Proposal summaries
B2106 - Predicting oral language development to middle childhood and its implications for later achievement and wellbeing - 07/11/2013
Aim
To evaluate the potential of early life biological, parental and socio-demographic factors to predict natural language skills, and the extent to which these skills have an impact on school outcomes in (late) adolescence.
B2105 - Does eye colour change between 3 months and 5 years of age - 07/11/2013
Perceived eye, or iris colour varies as a continuous from blue to brown/black and is determined by the melanin pigment, quantity, packaging and type produced in the melanocytes of the anterior border layer and stroma of the iris. Brown eye colour is the result of abundant melanin pigment content and a higher ratio of pheomelanin to eumelanin. The number of melanocytes is not a determining factor. Blue eye colour results from the scattering of most blue wavelengths to the surface by collagen fibrils, in the presence of minimal melanin pigment. (1)
Once thought to be an example of simple Mendelian inheritance where brown colour was dominant and blue colour recessive, iris colour is now known to be a polygenic phenotypic characteristic with a myriad of possible combinations of parent and child eye colours. For example, two blue-eyed parents may produce a brown, green-hazel, or blue-eyed child. (1)
It is accepted that infant eye colour at birth does not necessarily correlate with resultant childhood and indeed adult eye colour, although it is found to be roughly stable by six years of age. (2) There is much anecdotal evidence of eye colour changing from one extreme of the spectrum to other in the first year of life. One study investigated this, finding a decrease in the number of light irises. (3) Congenital conditions affecting iris colour include albinism, in which the iris may be red or violet and heterochromia in which the two irises are different colours. (4)
The main contributory genes for iris colour are HERC2 (hect domain and RCC1-like domain-containing protein 2) and OCA2 (oculocutaneous albinism II) on chromosome 15, which account for around 74% of variation. Depression of OCA2 transcription results in a blue-eyed individual. A further 14 genes have been identified as contributing, however many of these play a greater role in determining skin and hair colour. Given the complex inheritance model of eye colour it is therefore difficult to predict final outcome based on the eye colour of the parents alone. (1, 4)
Many parents in the neonatal unit, ophthalmology and paediatric clinics enquire about changes in their child's eye colour, however literature is limited on the topic and the timing and nature of the change in eye colour in healthy neonates and young children is not well described.
ALSPAC is a vital resource in the study of child development and has contributed to much influential work on the topic of child development and paediatric disease. Simple data were collected regarding iris colour at various stages in the first 2 years of life and later at age 5. To our knowledge, this data has not been analysed to look at change in eye colour over time.
Understanding the nature of eye colour change in young children will broaden the knowledge base of both clinicians and patients or relatives and may aid in the understanding of iris development, which is important as it appears to be closely linked with brain development. (1) To date eye colour has not been found to be associated with visual acuity, but has been linked with reaction time, shyness, noise-induced hearing loss and ability to overcome seasonal affective disorder. (4) The individual iris is so unique in terms of colour, pattern and features that it can be reliably used in identification in place of a passport. (5)
The study team would be interested to investigate whether there was a change in iris colour between the age of 3 months and 5 years; at what point these changes occur and what form these changes take.
The study team are experienced in working with ALSPAC data and have paediatric ophthalmological clinical experience. Dr Creavin is an academic ophthalmology trainee whose research interest is ophthalmic epidemiology.
References
1. Sturm RA & Larsson M. Genetics of human iris colour and patterns. Pigment Cell Melanoma Res. 22;544-62
2. Bito LZ, Matheny A, Cruickshanks KJ, Nondahl DM, Carino OB. Eye color changes past early childhood: The Louisville Twin Study. Arch Ophthalmol 1997;115:659-63
3. Matheny AP and Brown Dolan A. Changes in eye colour during early childhood: sex and genetic differences. Annals of Human Biology 1975;2(2):191-6
4. White D and Rabago-Smith M. Genotype-phenotype associations and human eye color. Journal of Human Genetics 2011;56:5-7
5.Dougman J. Probing the uniqueness and randomness of IrisCodes: results from 200 billion iris pari comparisons. Proc. IEEE 2006;94:1927-35
B2103 - Communication difficulties peer victimization and mental health - 31/10/2013
AIMS
The main aim of the study is to explore the relationships among speech, language and communication needs, peer victimisation during childhood and adolescence, and mental health across the lifespan. The research questions are:
* Are levels of reported peer victimization across different SLCN groups (such as stuttering, other speech difficulties, and developmental language difficulties) significantly greater than for cohort members without such needs? Where possible we will take into account data from cohort members with non-SLCN disabilities.
