Proposal summaries
B800 - The Impact of Prolonged Infertility on Parenting - 20/03/2009
Previous studies have small samples with small or no control groups. ALSPAC's vast data will allow for a larger sample of women who have experienced prolonged infertility. The data also provides for control groups. Due to the large numbers of variables present in the data, it will be possible to screen out for a variety of variables that might skew the data. For example, age of mother, ethnicity, socioeconomic status, and other variables. To date I have not found other studies that use the length of time of being infertile as a variable. Using the ALSPAC data, this will be possible. Instead of focusing on the type of technology used to become pregnant, I will focus on how the length of time trying to conceive influences subsequent parenting.
B798 - Understanding the lifestyle molecular and genetic pathways that link womens reproductive function to healthy ageing LINKED TO B1193 - 15/03/2009
Aims and objectives of the programme
Broad aims of programme
The aims of the programme are to (i) understand the mechanisms that underlie the associations of women's reproductive characteristics (age at menarche, menstrual patterns, follicular activity, fertility, pregnancy and age of menopause and menopausal changes) with later risk for chronic complex diseases and their risk factors (obesity, hypertension, dyslipidaemia, hyperglyaceamia, insulin resistance, type 2 diabetes, coronary heart disease, stroke, osteoporosis, depression, breast density and breast cancer); (ii) to understand the role of women's reproductive health in healthy ageing and (iii) to determine the mechanisms for the intergenerational transmission of patterns of women's reproductive, cardiovascular, metabolic, skeletal and mental health.
The programme will bring together existing funded work of the PI and co-applicants that is concerned with pregnancy related changes and future cardiovascular, metabolic and bone health in offspring and mothers (project grants from US NIH, MRC, Wellcome Trust & BHF). In the first phase we will focus primarily on consolidating the work from these different projects (objective 1 of the first 5 years) in order to obtain a comprehensive picture of how pregnancy related changes affect a wide range of future health related outcomes in mother and offspring. In addition in the first 5 years we will obtain detailed repeatedly assessed phenotypic data (hormonal, vascular, metabolic, bone and DNA methylation changes) on a cohort of women (the mothers) as they go through the menopausal transition (from age 47-52 years). These new data will be used to address objectives 2-7 below and will provide the evidence based for understanding how oestrogen deficiency and menopausal changes influence ageing in general and specifically vascular, metabolic and muscular-skeletal ageing. With subsequent renewal of the programme , after the first 5 years, we would focus on the daughter's menstrual pattern, follicular activity and emerging fertility, as well as linking data on the mother's breast density from routine mammography and mental health outcomes to the main dataset.
Specific objectives of the first 5 years
We will:
1. Determine the extent to which pregnancy related weight gain, vascular and metabolic changes are related to the mother's and her offspring's future reproductive, vascular, metabolic and muscular-skeletal health.
2. Determine the pattern of changes in glucose, insulin, lipids, blood pressure, total and truncal fat and bone mineral density as women go through the menopausal transition and distinguish whether there is a specific menopausal effect over and above age related changes in these phenotypes.
3. Determine the hormonal, genetic, molecular and lifestyle pathways that underlie variation in age at menopause and variation in changes in vascular, metabolic and bone phenotypes over the menopausal transition.
4. Determine the association of different patterns of change in glucose, insulin, lipids, blood pressure and total and truncal fat over the menopausal transition with variation in postmenopausal carotid intima media thickness.
5. Establish the role of DNA methylation in determining the timing and magnitude of menopausal changes.
6. Determine the pattern of global and gene-specific (e.g. ESR1) DNA methylation patterns as women go through the menopausal transition.
7. Determine the consequences of menopause- related DNA methylation changes with respect to subsequent changes in vascular, metabolic and muscular-skeletal health.
Data requirements and new data collection
Objective 1 above will use existing data or data currently being collected (e.g. mums clinic and 17+ clinic fasting blood samples and assays) and brings together agreed work of the PIs in ALSPAC as funded by existing grants (NIH; MRC; BHF).
The remaining objectives will be addressed by collection of new data from a subgroup (~3000) of the ALSPAC mothers who fulfil the following criteria:
Age 47-49 years at start of new clinics (September 2010)
No previous history of hysterectomy or bilateral oophorectomy
Not known to have undergone natural menopause
Mothers fulfilling these criteria will be invited to attend annual clinics over a 4 year period (4 clinics in total) at which the following will be completed:
1. Completion of menstrual cycle & hormonal use questionnaire
2. Taking of a fasting blood sample
3. Measurement of weight, height, waist circumference and blood pressure
4. DXA scan - total & hip
The grant will request funds to complete the following on the blood samples:
1. Repeat assessment (at each clinic) of sex hormones, glucose, insulin and lipids
2. Global and gene specific DNA methylation patterns.
B796 - Metabolic syndrome in adolescents Associations with dietary intakes circulating 25-hyrdroxyvitamin D and IGF-1 - 05/03/2009
The prevalence of metabolic syndrome (MetS) has been estimated anywhere from 2% to 9.4% for US
adolescents and varies depending on the definition used (1-3). A more recent report based on the National
Health and Nutrition Examination Survey (NHANES 1999-2002) estimated the prevalence of MetS as
high as 23% for overweight/obese children aged 12-18 years (4). MetS components in childhood are
carried into adulthood (5, 6). With the growing obesity epidemic and the positive relationship between
obesity and MetS (7), research aimed at understanding the risk factors for MetS in children is needed and
is likely to have important public health implications.
Diet is a known risk factor for MetS, although contributions of individual dietary components to MetS
remain relatively ambiguous for children and adolescents. In particular, associations between dairy intake
and MetS remain unclear, although several studies, mainly in adults, suggest a protective effect crosssectionally
(8-10) and prospectively (11, 12). The Coronary Artery Risk Development in Young Adults
(CARDIA) study, a 10-year prospective study, reported a lower incidence of MetS (OR: 0.28; 0.14-0.58)
among overweight individuals consuming the highest compared with the lowest dairy category (12).
Little information exists regarding this relationship in children and adolescents. A recent cross-sectional
study observed a decreased likelihood of MetS with higher frequency of dairy, fruit, and vegetable
consumption in children aged 6-18 years living in Iran (13).
Calcium and vitamin D are two major nutrients found in dairy products that may play a protective role
against MetS (10, 14-16). Serum 25-hydroxyvitamin D is used to assess overall vitamin D status. A few
population-based studies have found inverse associations between 25(OH) D and MetS (17, 18). Data
regarding the relationship between calcium, vitamin D, and MetS are limited for children. However, a
cross-sectional study of 217 obese children aged 7-18 years found that vitamin D insufficiency was
associated with several MetS risk factors including higher BMI and systolic blood pressure and lower
HDL-cholesterol concentrations (19). Therefore, examining the potential relationship between dietary
calcium, serum vitamin D and MetS may be important in understanding the associations.
Higher circulating levels of IGF-1 have been associated with risk of certain types of cancer such as
prostate cancer (20, 21), whereas lower levels have been related to other chronic conditions such as
obesity and MetS (22, 23). In several studies, IGF-1 has been positively associated with dairy and milk
intake (24-26). Rich-Edwards et al (27) reported results from two pilot studies examining associations
between milk intake and IGF-1 as follows: 1) Mongolian children showed significant increases in IGF-1
and other factors with whole milk intake over 1 month, and 2) girls living in Boston showed small
increases in IGF-1 when consuming lowfat milk compared with a vegetable-based milk substitute over a
1 week period; these findings were not statistically significant. Rogers et al (26) found that milk and
dairy intakes were associated with IGF-1 and its binding protein (IGFBP-3) concentrations for all
children and for boys after adjustment. These associations were no longer statistically significant after
additional adjustment for protein intake, suggesting that protein may be an important mediator in this
relationship. In that study, dairy intake was positively associated with leg length in boys but not in girls,
and it appeared that IGF-1 played a role in this relationship as the association was attenuated after
adjustment. The mechanism by which IGF-1 is related to milk consumption is not fully understood.
Possible explanations include the high protein content of milk and dairy (26, 28) and/or constituents in
milk that may not be degraded/deactivated during digestion, such as growth hormones used in milk
production (27). More research is needed to identify the exact mechanism by which milk intake increases
IGF-1 and other growth factors. A recent population-based study of 6,810 British subjects found that
serum 25(OH)D and IGF-1 concentrations were inversely associated with MetS. However, associations
with IGF-1 were not statistically significant for participants with the lowest vitamin D concentrations,
indicating that both need to be considered in future research studies (22). Research projects that consider
all of the nutrients and factors discussed above are needed, especially in child and adolescent populations.
