Proposal summaries
B1082 - The impact of fathers age on offspring intelligence development and health - 09/12/2010
Changing patterns in education, employment and marriage along with improved reproductive technologies mean that the average age of childbearing in men and women is increasing while the average family size is falling. Although there are potential advantages to these trends, particularly in terms of financial security, there are also disadvantages, many of which are poorly understood at present. The detrimental effect of increasing maternal age on the health and development of offspring is widely recognised but the effect of increasing paternal age remains largely unexplored. However, there is emerging evidence that pregnancies conceived to older men are more likely to end in spontaneous abortion and that their children may be less intelligent, and be at higher risk of adverse outcomes and developmental disorders independent of the age of their mother.1-2 Moreover, these increased risks are not confined to childhood and advanced paternal age has also been reported to be associated with a number of adverse outcomes in adult offspring, most notably schizophrenia and certain cancers (principally breast, prostate and leukaemia).3-5 It is hypothesised that these associations may be due to the accumulation of chromosomal aberrations and mutations during the maturation of male germ cells.6 Later reproduction is also leading to a trend towards smaller families. While it is known that morbidity and mortality often rise with increasing number of siblings, there is also evidence to suggest that children from smaller families, and in particular only children, have a health experience that is out of line with anticipated gradients with number of siblings, specific examples being high blood pressure and asthma.7-8
Although the individual risks from having an older father or fewer siblings may be low, current trends in childbearing mean that these will increase at a population level and it is important that the risks are fully understood to allow appropriate education and to inform social policy changes. The aim of this project is to systematically investigate the effects of increasing paternal age and decreasing family size on the health and development of offspring throughout the life course. Systematic reviews of the available evidence will be carried out along with original research utilising a wide range of existing datasets.
Research plan
The project will involve a diverse range of existing large, good quality prospective datasets that cover the whole of the life-course, in different populations, over a range of calendar periods. These data sets include: ALSPAC, ProtecT, Swedish record linkage studies, Midspan Family Study, Glasgow Students Cohort, Caerphilly Cohort, and Boyd Orr Cohort. Parental age is available in all cohorts, along with a wealth of additional relevant data such as: mortality (Swedish, Midspan, Glasgow Students), cancer (ProtecT, Swedish, Midspan, Glasgow Students), offspring IQ (ALSPAC, Swedish), other mitogenic exposures (ALSPAC, Midspan), and details of family formation (ALSPAC, Swedish, Midspan, Glasgow Students).
This wide range of studies will form a consistent and complementary body of evidence on the short and longer-term effects of paternal ageing and smaller family size on offspring intelligence, development and health, and will also allow identification of critical periods in the life-course and investigation of how these interact with other risk factors. Examples (not an exhaustive list) of some specific hypotheses of interest include:
- Is greater paternal age associated with an increased risk of neuro-developmental markers of future mental disorder such as low intelligence or delay in obtaining motor milestones? How important is intelligence in setting an individual's life-course in terms of education, future financial attainment and long-term health? These questions will be explored using ALSPAC, Swedish and other datasets.
- Is increasing paternal age is associated with an increased risk of cancer? This will be examined in ProtecT (prostate cancer), Swedish (leukaemia, lymphoma and testicular cancer), and other datasets.
- How do offspring risks from mitogenic exposures in the father, e.g. smoking, alcohol, diet and occupation, combine with those from advancing paternal age? This will be explored using ALSPAC, Midspan and other datasets.
* It has been suggested that poorer health in only children may be a result of a more sedentary lifestyle. However, there are alternative hypotheses: Are only children more likely to be born to older parents and have a poorer health experience as a result? Or are only children the result of poor reproductive experience with hereditary factors responsible for poorer health? (e.g. high blood pressure in pregnancy is associated with high blood pressure in offspring; if a negative experience in pregnancy (e.g. eclampsia) results in a decision not to have any further children then this could explain the apparent pattern of increased blood pressure in only children) These hypotheses will be investigated using ALSPAC and other data on maternal health in pregnancy.
* To what extent are paternal age and family size associations confounded with each other and with other factors, in particular, parental intelligence, maternal age and changing social class? The availability of a wide range of datasets from across the life-course will allow a thorough investigation of the impact of these inter-correlated confounding variables through direct statistical analysis, appropriate simulation work and alternative study designs, e.g. in the Swedish studies data are available on both biological and step-fathers; if associations are restricted to biological father's age then, assuming that parents tend to be similar in age, this will provide evidence that the relationship is independent of maternal age.
The specific assemblage of different cohorts provides additional strength and value to the proposal. For example, the use of cohorts, some historical, from a range of calendar periods will allow a comparison of associations over time and insight into the impact of changing attitudes and societal trends in the reasons for delayed parenthood. In addition, several cohorts (e.g. ALSPAC, Glasgow Students) have repeated sweeps of data collection and these will be used to explore the impact of missing data on the results and conclusions of the analyses.
References
1. Bray I, et al. Advanced paternal age: How old is too old? J Epidemiol Community Health 2006;60:851-3
2. Cannon M. Contrasting Effects of Maternal and Paternal Age on Offspring Intelligence The clock ticks for men too. PLos Med 2009;6
3. Sipos A, et al. Paternal age and schizophrenia: a population based cohort study. BMJ 2004;329:1070-3
4. Zhang Y, et al. Parental Age at Child's Birth and Son's Risk of Prostate Cancer. Am J Epidemiol 1999;150:1208-12
5. Hemminki K, Kyyronen P. Parental age and risk of sporadic and familial cancer in offspring: Implications for germ cell mutagenesis. Epidemiology 1999;10:747-51.
6. Crow JF. The origins patterns and implications of human spontaneous mutation. Nat Rev Genet 2000;1:40-7
7. Okasha M, et al. Determinants of adolescent blood pressure: findings from the Glasgow University student cohort. J Hum Hypertens 2000;14:117-24
8. Rona RJ, et al. Association between asthma and family size between 1977 and 1994. J Epidemiol Community Health 1999;53:15-9
B1083 - Is pet ownership associated with childhood asthma - 02/12/2010
We propose to examine the association between pet ownership, allergic sensitization and asthma, within a cohort of children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC). On the basis of the findings of previous studies, we hypothesise that childhood household pet ownership will be associated with childhood asthma and asthma/atopy symptoms, and that these associations will be moderated by a number of factors including child genotype, time and duration of exposure, species of exposure (cats, dogs, other pets), and associated parental behaviours (domestic hygiene practices). By making use of an existing large-scale database, which has detailed records of pet keeping in the prenatal and early-to-middle childhood period, as well as extensive information concerning potential confounding factors, we propose to conduct the most rigorous study to date of the relationship between pet keeping and childhood asthma morbidity.
5.2. Hypotheses
We hypothesise that household ownership of cats, dogs and other pets, prenatally, in infancy and in early-to-middle childhood will be associated with:
1. Sensitisation to aeroallergens at 84 months (7 years);
2. Wheezing illnesses during early childhood up to 81 months of age (6 years 9 months);
3. Doctor-diagnosed asthma by 96 months(8 years);
4. Lung function and bronchial responsiveness at age 96 months (8 years).
We additionally hypothesise:
1. that pet ownership effects on sensitisation to aeroallergens, wheezing illness and asthma are independent of other social and lifestyle variables;
2. age and duration of pet exposure, number and types of pets owned (e.g. cats & dogs, cats only, dogs only, other furry pets., etc.) will moderate these associations;
3. parental hygiene practices (e.g. cleaning frequency and use of household cleaning products) will moderate these associations.
5.3. The study population - The Avon Longitudinal Study of Parents and Children (ALSPAC):
Child health questionnaires: Maternal reports of their children's health were collected using questionnaires issued six months after birth and at annual intervals thereafter. Mothers were asked if, during the preceding 12 months (6 months for the initial questionnaire), their child had 'wheeze with whistling on his/her chest when s/he breathed'. If they answered, "Yes," they were asked to complete a number of supplementary questions detailing the frequency of wheezing episodes, duration of wheezing, associated symptoms of breathlessness or fever, and what (if anything) provoked the wheezing. At 91 & 103 months of age (7 1/2 & 8 1/2 years approximately) they were also asked to report if a 'doctor had ever diagnosed (their) child as having asthma'. From responses to these questions, we reported differences in the epidemiological associations of wheezing illnesses in young children (Sherriff et al., 2001) and we have been able to map these symptoms to early wheezing phenotypes reported from the Tucson Children's Respiratory Study (Martinez et al., 1995).
Household pet ownership questionnaires: Details of pets kept in the household of the child were reported by mothers within the same questionnaires used to obtain details concerning child and maternal health. Respondents were asked "Do you have any pets?" and "How many of the following pets do you have?". Pet types listed included cats, dogs, rabbits, rodents (mice, hamster gerbil, etc.), birds (budgerigar, parrot etc.) and 'other' pets. Two additional categories of pet type (fish and turtles/tortoises/terrapins) were added when the cohort children were 2 years of age and onwards. Pet questions were asked prenatally (when the mother was between 8 and 32 weeks pregnant), at 8 months, and at 21, 33, 47, 85 and 97 months (approximately 2, 3, 4, 7 and 8 years).
