Proposal summaries
B1511 - APOE and working memory at 17 - 14/02/2013
APOE is a gene found on chromosome 19 in humans, which encodes a protein (ApoE) which is involved in lipid transport. ApoE is the main lipid transport protein in the brain.There are 3 known variants of APOE: epsilon2, epsilon3 and epsilon4. epsilon4 is thought to be the ancestral allele of APOE(Mahley et al 2000), but in the UK population the expected frequencies of epsilon3, epsilon4 and epsilon2 are 0.78, 0.14 and 0.08 respectively.(Abdollahi et al 2006) These variants are the single of single nucleotide polymorphisms at two locations: T2060C(Cys112Arg) and C2198T (Arg158Cys).(Ensembl) The epsilon3 allele has cysteine and arginine in these two positions, the epsilon2 allele has cysteine in both and the epsilon4 allele has arginine in both.(Weisgraber et al 1981)
Possession of an e4 allele has been robustly shown to increase the risk of late onset Alzheimer's disease (Corder et al 1993). It is now known that ApoE is involved in neuronal repair, with E4 being the least efficient isoform (White et al 2001) and that APOE genotype influences outcome following head injury (Teasdale et al 1997).
Positive pleiotropy of the e4 allele has been investigated over the last 10 years with mixed results (e.g. Hubacek et al 2001, Bunce et al 2011). There is no effect of e4 on IQ (Taylor et al 2011), but several fMRI studies have been reported as showing more efficient memory activation in young adult e4 carriers (e.g. Scarmeas et al 2005). Working memory and e4 has been little studied, but there are suggestions from small imaging studies that e4 may be beneficial for working memory in young adults (Rusted et al 2013). Conversely studies of middle aged and older adults have found a deleterious effect of e4 on working memory (Reinvang et al 2010, Greenwood et al 2005)) A study of 445 people of mixed ages found no effect (Alexander et al 2007)
Defects in working memory have been reported as one of the earliest deficits seen in Alzheimer's disease (McKhann et al 1984). I therefore aim to study the relationship between APOE genotype and working memory in a large community sample of young adults.
Hypotheses
1) Null hypothesis: APOE genotype does not influence working memory performance
2) APOE genotype influences working memory performance, either positively or negatively.
Exposure Variable
APOE genotype
Outcome Variables
Working memory performance, specifically performance on the n-back test aged 18 with accuracy across the 2 and 3 back levels being the primary outcome.
Confounding Variables
In genetic studies it is often difficult to identify confounders as they have to have an independent relationship with both the genotype and the outcome of interest. Head injury outcome is known to be associated with APOE genotype and such injuries can have a wide range of adverse neuropsychological effects. APOE genotype is known to influence LDL levels. I would like to use this as a proxy means of checking genotyping accuracy as is routinely done in this field. Higher LDL levels have also been linked to increased cognitive problems in later life. I would like to investigate a number of other variables likely to modify working memory performance to see if they have any effect on my results.
B1510 - Children of parents with depression DANVA as a predictor of child psychopathology - 14/02/2013
Depression is one of the most commonly occuring mental illnesses, with a lifetime prevalence of 9.4%
(Kessler, 2012). The World Health Organization has ranked depression among the top 4 leading causes of
disability worldwide (WHO, 2008). Rates of depression also appear to be universally higher for women
than men, with women being roughly at 2 times greater risk of developing depression than males
(Kessler, 2003; Weissman & Klerman, 1977). This sex difference has been attributed to differences in
seeking out rewarding behaviours (Ryba & Hopko, 2012), response toward emotionally salient stimuli
(Bradley, Codispoti, Sabatinelli, & Lang, 2001) and differences in underlying neurocircuitry including the
inferior frontal gyrus and left amygdala (Stevens & Hamann, 2012). Children of parents diagnosed with
major depressive disorder (MDD) are also 2-3 times more likely to develop depression (Johnstone,
Lawrie, & Cosway, 2002; Lieb, Isensee, Hofler, & Wittchen, 2002; Weissman et al., 2006) and 2-3 times
more likely to develop other anxiety or behavioural disorders (Lieb et al., 2002; Mars et al., 2012;
Weissman et al., 2006). This risk suggests the influence of either familial genetic loading or
environmental factors. The most commonly reported risk allele is a low-expressing variant of the
serotonin transporter gene (5HTTLPR) (for more information please see appendix 1b).
Maternal behaviours towards their own children can also be affected by depression. Mothers become less
emotionally responsive to their infants as a result of depression and this has noticable effects on the longterm
behavioural and social outcome of the offspring. In infancy, these children are more likely to show
avoidance or disorganized attachment behaviours (to strange situation tasks) (Madigan, Moran, &
Schuengel, 2007; Martins & Gaffan, 2000) and higher rates of internalizing/ externalizing behavioural
problems (Garai et al., 2009) than children of non-depressed mothers. Children of depressed mothers have
poorer scores on the Child Behavioural Checklist (CBCL) when children were exposed to maternal
depression during their first year of life (Bagner, Pettit, Lewinsohn, & Seeley, 2010). They also show
lower scores on the Peabody picture vocabulary test; a measure of verbal fluency (Brennan et al., 2000),
lower scores on the Rey Auditory Verbal Learning task; a measure of declarative recall memory (Mannie,
Barnes, Bristow, Harmer, & Cowen, 2009), but, executive functioning does not seem to be affected by
parental depression (Micco et al., 2009). However, emotional labeling deficits remain the most commonly
reported deficit among offspring of depressed parents, suggesting difficulties in the emotional processing
network is part of the core psychopathology among at-risk children.