B791 - Investigation of population prevalence and health consequences of structural genetic variants using genome-wide SNP data - 03/03/2009
We propose an analysis of the prevalence and health consequences of genetic variants that are not single nucleotide polymorphisms (SNPs). These include deletions, duplications, variations in copy number and translocations of parts of the genome, up to and including the duplication or deletion of whole chromosomes (monosomy, trisomy etc). Specific examples are: duplications/deletions of parts of genes such as the Haptoglobin duplicon (HP gene) and growth hormone receptor exon 3 insertion/deletion (GHR gene), large chromosomal alterations such as Prader-Willi syndrome (deletion of part of chromosome 15) and changes in chromosome number such as Klinefelter's syndrome (XXY, an additional sex chromsome), triple X syndrome (XXX, an additional sex chromosome) and Down's syndrome (three copies of chromsome 21). These types of genetic variation are not directly measured by current genome-wide SNP arrays, but can be inferred from the raw data, and present the opportunity to gain added value from existing data.
Experimental plan:
* Existing raw genotyping data from Illumina SNP genotyping performed at the Wellcome Trust Sanger Institute will be used
* Raw fluorescence data will be analysed for reductions or increases in total fluorscence across a number of genomically adjacent SNP tests (representing loss or gain of the DNA sequence containing those SNPs
* "Extended homozygosity" (regions where many SNPs appear to have two copies of one allele, rather than two different alleles) will also be identified - some of these will represent deletions
* Pairwise Hardy-Weinberg equilibrium will be used to identify distortions in genotype frequencies that might represent a "null allele" in the sample
* All identified variants will be "phenome-scanned" (i.e. tested against a range of phenotypes representative of all data available), and/or specifically analysed (if they affect a single gene for which the function is known). Whilst numbers may be small, the aim is to identify whether a genetic variant causes individuals to be in the "tail" of the population distribution for particular phenotypes
* Population frequencies of variants, and potentially differences in break-points, will be estimated. Further testing of DNA for breakpoint location and fine mapping is beyond the scope of the current application, but may be requested in the future
For phenotypic analyses a representative range of phenotypic data will be needed. We ask the committee to approve "all" phenotypes, as genomic analyses will inform the phenotypes to analyse on a case-by-case basis, and as such phenotype choice will be iterative. In each case we would wish to compare relevant phenotypes for those individuals with a genetic variant to the phenotype distribution or frequency in the rest of the ALSPAC cohort.
B793 - Association of childhood socioeconomic position at birth with adiposity and metabolic markers at age 9 and 15 - 25/02/2009
Adverse childhood socioeconomic position is associated with increased coronary heart disease (CHD) risk in later life,(1,2,3) and it has been suggested that this may, at least in part, be mediated by adiposity and its associated adverse metabolic and vascular changes. As well as being associated with future risk of CHD, individuals from poorer socioeconomic backgrounds in childhood have also been found to be more obese, more dyslipidaemic and more insulin resistant in adulthood than those from higher socioeconomic groups.( 4,5) Greater BMI and obesity in childhood and early adulthood have been shown in two very large studies to predict CHD risk in adulthood,( 6,7) but it is unknown whether this association is because of the tracking of BMI from childhood to adulthood (in which case interventions to prevent/treat obesity in adulthood might be an appropriate option) or whether permanent changes in metabolic and vascular function occur in childhood as a result of greater adiposity (in which case interventions in childhood would be paramount). A major problem with life course studies that identify associations of risk factors in childhood / early adulthood (socioeconomic position or BMI in the examples above) with future risk of adult diseases such as CHD, is that by definition the populations being studied experienced their childhood at least 5-6 decades ago and the relevance of these findings to contemporary populations of children, who live in very different circumstances, is unclear.
If the association of childhood adverse socioeconomic position with adult CHD risk from older birth cohorts is at least in part because those from poorer backgrounds in childhood were more obese and therefore experienced adverse metabolic consequences which resulted in long-term damage and increased susceptibility to future CHD risk, and if socioeconomic differentials in contemporary children were likely to have similar long term effects on future CHD risk, then one would expect to find socioeconomic differentials in adiposity and its associated adverse metabolic outcomes in contemporary cohorts of children.
Studies in contemporary populations of children from high income countries have shown socioeconomic differentials in adiposity, with those from more deprived socioeconomic backgrounds being more adipose.( 8,9) For example, in the European Heart Health Study children aged 9 and 15 from Denmark (high income country) whose parents were least well educated and who came from houses with the lowest income had larger waist circumferences and skinfold thicknesses and greater BMI than those from more educated parents and higher income families, though in two lower income countries (Estonia & Portugal) associations were in the opposite direction.(8) In that study socioeconomic differentials in lipids (HDLc, LDLc and triglycerides) and circulating insulin were in the directions that one would anticipate from the associations with adiposity, but few other studies have been able to examine socioeconomic differentials in a wide range of metabolic markers in a contemporary population of children. Of particular relevance to this application, it has also been show in ALSPAC that there is a clear social gradient (based on head of household social class at birth) of fat mass (with children of higher social class having a lower fat mass), but no gradient in lean mass.(9) Comparing these results to published studies using BMI the authors concluded that social inequalities in childhood obesity may have been underestimated in previous studies.(9) Our aims here are to extend that work by looking at other adiposity markers within ALSPAC and also metabolic and vascular risk factors. The lead author of that published paper (Andy Ness) is a co-applicant on this application and we would be happy to involve others who worked on those data on the papers that result from this application.
The aim of this proposal is to examine the association of socioeconomic position at birth with adiposity and metabolic markers in childhood at age 9.
Our specific objectives are:
1. Determine the magnitude of the association of head of household occupational social class, maternal educational attainment and parental educational attainment (as determined at birth) with BMI, waist circumference and DXA assessed fat mass at age 9.
2. Determine the magnitude of the association of head of household occupational social class, maternal education and paternal education (at birth) with blood pressure and circulating levels of insulin, HDLc, LDLc, triglycerides, apolipoprotein, adiponectin, leptin, CRP and IL6 at age 9.
3. To determine whether any associations in objective 2 are mediated by adiposity measurements.
In a second paper we would like to build on this first paper (whatever the findings) by completing the following objectives:
1. Determine the magnitude of the association of head of household occupational social class, maternal educational attainment and parental educational attainment (as determine at birth) with BMI, waist circumference and DXA assessed fat mass at age 15.
2. Determine the magnitude of the association of head of household occupational social class, maternal education and paternal education (at birth) with blood pressure and circulating fasting levels of insulin, HDLc, LDLc, triglycerides, apolipoprotein at age 15.
3. To determine whether any associations in objective 2 are mediated by adiposity measurements.
The rationale for this second paper is that the association of childhood BMI/obesity with future CHD risk (as shown in two very large study populations (6,7)) strengthens with older age at BMI assessment, suggesting that later childhood/early adulthood may be a more important risk period and/or that tracking of obesity into adulthood might be an important mechanism for the association of childhood adiposity with future CHD risk. There is also some evidence that the associations of childhood socioeconomic position with adiposity and metabolic and vascular risk factors increase with age. In the European Heart Health Study point estimates are larger at age 15 than 9 but the sample size it too small to determine whether these differences are statistically robust.
Our rationale for treating these as two separate papers is that (a) we believe there is sufficient data for two papers each with distinct and clear messages, with the second clearly building on the first; (b) the measurements at age 15 were on fasting samples, whereas those at 9 were not, and at age 9 a wider range of measurements (including leptin, adiponecting and markers of inflammation) have been completed than at 15 and we do not wish to distract from the messages of the paper by having in one paper to discuss these differences in detail (they will be discussed in the second paper).
Plan for completing work
1. DAL will put dataset together
2. DAL, LH & BG will agree analysis plan
3. LH will complete initial analyses with input from DAL & BG
4. LH will draft initial paper with input from DAL & BG
5. Other applicants on this proposal (and others they suggest as appropriate) will comment on draft and further revisions
References:
1. Galobardes B, Lynch JW, Davey Smith G. Childhood socioeconomic circumstances and cause-specific mortality in adulthood: systematic review and interpretation. Epidemiol Rev. 2004;26:7-21.
2. Galobardes B, Lynch JW, Davey Smith G. Is the association between childhood socioeconomic circumstances and cause-specific mortality established? Update of a systematic review. J Epidemiol Community Health. 2008 May;62:387-90
3. Galobardes B, Davey Smith G, Lynch JW. Systematic review of the influence of childhood socioeconomic circumstances on risk for cardiovascular disease in adulthood. Ann Epidemiol. 2006 Feb;16:91-104.