Additional Questionnaire information: Measures of numerous potential confounds and moderators of pet ownership-asthma associations were collected using the same and additional maternal questionnaires administered both before birth and at yearly intervals thereafter. ALSPAC variables that have previously been found to be associated with variations in pet ownership include: gender of child, number of people in household, presence of older sibling, type of dwelling, maternal age, maternal and paternal social class, presence of other species of pet and maternal and paternal education (Westgarth et al 2010). ALSPAC variables that have previously been found or are thought to be to be associated with childhood asthma include: maternal and paternal smoking (including total number of hours of exposure to tobacco smoke per week in home), environmental pollution, use of household cleaning products, maternal anxiety during pregnancy, maternal and child diet, child activity levels (Shaheen et al 2002, 2004, 2005; Sherriff et al 2005, 2010; Cookson et al 2009).
Child clinic assessments: A range of clinical and behavioural data were collected between 91 and 103 months of age (approx. 7-8 years), including skin prick test responses to cat (felis domesticus), house dust mite (Dermatophagoides pteronyssinus), and mixed grass pollen. A subsample of the clinic population (approx 2500 children) was also assessed by skin prick test responses to other animals commonly kept as domestic pets (dog, horse, mouse, rabbit, guinea pig and hamster). For genetic analyses, DNA was extracted from maternal blood and from infant cord blood samples at birth, and later supplemented by blood samples drawn at approx. 91 months; such samples are currently available for approximately 10,000 mothers and 10,000 children.
The ALSPAC population is broadly representative of the rest of the British population based on 1991 census data, although participants in the study were more likely to live in owner-occupied accommodation and less likely to have a non-white mother (ALSPAC 2.6%; population of Avon 1970 4.1%; UK census 1991 7.6%). In common with all population-based longitudinal studies, there has been incomplete retention of the cohort with attrition biased towards the more socially disadvantaged groups. However, over 11,000 children actively participated in the study to age 96 months (8 years), providing a large dataset with which to assess antenatal and early life effects on the development of childhood asthma and wheeze.
5.4. Health outcomes (see Hypotheses):
1. Sensitisation to aeroallergens was assessed by skin prick test responses to cat (felis domesticus), house dust mite (Dermatophagoides pteronyssinus) and mixed grass pollen at the age of 91 months (approx. 7 years). A positive skin prick test response (greater than 2mm weal) to any of these three allergens identifies over 95% of atopic children in our population (i.e., positive skin test to any allergen).
2. Doctor diagnosed asthma at approx. 96 months (8 years) was assessed from response to questionnaires completed by the mother.
3. Wheezing illness during early childhood is based on a novel approach to wheezing phenotype characterisation developed by our group from longitudinal analyses of wheeze data using latent class models (Henderson et al 2008). This analytical approach defines the minimum number of wheezing trajectories (classes) that best describe the data and is robust to missing data, providing wheeze phenotype classifications for 11,625 of the study population from birth through 81 months. The best fitting model to our data suggested the presence of 6 classes (5 wheezing classes plus non-wheezers). We have named these five wheezing trajectories Transient Early, Prolonged Early, Intermediate-onset, Late-onset and Persistent Wheezing as shown in the legend. These include classes that have been suggested to be associated with abnormalities of early (including intrauterine) airway development (Stocks and Dezateux, 2003). Our analyses showed strong associations between intermediate and late onset wheezing with bronchial hyper-responsiveness and of intermediate onset and persistent wheezing with allergy to cat and house dust mite. Therefore, it appears that these classes are representative of discrete wheezing phenotypes in early childhood that may have differing natural histories and aetiology (Henderson et al 2008).
4. Lung function and bronchial responsiveness were assessed at a research clinic at approximately 103 months. Spirometry was performed according to American Thoracic Society criteria for acceptability and reproducibility (American Thoracic Society, 1995). Measurements were quality controlled to ensure appropriate selection of the optimal curve from which lung function variables (FEV1, FVC, MMEF, FEF50, FEF75) were derived. Each variable was converted to a scale of gender- age- and height-adjusted standard deviation units based on log-linear regression against age and height, for boys and girls separately and then combined across genders (Chin and Rona, 1992). After completion of satisfactory baseline lung function measurements, bronchial responsiveness to methacholine was measured in consenting children (n=5000) according to the rapid method of Yan et al, (1983) using hand-operated glass nebulisers. For each participant, we measured forced expiratory volume (FEV1) post-saline inhalation (baseline) and 1 minute after each of a sequence of cumulative doses of methacholine.
B1078 - Early Adversity Psychological Functioning and Cardiovascular Risk in Youth Fellowship - 22/11/2010
An expanding literature has documented that adverse childhood experiences are associated with increased risk for a broad range of chronic diseases later in life, including cardiovascular diseases (CVD) (Felitti, Anda et al. 1998; Galobardes, Lynch et al. 2004). There is growing interest in clarifying the physiological mechanisms that link early experiences to health later in life (Taylor 2010); however, the majority of existing studies on this topic are retrospective and have a large window of time between the time of exposure and assessment of cardiovascular risk factors or health outcomes (Miller, Chen et al. 2009). Recent improvements in our understanding of atherosclerosis, and technologies to detect early indicators of CVD, have made it possible to identify risk factors among children and adolescents (Groner, Joshi et al. 2006). However, few studies have examined the association between early life adversity and CVD risk factors that emerge during the child and adolescent period. And, among existing studies, the majority have focused on socioeconomic factors (Batty and Leon 2002; Howe, Galobardes et al. 2010) to the exclusion of other types of stress exposures (e.g., family conflict, abuse, or acute stressful events). A related short-coming is that we have a limited understanding of the role of psychological health in the relationship between early adversity and development of CVD risk factors, despite substantial evidence that exposure to adversities negatively affects child mental health (Repetti, Taylor et al. 2002). The goal of the research described in our proposal is to address these gaps in knowledge by considering a range acute and chronic family-level adversities in relation to pro-inflammatory markers (CRP and IL-6) and blood pressure (BP) measured during childhood and adolescence, and to examine the potential role of child mental health within this relationship.
B1076 - The relationship between autistic spectrum traits and psychotic symptoms in the ALSPAC birth cohort - 15/11/2010
The social disabilities described in autism are often reminiscent of classic descriptions of social disinterest and emotional coldness of schizoid personality types. Clinicians often report encountering brief psychotic episodes in people with autism spectrum disorders (ASDs) additionally many adults with ASD have had a 'misdiagnosis' of schizophrenia, particularly before the 1980s when autism was introduced in classification systems. Both disorders are defined by deficits in interpersonal relationships, and social skills1;2 frequently displayed as active and passive social withdrawal. Also it has been suggested that both disorders may be considered as existing on a continuum ranging from mild symptoms to clinical disorder3;4. Mild symptoms of both disorders are prevalent in community samples3;5 Theoretically it has been suggested by Crespi & Badcock6 that autism and psychosis are diametrically opposite disorders of the social brain, (the areas of the brain that are associated with social information processing). They suggest that austim is characterised by hypo-development of of social cognitive skills and that psychosis is characterised by hyper-development of these skills. There is reliable evidence for social cognitive deficits in both disorders7;8. There have been a few previous studies on social cognition9-11 12which have compared small clinical samples of both groups. These studies have been cross-sectional and some have included healthy comparison groups. The findings of these studies have been mixed with some studies suggesting similar deficits and others finding differences. There have been no previous studies using longitudinal or cohort data.
If there is a true overlap between autistic spectrum and psychosis spectrum disorders one would expect to find an association between autistm spectrum traits and psychotic symptoms. This study aims to investigate these links in the ALSPAC birth cohort using previously identified autistic spectrum traits, a diagnosis of autism taken from medical records, and later experience of psychotic symptoms.
Method
Sample
ALSPAC birth cohort
Study sample
Cohort members who have contributed to the data used to identify autistic spectrum traits and who have participated in the clinical interview to detect psychotic symptoms.
Measures
Primary Outcome
PLIKSi. Information on experience of 12 core psychotic symptoms was collected from cohort members who attended an ALSPAC clinic at the age of approximately 12 years. For the purposes of this study the variable is dichotomously coded as; experience of suspected or definite symptoms over the previous 6 months (yes), and no experience of symptoms over the previous 6 months (no).
Exposure
Four of the seven autistic spectrum traits identifed by Steer & Golding13; verbal ability, language acquisition, social understanding, semantic-pragmatic skills.
A confirmed diagnosis of autism taken from medical records
Other Measures
Demographic measures from the ALSPAC database
Statistical Analysis
Multivariate logistic regression models will be used to examine the association between autistic spectrum traits and later experience of psychotic symptoms
Implications
This analysis will confirm or otherwise any overlap between autism and psychosis in a large community sample. It will generate new information on whether people with autism may be more likely to develop a later psychotic illness, and if so, which autistic traits may be most strongly associated.
Reference List
(1) Green J, Gilchrist A, Burton D, Cox A. Social and psychiatric functioning in adolescents with Asperger syndrome compared with conduct disorder 1. J Autism Dev Disord 2000; 30(4):279-293.
