Is there such a thing as a "sweet tooth" that is acclimatisation to sweetness in foods. Is it possible that if an individual is exposed to foods rich in sugar that they can develop a "sweet tooth" and if a person is classified as having a "sweet tooth" does it matter?

Does having a diet rich in sweet foods impact on the nutritional quality of the diet? Does intake of sugary foods result in an excessive intake of non-milk extrinsic sugars, total energy and do they displace healthier food items from the diet? Do children who don't have a "sweet tooth" have a healthier diet than those with, and is there value in recalibrating a "sweet tooth"?

Subjects:

Avon Longitudinal Study of Parents and Children (ALSPAC) study is an ideal population in which to investigate these questions as it has a wealth of dietary data collected at several time points and valuable questionnaire data.

Data:

Dietary data has been collected using two methods. Food frequency questionnaire data is available at ages 3 years, 4 years, 7 years and 9 years. Food record data (3-day) is available on approximately 1000 children at 4 months, 8 months, 18 months, 43 months and 5 years and for approximately 7000 at 7 years, 10 years and 13 years. In addition there is age of introduction to various food items, including fizzy drinks, chocolate and sweets collected at 6 months and 15 months. The parents/carers were asked at 65 and 78 months if their child seemed to prefer sweet foods, these questions can be used to identify children with a 'sweet tooth'.

Methods:

1. Parent identified 'sweet tooth':

Analysis will be carried out to identify if there is any difference between the diets of children who were identified by their parents as having a "sweet tooth" and those who were not.. We will investigate if these children were introduced to sweet foods at an early age. Using the longitudinal data we will investigate if their diet tracks over time.

2. NME intake at 7 - used to identify those eating most sugar:

We will calculate non-milk extrinsic sugar intake at 7 years and divide intake into quintiles. We will compare the diets of children in the upper quintiles with the lower quintiles and indentify differences in intakes of nutrients and foods. We will track children's NME sugars intake from 7 years to determine if they remain within or cross centiles at age 10 and 13 years.

3. Early Introduction to sweet foods:

We will indentify children who were introduced to sweet foods at an early age, and identify if exposure to sweet foods at an early age leads to a higher intake of sugars in later diet.

Staff

Louise Jones Research Nutritionist (60% for 6 months) will perform the analyses and prepare manuscripts and reports.

Pauline Emmett Senior Research Fellow in nutritional epidemiology will will suppy expertise in analysis and manuscript preparation (2 hours per week)

Colin Steer will provide statistical support (1 hour per week)

Steve Gregory will provide data and manuscript preparation support (20% for 6 months)

The work will be part of the School Food Trust research strategy.

Replications of eye_quantitative_traits hits Genome-wide significant :

For genome-wide significant hits in our respective cohorts for which we (reciprocally) are seeking replication in each other cohort, lead for follow up and publication would be given to the group seeking replication. Effect size , P-value for association at the specific SNPs and method of analysis would be requested (ALSPAC's GWA analyses are ongoing). All work and analyses would be acknowledged in the publications and the replicating group would provide authors for the papers written by the leading group, whatever the results.

The summary of the measures used in our analyses in the 2 croatian population-based studies are

attached with this proposal. We are seeking data in the ALSPAC study for one SNP which reached genome wide significance in our metaanalysis of ocular axial length in the 2 Croatian isolates,and showed the same magnitude and direction of effect in our 2 independent isolates. We would also like, if the meta-analysis proposal (below) was not to go ahead , to get similar data on 2 additional regions (2 SNPs) that showed strong evidence of association with axial length, in females only. These do not reach genome wide significance in the initial genotyped set but show strong cluster of association in the imputed dataset and make biological sense.

Meta-analysis on GWA data for eye traits on a collaborative basis:

This analysis required harmonisation of the traits analysed before pooling data. Each group would analyse his own dataset. We can include more trait data than in the replication study, to maximise the value of the analyses for each group.Material tranfert agreements would be drawn to insure that the shared analysis results are not passed on to third party without formal approval. We propose to use rank normalised data post adjusted for age and sex for axial length and refractive error. This is because spherical equivalent usually has a non normal distribution. We propose to also perform the analysis separately for each gender. Analysis would be done using an additive genetic model, for example using the function formetascore of the R package GenABEL for easy merging of the data.