4. Davey Smith G, Hart C. Insulin resistance syndrome and childhood social
conditions. Lancet 1997;349:2845.
5. Lawlor DA, Ebrahim S, Davey Smith G. Socioeconomic position in childhood and adulthood and insulin resistance: cross sectional survey using data from the British women's heart and health study. BMJ 2002; 325:805-807
6. Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in adulthood. N Engl J Med 2007;357:2329-2337
7. Bjorge T, Engeland A, Tverdal A, Smith GD. Body Mass Index in Adolescence in Relation to Cause-specific Mortality: A Follow-up of 230,000 Norwegian Adolescents. Am J Epidemiol 2008;168:30-37
8. Lawlor DA, Harro M, Wedderkopp N, Andersen LB, Sardinha LB, Riddoch CJ, Page AS, Anderssen SA, Froberg K, Stansbie D, Davey Smith G. The association of socioeconomic position with insulin resistance among children from northern (Denmark), eastern (Estonia) and southern (Portugal) Europe: findings from the European Youth Heart Study. BMJ 2005;331:183-86.
9. Ness AR, Leary S, Reilly J, Wells J, Tobias J, Clark E, Davey Smith G, the ALSPAC Study Team. The social patterning of fat and lean mass in a contemporary cohort of children. International Journal of Pediatric Obesity 2006; 1:1, 59-61
Data required
1. SEP at birth (exposure) - occupational social class mother & father; education mother; education father
2. Adiposity measurements at age 9 (outcome 1): month and year of clinic; age of child at clinic; weight; height; waist circumference; DXA fat mass & lean mass from 9 year clinic
3. Metabolic and vascular measurements at age 9 (outcome 2): BP, lipids, insulin, adiponectin, leptin, CRP, IL6 from samples taken at 9 year clinic
4. Adiposity measurements at age 15 (outcome 1, second paper): month and year of clinic; age of child at clinic; weight; height; waist circumference; DXA fat mass & lean mass from 15 year clinic
5. Metabolic and vascular measurements at age 15 (outcome 2, second paper): BP, fasting lipids, insulin and glucose from samples taken at 15 year clinic
6. Potential confounding factors: Maternal and Paternal age at birth, ethnicity, maternal parity, maternal smoking in pregnancy, paternal smoking around time of birth/pregnancy, maternal pre-pregnancy BMI, paternal BMI around time of birth/pregnancy; child's sex.
B794 - Psychosocial aspects of maturation family functioning and substance use in adolescence - 24/02/2009
Aim: To identify whether pubertal timing moderates longitudinal associations between parent substance use, parent-child relationship quality and adolescent substance use.
Background: Early initiation of substance use has been associated with a more rapid progression to heavier use and abuse (Spear, 2000), has short- and long-term health implications (van den Bree, 2005) and can impact on individual and others' welfare through associations with increased risky behaviour (Patton et al., 2004). Understanding the psychosocial risk mechanisms that lead some adolescents to earlier initiation and heavier use of substances is arguably central to reducing the existing public health burden presented by frequent and/or excessive drinking and smoking. The quality of family relationships, parents' own substance use and the timing of pubertal maturation relative to one's peers are risk factors for substance use in adolescence. The potential interplay between these risk factors in influencing the use of cigarettes and alcohol in early to mid-adolescence is not well understood.
Children from homes characterised by poor family functioning and by parents own heavy substance use are at increased risk of substance use (Hawkins, Catalano & Miller, 1992; Engels et al., 2004). Family relationships that are non-supportive or characterised by conflict can undermine adolescents' ability to regulate their behaviour in a goal-oriented way, with self-regulation linked in turn to substance use (e.g. Brody & Ge, 2001). On the other hand, adolescents who smoke or drink regularly may incur parents' disapproval that in turn is linked to decreased expressions of warmth and affection by parents and increased conflict (Shelton et al., 2008).
The timing of the pubertal transition (compared to same-sex, same-age peers) is theorised to be an important determinant of the relationship between pubertal maturation and psychopathology (Graber et al., 1997). Early maturing adolescents may be more prone to experiencing difficulties because they are less well prepared for pubertal change (Peskin, 1973). Early pubertal timing is associated with the increased use as well as abuse of substances (e.g. Graber et al., 1997; Lanza & Collins, 2002; Orr & Ingersoll, 1995). Other studies, however, have also shown that late-maturing males begin to drink earlier and to smoke more than on-time maturing males (Graber et al., 1997; (Bratberg et al., 2007).
Early maturation is theorised to sensitise children to variations in parent mood and behaviour, which heightens risk for psychological adjustment problems (e.g. Ge et al., 2002). In addition, while pubertal maturation has been associated with negative emotions among adolescents, this emotionality may be partly attributed to parents who are not perceived to be sensitive to the adolescent's needs (Paikoff & Brooks-Gunn, 1991). Findings suggest a potential disparity between parent and adolescent expectations about the timing of developmental tasks in the families of off-time maturing boys and girls.
While previous research has independently identified early maturation, parent substance use and parent-child relationship quality as risk factors for adolescent substance use, it is not clear how domains of family functioning might interact with the timing of pubertal development to influence use of cigarettes and alcohol. In our analyses based on Addhealth data we found that the longitudinal association between parent-child relationship quality (assessed in 1995) and alcohol use (assessed one year later in 1996) was stronger for early than late maturing girls, in addition, we also found gender differences in the moderating influences of pubertal development on the associations between relations with the parents and adolescent substance use (Shelton and van den Bree, submitted).
The aim of the proposed research is to investigate in ALSPAC the transactional nature of longitudinal associations between the quality of parent-child relations, parent substance use and adolescent cigarette and alcohol use and to assess whether any such relationships are moderated by the timing of pubertal maturation as well as to further explore potential gender differences.
Analyses will involve structural equation models using maximum likelihood estimation in LISREL (Joreskog & Sorbom, 1996).
Data which we would like to use for this project are:
103 months of life (frequency of use of different alcoholic beverages)
115 months of life (parental awareness of child alcohol use)
140 months of life (parental awareness of child alcohol use)
157 months of life (frequency of use of different alcoholic beverages)
8 Years old Ever drunk without permission (antisocial behaviour questionnaire)- personal interview
10 Years old Ever drunk without permission (Antisocial behaviour questionnaire)- personal interview
11 Years old Got very drunk (sensation seeking questionnaire) - personal interview based
13 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends.
14 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends .
15 Years old Several question related to alcohol use, frequency of use, pattern of use, binge drinking, getting drunk, age started, usage by friends.
115 months of life (parental awareness of child cigarettes use)
140 months of life (parental awareness of child cigarettes use)
167 months (cigarettes use attitude) - questionnaire based
8 Years old Ever smoked - personal interview based
10 Years old Ever smoked - personal interview based
13 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
14 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
15 Years old Several question related to cigarettes smoking, frequency of use, pattern of use, age started, usage by friends.
Parental reports
97 months of life Cigarettes use/ Partner smoking/ Alcohol use
110 months of life Drug use/ Partner smoking/ Partner drinking
134 months of life Cigarettes use/ Partner smoking
145 months of life Cigarettes use/ Partner smoking/ Partner drinking
97 months of life Parent to child interaction (Enjoyment)
Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (aggression, affection)
110 months of life Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (activities together, satisfaction, rows, warmth, authority)
145 months of life Partner's parent to child interaction (Parental enjoyment)
Parent to parent interaction (activities together, satisfaction, rows, warmth, authority)
169 months of life Parent to child interaction (Parental involvement in child social life and parental awareness)
Timing of variables of pubertal development SPECIFIC CHILD BASED QUESTIONNAIRE "Growing and Changing" (including Tanner assessments).
B785 - Pilot study of Bisphenol A concentrations - 19/02/2009
(No outline received).
B784 - An analysis of the mathematics achievements of hearing impaired children in primary school - 19/02/2009
The ESRC-RNID project has two aims: (1) to provide a large scale survey of deaf children's numeracy achievements in primary school, analysing the relationships between background variables and achievement; (2) to investigate longitudinally the connections between different aspects of numeracy achievement (number knowledge, spatial knowledge, knowledge of number facts, word problem solving) and cognitive competencies (the understanding of some logical principles; working memory) that are strong predictors of hearing children's mathematics achievements, after controlling for the effects of general intelligence. The focus of the project is on attainment at Key Stages 1 and 2.