* How do measures of mental health and emotional well-being in these groups compare across the lifespan?
* To what extent does peer victimization contributes to mental health in these groups across the lifespan?
* Does SLCN remain a risk when other factors are controlled for?
* Have levels of reported peer victimization in SLCN groups changed in response to initiatives to tackle bullying?
A further aim of the study is to develop a framework for future collaborative work involving the co-applicants and in the longer term other birth cohort researchers in the international academic community.
We plan to use data from the National Child Development Study and the Millenium Cohort Study as well as ALSPAC, because we wish to explore the impact of SLCN across the lifespan. However, ALSPAC offers the richest source of information in many respects. First, parental report of stuttering and developmental speech difficulties is verified by a trained researcher, which is not the case for any other British birth cohort study to date; second, parents, teachers and the cohort members themselves provide report of peer victimization; third, it provides a wide range of mental health measures.
Mental health and peer victimisation will both be considered as outcomes in different models. We will consider a variety of models as appropriate for the different outcome variables, including different types of multivariable regression such as binary and multinomial logistic regression and hierarchical linear regression. We would also conduct path analysis to examine direct pathways between SLCN and mental health, as well as indirect pathways via peer victimization over and above the effects of individual and socio-demographic factors and life events.
HYPOTHESES
Based on prior research, we hypothesise that cohort members with SLCN will be more likely to experience bullying and mental health problems than controls without these conditions. As suggested above, we expect that we will find direct pathways between SLCN and mental health, as well as indirect pathways via peer victimization, over and above the effects of individual and socio-demographic factors and life events.
B2102 - Novel Methods to Study Diet andObesity Compared to Genetics and Other Lifestyle Factors Agent-Based Modelling - 31/10/2013
Our specific aims are:
1. Derive empirical lifestyle patterns using cluster and/or factor analysis in a cohort of British
children.
2. Develop a mathematical model to simulate the association between derived dietary patterns and
other lifestyle factors (breakfast consumption, family dinner, breastfeeding history) and demographic
covariates (age, sex, socioeconomic status) with body fat using agent-based modeling (ABM).
3. Test the model using data collected from children aged 10 to 13 years over 4 time points (2004,
2006, 2008) to determine which variables are most strongly associated with changes in body fat over time
as children transition into adolescence.
4. Examine whether and how associations between dietary patterns, lifestyle factors, and obesity
shift when genetic data are included in the model (subset analysis*).
5. Reproduce aims 1 through 3 in a large prospective cohort of American children aged 10 to 13 y.
B2101 - Shared genetic determination of refractive error with age and ethnicity - 31/10/2013
Aims: To assess the genetic correlation between refractive error in (a) European vs. East Asian adults, (b) European children vs. European adults, and (c) European children vs. East Asian adults.
Hypothesis: The above genetic correlations are high (i.e. greater than 0.5), which implies that the higher prevalence of myopia in East Asians compared to Europeans is not simply genetic in origin.
Variables: Refractive error will be based on autorefractor measurement. Within each of the 3 subject cohorts, refractive error will be rank-transformed to a give a Normal Score, using Blom's method. (Our ultimate aim is to compare the refractive error of individuals of different ethnicity/age after accounting for absolute differences due to the environment in which they grew up. Also, heritability analysis is not robust against departures from normal trait distributions).
Analysis method: The degree of genetic relatedness between all pairs of individuals in 2 cohorts combined will be calculated using the GCTA program (for the 3 sets of 2 cohorts listed as a, b and c in the Aims above). Bivariate variance components analysis will be carried out using GCTA, as described [4].
Preliminary work: We have used bivariate GCTA in ALSPAC YPs to show that the shared SNP-heritability across childhood is high (greater than 0.7) (unpublished results). Too few ALSPAC mothers have refractive error information for estimation of its SNP-heritability (unpublished results).
