Proposal summaries
B2019 - Investigating the impact of maternal iodine and sodium status throughout pregnancy on outcome of the offspring - 06/06/2013
AIMS
This study aims to investigate the affect of iodine and sodium status throughout pregnancy on outcome of the offspring.
HYPOTHESIS
Iodine is required for the production of thyroid hormones which have a role in brain and neurological development during gestation and early life. The mother is an important source of thyroid hormones to the developing fetus particularly before the fetus is able to produce its own. Mild to moderate maternal iodine deficiency has been associated with a reduction in IQ and psychomotor development in the offspring and has also been linked to the development of ADHD. Excessively high or low intake of sodium throughout pregnancy can have adverse effects on both the mother and the offspring and therefore maternal sodium levels will also be analysed in the urine. Measuring iodine and sodium levels in maternal urine throughout pregnancy and analysing against offspring outcome will identify the most influential period of development on which iodine and sodium have an affect.
EXPOSURE VARIABLE
All maternal urine samples from each trimester
OUTCOME VARIABLE
Iodine, sodium and creatinine levels. Creatinine will be analysed to correct for urine volume.
CONFOUNDING VARIABLES
maternal age at delivery, mother's parenting score, HOME score, family adversity index, life-event score, intakes of omega-3 fatty acids and iron
child factors
sex, birthweight, preterm birth, breastfeeding, and ethnic origin
maternal factors
smoking status, alcohol intake, parity, maternal depression since birth and use of fish-oil supplements during pregnancy
markers of socioeconomic status
maternal and paternal education, housing status and crowding
B2020 - Bio-social enhancements to the Millennium Cohort Study - 24/05/2013
1. Collection of height, weight and body fat.
As well as reflecting the substantive comments from earlier discussions this paper in setting out the main details of the enhancement, this paper outlines pre-and post- March 2015 costs, in order to enable a profiling of spend. In the original proposal all staffing costs were censored at March 2015, given that was the limit of the spend period. However, this was not in expectation that all the work would be completed by that point, but a reflection of the limits of the funding source. It was anticipated that the extension of staffing costs would be found by some other means (e.g. through the core CLS funding, or through a separate funding proposal).
This paper instead builds in staffing costs that are appropriate for the enhancement even when they extend beyond March 2015. However, for consistency with the earlier paper, the post-March 2015 totals are also shown excluding these post-March 2015 staffing costs.
Key elements of enhancement
The continued collection of height and weight will allow a robust understanding of contemporary children's physical and developmental trajectories over time across the UK and how this physical development relates to family context, child and family practices and behaviours, neighbourhood and environment, and other aspects of children's development, and wellbeing.
Height will be measured by trained and accredited interviewers using a height measure that is appropriate for teenagers and using best practice protocols. As usual we will check what the most up-to-date protocols are and ensure that the MCS team and the fieldwork agency are fully versed in them. This will also maximise comparability with measurement carried out for example on the National Child Measurement Programme (NCMP) using the same protocols.
Weight and body fat will be measured by trained interviewers using Tanita scales that capture both weight and body fat percentage.
Following full briefing, interviewers will practice the height, weight and body fat measurement on young people of the relevant age, as part of their training, and will be require to be accredited in height measurement before they can implement it in the field.
All measures will be captured in CAPI, alongside a record of any specific circumstances relating to the measurement that might have affected its accuracy. These data will be returned to CLS by the contracted fieldwork agency within four months of the conclusion of fieldwork.
The existing data manager team will check and clean the data, create appropriate derived variables and prepare it for release within six months of receipt from the fieldwork agency.
The data manager team will be able to provide value added to the physical measurements data by linking the height weight and body fat measurements to updated growth charts constructed according to standard methodology but based on contemporary growth patterns, using the National Child Measurement Programme (NCMP) data. We are currently in discussion with the Department of Health about access to measures collected in the NCMP but not currently deposited (specifically ethnicity). Growth charts based on national NCMP data and incorporating ethnic differences would be a more appropriate reference population than currently used growth charts. We are thus seeking to develop such contemporary growth charts employing the methodology used in the 1990 charts but based on a contemporary, nationally representative and multi-ethnic population.
2. Collection of saliva for DNA extraction.
This element represents a collaboration between Dr Sue Ring of Bristol University and the MCS team at CLS. The collection of saliva samples would enable a genetic record of both the child and their parents to be preserved. This would provide enormous potential for both genetic and epigenetic research on a young, nationally representative cohort and enhance the multidisciplinary, bio-social potential of the study both now and in the future.
There is already great interest in the potential of a DNA resource derived from MCS. Given the wealth of existing data collected in MCS from both survey questions and direct measures and assessments, there is huge potential to understand associations between genetic make-up and a whole series of outcomes relating to e.g. learning, dyslexia, obesity and overweight, behaviour and mental health.
The large sample size and national coverage of MCS are particularly beneficial: as well as offering detailed family-level, individual and contextual information, MCS enables analysis to explore the contexts of varying environmental exposures as well as genetic dispositions. In particular, the value of the oversampling of those from more disadvantaged socio-economic backgrounds is regarded as being particularly valuable in
There is clearly great potential from the collection of triads of samples (both biological parents and the cohort child) for the investigation of epigenetic processes. It is increasingly recognised that non-target tissue sources of DNA can be informative about the relationship between epigenetic variation and phenotype.
It is clear that, while attention would need to be given to ensuring the resource was both known about and used (utilising both the Access Committee and Closer in doing this), there would be a number of scientists ready to build proposals to exploit the data once they became available. For example, researchers who have already identified genetic data from MCS as offering enormous potential include, Silvia Parracchini who has expressed interest in utilising MCS to enhance her existing studies of genetic variants associated with dyslexia; and Caroline Relton, who is working on epigenetics using non-target tissues, and is developing an approach which places DNA methylation changes as in intermediate phenotype on a pathway between exposure and outcome, including such outcomes as obesity, and cognitive and behavioural outcomes.
With ensuing genome-wide genotyping, an MCS DNA back can be expected to provide an extremely valuable resource for analysis that is likely to be very well used. The success of the NCDS resource is testament to the volume of research that such a resource can invite, and we would expect certain of the key features of MCS, such as its demographic coverage, to enhance its utility.
In terms of the planned provision to result from this enhancement; the key element is the collection of saliva, from both the cohort member and from their co-resident natural parents, where applicable.
Such collection was successfully piloted at age 11, but we would expect that the change in age and the context of different instruments would require some additional pretesting. We would then implement in pilot, dress-rehearsal and main stage. We would also need to ensure proper briefing of interviewers and the available of appropriate subsidiary materials such as clear question and answer guidance.
The second key element is the preparation and storage of the samples, which would be undertaken in Bristol using a similar approach and protocols as were developed for the Age 11 pilot in relation to delivering the samples from the field, conduction quantification and extraction. Clearly in the main stage, this would take place on a much larger scale and would require adequate systems being fully in place for that
The third key element is the genotyping of the samples. This would also be undertaken by Bristol. While indicative support has been indicated for this element of the proposal, it would need to be aligned with the ESRC biosocial strategy which is expected later in 2013. Indicative costs for the genotyping would also need to cover staff to support accessing the samples and ongoing storage and maintenance.
Access to the sample would also need to be ensured through adequate resourcing of the Access Committee to support their existing work. The existing access arrangements for NCDS would clearly be suitable for accessing the genotyped data from MCS; and the learning that is being developed in relation to 'accidental' findings would also need to be built into procedures for MCS, as well as informing the consent process itself.
Substantive proposals for analysis would be subject to separate applications to relevant funding organisations but would be enabled and facilitated by this support.
3. Collection of physical activity data.
There is a great deal of interest in understand the patterns of physical activity, including sedentary behaviour, and how these relate to young people's growth patterns, including overweight, as well as to other aspects of their wellbeing and to their long-term outcomes and other.Self-report measures need to be extensive and detail to capture the range of patterns of physical activity and inactivity, and without a complex battery of questions can only provide limited insight into young people's activity patterns. Objective measures can be more convincingly obtained through direct measurement using accelerometers. Direct measures of physical activity can give a much better insight into patterns of moderate and intense activity, and into sedentary behaviour than report measures.
Accelerometers has been successfully collected not only in health-related surveys but also in MCS itself at sweep 4 (the age 7 sweep). Best practice in collection is also improving. At MCS4, 7-day wear was recommended. However, this was not only hard to achieve for many of the children, it is becoming accepted that two days of complete wear may be sufficient to understand activity patterns. Collection of data can contribute to ongoing debates about optimal forms and intensities of activity in relation to health and wellbeing. Combined with the planned age 14 diary, physical activity measures themselves can be enhanced by understanding the context of the activity as well as periods of non-wear.
