Proposal summaries
B1415 - Mode of delivery and offspring body mass index overweight and obesity in childhood a systematic review and meta-analysis - 16/08/2012
Our study aims to identify the association between mode of delivery and later life BMI, overweight and obesity, and subsequent addition of such a large dataset will give this study the ability to more accurately identify this link.
B1414 - Interactive analysis for ResearchFest 2012 - 16/08/2012
We often receive feedback from participants that they are unaware of what ALSPAC does with the data it collects, what results have come from the study, or why some of the questions are so 'weird'! ResearchFest 2012 is ALSPAC's first event which tries to answer some of these questions.
This application is to use anonymised datasets to demonstrate to participants in an engaging and visual way what data can look like. Specifically we aim to explain:
1. correlation
2. confounding
3. why we have asked certain questions/ collect certain information:
a) alcohol use* - contains percentages of girls and boys with certain drinking habits at age 10-15. We would like to contrast use in girls and boys as although boys claim to drink more at age 10, girls are drinking more at age 13 and 15
b) birthweight - this is the file which illustrates confounding. We plan to create a line/scatter plot of "coffee" (cups of coffee) with "both" (average birthweights of the children of both smokers and non-smokers combined) to see an inverse association between coffee drinking during pregnancy and birthweight. If you "adjust" for smoking during pregnancy, i.e. stratify on smokers/nonsmokers this association between coffee drinking and birthweight largely goes away i.e. can do a line/scatter plot of "coffee" with "smoker" and "coffee" with "non-smoker".
c) reasonforsex - again, we thought it would be interesting to contrast the different reasons boys and girls had for having sex at age 15 so have included relative proportions of the different answers for boys and girls separately
d) riskbehaviour15_16* - table of various risk behaviours and proportions of individuals (total, boys and girls) partaking in them. We will either contrast boys/girls; or perhaps make the participants guess the % of individuals who had partaken in such risk behaviours at age 15-16 (some of the % ages are suprising - e.g. 42.1% of individuals reported criminal offending or antisocial behaviour. Other data on drug use and sexual activity is also in this file.)
e) tannergrp - this is the "lie-detector" file which shows how boys generally lied about their stage of pubertal development when asked at a young age. We would like to see if we could develop the programme so that participants could plot on a graph the age at which they think boys go through each of the stages. This can then be contrasted with the different trends I have compiled for:
- boys who claimed they were at tanner stage 4 when they were age 8 (which shows that these boys seem to go backwards in their stage of development when asked at later time points)
- boys who claimed they were at tanner stage 1 when they were age 8 (this is the anticipated stage at this age)
- average stage reported by boys in ALSPAC at all ages
- population-average tanner stage at each age
(basically what these trends show is that boys in ALSPAC generally exaggerated their stage of penis development compared with what is expected at the different ages).
[*both these data sets are taken directly from a publication: Patterns of alcohol use and multiple risk behaviour by gender during early and late adolescence: the ALSPAC cohort - MacArthur et al, 2012]
f) "talking fridges" The data collected to provide the PLIKS score remain memorable to many YPs. We would like to highlight that each question individually might seem odd, but together they can show something interesting that correlates with other things e.g. IQ and mothers smoking during pregnancy.
LH, LP, RR and MT are all direct users of ALSPAC data and willing to collate the information so no data buddy will be required.
B1412 - Psychotropic medication use during pregnancy Impact on obstetric neonatal and early childhood outcomes - 02/08/2012
Aims
There is a body of research examining the impacts of medication for depression and anxiety in pregnancy. This suggests that maternal use of SSRIs and Tricyclic Antidepressants may have a negative impact on obstetric outcomes and on child development, when these mothers are compared with those who are unexposed. However, other research, including from the ALSPAC cohort, suggests that maternal depression and anxiety also have negative outcomes for the neonate and young child. Therefore, it is unclear whether the negative outcomes from the medication studies have arisen as a result of the medication, or because of the underlying condition that the medication was intended to treat. For ethical reasons, it has not been possible to conduct a randomised trial, comparing treated and untreated depressed and anxious pregnant women, therefore, databases and naturalistic studies have been used to tease out these relationships.
We plan to carry out a case control study using the ALSPAC data set because:
1. to date, there are only four studies that have managed to compare pregnant women who are and are not receiving medication for their mental health condition. Each of these studies has been very small, and substantially underpowered to detect small group differences or rare events.
2. All of the studies have focused on maternal depression, whereas the literature suggests that maternal stress and anxiety is just as problematic for the developing fetus.
3. None of the existing studies have focussed on outcomes that extend beyond the immediate neonatal period.
The ALSPAC dataset is ideally placed to address these difficulties, given its exceptionally large sample size, its detailed data on both maternal anxiety and depression, and its follow up into childhood and beyond.
Questions / Hypotheses
Do pregnant women using medication for the treatment of anxiety / depression have poorer outcomes on obstetric, neonatal, and early childhood variables than matched depressed / anxious pregnant women who do not use medication, and than a healthy, unmedicated control group?:
Exposure Variables
* Maternal self-reported use of medication for anxiety or depression during pregnancy.
* Maternal anxiety and depression during pregnancy.
* Maternal exposure to other psychotropic medicines
Outcome Variables
Neonatal outcomes:
* Fetal loss
* Neonatal death
* Length of gestation
* Birth weight
* Birth length
* Head circumference
* APGAR score at 1 and 5 minutes
* Length of hospital stay for newborn
* Special Care Baby Unit admission
Early childhood outcomes:
* Mother's bonding with baby
* Child growth
* Colic
* Jitteriness
* Child development
* Child temperament
Confounding Variables
* Maternal socio-economic status
* Maternal ethnicity
* Maternal age
* Maternal use of other agents known to affect development (alcohol, tobacco, street drugs, other prescription and non-prescription drugs).
