Proposal summaries
B2958 - Shift work and health Measuring health outcomes of shift work in longitudinal studies - 28/10/2017
B2961 - Investigating the impact of cigarette smoking behaviours and time since initiation on DNA methylation patterns in adolescence - 24/11/2017
Exposure to tobacco smoke has been shown to have a profound effect on DNA methylation patterns in many recent studies. Site-specific DNA methylation in response to smoking is dynamic and may change over time. Although studies have investigated the extent to which changes in DNA methylation that are associated with smoking, persist after smoking cessation (1-3), the length of time required for smoking to have an impact on DNA methylation is currently unstudied. A number of studies, focused on young people and adolescents, have shown that site-specific DNA methylation is associated with smoking (4-9), suggesting that methylation changes may be induced in individuals with a relatively short smoking history. However, the previous studies have typically evaluated methylation at a few CpG sites and have not modelled methylation changes with time since smoking initiation. This study aims to assess the dynamics of smoking-induced genome-wide methylation changes with time since smoking initiation in a cohort of adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC).
B2960 - Social environmental and epigenetic predictors of atopic dermatitis disease course - 04/10/2017
Atopic dermatitis (AD, also known as âatopic eczemaâ or simply âeczemaâ) is one of the most common chronic dermatologic diseases and is characterized by intense pruritus, sleep disturbances, and large reductions in patientsâ quality of life. It may increase the risk of allergies and asthma, and has recently been characterized as a systemic inflammatory disorder. Clinical treatment guidelines recommend standardized approaches for most patients, but emerging evidence and the highly variable clinical course suggest that personalized interventions hold the promise of much more efficacious treatment. Identifying groups of individuals with similar patterns of disease activity will facilitate the identification of factors that drive disease activity over time and form the basis for studies that seek to identify more tailored interventions.
AD has become much more common over the past few decades, suggesting that environmental factors play an important role in the disease. Many studies have found relationships between early life exposures and AD onset, but few have examined how environmental factors affect disease activity over time. Epigenetic factors (functionally relevant changes in chromosomes that do not affect the DNA sequence including methylation patterns) are hypothesized to link socio-environmental exposures with disease trajectory.
The objectives of our study are three fold: (1) to identify subgroups of individuals with distinct disease trajectories (for example, early-onset resolving, early-onset persistent, and late-onset), (2) to determine the extent to which in utero and early life nutritional, microbial, toxic and stress-related exposures are associated with disease trajectory, and (3) to test the extent to which the associations between in utero and early life risk factors are explained by methylation changes that affect how DNA is transcribed.
B2959 - Replication of a novel genetic variant associated with dental development - 27/09/2017
Dental development begins between the sixth and eighth week of pregnancy. Teeth start to form inside the jaws long before moving to become visible inside the mouth in a process called eruption. The teeth of some children erupt earlier or later than others, and it appears that genetics play a part in regulating this process. The number of teeth in the mouth at age 15 months provides a simple measure of how far children have advanced in their dental development compared to other children the same age, and this data was used some years ago in ALSPAC to identify genetic variants which influence dental development. A collaborating research centre in the Netherlands has identified a genetic variant which they believe alters tooth eruption. Before publishing this finding they have asked us to check whether this variant has a similar effect on tooth eruption in ALSPAC, and cannot do this using the existing published results from ALSPAC as this particular genetic variant was not included in the previous study. We plan to test for association between this genetic variant and number of teeth at 15 months in ALSPAC.
B2955 - Lifecourse approach to study of onset development and cessation of cigarette smoking during adolescence and young adulthood - 21/09/2017
Lifestyle factors including cigarette smoking, obesity, and alcohol consumption are responsible for 40-60% of cancers in Western countries. We want to better understand the effect of these factors â as well as of mental health problems such as depression, stress, and anxiety â on smoking behaviors in adolescents and young adults. In particular, we are interested in how these factors influence the onset, development, and cessation of cigarette smoking. We will identify the causal associations between initiation of alcohol and cannabis use on these smoking outcomes. By gaining better understanding of why adolescents and young adults begin, continue, and stop smoking cigarettes, we can inform the development of more effective preventive interventions, and ultimately reduce the incidence of cancer later in life.
B2954 - Prenatal smoking pre-pregnancy BMI and dental caries experience in the offspring ALSPAC Study - 27/09/2017
The prenatal period is a sensitive time for fetal growth and development. Maternal life-style related factors during this critical period affects the health and wellbeing of the developing fetus. Specifically, prenatal exposure to tobacco smoke via maternal smoking during pregnancy, increases the risk for respiratory illnesses [1, 2], asthma [3], cleft lip and palate [4] as well as inflammatory polyarthropathies [5] and childhood obesity [6]. Similar to maternal smoking during pregnancy, maternal overweight and obesity is associated with adverse birth outcomes and has been reported in at least one study to exceed smoking as a risk factor with the greatest risk of adverse pregnancy outcomes [7]. While maternal overweight likely affects caries development in the child, the mechanism by which this happens is yet to be elucidated [8].
