Childhood obesity is a major and increasing public health concern, with prevalence in the UK rising rapidly in children as young as 3 years (Buchan et al., 2007; Bundred et al., 2001). Some risk factors associated with childhood obesity include parental obesity, maternal smoking, increasing birth weight, and a positive mismatch between energy intake and energy expenditure (Prentice & Jebb, 1995; Reilly et al., 2005). Similarly, the incidence of obesity in companion pets is also thought to be increasing (German, 2006), and is known to have detrimental effects on pet health and longevity (Kealy et al., 2002; Lund et al., 2006). Furthermore, there is emerging evidence of a possible link between human and companion animal obesity, since overweight owners are more likely to own overweight dogs (Holmes et al, 2007). Given that the prevalence of childhood obesity is greater in families where mothers are heavier (Hawkins & Law 2006), there may be close associations between the causes of obesity in both children and companion animals. This is, perhaps, not surprising since the owner-pet relationship is similar to that between parent and child (Berryman et al., 1985). Given such associations, it is likely a major cause of human and companion animal obesity is the fact that all family members (including pets) are exposed to common environmental factors, namely the 'family food environment' (Campbell & Crawford 2001), which may predispose to obesity.

Half of UK households own a pet of some type, with one in four owning a dog( Anon, 2004; Westgarth et al., 2007). In a community-based study of 1278 households, we have identified a number of factors that are associated with households that choose to own dogs, including families with school age children being more likely to own a dog (Westgarth et al., 2007a). The beneficial impact of companion animal ownership on the physical, social and psychological health of people has been well documented (Friedmann, 1995; Headey, 2003; Katcher, 1981; Katcher & Friedmann, 1982; McNicholas et al., 2005). However, although there is some evidence of a link between obesity in dogs and their owners, there has been no specific research into a possible association between pet ownership and childhood obesity.

In the light of the increasing childhood obesity epidemic across western societies, and failure of measures taken so far to control this, new intervention means are urgently required. Intervention may also have implication for the pet population; given the suggested links between obesity in humans and companion animals, interventions can be adopted which tackle both problems concurrently. Indeed it is possible that pet ownership, and in particular dogs, may reduce the risk of childhood obesity. This may be through exercise and lifestyle factors, or some other measure associated with the types of families that choose to own dogs/pets. In fact, a previous study has demonstrated the effectiveness of a combined weight loss programme, for owners and pets, and suggested that social support for human weight loss in family members should be extended to include pets (Kushner et al., 2006).

The null hypothesis to be tested using ALSPAC data is that pet ownership has no association with childhood obesity. In order to investigate this a number of strategies will be used, including investigation of ALSPAC data of children of 7yrs. On discussion with the ALSPAC group and subject to there being appropriate data, the investigation may also be conducted in a longitudinal manner, using pet ownership and BMI at different ages of the child. This may provide additional insight into direction of causality.

Variables requested will be similar to this paper

Reilly, J. J., Armstrong, J., Dorosty, A. R., Emmett, P. M., Ness, A., Rogers, I., Steer, C. & Sherriff, A. (2005). Early life risk factors for obesity in childhood: cohort study. Bmj 330, 1357.

As this paper only includes risk factors before 3yrs (but an outcome of obesity at 7yrs), other useful variables may be identified up to the age 7yrs, on discussion with the ALSPAC group.

Pet ownership variables are also requested, including during pregnancy and each year, in addition to contact with animals, those years that these questions were asked. All data was collected using questionnaires unless otherwise stated. Pet ownership and contact with animals will be investigated as a whole and for individual species types.

BMI, child, 7yrs (and possibly yearly).

Pet ownership, mother/principal carer, pregnancy to 7 years.

Contact with animals (at least once a week at home or elsewhere), for child, 15, 24, 38 and 54 months.

Maternal social class (SES), mother, 32 weeks gestation.

Maternal education, mother, 32 weeks gestation.

Ethnicity, child, birth.

Energy Intake of Child, child, food frequency questionnaire at 30 months.

Birth weight, child, birth, delivery room.

Sex, child, medical records.

Maternal parity, mother, questionnaire 18 weeks gestation.

Maternal smoking during pregnancy, mother, 32 weeks gestation.

Season of birth, child, medical records.

Gestational age, child.

Number of foetuses, child, medical record.

Breast feeding, child, 6 months questionnaire.

Age at introduction of complementary feeding, child, 6 months questionnaire.

Parents body mass index, mother, prepregnancy.

Parents body mass index, father, prepregnancy.

