of risk where depleted maternal nutrient reserves could affect neurogenesis during early fetal development. In order to examine causality of the association being tested, we will also examined the association between post-birth inter-pregnancy interval (time between the index birth and conception of the subsequent live birth), where the hypothesis regarding folate/micronutrien depletion would not apply.

Over the last 4 years(2007-2011) we have collected detailed longitudinal information on mental health, physical health, environmental measures, demographic information and biological measures associated with mood problems from the child and adolescent offspring of adults with depression (i.e. a high risk sample). Part of the remit of the study was to develop a basic quick screening and risk prediction tool for adolescent depression to ensure that the research findings could be applied to clinical practice. A set of predictors for screening for current and predicting risk for future major depressive disorder amongst adolescents has been identified using data from this study. Developing an effective risk prediction tool: A pilot computerised version of this tool for GP software has been developed based on early results and is being piloted in a single practice. However it is clear from the scientific literature that, given the complexity of illness, there is a need to ensure that risk prediction tools are accurate so need considerable refinement by piloting. It is also clear that these tools have to acceptable to users and service providers and the users and user-friendly and pragmatic for use in real life situations. Once the predictors have been validated in the external dataset it is planned to apply for funding for a 2 stage project in which the first stage would be qualitative, health professionals, school counsellors and other agencies dealing with the mental health of young people and would include developing and further piloting the software) and the second stage would be a formal pragmatic trial of evaluating this web-based screening and risk prediction tool for adolescent