The output files to be exchanged and meta-analysed lay-out would be :

(1) " name": SNP rs number

(2) "chromosome"

(3)"position"

(4)"strand" ideally all standardise to the top strand using build 36

(5) "allele1"

(6)"allele2"

(7)"build"

(8)"effallele" allele for which effect is reported

(9)"effallelefreq"

(10)"n" number of individuals with genotypes and phenotypes available for that SNP

(11) "beta"

(12) "sebeta"

(13)"p" uncorrected P-value for the additive test

(14)"pgc" above corrected after genomic control correction

(15)"lambda" estimated inflation factor (genomic control lambda) for the test

(16)"pexhwe" exact P-value for HWE test

(17) "call" Call rate for the SNP

Results from this meta-analysis would be described in a paper/papers with shared authorship between the groups and 2 co-corresponding authors, one from each group.

The aim of the proposed programme of work is to establish the role of epigenetic mechanisms (DNA methylation) in the developmental programming of disease in later life. This will involve establishing both the determinants of epigenetic variation (i.e. the relationship between various exposures and methylation status in DNA at available time points) and the consequences of epigenetic varaition (i.e. the relationship between DNA methylation status and phenotypic outcomes).

In addition, the transmission of epigenetic patterns from mother to child will be investigated. The role of maternal epigenetic signatures in determining child epigenotype and phenotype will be explored.

A further area of interest is the role of common genetic variation in dictating epigenetic patterns. Using existing ALSPAC genotype data will we be able to explore whether genotype (both maternal and child) impacts upon epigenetic variation. When epigenotype is considered a a phenotype, a Mendelian randomisation approach can be used to explore the determinants of epigenetic status.

This work will be pursued via a varity of funding opportunities including the following;

1. ERC Programme Grant: "Epigenetic Epidemiology; the role of epigenetic variation in common complex disease". 2 million euro, submitted Dec 2008, outcome July 2009.

2. Biomedical Research Centre in Ageing, Newcastle University: "DNA methylation and ageing". £60K, submitted Feb 2009, outcome April 2009.

3. MRC Project grant: "Epigenetic mechanisms in the developmental programming of obesity". For submission May 2009.

4. Wellcome Trust; "A comparative study of epigenetic variation in low and middle income country settings with a UK adolescent birth cohort". For submission July 2009.

Studies will involve array-based approaches to define gene loci that demonstarte epigenentic variation (MeDIP-chip, Illumina BeadArray probable platforms) in a small sub-set of samples (typically 24 paired; exposed/unexposed, case/control or 2 extremes of phenotype) followed by quantatitive DNA methylation (qCpG) analysis of specific loci in a substantial number of samples (n=1000+). qCpG analysis will be undertaken using Pyrosequencing or Sequenom MassArray. A candidate gene-based approach utilising qCpG without requiring array analysis is also feasible.

DNA requirements for microarray are 1ug at 100ng/ul. For subsequent qCpG analysis the same quantity is required to analyse 5-10 loci.

Data will be required on a range of exposures and phenotypes at serail timepoints and in both children and mothers. An outline description of the data required is provided below;

Phenotypes of multiple outcomes that show evidence of developmental programming including; obesity and related traits, cardiovascular disease and related traits in children from the ALSPAC cohort; Pre- and postnatal exposures which may plausibly influence programming including maternal smoking and nutritional variables and maternal and child genotypes that can be used as instrumental variables (e.g. MTHFR) ; other prenatal exposures and socio-demographic variables. DNA methylation profiles of children linked to phenotype and exposure data.

(No outline provided).