(2) Bora E, Eryavuz A, Kayahan B, Sungu G, Veznedaroglu B. Social functioning, theory of mind and neurocognition in outpatients in with schizophrenia; mental state decoding may be a better predictor of social functioning than mental state reasoning. Psychiatry Research 2006; 145:95-103.
(3) Baron-Cohen S. Two new theories of autism: hyper-systemising and assortative mating. Arch Dis Child 2006; 91(1):2-5.
(4) van Os J, Linscott Ra, Myin-Germeys I, Delespaul P, Krabbendam L. A systematic review and meta-analysis of the psychosis continuum: evidence for a psychosis proneness?persistence?impairment model of psychotic disorder. Psychological Medicine 2009; 39(02):179-195.
(5) Horwood J, Thomas K, Duffy L, Gunnell D, Hollis C, Lewis G et al. Frequency of psychosis-like symptoms in a non-clinical population of 12 year olds: Results from the Alspac birth cohort. European Psychiatry 2008; 23:S282.
(6) Crespi B, Badcock C. Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences 2008; 31(03):241-261.
(7) Muris P, Steerneman P, Meesters C, Merckelbach H, Horselenberg R, van den HT et al. The TOM test: a new instrument for assessing theory of mind in normal children and children with pervasive developmental disorders 1. J Autism Dev Disord 1999; 29(1):67-80.
(8) Sprong M, Schothorst P, Vos E, Hox J, van Engeland H. Theory of mind in schizophrenia-metanalysis. British Journal of Psychiatry 2007; 191:5-13.
(9) Bolte S, Poustka F. The recognition of facial affect in autistic and schizophrenic subjects and their first-degree relatives 6. Psychol Med 2003; 33(5):907-915.
(10) Craig JS, Hatton C, Craig FB, Bentall RP. Persecutory beliefs, attributions and theory of mind: comparison of patients with paranoid delusions, Asperger's syndrome and healthy controls. Schizophrenia Research 2004; 69(1):29-33.
(11) Pilowsky T, Yirmiya N, Arbelle S, Mozes T. Theory of mind abilities of children with schizophrenia, children with autism, and normally developing children. Schizophrenia Research 2000; 42:145-155.
(12) Couture SM, Penn DL, Losh M, Adolphs R, Hurley R, Piven J. Comparison of social cognitive functioning in schizophrenia and high functioning autism: more convergence than divergence 1. Psychol Med 2010; 40(4):569-579.
(13) Steer CD, Golding J, Bolton PF. Traits contributing to the autistic spectrum 2. PLoS One 2010; 5(9):e12633.
B1074 - ARIES - A multigenerational prospective resource for integrating genetic epigenetic and dense phenotypic measures from birth to 18 - 15/11/2010
We will obtain genome-wide white blood cell methylation data on 1000 mother-child pairs in the Avon Longitudinal Study of Parents and Children. Mothers' DNA was obtained during pregnancy and 18 years later and offspring DNA from cord blood, at age 7 and age 15-18. Genome-wide SNP data are available on all participants and the children of the 1000 mother-child pairs taken included in the present proposal have CNV analysis and genome-wide gene expression data available and whole genome exon sequencing is in progress. 2000 of the offspring will have whole genome exon sequencing, CNV analysis and genome-wide gene expression data. Dense phenotyping on the mothers and their offspring has been completed, with exposure and outcome measures relevant to cognitive development, growth, behavioural patterns, metabolic health and detailed functional, physiological and biochemical assessments. The generation of DNA methylation data will provide unparalleled opportunities for the integration of multi-dimensional biological data in human samples for the benefit of the scientific community. Stored samples of blood, hair, teeth, placentas, umbilical cords and urine are available for further analysis. These data will be curated and made fully available to the scientific community. The resource will address the issue of healthy human development (the cohort are currently in early adulthood) and, in the mothers, the avoidance of age-related decline.
Due to the poor accessibility and availability of DNA from human tissues we will complement the proposed resource with tissue-specific methylation and gene expression analysis in animal (rodent) models (incuding those with diet-induced altered ageing trajectories) which will include WBC DNA methylation to facilitate a direct comparison of WBC epigenetic signatures to those of target tissues. Rodent tissues will be banked and available to undertake fine mapping methylation analysis and gene expression studies of differentially methylated regions identified through analysis of ALSPAC data.
Resource development will be complemented by an overarching bioinformatics arm that will ensure the integration of respective data sets and the development of accessible data formats.. We will also integrate the resource with the Human International Epigenome Consortium (IHEC) to ensure maximal utilisation and added value for the data.
1. Strategic Relevance
Epigenetic studies of readily obtainable material are becoming a central focus of biological research internationally. Epigenetic profiles can serve as exposure markers and as prognostic or predictive biomarkers. ALSPAC is a unique resource in having two-generational data and cord blood samples available, allowing for intrauterine influences, intergenerational transmission, change in methylation from birth through to pre-pubertal and post-pubertal age, and investigation of how methylation patterns predict and change with development. This resource, coupled with studies of the relationship between white cell and other tissue methylation, would be unequivocally world leading.
This resource provides an excellent match with the current "BBSRC Priorities" document. Under "Ageing Research: Lifelong Health and Wellbeing" it is stated that "Evidence increasingly suggests that impaired growth in utero especially when followed by rapid post-natal growth can seriously impair many aspects of health and may influence ageing. The mechanisms by which these early life exposures are mediated are poorly understood. There is a need to encourage research that investigates how early developmental factors may influence health during ageing. Specifically, the challenges are to understand i) how nutritional (and other) exposures are recorded and transmitted through subsequent generations of cells and ii) how this "memory" is translated into altered function in later life." Our study will directly allow these issues to be addressed. In "The Age of Bioscience: Strategic Plan 2010-2015" the 3rd strategic research priority is "Basic Bioscience underpinning health", which the proposed resource will directly address, including the "key research goal [which] is to develop a better understanding of the role of diet and physical activity and the mechanisms by which they affect development and health" and the key priority to "establish greater understanding of how diet affects health throughout life, including epigenetic effects".
B1073 - Beverage consumption and adiposity in childhood and adolescence - 08/11/2010
Currently there is intense interest in the possible role of beverages in increases in childhood obesity, particularly sugar-sweetened beverages (SSB) and artificially-sweetened beverages (ASB). Observational and intervention studies in adults have linked the consumption of SSB to weight gain, insulin resistance and dyslipidaemia [1], and CVD incidence in women [2]. Less research has been conducted on children and adolescents. However, limited evidence suggests that SSB and ASB are associated with weight gain and have metabolic effects in young people [3]. Whereas, fruit juice and milk consumption have not been associated with weight gain in children [4].
There have been concurrent increases in obesity prevalence and sweetened beverage consumption in the UK (as well as Australia and USA) over the past two decades. Therefore, the possible association between sweetened beverage (caloric and non caloric) consumption and the development of adiposity during childhood and adolescence deserves investigation.
Hypotheses to be examined in ALSPAC cohort:
1. SSB intake at an early age (7 yrs) predicts SSB intake throughout middle childhood and adolescence, i.e. SSB intake tracks modestly from early childhood into adolescence.
2. Greater intakes of SSB (sugar-sweetened fizzy drinks, squashes, fruit drinks) are independently associated with the longitudinal development of excess adiposity (fat mass, fat mass index) between the ages of 9 and 15 years.
3. Greater intakes of ASB are independently associated with the longitudinal development of excess adiposity between the ages of 9 and 15 years.
4. Greater intakes of fruit juice are not associated with the longitudinal development of excess adiposity between 9 and 15 years of age.
The following will be considered as potential confounding variables in longitudinal models: sex, age, height, baseline fat mass/fat mass index, pubertal stage, physical activity levels. To investigate whether associations with beverage intake are independent of overall diet quality, we will also adjust for score for an energy dense, high fat, low fibre dietary pattern measured at the same time points as beverages.
Data required -
1. 3 day food diary data collected at 7, 10 and 13 years of age (foods and nutrients)
2. Fat mass measured at 9, 10 and 13 years of age
3. Height, weight and BMI at 7 through 15 years
4. Pubertal development (Tanner Stage) from 9 through 15 years
5. Physical activity (accelerometer data) at 11 and 13 years
6. Age (months) from 7 year follow up through to 15 y follow up
Note that the applicants have the data required for this project'- data were obtained for another ALSPAC analyses being conducted by the applicants examining 'Dietary determinants of fat mass in adolescents' (WCRF funded).
References
[1] Malik VS, Popkin BM, Bray GA, Despres J-P, Hu FB. Sugar-sweetened beverages, obesity, Type 2 Diabetes Mellitus, and cardiovascular disease risk. Circulation. 2010;121(11):1356-64.
[2] Fung TT, Malik V, Rexrode KM, Manson JE, Willett WC, Hu FB. Sweetened beverage consumption and risk of coronary heart disease in women. Am J Clin Nutr. 2009;89(4):1037-42.
[3] Brown RJ, de Banate MA, Rother KI. Artificial sweeteners: a systematic review of metabolic effects in youth. Int J Pediatr Obesity. 2010;5(4):305-12.