Precautions to ensure the identity of participants cannot be revealed: Under certain circumstances, access to high-density genotype data is sufficient to reveal the identity (e.g. surname) of an individual [5]. We propose the following scheme to make such identification impossible (given current knowledge):
a) Create a list of the SNPs present on the genotyping platform used for each of the 3 cohorts (ALSPAC, Rotterdam, Nagahama).
b) Identify SNPs genotyped in all 3 cohorts. Sort the list by chromosome, then by genomic position.
c) From the list generated in step (b) randomly delete 5% of SNPs.
d) From the list generated in step (c) randomly re-order the SNPs within chromosomes (i.e. shuffle the order of SNPs on chromosome 1, then shuffle the order of SNPs on chromosome 2, etc.).
e). Send the list generated in step (d) to each site (ALSPAC, Rotterdam, Nagahama).
f) At each site, an analyst links refractive error and genotype data. The order of subjects in the data file is then randomised, and the unique subject identifier (e.g. "ALN") is replaced with a new identifier based on file order, e.g. ALSPAC1, ALSPAC2, ALSPAC3, ... ALSPAC9999.
g) For the data file generated in step (f), the analyst at each site sorts the order of SNPs so that it matches the order of SNPs in the circulated list (e). SNPs missing from the list are deleted.
g) For the data file generated in step (g), the analyst at each site replaces the SNP name with a new name based on chromosome and file order, e.g. chr1snp1, chr1snp2, chr1,snp3, ...chr22snp3455.
h) The analyst at each site sends the file generated in step (g) to a central site for GCTA analysis.
NB. Without knowing the order of SNPs in the circulated list (e), the order of SNPs in the data files (h) is unknown, and thus cannot be used to infer identity....yet it can be used to calculate relatedness of subjects whose SNPs are sorted in the same order.
References
1. Pan CW, Ramamurthy D, Saw SM (2012) Worldwide prevalence and risk factors for myopia. Ophthalmic and Physiological Optics 32: 3-16.
2. Morgan IG, Ohno-Matsui K, Saw SM (2012) Myopia. Lancet 379: 1739-1748.
3. Verhoeven VJM, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, et al. (2013) Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nature Genetics 45: 314-318.
4. de Candia Teresa R, Lee SH, Yang J, Browning Brian L, Gejman Pablo V, et al. (2013) Additive genetic variation in schizophrenia risk is shared by populations of African and European descent. American Journal of Human Genetics 93: 463-470.
5. Gymrek M, McGuire AL, Golan D, Halperin E, Erlich Y (2013) Identifying personal genomes by surname inference. Science 339: 321-324.
B2100 - Longitudinal genome-wide association study GWAS for refractive error - 31/10/2013
Overview.
We will request funding to employ a post-doctoral RA to carry out these analyses. The RA will be based at the PI's institution (Hong Kong Polytechnic University) and supervised by the PI and co-I's.
We seek approval from the ALSPAC Executive Committee to run the proposed analyses on the blue crystal computing cluster. The analyses are very computationally intensive (fitting a mixed model for each of millions of SNPs). We will include in the grant any funds specified by the Executive Committee required to cover this computing time as well as other appropriate costs incurred by ALSPAC. (NB. The longitudinal GWAS for BMI, which examined ~3 million SNPs, required approximately 8648 days of computing time to complete).
Aim.
To identify genetic variants influencing refractive error trajectory (either in the general population or in subjects classified as spending a high/low amount of time reading or outdoors).
Methods.
The refractive error and genotyping data has already undergone QC filtering for use in a closely related project that has received Exec approval: B1352 'CREAM (Consortium for Refractive Error and Myopia) 1000-genomes meta-analysis'.
Preliminary analysis of refractive error trajectories using linear mixed models are very promising (for example, as part of the above amendment work, we have been able to identify known myopia SNPs that (a) act early in childhood and retain stable effects during childhood, (b) exert a progressively increasing effect during childhood, and (c) interact with time spent outdoors or time spent reading.
However, fitting the model for each SNP currently takes ~1 minute. We propose to test simplified models and examine the robustness of fixed effects estimates, in order to minimse the time required to fit each model. Once optimised, we will conduct three longitudinal GWAS analyses for three models:
Model 1. Test for SNP main effects and 'SNP x age' interaction.
Model 2. As model 1, plus a test for 'SNP x nearwork' interaction.
Model 3. As model 1, plus a test for 'SNP x time outdoors' interaction.