B1411 - The value of head circumference in identifying underlying pathology - 02/08/2012
Head circumference (HC) is routinely measured in infancy and is widely assumed to be valuable in helping identify children with intracranial pathology or neurodevelopmental problems, and for monitoring such children over time. However the evidence base for screening HC is very limited. Very little is known about the extent to which deviation in head size or growth predicts underlying pathology. A common clinical assessment made where a child has a very large or small head is to compare the child's head circumference centile with that of their parents. However we do not at present know the extent to which children may vary from their parents in head size and we do know how well the existing growth reference (UK1990) age 20 fits to the normal distribution of adult heads. The ALSPAC data set provides a large population data set which will both allow us to explore the range of normality and supply enough numbers at the extremes to examine the extent to which extreme values do predict pathology. We have previously used the ALSPAC dataset to investigate the fit of UK children to the new WHO standard and found that ALSPAC children have larger heads than the WHO standard, and commonly cross centiles upwards. We will thus seek to answer two related research questions: 1/ How does parental head circumference correlate with head circumference centile in infancy and childhood, and what is the normal range of variance from this? (Concept: Parent-child HC) 2/ To what extent do variations in head circumference in the preschool years predict neurodevelopmental problems in childhood? (Concept: predictive value of HC). Head circumference (HC) is routinely measured in infancy and is widely assumed to be valuable in helping identify children with intracranial pathology or neurodevelopmental problems, and for monitoring such children over time. However the evidence base for screening HC is very limited. Very little is known about the extent to which deviation in head size or growth predicts underlying pathology. A common clinical assessment made where a child has a very large or small head is to compare the child's head circumference centile with that of their parents. However we do not at present know the extent to which children may vary from their parents in head size and we do know how well the existing growth reference (UK1990) age 20 fits to the normal distribution of adult heads. The ALSPAC data set provides a large population data set which will both allow us to explore the range of normality and supply enough numbers at the extremes to examine the extent to which extreme values do predict pathology. We have previously used the ALSPAC dataset to investigate the fit of UK children to the new WHO standard and found that ALSPAC children have larger heads than the WHO standard, and commonly cross centiles upwards. We will thus seek to answer two related research questions: 1/ How does parental head circumference correlate with head circumference centile in infancy and childhood, and what is the normal range of variance from this? (Concept: Parent-child HC) 2/ To what extent do variations in head circumference in the preschool years predict neurodevelopmental problems in childhood? (Concept: predictive value of HC).
B1410 - Changes in diet and weight gain in children - 02/08/2012
Aim:
We intend to quantify the impact of diet on children's BMI z-scores. Instead of classifying food consumption based on nutritional components or dietary pattern, we propose examining individual foods or food categories following the method by Mozzafarian et al (2011, NEJM). By tracking dietary consumption from age 2 to age 13, we aim at assessing whether higher dietary intake of certain food items or categories is associated with higher BMI z-scores, thus increasing propensity of childhood obesity.
Hypotheses:
1. Using a multivariate regression model on first differences of BMI z-scores, more frequent consumption of potato chips, potatoes, sugar-sweetened beverages, unprocessed red meat and processed meats is positively associated with BMI z-score increase; whereas more frequent consumption of vegetables, fruits, whole grains, nuts, and yogurt is negatively associated with BMI z-score increase.
2. When using a fixed-effect (FE) model, hypothesis1 still holds.
3.Using a quantile regression, the impact of diet on BMI z-score is stronger in the upper BMI z-score quantile.
4.Using a dynamic panel data model, an induction period can be identified. The effect of diet on weight is more significant after the induction period.
Exposure variables:
Food consumption for each food category
Outcome variable:
BMI z-score (calculated using weight, height, gender and age)
Confounding variables:
Socioeconomic measures such as ethnicity and family income, lifestyle behaviours including diet control, TV viewing, physical activity, tobacco use, and sleep duration.
References:
Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. New England Journal of Medicine 2011;364:2392-2404.
B1409 - Interpreting Rare Variation in Major Neuropsychiatric Disease - 02/08/2012
Background. We anticipate that a collection of rare variants will be found to be associated with major neuropsychiatric disease over the course of sequencing projects over the next year. The Daly lab is responsible for some of those efforts, particularly in relation to a large sample of autism spectrum disorder cases. While associating new genetic variants with mental illness will add much to existing etiologic awareness, many of the questions that follow other forms of genetic association will equally apply to whole genome sequencing. As with strongly predisposing copy number variants, newly discovered rare variants are likely to have highly pleiotropic effects, the nature of which his largely obscured in case-control studies.
Aims. We hope to examine the average quantitative effect of rare variants (both copy number variants and single nucleotide variants) in coding regions associated with major neuropsychiatric disease on trait measures of behavior and cognition in the ALSPAC/UK10K data. The specific aims of the study are as follows:
To examine the range of behaviors and average impairment burden associated with autism,
schizophrenia, and bipolar disorder-implicated rare variants using the following outcome
measures: IQ, autism-like social and communication impairment, psychotic traits, overall behavior
difficulties, and language ability.
Hypotheses. The predictor set will include rare variants in the ALSPAC/UK10K data that fall in the same genes as those found to harbor rare variation associated with autism, schizophrenia, and bipolar disorder. We hypothesize that, en masse, those variants will predict a shift towards affectedness in distributions of behavioral and cognitive impairment in the ALSPAC/UK10K cohort.
Exposure variables- Genotypic variation in the UK10K sequencing data
Outcome variables-
IQ (Full, Verbal, Nonverbal) - Ages 8 (WISC) and 15 (WASI)
Behavior Problems (Strengths and Difficulties Questionnaire) - All available time points
Autistic Traits (Social and Communication Disorders Checklist) - All available time points
Psychotic Traits (PLIKS) - All available time points
Language Ability (Children's Communication Checklist) - All available time points
Control/ Additional Variables-
Sex of the Child
Parental Age (Maternal and Paternal)
Child's Ethnicity
Maternal Education
Child's Age
Child's Height (phenotypic specificity consideration)
Child's Weight (phenotypic specificity consideration).
B1408 - Validation of Born in Bradford childhood obesity risk prediction equations in ALSPAC - 02/08/2012
Our research team have developed equations that can be used throughout infancy to predict risk for childhood obesity using data from the Born in Bradford (BiB) birth cohort study. Birth weight, weight gain during the first year of life, and maternal body mass index (BMI) were all important factors in predicting risk for childhood obesity. As a next step in this research, we would like to test the validity of our equations in a different sample of UK children. ALSPAC is an ideal candidate for this validation study because of its large sample size and similarity of data to that used to develop the equations in the BiB sample. Bradford has high levels of socio-economic deprivation and ethnic diversity, so validation in the predominately White, middle-high SES ALSPAC sample would allow assessment of the external generalisability of our equations. This work is being conducted as part of a Child Growth Foundation funded project to provide proof of concept that prediction equations for childhood obesity could be developed and incorporated into a mobile phone application for use in primary care practice. We would be happy for the advice and input of interested ALSPAC team members, particulary from those already involved with the BiB study. Any resulting publications from the use of ALSPAC data will acknowledge the study as required.