The purpose of this study is to determine the extent to which childhood emotional face labeling ability
mediates risk for depression (by having one or more parent with depression) and the psychiatric outcome
in adolescence. We predict that errors in emotional labeling (measured at 8 years of age) in childhood will
be significantly associated with (1) exposure to maternal depression in childhood, and (2) depression or
other psychiatric effects in adolescence. We predict this emotional face labeling ability will account for
part of the measured association between maternal depression severity and youth depression in
adolescence. Furthermore, we predict that the child's genetic risk for depression (identified by the lowexpressing
serotonin allele status) will be a moderator between maternal depression exposure and their
emotional face labeling ability. We predict that short allele status in the children will increase the effect of
exposure to maternal depression and this effect with be seen as greater difficulty on the
B1509 - GWAS meta-analysis on sleep duration - 14/02/2013
Aims: Humans sleep a third of their life and adequate sleep duration is an important factor in preventing metabolic and psychiatric disorders.
Two GWAS studies in adults have suggested that genetic factors may influence the sleepiness and circadian rhythms. Allembrandt et al. (2011) conducted high-density genome-wide association studies for sleep duration in seven European populations and identified an intronic variant (rs11046205; P=3.99 * 10(-8)) in the ABCC9 gene that explains Approximately 5% of the variation in sleep duration. RNA interference knockdown experiments of the conserved ABCC9 homologue in Drosophila neurons renders flies to sleep less during the first 3 h of the night. ABCC9 encodes an ATP-sensitive potassium channel subunit (SUR2), serving as a sensor of intracellular energy metabolism. Similarity the linkage analysis of sleep by Gottlieb et al. (2007) revealed a linkage peak close to the gene PROK2. Its product is the precursor of prokineticin 2, which is highly expressed in the suprachiasmatic nucleus, regulated by the circadian molecular clock, and believed to be an important output molecule from the suprachiasmatic nucleus, coordinating and transmitting the behavioural circadian rhythm to multiple brain regions (Cheng et al. (2002); Li et al. (2006).
Little is known about the genetic underpinnings sleepiness at distinct childhood growth phases. Through a large-scale meta-analysis of GWAS data for sleep duration, our main aim is to identify genetic mechanisms that underlie sleep duration during childhood.
Hypotheses: We hypothesize that a meta-analysis of GWAS data can identify genetic factors associated with sleep duration.
Outcome variable: Sleep duration during day (night + naps)
Exposure variables: Genetic variants as identified by GWAS genotyping and imputing (1000 Genome Project, release March 2012)
Confounding variables: sex, age, BMI
B1506 - Alcohol consumption and cardiovascular health in adolescents - 14/02/2013
Title:
Alcohol consumption and cardiovascular health in adolescents
The question whether alcohol is protective or a risk factor for cardiovascular disease in adolescents and, if so, where the threshold might be, remains largely unanswered. There are interesting similar behavioural patterns regarding excessive alcohol consumption and overindulgence in eating that leads to obesity, the mechanisms of which are relatively unknown. Marc Schuckit and co-workers have shown that the drinking pattern and level of response to alcohol have values in predicting future heavy drinking and alcohol problems in earlier studies of the ALSPAC cohort (Schuckit & Smith, 2008) as well as other populations (Schuckit & Smith, 2011). Both excessive alcohol consumption and obesity are well- known risk factors for developing cardiovascular disease (Juonala et al., 2009), (Romelsjo, Allebeck, Andreasson, & Leifman, 2012), but the mechanisms and interactions are not easy to investigate in an adult population where the damage is already well established.
Regarding the possibility of a common genetic origin of disease for obesity and alcoholism, there have been few studies with different results. Closely connected to obesity, the FTO rs9939609 genotype has been investigated for association with measures of alcohol consumption, but with inconsistent results (Sobczyk-Kopciol et al., 2011). There are to our knowledge no studies in children, when the epigenetic influence might be less muddled, and therefore present a truer picture of these associations.
Similarly, we know of no previous prospective studies of alcohol consumption and its influence on cardiovascular health, or the connection to obesity, in adolescents of both genders.
Aim:
The ALSPAC - study has investigated cardiovascular risk factors, adiposity, alcohol consumption, a low sensitivity to alcohol (a risk factor for heavy drinking), drinking patterns and drug in children at the ages 9-12 and 17-20.
In the present study our aim is to study cross-sectionally and longitudinally whether alcohol consumption is associated with cardiovascular changes in young healthy adults.
Hypotheses:
We hypothesise that:
1. Alcohol consumption affects cardiovascular risk factors and vascular phenotype:
- cross- sectionally at age 17-20
- with detectable thresholds of alcohol consumption for increased cardiovascular risk or deleterious vascular phenotypes
- with detectable gender differences
We also hypothesise that an earlier onset of alcohol consumption (ages 9-17) relate to the cardiovascular measurements more closely than alcohol quantities and frequencies alone
2. There is an additive effect of alcohol and obesity on cardiovascular risk and vascular phenotype, in the sense that alcohol consumption have an additive relationship to the cardiovascular risk development or adverse vascular phenotype in obese children.
3. That alcohol consumption and obesity are related as measures of common behavioural origins, and that obesity is associated with the sensitivity (i.e., the level of response) to alcohol or alcohol consumption:
- at age 12 or 17 (cross- sectional)
- obesity at age 12 predicts the level of response to alcohol at age 17
- obesity at age 12 predicts the alcohol consumption at age 17
- alcohol consumption at age 12 predicts the development of obesity at age 17
4. That the genetic predisposition to obesity is augmented by alcohol consumption in young.
Exposure variables will be: alcohol intake, level of response to alcohol, duration of alcohol intake, obesity genes.
Outcome variables will be : Cardiovascular measurements: PWV, FMD, brachial distensibility, blood flow, IMT, carotid distensibility, blood pressure and heart rate. Biochemical measurements: IL-6, CRP, Adiponectin, Leptin, Cholesterol, Non-fasting triglyceride. Obesity outcome: BMI, Fat mass.
Confunding variables are: age, gender, heart rate, height, weight, smoking, exercise, medical history, drugs intake.