Both aims will produce original contributions to knowledge. (1) A survey of deaf primary school children's mathematics is urgently needed.The last extensive U.K. survey of deaf children's mathematics achievement that described the attainments of school leavers was carried out by Wood et al. (1984) and showed that deaf children lag behind their hearing peers by 2 to 3.5 years in mathematics attainment.Due to changes in educational provision (e.g. access to BSL) and technology (use of computers and calculators), audiological interventions (better hearing aids and cochlear implants), and progress in knowledge of how deaf children learn, previous surveys may not reflect present achievements. The inclusion of data already available for the ALSPAC study would strengthen the database for this ESRC-RNID project. (2) Research on deaf children's mathematics learning (Nunes et al., 2008) shows that they underperform in mathematics in relation to their level of non-verbal intelligence; when non-verbal intelligence is controlled for, hearing children still perform significantly better than deaf children in a variety of measures of numeracy and cognitive competencies (logical reasoning and working memory). However, it is not known how well the cognitive measures predict deaf children's mathematics learning. This project will analyse whether these cognitive measures predict deaf children's mathematics learning longitudinally as well as they predict hearing children's learning (Nunes et al, 2007).Tymms et al. (2003) found that the school-entry measures that predict hearing children's performance in Year 2 do not predict the performance of profoundly deaf children. This may have been due to their small sample size. It would be very important to attempt to attempt to replicate and understand these results, if they are replicated.
The data available in ALSPAC would provide an initial analysis of some of these aspects, namely:
- the importance of background variables (SES and mother's education);
- the performance of deaf children in comparison to that of hearing children, controlling for SES and mother's education;
- the importance of age of diagnosis;
- the performance of deaf children in comparison to that of hearing children, controlling for cognitive factors (performance IQ and working memory)
- the connections between mathematical reasoning, working memory, knowledge of number facts and visual-spatial organisation and mathematics attainment.
The analysis of the connections between the cognitive factors and mathematics attainment would not be possible in terms of a longitudinal prediction because the children's Key Stage 1 results precede the focus@8 assessments, which contain the relevant cognitive variables, and there may be very few children with hearing loss taking Key Stage 2 assessments (often they are not included in these assessments).
It is likely that there are many more deaf children who have received cochlear implants currently in school than those included in the ALSPAC sample. A careful description of the mathematics attainment of children who did not receive an implant could be used at a later point by professionals interested in analysing the effects of implantation on children's attainment. If the report provides detailed information, it could be used in a meta-analysis for comparison with children who had cochlear implants.
Variables relevant for this analysis
The predictors relevant for this analysis are measures of SES and maternal education, age of diagnosis, and the cognitive measures, which include assessments of the children's:
a) mathematical reasoning (Year 4);
b) knowledge of arithmetic (a sub-test of the WISC);
c) working memory (backward digit span), short-term memory (non-word repetition and forward digit span) and attention (Coding and two Digit Span tasks from the WISC and the scale within the Strengths and Difficulties Questionnaire);
d) general intelligence (Weschler Intelligence Scale for Children: WISC);
e) Key Stage 1 and 2 Maths results.
These variables are included in the dataset which T. Nunes, P. Bryant and K. Sylva are currently analysing for a previously approved DCSF project, with the exception of the age of diagnosis of the child's hearing impairment. This information will be obtained from the earliest age at which there is an entry of hearing impairment for the child and compared to later entries (to avoid including children who had temporary impairments due to illness, for example).
B786 - Replication of the association of a functional gene-network with intelligence - 18/02/2009
Introduction
Using an existing IQ GWAS dataset, we have analyzed the combined effect of genes in the same functional gene-networks in the variation of human intelligence. Our functional gene-networks were defined based on biological knowledge and the combined analysis was done by developing a novel datamining and analysis procedure.
Method
The novel data-minining and analysis procedure has been implemented in a tool-chain, to be used on a computer cluster. The tool-chain has been run on the SARA supercomputing cluster in Amsterdam to collect, transform, and analyze the relevant data.
Findings to be replicated
After correction for multiple test analysis one of the analyzed functional gene-networks revealed association. The set of genes included in the associated network is currently under embargo, until the conclusion of replication studies.
Replication cohort
We would like to replicate our result using the GWAS data form the ALSPAC study.
Replication requirements
We will need to have access to the IQ scores of all individuals and to the genotypes of 265 SNPs that were obtained using the Illumina 317k platform. These 265 SNPs are present in genes that are contained in the functional gene-network that we have found to be associated to intelligence in the IQ GWAS dataset previously analyzed.
Replication method
The tool-chain developed by Dr. Dina Ruano will be made available to Dr. Beate Glaser of ALSPAC for use in the replication result. The tool-chain will be applied to the replication cohort by Dr. Glaser. The results of the replication will be supplied to Dr. Ruano for further analysis and for publication.
Intellectual property
The tool-chain made available by Dr. Ruano will be used only for the replication study and will remain the intellectual property of VUmc.
Publication plan
A paper has been prepared on the original findings, including the applied method. The intention is to add the replication results to this paper before submission.
B787 - Investigating the role of novel glycaemic trait variants in fetal and childhood growth - 13/02/2009
We propose to test the following hypotheses:
1) Fetal genotype and maternal genotype are associated with fetal growth measures (birth weight, birth head circ, birth length).
2) Fetal genotype and maternal genotype ar associated with measures of growth in infancy and childhood (height, weight, BMI, fat mass etc).
3) Child's genotype is associated with intermediate traits related to Type II diabetes including fasting insulin, fasting glucose and insulin secretion and related metabolic traits (in the subset of offspring with OGTT data).
B789 - Do early life experiences influence the development of myopia in adolescents Analysis of data from the ALSPAC cohort - 10/02/2009
People who are short sighted (myopic) have blurred vision for distant viewing, but clear vision for near, and this occurs because their eyes grew too long during childhood and early adolescence. Myopia is becoming more common, and can lead to loss of vision in middle and from degenerative and other changes. Studies show that "nature and nuture" are both important in the development of myopia and the "epidemic" of myopia in Asian children is attributed to as yet little understand factors associated with urban living. As it is becoming increasingly realized that what happens to individuals early in life, indeed, even before they are born, can influence later disease risk, we plan to analyse data collected from a cohort of children when they were aged 15 years who have been followed up regularly since they were born. To our knowledge this will be the first study of myopia during children to use the "life course" approach to analysis although data from the 1958 birth cohort (who are now middle aged) is ongoing, providing a very useful comparative study.
Background: The World Health Organization (WHO) estimate that 153 million people worldwide are visually impaired from uncorrected refractive error, 8 million of whom are blind. The report suggests that 12 million school-age children (5-15 years) are visually impaired from uncorrected refractive errors, and population based surveys undertaken using standard methods and techniques suggest that 90-95% of visual impairment in this age group is due to myopia. Uncorrected myopia is, therefore, a major public health problem.
The following 4 components of the eye determine its refractive status: axial length (AL), corneal curvature, anterior chamber depth, and the thickness, curvatures and internal refractive indices of the lens. After birth the eyes grow in all dimensions, increasing almost threefold in volume by the time adult size is reached. Eye growth is exquisitely controlled so that in most people the AL of the eye increases in tandem with changes in corneal curvature and dimensions of the lens so that the image of distant objects remains focused on the retina. Evidence from laboratory, animal and clinical studies suggests that growth of the cornea and lens are largely controlled genetically whereas AL is influenced at least in part, by visual stimuli. How the visual system detects and adapts to blur, and how this is then translated into altered growth is not known. However it is known that emmetropisation is an active and dynamic process which persists throughout childhood and adolescence, involving an image-processing feedback mechanism in the retina which ultimately influences growth of the sclera. Failure or perturbation of emmetropization can give rise to myopia. The plasticity of this process has been demonstrated in animal experiments in which eye growth has been manipulated by lid closure, diffusers and plus or minus lenses but there is considerable species variation. It seems reasonable, therefore, that changes in the environment in children may also modify eye growth.
There is compelling evidence from twin, family and association studies, and epidemiological research that myopia is a complex disease. However, the rapidly increasing incidence in SE Asia can only be explained by exposure to environmental risk factors that are new or where exposure at the population level is greater and/or more intense. Changes in behaviour and life style consequent to urbanization have been implicated but there are controversies surrounding which elements in childrens' environments are the more important. To date all studies have been either cross sectional or relatively short-term longitudinal studies in which standard multivariate statistical methods have been used. The latter cannot take account of the sequence and timing of the different exposures which are likely to be critical in the development of myopia.