We will aim to examine the ~4.5 million very high confidence imputed (quality metric RSQR greater than 0.8) very common variants (minor allele frequency, MAF >=0.1) SNPs in the 1000G-imputed dataset.
B2099 - Associations of hypertensive disorders of pregnancy with adolescent offspring cardiac function and structure - 31/10/2013
AIMS
* To investigate the associations between exposure to HDP and blood pressure trajectories during pregnancy with offspring cardiac structure and function.
HYPOTHESIS
We hypothesize that the cardiac function and left ventricular geometry in adolescents exposed to HDP is less favorable compared to offspring of normotensive mothers.
METHODS
We will use data from ALSPAC to investigate the association between preeclampsia and offspring cardiac structure and function. Of the 5,217 adolescent children investigated, 2,000 conceded to echocardiography.
The echocardiograph examination
Echocardiography was performed using a HDI 5000 ultrasound machine (Phillips) equipped with a P4-2 Phased Array ultrasound transducer using a standard examination protocol. All measurements were made according to American Society of Echocardiography (ASE) guidelines.
Definition of exposure variables
* Being born to a mother with preeclampsia or GH.
* Blood pressure trajectories during pregnancy
Confounding/mediating variables (available data)
Sex of offspring, birth weight, length of pregnancy, the adolescent's own blood pressure, maternal pre pregnancy blood pressure, maternal pre pregnancy BMI, maternal and offspring smoking and physical activity, age and parity of mother, height in adolescence, weight/fat mass in adolescence, occupational social class, maternal diabetes in pregnancy.
Outcome variables
Cardiac structure
* Left ventricular size indexed to height (LVMI)
* Left ventricular geometry (based on LVMI and left ventricular relative wall thickness)
Cardiac function
* Left ventricular systolic function (Ejection fraction etc.)
* Left ventricular diastolic function (E/A, E'/A')
Statistical analyses
All statistical modeling will be made in SAS (SAS Institute inc., Cary, NC, USA). We will use multivariate linear models to estimate the associations and adjust for potential confounders and mediators. A previous study based on the follow-up clinic at 17 years reported the prevalence of exposure to preeclampsia and GH in utero to be 2% and 15%, respectively.5 Assuming a similar prevalence in the subgroup examined by echocardiography, this would result in 40 study participants having been exposed to preeclampsia and 300 having been exposed to GH.
B2098 - Genome-wide analysis of association between genotype and methylation - 24/10/2013
Outline
DNA methylation data has recently been generated from ALSPAC samples at multiple timepoints using the Illumina HM450k DNA methylation array. Comprehensive genotype data also exists for the same samples. This project will integrate these two large-scale datasets to investigate the role of genetic variation in DNA methylation.
Aims
1. Genome-wide association analysis of methylation in children and mothers to identify both cis and trans associations between genetic variants and methylation
2. Analysis of change in genotype/methylation associations through the lifecourse
3. Comparison of genotype/methylation associations to published genotype/phenotype and genotype/outcome associations
4. Comparison of genotype/methylation associations to genotype/expression associations (published and within ALSPAC)
5. Comparison of genotype/methylation assocations to ENCODE regulatory regions
6. Analysis of proportion of methylation variance that is influenced by genotype (cis/trans) and non-genetic factors.
9. Single point genotype-stage interaction analysis
10. Genetic and non-genetic correlation over space and developmental stages.
B2096 - Relationship between nicotine metabolism rate as determined by CYP2A6 genotype and smoking patterns in adolescence - 24/10/2013
Aims:
1. Examine patterns of cigarette use across ages 13 to 21 years and identify sources of heterogeneity in smoking phenotypes
2. Identify relationships between CYP2A6 nicotine metabolism group and smoking patterns across ages 13 to 21 years
3. Compare the relative influence of CYP2A6 nicotine metabolism group on smoking initiation vs. smoking escalation across ages 13 to 21 years
Hypotheses:
Relative to normal CYP2A6 metabolizers, reduced CYP2A6 metabolizers will:
1. Escalate cigarette consumption faster in earlier adolescence
2. Escalate cigarette consumption slower in later adolescence/young adulthood
3. Have higher levels of cigarette consumption at earlier stages in adolescence
4. Have lower levels of cigarette consumption at later stages in adolescence/young adulthood
We also predict that there will be no association between CYP2A6 metabolism group and smoking initiation.