There is substantial appetite within the scientific and policy community for utilising direct measures of physical activity and for repeating the measurement of physical activity at the critical age of age 14.
Thus the key element of this proposal is to implement collection of two full days of physical activity monitoring of MCS cohort members, using age appropriate and high quality accelerometers.
The proposed collection of physical activity using accelerometers would involve the young people being asked to consent to wear the accelerometer for 2 days, days that coincided with the days they completed a time diary. Parental consent would also be sought prior to the young person being approached.
There are two models that could be implemented. At the age 7 survey, those families that consented to wear the accelerometer were then posted from an external unit the accelerometer, and that unit, based at the Institute of Child Health (ICH) also dealt with follow-up, sending feedback and reminders to return. The ICH unit was responsible for charging the accelerometers, setting them in advance of posting them out, and downloading the data from them on return, before sending them out to the next batch of respondents. The first model would follow this approach but rather than an external unit, the fieldwork agency would themselves log the consenting cases, and send out the equipment, with a pre-paid envelope for return, download data on return and reset the devices for the next batch of consenting participants. On this model we would anticipate a 90 per cent consent rate and that up to 70 per cent of cohort families would return the accelerometers resulting in a gradual depletion of the stock.
A variant on this model (Model 1a) would be to integrate the enhancement fully into the MCS6 fieldwork. Interviewers would supply the accelerometers at the point of the survey having guided the cohort members on use, setting and administration. The interviewers would then be responsible for ensuring the devises were charged and set, and would need to be thoroughly briefed on this. They could then leave the accelerometers to be returned by post, as with the original version, and the fieldwork agency would need to ensure that reminders were sent in a timely fashion to maximise return. This would be more intuitive approach, in that distributing and implementing while in the household would accord with the general practice of the survey and enable questions to be dealt with on the spot, as well, potentially as encouraging wear. However, there would be an additional layer of complexity introduced as a result of the fact that the interviewers would need to be supplied on an ongoing basis with sufficient numbers to carry out the fieldwork, while the accelerometers were being returned, and data downloaded from the respondents. To ensure a smooth process would probably require a larger number of accelerometers than the total used at MCS4. The consent and return rates overall would be expected to be similar, though we could anticipate that a larger number would actually wear the devices prior to return increasing the overall data collection, and that thus the level of productive cases would be higher.
A second model would involve the interviewers not only administering but also collecting the accelerometers after the week containing the two 'wear days' had passed, and while they were in the area. This would increase fieldwork costs, possibly substantially and would require the interviewers themselves to be trained in downloading the data before resetting for subsequent participants or that they returned them in batches to the central office; but would increase the number of returned accelerometers, and thus reduce the total number needed / lost. It would obviate the need for requests for return, except in those cases where the interviewer was unable to follow up.
There are clearly advantages and costs associated with each of the approaches, and the tendering fieldwork agencies will propose and cost what they think is the optimal model. At present we judge this is likely to be closest to Model 1a, and we have estimated costs on that basis. For this we have assumed around 4000 accelerometers will be needed, rather than the 3000+ used in the age 7 survey, since at Age 11 the total stock was almost totally depleted by the end and left no room for flexibility in distribution.
As well as collecting the data, since these are complex data, to provide suitable outputs for users there would be the need to construct age-appropriate derived measures of activity and sedentary behaviour from the data, as was achieved for MCS4. This would be the key data deposit from this element of the data collection, though the 'raw' data would also be deposited for those who wished to work with it directly.
The derived variables would be constructed by an experienced data manager working with a statistician to produce the derived variables useable by the wider research community.
B2018 - Peer Mediating and Moderating Effects Upon Parent-Child Relationships School Connectedness and Adolescent Substance Use - 24/05/2013
This study aims to:
a) Independently assess the predictability of early social experiences [family, school and peers] upon the initiation and progression of substance use in late adolescence, and examine if they vary in importance according to different substances [alcohol, cannabis, smoking] and/or level of use [experimental, occasional, regular].
b) Examine the extent to which family relations and/or school experiences in childhood and substance use in late adolescence are mediated by peer's substance use in early adolescence.
c) Create two models of substance use: one to test whether peer use is moderating the effect of parent-child relationships upon substance use in late adolescence; and the other to test whether peer use is moderating the effect of school connectedness on substance use in late adolescence.
B2017 - Foetal programming of childhood asthma - 24/05/2013
Aim:To determine if the critical periods of growth and asthma/wheeze phenotypes identified in the BiB cohort be replicated in other populations. (ii) To determine if there are links between growth in early life and asthma.
Hypotheses:That the relationships observed between asthma/wheeze and growth in the BiB and other cohorts will be replicated in the ALSPAC cohort.
Exposure variables: Asthma/Wheeze symptoms and diagnoses (examined as latent class phenotypes)
Confounding variables: maternal/paternal history of asthma, maternal/paternal height, maternal/paternal smoking, maternal BMI, gestational length, mode of birth.
Outcome variable: Trajectories of growth (length and weight).
Statistical analyses: Firstly Latent class analyses will be undertaken to determine discrete phenotypes of asthma to be established that are specific to the ALSPAC cohort. Latent class analysis (LCA) allows classification of individuals into groups based on conditional probabilities as within each class individuals will have a similar pattern of response. As these models work with probabilities rather than absolute values this allows children to potentially be fractional members of all classes and use probability to assign class membership. The first stage of LCA will be to determine the optimal number of classes to the data by evaluating the best fitting model using multiple indices of model fit including Akaikes Information Criterion, Bayesian Information Criterion, entropy and likelihood ratio test using bootstrapping as well as assessing the face validity and meaningfulness of the resultant classes. The second stage of the modelling process, to determine the relationship between co-variates including ethnicity, gender and the latent class groups of phenotypes, will be conducted using multinomial logistic regression adjusted for probability weighted class assignment. For the regression analysis we will include co-variates that are significant at the 5% level in the univariate analysis. Any variables with greater than 3% missing data will be tested at the end of the modelling procedure using imputation to determine the resultant sensitivity of results to missingness.
Separate models of growth, for height and weight, will then be created for each latent class grouping. Growth models will be undertaken using heirachical linear spline models using knot points for growth identified in previous studies undertaken using ALSPAC data.In line with previous ALSPAC growth analysis the source of measurement (height and weight) will be included as a covariate in the models. Appropriate adjustment for other known confounders such as gestational length, maternal height and childs gender.
B2016 - Children of Alcoholic parents Cognition Behaviour Mental Health and Alcohol Use Trajectories - 24/05/2013
Background:
Alcohol use disorders (AUDs) are highly prevalent, affecting 3.6% of the global population (Rehm, Mathers & Popova et al., 2009). AUDs impact on the physical (liver disease, brain damage and injuries) as well as psychological well-being of the affected individual. Furthermore, AUDs have a considerable impact on the affected individual's family, larger social circle and society as a whole. There is a considerable genetic component to AUDs with heritability estimates of ~50-60% (van den Bree, Johnson eta, 1998). As many as 15% of children report living with an alcoholic parent (US data reported by Grant, 2000) while 43% of Children of Alcoholic parents (CoAs) will themselves develop an AUD in adulthood (Grant, 2000). It is therefore important to understand the developmental pathways of alcohol use/ misuse in this high-risk population.
Children of Alcoholics:
CoAs have been consistently reported to have poorer academic achievement than children of non-alcoholic parents (non-CoAs) (e.g. Puttler, Zucker, Fitzgerald and Bingham, 1998; Diaz, Gual & Garcia et al., 2008). However, the evidence regarding impaired performance on cognitive assessments (e.g. WASI/WISC) is less clear, with some studies reporting worse full-scale, verbal and performance IQ in CoAs (e.g. Diaz, Gual & Garcia et al., 2008) (Yang & Kramer, 2012), while others report no difference (e.g. Kultur, Unal & Ozusta, 2006). There have been no studies based on a large scale longitudinal population-based sample.