B1406 - Does repeated school change during childhood increase the risk of psychosislike symptoms PLIKS in adolescence - 02/08/2012
BACKGROUND: Schizophrenia is thought to be a genetically mediated illness affecting neural development from early childhood, with symptoms usually appearing during adolescence. However, in the last twenty years evidence has emerged supporting that social and environmental factors play a strong aetiological role in the development of schizophrenia. Robust findings include an association between migration and psychosis, which is not explained by a higher genetic risk among migrants (Morgan et al., 2010; Cantor-Graee et al., 2003); and between urban upbringing and psychosis (Pedersen et al., 2001; Pedersen et al, 2006). Other social risk factors include: childhood exposure to socioeconomic adversity (Wicks et al., 2005); family breakdown (Fearon et al., 2006); and bullying (Schreier et al., 2009). Selten & Cantor-Grae (2005) have proposed that "social defeat," representing repeated experiences of exclusion, discrimination and marginalisation, is the common underlying factor explaining the role of different social adversities in the development of psychosis.
In a Danish study of urban upbringing and increased risk of psychosis, Pedersen et al. (2001) found that it was a change of municipality rather than a change of address within the same municipality, that increased the risk of psychosis. In Denmark, a change of municipality always leads to a change of school. The authors speculated that the stress of changing school, making new friends, and perhaps worsening anxiety in those already prone to schizophrenia, might explain the increased risk of subsequent schizophrenia, i.e., the urban risk is partly mediated by a frequent change of schools. In a subsequent analysis, the authors found that the increased risk attributed to urban upbringing could not be entirely explained by familial factors (likely to be genetic risk); some of the risk was rooted in the individual (Pedersen & Mortensen, 2006). However, there are no studies which have further explored the hypothesis that repeated changes in school during childhood increase the risk of psychosis symptoms in adolescence.
AIMS: To explore whether repeated changes of school in childhood independently increase the risk of psychosis symptoms in early (and late) adolescence.
HYPOTHESES: 1) Children exposed to repeated changes of school will be at increased risk of PLIKS during adolescence. 2) There will be an independent association between changes in school and PLIKS when degree of urbanicity is controlled for 3) The predictive association between changes in school and increased risk of PLIKS will remain after controlling for other known confounders.
EXPOSURE VARIABLES: Number of school changes during childhood.
OUTCOME VARIABLES: Psychosis symptoms (PLIKS) at 12 years (and 17-18 years when available).
CONFOUNDING VARIABLES: Confounding variables have been selected for their previously reported associations with the likelihood of school change or psychosis symptoms. These include: socioeconomic adversity (as indexed by the Family Adversity Index); exposure to bullying during childhood; family breakdown (as indexed by exposure to domestic violence, harsh parenting and parental hostility); IQ of child; family history of schizophrenia; and urban/rural index at birth.
REFERENCES:
Cantor-Graae, E., et al., (2003). Migration as a risk factor for schizophrenia: a Danish population-based cohort study. Br J Psychiatry, 182, 177-22.
Fearon, P, et al. (2006). Incidence of schizophrenia and other psychoses in ethnic minority groups: results from the MRC AESOP Study. Psychol Med, 36, 1541-50.
Morgan, C., et al., (2010). Migration, ethnicity, and psychosis: toward a sociodevelopmental model. Schizophr Bull, 36, 655-64.
Pedersen, C.B., & Mortensen, P.B. (2001). Evidence of a dose-response relationship between urbanicity during upbrining and schizophrenia risk. Arch Gen Psychiatry, 58, 1039-46
Pedersen, C.B., & Mortensen, P.B. (2006). Are the cause(s) responsible for urban-rural differences in schizophrenia risk rooted in families or individuals? Am J Epidemiol, 163, 971-8.
Schreier, A., et al., (2009). Prospective study of peer victimisation in childhood and psychotic symptoms in a non-clinical population at 12 years. Arch Gen Psychiatry, 66, 527-36.
Selton, J.P., & Cantor-Graae, E. (2005). Social defeat: risk factor for schizophrenia? Br J Psychiatry, 187, 101-2.
Wicks, S., et al., (2005). Social adversity in childhood and the risk of developing psychosis: a national cohort study. Am J Psychiatry, 162, 1652-7.
B1405 - The role of obstetric neonatal and genetic factors in autistic trait development in two UK cohorts - 02/08/2012
The observed prevalence of autistic spectrum disorders (ASD) has risen dramatically in the western world over the past 30 years. It is still unclear whether this is a true rise in incidence, or an artefact due to increased awareness and more inclusive diagnostic criteria. If the former, then an increased exposure to environmental influences (probably interacting with genetic variants) is likely to be responsible. The role of environmental factors in ASD is increasingly being acknowledged1 and the identification of modifiable environmental determinants offers potential for primary prevention of ASD. The diagnosis of ASD relies on behaviorally defined impairments in social interaction, communication, restricted patterns of interests and repetitive behaviors. Proposed revisions to the classification of ASD highlight the importance of studying it dimensionally; thus it is important to use study trait measures, as the various autistic traits (ATs) may have different aetiologies.2
Since features of ASD are evident in early life, processes leading to ASD are likely to begin during the perinatal period. Procedures such as induction of labour, epidural anaesthesia and caesarean section have also increased over time throughout the Western world. Thus features of the management of pregnancy, labour and delivery are plausible candidates for ASD risk; however high quality studies investigating these are lacking and may have resulted in misleading conclusions in recent meta-analyses, which did not take into account the quality of the data, or methodological issues such as identification of ASD cases, appropriate choice of controls, specificity of definitions of obstetric details, or sources of data.3,4 For example, the meta-analyses grouped together hypertension, pre-eclampsia (PE) and 'swelling'- probably to increase statistical power, but this strategy was far from biologically appropriate since PE has a major deleterious effect on the fetus, but neither hypertension without PE nor oedema (swelling) do. Other studies used obstetric optimality indices combining biological features such as parity, social circumstances and medical conditions. The resulting indices are unable to provide information on any specific factors or mechanisms and often reflect whether this was a first pregnancy rather than any clinical abnormality. No studies appear to have considered obstetric/neonatal factors in regard to measures of autistic traits.
Aims: The proposed study has the overall aim of carrying out a detailed assessment of the association between features of pregnancy and delivery with autism and autistic traits, to assess whether there is any evidence of a dose dependent relationship, and to determine whether there is any evidence of interactions between obstetric features and autistic traits contingent upon (a) other aspects of labour/delivery or (b) of genetic markers.