We request permission to use available funds to complete assays of Anti-Mullerian hormone (AMH) on the serum residuals that are currently held in Glasgow from samples taken at the 15+ clinic. An NIH funded grant (PI: DA Lawlor) provided funds for fasting glucose, insulin and lipids to be completed on a predicted 7000 samples at the 15+ clinic. Blood samples from this clinic were only available on ~3500 samples and relevant assays are now near complete on these. Because a smaller number of samples were assayed funds are available to complete AMH assays on these 3500; and sufficient serum for these assays is currently available in Professor Sattar's laboratory in Glasgow. AMH assays would be relevant to the NIH grant application since we will use these to examine developmental origins of ovarian and testicular function which are in turn related to vascular and metabolic health outcomes.

We would like to address the following objectives in relation to AMH:

a. Describe the distribution of AMH in contemporary males and females at mean age 15

b. Determine the association of parental smoking in pregnancy; maternal weight gain in pregnancy; blood pressure change in pregnancy; gestational diabetes/glycosuria in pregnancy and parental smoking whilst breast feeding (in those offspring who were breastfed) with offspring AMH levels at mean age 15

c. Determine the prospective associations of offspring smoking, fat mass and change in fat mass, growth trajectories from birth to age 15, age at menarche (females) with AMH levels at mean age 15

d. With available data (current 3000 or larger if grants funded) complete a genome-wide association study with AMH (In collaboration with David Evans & Nic Timpson) of AMH levels

e. Examine the cross-sectional associations of AMH with glucose, insulin and lipids at age 15.

Background

AMH and ovarian and testicular function

Anti-Mullerian hormone (AMH, Mullerian-inhibiting substance) is a member of the transforming-growth factor-beta family. AMH has the primary role of regression of the Mullerian duct in the male fetus during early testis differentiation. However, expression of AMH persists after completion of the reproductive duct system in males, and furthermore commences expression in females at this time, in whom it is produced by ovarian granulosa cells from early fetal life[1]. Although AMH is initially observed in granulosa cells of primary follicles, maximal expression occurs in preantral and small antral follicles[2, 3]. AMH expression declines as antral follicles increase in size, with nominal expression restricted to the granulosa cells of the cumulus[3]. This loss of AMH expression during the follicle stimulating hormone (FSH)-dependent final stages of follicular growth, and the lack of expression by atretic follicles[4], suggests that basal levels of AMH may more accurately reflect the total developing follicular cohort and consequently potential ovarian response to FSH. The clinical utility of this, and a demonstration of the likely causal signficance of AMH as a measure of ovarian function, is that AMH is strongly associated with oocyte yield, clinical pregnancy and live birth in IVF cycles[4-7]. It is also a sensitive measure of the gonadotoxic effect of differential chemotherapy regimens and falls rapidly after toxic stimuli[8-12]. It is elevated in polycystic ovarian syndrome, a condition associated with increased preantral follicles[13-18]. Lastly, it can indicate the timing of the menopause transition approximately 5 years prior to the sentinel event as determined by amenorrhoea and circulating follicle stimulating hormone levels[19, 20]. Importantly, AMH has also been shown to be relatively consistent across the menstrual cycle[21-23], consistent with its role reflecting the continuous, non-cyclic growth of small follicles in the ovary. AMH has therefore overtaken other markers and is now recognised as the optimal measure of follicular reserve in females[7, 24, 25].

AMH is also produced in males, and the ontogeny of AMH is similar across species[26, 27], in that circulating AMH produced by Sertoli cells remains high until the onset of puberty, when they progressively decrease, correlating with the stage of pubertal development. This decline in AMH is principally due to the inhibitory effect of intratesticular testosterone and meiotic cells on Sertoli cell AMH expression[28], and male AMH values decrease to female levels[29]. Male AMH therefore provides a unique handle on Sertoli cell number and function - the principal determinant of testicular germ cell number. Consistent with this subfertile men have a significantly lower AMH than controls[30], and that even the relatively mild insult of a varicocele is associated with a lower AMH in prepubertal, pubertal and adult males[30, 31].