B1504 - Exploring genetic association between schizophrenia and dimension-specific psychotic experiences in adolescence - 14/02/2013
The current project is an initial step aimed at uncovering genetic aetiology of psychotic experiences in a population based study of adolescents. The aims of the current study are three-fold. First, to examine potential associations between previously identified and reviewed Schizophrenia associating single nucleotide polymorphisms (SNPs) and dimension-specific psychotic experiences in a community based sample, using Twin Early Development Study (TEDS;Oliver & Plomin, 2006) data. Psychotic experiences are measured in TEDS using a quantitative dimension-specific Psychotic Experiences Questionnaire. Second, to create a gene score made up of previously identified risk alleles and to test for associations with psychotic experiences. Third, to replicate significant associations found in stage one of the analyses using Avon Longitudinal Study of Parents and Children (ALSPAC) sample.
It is hypothesised that some of the previously identified Schizophrenia associating SNPs will be also associating with the dimension-specific psychotic experiences. It is further expected that there will be an association between the polygenic scores and psychotic experiences. Finally, it is hypothesised that any statistically significant findings made using TEDS sample will be then replicated using ALSPAC.
The study will employ allelic and genotypic association analysis between SNPs of interest and psychotic-like symptoms as well as polygenic risk analysis. Sex, age and SES will be treated as potential covariates.
B1494 - The development of aggregation methods for rare variant analysis - 14/02/2013
Aim: To apply a range of statistical methods involving the aggregtion of genetic variant data. We intend to undertake this with the aid f pathway analysis and weighing the analysis with prior biological information.
Hypothesis: Pathway analysis and prior biological information can improve the performance of analytical methods involving the aggrevation of rare genetic variants.
Exposure variables: We would like to carry out the project with as much data as possible as this will give us the maximum amount of statistical power for our analysis. Therefore we would like all available genotype data from the ALSPAC cohort for genetics vriants with MAFless than = 0.05 if possible.
Outcome variables: We would also like access to the phenotype data mentioned in Section 8. If possible we would also like to perform a hypothesis free analysis using a wide range of phenotypes. It would therefore be ideal to have direct access to the R drive which I've had experience with on a previous project.
Confounding variables: As we will be looking a the effects of aggregated genetics variant scores on individual phenotypes on interest we will not have to consider possible confounding phenotype variables.
Project Background:
Currently there are few analytical approche that provide the necessary power to efficiently analyse rare variant data (ie variants with MAFless than 0.05) and therefore there needs to be an emphasis on the development of new methods. Our aim is to conduct an overview of the existing methods which aggragate rare variant data together and then to apply more novels measures to develop improved methods with greater statistical power,. In order to achieve this we owuld like to request access to all the ALSPAC genotype data for genetic variants with a minor allele frequency of 0.05 or les. Although we have some phenotypes i particular that we are interested in, we would also like to be able to undertake a hypothesis free analysis of cardiovascular phenotypes if possible.
B1491 - Life course socioeconomic patterning of dental health in ALSPAC - 06/02/2013
Aims: Describe the socioeconomic patterning of dental health trajectories, in terms of changes in number
of decayed, missing and filled primary and permanent teeth, from birth to young adulthood, in the
ALSPAC cohort.
Analyze whether changes in dental health in this period is related to socioeconomic background, in terms
of parental socioeconomic data, and to suspected adverse early exposures antenatal and postnatal, and
finally to individual characteristics from birth to young adulthood.
Hypotheses:
a) Early adverse exposures both antenatal and postnatal have causal relations to dental health
trajectories.
b) Expected relations between socioeconomic position of parents and dental health trajectories of
their offspring can be explained by overrepresentation of early adverse exposures in low socioeconomic
groups.
c) Dental health trajectories from birth to young adulthood also relate to various individual
characteristics. For instance individual level of education, health behaviors and awareness, and general
health.
d) Social mobility will affect the level of dental health as young adult.
Outcome variables: Number of decayed, missing and filled primary and permanent teeth (dmft
and DMFT) from children in focus obtained from clinical examinations at 31,43 and 61 months.
Combined with appropriate outcome measures from questionnaires antenatal to age 17.
2. Main exposure variables: Life course socioeconomic position
- Parental Socio-economic position: Educational level of parents, marital status, housing tenure,
income level, car ownership
- Child's Individual socio-economic position: Educational level, labour market association
3. Other exposure/mediating/confounding factors:
Antenatal:
- Parents health status: Comorbidity such as diabetes, psychological disorders etc.
- Maternal health awareness: Dietary habits, smoking habits (both parents), level of physical
activity, BMI, use of dental health care system, medication
Postnatal:
- Parents health status: Comorbidity
- Parents health awareness: Breastfeeding characteristics, dietary habits, smoking habits, use of
dental health care system
- Individual dental hygiene
- Individual health behavior and awareness: Dietary habits, smoking habits, physical activity level,
BMI
- Individual general health: Birth weight, Comorbidity
- Individual social network: Level of support from family and friends
B1503 - Mapping and assessing TP53-associated linkage disequilibrium blocks in cancer reproductive traits and viral infections - 31/01/2013
The general focus of the work to be carried out is to understand the importance of the TP53 gene and its product (p53 protein) to several aspects of human health and disease (comprehensively available in the ALSPAC cohort database), including cancer, reproductive traits (such as pregnancy loss and success of assited reproduction) and viral infections. The p53 protein is essentially a transcription factor that is well-understood to play crucial roles in cancer. This protein mediates the response to DNA damage signals by activating cellular pathways that result in senescence or apoptosis. Mutations in the coding region of TP53 have been found in approximately 50% of all human cancers (although this can vary considerably depending on the cancer type), thus being a hallmark of tumourigenesis. More recently, p53 has been evidenced to participate of other biological contexts, including skin colour, embryo implantation to the uterus, metabolic disorders, ageing and viral infections.