B2095 - Sex specific differences in the placental syndrome and markers of placentation - 24/10/2013
AIMS
We aim to
1) Investigate sex-specific differences in the occurrence of early onset and late onset pre-eclampsia, SGA and preterm birth
Where studies currently have relevant data and/or in the future we also plan to add to this aim with the following two aims. However, this request is currently ONLY for aim 1 above.
2) Explore sex-specific differences in markers of placentation in maternal blood
3) Undertake (epi)genetic studies assessing methylation / imprinting differences.
B2093 - Gender nonconformity sexual orientation and distress - 24/10/2013
The present study aims to address these previous research gaps and limitations by examining associations between prospective measures of childhood gender non-conformity and subsequent negative social interactions, poorer self-image, and distress. A wider range of forms of negative interpersonal reactions and types of distress will be examined than in previous studies.
B2097 - Analysis of correlation patterns in DNA methylation through the lifecourse - 23/10/2013
Outline
DNA methylation data has recently been generated from ALSPAC samples at multiple timepoints using the Illumina HM450k DNA methylation array. Genome-wide correlation analysis is now possible to (a) identify potential coregulation and (b) to inform dimension reduction strategies to data analysis. It is also possible to explore the correlation between timepoints to determine which CpG sites in the genome are functionally stable, and which change over time.
Aims
1. Windowed analysis across the genome to generate "methylation correlation maps" at all time-points
2. Genome-wide analysis of correlation between variable loci to identify networks of genes that appear to be coregulated
3. Analysis of correlation of methylation between timepoints at each site in the HM450k to identify stable and labile CpGs.
B2091 - An investigation into the confounding associated with genome-wide score and methods to minimise its impact - 10/10/2013
AIM
We plan to investigate the reasons for confounding of the genome-wide genetic BMI score and its extent using in ALSPAC and examine various means to minimise its impact any subsequent analysis.
Hypothesis
In an ongoing study of ALSPAC participants (Deanfield London Study) our recruitment is based on extremes of BMI percentages as determined by BMI associated common genetic variants. We used a genome-wide score that enabled us to reach a difference of 3 BMI units between the top and bottom percentages of BMI categories.
Preliminary data analysis on 200 subjects in the current study suggests that while the genetic score has as expected separated the population into two distinct BMI categories with mean difference of 3 BMI unit difference. However, the score itself is not totally unconfounded from environmental factors as was predicted at the start. This is likely is due to the use of a genome-wide score, instead of using a score from a limited set of strongly associated SNPs, that appears to have re-introduced confounding to some extent, although the reason behind these unexpected properties is unclear.
Methods
We will to explore this confounding and aim to answer the following questions.
a) What is the extent of the confounding of the genetic score i.e. what are the main confounders?
b) What is the main driver of this confounding: Genuine or horizontal pleiotropy? Vertical pleiotropy with SNPs acting on intermediate pathways to BMI or population stratification?
c) Can this confounding be controlled by adjusting for the main confounders?
d) Is this confounding less than what is expected by generation of groups by BMI alone? If yes, by how much?
e) In light of the above what are the limitations of our selected groups with differential BMI for the purpose of using them to study the main programme question i.e. adiposity-cardiovascular disease associations.
To answer the above questions we would require extensive data on confounders, the genetic score groups, obesity profiles and cardiovascular risk factors. In brief the following analysis will be performed.
Using standard regression model we shall investigate if the BMI genetic score is associated with an extensive list of confounders. We shall use adjustment methods for various confounders to investigate the the drivers of confounding and if their effect can be minimized. Intermediate pathway confounders will be exploited to investigate the presence or absence of vertical plieotropy.
Employing PCA (principle component analysis) we shall also investigate if there is a structure in the SNP sets used in the score and can PCA adjustment remove the confounding effect.
Using regression modelling we shall quantify extent confounding using conventional BMI and compare and contrast with the ones revealed from the genetic score analysis.
Using dummy data which shall be used to study the main questions from the ongoing study (Deanfield London Study) i.e. visceral adiposity-cardiovascular disease markers association, this way we can inquire into any limitation of adjustment for these confounding on any subsequent analysis on the real data when its available after study completion.