One of the most consistently reported differences between children with and without alcoholic parents is increased problem behaviours. These include externalising and antisocial behaviours, as well as internalising and hyperactive behaviours. Externalising and antisocial behaviours have been reported in children with alcoholic parents from a very young age, even including infancy (Edwards, Eiden, Colder & Leonard, 2006). These behaviours then appear to persist throughout development into adolescence (Hussong, Huang & Curran et al., 2010). Internalising behaviours, such as negative affect and anxiety are less reliable reported. There have been some positive results in early childhood (Haugland, 2003), but the majority of studies have reported that internalising behaviours become more common in children with alcoholic parents during adolescence (Hussong, Cai & Curran et al., 2008). This increase during adolescence may be related to the onset of the child's own alcohol use.
There is some evidence that suggests that maternal and paternal alcohol use can have differential effects on offspring (Connell & Goodman, 2002) and that offspring gender can influence the impact of parental alcohol use (Eisenberg, Haugen & Spinrad et al., 2010). Social factors, such as parental-offspring relationships and peers, can also influence the effect of parental alcohol use on the offspring (Stice & Barrera, 1995).
Current proposed study:
There is currently an absence of large population-based longitudinal studies which examine the associations between parental alcohol problem use and offspring behaviour. While there have been a number of small-scale longitudinal studies using high-risk populations (e.g. Chassin, Rogosch & Barrera, 1991; Eiden, Edwards, Colder & Leonard, 2009) and some larger population-based comparative studies (e.g. Yang & Kramer, 2012), there have been no studies which have the breadth of information available in the ALSPAC data set.
We propose to use already collected ALSPAC data to address the important issue of parental alcoholism. We will compare with and without alcoholic parents in the areas of cognition, behaviour, psychiatric problems and substance use. Additional analysis will be used to see if offspring's own alcohol use contributes to any differences we find and to see if parent or offspring gender and offspring's peer group also have an impact.
Aims:
1. Conduct comparisons between CoAs and nonCoAs at an early age (i.e. age 8), before alcohol use initiation, on relevant indices reported in the literature, including behaviour, academic performance and cognition, social factors (family and peer relations), and mental health problems.
Sub aims: examine any evidence for gender-specific effects (i.e., parent or offspring)
2. Conduct similar comparisons at later ages (i.e. 8-15), when participants are increasingly starting to use alcohol. Here comparisons will also include alcohol and other substance use at different ages.
3. Examine the longitudinal alcohol use/ misuse trajectories for CoAs and non-CoAs and to what extent specific covariates (see above) play a role in any differences.
Analyses:
Analysis 1 and 2. ANOVAs, chi-square tests, or regressions where CoA (yes/ no) is the dependent variable.
Analysis 3. Trajectories already exist. Each individual in the sample has been assigned a probability of belonging to different categories based on repeated measures of alcohol use collected at different ages. We will plot the trajectories for the two groups. We will conduct regression-based analysis to determine whether CoAs are more likely to belong to certain alcohol trajectories compared to non-CoAs, before and after adjustment for covariates.
References:
Chassin, L, Rogosch, F, & Barrera, M. (1991). Substance use and symptomatology among adolescent children of alcoholics. Journal of abnormal psychology 100(4), 449-463.
Connell, A.M., & Goodman, S.H (2002). The Association Between Psychopathology in Fathers Versus Mothers and Children's Internalizing and Externalizing Behaviour Problems: A Meta-Analysis. Psychological Bulletin, 128 (5), 746-773.
Diaz, R., Gual, A., Garcia, M., Arnau, J., Pascual, F., Canuelo, B., & Garbayo, I. (2008). Children of alcoholics in Spain: From risk to pathology. Social psychiatry and psychiatric epidemiology, 43(1), 1-10.
Edwards, E. P., Eiden, R. D., Colder, C., & Leonard, K. E. (2006). The Development of Aggression in 18 to 48 Month Old Children of Alcoholic Parents. Journal of abnormal child psychology, 34(3), 409-423.
Eiden, R. D., Colder, C., Edwards, E. P., & Leonard, K. E. (2009). A longitudinal study of social competence among children of alcoholic and nonalcoholic parents: Role of parental psychopathology, parental warmth, and self-regulation. Psychology of addictive behaviors, 23(1), 36-46.
Grant, B.F. (2000). Estimates of US Children Exposed to Alcohol Abuse and Dependence in the Family. American Journal of Public Health, 90 (1), 112-115.
Haugland, B. S. M. (2003). Paternal alcohol abuse: Relationship between child adjustment, parental characteristics, and family functioning. Child psychiatry and human development 34(2), 127-146.
Heron, J., Macleod, J., Munafo, M. R., Melotti, R., Lewis, G., Tilling, K., & Hickman, M. (2012). Patterns of alcohol use in early adolescence predict problem use at age 16. Alcohol and alcoholism, 47(2), 169-177.
Hussong, A. M., Cai, L., Curran, P. J., Flora, D. B., Chassin, L. A., & Zucker, R. A. (2008). Disaggregating the distal, proximal, and time-varying effects of parent alcoholism on children's internalizing symptoms. Journal of abnormal child psychology 36(3), 335-346.
Hussong, A. M., Huang, W., Curran, P. J., Chassin, L., & Zucker, R. A. (2010). Parent alcoholism impacts the severity and timing of children's externalizing symptoms. Journal of abnormal child psychology, 38(3), 367-380.
Kultur, S. E. C., Unal, M. F., & Ozusta, S. (2006). Psychopathology in children of alcoholic fathers. Turk Psikiyatri Dergisi, 17(1), 3-11.
Puttler, L. I., Zucker, R. A., Fitzgerald, H. E., & Bingham, C. R. (1998). Behavioral outcomes among children of alcoholics during the early and middle childhood years: Familial subtype variations. Alcoholism: clinical and experimental research, 22(9), 1962-1972.
Rehm, J., Mathers, C., Popova, S., Thavorncharoensap, M., Teerawattananon,Y., & Patra, J. (2009). Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders. Lancet, 373, 2223-2233.
Stice, E., & Barrera, M. (1995). A longitudinal examination of the reciprocal relations between perceived parenting and adolescents' substance use and externalizing behaviours. Developmental psychology, 31(2), 322-334.
van den Bree, M., Johnson, E. O., Neale, M. C., & Pickens, R. W. (1998). Genetic and environmental influences on drug use and abuse/dependence in male and female twins. Drug and alcohol dependence, 52(3), 231-241.
Yang, S., & Kramer, M. S. (2012). Paternal alcohol consumption, family transition and child development in a former Soviet country. International Journal of Epidemiology, 41(4), 1086-1096.
B2015 - Intrauterine stress effects on the intergenerational transmission of risk for adverse childhood experiences - 24/05/2013
Summary:
The proposed project will investigate the impact of foetal exposure to maternal depression on the intergenerational transmission of adverse childhood experiences (ACE) and psychopathology in a prospective longitudinal cohort study: the Avon Longitudinal Study of Parents and Children (ALSPAC). The overarching goal of this project is to elucidate key psychosocial pathways that underpin the intergenerational transmission of risk for childhood adversity (ACE, psychopathology, inflammation). The identification of such pathways would be of great clinical utility: targeted interventions early on could provide preventative strategies to limit these transgenerational cycles.
Background:
Childhood maltreatment is a major public health issue. Currently, over 50,000 children in England are on the child protection register (Department for Education, 2011). The National Society for Prevention of Cruelty to Children (NSPCC) identifies childhood maltreatment as any exposure to physical abuse, sexual abuse, physical neglect, emotional neglect or domestic violence. For research purposes, the term "adverse childhood experiences" (ACE), "victimisation" or "trauma" has been applied in a more generic manner to refer to such forms of maltreatment, as well as to other negative childhood experiences such as peer bullying and exposure to major traumatic life events. For the purpose of this proposal we refer to ACE as a means to encapsulate all such types of detrimental experiences.
ACE have repeatedly been shown to be associated with severe psychiatric illness in adulthood and adolescence, such as depression, psychosis and personality disorders (Fisher et al. 2012; McLaughlin et al. 2012; Nanni et al. 2012; Reed et al. 2013) as well as adulthood inflammation (Danese et al 2007, 2008). There is also a robust relationship between offspring exposure to maternal prenatal stress in utero and later psychopathology (O'Connor et al. 2002; Pawlby et al. 2009; Hay et al. 2010; Rice et al. 2010). Moreover, in our recent work we have demonstrated a strong association between an offspring's exposure to intrauterine stress (maternal depression) and their increased likelihood to experience ACE in middle childhood (Pawlby et al. 2011). Similar associations have since been reported in other samples, specifically the ALSPAC cohort, whereby offspring exposed to maternal depression/anxiety in utero were found to be at an increased risk for peer victimisation in middle childhood (Lereya et al. 2012). These data suggest two important points: i) exposure to depression in utero and ACE are likely part of the same putative pathway that links early life insults with an increased risk for persistent psychiatric disorders, and ii) exposure to maternal prenatal stress is a key risk factor for ACE.