Germline genomic variations (mainly Single Nucleotide polymorphism - SNPs) in TP53 have thus been extensively studied as an attempt to identify genetic markers of cancer predisposition, which would represent a contribution to the clinical field. SNPs are, in general, low-penetrance genetic variations that depend on complex interactions with other genetic profiles and environmental factors to be associated with a certain phenotype or disease. Considering that SNPs that change protein primary amino acid sequence (non-synonymous SNPs - nsSNPs) tend to have more prominent effects on protein function than synonymous or non-coding SNPs (although the relevance of these two last have been evidenced in the context of mRNA expression, splicing or translation), the majority of the currently available association studies has given attention to TP53 nsSNPs. Although there is a considerable amount of nsSNPs reported for TP53, the current work focus is on four of them, which may be considered the best validated: P47S, R72P, V217M and G360A. The two first nsSNPs have been substantially evidenced to functionally impact p53 function (p53 transactivation activity and apoptosis efficiency, respectively) and have been associated with cancer risk, while the remaining two currently lack such association findings. Interestingly, both these nsSNPs have functional experiments suggesting they might be important in cancer (V217M is located in the DNA binding domain of p53 and G360A has been evidenced to impact the transactivation of some p53-interacting proteins).
The notion that the association between a SNP and a phenotype is complex and the experimental evidences for assuming V217M and G360 SNPs might have significant impacts on p53 function, the current project proposes the investigation of TP53 haplotypes (set of SNPs on a single chromosome that are statistically associated) regarding the four nsSNPs described, as well as linkage disequilibrium (LD) blocks (which are composed of genetic loci that do not - in a statistical sense - do not segregate randomly) with SNPs in other genes. For instance, the association of TP53 R72P SNP and response to UV exposure (and, consequently, associations with tanning and skin cancer) are dependent on SNPs in the MC1R gene (a typical epistatic effect).
Studies of this nature are particularly suitable for large population cohorts such as ALSPAC, since the tendency of reducing the number of individuals per genetic subgroup when analyzing haplotypes would not result in insufficient statistical power. Moreover, there are comprehensive data available regarding ALSPAC mothers health, which is invaluable for the present study. Since TP53 R72P SNP is well-established to be associated with skin color, ALSPAC data is also of interest because it has little ethnic admixture, reducing bias. In this topic, the large and high-quality characterization of the sample (including massive data at the genetic level) allows the construction and assessment of LD blocks with high accuracy, converging information of different pathways at the genetic level.
The aims of the project can be divided in: 1) Identify haplotype and LD blocks involving the nsSNPs of interest. 2) Investigate possible associations of these blocks with different disease traits available for ALSPAC cohort. 3) Investigate possible interactions of TP53 nsSNPs with SNPs in LD with them regarding the associations of the latter with traits currently not described as affected by TP53. 4) Understand how TP53-associated SNPs interact with each other in order to provide substantial insights related to the genetics of complex traits. ((5) With a possibel amendment, extend analyses to other variants collected in ALSPAC (from GWAS/sequence data) across the TP53 locus).
B1502 - Variations in wound healing loci and their association with injury and scar related outcomes in the ALSPAC cohort - 31/01/2013
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.
Using ALSPAC data we want to perform both a candidate driven analysis and a non-hypothesis driven GWAS (the latter being determined by the sample sizes generated from available phenotypic data) comparing individuals involved in an accident developing a scar compared to individuals involved in an accident who did not develop a scar. Where possible, we will attempt to assess differing types of scar
tissue and healing related phenotype, however this will again be contingent upon available phenotypic data).
Analysis plan:
(i) assess the depth of data pertinent to scarring phenotypes and establish cases
control series according to differential scarring patterns.
(ii) perform bioinformatic work up of select genes (LIST) to establish likely
functional variants across the coding region and surrounding region.
(iii) unite both genetic and phenotypic data to undertake tests of association
between genetic variation and phenotypic characterisation.
B1501 - NUTRIMENTAL call under FP7-KBBE-2013-7 - 31/01/2013
The aim is to examine the role of life styles, social background and socioeconomic factors on the mood-nutrition reciprocal relationships using samples from countries with different diets and different levels of mental health problems. For example, Mediterranean, Scandinavian and UK or US samples have been investigated in isolation but no study has carried out a comparison of social and dietary influences on mental health in different countries. Other factors which can be examined are changes in diet-mental health relationships across different age groups, gender and socio-economic status.
The research methodology will be largely based on secondary analyses of existing databases. In some cases the diet-mental health relationships have already been examined and the novel part will be the inclusion of social influences into the analyses. However, there are also extensive new samples which can provide new information on these topics. For example, in the UK the Biobank initiative has led to the collection of relevant data from 350,000 individuals. This database is potentially available (for a small fee) to the present project.
B1500 - External validation of an algorithm to estimate overweight risk in childhood from predictors during infancy - 31/01/2013
Background:
In the United Kingdom in 2010, around three in ten boys and girls (aged 2 to 15) were classed as either overweight or obese. However, overweight and obesity rates are not currently available for the under 2s despite evidence that some infants are larger than desired. Estimates vary but it is thought that between 25% to 33% of infants gain weight rapidly during the first six months of life. Rapid weight gain during infancy is associated with obesity between 6- 8 years of age and later life. There is evidence that weight at 5 years of age is a good indicator of the future health of a child and that obesity during childhood increases the risk of adult obesity. This has a clearly measurable impact on physical and mental health, quality of life, and generates considerable direct and indirect costs. Thus, there is a compelling rationale for identifying those infants at greatest risk.
Previous work:
We have developed a risk score algorithm for overweight in childhood based on a predictor model in infants using the Millenium Cohort Study, a large British birth cohort. Stepwise logistic regression was used to determine a predictor model for childhood overweight at 3 years defined by the IOTF. A risk algorithm was developed by assigning integer values to beta-coefficients based on relative strength. Discrimination was analysed using the receiver operating characteristic (ROC) curve.The strongest predictors of overweight risk at 3 years were rapid weight gain during the first year of life, infant birth weight greater than 3.81 kg, maternal pre-pregnancy BMI from 25 kg/m^2 to 30 kg/m^2 and maternal pre-pregnancy BMI >= 30 kg/m^2. The total risk score ranged from a minimum of 0 to a maximum of 33 corresponding to a predicted risk of overweight from 5.1% to 68.8%. The c-statistic from the ROC was 0.70. While the risk algorithm has been proven to have good internal validity, we have yet to test/validate the algorithm on an external cohort.