The ALSPAC birth cohort enrolled 14,000 children born in Avon in 1991/92. The cohort have had eye examinations at different time points (see below) and there is a wealth of other data on relevant exposures (e.g. socioeconomic status of parents prior to enrolment and throughout the study; birth weight; breast feeding; early growth; parental myopia; close work; outdoor activities; intelligence etc). We will use the life course approach to analyses which will be the first time these methods will have been used in myopia research in children although we understand that data from the 1958 birth cohort are being examined in this manner. The following data on myopia and ocular dimensions are available from the ALSPAC cohort:
* undilated (ie without cycloplegic drops) autorefraction at ages 7, 10, 11 and 15 years. The prevalence of myopia (defined as less than 1.5D to take account of non-dilation) increased from 1.5% at the 7-year clinic (n=8003 right eyes) to 3.6% at the 10-year (n=7467 right eyes) and 4.9% at the 11 -year (n=6730 right eyes) clinics; 5500 attended and were autorefracted at the 15-yr clinic (data in preparation for analysis).
* vision related questionnaire data at 7 years and clinical examination at 7 years which included eye examination and the following measurements: LogMAR visual acuity, contrast sensitivity, stereo acuity, motor fusion; ocular alignment, eye preference, subjective accommodation.
* 2900 participants also have data on axial length and corneal curvature from the 15-year clinic
* Up-to-date optometric records for approximately 3000 participants who came to the 15-year clinic, and their siblings and parents
* Opportunistic autorefraction of approximately 2500 parents of the study participants who came to the 15-year clinic.
B788 - Comparison of human and mouse quantitative trait loci - 10/02/2009
We are requesting the P values for each marker from genomewide analysis of available samples in a number of ALSPAC phenotypes. We need the genome-wide set of P-values to compare with a similar set of measures obtained in a study of mouse complex phenotypes. Our justification for wanting to carry out this comparison is as follows:
Genetic mapping of disease models in rodents has long been expected to help with the identification of genes involved in human illness. Yet, while this is true for models that arise from abnormalities of a single gene, leading to new insights into diverse conditions such as obesity (leptin), susceptibility to infectious disease (toll receptors) and mental retardation (lissencephaly), the approach has been far less successful for phenotypes with a complex genetic basis. In a few instances common genes have been found: variants in CTLA4 increases risk of autoimmune disease in humans and a mouse model of type 1 diabetes (Ueda et al. 2003); a copy number variant in the same susceptibility gene (Fcgr3) contributes to immunologically mediated glomerulonephritis in humans and rats (Aitman et al. 2006).
The conservation of many physiological processes between the two species suggests that variation at genetic loci might be shared, and there is some evidence that this is so. Paigen and colleagues used linkage results to argue that more than half of human atherosclerosis QTLs are located in regions homologous to mouse QTLs (Wang et al. 2005a). However human linkage results are notoriously unreliable and, as Risch and colleagues pointed out, concordance is unlikely given that the genetic effect in humans depends on disease allele frequencies and such allele frequencies are unpredictable (Risch et al. 1993). The lack of power in human linkage studies compromises their use in comparison with the mouse findings. Furthermore, while the mapping of complex traits has proved to be an effective technique, delivering many thousands of quantitative trait loci (QTLs) its power is not matched by high resolution. The large confidence intervals into which both mouse and human QTLs were mapped made it difficult to exclude the possibility that overlap was coincidental.
Two developments allow us to revisit the question of the overlap between mouse and human QTLs, First, the advent of adequately powered genome-wide association studies in humans, which map genetic effects at high resolution, has proved to be a robust method for QTL identification (McCarthy et al 2007, Nature Reviews Genetics) Second, progress in mapping QTLs at high resolution in mice has yielded a map of over 900 QTLs for 100 phenotypes, each mapped to approximately 3 Mb (Valdar et al. 2006a). This was achieved using a quasi outbred population of mice, the heterogeneous stock (HS). While HS mouse QTLs are not mapped to the same resolution as is obtainable in human association studies, we hypothesize that it should be possible to perceive overlap between data sets.
In order to test this idea, we need a large set of data comparable to that mapped in the HS. All of our data, genotypes and phenotypes are freely available online (http://gscan.well.ox.ac.uk). We wish to compare the distribution of the mouse QTLs to the distribution of P-values found in human GWAS studies. Our mouse data set contains the following phenotypes that we wish to compare with the GWAS data from ALSPAC, Table 1 (appendix).
To carry out our analyses we need the P values for each marker. We do not need the individual genotypes, nor the individual phenotypes. We need the result of the analysis of association for every marker in the genome.
B790 - Genomewide association studies into circulating levels of adiponectin - 09/02/2009
Insulin resistance is a highly heritable trait and predisposes to both type 2 diabetes (T2D) and coronary heart disease (CHD). Whilst genome-wide association approaches have revealed multiple variants reproducibly associated with either T2D or CHD few of these variants are shared at a biological level. Additionally, there are no common variants yet reported to be reproducibly associated with biochemical measures of insulin resistance. Using serum adiponectin levels as a surrogate biomarker of insulin sensitivity, we aim to perform a meta-analysis of 3 genome-wide association studies and sought replication of our findings in 5 additional cohorts (including the ALSPAC children with non-fasting adiponectin levels measured at age 9).
Insulin resistance is a quantitative trait that predisposes to, and predicts independently, adverse metabolic and cardiovascular outcomes such as type 2 diabetes (T2D) and coronary heart disease (CHD)(1-3). Although factors such as obesity, diet and exercise importantly influence insulin resistance there is compelling evidence that it is strongly influenced by hereditary factors(4), yet few genetic determinants of insulin resistance have been described and none of these have been found to alter risk of T2D and CHD.
The precise mechanism through which insulin resistance has adverse impacts on metabolic and cardiovascular outcomes is as yet unclear and, indeed, may differ depending on the particular downstream pathology. Thus, while impaired insulin action per se may contribute directly to hyperglycemia, it has been suggested that the compensatory hyperinsulinemia that inevitably accompanies insulin resistance in the non-diabetic individual may have adverse consequences on the vasculature and liver that could predispose to athero-thrombosis(5, 6). However the precise quantification of insulin resistance in the epidemiological setting is challenging; "gold standard" measures of insulin resistance require technically demanding hyperinsulinemic clamp studies employing stable isotopes to dissect hepatic effects of insulin from those on muscle and fat, and such studies have consequently rarely been performed in populations large enough to generate meaningful information through genome wide association (GWA) studies(7).
We plan to undertake a large-scale meta-analysis of GWA studies (n = 14, 733) of circulating adiponectin levels in the hope that this will reveal common genetic variants that might at least in part explain the heritability of insulin resistance. Given the importance of insulin resistance as a precursor of both T2D and CHD, we anticipated that the identification of genetic variants associated with circulating adiponectin levels might be exerting their effects through an influence on insulin sensitivity/resistance and that such variants might therefore modulate the risk of T2D or CHD, or indeed both.
1. Chen, K.W., Boyko, E.J., Bergstrom, R.W., Leonetti, D.L., Newell-Morris, L., Wahl, P.W., and Fujimoto, W.Y. 1995. Earlier appearance of impaired insulin secretion than of visceral adiposity in the pathogenesis of NIDDM. 5-Year follow-up of initially nondiabetic Japanese-American men. Diabetes Care 18:747-753.
2. Beck-Nielsen, H., and Groop, L.C. 1994. Metabolic and genetic characterization of prediabetic states. Sequence of events leading to non-insulin-dependent diabetes mellitus. J Clin Invest 94:1714-1721.
3. Meigs, J.B., Wilson, P.W., Fox, C.S., Vasan, R.S., Nathan, D.M., Sullivan, L.M., and D'Agostino, R.B. 2006. Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab 91:2906-2912.
4. Laws, A., Stefanick, M.L., and Reaven, G.M. 1989. Insulin resistance and hypertriglyceridemia in nondiabetic relatives of patients with noninsulin-dependent diabetes mellitus. J Clin Endocrinol Metab 69:343-347.
5. Despres, J.P., Lamarche, B., Mauriege, P., Cantin, B., Dagenais, G.R., Moorjani, S., and Lupien, P.J. 1996. Hyperinsulinemia as an independent risk factor for ischemic heart disease. N Engl J Med 334:952-957.