Methods: The study will take advantage of 2 data-rich cohorts in England.
The Avon Longitudinal Study of Parents and Children (ALSPAC):has collected detailed information on approximately 14000 mothers and children born 1991-2 in England.5 The mothers, who were enrolled in early pregnancy, completed detailed questionnaires at various times during pregnancy and subsequently. Information has been extracted from the medical records of both mother in pregnancy, delivery and postpartum, and of the infant in the neonatal period; the data abstracted includes the conditions arising, the treatments given, and biological measurements for 8300 mothers, comprising approximately 3000 variables. Thus, for example, the detailed blood pressure measures throughout pregnancy, together with gestation at which proteinuria was detected, allow a rigorous definition of pre-eclampsia, together with the gestation at onset.
Although 86 children with a confirmed diagnosis of ASD by age 11 years have been identified,6 the true strength of ALSPAC lies in the extensive autistic trait measurements throughout childhood.7 Of 93 individual trait measures available between age 6 months and 9 years, 4 have been identified that together explain 48% of the variance in diagnosis: the coherence subscale of the Children's Communication Checklist(CCC), the Social and Communication Disorders Checklist, repetitive behavior, and the sociability subscale of the EAS measure (38 m).7 We have shown that epidemiological and genetic associations with ASD are found in specific traits as predicted.7,8
The Twins Early Development Study(TEDS) is a prospective longitudinal study of a UK-based community sample of twins9 comprising all live twin births between January 1994 and December 1996 in England and Wales (n=16,810 families). Information about prenatal and neonatal problems were first collected at around 1 1/2 years of age using a questionnaire that asked about prenatal, birth and neonatal experience using the Obstetric Enquiry Schedule,10 a validated maternal interview on pregnancy and birth complications. Families have subsequently been followed and assessed using a variety of measures of development and behavior. Between the ages of 7-12 years of age, autistic traits were assessed using (CAST)11 and the CCC.12 Intellectual ability was assessed using the WISC.13 Mothers were interviewed about the pregnancy and birth.
Statistical analyses: Methods of analysis will be decided in view of the frequency distributions, and will use, where appropriate, apart from traditional analyses, statistical techniques that may further illuminate causal inferences including sibling-control design and propensity score matching . Careful consideration will be given to the multiple factors that may confound observed relationships, and a focus will be to disentangle any causal role of treatment from condition (confounding by indication). We will take account of the numbers of tests undertaken using the false discovery rate. The ALSPAC analyses will take advantage of the gene-environment interaction results identified in the project currently underway by Beate St Pourcain. Twin analyses as described by Purcell et al14 and van der Sluis et al15 will be used as a general test of gene-environment interaction; and candidate genes e.g. those concerned with the oxytocin / vasopressin system to test for specifc GxE interactions.
Unique features of proposed study:
1.Extensive prospectively recorded information concerning obstetric features in ALSPAC, blind to whether or not the child would develop ASD or autistic traits including detailed time related measures where appropriate.
2. ALSPAC and TEDS data-bases contain many genetic variants which will be used to determine interactions between obstetric factors with candidate genes. In addition ALSPAC will include epigenetic and CNV results, as they become available.
3. Both studies include information on a large number of potential socioeconomic, lifestyle and health-related confounders. Both include IQ measures on the child.
4. The ability to study various trait dimensions of autism in singletons in ALSPAC, and in twins in TEDS.
Expected results: The information generated should be of immediate clinical and policy importance, and impact on the current guidance related to obstetric treatment. The data should clarify whether features of obstetric management contribute to the development of autistic traits and whether the effects are contingent on genetic background.
Funding will be sought to enhance the obstetric data base by: [i] extract further details from medical records, focusing in particular on pregnancies resulting in the remaining cases of autism, and those scoring high on the 4 autistic traits, together with a control sample collected at random from the remaining records [total n=500+]; the records will be extracted by trained personnel, blind to whether a case or control. [ii] keying of the text data on the cases that have already been documented (n=~2000 records); [iii] coding of the various text categories, including the causes of admission(s), induction, caesarian section; the medication given in pregnancy and delivery; the characteristics of the neonate. All such factors will be categorized, documented and returned to the built files for use by others.
References
1. Hallmayer J et al. Arch Gen Psychiatry 2011; 68: 1095-1102. 2. Happe F et al. Nature Neuroscience 2006; 9: 1218-1220. 3. Gardener H et al. Brit J Psychiatry 2009; 195: 7-14. 4. Gardener H et al. Pediatrics 2011;128: 344-355. 5. Golding J et al.. Paediatr Perinat Epidemiol 2001; 15: 74-87. 6. Williams E, et al. Dev Med Child Neurol 2008; 50: 672-7. 7. Steer CD, et al., PLoS One 2010; 5: e12633. 8. Golding J et al. PLoS One 2010; 5: e9939. 9. Oliver BR, Plomin R. Twin research and Human Genetics 2007; 10: 96-105. 10. Bolton PF et al. J Amer AcadChild and Adolescent Psychiatry 1997; 36: 272-281. 11. Scott FJ et al. Autism 2002; 6: 9-31. 12. Bishop DVM. J Child Psychology and Psychiatry 1998;39: 879-891. 13. Weschler et al. The Psychological Corporation 1992.14. Purcell S. Twin Research. 2002; 5: 554-571.15. van der Sluis S et al. Behav Genet 2012; 42: 170-186.
B1385 - X Chromosome and asthma - 21/07/2012
Aim: Despite genes on the sex chromosomes contributing to many sexually dimorphic traits, associations on the X-chromosome have been overlooked in previous genome-wide association scans (GWAS) of asthma. Our aim is to impute and test genetic variants on the X-chromosome for association with asthma risk.
Hypotheses: Genetic variants on the X-chromosome contribute to asthma risk and these can be identified through a well powered meta-analysis of results from GWAS of asthma.
Independent variable: Individual genotyped or imputed SNPs located in the X-chromosome, coded as allelic dosage and assuming a dosage compensation model (see below).
Dependent variable: Binary phenotype (ie case-control status) with affected individuals defined as those individuals who reported in any of the available ALSPAC surveys to have been diagnosed by a doctor with asthma. So lifetime self-reported asthmatics. Unaffected individuals are defined as those individuals who never reported to have asthma in any survey.
Confounding variable: None.