[4] Fiorito LM, Marini M, Francis LA, Smiciklas-Wright H, Birch LL. Beverage intake of girls at age 5 y predicts adiposity and weight status in childhood and adolescence. Am J Clin Nutr. 2009;90(4):935-42.
B1072 - Co-morbidity of autistic traits - 08/11/2010
Autism spectrum disorder (ASD) is associated with a range of comorbid psychopathology, with 70% of children with ASD meeting criteria for at least one other mental disorder 1. Furthermore, in the general population even the presence of subtle, sub-clinical ASD traits predicts the presence of additional internalising and externalising difficulties2. This suggests that mildly elevated ASD traits may be implicated in the onset and maintenance of a range of common psychological and behavioural difficulties that carry a significant cost to the individual and those around them. For example, it has recently been shown that the majority of 'severely disruptive' pupils in one UK inner city area have undetected ASD traits3.
The relationship between ASD traits and other internalising and externalising psychopathology has not been delineated in any detail, and a number of areas for investigation exist. Firstly, the cross-sectional analyses used so far cannot address the question of whether ASD traits precede the development of additional psychopathology. There is some evidence that 'social competence' in early childhood does predict later externalising and internalising problems4, but it is unclear to what extent the narrower, ASD-relevant construct of 'social-communication' (measured in ALSPAC by the Social Communication Disorders Checklist [SCDC]) precedes later psychopathology. This issue is relevant to whether or not ASD traits play a causal role in the development of non-ASD psychopathology. Secondly, nothing is known about what factors might moderate the risk conferred by elevated ASD symptomatology. Given the impact of age and gender on the type and degree of risk posed by other types of psychopathology5, it will be useful to consider these variables as potential moderators of the relationship between ASD traits and additional psychopathology. Thirdly, it is unknown whether ASD social-communication traits moderate well known pathways to psychopathology, such as the transition from oppositional defiant disorder to conduct problems6.
Data collected in the ALSPAC study offer a unique opportunity to address these issues, which are of clinical and theoretical importance. We propose using ALSPAC data for the following:
1/. An investigation of the moderating effects of gender and age on the relationship between social communication deficits and additional psychopathology. We will use SCDC data to identify individuals with consistently elevated social communication difficulties in middle and late childhood. We predict males in this group will experience an increase in their externalising psychopathology during adolescence. In addition we predict that females will experience increased internalising difficulties in adolescence.
2/. An investigation of whether social-communication abilities moderate the relationship between earlier oppositional behaviour and later conduct disorder symptoms. We aim to test this hypothesis using a cross-lagged panel design, modelling the relationships between DAWBA-measured oppositional behaviour, hyperactivity and conduct disorder symptoms at 7 and 10, and testing whether these are moderated by an individual's social-communication abilities at 7 years.
1Simonoff E, Pickles A, Charman T, Chandler S, Loucas T, Baird G. Psychiatric disorders in children with autism spectrum disorders: prevalence, comorbidity, and associated factors in a population-derived sample. J Am Acad Child Adolesc Psychiatry 2008 Aug;47(8):921-9.
2Skuse DH, Mandy W, Steer C, Miller LL, Goodman R, Lawrence K, et al. Social communication competence and functional adaptation in a general population of children: preliminary evidence for sex-by-verbal IQ differential risk. J Am Acad Child Adolesc Psychiatry 2009 Feb;48(2):128-37.
3Donno R, Parker G, Gilmour J, Skuse DH. Social communication deficits in disruptive primary-school children. Br J Psychiatry 2010 Apr;196:282-9.
4Bornstein MH, Hahn CS, Haynes OM. Social competence, externalizing, and internalizing behavioral adjustment from early childhood through early adolescence: developmental cascades. Dev Psychopathol 2010 Nov;22(4):717-35.
5Zahn-Waxler C, Shirtcliff EA, Marceau K. Disorders of childhood and adolescence: gender and psychopathology. Annu Rev Clin Psychol 2008;4:275-303.
6Rowe R, Maughan B, Pickles A, Costello EJ, Angold A. The relationship between DSM-IV oppositional defiant disorder and conduct disorder: findings from the Great Smoky Mountains Study. J Child Psychol Psychiatry 2002 Mar;43(3):365-73.
B1069 - Changes in sedentary behaviour and cardiorespiratory fitness during childhood LINKED WITH B0679 - 03/11/2010
Background:
Sedentary behaviour, independent of physical activity, is a risk factor for impaired metabolic health and early mortality (1, 2). A limited number of cross-sectional studies have been conducted to determine if sedentary behaviour is associated with cardiorespiratory fitness (CRF) (3, 4). A study assessing change in sedentary behaviour with regard to CRF levels would advance the understanding of the association between sedentary behaviour and CRF.
Purpose:
The purpose of the study is to determine if high levels of sedentary behaviour are independently associated with CRF levels during childhood.
- Objective 1: To determine if changes in sedentary behaviour from 12- to 16-years influence CRF levels at 16-years, independent of physical activity levels.
- Objective 2: To determine if gender, socioeconomic status and adiposity categories modify the association between changes in accelerometry determined sedentary behavior and CRF levels, as children age over time.
Dependent Variable:
- CRF at 16-years
Independent Variable:
- Sedentary behaviour class trajectory
Covariates:
- Moderate-to-vigorous physical activity at 16-years (MVPA; mins/d(cubed)3600cpm)
- CRF at 9-years
- Fat mass at 16-years (DXA)
- Breast-feeding status
- Social class
- Maternal obesity
- Maternal smoking status
- Birth weight
- Length of gestation
Statistical Analysis:
Trajectory classes of sedentary behaviour will be identified using latent class growth analysis, using PROC TRAJ (SAS version 9.2). Consideration will be given to quadratic models to determine if the trajectory classes are linear or curvilinear over time. The final number of classes identified will be determined by comparing Bayesian Information Criterion (BIC) values. The resulting trajectory classes identified include individuals with the highest posterior probability of belonging to a particular trajectory class (5).
To address objective 1, analysis of covariance (ANCOVA) models will be conducted to determine if CRF levels at 16-years vary among the trajectory class of sedentary behaviour. The first ANCOVA model will adjust for CRF at 9-years-old, and the second ANCOVA model will additionally adjust for daily minutes of moderate-to-vigorous physical activity (MVPA; accelerometer counts >=3600cpm) at 16-years-old. The third model will additionally adjust for fat mass at 16-years. The forth model will additionally adjust for breast-feeding status, maternal obesity, social class and maternal smoking status. The sedentary behaviour trajectory class variable will be treated as a categorical variable throughout and Tukey adjustments will be made to account for multiple comparisons between the trajectory classes.
To address objective 2, interaction terms will be included in the ANCOVA models. Specifically, a gender x sedentary behaviour interaction term will be included to assess if the association between change in sedentary behaviour and CRF is different for boys and girls. Second, a social class x sedentary behaviour interaction term will be included to determine if the association between change in sedentary behaviour and CRF is different between social class categories. Finally, a fat mass x sedentary behaviour interaction term will be included to determine if the association between change in sedentary behaviour and CRF is different depending on the level of fat mass. All analyses will be using SAS (version 9.2) and the statistical significance level of alpha=0.05 will be used throughout.
Proposed Tables/Figures:
- Figure 1: Trajectory classes of sedentary behaviour from 12- to 16-years
- Table 1: Descriptive statistics by sedentary behaviour trajectory classes
- Table 2: Association between sedentary behaviour class and CRF at 16-years
- Table 3: Association between sedentary behaviour and CRF at 16-years by gender, socioeconomic status and adiposity categories
Target Journals:
- Medicine and Science in Sports and Exercise (MSSE)
- British Journal of Sports Medicine
References:
- Katzmarzyk PT, Church TS, Craig CL, Bouchard C. Sitting time and mortality from all causes, cardiovascular disease, and cancer. Med Sci Sports Exerc. May 2009;41(5):998-1005.
- Ekelund U, Brage S, Froberg K, et al. TV viewing and physical activity are independently associated with metabolic risk in children: the European Youth Heart Study. PLoS Med. Dec 2006;3(12):e488.
- Grund A, Krause H, Siewers M, Rieckert H, Muller MJ. Is TV viewing an index of physical activity and fitness in overweight and normal weight children? Public Health Nutr. Dec 2001;4(6):1245-1251.
- Lobelo F, Dowda M, Pfeiffer KA, Pate RR. Electronic media exposure and its association with activity-related outcomes in female adolescents: cross-sectional and longitudinal analyses. J Phys Act Health. Mar 2009;6(2):137-143.
- Andruff HC, N.; Thompson, A.; Gaudreau, P.; Louvet, B. Latent class growth modelling: a tutorial. Tutorials in Quantitative Methods for Psychology. 2009;5(1):11-24.