Aim of current study:
Therefore, the aim of the current study is to determine the validity of the risk algorithm developed from the MCS using the ALSPAC data set.
Methods:
We have a developed risk equations from the MCS that we will apply to the infants in the ALSPAC cohort. We will compare the predictive risk of overweight at 3 years to the observed risk of overweight at 3 years. Discrimination will be assessed using ROC c-statistics (AUC). This will allow us to calibrate the existing risk equations if neccessary.
Key exposure variables:
Child's gender, household income, infant birth birth, infant weight gain the first year of life, maternal pre-pregnancy BMI, maternal smoking in pregnancy, infant breastfeeding status in the first year, formal childcare arrangements in the first year
Outcome variables: Child's weight at 3 years, Child's height at 3 years, Child exact age at follow-up
Final outcome:
Using those three variables, the primary clinical outcome for childhood overweight at 3 years was defined by the International Obesity Task Force sex and age-specific cut-offs corresponding to an adult BMI >= 25 kg/m^2 (Girls: 18.02 kg/m^2; Boys: 18.41 kg/m^2).
Other confounding variables for the investigation and calibration of the risk equations (We have conducted a systematic review which has informed variable selection):
Child's ethnicity, maternal marital status, maternal education, maternal employment, delivery type, maternal age, maternal alcohol consumption, maternal depression, diabetes, breastfeeding duration, formula feeding, age at introduction of solid food, infant temperment, feeding/eating, sleep, activity, SES
B1499 - Efficient estimation of causal treatment effects using genotypic data - 31/01/2013
Aims: We will investigate the optimal methods for combining multiple genetic variants to estimate the causal effects of risk factors on outcomes. This is a methodological investigation, however as an example, we will investigate the associations of height and weight and IQ, behavioural problems (hyperactivity, emotional problems, conduct problems and peer problems) and academic achievement across childhood and adolescence.
Mendelian randomization uses genetic variants as instrumental variables for modifiable risk factors.5 It has been widely applied to investigate the effects of risk factors for disease such as weight, blood pressure, cholesterol, and behavioural risk factors such as alcohol and tobacco consumption on health and socio-economic outcomes.1-4 To be valid instruments, variants must be associated with risk factors of interest, and have no direct effect on the outcome of interest. The stronger the association between the instrument and the exposure, the more statistical power and precision a Mendelian randomization analysis can achieve. One challenge in using genetic instrumental variables is that many variants only have modest effects on the risk factor of interest.6 The use of multiple variants as instruments, thereby explaining more of the variability in the risk factor,7 could therefore increase the precision of the results, improving the likelihood of being able to draw inferences from any given dataset.
Researchers have used various approaches to construct instruments, including allele scores, weighted allele scores, using each genetic variant as an independent instrument, and using generalized method of moment estimators to efficiently weight each of the variants. However, we currently do know the optimal approach for aggregating this information for Mendelian randomization analysis. Thus in this project we will investigate the optimal methods for combining multiple variants to maximise statistical power.
We will examine the effects of anthropometry on cognitive and behavioural outcomes as a motivating example. However our major objective is to develop methodologies rather than investigating any single hypotheses.
Hypotheses: What is the most efficient method for combining multiple variants into a Mendelian randomization analysis?
Exposures: Height, weight and adiposity at age 8-13, genome-wide data.
Outcomes: Academic achievement, IQ score aged 8, measures at age 13 of hyperactivity, emotional problems, conduct problems, and peer problems (from SDQ).
Potential confounding variables or descriptive data: Age, birth weight, number of younger and older siblings, income, parents' education, social class and employment status. Index of multiple deprivation of families' neighbourhood. Mothers' characteristics during pregnancy: age, locus of control, EPDS, CCEI, and teaching score.
B1498 - MSc project Validation of essential fatty acid intakes using FFQ at age 7 with plasma fatty acid measures - 31/01/2013
MSc Project for Nutritions student in School for Policy studies
We have been unable to calculate the intake of essential fatty acids from the FFQ to date due to lack of funding - this is an oportunity to obtain this useful data and partially validate it against blood fatty acid levels at age 7 years.
The student would be provided with a copy of the macro used to calculate the intake of total polyunsaturated fatty acids (PUFA) from the food frequency questionnaire completed by parents for their child age x months (7y FFQ). We would also provide a list of the foods and portion sizes used to calculate total PUFA. The student would search for data on the content of selected fatty acids, particularly Arachadonic acid and Alpha-linoleic acid (the precursors of the omega-6 and omega-3 series respectively) of the foods used. They would record the sources of all data on a spread sheet and complete the macro to enable calculation of each of these new fatty acids.
The calculation of the intake of the fatty acids from ALSPAC participants data would be carried out by Pauline Emmett so that the student would not need access to the ALSPAC dataset. Unlinked summary results would be used by the student to assess possible outliers and for their MSc write-up. The fatty acid intakes thus claculated would be correlated (by Pauline Emmett) with blood measures of these fatty acids to assess the effectiveness of the FFQ to assess these nutrients. Summary unlinked results would be returned to the student. The calculated fatty acid intake for ALSPAC 7 year olds would become available to other users at the end of this project.