ACE tend to be correlated across generations. Indeed, in both US and UK samples - namely the ALSPAC cohort - a mother's history of maltreatment in her own childhood predicts an increased probability for her offspring to be exposed to maltreatment (Sidebotham et al. 2006; Berlin et al. 2011). In our own sample - the South London Child Development Study (Sharp et al. 1995) - we have recently demonstrated the synergistic effects of maternal prenatal stress on the intergenerational transmission of ACE and psychopathology (Plant et al. 2013). Our findings indicate that maternal history of ACE and depression during pregnancy are key risk factors that interact, whereby the occurrence of both insults results in the greatest risk for offspring being exposed to childhood maltreatment and subsequent adolescent disruptive behaviour disorders. This data suggests that prenatal stress is a key risk factor for the intergenerational transmission of ACE and its sequelae. Whilst investigations into the intergenerational transmission of maltreatment have been conducted previously in the ALSPAC sample (see Sidebotham et al. 2001, 2006), to our knowledge, there has been no direct test of the impact of offspring exposure to maternal stress in utero on the transgenerational transmission of ACE and psychopathology. We thus propose to test this putative pathway for the intergenerational transmission of ACE and psychopathology in the ALSPAC sample, which will allow for a more robust and dynamic investigation of this model and its intricacies that were not so permitted in our existing analyses given our smaller size (n = 125).
B2013 - Understanding the wider context of the development of basic skills - 10/05/2013
We are about to apply for an ESRC Research Centre Grant, which will fund a cross-institutional (international) research centre for three years, with Coventry University acting as a 'hub' for collaborative working across the other centre sites. We would like to include ALSPAC as one of the national sites in this networked research centre, and cost into the project the price of one data analyst, to be employed by and based at ALSPAC for the three years that the Centre is funded (if the application is successful). This would enable us to identify research questions and specific hypotheses as a team and then ask the ALSPAC statistian to create and clean the data file and conduct the analysis agreed by the research team, with the statistian's input into this process too. This individual would be named as a coauthor on all outputs which draw on his/her work (i.e. all the activity associated with this specific work package within the centre). Broadly, we are interested in modelling the developmental relationships between key variables of interest, with a view to understanding some of the wider factors which appear to impact on children's school attainment, and their basic skills (reading, writing and mathematical abilities) in particular.
B2014 - Suicide attempt and self harm and its association with adolescent sexuality A UK community based study - 09/05/2013
Aims and Objectives:
To determine whether there is an association with minority sexual orientation in adolescence and self-harm or suicide attempt.
B2012 - Estimating features of trajectories in the diurnal BP of adolescents - 09/05/2013
Background: In many epidemiological scenarios, understanding change is crucial. Repeated measures (or longitudinal) data are one of the pillars of this understanding. Cohort studies and randomised controlled trails produce such data since a group of individuals are followed over time with repeated measurement of key exposure(s) or outcome(s). A plethora of methods exist for modelling such data, with mixed or multi-level models being at the forefront. However there is a lack of approaches capable of estimating features of trajectories borne out of such data. To accurately estimate a feature (such as the minimum or maximum of a trajectory) requires a descriptive approach not restricted by parametric assumptions. Furthermore, many features of a trend can only be extracted through derivative estimation. For example, derivative estimates are needed to obtain the maximum rate of change of a biological process or the time at first decline of a biomarker.
There is a strong positive association of systolic and diastolic blood pressure (SBP and DBP) across most of their distribution with increased cardiovascular disease risk. Higher SBP and DBP measured in adolescence and early adulthood are associated with increased coronary heart disease and stroke risk with magnitudes of association that are similar to those seen when blood pressure is measured in middle-life.
Blood pressure varies, by up to 20%, over the day (with lower levels during rest and in particular in deep sleep) and in response to different stimuli, one of which is physical activity. Variability in blood pressure across the day, and the magnitude of the difference between day- and night-time blood pressure have been proposed as independent cardiovascular risk factors over and above the mean level of blood pressure. Relatively little is known about these patterns and their correlates in healthy adolescents.
Aim: The aim of this proposal is to develop methods to accurately extract features of diurnal BP for individuals and for the sample. These may then be used to investigate associations with outcomes.
Hypothesis: Specific features of diurnal SBP and DBP trajectories in adolescents are associated with cardiovascular risk factors
Exposure: Extracted features of diurnal SBP and DBP. Linear mixed models are one commonly used approach for modelling continuous repeated measures. These allow separate modelling of the variability between members of the cohort and the variability within individuals. To handle non-linear trajectories over time, alterations to the linear mixed model are available, such as transforming the outcome, allowing for polynomial trends of the outcome over time (fractional polynomials) or allowing the outcome trend to change in different segments of time (regression splines). These can be useful if statistical inference is of primary concern. At the other end of the spectrum, when the question of interest is to describe the trend over time, these simple alterations can prevent goodness of fit because of the restrictions of a fully parametric model. In particular, when interest lies in identifying a feature of repeated measurements, a fully parametric model is not sufficiently flexible to obtain reliable estimates.
Flexible methods which borrow from the fields of mixed models and non-parametric smoothing come under the umbrella of functional data analysis (FDA). FDA encompasses the various modelling methods for these non-linear repeated measures data. Unfortunately, in the situation where measurement times are irregular across individuals, many methods under the umbrella of FDA become inefficient. In epidemiology such data are common since measurement often occurs within routine GP visits. Three approaches to modelling non-linear irregular repeated measures data have been identified, namely semiparametric mixed models, P-Spline mixed models and Principal components Analysis through Conditional Expectation (PACE). These have not been used to their full potential in the epidemiological literature.
In a range of disciplines it is often the case that the derivative, or rate of change, of observed data is of primary interest. In the situation where data are observed over time, the first derivative will correspond to velocity, the second to acceleration. In a LMM the rate of change is, by definition, constant for both the individual and cohort. Where the LMM contains a complex polynomial of time, this polynomial can be differentiated to give the rate of change of the biomarker at any timepoint, both on average and for each individual. When non-linear methods such as P-Splines are used, it can be difficult to obtain derivative estimates and their standard error analytically. Derivative estimation is a difficult problem for several reasons. Firstly, with no observations for derivatives, testing goodness of fit does not exist. Secondly, modelling the change of a variable over time is more sensitive to measurement error and outliers than modelling observed data. Third, standard errors can be difficult to obtain since many approaches use numerical methods to estimate the derivative as a by-product. However, derivative estimates can be very useful. For instance, when a first derivative estimate of a biomarker over time is below zero, the process is declining. Using the standard error to create variability bands, we obtain an analogous confidence interval comparison for evidence of decline. Derivative estimates allow us to obtain features of trend such as the maximum/minimum velocity or acceleration. These have been used in physiology as a marker for endurance and in child growth as a marker for puberty. Derivative estimates and their standard errors have yet to be obtained for several approaches to longitudinal data.
Outcome: Cardiovascular risk factors
Confounders: Age, sex, socio-economic status, smoking status, weight, height, fat mass, physical activity.
B2011 - Rural/urban differences in dietary intake in a UK cohort of children - 09/05/2013
Clear differences in dietary intake have been reported in residents of urban compared to rural areas. This has been frequently reported in developing countries (Bowen et al, 2012) but also in the USA and Canada (Downs et al, 2012). Differences have been reported in children/adolescents as well as adults. However, little is known about any differences in the UK.
It has generally been shown that residents of rural areas have a poorer nutrient intake compared to residents of urban areas. In developed countries, the primary reason put forward to explain these differences is down to the the food environment whereby food is generally reported to be more expensive in rural communities, with less availability and variety. It is unlikely that families living in rural communities in the UK exclusively purchase food in their immediate suroundings and we hypothesise that there will be no obvious differences in dietary profile. However, differences have been reported in obesity levels in the UK in rural versus urban areas through secondary analyses of the Health Survey for Englanddary analyses of the Health Survey for nhtat dietary intake is a driverand it is possible that dietary intake is a driver in this, so warrants attention. In addition, previous studies examining areas of residence and dietary intake suffer from residual confounding; not taking into account familial factors such as socio-economic status.