B1071 - Maternal stress in pregnancy and risk of autistic traits and autism spectrum disorder in offspring - 02/11/2010
Several converging lines of evidence point towards the role of prenatal stress and anxiety in the aetiology of autism spectrum disorders , although population based human studies are scarce.1 One large Danish study investigating this issue used bereavement as a proxy for stress during pregnancy and observed associations which were lost in adjusted analysis (this included possible mediating factors that should arguably not be adjusted for). Two clinic based studies reported a significant effect of exposure to stressful life events on the diagnosis of autistic disorder in the child. Both these were small with retrospective data collection and may be open to selection and recall bias.2,3 There is also evidence from an ecological study describing higher incidence of autism in areas affected by tropical storms. Affective disorders in parents have also been reported to be 'independent' risk factors for autism in one study.4 However, reverse causality may explain this association since no study has ascertained parental diagnoses prior to the birth of the child, and caring for a disabled child may predispose parents to develop mood and anxiety disorders.
It is also not known if observed associations are largely due to a) genetic or biological factors related to stress and anxiety, b) foetal exposure to antidepressant or similar medication, c) due to early life environmental disadvantage associated with growing up with a stressed or mentally unwell parent, or d) chance findings as they have yet to be replicated in other well designed population based studies.
The ALSPAC data allows us to investigate these questions in some detail. First, stress and anxiety are measured in a number of ways, at different time points including adverse life events (possibly other measures of adversity- the 'stressors') as well as self reported anxiety (that may depict the individuals' response to stress, and may be used to differentiate between acute or chronic/ state or trait anxiety based on the number of times the woman appears stressed on questionnaires) along with possible confounders in this relationship including drug use and important socio-demographic characteristics.
1 Kinney DK, Munir KM, Crowley DJ, Miller AM. Prenatal stress and risk for autism. Neurosci Biobehav Rev 2008;32:1519-32.
2 Beversdorf DQ, Manning SE, Hillier A, Anderson SL, Nordgren RE, Walters SE, et al. Timing of prenatal stressors and autism. J Autism Dev Disord 2005;35:471-8.
3 Ward AJ. A comparison and analysis of the presence of family problems during pregnancy of mothers of "autistic" children and mothers of normal children. Child Psychiatry Hum Dev 1990;20:279-88.
4 Larsson HJ, Eaton WW, Madsen KM, Vestergaard M, Olesen AV, Agerbo E, et al. Risk factors for autism: perinatal factors, parental psychiatric history, and socioeconomic status. Am J Epidemiol 2005;161:916-25.
B1080 - The determinants of measures of immune function in a wild mammal - 02/11/2010
The purpose of the proposed research is to identify and quantify the principal determinants of measures of immune
function of a wild mammal, Mus musculus. The immune function of wild animals, and its control, is very poorly
understood, despite the key role that immune function plays in their fitness. We do not know what immune responses wild
animals make, nor what affects and controls this.
Wild animals are continually exposed to infections, against which they make immune responses. This inter-play between
exposure to infection and retaliatory immune responses ultimately determines the fitness and survival of individual
animals. Animal immune function is also central to host-pathogen population dynamics. Immune responses are the key
link between, and mediator of, these processes but are poorly understood in the natural environment. Understanding
what controls immune function, and the effects of immune function, is central to understanding the consequences of
infection for wild animals (as well as for their pathogens). Our work will exploit the deep laboratory based knowledge and
understanding of murine immunology and use a wide range of validated tools to - for the first time - discover what immune
responses a wild animal makes and what controls this.
Laboratory studies have shown the many factors that may affect immune responses (sex, genetics, nutritional status, age,
infection status etc.) but which factors actually do affect immune function, nor their relative roles and importance, in wild
animals is not known.
In a pilot project that investigated the immune function of wild caught M. musculus, we found that the immune responses
of these animals differed substantially from each other (and differed markedly from laboratory mice).
We now to propose to undertake a full study of the immune function of wild mice and to partition the effect of different
intrinsic and extrinsic factors on M. musculus immune function. The specific objectives of the proposed work are to:
1. Make measures of immune function of wild M. musculus,
2. Quantify the effect of extrinsic and intrinsic factors on measures of immune function, and
3. Experimentally test causality of key explanatory factors of immune function.
To do this we will undertake a cross-sectional survey of wild M. musculus populations. We will assay the humoural and
cellular, innate and adaptive immune function of the mice. This will address objective 1. At the same time we shall
measure likely key intrinsic factors (sex, genetics, reproductive status, hormone status, body condition, infection status)
and extrinsic factors such as season and location. We will then seek to explain how the intrinsic and extrinsic factors (and
combinations of these factors) affect immune function, particularly using structural equation modelling. This will address
objective 2. To move from association to causality, we will then experimentally test these findings in wild mice, which will
address objective 3.
Understanding the control of immune responses and their relationship to other life-history aspects is central to ultimately
understanding fitness of wild animals. This information is key to understanding how wild animals deal with their existing
range of infection challenges and the effects that novel and emerging infections, or other changes in their environment,
will have on them. This is particularly pressing given the current high rate of environmental change.
B1067 - Intrauterine exposure to tobacco use and childhood cognitive skills a parental-offspring comparison using the Avon Longitudinal Study of Parents and Children - 31/10/2010
Evidence increasingly suggests that mental health problems are associated with insults during critical times of brain development, and also by exposures over an individual's life course. These include in-utero exposures, which may lead to subtle neurobehavioral difficulties. Further, there is a body of evidence relating birth weight to cognitive function in childhood, though sibling-based analyses suggest the association is more likely to be due to fixed familial factors such as background socioeconomic position and behaviours/exposures that are similar for all siblings within a family. (1)
However, there is relatively little work on the role of early alcohol and tobacco exposure on the occurrence of a range of cognitive, behavioural and emotional difficulties. In-utero to these substances may cause a variety of adverse developmental outcomes. (2) Finally there is emerging evidence pointing to an association between alcohol and tobacco use in pregnancy and the development of addictive behaviours, such as addiction to alcohol and tobacco. (3-6)
The mechanisms underlying these associations are unclear. It is assumed that the effects are due to specific intrauterine exposure, but genetic factors and shared familial factors (including socioeconomic position, shared/learnt familiar behaviours) may well explain any link between maternal alcohol and tobacco consumption in pregnancy and later effects on offspring cognitive function and behaviour. One way to further explore this is to compare associations of maternal alcohol and tobacco use during pregnancy with offspring outcomes to the same associations with paternal alcohol and tobacco consumption. Analyses using these analytical techniques are needed to ascertain whether in-utero exposure to alcohol and tobacco consumption truly contributes to later developmental problems. If this is so it is also important to understand the mechanisms underlying these associations. To date only one study has done this and both George Davey Smith and I have been involved in preparing that paper (7).
In the previous paper published in 2008, we carried out comparisons of both alcohol and tobacco use with child's IQ at age 8 and found no important adverse effect of both moderate maternal alcohol and tobacco consumption on offspring IQ at age 8, though IQ scores were lower in children of mothers who reported greater quantity of 'binge'- like style of drinking. (7) Further to that study, a Welcome Trust project grant led by Dr Ron Grey, has allowed us to progress our work in this area and carry out maternal-offspring and paternal-offspring alcohol comparisons with a range of child's neuro-developmental outcomes, including cognitive abilities at age 11 (paper awaiting ALSPAC Exec approval).
The role of intra-uterine exposure to tobacco has not been investigated in this grant. Hence, we propose to examine the association between parental smoking and offspring cognitive abilities at age 11. Several studies have found an inverse association between parental (usually maternal) smoking during pregnancy and offspring IQ. Biological mechanisms involving in utero exposure to tobacco combustion products and their metabolites have been proposed however other evidence suggests that confounding by factors related to social position may be more important. [2,3] Unlike alcohol use, smoking at even relatively moderate levels may be a marker of adverse social environment in contemporary populations. This is likely to be particularly true of maternal smoking during pregnancy.
The aim of this proposal is to use ALSPAC data in order to determine whether intra-uterine exposure to tobacco consumption (assessed by maternal self-reports during pregnancy) is related to poorer academic abilities at age 11 (KS2 linked data). The association of maternal smoking during pregnancy with academic abilities will be compared to similar associations of paternal tobacco use (based on self-report by the partner of the mother, or where this is not available the mother's report of the fathers tobacco use, with restriction to those who define themselves as the biological father). This comparison will strengthen our ability to determine whether there is a true intrauterine effect, since if there is one, it should be only apparent with maternal tobacco use. Similar association between maternal and paternal tobacco use and child's cognitive skills would suggest that genetic factors and/or shared family environmental factors explain the association rather than specific intrauterine effects. We propose to examine the effect of maternal and paternal smoking during pregnancy and offspring KS2 scores at age 11, both before and after adjustment for covariates. I will conduct the analysis using the current Wellcome Trust dataset, and will need additional alcohol and tobacco variables in the postnatal period to include prenatal and postnatal parental effects in the analysis (see analysis used in the alcohol paper awaiting approval).
B1019 - An investigation of common genes influencing depression and cardiovascular disease in early life - 29/10/2010
This proposal is an extension of our proposal previously accepted by the ALSPAC executive committee (B627). The proposal (B627) was approved to investigate genetic mechanisms that may potentially explain the association between cardiovascular disease risk factors and psychosocial outcomes (specifically aggressive behaviour and anxious/depressed symptoms) throughout childhood. The association between CVD and its risk factors and psychosocial outcomes has been well documented in adult studies and more recently in childhood studies. There are no studies that have been published that have investigated genetic mechanisms that may explain this association.