Number of siblings, child, 18 months.

Ethnicity of child, child, 32 weeks gestation.

Age of mother at delivery, mother, birth, clinical records.

Time spent watching tv per week, child, 38 months.

Time in car on weekdays per day, child, 38 months.

Time in car on weekend days per day, child, 38 months.

Duration of nighttime sleep, child, 38 months.

Dietary patterns (food frequency questionnaire), child, 38 months.

A range of studies have now demonstrated human health benefits from pets. However, the vast majority of this work has used samples of Caucasian origin. Where non-Caucasian owners have been included, they have been in numbers too low to draw conclusions about differences in pet ownership across ethnic groups. It is important to look at patterns of pet ownership across ethnic groups to understand differences in attitudes and behaviour toward pets. Significance of the relationship with pets, levels of attachment and patterns of activity with pets may all vary so that ethnic groups may differ in potential benefits from pet ownership. The ALSPAC data may provide us with some insights to ethnic differences in pet ownership within the UK.

The University of Liverpool is an appropriate institution to be conducting this study, due to its international reputation, in both medical and veterinary fields, for obesity research and track record of collaboration. Comparative obesity research is actively encouraged and co-ordinated through the Liverpool Obesity research Network (LORN), which arranges regular meetings and discussion on all aspects of obesity research. Previous collaborations between the Faculties of Veterinary Science and Medicine have been highly successful, for instance, leading to the foundation of Europe's' first weight management referral clinic for companion animals (www.pet-slimmers.com), funded by WALTHAM. Dr Peter Bundred is an acknowledged expert in the field of childhood obesity epidemiology, and has published widely in this area. Therefore, he is accustomed to the procedures necessary for undertaking such research. Dr Alex German is an RCVS-recognised specialist in internal medicine whose main research focuses is in companion animal obesity biology, and who already collaborates with WALTHAM in this area. Dr Carri Westgarth is experienced in investigating factors associated with pet ownership and the characteristics of human-dog interactions.

The science is novel and of high priority, given that it targets the most important medical disease in humans and companion animals and given current estimates on obesity prevalence. The information gained will significantly increase the understanding of beneficial or other associations between pet ownership and childhood obesity, and be the first step towards developing effective strategies to improve obesity management.

Anon (2004). Pet ownership trends. Pet Food Manufacturers Association

Available at http://wwwpfmacom/public/petownershiphtm.

Berryman, J.C., Howells, K., Lloyd-Evans, M. (1985) Pet owner attitudes to pets and people: a psychological study. Veterinary Record, Vol 117, Issue 25-26, 659-661

Buchan, I. E., Bundred, P. E., Kitchiner, D. J. & Cole, T. J. (2007). Body mass index has risen more steeply in tall than in short 3-year olds: serial cross-sectional surveys 1988-2003. Int J Obes (Lond) 31, 23-29.

Bundred, P., Kitchiner, D. & Buchan, I. (2001). Prevalence of overweight and obese children between 1989 and 1998: population based series of cross sectional studies. Bmj 322, 326-328.

Campbell K & Crawford D (2001). Family food environments as determinants of pre-school aged children's eating behaviours: implications for obesity prevention strategies. Australian Journal of Nutrition and Dietetics 58, 19-25.

Friedmann, E. (1995). The role of pets in enhancing human well-being: physiological effects. In The Waltham Book of Human-Animal Interaction: Benefits and Responsibilities of Pet Ownership, pp. 33-53. Edited by I. Robinson. Oxford: Elsevier Science Ltd.

German, A. J. (2006). The growing problem of obesity in dogs and cats. J Nutr 136, 1940S-1946S.

Hawkins, SS & Law, C (2006). A review of risk factors for overweight in preschool children: a policy perspective. Int J Pediatr Obes 1(4), 195-209.

Headey, B. (2003). Pet ownership: good for health? Medical Journal Of Australia 179, 460-461.

Holmes, K.L., Morris, P.J., Abdulla, Z., Hackett, R. & Rawlings, J.M. (2006) Risk factors associated with excess body weight in dogs in the UK. Journal of Animal Physiology and Animal Nutrition 91, 166-167.

Katcher, A. H. (1981). Interactions between people and their pets: form and function. In Interrelations between people and pets, pp. 41-67. Edited by B. Fogle. Springfield: Charles C. Thomas.

Katcher, A. H. & Friedmann, E. (1982). Potential health value of pet ownership. California Veterinarian 36, 9-13.