6. Semple, R.K., Sleigh, A., Murgatroyd, P.R., Adams, C.A., Bluck, L., Jackson, S., Vottero, A., Kanabar, D., Charlton-Menys, V., Durrington, P., et al. 2009. Postreceptor insulin resistance contributes to human dyslipidemia and hepatic steatosis. J Clin Invest.
7. Howard, G., O'Leary, D.H., Zaccaro, D., Haffner, S., Rewers, M., Hamman, R., Selby, J.V., Saad, M.F., Savage, P., and Bergman, R. 1996. Insulin sensitivity and atherosclerosis. The Insulin Resistance Atherosclerosis Study (IRAS) Investigators. Circulation 93:1809-1817.
B783 - COMT genotype pregnancy outcome psychosis and cognitive abilities - 09/02/2009
(No outline received).
B778 - Moderation by foetal and maternal NQO1 Pro187Ser rs1800566 genotype of the effects of prenatal tobacco exposure - 06/02/2009
Summary
Maternal smoking during pregnancy is a well-established and preventable risk factor for low birthweight and its sequelae of poor physical, cognitive and behavioural development, excess morbidity, and increased rates of both perinatal and adult mortality. Preliminary findings from genetic epidemiology studies suggest that the degree to which prenatal tobacco exposure depresses birthweight may be moderated by foetal and maternal genotype for NQO1 Pro187Ser (rs1800566). We propose to genotype this variant in mothers and children participating in ALSPAC to test hypotheses about the moderating effects of maternal and foetal rs1800566 genotype on the effects of prenatal tobacco exposure to reduce birthweight, shorten gestation, and alter postnatal physical, cognitive, and behavioural development.
Background
Maternal smoking during pregnancy is a well-established and preventable risk factor for low birthweight (less than 2,500g) and its sequelae of poor physical, cognitive and behavioral development, excess morbidity, and increased rates of both perinatal and adult mortality (Kramer, 2003). The primary causes of low birthweight are preterm birth and intrauterine growth restriction (IUGR). The consequences of IUGR include both short-term and long-term morbidity and permanent deficits in growth and neurocognitive development (Kramer, 2003). Epidemiological studies have shown that maternal smoking is associated with both short gestation and IUGR (Kramer, 2003). Mothers who quit smoking while pregnant have longer gestations and heavier newborns than those who continue to smoke (Lumley, Oliver, Chamberlain, & Oakley, 1998). This fact is recognized in public policy: in the UK, formal smoking cessation programs are recommended as part of antenatal care to prevent low birthweight (Health Development Agency, 2004).
Preliminary findings from studies in genetic epidemiology (Sasaki et al., 2008; Price, Grosser, Plomin & Jaffee, in press) suggest that the degree to which prenatal tobacco exposure depresses birthweight may be moderated by foetal and maternal genotype for NQO1 Pro187Ser (rs1800566). To date, no study has replicated these initial findings, nor tested the effects of both maternal and foetal rs1800566 genotype, nor investigated the possibility that rs1800566 genotype interacts with prenatal tobacco exposure to influence postnatal physical, behavioural, and cognitive development.
Methods
Data collection. We propose to genotype approximately 10,000 mothers and 10,000 children participating in the ALSPAC study for the NQO1 Pro187Ser variant (rs1800566).
Existing data required
Concept
Specific Measure
Person
Source
Time Point(s)
Demographic variables (age, sex, ethnicity, marital status, family structure, SES, education, employment, income etc.)
Family
Questionnaire
Antenatal
Pregnancy health variables (nulliparity, pre-eclampsia, IUGR, gestational diabetes etc.)
Mother
Questionnaire, medical records
Antenatal
Parental anthropometrics (height weight)
Mother, Father
Questionnaire
Antenatal
Pregnancy exposure variables (tobacco, alcohol and drug use; chemical exposure; diet; nutrient supplementation; stress; life events; partner cruelty; lack of social support)
Mother
Questionnaire
Antenatal
Birth/delivery variables (weight/length, placental weight, gestational age, Caesarian), perinatal health
Child
Questionnaire, medical records
Birth/perinatal period
Childhood head injury
Child
Questionnaire
Birth - 4 years
Childhood temperament
Carey
Child
Questionnaire
24 months
Childhood behaviour
SDQ
Child
Questionnaire
42 - 157 months
ADHD
Child
Questionnaire
166 months
Antisocial behaviour
Child
Questionnaire
169 months - 198 months
Psychotic symptoms
Child
Questionnaire
140 months - 198 months
Adolescent substance use (tobacco, alcohol, drugs)
Child
Questionnaire
157 months - 198 months
Language development
McCarthy
Child
Questionnaire
24 months
Cognitive ability
WISC
Child
Clinic test
8 years
Scholastic achievement
Child
Questionnaire
166 months
Anthropometrics (Height, weight)
Child
Questionnaire
Birth - 157 months
Parental antisocial behaviour (antisocial behaviour as children or adults; contact with police; criminal convictions)
Mother, father
Questionnaire
Antenatal - 145 months
Childhood postnatal experiences (maternal depression and anxiety, parental discipline)
Mother
Questionnaire
Birth - 145 months
Parental postnatal substance use (tobacco, alcohol, drugs)
Mother, father
Questionnaire
Birth - 145 months
Data Analysis. Hypotheses about effects on birthweight and gestational age will be tested using linear models incorporating terms for prenatal tobacco exposure, maternal genotype, foetal genotype, interaction between maternal genotype and prenatal tobacco exposure, interaction between foetal genotype and prenatal tobacco exposure, plus relevant covariates (including demographics, pregnancy and antenatal health variables, and parental physical and behavioural characteristics). Analyses will be stratified by ethnicity to guard against spurious associations due to population admixture. Hypotheses concerning low birthweight and premature gestation will be tested similarly, but using a logistic regression model. Hypotheses about trajectories of postnatal physical, behavioural, and cognitive development will be tested using growth curve models and growth mixture models; in addition, mediation analyses will be conducted to test whether postnatal development is conditionally independent of genotype and prenatal tobacco exposure after controlling for any effects on birthweight and gestational age. Hypotheses about the effects of prenatal tobacco exposure will test for heterogeneity of the effects with respect to mode of exposure (maternal smoking/maternal exposure to second hand smoke), dose, and timing of smoking cessation. A parallel set of analyses will be conducted using paternal tobacco exposure as the environment of interest in order to validate the inference of intrauterine effects. Analyses will be conducted to assess the possible influence of attrition in the sample on the outcomes of interest. If necessary, informative missingness will be explicitly modelled.
References
Health Development Agency. (2004). The evidence of effectiveness of public health interventions - and the implications.
Kramer, M. S. (2003). The epidemiology of adverse pregnancy outcomes: An overview. Journal of Nutrition, 133, 1592S-1596S.
Lumley, J., Oliver, S., Chamberlain, C., & Oakley, L. (1998). Interventions for promoting smoking cessation during pregnancy. Cochrane Database of SystematicReviews, Art. No.: CD001055. DOI: 001010.001002/14651858.CD14001055.pub14651852.
Price, T. S., Grosser, T., Plomin, R., and Jaffee, S. R. (in press). Fetal genotype for the xenobiotic metabolizing enzyme NQO1 influences intrauterine growth among infants whose mothers smoked during pregnancy. Child Development.
Sasaki, S., Sata, F., Katoh, S., Saijo, Y., Nakajima, S., Washino, N., et al. (2008). Adverse birth outcomes associated with maternal smoking and polymorphisms in the N-nitrosamine-metabolizing enzyme genes NQO1 and CYP2E1. American Journal of Epidemiology, 167, 6.
B780 - Development of conduct problems and violence in England and Brazil - 04/02/2009
DEVELOPMENT OF CONDUCT PROBLEMS AND VIOLENCE IN ENGLAND AND BRAZIL
This project will compare the development of violent behaviour among adolescents in ALSPAC and in a Brazilian birth cohort also born in 1993. The critical question for investigation is why Brazilian youth develop much higher levels of violent behaviour by late adolescence than English youth, despite quite similar levels of conduct problems in childhood.
BACKGROUND
Out of 83 countries surveyed worldwide, Brazil has the 5th highest rate of youth homicide (51.6 per 100,000) and England and Wales ranks 71st (0.4 per 100,000) [1]. The high rate of homicide in Brazil appears to reflect the tip of a wave of serious and violent crime. Despite the very high rates of these problems in Brazil, there is almost no empirical evidence about their causes.