In this proposal we seek approval for use of candidate genes, specifically Leptin (LEP), its receptor (LEPR) and Monoamine Oxidase A (MAO-A) gene, available within the ALSPAC genome wide scan genotype data.
We will use these SNPs to replicate our findings within the Western Australian Pregnancy Cohort (Raine) Study, an ongoing longitudinal prospective birth cohort of children. Briefly, the original cohort consisted of 2,900 pregnant women, all of whom were recruited at approximately 18 weeks of gestation. Their babies were serially followed from recruitment at the average ages of one, two, three, six, eight, ten and fourteen, seventeen and currently twenty-one years. The majority of the children are of Caucasian ethnicity (82% have two Caucasian parents). Depression and Aggression measures and certain CVD risk factors were assessed from the ages of five onwards.
Analysis of the ALSPAC data (genotype and phenotype) will be carried out inBristol. As we have most of the phenotype data, Sandra Louise will be able to provide all the necessary syntax required to carry out the genetic analysis.
B1065 - Adiposity and risk of self-harm/suicidal behaviour in ALSPAC trajectory analyses and a Mendelian randomisation study Fellowship - 27/10/2010
Background
Several recent cohort studies have reported inverse linear associations of adiposity measures (e.g. body mass index, BMI) with risk of completed suicide (Magnusson et al. 2006; Mukamal et al. 2007; Bjerkeset et al. 2008; Batty et al. 2010; Mukamal et al. 2010). Stepwise associations are found across the range of BMI - low BMI is associated with increased suicide risk, and raised BMI is associated with reduced suicide risk. These associations are robust to controlling for a range of possible confounding factors, including mental illness, and are seen regardless of suicide method. In contrast, results from studies of non-fatal suicide attempts have been markedly less consistent (Jiang et al. 1999; Carpenter et al. 2000; Falkner et al. 2001; Eaton et al. 2005; Brunner et al. 2006; Dong et al. 2006; Crow et al. 2008; Osler et al. 2008; Dave et al. 2009; Batty et al. 2010). Likewise, studies report inconsistent findings for the association of obesity with depression (Lawlor et al. 2007; Atlantis et al. 2008; Bjerkeset et al. 2008; Luppino et al. 2010).
Body weight fluctuates over time, and distinct patterns of its change have been shown to be associated with particular psychiatric outcomes. For example, a prospective study of a sample of American children found associations of chronic obesity with defiant oppositional defiant disorder in boys and girls and with depressive disorders in boys (Mustillo et al. 2003). A recent birth cohort study finds associations of mood symptoms with change in body mass index over the course between age 15 to 53 years but the relationship varies by sex and age at onset of symptoms (Gaysina et al. 2010). However, there have been no studies investigating the association of the growth or adiposity trajectories with risk of suicidal behaviours.
One possible explanation for the conflicting findings of the association of adiposity with non-fatal suicide attempts is that the relationship is subject to confounding by other risk factors for suicide (e.g. smoking, alcohol use, physical and mental illness and socioeconomic position), which are associated with both body weight and suicide (Mukamal et al. 2010). One possible approach to examining the causality of the observed adiposity-suicide relationship is Mendelian randomisation (Batty et al. 2010), which uses genetic variations as non-confounded proxies for environmental exposures (Davey Smith et al. 2003; Lawlor et al. 2008). The recent discovery of common markers of obesity such as FTO (Frayling et al. 2007) and MC4R (Loos et al. 2008) makes it possible to investigate the association of adiposity with suicide using such an approach.
Aims
We aim to investigate whether self-harm/suicidal behaviour is associated with body weight or distinct growth/adiposity patterns within the ALSPAC cohort. We also aim to explore the potential of using the ALSPAC to investigate the causality of any observed relationship between adiposity and self-harm/suicidal behaviour using the Mendelian randomisation approach.
B1066 - The short and long-term impact of eating disorders on bone health and development - 26/10/2010
Objectives
1) To determine the impact of adolescent eating disordered (ED) behaviours on bone accrual and bone development. To determine the role of factors such as caloric restriction, delayed puberty, excessive exercise, gender in explaining the effect of ED behaviours on bone health in adolescence.
2) To investigate the long-term impact of ED on bone mass in perimenopausal women.
3) To inform the development of effective strategies to prevent long-term consequences on bone health in subjects with ED
Background
Eating disorders (ED) are chronic disorders and affect about 5-10% of the population (Hoek and Van Hoeken, 2003).
Adolescent ED and bone development: ED have a peak incidence in adolescence, a crucial time for physical and skeletal development. Pubertal years are the period in the life course when bone mass reaches its highest level. The level of bone mass attained at this age is a key determinant of long-term bone health and risk of osteoporotic fractures in later life (Ott, 1991).
Past research focusing on bone density in ED has shown that restrictive ED (such as anorexia nervosa (AN) and atypical anorexia nervosa/ Eating Disorder not otherwise specified-EDNOS) are associated with reduced bone mass. This is probably secondary to low weight, reduced fat mass and hormonal abnormalities secondary to poor nutrition (ref). Whilst recovery from the ED has been shown to lead to improvements in bone density, several studies show that bone density remains lower than in individuals who have not experienced an ED, particularly in cases where the ED onset was in adolescent years (Biller et al., 1989; Hartman et al., 2000; Wentz et al., 2007; Bolton et al., 2005).
Binge- type ED (such as bulimia nervosa and binge eating disorder) have been less well studied, and appear not to affect bone density to the same extent as restrictive ED, particularly if normal weight is maintained (Misra, 2008). However, higher fracture risk was also shown in these women compared to controls (Vestergaard et al., 2003).
Studies investigating bone density in adolescents with restrictive ED as measured by dual energy X-ray absorptiometry (DXA) have shown low bone density at the spine, hip and femoral neck (Misra, 2008); as well as reduced bone turnover. These effects are apparent in both girls and boys (Castro et al., 2002). Follow-up studies of adolescents have reported some improvement in bone density with nutritional restoration, mainly in areas of trabecular bone, such as the spine. Several studies, however, have shown fewer improvements in bone density at cortical sites despite recovery from the ED ((Herzog et al., 1993; Mika et. al, 2007). Given that the adolescent years provide a narrow window of opportunity in which to optimize bone mass accrual, disruption during these years might lead to permanent deficits.
Long-term bone health: Osteopenia, osteoporosis and higher fracture risk have all been shown as a short and long-term consequence of ED (Hartman et al., 2000; Ward et al., 1997; Vestergaard et al., 2003). The latter study showed a 2.5-fold increased risk of any fracture in patients with AN compared to general population controls, and a 5-fold increased risk of hip and spine fractures. As highlighted above there is evidence that ED affect long-term bone health, with little increase in mean bone density after weight recovery in adult women with AN (Rigotti et al., 1991; Hartman et al., 2000).
Gaps in the literature:Most studies in the field to date rely on small clinical samples, and are likely to represent more severely ill subjects attending in- or out-patient services and not be generalisable to all ED. Length of follow-up has often been limited to 1-2 years. Moreover, DXA provides an overall estimate of bone mass but does not directly measure aspects like cortical thickness and cross sectional area that determine overall bone strength. Techniques like peripheral quantitative computed tomography (pQCT) can provide detailed information about cortical bone geometry and strength, but only one study to date has used this method to study bone changes in adolescents with ED (Milos et al.,2007). In light of our recent finding that fat mass is an important positive determinant of cortical bone size and thickness (Sayers & Tobias, 2009), we are particularly interested in examining whether adolescent ED predicts weaker cortical bones due to reduced fat mass.
To our knowledge there are: (1) no studies on a general population sample of adolescents able to link temporal relationships between ED behaviours and bone development; and (2) very few long-term studies on bone health in relation to ED. Both would allow a clear identification of causal biological mechanisms, and take into account the role of confounders. The current lack of evidence impacts on available prevention and early treatment for patients with ED.
This study is unique in that data have already been collected prospectively and independently on bone density and ED behaviours in about 6,000 adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC); and on lifetime ED history and bone density in 5,500 mothers from the same cohort. This longitudinal prospective study will allow: (1) determining precise temporal relationships between predictor (ED behaviours) and outcome (bone density and cortical bone size and thickneness); (2) generalisability of findings (general population sample); (3) focusing on causal biological mechanism taking into account the role of confounders (thanks to the wealth of data available in ALSPAC).
Methodology
Theoretical/conceptual framework: This is a longitudinal study which will rely on data prospectively collected as part of the ALSPAC study. The ALSPAC study is a longitudinal prospective cohort of 14,000 mothers and their children. Women were enrolled in the study in pregnancy. Children have been followed up at regular intervals from birth up to age 18.