B2090 - Statistical methods to improve clinical interpreation of physiological data from real-time monitoring devices - 03/10/2013
The aim of this project is to develop the analysis of complex, high-dimensional, functional data collected from research into sleep, glucose and cardiometabolism. The identification of zeitgebers in sleep/activity, light and temperature, and their prediction of patterns in glucose and melatonin, will be explored. Ambulatory blood pressure is measured using personally-worn devices.
The outcome is blood pressure measured over time and the exposures of interest are age and sex, with adjustment for the usual confounders.
These types of data are becoming more widespread as the technology develops for personal measures of real-time events. The overarching characteristic is that they produce patterns over time. A recent review (Ullah & Finch, 2013) concluded that there is a lack of appreciation of the value of FDA for biomedical problems.
The aim of the proposed project is to develop clinically relevant statistical techniques for analysing real time complex data made available through recent advances in ambulatory physiological monitoring systems, and thereby establish:
1. the strengths and weaknesses of each statistical and methodological technique for generating comprehensive and holistic analyses of real time complex data series;
2. the extent to which these statistical techniques might offer more sophisticated interpretations of real time physiological data recorded from free-living patients, and thereby improve the clinical acuity of aetiological, diagnostic and prognostic investigations; and
3. the most appropriate format(s) in which such techniques might be made available for non-specialist biomedical technicians and clinicians to optimise the impact of these techniques on aetiological, diagnostic, prognostic and therapeutic decision-making.
A dedicated Work Package for each of these three objectives will involve an assessment of empirical evidence drawn from:
Work Package 1. continuously recorded measurements of interstitial glucose concentration, activity, ambient temperature and light from free living pregnant women with gestational diabetes in order to identify any occult glycaemic abnormalities capable of predicting macrosomia and/or abnormal neonatal glycaemic control - data that will support a robust comparison of the different analytical techniques examined;
Work Package 2. clinically relevant real time physiological data series provided by project partners from the commercial (industrial) and public (healthcare) sectors using recent advances in ambulatory monitoring systems for: body temperature; ECG, EMG and EEG; respiration; blood pressure; heart rate; and blood oxygenation - data that will allow the team to assess the generalisable utility of the analytical techniques developed in WorkPackage 1; and developmental workshops with commercial and public sector partners where mechanisms and associated tools for supporting the uptake, application and integration of the analytical techniques developed and tested in Work Packages 1 and 2 will be designed and implemented - data that will ensure that any advanced statistical techniques become available in a format that is accessible and useful to non-specialist biomedical technicians and clinicians.
B2089 - Prenatal lead exposure gene polymorphisms and child temperament - 26/09/2013
We propose to test three specific hypotheses for children experiencing a range of low-to-moderate prenatal BLL concentrations:
1)Higher BLLs will be associated with higher parent ratings of the child on negative temperamental attributes (grizzly, fretful, stubborn, demanding, unresponsive, active) and lower ratings on positive attributes (happy, alert, cuddly, sociable) at 4 weeks of age when the infants also have polymorphisms previously related to negative emotionality or heightened behavioral reactivity.
2)Higher BLLs will be associated with higher parent ratings of activity, approach, intensity, and distractibility at 6 and 24 months among children who also have polymorphisims previously shown to be related to negative emotionality or heightened behavioral reactivity.Higher BLls will be associated with lower scores on rhythmicity, adaptability, mood, persistence and threshold in the presence of the same gene polymorphisms.
3)Higher BLLs will not be associated with negative temperament traits at 6 and 24 months among children who have gene polymorphisms previously shown to be related to altruism or self-regulation.
In addition to gene-environment interactions, we will test for interactions between maternal hemoglobin and lead levels on the same outcomes to understand if maternal nutritional status acts as a protective or susceptibility factor for the assocation between lead exposure and temperament.
B2088 - Metabolomic and Epigenomic Mechanisms in Developmental Overnutrition - 26/09/2013
AIMS
Our overarching aim is to determine the role of metabolomic and epigenomic mechanisms in the relationships between maternal risk factors for developmental overnutrition and offspring adiposity and related metabolic outcomes. We will also determine the effects of these intrauterine mechanisms on greater adiposity and associated metabolic risk into the next generation. Three related aims with specific objectives are detailed below and illustrated in figure 1 of the research strategy.