Analysis plan: Perform association analysis of SNP dosage after applying standard QC filters (eg. MAFgreater than 1%, HW P-value [in females] greater than 10-6, call rate greater than 95%, imputation info/r2 greater than =0.3) and excluding samples of non-European ancestry. Analyse males and females separately and assume a dosage compensation model (ie. equate hemizygous male to homozygous female, see Clayton 2008), such that the allelic dosage extremes for males are 0 (if A/-, which is the same as for AA females) and 2 (if B/-, which is the same as for BB females)
B1384 - A proof of principle approach of sparse structure learning instrumental variable analyses of adiposity related traits - 21/07/2012
Aims:
1. Utilise the Sparse Instrumental Variable approach (SPIV) to identify combinations of genetic varinats for use as instrumental variables in Mendelian Randomization studies.
2. Construct sparse networks of associations between outcomes using the sparse random field models.
3. Use Mendelian Randomisation approaches to investigate the causal direction of the network edges.
4. Investigate robustness of the resulting structures for multiple variable selection criteria and data subsamples.
Agakov and colleagues have been developing machine learning based methods for selecting meaningful associations both in phenotypic data and, using modifications of Mendelian Randomization approaches, in data combining genotypes and phenotypes. These variable selection methods will be applied to a network of phenotypes and genome wide-data predicting such phenotypes. The methods are based on probabilistic sparse latent variable models applied either for feature selection and structure learning in layered directed networks [1, 2] or more complex networks of associations [3]. The variables in this exploration of these methods will be: BMI, blood pressure, IL6, CRP, LDL cholesterol, HDL cholesterol, triglycerides, leptin, WISC score and adiponectin.
The analysis will either be conducted by Louise Millard (who will visit Edinburgh for training) or by a member of the Edinburgh group visiting CAiTE.
[1] F. V. Agakov, P. McKeigue, J. Krohn, A. Storkey. Sparse Instrumental Variables (SPIV) for Genome-Wide Studies. In Advances in Neural Information Processing Systems 23, 2010.
[2] F. V. Agakov, P. McKeigue, J. Krohn, J. Flint. Inference of Causal Relationships between Biomarkers and Outcomes in High Dimensions, Journal of Systemics, Cybernetics and Informatics 9(6), 2011.
[3] F. V. Agakov, P. Orchard, A. Storkey. Discriminative Mixtures of Sparse Latent Fields for Risk Management, Journal of Machine Learning Research W&CP 22, 2012.
B1404 - Adolescent and peer smoking trajectories - 17/07/2012
Our aim is to examine how peer smoking affects smoking in adolescents. We would also like to look at the relationship between parental smoking, parenting and child smoking. We will use longitudinal latent class analysis in mplus to generate trajectories for adolescent and peer smoking. Adolescent smoking trajectories will be based on both self report smoking data and cotinine measures. We hypothesise that adolescents who smoke have more peers who smoke and that trajectories of adolscent smoking closely map the trajectories of peer smoking. The association between child and peer smoking may be due to influence, selection or both. Children with parents who smoke are expected to be more likely to smoke, however parental monitoring is expected to be associated with lower smoking. We also hypothesise that the association between peer and adolescent smoking may differ by level of parental monitoring. Smoking behaviour may also be associated with gender, SES (housing tenure, crowding status and maternal educational attainment) and other substance use. These covariates will also be included in our model.
B1403 - Is fertility in the genes A GWAS genetic-wide association search of fertility tempo and quantum - 17/07/2012
In the last decade, many industrialised societies experience massive changes in both the postponement of age at having a first child (tempo) and a drop in the total number of offspring (quantum) (Mills et al 2011). Previous studies suggest that there are genetic influences on fertility behaviour, but specific genetic variants have not yet been identified. The aim of this study is to bridge demographic and genetic research by having ALSPAC participating to the first large scale genome-wide association (GWAS) meta-analysis to identify the novel genes that influence the tempo (age at first birth, AFB) and quantum (number of children ever born, NEB) of human fertility.
B1402 - Evaluation of the prospective effect of chronic pain on social development and behaviour in young people - 17/07/2012
1. Young people's social development and emotional management in the presence of persistent pain.
Aim - to understand the effect of pain on social development in young people with chronic pain compared to their own younger selves, and compared to those without.
We hypothesize:
a) That young people will judge themselves to be socially delayed in comparison to their peers, and be less independent
b) That they will be advanced in terms of their emotional management skills.
c) That those high in pain related anxiety will show deficits in all areas of self-rated social development.
2. Young peoples social and physical functioning (including risk taking) in the presence of persistent pain.
Aim - to understand the effect of chronic pain on social behaviour in young people, compared to their own younger selves, and compared to those without.
We hypothesize:
a) that young people with pain will have radically reduced physical activity
b) that young people with pain will be risk averse and show fewer risk behaviours
c) that these effects will be moderated by anxiety.
Dependent variables
1. Pain (location, VAS)
2. Pain related anxiety
Independent variables
1. Social development
2. Social and physical behaviour
3. Age
Background
Pain is a common phenomenon in adolescence (Deere et al 2011)(Clinch et al 2009), with 25% of children and adolescents reporting recurrent or continuous chronic pain and 8% reporting persistent, disabling pain (Perquin et al., 2000). Adolescents who experience chronic pain typically report school absence, elevated levels of disability, emotional distress, social role disruption and complex family issues (Walker et al., 1998, Roth-Isigkeit et al., 2005; Eccleston et al., 2004). It is likely that pain and associated disability will affect adolescents' developmental trajectory. Findings from this research group suggest that adolescents with chronic pain perceive their developmental progression to lag behind that of peers (Eccleston et al.2008), particularly with regard to academic progress. Others have found that adolescents with chronic pain report poor quality relationships with peers and low levels of autonomy (Kashikar-Zuck S 2006).
It has been theorised, but not robustly investigated, that adolescents with persistent pain have altered behaviour that has a direct effect on their physical and psychosocial development. Understanding this relationship will enable therapuetic interventions to be developed, studied and targeted for identified families.
The Bath Centre for Pain Research, in collaboration with Bath Centre for Pain Services, has an international reputation in progressing clinical therapies and academic understanding of disease and non-disease related pain across the lifespan. The teams, under the guidance of Prof Eccleston and Dr Clinch, developed the Bath Adolescent Pain Questionnaire that is now used internationally as a measure of the impact of pain in adolescents and families (Eccleston 2005 , Jordan 2008). 2 domains of this questionnaire, adressing psychosocial aspects of pain, were included in the age 17 ALSPAC pack as part of the ARUK study (Prof Tobias, Dr Clinch et al) evaluating joint hypermobility and pain.