B1497 - Facial dysmorphism and maternal alcohol consumption in the ALSPAC cohort - 31/01/2013
Background
Development of the face is dependent on complex interactions of genetic and environmental factors, and is also affected by maternally derived exposures. Alcohol consumption in pregnancy is an important health issue and the DOH currently advise that pregnant women or women trying to conceive should avoid drinking alcohol1.Prenatal alcohol exposure causes a continuum of effectsand is thought to be a leading cause of learning disability in the western world with between 0.2 and 2.0 cases per 1,000 live births. Some of the highest incidence levels have been identified in Eastern Europe, in indigeneous North American communities, and in the South African Cape-Coloured population.The most severe phenotype, fetal alcohol syndrome (FAS), affects face shape, growth and neurobehavior. Fetal alcohol spectrum disorders (FASD) include FAS and other pathologies arising from prenatal alcohol exposure.
The characteristic facial features believed to be due to alcohol ingestion between 10 and 20 wks of gestation include smooth philtrum, thin upper lip vermilion, long upper lip, shortened palpebral aperture width, flattened mid-face and small head circumference. The timing of maternal alcohol consumption is considered to affect the severity of facial dysmorphology and through PH's involvement in the CIFASD consortium (www.CIFASD.com), we recently reported on the link between neurofacial effects and timing of ethanol exposure in a mouse model2. In another CIFASD study, of South African children3, we used face shape to induce classification schemes and tested agreement with clinical FASD categorization: FAS, partial FAS, and HE (heavily alcohol exposed without clinically detectable facial features). The more heterogeneous phenotype of HE forced us to introduce a novel clustering technique, signature graph analysis4, which normalizes face shape and links individuals with similar facial dysmorphism. Signature graph analysis identified half of the HE group as having facial dysmorphism more FAS-like than control-like. These HE individuals performed less well on psychometric tests than HE individuals who facially were more control-like. We also demonstrated that heat map comparisons of, and animated morphs between, individual faces and matched control means revealed facial dysmorphism otherwise overlooked. Thus, visualizations and signature analysis can help pediatricians detect facial dysmorphism across the fetal alcohol spectrum, especially in non-syndromal alcohol exposed cases.
The ALSPAC database provides an opportunity for a much larger-scale investigation of associations between volume and timing of maternal alcohol consumption during pregnancy and facial dysmorphism. In addition, we wish to explore further associations between facial characteristics, cognitive impairment and psychosis
Subjects and data
There are 4747 3D facial scans captured for the 15 year old cohort and these images provide detailed facial morphology at tens of thousands of 3D surface points. The 3D scans have been landmarked and derived facial features recorded. ALSPAC has also collected information on maternal alcohol consumption through questionnaires at 12, 18 and 32 weeks of gestation as well as data regarding the drinking consumption of the parents. In addition, quantity of maternal alcohol intake data is available related to the timing of fetal development: before pregnancy, first trimester of pregnancy, and at around the time the baby was first felt to move. The dataset identified above will need to be extracted and sent to both Peter Hammond and Stephen Richmond.
B1493 - Utilising population-based collections from the UK to identify genetic risk factors for idiopathic scoliosis - 31/01/2013
Aims
We aim to carry out the first population-based genome wide association studies for the presence of scoliosis using white European populations, and to investigate whether similar genetic associations are seen in different ethnic groups. In addition, by utilising resources already available from ALSPAC we will carry out preliminary functional investigations on any identified genetic loci.
To utilise the genetic data already collected to investigate the genetic contributions to scoliosis we will
1. Investigate if the SNP rs11190870 is associated with the presence of scoliosis
2. Perform GWAS in ALSPAC
3. Meta-analysis of GWAS from ALSPAC and Twins-UK
4. Evaluate if identified novel SNPs are likely to have biological relevance bioinformatically and by utilising gene expression, DNA methylation and metabolomic data
5. Continue to develop a model to predict the progression of scoliosis
Methods 1: GWAS
Only those common genotypic variants with a minor allele frequency greater than 5% will be studied. Only SNPs which passed an exact test of Hardy-Weinberg equilibrium are considered for analysis. Association analysis will be performed using logistic regression models based on log additive models, adjusting for age, gender and other appropriate variables. We will assess genome-wide data for associations with scoliosis in ALSPAC alone, setting genome-wide significance at P<=5x10-8.
Methods 2: Power
The power of our GWAS depends on the minor allele frequency of SNPs, the likely size of effect and our cut-off for defining scoliosis. Given the two previous genome-wide studies have found an effect size of 1.56 and 1.85, and the rs11190870 has an allele frequency of 0.437 in ALSPAC, we have reasonable power to detect de novo effects of a comparable magnitude to those previously published.
Methods 3: Meta-analysis
We will perform a meta-analysis of the ALSPAC and Twins-UK GWAS. Prior to meta-analysis, poorly imputed SNPs and those with an allele frequencyless than 5% will be excluded. Inverse variance fixed-effects meta-analyses will be undertaken using METAL. Genomic control corrections will be applied before reporting SNPs which reach genome-wide significance (Pless than 1x10-5) for further investigation.
Methods 4: Replication
We will select signal loci (+/-500mb) with the greatest evidence for association with the risk of scoliosis for replication within data from Japanese and Hong-Kong case-control studies that have GWAS data already available. Population linkage disequilibrium (LD) will be taken into account and where possible used to aid fine mapping. The Chinese Hong Kong disease cohort will then be genotyped for our top 10 SNP hits. Associations between SNPs and scoliosis will then be analysed as described above. We will then repeat the meta-analysis based on all five cohorts.
Methods 5: Bioinformatics
We will use all existing knowledge to analyze our identified SNPs in order to establish its status as a potential functional variant for scoliosis. A bioinformatic approach will be taken to help identify which gene the signal is in, and its likely functional networks. The potential impact of coding variation will be assesed with a series of predictive approaches including SIFT and PolyPhen and we will also followup non-coding functional elements recently annotated by the ENCODE consortium. This will generate prioritised lists of variants for further functional examination in future research projects.
Methods 6: Integrated use of available expression, methylation and metabolomic data
We will examine the impact of our identified SNPs on patterns of protein expression in cell lines, in DNA methylation and through examination of detailed banks of metabolomic data. Along with a sub-set of ALSPAC and Twins-UK samples with transformed multi-tissue specific expression data, the BBSRC-funded ARIES study provides an opportunity to examine the likely effect of our identified SNPs on methylation, as a potential mechanism of gene-environment interaction. This will allow us to extend our primary goal and to begin to unpick the contributing nature of genetic loci to scoliosis risk in a unique study environment.