Research questions:do adolescent eating disordered behaviours (not only clinical ED) negatively affect bone accrual and bone development during puberty, including children with subclinical disorders not currently viewed as being at risk? Do reductions in fat mass contribute to these deleterious effects of ED behaviours on bone development particularly those on cortical bone? This being the case, are reductions in fat mass in the context of ED behaviours particularly harmful, reflecting the fact that they are achieved by dietary restriction as opposed to by increased physical activity? What is the long-term impact of eating disorders (ED) on bone mass? Can effective strategies be developed to prevent long-term consequences on bone mass in subjects with ED?
Methods:
Outcomes:
1) Total DXA scans have been performed on the children/adolescents at ages: 11.5 (n = 7159), age 13.5 (n = 6147), age 15.5 (n= 5509) and age 17.5 (approximately 4000). In addition, hip DXA scans have been performed at age 13.5 and 17.5, and pQCT scans of the mid tibia at 15.5 and 17.5. Standard DXA and pQCT parameters related to bone development have been derived and will serve as the main outcomes. Data on fractures has also been collected at regular intervals.
2) Total body and hip DEXA scans have been performed on the ALSPAC mothers between ages 42 and 47.
Women will be sent a 1-page questionnaire on osteoporosis and fractures.
Predictors:
1) Data on adolescent ED behaviours have also been collected at age 13, 14 and 16, on 8,000 adolescents (as part of an NIHR clinician scientist award).
2) Data have been collected on maternal lifetime ED behaviours (at maternal age 46-47). We have interviewed all women screening positive for lifetime ED for complete details on ED lifetime history (n=900) and a random sample of screen negative women (n=400) (as part of an NIHR clinician scientist award).
Other explanatory variables (mediators and/or confounders):
1)- Data are also available on pubertal timing and anthropometric measures at all the above ages on ~8,000 adolescents.
-Total body fat and lean mass as measured by total body DXA
-Physical activity as measured in the children by accelerometry at multiple time points
-Detailed information on diet in the children using a combination of diet diaries and food frequency questionnaires
2) Data on maternal menstrual history and Hormone replacement therapy (HRT) have also been collected.
-Extensive information on socio economic status
Analyses: Univariate and multivariate logistic models will be sued to determine the effect of relevant predictors on outcomes. Longitudinal statistic modelling will be used for longitudinal repeated data and to model hypothesised relationships.
Timeplan:
Oct 2011-March 2012: data entry, data clearing and extraction of data specific for this study. Sending out additional questionnaires to mothers.
March 2012-October 2012: initial analyses of data relating to adolescents. Receipt of all maternal additional questionnaires
October 2013-March 2013: data entry of maternal additional questionnaires. Write up of findings in relation to adolescents. Initial analyses of data on mothers.
March 2013-October 2013: complete all analyses, write up and dissemination.
B1058 - Early life fatty acid status and obesity risk - 21/10/2010
As obesity is a powerful risk factor for a variety of diseases, this development represents a tremendous challenge to the healthcare systems worldwide. Such complications are particularly serious if obesity starts early in life and causes long term exposure of organs to excess body fat. There are convincing indications that early life weight gain is a strong influencing factor a later weight and thus contributes to the risk of developing obesity eventually already in childhood (Gillman et al, 2008; Stettler et al, 2010).
Although current knowledge about mechanisms which contribute to early childhood obesity is limited, there is some evidence that fatty acid status may influence the risk to become overweight or obese. Fatty acids influence adipogenesis by binding to PPARgamma and beta/(delta), which act as a regulator of fat cell formation (Spiegelman, 1998), thereby providing a molecular link between fatty acid status and fat cell development. Of particular importance for adipogenesis seems arachidonic acid, the major long chain polyunsaturated fatty acid of the linoleic acid derived n-6 series (Demmelmair et al, 1999). Arachidonic acid is converted into prostacyclin, which stimulates via cAMP production adipose differentiation of primary preadipocytes in cell culture studies (Massiera et al, 2003). In contrast, the n-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid were found to inhibit the stimulatory effect of arachidonic acid on cAMP production (Massiera et al, 2003).
Based on these findings G. Alihaud developed the hypothesis that a high intake/availability of n-6 polyunsaturated fatty acids is a potent promoter of adipogenesis in vitro and adipose tissue development in vivo (Massiera et al, 2006; Ailhaud et al, 2004).
Although the observed increase of the intake of n-6 fatty acids during the last decades and the increase in childhood obesity agree with this hypothesis (Ailhaud et al, 2008), it has not been tested so far in birth cohorts. By now the importance of the influence of genetic variants of the fatty acid desaturases FADS1 and FADS2 on human fatty acid status primarily in respect to n-6, but also on n-3, long chain polyunsaturated fatty acids has been demonstrated (Glaser et al, 2010). Inclusion of FADS genotype into studies relating fatty acid status to weight development seems important, as this provides the opportunity to identify a relationship between FADS genotype and obesity risk..
Considering the numerous identified and potentially also unidentified factors, which determine anthropometry during infancy and child adequate statistical power has to be achieved. An ideal opportunity to investigate the hypothesis provides combination of several sizable, well characterized birth cohort for an individual subject based metaanalysis.
Aim
To test whether fatty acid status during early life and/or FADS genotype are related to growth during childhood in population based prospective birth cohorts considering further (e.g. diet, socioeconomic status) influencing factors.
Workplan
Data on fatty acid status at various time points during infancy, genotype, parental anthropometry, dietary intake and socioeconomic status shall be combined for analysis from birth cohorts: e.g. ALSPAC (Bristol, UK), Generation R (Rotterdam, NL),
Statistical modelling will start by applying latent cluster structure analyses techniques to study trajectories for height, weight, relative weight (z-scores), and overweight. Further factors will be considered as confounders and/or effect modifiers. Suitable models were described in a recent paper (Rzehak et al, 2009), which has also shown that a study of approximately 1000 subjects has sufficient power to detect small differences in weight gain due to the longitudinal modelling and the continuous outcome. Thus, it can be expected that even a small effect of fatty acid status on anthropometric development can be detected/excluded by studying more than 10 000 subjects, even if not fully standardized measurements of fatty acid status (age of sampling, analytical procedure) and corresponding modelling is needed.
Expected output
Scientific manuscript describing and discussing the relationship between the levels of fatty acids and genotype with infantile anthropometric development, with a focus on the incidence of overweight and obesity, until the age of 10 years.
References
(1) Gillman MW, Rifas-Shiman SL, Kleinman K, Oken E, Rich-Edwards JW, Taveras EM. Developmental origins of childhood overweight: potential public health impact. Obesity (Silver Spring) 16 (2008): 1651-6.
(2) Stettler N, Iotova V. Early growth patterns and long-term obesity risk. Curr Opin Clin Nutr Metab Care 13 (2010): 294-9.
(3) Spiegelman BM. PPAR-gamma: adipogenic regulator and thiazolidinedione receptor. Diabetes 47 (1998): 507-14.
(4) Demmelmair H, Iser B, Rauh-Pfeiffer A, Koletzko B. Comparison of bolus versus fractionated oral applications of [13C]-linoleic acid in humans. Eur J Clin Invest 29 (1999): 603-9.
(5) Massiera F, Saint-Marc P, Seydoux J, Murata T, Kobayashi T, Narumiya S, et al. Arachidonic acid and prostacyclin signaling promote adipose tissue development: a human health concern? J Lipid Res 44 (2003): 271-9.
(6) Massiera F, Guesnet P, Ailhaud G. The crucial role of dietary n-6 polyunsaturated fatty acids in excessive adipose tissue development: relationship to childhood obesity. Nestle Nutr Workshop Ser Pediatr Program 57 (2006): 235-42.
(7) Ailhaud G, Guesnet P. Fatty acid composition of fats is an early determinant of childhood obesity: a short review and an opinion. Obes Rev 5 (2004): 21-6.
(8) Ailhaud G, Guesnet P, Cunnane SC. An emerging risk factor for obesity: does disequilibrium of polyunsaturated fatty acid metabolism contribute to excessive adipose tissue development? Br J Nutr (2008): 1-10.
(9) Glaser C, Heinrich J, Koletzko B. Role of FADS1 and FADS2 polymorphisms in polyunsaturated fatty acid metabolism. Metabolism 59 (2010): 993-9.
(10) Rzehak P, Sausenthaler S, Koletzko S, Reinhardt D, von BA, Kramer U, et al. Short- and long-term effects of feeding hydrolyzed protein infant formulas on growth at less than or = 6 y of age: results from the German Infant Nutritional Intervention Study. Am J Clin Nutr 89 (2009): 1846-56.
B1057 - GWA association study of haemoglobin and red cell indices - 21/10/2010
Genome-wide association analysis of haemoglobin at age 7. The results are to be submitted as part of a large consortium on the genetics of red cell indices led by John Chambers of the CHARGE consortium. Analysis via standard methods.
B1060 - Genes and Mechanisms in Type 1 Diabetes - 20/10/2010
As part of our ongoing research into the soluble form of the interleukin-2 receptor alpha (sIL-2RA) and
type 1 diabetes (T1D) risk, we would like to measure sIL-2RA in plasma or serum of ALSPAC children
aged 7, 9 and 11 years old. This would provide the sIL-2RA measurements that we currently lack in
controls subjects. We would measure sIL-2RA in all available samples, or at least 500 samples per age
group. In particular, we would like to measure sIL-2RA in the 500 ALSPAC children bled at the 7, 9 and
11 year clinics, as this would be informative about how well the levels of sIL-2RA tracked in children,
that is, are children in the lower quartile for levels of sIL-2RA at 7 years old, more likely to be in the
lower quartile at subsequent assessments?