Exposures:
We plan to use the Rural/Urban Definition (England and Wales), a detailed rural/urban indicator defined by the Rural Evidence Research Centre at Birkbeck College (RERC) based on 2001 Census data and will be derived from our address information. The use of this indicator will allow us to distinguish between rural and urban areas using eight categories: Urban, Town and Fringe, Village, Hamlet and Isolated Dwellings; each on two sparsity levels) to examine detailed rural and urban residential effects on dietary patterns.
Given the heavily urban-weighted spatial distribution of the ALSPAC cohort and the potential lack of geographical representation of data in more remote areas, we also request Output Area (from which the Rural/Urban Indicator is built) and Super Output Area (Lower & Middle) to permit analysis in the event of unsatisfactory statistical power at the preferred (OA) scale.
Outcomes:
At each time point (7, 10 and 13 years) we will examine differences in selected energy-adjusted macro- and micronutrients and food group intakes derived from diet diaries according to the divisons described above using t-tests/ANOVAs as appropriate and will use general linear models to adjust for a variety of potential confounding factors.
We will also examine any differences in the clusters of dietary patterns previously described (Northstone 2012). When examining effects at ages seven and thirteen, population changes will be used to assess the accuracy of using the 2001 data for earlier/later years and extrapolating data appropriately if necessary.
If possible (dependent on relevant numbers) we will determine whether any changes in rural/urban indicator lead to any changes in dietary intake over time in an attempt to infer causality.
References
Downs SM, Fraser SN, Storey KE, Forbes LE, Spence JC, Plotnikoff RC, Raine KD, Hanning RM, McCargar LJ. Geography influences dietary intake, physical acitivity and weight status of adolescents. Journal of Nutrition and Metabolism 2012; doi:10.1155/2012/816834.
Bowen L, Ebrahim S, De Stavola B, Ness A, Kinra S, Bharathi AV, Prabhakaran D, Reddy KS. Dietary Intake and Rural-Urban Migration in India: A Cross-Sectional Study. PLoS ONE 6(6):
e14822. doi:10.1371/journal.pone.0014822.
K Northstone, AD Smith, PK Newby, and P Emmett. Longitudinal comparisons of dietary patterns derived by cluster analysis in 7 to 13 year old children. Br J Nutr 2012; 15: 1-9.
B2008 - Biomedical Research Informatics for Data Gathering and Exploitation in Systems Medicine BRIDGES - 09/05/2013
Margaret Thatcher was famous for her need for little sleep, though nobody knows with any accuracy, how little. Now we have the sensor technology to capture many such types of lifecourse data in real-time, to passively stream those data directly to databases, and to connect 'research,' 'health' and 'clinical' data seamlessly together. This opens the potential for highly integrated systems?medicine research encompassing many disease domains in conjunction with highly multidimensional data -for example, linking data for sleep, environment, genetics, diabetes and cardiovascular health, and neuropsychiatry for an holistic approach to reearch. Such data not only encompass simple tabulatable information but also complex data types that cannot be represented in standard formats, for example, MRI, continuous monitoring/signal processing, quantitative proteomics and next-generation sequencing. Novel data types rely on emergent database technologies and as yet many different types of issues tend to confine individuals' data into isolated and lost 'pockets' - in the NHS, in research units or simply unrecorded. There might, for example, be signature relationships between sleep duration, neuroanatomy, genetic and 'omic determinants, lifecourse, and health outcomes - we need the technology and data silos to be joined up to find out.
Our proposal capitalises on unique data-orientated developments in the co-applicants' institutions and aims to integrate, structure global access, innovate real-time sampling of patient data, facilitate complex analyses across and within diseases and train a new cohort of medical informaticians to pave the way for personalised and systems medicine of the future. The institutions are already engaged with large scale multilevel data (e.g. MRC Centres in Bristol and Cardiff; ALSPAC and 1958 birth cohort in Bristol; diabetes collections in Exeter; BRU's in Leicester) and technological developments in the vanguard for database integration, access and analysis challenges. They also have large scale funding for sensor technology development (EPSRC - Bristol and collaborators), for omics integration (EU - Leicester), for graduate training in complexity (EPSRC) and analysis bioinformatics (MRC), for integrated biostats/bioinformatics (BBU - Cardiff) and importantly, for splicing or searching biomedical data types together flexibly and securely (e.g. BRISSKit, SHRINE, DataSHIELD - Bristol and Leicester). The deep complementarities between the co-applicant centres, form the basis of the proposal's workpackages which work toward seamless streaming, integration and analysis of data for biomedical research driven by the context of our specific health and disease studies.
B1536 - The association of ADHD symptoms in childhood to self-harm in adolescence - 09/05/2013
Aims: To investigate the relationship between ADHD and self-harm, in order to see if self-harm can be considered to be a risk factor, and to explore any possible gender effects.
Hypothesis: That self-harm will be more prevalent in individuals with ADHD, particularly in females with ADHD, compared to controls with ADHD.
Method
We propose to obtain participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) which is an ongoing population-based study investigating a wide range of environmental and other influences on the health and development of children. Of the core cohort of 13,988 infants, 10% were randomly selected to be examined in more detail encompassing 10 examinations between 4 months and 5 years - the Children in Focus (CiF) clinics.
Outcome Variables
Diagnostic information (ADHD diagnosis) will be derived from the Development and Well-being Assessment (DAWBA) which was administered to all children remaining in the CiF cohort at 91 months of age (7 years 9 months). All children who were given a diagnosis of ADHD using the DAWBA will be included in the clinical experimental group (currently unknown figure). There will be a sex and age-matched control group. The number in this control group will be twice the amount in the clinical/experimental group.
We are interested in seeking data on self harm in the questionnaire at 16 years 6 months for all individuals that we have DAWBA information on (Section L: Deliberate self-harm, p. 39-43). Can be downloaded from the ALSPAC site: http://www.bristol.ac.uk/alspac/researchers/resources-available/data-det...
Confounding Variables
Associations between diagnosis of ADHD as a predictor for self-harm will be calculated using Chi square analysis. We will control for potential confounders in a logistical regression analysis exploring ADHD and self-harm: presence of learning difficulties and behavioural problems (DSM-IV items on Oppositional Defiant Disorder (ODD); anxiety, social class (of parents); gender and substance abuse. Both ODD and learning difficulties will be evaluated since both have significant impact on functioning and frequently co-occur with ADHD, however they are relatively unexplored as a potential confounding factor in ADHD studies.
B2010 - The developmental role of Behavioural and Neurobiological Dimensions in predicting Eating Disorders in adolescence/young - 08/05/2013
Eating Disorders (ED) are serious mental health disorders affecting approximately 5-10% of adults (Hudson et al., 2007; Swanson et al., 2011) and have a peak of onset in adolescence between the ages of 15-19 (Micali et al., 2013; Field et al., 2012). The etiology of ED remains poorly understood, though and interplay of genetic and environmental factors is likely to be at play. Research into the clarification of risk factors has been hampered by uncertainties about clear phenotypic distinctions across ED categories, and by a lack of integrative studies using a longitudinal approach to clarify risk for ED. This study aims to focus on how cognitive, emotional and social processes cause ED behaviors in adolescence and young adulthood in interaction with environmental factors from infancy onwards.
Cross-sectional studies have identified cognitive, emotional and social difficulties that are associated with ED.
There is cross-sectional evidence that anorexia nervosa (AN) is associated with emotional and social communication difficulties and that specific cognitive profiles characterize bulimic type disorders.
AN shares common features with anxiety (Silberg & Bulik, 2005; Micali et al, 2011); and a range of social communication deficits, including interpersonal problems and poor emotion recognition, are present in individuals with AN (Tchanturia et al., 2012; Treasure et al., 2012).
Bulimic-type ED are cross-sectionally associated with specific cognitive profiles characterized by poor attention (Dobson & Dozois, 2004; Faunce, 2002) and low inhibition (Galimberti, et al., 2012; Rosval et al., 2006).
Most of the studies cited above are cross-sectional and have often focused on one specific area of behavior or cognition.
In relation to genetic risk for ED poor replication of early candidate genes studies has led to newer approaches heralding possible successful identification of risk markers. Large genome-wide studies of psychiatric disorders have highlighted genetic similarities across disorders, indicating either poor specificity of genetic markers or poor specificity of categorical classification systems. It also remains to be determined what the role of genetic mechanisms that affect gene expression, such as epigenetic processes, is in relation to ED.