We are now in a position to evaluate the collected data from these 2 domains with respect to current and previous measures of social and physical functioning and development.
We would be grateful if Prof Ecclestone could be allowed access to this psychosocial data (alongside Dr Clinch).
Clinch J, Deere K, Sayers A, Palmer S, Riddoch C, Tobias JH, Clark EM.Epidemiology of generalized joint laxity (hypermobility) in fourteen-year-old children from the UK: a population-based evaluation. Arthritis Rheum. 2011 Sep;63(9):2819-27
Clinch J, Eccleston C. Chronic musculoskeletal pain in children: assessment and management.
Rheumatology (Oxford). 2009 May;48(5):466-74.
Eccleston C, Jordan A, McCracken LM, Sleed M, Connell H, Clinch J.
The Bath Adolescent Pain Questionnaire (BAPQ): development and preliminary psychometric evaluation of an instrument to assess the impact of chronic pain on adolescents.
Pain 2005 Nov;118(1-2):263-70
Eccleston C, Crombez G, Scotford A, Clinch J, Connell H.
Adolescent chronic pain: patterns and predictors of emotional distress in adolescents with chronic pain and their parents.Pain. 2004 Apr;108(3):221-9
Eccleston C, Wastell S, Crombez G, Jordan A.
Adolescent social development and chronic pain.Eur J Pain. 2008 Aug;12(6):765-74.
Kevin C Deere, Jacqui Clinch, Kate Holliday, John McBeth, Esther M Crawley, Adrian Sayers, Shea Palmer, Rita Doerner, Emma M Clark, Jon H Tobias
Obesity is a risk factor for musculoskeletal pain in adolescents:findings from a population based cohort. (In press Rheumatology)
Jordan A, Eccleston C, McCracken LM, Connell H, Clinch J.
The Bath Adolescent Pain--Parental Impact Questionnaire (BAP-PIQ): development and preliminary psychometric evaluation of an instrument to assess the impact of parenting an adolescent with chronic pain.Pain. 2008 Jul 31;137(3):478-87
Kashikar-Zuck S. Treatment of children with unexplained chronic pain. Lancet 2006; 367(9508):380-2
Perquin C.W., Hazebroek-Kampschreur A.A.J.M., Hunfeld J.A.M., Bohnen A.M.,
van Suilekom-Smit L.W.A., Passchier J., van der Wouden J.C. (2000). Pain in
children and adolescents: a common experience. Pain, 2000 87, 51-58.
Roth-Isigkeit Aet al. Pain amoung children and adolescents:restrictions in daily living and triggering factors. Pediatrics 2005; 115:152-62.
B1393 - Contributions of genetic and environmental factors to muscle density - 05/07/2012
Background
There is increasing interest in the contribution of sarcopenia to frailty and ageing, but research in this area is hampered by the lack of accurate non-invasive measures of muscle function. Though a number of assessments related to muscle function are available, including tests of muscle strength, and functional assessments such as timed chair raise and 'get-up-and-go', objective imaging-based techniques are very limited. Measurement of lean mass, for example by DXA scanning, provides one potential option, based on evidence that this is related to muscle strength and physical activity. However, the overall amount of muscle provides limited information as to its function, suggesting the need for other imaging modalities. One such candidate is pQCT-based measurement of muscle density. However, rather than muscle function, it may be that this primarily provides a measure of intramuscular fat. Consistent with this suggestion, we recently reported a relatively strong inverse correlation between muscle density and total body fat mass (1). A similar relationship was reported between muscle density and insulin levels, consistent with the fact that intramuscular fat deposition is thought to represent an initial step in the development of insulin resistance.
Aims
In the present proposal, we aim to address the hypothesis that muscle density as measured by pQCT provides useful information about muscle function, which is independent of estimates of fat mass/insulin resistance. This will be investigated by examining whether muscle density (adjusted for fat mass) is related to relevant environmental factors such as physical activity, or to genetic factors unrelated to obesity (this research programme will also link in with a parallel project involving Celia Gregson using the Hertfordshire cohort, intended to examine relationships between equivalent pQCT-derived measured of muscle density and findings from muscle biopsies).
Methods
Outcome variables:
Muscle density and cross sectional area as measured by tibial pQCT at 15.5 and 17.5 clinic visits.
Exposures:
Moderate and/or vigorous physical activity, based on Actigraph measures at age 15.5 years, as previously used to examine relationships with other pQCT-derived variables at age 15.5 (2).
High impact activity, based on Newtest monitors at age 17.5 years, as previously used to examine relationships with other pQCT variables at age 17.5 (K Deere et al, JCEM, In Press).
Genome-wide genetic markers, imputed to the latest version of hapmap, as used in our recent GWAS studies of other pQCT parameters in our pQCT consortium (3) (discovery cohorts: ALSPAC, GOOD, Young Finns; replication cohorts: Mr Os, Hertfordshire, EMAS; second meta-analysis centre: University of Gothenberg).
Confounders: age, gender, height, weight, subcutaneous fat area (pQCT), lean mass, fat mass.
1. Sayers A, Lawlor DA, Sattar N, Tobias JH. The association between insulin levels and cortical bone: findings from a cross-sectional analysis of pQCT parameters in adolescents. J Bone Miner Res. 2012;27(3):610-8. Epub 2011/11/19.
2. Sayers A, Mattocks C, Deere K, Ness A, Riddoch C, Tobias JH. Habitual levels of vigorous, but not moderate or light, physical activity is positively related to cortical bone mass in adolescents J Clin Endocrinol Metab. 2011;In Press.
3. Paternoster L, Lorentzon M, Vandenput L, Karlsson MK, Ljunggren O, Kindmark A, et al. Genome-wide association meta-analysis of cortical bone mineral density unravels allelic heterogeneity at the RANKL locus and potential pleiotropic effects on bone. PLoS Genet. 2010;6(11):e1001217.