Kealy, R. D., Lawler, D. F., Ballam, J. M. & other authors (2002). Effects of diet restriction on life span and age-related changes in dogs. Journal of the American Veterinary Medical Association 220, 1315-1320.

Kushner, R.F, Jackson Blatner, D., Jewell, D.E., Dudloff, K. (2006) The PPET Study: People and Pets Exercising Together. Obesity 14:1762-1770

Lund, E. M., Armstrong, P. A., Kirk, G. A. & Klausner, J. S. (2006). Prevalence and risk factors for obesity in adult dogs from private US veterinary practices. International Journal of Applied Research in Veterinary Medicine, 177-186.

McNicholas, J., Gilbey, A., Rennie, A., Ahmedzai, S., Dono, J.-A. & Ormerod, E. (2005). Pet ownership and human health: a brief review of evidence and issues. BMJ 331, 1252-1254.

Prentice, A. M. & Jebb, S. A. (1995). Obesity in Britain: gluttony or sloth? Bmj 311, 437-439.

Reilly, J. J., Armstrong, J., Dorosty, A. R., Emmett, P. M., Ness, A., Rogers, I., Steer, C. & Sherriff, A. (2005). Early life risk factors for obesity in childhood: cohort study. Bmj 330, 1357.

Westgarth, C., Pinchbeck, G. L., Bradshaw, J. W., Dawson, S., Gaskell, R. M. & Christley, R. M. (2007). Factors associated with dog ownership and contact with dogs in a UK community. BMC Vet Res 3, 5.

The ALSPAC study includes two different assessments for the presence of tic disorders in the offspring cohort. The first is a screening question for "tics or twitches that he/she [the child] can't control" which is asked in nine of the mother-completed questionnaires between ages 18 months to 11 years. The second, more detailed, tic assessment occurs in the Age 13 mother-completed questionnaire, in which a section entitled "Tics and Unintended Habits" asks five different questions about specific motor and vocal tics (face/head, neck/shoulder/trunk, arms/hands/legs/feet, repeated simple noises/sounds, and repeated words/phrases) as well as two additional questions about the pattern and frequency of these repeated movements. If record linkage or abstracted medical data are available for a subset of the Age 13 children, we will examinethe validity of these two different assessments by correlating questionnaire responses to a clinical diagnosis of TS or CT. While the Age 13 questionnaire will likely be more specific in identifying TS cases, the serial screening questions from age 18 months to 11 years may be able to detect children with chronic tics (those whose mothers endorse the presence of tics in two or more questionnaires spaced greater than 1 year apart) for whom symptoms may have abated by age 13. Since ~7500 mothers completed the study through Age 13 and the prevalence of either TS or CT is approximately 1-2% in the general population, we expect to find 75-150 cases of TS/CT in the sample.

Exposures of interest will include prenatal and perinatal factors reported to be associated with either TS or tic severity in at least one previous study, including birth weight, Apgar scores, paternal age, hyperemesis of pregnancy, increased maternal stress during pregnancy, maternal smoking, alcohol, and caffeine use, as well as obstetrical complications (specifically forceps delivery and neonatal hypoxia). Three to five controls will be selected per case and will be matched based on gender, month and year of birth. Both univariate analysis and multivariate analysis using logistic regression will be performed. We hypothesize that maternal smoking, paternal age and perhaps other environmental variables will be associated with the development of TS/CT in this population.

Aim 2: In the subgroup of ALSPAC subjects with TS and/or CT, examine the non-genetic risk factors identified in Aim 1 for association with comorbid OCD and/or ADHD.

In addition to the above tic assessments, ALSPAC subjects have been screened for DSM-IV diagnoses of OCD and ADHD at three different time points thus far (ages 7, 10 and 14). In this aim, we will evaluate each subject with a chronic tic disorder (TS and/or CT) based on the criteria validated in Aim 1 for the presence of OCD and/or ADHD. We will then perform both univariate and multivariate analyses to test for an association between the presence of comorbid OCD and/or ADHD and the same previously reported prenatal and perinatal risk factors, focusing primarily on maternal smoking, alcohol and caffeine use during pregnancy as well as forceps delivery. We hypothesize that at least one of these variables will prove to be associated with TS-associated comorbidities, similar to the findings observed by Mathews and colleagues (Mathews et al., 2006).