Prenatal/developmental determinants of ovarian and testicular function

Gestational cigarette smoking is plausibly a strong determinant of ovariant and testicular function and likely to be related to AMH via intrauterine and lactation exposure. In female fetuses, smoking may have a direct toxic effect on the primordial follicle, leading to premature exhaustion of the follicular germ pool[32, 33]. In animal models impairment of fertility in the offspring following prenatal exposure to polycyclic aromatic hydrocarbons (in cigarette smoke) via the mother during pregnancy has been demonstrated. Histological analysis of ovarian tissue from the exposed offspring mice demonstrate a markedly reduced number of primordial follicles[34, 35], suggesting that a detrimental impact on ovarian reserve and follicular dynamics underlies this phenomenon. Notably, in mice models, the combination of pre-pregnancy and lactational exposure to polycyclic hydrocarbons was associated with a 70% reduction in primordial follicle number[36]. This loss of primordial follicles and primary follicles if applicable to humans has profound biological consequences, as it is generally accepted that mammals are born with a finite number of primordial follicles that are incapable of proliferating and replenishing, and it is this dogma which underlies the chronological decline in the fecundity of both natural[37-39] and stimulated ovarian cycles[40, 41] and the relatively static onset of the menopause.

Human studies examining the impact of maternal smoking on the ovarian reserve of the offspring have been limited[42, 43]. A small epidemiological study of 230 women with offspring recall of maternal smoking status during the index pregnancy demonstrated a reduced cumulative conception rate[42]. This association was robust to adjustment with frequency of intercourse, the offspring's age and own smoking status and childhood exposure. Prenatal exposure to maternal smoking and reduced fecundability in the offspring was also observed in a recall study of 663 women from Minnesota[43]. Analysis of time to pregnancy in 1653 female twins also demonstrated a reduced fecundability in the exposed female offspring[44]. In contrast for offspring exposed during childhood to parental smoking an increased fecundability in the offspring was observed in both of these studies[43]. Importantly this apparently conflicting data regarding the timing of exposure is dependent on offspring recall of parental smoking status and has not examined differential smoking status across gestation, lactation and childhood and has no information regarding dose-dependent effects. With the prospective data in ALSPAC we will be able to examine the association of smoking in pregnancy, during infancy (and lactation where relevant) and childhood on AMH levels an index of ovarian reserve (see above) and we will be able to compare associations with paternal smoking to establish whether maternal associations are likely to be acting through intrauterine mechanisms.

With respect to males maternal cigarette smoking during gestation has been increasingly associated with rising incidences of cryptorchidism and hypospadias and reductions in testis size, sperm counts/quality, and fertility[45-47]. Thus, we hypothesise that maternal smoking during pregnancy and lactation will also be related to reduced AMH levels in males as well as females.

In both males and females there is epidemiological evidence of an association between obesity, metabolic parameters and fertility and other reproductive outcomes. These characteristics also cluster within families, with intergenerational associations. Whilst AMH levels have been assessed in prepubertal offspring of mothers with PCOS (and shown to be elevated in comparison to similar aged offspring of women without PCOS[14], to our knowledge no one has previously examined the association of maternal obesity, weight gain and metabolic/ vascular characteristics during pregnany with offspring AMH levels

Genetic determinants of AMH

Many reproductive characteristics and diseases have high levels of heritability including age at menarche (50-70%; [48]), age at menopause (~ 50%;[49, 50]) and PCOS (~60% [51]). Analysis of 359 women with PCOS, demonstrated an association between circulating AMH levels and three SNPs of the ACVR1 gene which encodes the common ALK2 component of the heteromeric AMH receptor complex in an allele dose manner[52]. In contrast AMH was not associated with SNPs in either the AMH gene or the specific AMH type II receptor part of the heteromer, despite biological effects when expressed in cell lines[53]. We hypothesise that in a general population a number of common variants will have modest associations with AMH levels. In particular given that AMH and follicular function are linked to metabolic derangements, we will examine common variants of genes, regulating metabolic function and adiposity.