B1392 - Dissection of ZNF804A association with complex psychiatric disorders - 05/07/2012
Building on the work of an existing, MRC-funded project examining the contributions of the ZNF804A zinc finger transcription factor locus to brain function in animal models, the work proposed here aims to apply recall studies to expand this effort to detailed examination of parallel human traits, combining the expertise and methods developed in MRC CAiTE with Cardiff's expertise in neuropsychiatric genetics and Bristol/Harvard's expertise in sleep neurophysiology. Crucial to the motivation of this study are the observations that (1) variation at the ZNF804A locus is associated with schizophrenia and related disorders risk and (2) that patients present with abnormalities in neural oscillations during sleep, which in turn cause or reflect cognitive deficits that respond poorly to current therapies. Since distinct patterns of oscillatory neural activity during sleep reflect functioning of well-defined neural circuits, this presents an opportunity to link ZNF804A variants to brain function and thereby rationalize future therapeutic design.
B1391 - The neurophysiological underpinnings of response to alcohol an aetiological examination of fMRI characterised physiology - 05/07/2012
Risk factors for heavy drinking operate primarily through intermediate characteristics that relate to environmental events and genetic influences to impact on the development of heavy drinking and alcohol use disorders (AUDs). One such pre-existing phenotype is low Level of Response (LR) to alcohol, where individuals who require higher doses of alcohol to achieve an effect are more likely to develop AUDs than those who react more intensely to ethanol. This trait can be measured as less alcohol-related change in positive (e.g., feeling high) and negative (e.g., feeling dizzy) subjective feelings of intoxication, hormones, and EEG measures at a given blood alcohol concentration (BAC), or as less effect per drink on a retrospective questionnaire. Low LR is seen in ~40% of the children of alcoholics, but only ~10% of controls, and the heritability of this trait measured by questionnaire is 40%-60%. Critically, LR predicts later heavy drinking and the negative impact of alcohol abuse and has been demonstrated to be an effective target for directed alcohol management intervention, yet despite its clear translational importance, the biological underpinnings of this trait have yet to be fully characterised and replicated. The proposed recall experiment will replicate novel work from collaborator MS and colleagues concerning the functional underpinnings of LR status and extend it in an independent collection (ALSPAC) with access to comprehensive genotypic data, life-course phenotypic data and prospective follow-up of alcohol related events and measures.
B1390 - Longitudinal bone health and development in adolescents with disordered eating - 05/07/2012
Objectives
1)To determine the impact of adolescent disordered eating behaviours on bone accrual and bone development throughout adolescence and young adulthood.
2) To determine the role of factors such as caloric restriction, delayed puberty, excessive exercise, gender in explaining the effect of disordered eating on bone health in adolescence.
3) To determine the impact of adolescent disordered eating behaviours on stress fractures in young adulthood.
Background
Eating disorders (ED) are chronic disorders and affect about 5-10% of the population (Hoek and Van Hoeken, 2003).
Adolescent ED and bone development: ED have a peak incidence in adolescence, a crucial time for physical and skeletal development. Pubertal years are the period in the life course when bone mass reaches its highest level. The level of bone mass attained at this age is a key determinant of long-term bone health and risk of osteoporotic fractures in later life (Ott, 1991).
Past research focusing on bone density in ED has shown that restrictive ED (such as anorexia nervosa (AN) and atypical anorexia nervosa/ Eating Disorder not otherwise specified-EDNOS) are associated with reduced bone mass. This is probably secondary to low weight, reduced fat mass and hormonal abnormalities secondary to poor nutrition (Misra, 2008; Mehler et al, 2011). Whilst recovery from the ED has been shown to lead to improvements in bone density, several studies show that bone density remains lower than in individuals who have not experienced an ED, particularly in cases where the ED onset was in adolescent years (Biller et al., 1989; Hartman et al., 2000; Wentz et al., 2007; Bolton et al., 2005).
Binge- type ED (such as bulimia nervosa and binge eating disorder) have been less well studied, and appear not to affect bone density to the same extent as restrictive ED, particularly if normal weight is maintained (Misra, 2008). However, higher fracture risk was also shown in these women compared to controls (Vestergaard et al., 2003).
Studies investigating bone density in adolescents with restrictive ED as measured by dual energy X-ray absorptiometry (DXA) have shown low bone density at the spine, hip and femoral neck (Misra, 2008); as well as reduced bone turnover. These effects are apparent in both girls and boys (Castro et al., 2002). Follow-up studies of adolescents have reported some improvement in bone density with nutritional restoration, mainly in areas of trabecular bone, such as the spine. Several studies, however, have shown fewer improvements in bone density at cortical sites despite recovery from the ED ((Herzog et al., 1993; Mika et. al, 2007). Given that the adolescent years provide a narrow window of opportunity in which to optimize bone mass accrual, disruption during these years might lead to permanent deficits.
Stress fractures:Although stress fractures are relatively uncommon, they affect as many as 15% of young women athletes and military recruits. Among females, other suspected risk factors for developing a stress fracture include disordered eating (Rosen et al, 1986) and irregular menstrual cycles, both which may result in a deficient estrogen status that can counteract the beneficial effects of exercise on bone density (Wolman et al., 1990; Lloyd et al. 2000; Bass et al.,1998).The combination of disordered eating, amenorrhea, and low bone density is characterized as the Female Athlete Triad. The recognition of the triad has served to increase awareness of bone health concerns among young female athletes (Yeager et al., 1993; Otis et al., 1997). Thus, it is extremely important to identify modifiable predictors of stress fracture so that prevention programs could be developed for high-risk populations.
Gaps in the literature:Most studies in the field to date rely on small clinical samples, and are likely to represent more severely ill subjects attending in- or out-patient services and not be generalisable to all ED. Length of follow-up has often been limited to 1-2 years. Moreover, DXA provides an overall estimate of bone mass but does not directly measure aspects like cortical thickness and cross sectional area that determine overall bone strength. Techniques like peripheral quantitative computed tomography (pQCT) can provide detailed information about cortical bone geometry and strength, but only one study to date has used this method to study bone changes in adolescents with ED (Milos et al.,2007). In light of recent finding that fat mass is an important positive determinant of cortical bone size and thickness (Sayers & Tobias, 2009), we are particularly interested in examining whether adolescent ED predicts weaker cortical bones due to reduced fat mass. More than half of adult bone calcium is acquired during adolescence and a woman's peak bone mineral density, a major determinant of her long-term risk of osteoporosis, is thought to be achieved by early adulthood. Therefore assessing bone density in young adulthood, as well as throughout adolescence, allows a better assessment of peak bone density. This additional investigation will allow a better understanding of the longitudinal effects of adolescent ED behaviours on bone development.
To our knowledge there are: no studies on a general population sample of adolescents/young adults able to link temporal relationships between disordered eating behaviours and bone development. Both would allow a clear identification of causal biological mechanisms, and take into account the role of confounders. The current lack of evidence impacts on available prevention and early treatment for patients with ED.