There is major public concern about the well-being of children in the UK. Recently, this concern has been sharpened with a UNICEF 'report card' ranking the UK in the bottom-third for child well-being (United Nations Children's Fund, 2007). The Government's recent agenda reflects this concern, with the Every Child Matters: Change for Children programme of reforms placing a duty on local authorities and key partners to cooperate in order to improve the well-being of children. More information, however, concerning the factors mediating the development of wider well-being in young people is needed. This project proposes to provide an initial investigation into the development of wider well-being in young people through the childhood life course from infancy, through middle childhood to early adolescence. The maturation of the ALSPAC dataset, making available longitudinal detail of psychological and behavioural trajectories of children from birth to 14, offers the opportunity to study a broader spectrum of childhood life course well-being while taking into account socio-economic background, aspects of parenting and the home environment, and the school through a number of developmental dimensions. This work will first attempt to develop indices of well being based primarily on the Development and Well-being Assessment (DAWBA) from 8 and 14 years combining these with other measures collected from parent report, child report and clinical assessments. The indices will consist of separate dimensions of well being: emotional, social, behaviour, and school. For example, for the emotional component, scores will be used for DAWBA Particular Fears, Separation Anxiety 8 to 14, the parent report of Mood and Feelings questionnaire from 8 to 14, as well as items of Strength and Difficulties over the same period. The component for social competences is expected to include DAWBA Social Fears 8 to 14, Skuse Social Cognition 7, 11 and 14, Peer Relations 8 to 14, Bullying and Victimisation age 8 and 11. Measures for earlier childhood will be mapped onto these component areas. The second step in this study will involve modelling predictors of these component scores. This is intended to simultaneously control and test for the relative contribution of factors established in the literature that determine well-being from childhood to early adolescence. We will first examine how children's earlier components of well-being predict their later well-being. This stems from our earlier research (Gutman and Brown, 2008) indicating that children's social competence at age 4 predicted their later involvement in bullying and/or victimisation. We wish to expand this previous research by examining the processes that may mediate the relationship between earlier and later well-being, particularly in the social realm. Previous research suggests that children who have more social difficulties also have lower emotional well-being, which, in turn may contribute to greater problems with their peers and in school (Gutman and Brown, 2008; Gutman and Feinstein, 2008). We expect, therefore, that emotional well-being may mediate the relationship between social competence in early childhood and later social competence in primary school. We are also interested in the role of parenting behaviours in this process. Waylen (2008) found that health changes in ALSPAC affected parents' feelings and attitudes regarding their children and child rearing at 61 months, but socio-economic status was not an influence. Our recent work (Gutman and Brown, in progress) shows that parents' feelings and attitudes used by Waylen (2008) were one of the leading predictors of quality of parent-child interaction at 61 months (Thorpe) in addition to breast feeding and parental social competence. We are interested in testing a model wherein parental health predicts parents' feelings and attitudes, which, in turn, influences parenting and lastly predicts later child well-being, controlling for earlier well-being. We are also interested in examining whether specific developmental periods are more important in determining well-being than others. We expect, for example, that well-being is particularly vulnerable during the transition from primary to secondary school. Protective factors, such as teacher and friend support, may buffer the impact of such transition. We expect, therefore, that those pupils who have better relationships with their peers and teachers may experience fewer negative changes in their well-being during such transitions than other pupils. Lastly, we are interested in how such pathways may be moderated by gender and socioeconomic status. Our research has found that low socioeconomic boys are more likely to experience a trajectory of low and declining well-being compared to other primary school children (Gutman and Feinstein, 2008). Boys are also more likely to engage in bullying behaviours (Gutman and Brown, 2008). Therefore, we might expect that earlier factors such as child social competence are more important for boys than for girls in determining later well-being. This proposal mirrors elements of the ESRC large grant on adolescent development especially the components led by Anna Vignoles and Paul Greg on peer effects and socio-economic impacts. This study complements the larger studies by offering an initial examination of the predictors influencing the developmental trajectory from childhood to early adolescence. This study will be carried out in 6 months and therefore only offer baseline findings to will inform the larger scale investigations. Owing to the different time constraints and different client readership, the methodologies of this proposed study are very different from the exhaustive approach possible in the ESRC study. This proposal therefore aims to control for the primary background factors using regression analyses rather than refine large models using advanced statistical techniques. Our study offers a further benefit from a more constrained study to identify the main effects with publication in a shorter time frame, by spring 2009. Additionally, the DCSF have expressed great interest in less methodological-based description of the main findings of well being trajectories from childhood to adolescence in a format appropriate for a non-specialist policy-based readership and feel that it would make a significant contribution to the development of debate on how the state my intervene most effectively to improve life chances.