Associations of AMH with vascular and metabolic traits

The relationship reproductive health with vascular and metabolic traits, and specifically the association of PCOS with insulin resistance and reduced insulin secretion would predict associations of AMH with glucose, insulin and lipid levels.

Methods

AMH will be assayed on existing ALSPAC samples from 15+ at Professor Naveed Sattar's laboratory. The AMH assay used will be the commercial ELISA kit provided by DSL (Webster, Texas, USA). This kit is in routine use in our laboratories[5, 7]. Current inter and intra-assay CVs in our laboratory are 3.0% and 2.6% respectively. The Glasgow laboratory adheres to UK external quality control for all parameters and is Clinical Pathology Accreditation (CPA) accredited.

For objectives a-c and e relevant datasets will be compiled by DA Lawlor and standard linear / logistic regression models used in analyses. Sensitivity tests of possible non-paternity will be used when comparing maternal and paternal exposures with offspring AMH levels.

For objective d, data management and analyses will be undertaken by Dave Evans & Nic Timpson from MRC CAiTE, University of Bristol.

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Hypothesis 1. Autism risk is associated with exposure to intrauterine cytokines and/or hypoxia.

Autism and other neuropsychiatric risks have been linked to intrauterine exposures to cytokines and/or hypoxia. These studies are limited in that they have been forced to rely upon retrospective cohorts, maternal serum samples, maternal medical history, etc., each of which is problematic in terms of bias (true peer "control" sample), ascertainment (retrospective assessment of maternal gestational illness), or true measure of fetal exposure (maternal serum cytokines do not necessarily imply fetal cytokinemia).

The ALSPAC cohort will allow us to avoid most of those pitfalls, in a nested case-control study that will use both standard histopathologists' definitions and image analysis, to determine the presence and severity of

* acute inflammation (most commonly a marker of intraamniotic infection),

* chronic placental inflammation (with a differential diagnosis generally considered to be congenital viral infection or maternal attack against the semi-allogeneic fetoplacental unit), and

* the villous effects of uteroplacental malperfusion (villous fibrosis, excess syncytial basophilia and knotting, infarcts, abruption, generally reflecting reduced fetal oxygenation secondary to the abnormal maternal perfusion of the placenta and/or damage to the placenta).

Hematoxylin and eosin stained slides (and special stains as indicated) will be scored by a team of 3 trained and expert pathologists, and the digitized slides will be evaluated using sets of segmentation and quantification algorithms developed to measure inflammation and hypoxia.These semiquantitative (pathologist') and continuous (image analysis) variables will be correlated with case-control status, with adjustment for gender, gestational age and birth weight at delivery using structual equation models in which the placental histology features are considered to be indicators of underlying latent variables (e.g., maternal acute inflammatory responses, fetal acute inflammatory responses, maternal malperfusion). The model including all

All cases of autism identified in ALSPAC (n=56) will be included in this nested case-control study. We will select four controls for each case to maximize statistical power of the comparisons. The gain in statistical power with the use of additional control subjects is negligible. The large size of the ALSPAC cohort allows us to match on a few key variables that may be differentially distributed among the cases. We propose to match on infant sex and gestational age (=/- 1 week ideally, 2 weeks if necessary). Prematurity is not a major risk factor for autism so we expect matching on gestational age to be feasible.

2. Placental vascular branching is a biomarker for Autism.

Autism is a disorder of abnormal neuronal connectivity and, by extension, abnormal neuronal dendritic branching. The placenta is an organ that is architecturally little more than a thin tissue sheath covering a vascular tree. It is uniquely dependent on coordinated and accurate paternal gene expression, and its growth is regulated by gene families that regulate events that may be key to the connectivity issues described in autism. We hypothesize that the vascular architecture of the placenta is a proxy for aspects of neuronal differentiation, elongation and navigation that are germane to the genesis of autism risk. Thus autism risk will have parallel placental findings of altered villous and vascular branching.