This study is unique in that data have already been collected prospectively and independently on bone density and ED behaviours in about 6,000 adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC). This longitudinal prospective study will allow: (1) determining precise temporal relationships between predictor (ED behaviours) and outcomes (bone density, cortical bone size and thickness, peak bone mass, and stress fractures); (2) focusing on causal biological mechanism taking into account the role of confounders (thanks to the wealth of data available in ALSPAC).
Methodology
Theoretical/conceptual framework: This is a longitudinal study, which will rely on data prospectively collected as part of the ALSPAC study. The ALSPAC study is a longitudinal prospective cohort of 14,000 mothers and their children. Women were enrolled in the study in pregnancy. Children have been followed up at regular intervals from birth up to age 18.
Research questions:do adolescent disordered eating behaviours (not only clinical ED) negatively affect bone accrual and bone development during puberty and into young adulthood, including individuals with subclinical disorders not currently viewed as being at risk? Do reductions in fat mass contribute to these deleterious effects of ED behaviours on bone development particularly those on cortical bone? This being the case, are reductions in fat mass in the context of ED behaviours particularly harmful, reflecting the fact that they are achieved by dietary restriction as opposed to by increased physical activity? What is the impact of disordered eating behaviours on peak bone mass?
Methods:
Outcomes:
1) Total DXA scans have been performed on the children/adolescents at ages: 11.5 (n = 7159), age 13.5 (n = 6147), age 15.5 (n= 5509) and age 17.5 (approximately 4000). In addition, hip DXA scans have been performed at age 13.5 and 17.5, and pQCT scans of the mid tibia at 15.5 and 17.5. Standard DXA and pQCT parameters related to bone development have been derived and will serve as the main outcomes. Data on fractures has also been collected at regular intervals.
We are seeking funding for a new wave of data collection to collect:
1. a 1-page questionnaire on stress fractures;
2. a two page questionnaire (or computerised assessment) on disordered eating behaviours and participation in exercise
3. DXA (hip and total body) and pQCT (tibia plus radius)
4. objective measurement of weight and height
Predictors:
1) Data on adolescent ED behaviours have been collected at age 13, 14, 16, and 18 adolescents
Other explanatory variables (mediators and/or confounders):
1)- Data are also available on pubertal timing and anthropometric measures at all the above ages on ~6,000 adolescents.
-Total body fat and lean mass as measured by total body DXA
-Physical activity as measured in the children by accelerometry at multiple time points
-Detailed information on adolescent diet using a combination of diet diaries and food frequency questionnaires
-Extensive information on socio economic status
Data collection: we envisage the new data collection can be part of an ALSPAC clinic, alternatively we will select individuals on the basis of their exposure (any disordered eating in adolescence, N=600-800) and unexposed individuals (no disordered eating in adolescence, N=600-800) to assess.
Analyses: Univariate and multivariate logistic models will be used to determine the effect of relevant predictors on outcomes. Longitudinal modelling will be used for longitudinal repeated data and to model hypothesised relationships.
B1398 - GWAS analysis of lymphoblastoid cell line growth characteristics - 05/07/2012
Aims and Hypothesis
During the production of lymphoblastoid cell lines for the ALSPAC cohort there has been circumstantial evidence that lymphocytes from some individuals are harder to transform with Epstein Barr Virus than others. Also there is variation in the growth rate of different cultures. The ALSPAC laboratory has collected data on the rate of transformation and rate of growth of cultures once transformed.
We would like to run a GWAS analysis of the cell line characteristics to see if there is a genetic association with transformation success or growth rate of the cultures. In particular we will look to see if genes that have been identified as host genes associated with cancers caused by Epstein Barr Virus are also associted with transformation efficiency. (HLA-A has been shown to be associated with risk of EBV-related Hodgkin lymphoma (Hjalgrim, et al., 2009, Urayama, et al., 2011) and Nasopharyngeal carcinoma (Tse, et al., 2009).
In addition there are phenotypes which could affect the transformation success, for example a recent or past infection with EBV. There are also some reports which suggest that blood pressure ia associated with different cell line growth rates. Therefore we will look to see if there is any association between the cell line characteristics and the infection history, blood pressure and smoking data of the participants the cell lines were obtained from.
Exposure Variables
Smoking, blood pressure and infection history
Outcome Variables
Transformation success rate and growth rate of established cultures
Confounding Variables
Cell counts of original samples, time to processing, original blood volume, age of participant
Karen Ho, ALSPAC cell line RA will provide all the cell line data which can also be incorporated into the main ALSPAC resource. George McMahon has agreed to carry out the GWAS analysis and assist with general statistical analysis.
Any findings could potentially be replicated using data obtained from 1958 birth cohort cell lines subject to approval from the 1958 birth cohort access committee.
B1397 - Induced Pluripotent Stem Cell iPSC Pilot Study - 05/07/2012
iPSC have been generated by reprogramming Lymphoblastoid Cell Lines (Blood. 2011 Aug 18;118(7):1797-800, Cell Cycle. 2011 Sep 1;10(17):2840-4, Blood. 2011 Aug 18;118(7):1801-5) Therefore we will pilot 4 methods to generate iPSC from lymphoblastoid cell lines generated in the ALSPAC laboratory.
There are four objectives for the pilot study:
1. Establish reprogramming of lymphoblastoid cell lines using 4 different methods
2. Identify and expand a number of prospective iPSC lines from the six EBV lines supplied by ALSPAC
3. Characterise the resulting iPSC using normal criteria used to asses pluripotency
4. Analyse the possible removal of the EBV genome from iPSC lines during derivation / extended culture
SAMPLE REQUEST
Six lymphoblastoid cell line samples will be chosen and distributed to the 4 laboratories. These will be selected using following criteria
3 male, 3 female
all with UK10K data
all ARIES cases
LCL's established from PBL obtained at 9yr clinic
PBL also available from F17 clinic
Methods to be used are detailed in appendix 1b, in summary groups will use the following
Lyle Armstrong, Majlinda Lako, University of Newcastle
Sendai virus reprogramming of lymphoblastoid cell lines
Maeve Caldwell, James Uney, University of Bristol
Reprogram the LCLs into iPS cells using the lentiviral system
Kevin Eggan, Harvard University
Generate iPSC from provided LCL lines using episomal plasmid based methods
Amanda Fisher, MRC Clinical Science Centre, London
heterokaryon iPSC generation system