Conduct problems are disruptive behaviours including physical aggression, lying, stealing, vandalism, and truancy. Studies in Europe, North America and Australasia have shown that conduct problems which start in childhood are particularly predictive of persistent antisocial behaviour, crime and violence. An obvious question is whether a high level of childhood conduct problems lies behind the high level of crime and violence in Brazil. It appears that it does not. One careful investigation of conduct and oppositional defiant disorders among children aged 7-14 years found rates of 7.0% in Brazil and 5.0% in England and Wales [2]. If this finding is replicated, it suggests that the higher rates of crime and violence in Brazil compared with England might be explained by different social processes during adolescence. This is the subject of the proposed study.
The theoretical model that will inform our investigation is Moffitt's influential taxonomy of early onset and adolescent onset antisocial behaviour [3]. Moffitt argues that early onset and persistent antisocial behaviour has its roots in interacting biological and social stresses in early life. By contrast, antisocial behaviour that emerges in the teenage years is driven mainly by the strains of role transitions and delinquent peer influence. Evidence to date suggests that serious violence is primarily committed following early onset and persistent antisocial behaviour. However, recent work shows that another pattern of antisocial behaviour needs to be distinguished. Some children, referred to as a "childhood limited group" show early onset conduct problems but desist from antisocial behaviour during adolescence [4]. Our analyses of ALSPAC data have identified a group of this kind, clearly differentiated from children with persistent early onset conduct problems on a range of early predictors [5].
Working from this model, the higher level of adolescent violence in Brazil than in England might be accounted for in a variety of ways. First, more children with early onset conduct problems might desist in adolescence in England. Second, among early onset and persistent offenders, the frequency of violent acts might be higher among Brazilian adolescents. Third, there might be a higher prevalence of adolescent onset offenders in Brazil. Fourth, adolescent onset offenders in Brazil might commit violent acts more frequently or for longer than their English counterparts. Of course, any combination of these four possibilities might also account for the higher level of adolescent violence in Brazil than in England.
In addition, there are many demographic, social, cultural, and criminal justice system differences between the two countries that might account for different patterns of violent development. Several distinctive demographic, social and cultural characteristics of Brazilian society stand out as potentially important; these include marked income inequality and absolute poverty, educational failure and school drop-out, and the occurrence of subcultures of gangs with high rates of drug use, especially in areas of concentrated poverty [6]. We hypothesise that this social context poses specific risks for the development of violence during adolescence that have not been documented elsewhere. This needs to be tested in high quality, well-matched, cross-national longitudinal studies.
PROPOSED STUDY
We propose to investigate the prevalence, frequency and continuity in conduct problems and violence between the ages of 11 and 17-18 years in ALSPAC and a similar birth cohort (also born in 1993) in Pelotas, southern Brazil, and to investigate possible mechanisms for different rates of these problem behaviours between the two sites. Collaboration has been agreed with the directors of the Pelotas study.
The Pelotas 1993 Cohort Study is a population based birth cohort study [7] of all 5,249 newborns delivered in hospitals in the city of Pelotas in 1993. Nearly all (greater than 99%) of the city's births occur in hospitals. Subsamples were visited at the ages of one, three and six months and one and four years. In 2004-5 it was possible to trace 87.5% of the cohort at ages 10-12 years. The whole cohort was most recently interviewed at age 15 in 2008, and the next wave of interviews will be conducted in 2011, when cohort members are aged 18. Extensive biosocial data have been collected through the course of the study. Many hypothesised predictors of conduct problems and violence have been measured with comparable instruments in Pelotas and ALSPAC.
In both ALSPAC and in the Pelotas study, cohort members' conduct problems were measured at about age 11 using the Strengths and Difficulties Questionnaire and the Development and Well-Being Assessment. At age 17+, a self-report delinquency questionnaire (developed in The Edinburgh Study of Youth Transitions and Crime) is being administered to ALSPAC participants (personal communication with Matthew Hickman). This questionnaire includes extensive information on involvement in fights, gangs and use of weapons, as well as other forms of delinquency. The same questionnaire will be translated for use in the next wave of interviews with Pelotas study participants at age 18. These measures would provide the key outcome variables for this research, and other data on antisocial behaviours would be used from each study where appropriate.
Analyses would address the following questions. 1) Are early childhood predictors of conduct problems at age 11 similar in Pelotas and ALSPAC? 2) Is there similar continuity from childhood conduct problems to adolescent violence in Pelotas and ALSPAC? 3) Are high rates of violence in Pelotas compared with ALSPAC explained by more youth being involved in violence, or by violent youths committing more violent acts? 4) To what extent is the high rate of adolescent violence in Pelotas compared with ALSPAC explained by differences in rates of: childhood biosocial risks, educational failure, teenage parenthood, stressful life events, drug use, gang involvement, concentrated poverty, and deprived neighbourhood contexts?
REFERENCES
1. Waiselfisz JJ. Mapa da Violencia: Os Jovens da America Latina 2008. Brasilia, DF, Brazil: RITLA, 2008.
2. Fleitlich-Bilyk B, Goodman R. Prevalence of child and adolescent psychiatric disorders in southeast Brazil. Journal of the American Academy of Child and Adolescent Psychiatry 2004;43(6):727-734.
3. Moffitt TE. Life-course-persistent and adolescence-limited antisocial behavior: A 10-year research review and a research agenda. In: Lahey BB, Moffitt TE, Caspi A, editors. Causes of conduct disorder and juvenile delinquency. New York: Guilford, 2003:49-75.
4. Rutter M, Kim-Cohen J, Maughan B. Continuities and discontinuities in psychopathology between childhood and adult life. Journal of Child Psychology and Psychiatry 2006;27(3):4.
5. Barker ED, Maughan B. Differentiating early onset persistent versus childhood limited conduct problem youth. American Journal of Psychiatry submitted.
6. Marsiglia RG, Silveira C, Carneiro Junio N. Brasil: indicadores sociodemograficos e caracteristicas das politicas publicas na decada de 1990. In: Mello MF, Mello AAF, Kohn R, editors. Epidemiologia da saude mental no Brasil. Porto Alegre, Brazil: Artmed, 2007:17-37.
7. Victora CG, Hallal PC, Araujo CLP, Menezes AMB, Wells JCK, Barros FC. Cohort Profile: The 1993 Pelotas (Brazil) Birth Cohort Study. International Journal of Epidemiology 2007; Advanced electronic access: doi:10.1093/ije/dym177.
B779 - Genome-wide association studies of cognitive functions in the SCORM and ALSPAC cohorts - 03/02/2009
(No outline received).
B777 - Investigating the role of novel variants associated with age at menarche in fetal and childhood growth - 02/02/2009
The regulation of the onset of menarche is not fully understood. Mean age of menarche is approximately 13 years in Caucasians, but has decreased over time in many populations and this reduction has been attributed to improved nutrition during recent history. One of the triggers for onset of puberty in girls is thought to be an increase in fat mass to greater than approximately 20% body fat. While non-genetic factors are obviously important in menarche, twin and family studies suggest a significant genetic component with at least 50% heritability (1-3), although linkage studies have not identified any strong candidate genes (4).
We have been involved in a meta-analysis of genome wide association studies to identify novel genetic variants associated with age at menarche. In Exeter we analysed imputed genome wide SNP data from the InChianti study of older people and collaborated with other studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium: in total, 15,661 women were included in the meta-analysis.
We identified 3 independent signals with p values less than 1x10-6, one of which reached the conventional genome-wide significance threshold of less than 5 x 10-8. In addition there were two SNPs neighbouring genes which are excellent candidates for involvement in variation in age at menarche. We would therefore like to genotype these 5 SNPs in ALSPAC, to replicate our initial findings.
In addition, the ALSPAC study provides an excellent opportunity to investigate the longitudinal role of these genes in childhod growth and development leading to the onset of puberty in both boys and girls.
Genotypes:
We would like to genotype (at Kbioscience) all ~20,000 ALSPAC samples.
The rs numbers of the selected SNPs are given in the appendix.
Phenotypes:
1. Age at menarche (including birth year as covariate) for all mothers and female offspring, as available.
2. Puberty phenotypes, eg. Age of secondary sexual characteristics
3. Growth measures in infancy and childhood (height, leg length, sitting height, weight and BMI, lean/fat/bone mass from DXA scan, waist circumference, WHR, skinfolds, birth weight, length & head circumference (& relevant covariates: gestational age, parity, twins, maternal smoking), where available)
4. Covariates of age at menarche to check if genotype is acting through them/to reduce variance in outcome: year of birth, BMI, height, ethnicity as genotype frequency may alter with ethnic origin and confound analyses.