Neurons and the Vasculature: Shared Pathways for Outgrowth, Proliferation and Branching Diversity. Placental blood vessels provide oxygen and nutrients to and remove metabolic products from the embryo/fetus. It has been recognized that the signals and guiding principles to differentiate, elongate and navigate blood vessels towards their destinations are analogous to those in neuronal development. Vascular endothelial growth factor (VEGF) promotes vascularization of the placenta as well as neuronal differentiation. Similarly, a number of factors promote endothelial proliferation and angiogenesis; moreover, their cross-talk-and in particular their defective cross talk-may be at the root of a wide range of both vascular/ neurological and placental diseases .

Antiangiogenesis and Autism: Thalidomide and Valproate. Thalidomide and valproate exposures in early pregnancy are recognized risk factors for autism. Animal models exposed in utero to valproate demonstrate neuroanatomical changes in the brainstem and cerebellum that are comparable to those in brains from children with autism. Both of these drugs are antiangiogenic as well as teratogenic. Mechanisms of such damage involve disruption to vascular growth factors, i.e., VEGF and placental growth factor (PlGF) and their associated signal transduction pathways. Note, VEGF and PlGF are produced and released by the placenta.

Hypothesis: Placental Vascular Branching is an Indicator of Normal Fetal Neuronal Connectivity. Autism is a disorder of abnormal neuronal connectivity and, by extension, abnormal neuronal dendritic branching. The placenta is an organ that is architecturally little more than a thin tissue sheath covering a vascular tree. It is uniquely dependent on coordinated and accurate paternal gene expression, and its growth is regulated by gene families that regulate events that may be key to the connectivity issues described in autism. We hypothesize that the vascular architecture of the placenta is a proxy for aspects of neuronal differentiation, elongation and navigation that are germane to the genesis of autism risk. Thus autism risk will have parallel placental findings of altered villous and vascular branching.

Measuring Placental Vascular Abnormality. The placenta is accessible (delivered with each baby born), and can be measured reliably. In a series of papers, we have developed novel methods for the study of the placental vascular arborization. We have introduced a dynamic model of the placental vascular growth based on a well-studied fractal random growth process (DLA). The model has allowed us to associate an abnormal morphology of the placenta with the abnormal vascular branching and connectivity. The standard marker of the branching density of a fractal tree is a version of a fractal dimension. While mathematically elegant, it is difficult to quantify in a practical study. We proposed a new idea, relating the placental vascular branching structure with a metabolic scaling exponent. This quantity is easy to measure as a ratio of logarithms of the fetal birth weight and the placental weight, and is a biologically relevant version of the fractal dimension of the vasculature. Our studies have demonstrated an association of the scaling exponent with the known factors affecting the normal vascular development.

Preliminary Findings on a Female-Specific Risk Factor for Autism: Advanced Paternal Age. Autism and Autism Spectrum Disorders have a strong genetic component, and a predilection for males. Recently, a risk factor for autism, advanced paternal age, was demonstrated to have an effect confined to female offspring, who inherit their second X-chromosome from their fathers [18]. The operative hypothesis is that the X-chromosome, which contains many genes associated with cognition and intelligence, may acquire either mutations or epigenetic alterations over the father's lifespan that then alter those gene's expression in his daughters. We have recently identified a female-specific negative effect of advanced paternal age on birth weight in the National Collaborative Perinatal Project, a well studied national cohort with over 24,000 cases with placental data. The placentas were thinner in this case, indicating a less arborized vascular tree.

Methods of the Proposed Research.

a. Placental Processing: Placentas will be processed according to protocols that have been reviewed and agreed to by the Pathology Department University of Bristol Hospital. Specific features include:

1. Digital photography of the chorionic surface and of slices of the placental disk.

2. Tissue sampling to include:

2 cross sections of the umbilical cord

1 membrane roll

4 samples of grossly normal placenta obtained from each placental quadrant

2 "functional units" (2.5 cm square full thickness regions with a terminal chorionic surface vessel)

Digital photographs will be uploaded to the Placental Analytics FTP site for analysis. Tissue samples will be processed to wax blocks. The blocks will be shipped to Placental Analytics, LLC for slide preparation.