Exposure variables
Common genotypic variants genotyped using the Illumina HumanHap550 platform.
Outcome variable
Scoliosis (yes/no as a binary variable) identified by the DSM at aged 9 and 15, will be defined as those with a curve >=10degrees, as this has substantial repeatability (Kappa of 0.74). Sensitivity analyses will be carried out using a lower cut-off of >=6degrees to define scoliosis, as the DSM underestimates curve size by approximately 40%, although this lower cut-off has only moderate repeatability (Kappa of 0.56). In addition, we will explore the use of angle size as a continuous variable.
Confounding and other variables
Age and gender
Gene expression data
DNA methylation data
Metabolomic data
B1492 - Explaining risk for suicidal behaviour in adolescent offspring of depressed parents - 31/01/2013
AIMS
(1) Examine in detail the longitudinal association between maternal and paternal depression and the course of offspring suicidal behaviour.
(2) Assess the extent to which prior child psychopathology accounts for excess risk of suicidal behaviour in offspring of depressed parents relative to offspring of non-depressed parents.
(3) Assess the extent to which other hypothesised mediating mechanisms (such as family factors, peer problems and other child factors) account for excess risk of suicidal behaviour in offspring of depressed parents and to examine how these factors interact with child psychopathology.
(4) Where possible, use repeated measures to test the direction of effects for identified mediating mechanisms and adolescent suicidality.
B1490 - Educational attainment and BMI bidrectional assessment of causal relationships using Mendelian randomisation - 17/01/2013
he aim of this miniproject is to look for relationships between educational attainment and BMI and assess causality between them using Mendelian randomisation. This will involve:
- Generating educational attainment (EA) scores derived from genotypic associations with EA from an independent study (carried out as part of the Social Science Genetics Association Consortium) and genotypic dosage information within ALSPAC data.
- Assessing the performance of a series of genotype based scores of EA in terms of their predictive ability for KS3 SATS results (and IQ) and their performance as potential instruments for EA within Mendelian randomisation frameworks.
- Undertaking both observational assessment and Mendelian randomisation analysis of relationships between EA and child BMI.
- Generating similar genetic scores for BMI (initially derived from the 32 most predictive loci taken from Speliotes et al, 2010) and undertake the same analyses as above, but in a bidirectional manner.
In order to perform these analyses, we will require access to ALSPAC genetic (I already have access via the alspac-shared directory on BlueCrystal) data and a series of key phenotypes outlined in the table earlier in this form.
Reference:
Speliotes et al (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nature Genetics. 42 (11). pp. 937-948.
B1489 - Associations between primary care measures and psychosis-like symptoms in the ALSPAC birth cohort - 17/01/2013
Aim:
The aim of this research is to identify if associations are present between PLIKS, recorded within ALSPAC, and primary health care measures, taken from GPRD.
B1488 - Maternal alcohol use during pregnancy and offspring growth trajectories - 17/01/2013
Maternal alcohol drinking during pregnancy and offspring trajectories of height, weight and head circumference
In Denmark, United Kingdom, Australia and Ireland it has been estimated that between 37% and 81% of fetuses are exposed to alcohol in pregnancy (1-5). While the hazards of heavy alcohol consumption in pregnancy on birth outcomes including preterm birth and birth weight are well recognized, the effects of moderate-low levels of alcohol drinking in pregnancy are less clear both at birth and in particular longitudinally. The association between alcohol use during pregnancy and postnatal growth throughout childhood is not well established. Studies which focus on postnatal growth are a priority (6, 7) if consensus on safe alcohol recommendations for pregnant women is to be reached.
Aim : To investigate whether different patterns of alcohol use during pregnancy adversely affect height, weight and head circumference between birth and 10 years
Objective #1 Recent work conducted using the ALSPAC data investigated maternal smoking during pregnancy and offspring trajectories of height and adiposity up to age 10 (8). We propose to replicate the approach taken in this analysis in an investigation of the associations between different levels of alcohol consumption during pregnancy and height, weight and head circumference trajectories between birth and age 10 years.
Briefly, we will estimate the association between maternal drinking during pregnancy (any versus none and by dose) and trajectories of height, weight and head circumference that have previously been developed using multilevel models by Laura Howe and Andrew Smith. In keeping with Lewis and colleagues' recent categorisation of alcohol use in pregnancy (9) moderate alcohol consumption will be defined as equal to 1-6 drinks on average per week during pregnancy, heavy consumption will be defined as consumption of greater than 6 drinks per day and binge drinkers will be classified as women who report consuming more than 4 units of alcohol at 18 and 32 weeks of pregnancy. This classification will be examined with reference to the growth trajectories of women who abstained from alcohol during pregnancy.
Covariates adjusted for will include maternal age, ethnicity, maternal education, household occupational class, parity, maternal height, paternal height, maternal BMI, smoking during pregnancy, and other key variables. We will also consider drug use as a potential confounder, but this has a very low prevalence, so we will investigate whether or not it is possible/appropriate to include in analyses.
Objective #2 Residual confounding is often a significant limitation in studies of fetal alcohol exposure and infant outcomes. The relationship between alcohol use during pregnancy and growth outcomes at birth could be confounded by shared familial characteristics as has been suggested for the relationship between smoking during pregnancy and growth (8). For this part of the analysis, we will compare the associations of maternal alcohol consumption during pregnancy to the woman's partners in order to explore the presence of unmeasured confounders. This will allow us to estimate the extent to which any associations detected are likely to be the result of unmeasured genetic, socioeconomic or behavioural confounders.
