AIMS: To establish the overlap in genetic associations for cleft lip/palate and for normal facial variation.

HYPOTHESES: (1) SNPs associated with cleft lip/palate will also be associated with normal facial variation. (2) SNPs associated with normal facial variation will also be associated with cleft lip/palate

EXPOSURE VARIABLES: Genome-wide SNP variables.

OUTCOME VARIABLES: face shape variables.

CONFOUNDING VARIABLES: Age, sex

OUTLINE: Prof Nothen/Dr Ludwig (University of Bonn) will provide us with a list of SNPs that they have found to be associated with cleft lip/palate. We will test these SNPs for association with normal facial variation in ALSPAC. Reciprocally, we will identify a list of SNPs that are associated with normal facial variation in ALSPAC and Prof Nothen/Dr Ludwig will test these SNPs for association with cleft lip/palate in their data. Both studies will also generate polygenic scores for their respective traits (incorporating thousands of SNPs from across the genome). The SNP lists (and results) used to construct these polygenic scores will be exchanged to allow these scores to be tested in the reciprocal group (and for the reciprocal phenotypes).

Aims: (1) Is there a direct link, independent of cognition, between parental SES and NCS in childhood?(2) What specific socio-environmental factors in the child's home, school and neighbourhood environments influence the link between parental SES and child NCS? (3) How does within-in SES variation impact the socialisation of NCS? Specifically, given the presence of environmental risks, what are the most important protective factors for NCS development?(4) Are there intergenerational links between maternal school attitudes and childhood experiences, and NCS in offspring?

Confounding variables:

(1) Childhood cognition, as measured at age 8 with an IQ test and by teacher reports of general ability level.(2) Childhood temperament, as measured at 24 months.(3) Socio-environmental exposures (in the home, neighbourhood, and school) measured at the same time point as the outcome variables.

Aims: The aim of this body of work is to develop a greater understanding of which infants are born needing support after birth and identify high risk infants who may benefit from interventions or changes in practice. This project also aims to provide greater understanding of these risks for women, from which they can make informed choices for their own births.

To do this we anticipate three components to the project:

1) Modeling of birth condition.

2) Gene polymorphisms

3) Placental examination

A final analysis will be designed after the 3 components are complete whereby a comprehensive model of poor condition at birth is derived.

Summary of proposed project: Through these three arms we hope to understand the processes through which infants are likely to be born in poor condition, and identify points at which the risk could be reduced or prevented.

Aims: To assess the association between gambling behaviours and other risk taking behaviours at age 17; To examine the extend to which these potential associations can be explained by the young person's/parental socio-demographic background characteristics, childhood antecedents such as hyperactivity and conduct disorders and parental gambling patterns.

Outcome variables: - Frequency of gambling (>= weekly)- Scope of gambling (4 or more gambling activites in the previous 12 months)- Problem gambling (Problem Gambling Severity Index score) .

Exposure variables:- Nicotine dependence (Fagerstrom Test of Nicotine Dependence)- Problematic Alcohol use (AUDIT scale)- Problematic cannabis use (CAST scale)- Inhalant use- Harder drug use- Sexual risk behaviour- Antisocial behaviour.

Variables proposed to be examined as potential mediating variables or confounders: - Socio-economic indicators - Gender- Ethnicity- Maternal alcohol, smoking and substance use- aternal depression (antenatal, postnatal)- Hyperactivity and conduct problems (SDQ) - Depressive symptoms or other indicators of mental health in YP- Parental monitoring- Parental gambling patterns- Stressful life events since age 12 (YP).

Aims: The aim of this project is to comprehensively assess the properties of genomic variation in light of their use for Mendelian Randomisation. It will follow on from research conducted by Davey-Smith et al (2007, PLoS Med) using Genome-wide data that was outside the scope of the paper when it was published. For more information see 'Justification' section.

Hypotheses: We hypothesise that clinic variables taken at any one age will show high levels of correlation (greater than would be expected by chance). In contrast, one would not expect the same inter-correlations to exist either within a collection of genotypic data or across genetic variation and randomly selected phenotype data.