The purpose of this study is to investigate the contribution of specific Research Domain Criteria (RDoC) constructs (across behavioral/self report and biological units of analyses (genetic, epigenetic and biomarkers data)) and their interaction with environmental factors to the risk for ED behaviors (restrictive eating, excessive exercise, bingeing, purging at ages 13,14, 16, 18, 24) in a longitudinal developmental fashion. We aim to develop a risk prediction algorithm for ED behaviors that incorporates these predictors.
We propose to use data collected prospectively (and carry out a new wave of data collection) from a unique ongoing cohort study: the Avon Longitudinal Study of Parents and Children (ALSPAC), based in the United Kingdom, to investigate the prospective association of anxiety and social communication and AN-type behaviors (restrictive eating and excessive exercise); and cognitive control and attention and BN-type behaviors (bingeing, purging).
The availability of biological (blood samples and cord blood for DNA at birth, age 7/9 and 15/17 years), neuropsychological (between ages 1 and 5, 8 and 13 years), behavioral (every two years from 3 1/2 until 12 years and more detailed at 7,10 and 13 years), social (ages 1 and 5, ages 8-10, 12 years) data at repeated time points in 7,000-9,000 adolescents/young adults over a period of 20 years makes this cohort a unique resource.
We will investigate the following specific aims:
1. To determine whether anxiety and social communication difficulties:
a) are longitudinally predictive of developing AN-type behaviors (restrictive eating, excessive exercise) in adolescence/young adulthood (ages 13-24);
b) interact with life events to predict AN-type behaviors (restrictive eating, excessive exercise)
We hypothesize that high childhood anxiety and poor social communication will be predictive of restrictive eating and excessive exercise in adolescence/young adulthood; and that they will interact with childhood life events.
2. To determine whether low cognitive control and poor attention:
a) are longitudinally predictive of developing BN-type behaviors (bingeing, purging) in adolescence/young adulthood (ages 13-24);
b) interact with life events/bullying to predict bingeing and purging from ages 13 to 24.
We hypothesize that low cognitive control and poor attention will be predictive of bingeing and purging in adolescence/young adulthood; and will interact with life events/bullying.
3. To build a risk model across domains and derive a risk prediction algorithm that can be used to identify high-risk individuals.
Exploratory aim: Exploratory analyses on the effect of poor emotion recognition on restrictive eating and excessive exercise in 500 young males, using functional and structural neuroimaging will complement the above aims.
We will look at whether these patterns and associations vary by gender. We propose to use one of the largest population-based longitudinal study in the world with a long enough follow-up and data available across most units of analyses, to investigate longitudinal associations between specific constructs and ED behaviors in adolescence/young adulthood. The size of our sample and the repeat and comprehensive assessments will allow an investigation of risk for ED across specific cognitive, social and behavioral constructs and their interaction with environmental factors in a unique and cost-effective way.
Methodology
Outcomes:
ED behaviours collected at ages 13,14,16,18. A questionnaire will be included in the 24/25 clinic to assess ED. We will use the same questionnaire used at age 14.
Predictors:
This grant focuses on using dimensional behavioural/cognitive predictors recently identified in the Research Domain Criteria (RDoC) proposal (one of the strategic aims of NIMH). RDoC focuses on understanding specific neurobiological dimensional phenotypes by studying each across a series of indicators-called units of analyses (including available biomarkers, self-report measures and behavioural observation).
Data collected throughout childhood on anxiety/emotional disorders, social communication and neuropsychological tasks (constructs) will be used as predictors. Additionally we will use data on evironmental risk factors, such as life events throughout childhood and bullying/teasing as predictors.
Genetic data already collected on ALSPAC participants will be used to investigate the role of genome and epigenome across the constructs under study. In particular a polygenic risk score will be generated using results (top SNPs) from current MEGA-analyses from two consortia. Genome-wide methylation data available from ARIES will also be used.
Biomarkers, i.e. salivary cortisol at age 11/12 will also be used as predictors.
Confounders:
data collected throughout childhood on socio-demographic data. Basic demographic characteristics and an overall environmental adversities index will be constructed from mothers' questionnaire data as collected from pregnancy through to child age 11. Information on gender, ethnicity, SES, employment, education, income, housing, family type and size, mother age at birth, gestational age and birth weight will be recorded.
Child IQ collected at age 8 will also be used as a confounder.
Data analyses:
After initial dscriptive analyses across each variable a stepped approach will be used.
Firstly each construct under study will be investigated across its units of analyses using factor analysis or by deriving latent variables.
Secondly the association between hypothesised constructs and outcomes will be investiagated using univariable analyses.
Fourthly multivariable models will be applied.
In relation to aim 3. we will use a multivariable Cox proportional hazard regression backward elimination model for each outcome under study, by including variables identified in objective 1 and 2 to build a riks prediction model.
B1537 - The genetics of wound healing Collection of scar phenotypes following common insult and their genetic analysis - 29/04/2013
Where adult tissue is damaged, a complex repair process is taking place involving regeneration and acute phase immunological response. Unlike embryonic tissues, adult repair always leads to the formation of a fibrotic scar where the wound has healed, which ultimately can disable proper tissue function [1]. In recent years, research was able to link several genes to the event of scar formation . Knockdown of Ostepontin (OPN) in mice for example resulted in reduced granulation tissue formation and scarring [2]. It also has been indicated that TGF-beta1 in conjunction with Connective tissue growth factor (CTGF) is promoting scar formation [3]. Most of this data comes from mouse model studies, in humans however, less is known.
BCG injections were routinely given in schools since the 1960s (up until 2005) and lead to a charateristic scar, which individually differs in size and character. Before injection, a skin test is performed to test for exsiting Tuberculosis antibodies. If the test is negative, BCG injections are given [4,5]. In the age group of ALSPAC mothers, up to 70% were immunised each year during childhood, making it a great read-out for assessing population wide scarring outcomes.
By collecting information about different levels of BCG scarring outcomes in ASLPAC mothers by telephone interviews and combining this data with genome data we hope to perform a genomewide associaiton study (and possible rare variant analysis) for scar type. For ethical approval this research proposal will be submitted to ALEC. Please find attached documents summarising the infornation and SOP to be summarised and used during the course of proposed telephone interviews. These are in the process of development before submission to ALEC.
Analysis plan:
(i) develop cover letter, info sheet, protocol and consent form for the BCG scar study for use within a telephone interview
(ii) submitt proposal to ALEC for ethical approval
(iii) collect phenotypic data - coordinated effort with Kate Sherlock and tele-contact team
(iv) submit data for processing by ALSPAC team
(v) unite both genetic and phenotypic data to undertake tests of association
between genetic variation and phenotypic characterisation.
(vi) test selected genes plus surrounding regions locally for variant associated with scarring outcome
Genetic analysis will be supported by Nic Timpson.
1. Stramer, B.M., R. Mori, and P. Martin, The inflammation-fibrosis link? A Jekyll and Hyde role for blood cells during wound repair. J Invest Dermatol, 2007. 127(5): p. 1009-17.
2. Mori, R., T.J. Shaw, and P. Martin, Molecular mechanisms linking wound inflammation and fibrosis: knockdown of osteopontin leads to rapid repair and reduced scarring. J Exp Med, 2008. 205(1): p. 43-51.
3. Shi-Wen, X., A. Leask, and D. Abraham, Regulation and function of connective tissue growth factor/CCN2 in tissue repair, scarring and fibrosis. Cytokine Growth Factor Rev, 2008. 19(2): p. 133-44.
4. NHS (1996) Immunisation against infectious disease - The green book 1996 edition.
5. Shaaban, M. A., Abdul Ati, M., Bahr, G. M., Standford, J. L., Lockwood, D. N. and McManus, I. C., Revaccination with BCG: its effects on skin tests in Kuwaiti senior school children. Eur Respir J, 1990. 3(2): 187-91.
B1352 - Participation in meta-analysis consortium CREAM Consortium for Refractive Error and Myopia - 26/04/2013
ALSPAC myopia GWAS methodology
The YP phenotypes analysed were those collected at the TF3 clinic (refractive error, myopia case/control status, astigmatism case/control status, eye axial length, and corneal curvature).
The only mother's phenotype we have analysed to date has been myopia case/control status (inferred from questionnaire responses). We also plan to analyse the mother's quantitative refractive error (data on a subset of mothers collected from opticians or from assessments at the TF3 clinic). [Note that Exec approval for analysis of the mother's data was kindly granted recently to allow us to check for replication of our YP GWAS results].