Partner alcohol consumption was collected in a questionnaire sent to them at 18 weeks gestation. Partner alcohol consumption will be classified as moderate, heavy and/or binge in line with UK recommendations of no more than 21 units per week and no more than 4 units in one occasion. We will run the analysis specified in objective #1 both with mutual adjustment for partner alcohol consumption and for partner consumption alone adjusting for covariates already specified.
As a further tool for the assessment of potential unmeasured confounding, we will compare the growth trajectories of children whose mothers drink alcohol during pregnancy with those who do not drink during pregnancy but resume alcohol consumption shortly after delivery.
References
1. Colvin L, Payne J, Parsons D, Kurinczuk JJ, Bower C. Alcohol consumption during pregnancy in nonindigenous west Australian women. Alcoholism: Clinical and Experimental Research. 2007;31(2):276-84.
2. Kelly Y, Sacker A, Gray R, Kelly J, Wolke D, Quigley MA. Light drinking in pregnancy, a risk for behavioural problems and cognitive deficits at 3 years of age? International Journal of Epidemiology. 2009;38(1):129-40.
3. Bakker R, Pluimgraaff LE, Steegers EAP, Raat H, Tiemeier H, Hofman A, et al. Associations of light and moderate maternal alcohol consumption with fetal growth characteristics in different periods of pregnancy: The Generation R Study. International Journal of Epidemiology. 2010;39(3):777-89.
4. Andersen AMN, Andersen PK, Olsen J, Gronbaek M, Strandberg-Larsen K. Moderate alcohol intake during pregnancy and risk of fetal death. International Journal of Epidemiology. 2012.
5. Mullally A, Cleary BJ, Barry J, Fahey TP, Murphy DJ. Prevalence, predictors and perinatal outcomes of peri-conceptional alcohol exposure - retrospective cohort study in an urban obstetric population in Ireland. BMC Pregnancy and Childbirth. 2011;11.
6. Patra J, Bakker R, Irving H, Jaddoe V, Malini S, Rehm J. Dose-response relationship between alcohol consumption before and during pregnancy and the risks of low birthweight, preterm birth and small for gestational age (SGA)-a systematic review and meta?analyses. BJOG: An International Journal of Obstetrics & Gynaecology.
7. Henderson J, Gray R, Brocklehurst P. Systematic review of effects of low-moderate prenatal alcohol exposure on pregnancy outcome. BJOG: An International Journal of Obstetrics & Gynaecology. 2007;114(3):243-52.
8. Howe LD, Matijasevich A, Tilling K, Brion MJ, Leary SD, Smith GD, et al. Maternal smoking during pregnancy and offspring trajectories of height and adiposity: comparing maternal and paternal associations. International journal of epidemiology. 2012;41(3):722-32.
9. Lewis SJ, Zuccolo L, Smith GD, Macleod J, Rodriguez S, Draper ES, et al. Fetal Alcohol Exposure and IQ at Age 8: Evidence from a Population-Based Birth-Cohort Study. PloS one. 2012;7(11):e49407.
B1487 - BRAINEAT - 17/01/2013
There is a bidirectional relationship between the brain and nutrition. The brain influences our food
choices and, therefore, the amount of macro- and micro-nutrients entering our bodies. These nutrients
affect body composition and a variety of metabolic processes that, in turn, influence brain function and
structure. Understanding the various elements of this brain-body loop is one of the overarching goals of
the proposed research, both in terms of gaining new knowledge about the underlying processes and
applying it to enhance population health.
We will take advantage of several community-based cohorts including ALSPAC to investigate bidirectional
brain-body relationships in the context of food choices; magnetic resonance images (MRIs) of
the brain and, in most cases, of abdominal fat have been collected in these cohorts together with a wealth
of other relevant information (e.g., food recall interviews) and blood samples suitable for genetic and
metabolomics analyses.
1. Cohorts
Given the high cost of acquiring large samples with imaging-based, systems-level phenotypes, we have
brought together several cohorts in which MRI of the brain and body have been already accomplished or
funded (~8,000 participants). Three of these samples are birth cohorts (ALSPAC, Generation R, and
NFBC86), thus allowing us to use all of the longitudinal data collected so far. In addition, we will be able
to incorporate the (Canadian) Saguenay Family Study, which is unique with regards to its twogenerational
design (adolescents and their middle-aged parents) and the detailed cardiovascular and
metabolic phenotyping available in all participants (15 hours of assessments).
Using these datasets, we will ask: (1) how do inter-individual differences in the structural (and functional)
properties of the relevant neural circuits relate to food choices, such as fat or carbohydrate intake; and (2)
how do inter-individual differences in body composition (visceral fat from MRI and/or body composition
from bioimpedance) influence metabolic profiles (as determined by metabolomics) and, in turn, brain
structure and function.
2. Magnetic resonance imaging
All cohorts acquired T1-weighted images of the brain, which are well suited for the quantification of a
number of grey-matter properties (see below). Furthermore, all cohorts used MR sequences (Diffusion
Tensor Images [DTI] and/or Magnetization Transfer Images [MTI]) suitable for quantifying various
properties of white matter. Three of the cohorts (Generation-R, NFBC86, and the parent arm of the SFS)
have acquired resting-state functional MRI (fMRIrs), and one of the cohorts (ALSPAC) has acquired a
paradigm-based fMRI (viewing faces; Grosbras and Paus 2006).
Using this rich dataset, we plan to use image-processing pipelines developed and implemented at two of
the sites (Erasmus University and University of Toronto) to process these images in order to generate
quantitative phenotypes suitable for answering both questions, namely from the brain to food choices and
from metabolic profiles (and body composition) to the brain. These brain MR phenotypes include:
MRI sequence Structure and physiology
T1-weighted Volumes, thickness, folding, shape, tissue density
Diffusion tensor imaging Fractional anisotropy, mean diffusivity, track delineation
Magnetization transfer Myelination index
Resting state functional Spontaneous cerebral networks; functional connectivity
Paradigm-based functional Brain response associated with specific stimuli/tasks; functional
connectivity.