Data extracted from the digital photographs and copies of the files of all digitized histology slides prepared from the placental tissue samples will be returned to ALSPAC as they are generated throughout the course of the study.

Tissue blocks will be retained by Placental Analytics, LLC until completion of the study at which point they will be returned to ALSPAC.

Placental Vascular Analyses: A key to our analysis of the placental vascular branching structure is the connection between the arborization of the vascular tree and the metabolic scaling exponent (a biologically relevant fractal dimension), as well as the morphological factors, such as the shape and the size of the placenta. Using the DLA model of placental angiogenesis, we can connect the variability in the placental shape with a perturbation in the placental vascular architecture. Fourier analysis of the two-dimensional images of the chorionic plate can be used to reliably identify such perturbations which appear early in gestation, and are hypothesized to be connected to Autism risk. An early reduction of the placental angiogenesis is also related to a larger value of the metabolic scaling exponent - a quantity which is particularly easy to measure at the time of delivery, with implications for an early diagnostic of the related Autism risk factors.

We have begun the analysis of 3-dimensional placental shapes, beginning with the study of the thickness and variability of slices perpendicular to the chorionic plate. The thickness of the slices, in particular, is associated with the vascular density. Our preliminary findings show that for female babies, the average thickness is adversely affected by the advanced paternal age, which is a known Autism risk factor. The variability of thickness is also associated with the suppressed angiogenesis in the DLA model [16]. We have also initiated the study of the skeletonized structure of the placental vasculature both for DLA models (with the skeletons of vascular trees traced automatically) and for digital photographs of the chorionic surfaces (with manually traced skeletons). We have developed measures of average density of the large and medium blood vessels in the placental surface, which complement the techniques described above, with similar results. We plan to further this approach by developing automated digital recognition of the large-scale branching structure in the chorionic plate surfaces.

Pregnancy has been conceptualised as a metabolic challenge, since the normal physiological/hormonal response to pregnancy - high oestrogens and cortisol levels - results in a temporary metabolic like syndrome.(1) These changes are likely to be hormonally driven through acquisition of fat in early pregnancy and its rapid mobilisation later, and it has been hypothesised that women with greater weight gain during pregnancy are likely to be at greater risk of extreme metabolic and vascular changes during pregnancy and increased risk of the later development of diabetes and CVD.(1;2) There is also increasing evidence that greater weight gain in pregnancy is associated with offspring obesity risk in childhood and early adulthood,(3-10) and from a recent study conducted by the PI of this application that this association results in greater blood pressure in offspring.(3) At the extreme, the metabolic and vascular changes of pregnancy are manifest as clinically diagnosed gestational diabetes and hypertensive disorders of pregnancy (HDP: preeclampsia and gestational hypertension) both of which are associated with a wide range of other adverse (for mother or general populations in non-pregnant states) vascular, metabolic and inflammatory changes during pregnancy and with future glucose intolerance, diabetes, dyslipidaemia, hypertension and cardiovascular disease risk in the mother,(1;2;11-15) and her offspring in later life.(2;3;16-18)

The mechanisms that link pregnancy related characteristics to later cardiovascular and metabolic phenotypes in women are unclear. Our proposal will contribute to understanding the extent to which two hypothesised mechanisms for this association might be responsible.(19) These two hypotheses are (i) that an existing predisposition (in part a genetic predisposition) for adverse vascular and metabolic outcomes is unmasked by the stress test of pregnancy(1;20) and (ii) that adverse vascular and metabolic changes are caused by pregnancy in some women and these changes remain permanent and therefore increase the risk of future disease in later life. In the latter fetal genotype might drive the maternal changes in order to increase their nutrition during intrauterine development, particularly in the situation of placental underperfusion.(19;21) If the first hypothesis has a substantial role in explaining the association of pregnancy with later life maternal phenotypes then we would anticipate similar genetic variation to be associated with both pregnancy and non-pregnancy (later life) phenotypes. If the second has a substantial role then we would anticipate some maternal genetic variation to be associated only with non-pregnant phenotypes and we might expect some fetal (offspring) genetic variation to be associated with maternal pregnancy phenotypes. We will be able to test these possibilities in this proposal.