Exposure, outcome and confounding variables: This is not an association study for risk, per se, rather an assessment of the properties of genetic and phenotypic data. As such there will be no outcomes and exposures.

Data: The data that is required for this study will be all that is contained within a "standard" ALSPAC clinic assessment at around age 7 year along with genome-wide common variation for individuals found within that clinic.

Aims: Iron deficiency has been associated with ADHD and low IQ in epidemiological studies (Froehlich et al., 2011), but this association is likely to be confounded with social class and other demographic variables and health behaviours. Our aim is to use Mendelian randomization to test the hypothesis that iron deficiency is a causal risk factor for ADHD and low IQ. A number of genotypes have shown replicated associations with serum transferrin and/or soluble serum transferrin and related phenotypes (Benyamin et al., 2009; Kamatani et al., 2010; McLaren et al., 2011; Oexle et al., 2011; Pichler et al., 2011) and could be used as instruments for iron status. Although our focus is on ADHD and IQ, we are requesting a broader set of outcome variables that represent related phenotypes (e.g., motor and language abilities, conduct problems).

Hypotheses: We hypothesise that if iron deficiency is a causal risk factor for ADHD and low IQ, then (1) selected gene variants will be associated (in predicted directions) with haemoglobin levels (measured at 8, 12, 18, 31, 43, 61 months and 7 yrs) and/or serum ferritin levels (measured at 8, 12, 18 months); (2) haemoglobin levels (measured at 8, 12, 18, 31, 43, 61 months and 7 years) and serum ferritin levels (measured at 8, 12, 18 months) will be associated with ADHD symptom scores, clinically-signficant levels of ADHD and IQ scores (measured from 7 to 10 yrs); and (3) selected genotypes will be associated with ADHD symptom scores, clinically-significant levels of ADHD, and IQ scores.

Exposure variables: serum ferritin (8, 12, 18 months), haemoglobin (8, 12, 18, 31, 43, 61 months and 7 years), HFE C282Y (rs1800562); TMPRSS6 (rs855791), PCSK7 (rs236918), TF (rs3811647)

Outcome variables: We propose to look at variables in early childhood and later childhood capturing IQ (e.g., WISC, WPPSI), externalizing problem behaviours (e.g., DAWBA ADHD and conduct disorder scores, SDQ scores), attentional problems, motor ability, and language ability.

Confounding variables: We are aware that previous ALSPAC publications have reported associations between demographic variables (e.g., maternal education) and serum ferritin and haemoglobin levels at 18 months (Sherrif et al., 1999). We are requesting the measure of maternal education so as to replicate the association with haemoglobin levels at 7 years (for the purpose of justifying, in part, the need to use MR). We are also requesting gestational age, child sex, child ethnicity, birth weight, childhood weight & height (8, 12, 18, 31, 43, 61 mos; 7 years), recent infection status, child iron supplements (up to 10 yrs), iron in diet (8, 18, 43, 61 mos; 7 & 10 yrs).

Note: We are aware of ALSPAC publications looking at the relationship between Hb and ferritin with neurodevelopmental outcomes in early childhood (e.g., locomotor activity; Sherriff et al., 2001), but not with outcomes in later childhood. If the associations between iron status and later childhood outcomes have already been examined and found to be non-significant, then we would not want to take this application forward.

References

Benyamin, B., McRae, A. E., Zhu, G., Gordon, S., Henders, A. K., Palotie, A. et al. (2009). Variants in TF and HFE explain ~40% of genetic variation in serum-transferrin levels. American Journal of Human Genetics, 84, 60-65.

Froehlich, T. E., Anixt, J. S., Loe, I. M., Chirdkiatgumchai, V., Kuan, L., & Gilman, R. C. (2011). Update on environmental risk factors for attention-deficit/hyperactivity disorder. Current Psychiatry Reports, 13, 333-344.

Kamatani, Y., Matsuda, K., Okada, Y., Kubo, M., Hosono, N., Daigo, Y. et al. (2010). Genome-wide association study of hematological and biochemical traits in a Japanese population. Nature Genetics, 42, 210-U25.