Outliers, defined as values 4 standard deviations from the mean, were excluded. Quantitative traits were transformed to normal deviates prior to analysis. Autosomes: quantitative traits and case/control status were analysed with mach2qtl and mach2dat, respectively, using sex as a covariate (for datasets of imputed genotypes previously prepared by John Kemp). Chromosome X: analyses were run in PLINK. SNPs with an imputation quality Rsqless than 0.3 or MAFless than 0.01 were excluded.
We have not yet attempted joint analyses of YP + mother's data. If this is done, we will take account of the non-independence of the genotypes and phenotypes in parents/offspring (e.g. perform analysis in GenABEL using the mmscore function).
ALSPAC myopia GWAS results
We found no evidence of population stratification (l~1.00; ditto QQ plots). In YPs, we replicated a locus within the PDGFRA gene associated with corneal curvature in Asians [6]. In mothers, we replicated a locus associated with refractive error and myopia at 15q14 [4]. However, only a single SNP had a P-value below 5x10E-8 (an imputed SNP on the X chromosome with a MAF =0.06....and we note our X-chromosome analysis did not properly account for genotype imputation uncertainty).
Plans for meta-analysis
Most members of the CREAM consortium, including ALSPAC, have already participated in a replication of the 15q14 and 15q25 myopia loci [as approved by the Exec; manuscript currently in revision].
Meta-analysis will be carried out using standard procedures [10]. An Executive Committee will set specific objectives, consider applications for consortium membership, and resolve conflicts. To accelerate progress, analyses/manuscript writing will be distributed to three Working Groups (Refractive Error/Ocular Biometry/Astigmatism). Each working group will be co-chaired by individuals with expertise in statistical genetics and/or the phenotype of interest. Working Groups will be expected to organise conference calls at approximately monthly intervals to monitor progress. CW and/or JG will represent the ALSPAC myopia team in each working group (this option will also be open to GM & BSP if other demands on their time permit).
As well contributing directly to the meta-analysis, the ALSPAC cohort is ideal for examining the effects of genetic variants across childhood (e.g. following the strategy of Sovio et al. [11]) and their interaction with environmental exposures (e.g. following the strategy of Kilpelainen et al. [12]).
As mentioned above, a draft MOU has been prepared to cover the operation of the consortium (attached).
We would be grateful for the Exec's opinion on the MOU and any amendments that would be required before it could be given approval.
If the MOU were to be approved, we would also be grateful for advice on how it should be processed through the University, e.g. via RED?
References
1. Bamashmus MA, Matlhaga B, Dutton GN. Causes of blindness and visual impairment in the West of Scotland. Eye 2004; 18:257-261.
2. Hysi PG, Young TL, Mackey DA, et al. A genome-wide association study for myopia and refractive error identifies a susceptibility locus at 15q25. Nature Genet 2010; 42:902-905.
3. Sanfilippo PG, Hewitt AW, Hammond CJ, Mackey DA. The heritability of ocular traits. Surv Ophthalmol 2010; 55:561-583.
4. Solouki AM, Verhoeven VJ, van Duijn CM, et al. A genome-wide association study identifies a susceptibility locus for refractive errors and myopia at 15q14. Nature Genet 2010; 42:897-901.
5. Fan Q, Zhou X, Khor CC, et al. Genome-wide meta-analysis of five Asian cohorts identifies PDGFRA as a susceptibility locus for corneal astigmatism. PLoS Genet 2011; 7:e1002402.
6. Han S, Chen P, Fan Q, et al. Association of variants in FRAP1 and PDGFRA with corneal curvature in three Asian populations from Singapore. Hum Mol Genet 2011; 20:3693-698.
7. Yang J, Manolio TA, Pasquale LR, et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nature Genet 2011; 43:519-U44.
8. Lango Allen H, Estrada K, Lettre G, et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 2010; 467:832-838.
9. Dudbridge F, Gusnanto A. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol 2008; 32:227-234.
10. Thompson JR, Attia J, Minelli C. The meta-analysis of genome-wide association studies. Briefings Bioinformat 2011; 12:259-269.
11. Sovio U, Mook-Kanamori DO, Warrington NM, et al. Association between Common Variation at the FTO Locus and Changes in Body Mass Index from Infancy to Late Childhood: The Complex Nature of Genetic Association through Growth and Development. PLoS Genet 2011; 7.
12. Kilpelainen TO, Qi L, Brage S, et al. Physical activity attenuates the influence of FTO variants on obesity risk: A meta-analysis of 218,166 adults and 19,268 children. PLoS Medicine 2011; 8.
B2005 - A comparison of twin and singleton data for early life characteristic - 23/04/2013
Aims/Hypothesis:
Twin data are valuable for quantifying genetic and environmental contributions to phenotypes, including both disease risk (e.g. type 2 diabetes) as well as quantitative traits (e.g. body mass index). However, twins can differ from singletons insofar as they tend to be born earlier (37 weeks rather than 40 weeks), and smaller (lower birth weight). The extent to which twins differ from singletons on a range of other early life characteristics (e.g. adiposity, growth, appetite and illness) is unclear. It is important to establish the extent to which twin data are comparable to singleton data, in order to ensure that results derived from twin studies may be generalisable to singletons.
The primary aim of this project is to establish the extent to which twins are similar to singletons on a variety of early life characteristics, by comparing twin data from two UK-based paediatric cohorts (the Twins Early Development Study, and Gemini - Health and Development in Twins), with singleton data from a number of large UK-based cohorts including ALSPAC. We hypothesize that twins will not differ from singletons on early life characteristics, thereby supporting the generalisability of findings from twin studies.
Our secondary aim is to test if the relationship between different early life characteristics is the same for twins and singletons.
Exposure variable:
We do not have exposure variables as such, as we are comparing summary statistics across different cohorts. 'Twinness' or 'singleton' (captured by the cohorts themselves) will be the primary 'exposures' of interest.
Outcome variables:
Our primary interest is anthropometric data. Primarily, we will compare anthropometric data from the singletons in ALSPAC to twin data from the Gemini cohort (at a number of different age points from birth to 5 years) and the Twins Early Development Study (TEDS) (at 7, 10, 11 and 12 years).
In addition to anthropometric variables, we will be comparing the twins and the singletons on appetitive data. In the Gemini cohort we have data from the Baby Eating Behaviour Questionnaire (BEBQ) and the Child Eating Behaviour Questionnaire (CEBQ) and would be looking for a comparator measure for appetite within ALSPAC. We also hope to compare feeding behaviour; encompassing breast versus bottle feeding to ascertain, for example, whether having multiple babies would make breast feeding more difficult. Other variables that we will examine are illness (to establish if the shorter gestational period of twins effects their general health in the early years of their life), infant temperament, physical activity and sleep.
One of the primary interests of the Gemini Study is to understand the predictors of weight gain in early life. As such, we have established relationships between appetite and weight, and sleep and weight, using the twin data. We will therefore examine if the magnitude of the association between appetite and weight, and between sleep and weight is the same for twins and singletons.
We are also planning to compare our twin data to singleton data from the Cambridge Baby Growth Study cohort and the Millennium Cohort Study.
Confounding variables:
When making comparisons between the cohorts we will take account of gestational age, postnatal age, gender, parental age at birth, parental health, ethnicity, and sociodemographic information.
B2003 - Sexual orientation and problem drinking in adolescence - 22/04/2013
Aims:
1. To establish whether sexual orientation (at 15) is associated with problem drinking in late adolescence;
2. To assess evidence that any link between sexual orientation and problem drinking in late adolescence may be mediated by high levels of depressed mood and/or anxiety;
3. To test whether there are gender-specific differences (females vs. males);
4. To establish the prevalence of substance use (i.e., tobacco and illicit substances) in non-heterosexual vs. heterosexual adolescents.
Adolescent alcohol use represents a main public health concern as it causes short and long-term health problems and antisocial behaviour, which can lead to self-harm or harm to others (Coleman & Carter, 2005). Alcohol use is widespread in the UK where 88% of 15 year-olds report having drunk alcohol in the past 12 months and 1% of 14-16 year olds drink nearly every day.
Adolescents who identify themselves as gay, lesbian or bisexual (i.e. sexual minority adolescents) are at increased risk of involvement in problem drinking compared to their heterosexual counterparts, with studies reporting earlier age of onset of alcohol use, more frequent and heavier (i.e., binge) drinking, and more alcohol-related problems than heterosexuals (Bergmark, 1999; Corliss et al., 2008). Although there is evidence of differences in risk of problem drinking between males and females from a sexual minority background, the pattern remains unclear. Some studies have observed more alcohol problems among females than males while others have observed the opposite pattern (Ziyadeh et al., 2007).