Aim 1: To determine the role of metabolomic mechanisms in developmental overnutrition, by identifying:
1.1: The associations of established maternal developmental overnutrition risk factors (adiposity in early pregnancy, gestational adipose gain, gestational diabetes (GDM) and continuous measures of fasting and postload glucose and fasting insulin) with maternal pregnancy metabolome, quantified in serum by nuclear magnetic resonance (NMR) spectroscopy.
1.2: The associations of established maternal developmental overnutrition risk factors and pregnancy metabolome with fetal metabolome, quantified in cord serum by NMR spectroscopy.
1.3: The associations of maternal pregnancy and fetal metabolome with offspring adiposity (BMI, waist, skinfolds, fat mass) from birth through to early adulthood, and with metabolic outcomes (fasting glucose, insulin and lipids from mid-childhood to early adulthood; metabolome in infancy and in adolescence).
1.4: The extent to which maternal pregnancy and/or fetal metabolome mediate the associations of established developmental overnutrition risk factors with offspring adiposity and metabolic outcomes.
Aim 2: To determine the role of epigenetic mechanisms in developmental overnutrition, by identifying:
2.1: The associations of established developmental overnutrition risk factors with fetal genome-wide DNA methylation, analysed on cord blood white cell DNA, with the Illumina 450K HumanMethylation array.
2.2: The associations of pregnancy and fetal metabolome with cord blood white cell DNA methylation.
2.3: The associations of cord blood white cell DNA methylation with offspring adiposity and metabolic outcomes.
2.4: The extent to which cord white blood cell DNA methylation differences mediate the associations of established maternal developmental overnutrition risk factors with postnatal offspring adiposity and metabolic outcomes.
Aim 3: To explore the role of developmental overnutrition, including metabolomic and epigenomic mechanisms, on risk of greater adiposity and metabolic outcomes in two generations.
[Note. we have used the following notation in objectives 3.1-3.3: G0=index pregnant women on whom developmental overnutrition risk factors were measured; G1= offspring of G0; G2 = offspring of G1 and their partners]
3.1: We will determine whether the G1 females who have been exposed to higher levels of intrauterine developmental overnutrition, determined by a weighted score of G0 developmental overnutrition risk factors, enter their pregnancies with greater adiposity and more adverse metabolic outcomes than G1 females who are less exposed to developmental overnutrition by their G0 mothers.
3.2: We will determine the associations of G1 female exposure to developmental overnutrition with G2 cord serum metabolome, cord blood white cell DNA methylation, birth weight and infant adiposity.
3.3: We will compare the associations examined in 3.2 to equivalent associations with exposure to different levels of intrauterine developmental overnutrition in G1 males.
B2087 - Methylation of maternal and cord blood as a mechanism in G x E interaction - 26/09/2013
Aims: There are many relationships between features of lifestyle and other exposures to the parents that have been shown to be related to the growth, behaviour and development of the child, but there is rarely a convincing mechanism to explain how they occur. This study aims to determine, for each of the known relationships, whether DNA plays a part in the mechanism.
The hypothesis is that DNA methylation is a mechanism to 'explain' a number of relationships between the environment and measures of growth, cognitive development and behaviour. The presumed mechanism is shown diagrammatically as follows:
Exposure to parents ? Methylation of mother's and/or child's blood ? child outcome
Exposure variables: The proposed study will concentrate on exposures related to toxins (particularly cigarette smoking), ionising radiation (especially X-rays and radon levels in the residential areas in which the parents were born and currently live which can be linked to 3-digit postcode using published data), nutrition (especially related to fish intake and to dietary patterns in pregnancy), and stress (particularly acute stressors during the parents' life-course, chronic stressors using social circumstances, and measures of their anxiety levels). Exposures to the parents and grandparents will be included.
Outcome measurements will concentrate on growth, behaviour, intellectual development and educational attainments (including SATS results as well as the ALSPAC assessments of maths, reading, spelling, scientific understanding and phoneme awareness).
Confounders will be chosen based on the original reports of an association between an exposure and an outcome. It is important to recognise that we are mainly testing the possibility of DNA methylation explaining relationships that have already been reported.
A variety of statistical analyses will be undertaken: (i) relationship between prior exposures to the mother and her parents and methylation of the mother's blood; (ii) relationship between the mother's methylation pattern and that in the cord blood; (iii) relationshipbetween exposures to both parents and grandparents andthe methylation levels of the cord blood; (iv) determination of ways in which these methylation patterns may explain how relevant exposures have influenced outcomes.