We will also be able to explore the extent to which intrauterine (developmental origin) mechanisms or shared genetic heritability contribute to the link between maternal pregnancy characteristics and offspring metabolic and vascular phenotypes. If intrauterine factors are important then we would anticipate that maternal genetic variation that is associated robustly with her phenotypes (e.g. weight change in pregnancy) to be associated with offspring phenotypes even after controlling for the offspring's own genotype. Whereas if genetic inheritance explains the intergenerational association we would anticipate the association of mother's genotype with offspring phenotype to be attenuated to the null upon adjustment for offspring genotype.

(No outline received).

Background

As interventions studies have shown it is difficult to change food habits once firmly established, identifying how they develop is crucial if public health recommendations or early interventions in at risk individuals are to be developed (Te Velde, 2008; Moreno, 2008). Few studies have investigated early factors influencing the development of food habits (Northstone, 2001; Coultard 2009). Early life is a period of fast and coordinated changes to establish physiological and social functions. Critical periods in child's growth that control later body composition have already been found (Botton, 2008; Monteiro, 2005, Ekelund 2007) and probably correspond to specific needs in energy and nutrients. In parallel cognitive and motor development follows well described steps. The development of the child eating behaviour is characterised by critical periods for food habits.

These are influenced by characteristics of the child including appetite, satiety, food preferences, food neophobia, fussiness, and by the food environment and the social and emotional context of meals. Parental attitudes are also important in determining what children eat.

Subjects

Avon Longitudinal Study of Parents and Children (ALSPAC) study is an ideal enviroment in which to investigate these critical periods and relate them to later outcomes such as eating behaviours, growth and development.

Data has been collect on 14000 children whose mothers were recruited between 1991 and 1992 early in pregnancy. The completed child follow-up comprises questionnaires at 6 months (n=11490), 15 months (11 077), 24 months (10 432), 3 year (10 145), 4 year (9722), 5 year (9013), 7 years (8515) and 9 years (7965). The early questionnaires covered milk feeding, weaning, age of introduction of each type of food and feeding problems. Parental attitudes to food and feeding their child have been covered in a series of questionnaires to parents about themselves. The study has collected detailed records of foods and drinks taken by the children over 3 days (up to 1000 children at 4, 8 & 18 months, 3.5 and 5 years and over 6000 children at 7, 10 & 13 years). These can be used to determine the amount and types of key foods, such as fruit and vegetables, eaten in relation to early feeding practice. The children have been weighed and measured at all these time points so these feeding practices can be related to growth and obesity development.

Methods

Secondary analysis of data already collected will be undertaken to build on the work of Emmett and Northstone which has investigated the relationship between late introduction of chewy foods and later feeding difficulties up to age 7 years. This will be extended to look at outcomes up to 13 years including body compostion and types of foods eaten (assessed by diet records). Further analysis will look at the age of introduction of various types of solid foods, such as meat, fruits, vegetables, processed foods and the relationship with eating patterns, foods and nutrients up to 13 years. Parental behaviours and attitudes to feeding the child will be investigated to determine benificial and detrimental practices.

Staff

Kate Northstone (5% for 2 years) will be a co-applicant and will provide statistical support to a team in COBM.

This will comprise 1-day per week from a statistical assissant, 3-days per week from a nutritionist (Louise Jones) and 2 days a month from Pauline Emmett as PI. This work will be for 24 months from Jan-01. The second 2 years of the project we will provide an advisory role only fullfilled by Pauline at 1.5 days a month.

The work will be part of an FP7 funded EU project lead by Dr. Sylvie Issanchou, Institut National de la Recherche Agronomique (INRA), France.