We have measured concentrations of sIL-2RA in plasma of 6,000 T1D patient (almost all under age 17
yrs) and 6,000 adult control samples using a reproducible and sensitive immunoassay. In control
subjects, sIL-2RA concentration does not increase with age at sample acquisition (age range 17-69) and
we would like to know whether children have similar concentrations of sIL-2RA. Currently, our data
indicate that T1D children have higher levels of sIL-2RA than adults and this is associated with age-atdiagnosis.
The exciting possibility, which we want to explore further, is the circulating sIL-2RA
concentration maybe a biomarker of T1D diagnosis.
Concentrations of sIL-2RA will be estimated using a commercially available sIL-2RA immunoassay,
OptEIA(tm) Human sIL-2R ELISA (BD Biosciences), with dissociation-enhanced lanthanide
fluoroimmunoassay (DELFIA) detection reagents. Duplicate dilutions of plasma and sera will be assayed
on the same 96 well plate containing a standard curve of recombinant human sIL-2RA. A minimum of 24
micro-l of plasma or sera is required for each sIL-2RA concentration estimate. However, we would like to
receive greater than 30 micro-l to allow for dead volume. We would require information on sex, body mass index (BMI),
age at sample acquisition, T1D status and age at T1D diagnosis information. Also, if asthma/allergy
status is recorded on the questionnaire this might affect sIL-2RA levels.
We would also like to apply for access to the circulating levels of vitamin D [25(OH)D] measured in
ALSPAC children aged 7, 9 and 11 years. The repeat 25(OH)D measures in about 500 ALSPAC children
would be informative about how well levels of 25(OH)D tracked in children. Also, the levels of
25(OH)D in ALSPAC children would be a useful population reference for our T1D patients with
25(OH)D measured. In addition to the 25(OH)D measurements, we would require sex, BMI, age at
sample acquisition, month of sample acquisition, year of sample acquisition, T1D status and age at T1D
diagnosis information.
B1062 - ADH1B Alcohol CVD Biomarkers Collaboration - 19/10/2010
The background to the project and analysis plan are attached in the Appendix. Specifically, with regard to ALSPAC we plan to examine associations with mothers blood pressure measured at the first antenatal clinic where this was done prior to 15 weeks gestation (recent analyses by C MacDonald-Wallis & Debbie Lawlor show that this is prior to the pregnancy related increase in blood pressure which occurs at 18 weeks (95%CI:17, 19) in ALSPAC mothers and between 18-20 weeks in other published studies). This will provide a large sample size. In addition we will examine associations with mothers blood pressure currently being assessed at the "focus on mothers" clinic in order to confirm that these associations with non-pregnant blood pressure are similar to those in the larger numbers with an early antenatal measure.
Data on 1 SNP in ADH1B is requested (rs1229984), which is already available for all the mothers who have extracted DNA (N~8,000).
B1059 - Toddler portion size range recommendations - 19/10/2010
It is important to give mothers good advice on feeding their young children. Part of this advice should be about how much of each food to offer to their children. Very little information is available about this.
ALSPAC has collected diet diary information at 18 and 43 months which could be used to inform us about the amount of food that children are likely to eat on each meal occasion at these ages. We will use this data to give a mean, median and inter-quartile range for each food eaten on more than five occasions by the children. This data would not be linked to other ALSPAC variables .
We would like to use this analysis of portion sizes as a backup resource to support a web-based educational tool for health care professionals, carers and parents to access. The aim of this tool is to give guidance on suitable portion sizes to offer and reassurance that the amounts being eaten are appropriate. Part of the reason for this is that excessive portion sizes are likely to be contributing to the increases in obesity in children. This will be part of the Infant and Toddler Forum educational initiative website which Pauline has contributed to in the past. It is funded by an educational grant from Danone but is totally independent scientifically. http://www.infantandtoddlerforum.org/.
B1055 - Identifying a subgroup of oppositional children who are at risk of depression - 06/10/2010
Fewer than twenty years ago, developmental psychopathologists and psychiatrists believed that there was little overlap between externalizing childhood psychiatric disorders, such as oppositional defiant disorder (ODD), and internalizing disorders, such as depression. There is now ample evidence from my own research (Boylan et al., 2007, 2010) and research of others (Copeland et al., 2009; Nock et al,.2007; Burke et al., 2010; Stringaris and Goodman, 2009), that childhood ODD shows significant concurrent and prospective associations or comorbidity with later depression. This discovery is changing the way we treat youths with ODD, and think about the causes of the disorder.
Despite these advances, important questions remain unanswered: Do all youths with ODD develop depression or will this only occur in sub-groups? What are the distinguishing characteristics of children belonging in one or other subgroups? The answers to these questions have profound clinical implications. If all youths with ODD develop depression, then perhaps we should begin prophylactic depression treatment, even before symptoms occur. On the other hand, if we can identify sub-groups of youths with ODD that develop depression, then prevention and treatment protocols can be applied in a more sophisticated and effective manner.
Based on my earlier work and the works of others which have demonstrated ODD symptoms cluster in various ways in the population , I propose that there are sub-groups of youths with ODD that will develop depression over time and the ability to identify and validate these groups is of substantial importance.
Study Aims:
(1) To determine whether oppositional symptom sub-groupings identified in previous factor analytic studies can be linked to groups of children who are oppositional.
(2) To determine whether these groups show differential risk for developing depression over time. If there is not strong evidence for person-based groupings, we will test how oppositional behaviours are associated with risk of depression across childhood.
Research objectives:
(1) To assess whether oppositional symptom subgroups identified by others (ie. a predominantly negative emotion and a predominantly antisocial symptom type) can be reliably identified in individual children using cross sectional and longitudinal data from an epidemiologic cohort sample.
(2) To determine if one, or more, of these groups is differentially associated with depression in late childhood and adolescence.
(3) To assess whether membership in these groups can be predicted on the basis of neurobiological and psychosocial risk factors that are associated with the ability to regulate negative emotions, in each of the following domains:
The child themselves (physiology of stress response, early life temperament, cognitive abilities, aggression, anxiety comorbidity)
The family context (family functioning, early attachment, parent discipline, family socioeconomic and family structure, parent mental health)
The peer and social context: peer relationships, school connectedness, social skills
Proposed methods:
We propose to use previously-collected questionnaire data for children from the ALSPAC study. The main outcome variables are the ODD and major depression and dysthymia symptoms from the DAWBA (at ages 7, 10 & 16) as reported by parents. Additional covariables, predominantly from questionnaire data, will be requested to distinguish the ODD groups and or predict relationships between ODD symptoms and depression based on study hypotheses. Longitudinal data on the DAWBA responses for the entire cohort will be requested to understand the impact of sample loss over time as complete data on DAWBA assessment periods is not necessary to conduct the analyses.
Analytic strategy:
Objective 1: A two step approach will test for the presence of groups of children with i) different types of ODD symptoms and ii) the stability (or reliability) of these prototypes/groups over time. The clustering of ODD symptoms will be identified from the DAWBA ODD symptoms data using factor analysis, followed by a confirmatory method (longitudinal confirmatory factor analysis). In step 2, we will test whether these (?#) identified ODD groups are developmentally distinct in that they can be distinguished based on the course of their symptom trajectory over time. To do this, we will use the group-based trajectory approach (with the Proc Traj procedure in SAS) which estimates the number and shape (course) of longitudinal trajectory groups in the sample, the proportion of children in each group and a probability for each child to belong to each group. Trajectories will be estimated for each ODD symptom cluster that is identified. Following this step, an extension of Proc Traj allows trajectory groups of one symptom cluster to be linked probabilistically to groups of another symptom cluster as joint trajectories to describe how the course of "comorbid" symptoms potentially overlap within individual children. As many children are likely to have both clusters of ODD symptoms over time, but most will have one or the other cluster (ie not have symptom overlap), assessing joint trajectories will establish how common these "comorbid" and non-comorbid children are. If comorbidity between ODD clusters is common, this suggests that there are not distinct ODD subtypes or subgroups.
In summary, the outputs of these analyses will identify: 1) are there likely ODD clusters? 2) how common are they? 3) how distinct are they from each other in terms of developmental course or how commonly do they overlap?
Objective 2: The identified joint oppositional symptom trajectory groups will be used to predict youth self-report of depression as an outcome at age 16 (measured as the youth DAWBA) using an extension in Proc Traj for this purpose. The output here will consist of a regression coefficient describing the strength of association between the various identified joint trajectory with the outcome of depression.
Objective 3: The same joint trajectory groups will be compared for their differential association with covariables (based on hypotheses which we do not outline here given space issues) as a means of exploring how they may differ etiologically from each other and how they may be differentially associated with risk of depression. Logistic regression will be conducted to examine if the prevalence rate of each covariate differs across trajectory groups.