The proposed analyses are exploratory in nature and will use simple methods in an attempt to idenitfy groups of children who follow certain dietary patterns throughout childhood. Dietary patterns have been obtained using Principal Components Analysis at the ages of 3, 4, 7 and 9 years in the ASLPAC children (1-3). For each child a continuous score was obtained for each dietary pattern. It is envisaged that there will be children who consistently score highly on individual patterns, e.g. the 'health conscious' or 'processed' patterns over time. On the other hand there are likely to be children whose diets have changed, for example, they may have initially scored highly on the 'processed' pattern and low on the 'health conscious' pattern in early childhood but reversed this trend through mid-childhood. Identifying such groups may be useful for examining the longitudinal associations between diet and a wide variety of health outcomes, by offering an alternative dietary exposure.

The preferred method for assessing trajectories of dietary patterns throughout childhood would be to use a technique such as latent profile or latent trait modelling. However, specialised software is required and time does not allow adequate learning of this application: It is anticipated that preliminary results will be presented at the ICDAM7 conference in June 2009 (abstract deadline is November 13th). We therefore propose to apply cluster analysis to the dietary pattern scores. This technique places individuals into distinct, non-overlapping groups based on the similarity of their dietary pattern scores. We will also investigate grouping children "by hand", based on quintiles of dietary pattern scores and compare the results obtained.

Depending on the results we hope to investigate the associations between a wide variety of variables and the 'trajectories' obtained, these will include social and parental lifestyle factors, feeding difficulties and other behaviours. This exploratory analysis will also set the scene for future analyses using the optimal methods of latent profile/trait modelling.

1. K North, P Emmett and the ALSPAC Study Team. Multivariate analysis of diet among three-year old children and associations with socio-demographic characteristics. European Journal of Clinical Nutrition 2000; 54: 73-80.3.

2. K Northstone, P Emmett and the ALSPAC Study Team. Multivariate analysis of diet in children at four and seven years of age and associations with socio-demographic characteristics. European Journal of Clinical Nutrition 2005; 59: 751-760.4.

3. K Northstone, PM Emmett. Are dietary patterns stable throughout early and mid-childhood? A birth cohort study. British Journal of Nutrition 2008. AOP: doi: 10.1017/S0007114508968264.5.

According to the foetal programming hypothesis, factors influencing growth and development in the prenatal and early postnatal periods may affect vulnerability to chronic diseases (e.g., type 2 diabetes, coronary heart disease, etc.). Animal studies suggest that the neuroendocrine system, in particular the hypothalamic pituitary adrenal (HPA) axis, is the primary biological pathway through which this occurs. This has prompted interest in the factors that may affect the foetal HPA axis in humans. Several plausible candidates exist including: prenatal maternal factors that may affect the intra-uterine environment (e.g., depression, smoking etc.) and genes affecting foetal development by regulating the maternal axis (e.g., glucocorticoid receptor and 11beta-hydroxysteroid dehydrogenase (11beta-HSD) isoforms1 and 2 genes). However, the human evidence regarding foetal programming of the HPA axis remains equivocal. This is due, in part, to (i) limitations of existing approaches to assessing the human neuroendocrine system and (ii) a paucity of relevant data on potential environmental determinants of prenatal maternal HPA activity.

This study has sought to overcome these limitations by undertaking a more rigorous assessment of the neuroendocrine system than has previously been possible, through the implementation of the CO2 test. This test provides measures of HPA, sympathetic and parasympathetic reactivity and recovery to a stressor. Furthermore, as our enquiry is based in the ALSPAC (Avon Longitudinal Study of Pregnancy & Childhood) cohort in which environmental data are available on mothers and their offspring, we will be able to examine the relationship between foetal and early life factors (in both mother and offspring) & neuroendocrine activity in offspring at 16 years.

Data we have collected/already have approval to access (ALSPAC proj. B277):

An acute novel stressor (the 'CO2 test') was used in a sub-sample of ALSPAC (N=142). The test involved a single inhalation of 65% oxygen/35% CO2. This acts as a transient physiological challenge activating the key stress-responsive neuroendocrine systems. Consequently, the task produces increases in cortisol, blood pressure and plasma noradrenaline concentrations and an immediate reduction in heart rate that precedes the rise in blood pressure.

In order to explore inter-individual differences in sympathetic and parasympathetic reactivity and recovery, blood pressure and heart rate were recorded every minute from 5 minutes prior to the inhalation and for the 5 minutes post inhalation. Heart rate variability was recorded by the use of a Polar watch over this same time period as the R-R intervals provide assessments of the dynamic vagal regulation of the heart and dynamic changes in baroreceptor sensitivity. HPA activity was captured by the measurement of salivary cortisol (using salivettes) immediately pre-inhalation (-1 minute) and 10, 20, 30 minutes post-inhalation.