McLaren, C. E., Garner, C. P., Constantine, C. C., McLachlan, S., Vulpe, C. D., Snively, B. M. et al. (2011). Genome-wide association study identifies genetic loci associated with iron deficiency. Plos One, 6.

Oexle, K., Ried, J. S., Hicks, A. A., Tanaka, T., Hayward, C., Bruegel, M. et al. (2011). Novel association to the proprotein convertase PCSK7 gene locus revealed by analysing soluble transferrin receptor (sTfR) levels. Human Molecular Genetics, 20, 1042-1047.

Pichler, I., Minelli, C., Sanna, S., Tanaka, T., Schwienbacher, C., Naitza, S. et al. (2011). Identification of a common variant in the TFR2 gene implicated in the physiological regulation of serum iron levels. Human Molecular Genetics, 20, 1232-1240.

AIM: The aim of this four year EU project is to analyse existing large cohort studies, with appropriate data already available on air pollution and other relevant risk factors, and to supplement with environmental data on environmental noise exposure. The specific workpackage outlined below relates to a workpackage on Cognition, being managed by Clark, which aims to examine associations between both air pollution and environmental noise exposure on children's cognitive abilities.

HYPOTHESES: This study would link environmental stressors (air pollution & environmental noise exposure) and educational outcome data from the ALSPAC databases, to examine both cross-sectional and longitudinal associations where possible. The following questions would be examined: 1.Is air pollution associated with poorer cognitive abilities? 2. Is noise exposure associated with poorer cognitive abilities? 3. Do any significant effects remain, after taking the co-exposure into account? 4. Is there an interaction effect of air pollution and noise exposure on children's cognitive abilities?

Paper 1: Childhood Literacy skills and psychotic-like-symptoms in a non-clinical population at 12 years of age. (1) Are here any associations between the selected literacy skills (language and speech functioning domains) of a child at ages 7, 8, 9, 10, and PLIKS (interview) at the age of 13 in the ALSPAC cohort? (2) What are the significant predictors of PLIKS after adjustment for confounding variables if there is any? (3) Are any associations stronger with stricter definitions of PLIKS?

Paper 2: Childhood literacy, neurocognition, , motor functioning and psychotic-like-symptoms trajectories in a non-clinical population. (1) Are there any significant associations of literacy variables, neurocognitive variables and motor functioning with PLIKS trajectories? (2) Out of (a) literacy variables, (b) neurocognitive variables, and (c) motor skills, what are the significant predictor variables of PLIKS trajectories?

Paper 3: Genetic variation and childhood social cognition, neurocognitive functioning as predictors of psychotic-like symptoms . Aim: examine the joint relationship between two exposure variables, (a) child genotype and (b) social cognition, neurocognition in the prediction of PLIKS (mean age 12.9). specifically, the purpose is to examine the prediction of PLIKS at age 12 as a function of (a) social cognition measures, (b) neurocognition measures, and (c) genetic variation.

There is strong evidence that rare copy number variants (CNVs) are associated with increased risk of schizophrenia (1-4) and autism (4-7), and a number of lines of evidence point to a shared genetic component to schizophrenia and autistic spectrum disorders. Aims: 1) To examine the frequency of CNVs within a population-based birth cohort. 2) To examine whether individuals with large/rare CNVs are at increased risk of developing autistic traits during childhood. 3) To examine whether individuals with large/rare CNVs show reduced cognitive ability during childhood and adolescence. 4)To examine whether individuals with large/rare CNVs are at increased risk of developing psychotic experiences during adolescence, and whether this association if present is mediated through autistic traits or impaired neurocognitive or social cognitive ability.

Hypotheses: We hypothesise that psychotic experiences, autistic traits, and impaired cognitive function will be more common in individuals with large, rare CNVs. We hypothesise that some CNVs will be shared across all neurodevelopmental outcomes (eg deletions in NRXN1), whilst others will show unique associations with these phenotypes. We hypothesise that autistic traits and impaired cognitive ability are unlikely to mediate any association between CNV burden and psychosis.

Outcomes: 1) Psychotic experiences at age 17 (definite psychotic experiences, and clinical/prodromal states). 2) Autistic traits. 3) Cognitive function.