Plans for meta-analysis:
The ALSPAC data on association with age at menarche will be meta-analysed with the original genome-wide association data and also other replication efforts, including the British Women's Heart & Health Study (BWHHS).
The longitudinal study of ALSPAC children will provide a large dataset on genetic association of confirmed variants that affect age at menarche and their role in pubertal development. However, the effects of the polymorphisms are likely to be modest and we will need to meta-analyse data from multiple studies using our own studies and extensive collaborations. These may include the Northern Finland Birth Cohorts of 1966 and 1986, 1958 British Birth Cohort and 1946 Birth Cohort. The statistical support for true associations with puberty will be greatly increased in the meta-analysis, relative to the individual studies.
References
1. Snieder, H., MacGregor, A.J. and Spector, T.D. (1998) Genes control the cessation of a woman's reproductive life: a twin study of hysterectomy and age at menopause. J Clin Endocrinol Metab, 83, 1875-80.
2. van den Berg, S.M. and Boomsma, D.I. (2007) The familial clustering of age at menarche in extended twin families. Behav Genet, 37, 661-7.
3. Towne, B., Czerwinski, S.A., Demerath, E.W., Blangero, J., Roche, A.F. and Siervogel, R.M. (2005) Heritability of age at menarche in girls from the Fels Longitudinal Study. Am J Phys Anthropol, 128, 210-9.
4. Anderson, C.A., Zhu, G., Falchi, M., van den Berg, S.M., Treloar, S.A., Spector, T.D., Martin, N.G., Boomsma, D.I., Visscher, P.M. and Montgomery, G.W. (2008) A genome-wide linkage scan for age at menarche in three populations of European descent. J Clin Endocrinol Metab, 93, 3965-70.
B776 - Is there such a thing as a sweet tooth - 29/01/2009
Is there such a thing as a "sweet tooth" that is acclimatisation to sweetness in foods. Is it possible that if an individual is exposed to foods rich in sugar that they can develop a "sweet tooth" and if a person is classified as having a "sweet tooth" does it matter?
Does having a diet rich in sweet foods impact on the nutritional quality of the diet? Does intake of sugary foods result in an excessive intake of non-milk extrinsic sugars, total energy and do they displace healthier food items from the diet? Do children who don't have a "sweet tooth" have a healthier diet than those with, and is there value in recalibrating a "sweet tooth"?
Subjects:
Avon Longitudinal Study of Parents and Children (ALSPAC) study is an ideal population in which to investigate these questions as it has a wealth of dietary data collected at several time points and valuable questionnaire data.
Data:
Dietary data has been collected using two methods. Food frequency questionnaire data is available at ages 3 years, 4 years, 7 years and 9 years. Food record data (3-day) is available on approximately 1000 children at 4 months, 8 months, 18 months, 43 months and 5 years and for approximately 7000 at 7 years, 10 years and 13 years. In addition there is age of introduction to various food items, including fizzy drinks, chocolate and sweets collected at 6 months and 15 months. The parents/carers were asked at 65 and 78 months if their child seemed to prefer sweet foods, these questions can be used to identify children with a 'sweet tooth'.
Methods:
1. Parent identified 'sweet tooth':
Analysis will be carried out to identify if there is any difference between the diets of children who were identified by their parents as having a "sweet tooth" and those who were not.. We will investigate if these children were introduced to sweet foods at an early age. Using the longitudinal data we will investigate if their diet tracks over time.
2. NME intake at 7 - used to identify those eating most sugar:
We will calculate non-milk extrinsic sugar intake at 7 years and divide intake into quintiles. We will compare the diets of children in the upper quintiles with the lower quintiles and indentify differences in intakes of nutrients and foods. We will track children's NME sugars intake from 7 years to determine if they remain within or cross centiles at age 10 and 13 years.
3. Early Introduction to sweet foods:
We will indentify children who were introduced to sweet foods at an early age, and identify if exposure to sweet foods at an early age leads to a higher intake of sugars in later diet.
Staff
Louise Jones Research Nutritionist (60% for 6 months) will perform the analyses and prepare manuscripts and reports.
Pauline Emmett Senior Research Fellow in nutritional epidemiology will will suppy expertise in analysis and manuscript preparation (2 hours per week)
Colin Steer will provide statistical support (1 hour per week)
Steve Gregory will provide data and manuscript preparation support (20% for 6 months)
The work will be part of the School Food Trust research strategy.
B775 - Functional Vision in children with disabilities or learning difficulties - 29/01/2009
his project is a fellowship application for CW. Two similar applications -one for a "new blood" CSL post, and one for an NIHR Career Development Fellowship are proposed. The programme for each is identical, and includes some work on ALSPAC data - see Study 2 below
Functional vision and disability in childhood
Functional vision (how well a person's vision equips them for the tasks they need to carry out) includes both "eye" and "brain" capabilities and is recognised by the International Council for Ophthalmology (ICO) as a key outcome for rehabilitation and support strategies. This fits into the broader context of the global World Health Organisation (WHO) emphasis on Functioning, Disability and Health as important measures of people's health and well-being. There is increasing evidence that "cerebral visual impairment" (CVI) is a cause of functional vision problems in children. Although many professional bodies in the UK and the National Service Framework for children advocate a review of visual function as part of the assessment of a child with disabilities, recommendations for registration of sight impairment (which aids access to support services) include only visual acuity and visual field deficits and do mention include CVI. However services that carry out functional vision assessments, including CVI, as part of a team approach to managing disability have been set up and commended in a government report. However, there are few data available on effectiveness of these services.
Estimates of the proportion of children with disabilities who have functional vision problems vary from 8% to 80%, depending on the definition used. Forty-four percent of children on the UK cerebral palsy (CP) register have associated visual impairment. In a small pilot study of 7-yr old children (not in ALSPAC) conducted by myself and colleagues - 5/11 children with a statement of educational special needs (SEN) had a previously unknown problem that might be expected to affect their functional vision (field loss, eye movement inaccuracies, failure of accommodation, 3+ yrs delay in visuo-perceptual abilities) whilst none of the 8 age-matched controls did. This study was hampered by very low recruitment but the results support the possibility that there may be "unmet need" in terms of visual morbidity amongst children with statements of SEN (results in preparation).
Testing and supporting functional vision in children with disabilities - a "complex intervention".
A key problem in designing, funding and running services in this area of healthcare provision for children with functional vision impairments is the lack of evidence on effectiveness, acceptability and cost-effectiveness, of interventions. The new MRC Guidance on Complex Interventions provides a useful conceptual framework to evaluate existing and guide new research. In line with this advice, I propose a 5-year programme of work designed to develop a complex intervention that will include assessing a child's "functional vision" and individualising their support accordingly. I will review existing evidence, carry out qualitative and physical assessments to characterise the deficits in more detail, and estimate the effectiveness of intervention strategies in pilot studies. I will then design a complex intervention and a study in which it can be evaluated.
PROPOSED RESEARCH IN THIS 5 YEAR PROGRAMME relevant section to ALSPAC:
Study 2. I will continue analysis of existing observational data within the Avon Longitudinal Study of Parents and Children (ALSPAC). These analyses will include:*
(a) contribution of CVI symptoms (elicited in a specific set of targeted questions) and other visual deficits (eg reduced acuity or contrast sensitivity) to educational, motor and social outcomes in children with ICD-10 diagnosed difficulties (ie prevalence of CVI as a co-pathology)
(b) self-esteem using a 12-item shortened form of Harter's Self Perception Profile for Children asked at age 8 (Harter, 1985) and peer relations (Questions from the Cambridge Hormones and Moods project Friendship questionnaire at 11y and 13y) for children with CVI compared to those without
(c )psychological well-being for mothers and mothers' partners, of children with CVI and other visual deficits, as compared to that of mothers and their partners where the children do not have CVI symptoms. without (using the anxiety subscale of the Crown Crisp Experiential Index (Crown & Crisp, 1979) and the Edinburgh Postnatal Depression scale (Cox, Holden, & Sagovsky, 1987),when child was 11y).
(d) contribution of any genetic factors that may contribute to CVI in children eg such as the deletion on chromosome 7q11.23, already identified as causing "Williams syndrome", in which functional vision is impaired because of impaired processing of visual input by the brain.
Funding-The only extra resource needed is a pro rata contribution to the time for a statistician to prepare specific files and help analyze and write up the data. Funds for this will be applied for as needed.
Further studies (1 and 3 - 5) in accompanying proposal will be conducted, with new data collection, not involving ALSPAC.