In order to control for factors known to affect salivary cortisol: all analyses will allow for time of day when samples were collected and stage in menstrual cycle will be considered for inclusion in the analysis. Participants were also asked to refrain from food and caffeine for at least 1 hour prior to the CO2 task until the final saliva samples have been taken.

In addition 2 psychological measures were administered prior to the CO2 test, the profile of mood states for adolescents (POMS-A) and the 10 item perceived stress scale (PSS-10). This was necessary to allow for inter-individual differences in mood on the day of the stress test.

Existing data on mothers and children will be collated as previously agreed. For mothers, this will focus on prenatal self-reports of social and emotional exposures captured through: (i) indices of quality of social environment; (ii) social support; (iii) distress and (iv) stressful life events. Data on health behaviour exposures (i.e., diet, smoking and alcohol consumption) will also be collated to examine the extent to which the effects of social and emotional exposures on offspring neuroendocrine activity are mediated by health behaviours.

For children, information will be extracted on birth weight, ponderal index and birth weight corrected for gestational age. While the effects of puberty on the neuroendocrine system are not expected to be significant, we will collate growth information from birth and, for girls, data on start of menses so that the effects of pubertal development on neuroendocrine outcomes can be examined.

What biological samples we would like access to and why:

We are seeking to extend the scope of our original application by requesting access to the fasting bloods samples for the 142 volunteers who participated in the stress test at the most recent recall of the cohort (2007/08). We propose to assay plasma cortisol from these samples in order to address the following issues:

1. Explore the relationship betweeen a measure of basal HPA axis function (i.e., plasma cortisol) and measures of HPA reactivity and recovery (i.e., salivary cortisol responses to the CO2 stress test).

2. Examine the relationship between foetal and early life factors and plasma cortisol and whether and how this relationship differs from relationships observed with salivary cortisol.

In addressing these issues, we will also be able to explore the 'added value' conferred by 'stress testing' in this cohort and the most appropriate primary outcomes for future research.

Thus, we are requesting access to 25 ul of the plasma samples collected in heparin containers, from the 142 participants who have participated in our preliminary study. These assays would be conducted in Clinical Biochemistry at the University of Bristol under the supervision of Professor Stafford Lightman.

The size of the placenta at birth has been shown to predict blood pressure levels and hypertension in later life. In some studies small placental size predicts raised blood pressure. In other studies raised blood pressure is predicted by high placental weight in relation to birthweight. This latter association is thought to result from compensatory placental expansion in mid gestation. It is well known that if a pregnant ewe is undernourished the fetal lamb is able to extend the surface area of its placenta to extract more nutrients from the mother. This response, however, can only occur if the ewe was well-nourished at the time of conception. Compensatory placental enlargement results in a larger lamb at birth than is seen in pregnancies where the ewe was well-nourished throughout. Inducing placental enlargement in mid-gestation is standard practice in sheep farming.

Almost all published studies in humans are based on placental weight at birth. We have examined the effects of placental surface area in the Helsinki Birth Cohort Study. In the past it was recognised that the surface of the placenta is oval rather than round. In the Helsinki study all placentas were weighed at birth and two diameters of the surface were recorded, a maximal one and a lesser one at right angles to it. Using these diameters it is possible to estimate the area and shape of the placental surface and its thickness. We find that the surface area predicts hypertension more strongly than the weight. Both a small and a large placental area predict the disorder. The association with a large placental area is only found in the offspring of tall mothers, which is consistent with the observations in sheep.

We are requesting permission to photograph the surface of all stored placentae, so that the surface area can be estimated. We recognise that storage will have shrunk the placentae, but one of us is a placentologist and is familiar with the issues. In the proposed study the predictors will be placental weight, the maximal and lesser diameter, measured surface area and measured thickness, body size at birth, length of gestation and mother's body size. The outcome will be systolic and diastolic blood pressure. The analyses will take into account child's age, sex and body size at the time of blood pressure measurement, together with the family's socio-economic status.

We estimate that it will be possible to photograph 300 placentas a week. The Director has told us there are 9,000 placentae and we should therefore be able to complete the photography in 30 weeks.