Evidence also shows that sexual minority adolescents experience more mental health issues (i.e., depression and anxiety) than their heterosexual peers (Fergusson, Horwood & Beautrais, 1999; Hatzenbueller et al., 2008). Greater levels of anxiety and depressive symptoms may be elicited by gay-related stressors, such as the stress of coming out (Elze, 2002; Hatzenbueller et al., 2008). Symptoms of depression and anxiety have been found to predict elevated drinking and alcohol-related problems among non-heterosexual youth. However, to our knowledge, no study has attempted to establish whether these risk factors may explain the developmental relationship between sexual orientation and drinking. Our study aims to fill this gap by assessing whether the relationship between sexual orientation and problem drinking is explained by internalising disorders. We will also include risk factors of problem drinking, identified in the general population, in order to establish if they can further help us to understand this relationship. The risk factors we intend to use are school satisfaction, relationships with friends and parents, parental monitoring and alcohol attitudes (Sareceno et al., 2010).
Few studies also identified greater substance use and misuse among sexual minorities although less research has been dedicated to tobacco and illicit drug use in this sub-group (Hefferman, 1998). Thus, our final aim is to assess substance use prevalence in the non-heterosexual group compared to their heterosexual counterparts.
Hypotheses:
1. Adolescents who identify as not heterosexual report an earlier onset age of alcohol use and greater problem drinking in later adolescences;
2. We expect that the relationship between sexual orientation and problem drinking may be stronger for those experiencing internalising disorders;
3. There are gender-specific differences in these patterns. Although there is evidence in the general population that rates of depression are higher in female than male adolescents (Thapar et al., 2012), the findings for non-heterosexual adolescents are unclear. Thus, these analyses will be exploratory in nature
4. We expect higher engagement with other substances among non-heterosexual individuals.
Exposure variable(s): Sexual orientation assessed as sexual identity and also as sexual behaviour (i.e., gender of sexual partner); depressive and anxiety symptoms experienced by the teenager; relationship within the family members; parental monitoring; relationships with peers; school satisfaction; attitudes to alcohols
Outcome variable(s): Alcohol use: age of onset; drinking patterns and alcohol-related problems. Tobacco and illicit drug use.
Covariates: Family socio-economic status (SES); parental alcohol and substance use; parental depression; sensitivity to alcohol; conduct problems (i.e., Strengths and Difficulties Questionnaire)
Analyses:
We will conduct preliminary correlations and univariate regression models between sexual orientation and problem drinking as well as substance misuse to examine the association at baseline (i.e., age 15; cross-sectional data). Moreover, we will use structural equation modelling (SEM) to assess these relationships over time while controlling for relevant covariates (e.g., family SES, parental depression and alcohol misuse). Finally, we will use SEM to test the effects of theorised moderators and mediators (i.e., depressed mood and anxiety) on this association and assess whether they explain the direction and/or strength of the relationship. The model will also be adjusted for variables which have been identified as risk factors for both alcohol and substance misuse to assess whether they further explain this mechanism (e.g., relationship with parents and peers; attitudes to alcohol). We will conduct Multiple Imputation to account for missing data.
B2002 - Role of selected endocrine disrupting chemicals on sex-hormone levels at age 15 girls enrolled in the ALSPAC study - 22/04/2013
Plasma levels of testosterone and sex hormone-binding globulin are associated with risk of diabetes. Several cross-sectional studies have reported positive associations between exposures to endocrine disrupting chemicals (EDCs) with BMI or insulin resistance. There are no longitudinal studies, however, exploring associations of gestational concentrations of EDCs during pregnancy with endogenous sex hormones known to predict obesity. For this proposal we want to use data on concentrations of sex hormones and insulin resistance generated by Hany Lashen on a sample of girls at age 15 to explore associations with EDCs.
The goals of this proposal are to explore feasibility of testing study associations with current data and development of future studies on this topic.
B2001 - Effects of vitamin B12 intake during pregnancy on offspring cognitive ability - 22/04/2013
Background: Vitamin B12 is an essential nutrient and it is required in one-carbon metabolism, the biochemical pathway that leads to DNA methylation. Maternal vitamin B12 and more generally the one-carbon metabolism are associated with neurodevelopment although the evidence is scarce (e.g. Bhate et al., 2008, Bonilla et al., 2012). Maternal vitamin B12 status seems to affect offspring's DNA methylation (McKay et al., 2012) suggesting a role for DNA methylation in the association between vitamin B12 and neruocognitive development.
Aim: To examine the causal association between vitamin B12 during pregnancy and offspring cognitive development, using genetic variants previously associated with one-carbon metabolism as proxies for vitamin B12 in a two-way Mendelian Randomization study. To assess the role of DNA methylation as a mediator in the association.
Hypotheses: We hypothesize that alleles which increase the levels of vitamin B12 during pregnancy will be associated with better cognitive performance. We hypothesize that DNA methylation mediates this association.
Exposure variables: Maternal and offspring genotypes for polymorphisms associated with vitamin B12 status and DNA methylation. Maternal vitamin B12 intake during pregnancy and cord blood levels.
Outcome variables: SCDC, WISC, WASI, CCC, DAWBA conduct problems.
Confounders and mediators: Maternal education, social class, age at delivery, parity, smoking during pregnancy, alcohol and folate assumption during pregnancy, infections during pregnancy. Child's date of birth, birth weight, sex, gestational age. Breastfeeding duration. Child's DNA methylation status.
Bhate V, Deshpande S, Bhat D, Joshi N, Ladkat R, Watve S, Fall C, de Jager CA, Refsum H, and Yajnik C. Vitamin B12 status of pregnant Indian women and cognitive function in their 9-year-old children. Food Nutr Bull. (2008) 29: 249-254.
Bonilla C, Lawlor DA, Taylor AE, Gunnell DJ, Ben-Shlomo Y, Ness AR, Timpson NJ, St Pourcain B, Ring SM, Emmett PM, Smith AD, Refsum H, Pennell CE, Brion MJ, Smith GD, Lewis SJ. Vitamin B-12 status during pregnancy and child's IQ at age 8: a Mendelian randomization study in the Avon longitudinal study of parents and children. PLoS One. (2012) 7:e51084. doi: 10.1371/journal.pone.0051084.
McKay JA, Groom A, Potter C, Coneyworth LJ, Ford D, Mathers JC, Relton CL. Genetic and non-genetic influences during pregnancy on infant global and site specific DNA methylation: role for folate gene variants and vitamin B12. PLoS One. (2012) 7:e33290. doi: 10.1371/journal.pone.0033290.
B2000 - Effects of pubertal timing on childrens bullying behaviour and mental health - 15/04/2013
Aim:
To investigate whether pubertal timing has an impact on bullying and victimisation at school for males and females and whether the relationship between peer victimisation and mental health problems (such as depression symptoms, psychosis symptoms, anxiety or self-harming behaviour) would be exacerbated by early maturation (girls) or late maturation (boys).
Hypotheses:
1) Early-maturing girls will be more likely to be victimised.
Outcome Variables:
Bullying status groups according to child, mother and teacher report at ages 8 to 18.
Exposure Variables:
Puberty measures from 8 years to 17 years
Confounding variables:
Demographics: gender, ethnicity, family social and economic status, home ownership;
Family factors: domestic violence and harsh parenting, maternal mental health status, child abuse and maltreatment;
Psychological factors: any mental health problems using DAWBA, internalizing and externalizing problems using SDQ, depression using SMFQ and MFQ;
Individual factors: sex, IQ, sexual relationships
2) Late-maturing boys will be more likely to be victimised.
Outcome, exposure and confounding variables:
Listed as above.
3) Off-time puberty will mediate/moderate the relationship between bullying involvement (at ages 8, 10 and 12) and menteal health problems (ie.depression, psychotic experiences, anxiety and self-harm) and sexual relationships.
Outcome, exposure and confounding variables:
Listed as above.
Outcome:
Depression, psychotic experiences and anxiety at 18 years and self-harming behaviour at 16.5 years and sexual relationship in adolescence.
Analysis:
Logistic regression analysis, multiple mediation model and structural equation modelling will be used to test the hypotheses. Given the potential impact of attrition on the findings, the data may be weighted for each part of the analysis. A logistic regression approach to weighting will be employed with bullying data available versus not available specified as the dependent variable and factors likely to predict attrition (e.g., gender, ethnicity, parental social class, family environment) included as independent variables and predicted probabilities (pprob) obtained. The inverse probability weight will then be calculated as 1/pprob.