B2086 - Does methylation mediate the effect of physical activity on obesity in childhood - 26/09/2013
Background
Evidence implies that there is an association between physical activity and DNA methylation and between methylation and obesity. I will therefore explore the potential mediating relationship of methylation in the relationship between activity and obesity, using epigenome-wide data which have only recently become available on this scale.
Objectives
Primary objectives:
1)Identify methylation variation associated with physical activity and then consider how this variation relates to obesity.
2)Use Mendelian randomisation to investigate causality in any associations between physical activity, differentially methylated regions (DMRs) of the genome, and obesity.
3)Investigate the underlying biological mechanisms that the DMRs may be acting through.
Secondary objective:
1)Explore the relationship between physical activity, DNA methylation variation and cardiovascular health in children.
B2081 - Alcohol harms in the family - 19/09/2013
Aims relating to ALSPAC
This project aims to identify the mechanisms by which different levels, patterns and durations of alcohol consumption by one family member impact the health, well-being and life opportunities of other family members.
Hypotheses
Core hypotheses (children):
1. Having a heavy drinking parent in the household will have a negative effect on child outcomes at present and future waves.
2. Negative effects will be more pronounced when (a) the mother rather than father is a heavy drinker and (b) where both parents rather than only one parent are heavy drinkers.
3. Amongst children with a drinking parent, negative effects will be more pronounced where (a) other risk factors are in place, (b) the drinking has an effect on parenting behaviours and (c) the drinking negatively affects the relationships in the household.
4. Negative effects will be less pronounced where heavy drinking is not present at all waves either due to cessation or the drinker leaving the household.
5. Negative effects will be less pronounced where children have protective or resilience factors in place.
Core hypotheses (partners)
1. Having a heavy drinking partner (HDP) will have a negative effect on the other partner's (OP) well-being.
2. Having a HDP will reduce the OP's relationship satisfaction and increase the likelihood of relationship breakdown.
3. Negative effects for the OP will be more pronounced where (a) the OP drinks significantly less/less often than the HDP (b), the OP experiences other concurrent risk factors and (c) the HDP's heavy drinking persists across multiple waves.
4. Negative effects on the OP will be less pronounced where protective or resilience factors are in place.
Exposure:
Drinking measures
High level of consumption
High score on dependence screeners
Perceived drink problems
Outcome measures:
Child development:
- Cognitive
- Behavioural
- Social
- Psychological/emotional
- Parent/child relationship
Child health:
- Developmental milestones
- Health problems
- Accidents
Adult (mother and partner) well-being:
- Mental health
- General health
- Quality of life
Mother and partner relationships:
- Relationship satisfaction
- Relationship breakdown
- Domestic abuse
Moderators/mediators
Parenting behaviours, style, resources and self-efficacy
Family organisation (e.g. regular mealtimes)
Social support
Parental mental health*
Household composition (e.g. no. of children)
Marital status*
Socioeconomic status
Demographic characteristics (e.g. age, gender, ethnicity)
Financial measures (e.g. income, debt)
Housing situation and characteristics (e.g. social housing, safe environment, neighbourhood deprivation)
Residential area characteristics (e.g. area-level deprivation)
*Indicates risk, resilience or protective factors which are also outcome measures in their own right.
B2084 - CLOSER SES DATA HARMONISATION - 19/09/2013
The Cohorts and Longitudinal Studies Enhancement Resources (CLOSER) project aims to provide and document a range of key variables that have been harmonised across multiple UK birth cohorts to encourage cross-cohort research on longitudinal data sets and permit compatrisons across as well as within cohort studies. Due to the restrictions on using and holding ALSPAC data (particularly data obtained through linkage) it is our aim to derive standardised measures from education, income and social class variables that are harmonised with derived data from the other cohorts. These variables, once derived, will be deposited back to ALSPAC with accompanying documentation and will not specifically be used for research outputs at this point other than documenting summary statistics. As such, there are no exposure, outcome or confounding variables to outline.
Documentation will be held by CLOSER and made readily available to researchers in an attempt to provide a suitable search platform for commonly requested variables and therefore encourage cross-cohort analysis of data.