1) Strabismus (Squint)

Strabismus (squint) is a misalignment of the eyes so that they are looking in different directions. It is one of the most prevalent neurological abnormalities seen in children; 2% - 4% being affected in white populations. It is associated with reduced ability to combine the images from each eye and often with reduced vision in one or both eyes. Surgery may be required to alleviate double vision, an abnormal compensatory head posture or most frequently for social and interpersonal difficulties.

There are several types of strabismus. ie different strabismus phenotypes, and there is evidence to suggest heritability for most of these. However, only for some of the rare (approx 5% cases) phenotypes involving incomitant strabismus (ie dependent on the direction of gaze) have specific genetic loci been described (Engle et al). These genes also affect other aspects of brain development. Far more prevalent are the comitant convergent or divergent strabismus phenotypes. These differ in prevalence between ethnic groups, are seen with more concordance in monozygotic than dizygotic twins and are seen more often in individuals with a family history of the same condition (Podgor et al).

There are, however, no candidate genes identified so far which map to more than one family. No Genome Wide Association (GWA) studies for strabismus have been reported to date. Understanding the genetic factors which contribute to keeping the eyes straight will help early identification and treatment of the many affected individuals as well as potentially providing important information about ocular and brain development.

ALSPAC is uniquely well placed to support a small but important study in this area because the study has accurate phenotypic data (at age 7 yrs) enabling the types of strabismus and related defects (eg amblyopia) to be clearly identified and GWA data on a subset of participants. We have already published data on risk factors for the two most frequently seen types of strabismus -convergent (211 children, 2.8%) and divergent (45 children, 0.6%), including an adjusted Odds Ratio (OR) of 2.37 for a positive family history as a predictor of convergent strabismus, after accounting for a key known environmental risk factor (prematurity) (Williams et al 2008).

Thus we will use existing 7-yr vision data ("clinically significant convergent strabismus" as in ref 3, plus amblyopia and or binocular vision data as needed), plus the GWA data

2) Stereopsis (binocular vision)

Stereopsis (depth perception) is one benefit of the fact we have two eyes, separated on the head, from which information can usefully be combined. Other manifestations are motor fusion (the ability to move the eyes separately to keep the object of regard in the visual axis for each eye), diplopia and binocular rivalry. The mechanisms for development of binocular vision remain poorly understood but may well be highly conserved as many species have evolved with two eyes in the front of the head.

Evidence from identical twin studies shows precision of stereoscopic depth perception may be heritable (Wilmer et al). That prevalence of primary monofixation syndrome in parents of children with congenital esotropia (Scott et al) is higher than the general population also supports the hypothesis that a hereditary abnormality in disparity sensitivity may be associated with infantile esotropia (convergent squint).

There are no GWA studies in this area. Some metabolic pathways have been linked to the development of stereopsis or binocular vision eg those relating to plasticity in the visual cortex (Cnops et al) and it can be conjectured that those relating to the metabolism of key neural components such as docosahexaenoic acid (DHA) may be implicated as there is evidence (from ALSPAC) that early exposure to DHA affects stereopsis development (ref 5)

ALSPAC data are ideal for an exploratory GWA analysis of the genetic predictors of stereopsis. We have assessed stereopsis at ages 7 and 11 using a well-established clinical test (the "Randot") and at 12 (n = 2000) using a newly designed stereotest which has been designed to avoid some of the flaws in the Randot and other more established tests. In addition ALSPAC has data on related factors such as strabismus, which may need to be included. Identification of genes involved in this important and basic cognitive function could enhance our understanding of brain development in general and of a range of vision problems, with better identification and treatments made possible. Thus we will use the stereo data and related ocular data as needed, plus the GWA data.

References:

1. Engle. Arch Ophthalmol. 2007;125(2):189-195

2. Podgor et al Arch Ophthalmol. 1996 Jun;114(6):739-44.

3. Williams et al Br J Ophthalmol 2008; 92: 959-964

4. Cnops et al Cerebral Cortex 2008 18(5):1221-1231

5. Williams et al Am J Clin Nutr 2001;73:316-22.

6. Wilmer et al Journal of Vision 2007;7:831

7. Scott et al J Pediatr Ophthalmol Strabismus 1994;31:298-301; discussion 302

A genome-wide association (GWA) study that aimed at studying loci associted with childhood obesity was carried out with the Singapore Cohort study of the Risk factors for Myopia (SCORM) samples (n=1004, age 9) using the Illumina 550 SNP chip. After initial genotyping and QC of SNPs and samples, imputation based on HapMap East-Asian samples (Chinese and Japanese) was carried out to increase coverage of SNPs detected in this study. Subsequent association analysis on zscores of BMI revealed several interesting SNPs from genes such as the apolipoprotein B mRNA editing enzyme and the tubby gene, with top p-values in the range of 10-6. Association analysis were also conducted on 695 samples who had relevant measures at birth (birth-weight, birth-length and head circumference), to detect genetic loci associated with obesity at birth.

However, as only a modest sample size (n=1004 at age 9) was available from the SCORM dataset it could be likely that important SNPs fail to reach higher levels of significance and are thus missed from the analyses. As such performing a meta-analysis with the SCORM GWA dataset and the ALSPAC GWA dataset would be useful for both increasing power to detect SNPs that are associated with childhood obesity and possibly reveal more relevant SNPs when they turn up in both these children datasets.

The ALSPAC GWA data carried out with individuals at a similiarly young age (age 11, n=1500+) on the Illumina 330 SNP chip, with relevant obesity measures (height and weight to calculate BMI, birth weight and birth length) and suitable covariates (gender, mother's education status, father's education status) would be used for the meta-analysis with the existing SCORM BMI zscore association results. This ALSPAC dataset would be put through quality control measures to filter of samples based on on call-rate (less than 95%) and gender discrepancies. Subsequently, ethinic confounders would be removed using using principal component analyses. Similarly SNPs would be filtered off based on call-rate (less than 95%), minor allele frequency (less than 0.5%) and Hardy-Weinberg equilibrium (pval less than 1O-7). Subsequently, additional SNPs would be imputed based on HapMap samples to increase coverage of SNPs and overlap between the existing SCORM imputed dataset. Genotype calling for impuation would be based on a posterior probability threshold of 90%. To further ensure confidence of selecting imputed SNPs, those that are solely imputed from both datasets and without any typed SNPs in the region (1.25Mb from the imputed SNP in both datasets) would be filtered off.

SNPs that overlap in both the datasets would be used for detecting association with zscores of BMI and relevant measures at birth for the ALSPAC dataset. This analysis would be done using the linear trend test under various models (additive, recessive, dominant and genotypic) and controlled for relevant covariates such as gender, using the PLINK genome-wide association analysis toolset. Subsequently, individual SNP results (beta, standard error, variance and p-values) from SCORM and ALSPAC datasets would be extracted and used to derive pooled estimates and overall p-values assuming a fixed effect model, with the inverse variance-weighted method. The pooled estimate for the 2 studies would be derived using the formula ? = ∑ w*beta / ∑w (where ? = pooled estimate, w = inverse variance weight of each study and beta= individual beta of each study), which incoporates a weightage for each SNP from the individual study into the overall estimate. Measures of heterogeneity, Cochran's Q and I square statistics would also be generated to gauge the level of heterogeneity between the 2 studies for each SNP. Subsequently, gene annotation of top hits that turn up from this meta-analysis exercise would be carried out to reveal any functional effects the SNP may have on the gene product.

As a follow-up step to the meta-analysis, the remaining subset of ALSPAC samples at age 11 could be used for a replication study and confirm obesity association of possible novel hits that are revealed from the meta-analysis. A tagging SNP approach would be used to best cover the top hits (pval less than 10-4 from the meta-analysis) and the suitable set of SNPs could be genotyped in the Illumina Golden-gate mutiplex genotyping platform.

Concept Specific measures Source Time points

Obesity Anthropometry measures Children in Focus Birth to 12 months

Obesity -Anthropometry measures Focus Clinic Sessions Age 7 to 11

- Measures

-Food and activity

-Health utilities index

-nutrition

AIMS

Primary

1. To test the hypothesis that maternal concentrations of anti-angiogenic factors (i.e. sFlt-1, s-ENG) are reduced and pro-angiogenic factors (i.e. PlGF) are elevated in women who subsequently developed breast cancer compared with women who did not develop breast cancer.

Secondary

2. To test the hypothesis that maternal concentrations of reproductive hormones including estradiol, androstenedione, testosterone, prolactin and hCG differ between women who subsequently developed breast cancer compared with women who did not develop breast cancer. (progesterone, afp and IGF axis also interesting but have been looked at previously.)

3. if blood pressure is available To test the hypothesis that maternal concentrations of anti-angiogenic (i.e. sFlt-1, s-ENG) and pro-angiogenic (i.e. PlGF) factors mediate the association of high MAP, systolic blood pressure increases between the second and third trimesters and breast cancer risk. Also, if possible placental infarcts.

4. if data are available To test the hypothesis that MAP, blood pressure changes and placental characteristics are associated with risk of all cancers, and particularly site-specific tumors.