Development of the primary tooth germ commences at the end of the 5th week of gestation with mineralization starting during the 13th week and continuing on throughout pregnancy to the end of the first year of life for primary teeth and up to 6 years of age for permanent teeth [10]. During this period of tooth development, prenatal exposure to tobacco smoke can negatively affect the quality (i.e. tooth calcification and mineralization) [11] and subsequent timing of tooth eruption [12, 13]. Ntani and colleagues reported that children whose mothers smoked during pregnancy had more teeth erupted at ages 1 and 2 compared to similarly aged children whose mothers did not smoke during pregnancy [13] and suggested that premature tooth eruption likely lie on the causal pathway between maternal smoking during pregnancy and subsequent caries development. In addition, smoking during pregnancy [14], and pregnancy adiposity [9] are associated with low-birth weight and prematurity, factors reported to increase the risk of developmental enamel defects like hypo-mineralization and hypo-calcification [11, 15]. These developmental tooth defects increases tooth susceptibility to cariogenic bacteria [16, 17] in the presence of fermentable carbohydrates [11].
Maternal smoking during pregnancy, exposes the growing fetus to chemical toxins including nicotine through its direct metabolite cotinine which cross the placenta to accumulate in fetal tissues [18]. Furthermore, prenatal exposure to tobacco smoke alters fetal blood flow and protein metabolism, resulting in the accumulation of chemical toxins in the mother and developing fetus [1]. While smoking throughout pregnancy likely increases offspring caries experience, the critical exposure period appears to be the first trimester of pregnancy. Indeed, maternal smoking and weight [8] in the first trimester, were independently associated with increases in subsequent dental caries risk in children [19] and teenagers [8] more so than exposures occurring during other periods of pregnancy. This finding has not been independently replicated in other population groups and there are methodologic limitations on how timing during pregnancy was assessed.
References Cited
1. Zhou S, Rosenthal DG, Sherman S, Zelikoff J, Gordon T, Weitzman M: Physical, behavioral, and cognitive effects of prenatal tobacco and postnatal secondhand smoke exposure. Curr Probl Pediatr Adolesc Health Care 2014, 44(8):219-241.
2. Jurado D, Munoz C, Luna Jde D, Munoz-Hoyos A: Is maternal smoking more determinant than paternal smoking on the respiratory symptoms of young children? Respir Med 2005, 99(9):1138-1144.
3. Metsala J, Kilkkinen A, Kaila M, Tapanainen H, Klaukka T, Gissler M, Virtanen SM: Perinatal factors and the risk of asthma in childhood--a population-based register study in Finland. Am J Epidemiol 2008, 168(2):170-178.
4. Chung KC, Kowalski CP, Kim HM, Buchman SR: Maternal cigarette smoking during pregnancy and the risk of having a child with cleft lip/palate. Plast Reconstr Surg 2000, 105(2):485-491.
5. Jaakkola JJ, Gissler M: Maternal smoking in pregnancy as a determinant of rheumatoid arthritis and other inflammatory polyarthropathies during the first 7 years of life. Int J Epidemiol 2005, 34(3):664-671.
6. Mizutani T, Suzuki K, Kondo N, Yamagata Z: Association of maternal lifestyles including smoking during pregnancy with childhood obesity. Obesity (Silver Spring) 2007, 15(12):3133-3139.
7. Djelantik AA, Kunst AE, van der Wal MF, Smit HA, Vrijkotte TG: Contribution of overweight and obesity to the occurrence of adverse pregnancy outcomes in a multi-ethnic cohort: population attributive fractions for Amsterdam. BJOG 2012, 119(3):283-290.
8. Julihn A, Ekbom A, Modeer T: Maternal overweight and smoking: prenatal risk factors for caries development in offspring during the teenage period. Eur J Epidemiol 2009, 24(12):753-762.
9. Lawlor DA, Relton C, Sattar N, Nelson SM: Maternal adiposity--a determinant of perinatal and offspring outcomes? Nat Rev Endocrinol 2012, 8(11):679-688.
10. Hujoel PP, Lingstrom P: Nutrition, dental caries and periodontal disease: a narrative review. J Clin Periodontol 2017, 44 Suppl 18:S79-s84.
11. Caufield PW, Li Y, Bromage TG: Hypoplasia-associated severe early childhood caries--a proposed definition. J Dent Res 2012, 91(6):544-550.
12. Aligne CA, Moss ME, Auinger P, Weitzman M: Association of pediatric dental caries with passive smoking. JAMA 2003, 289(10):1258-1264.
13. Ntani G, Day PF, Baird J, Godfrey KM, Robinson SM, Cooper C, Inskip HM, Southampton Women's Survey Study G: Maternal and early life factors of tooth emergence patterns and number of teeth at 1 and 2 years of age. Journal of Developmental Origins of Health and Disease 2015, 6(4):299-307.
14. Jaddoe VW, Troe EJ, Hofman A, Mackenbach JP, Moll HA, Steegers EA, Witteman JC: Active and passive maternal smoking during pregnancy and the risks of low birthweight and preterm birth: the Generation R Study. Paediatr Perinat Epidemiol 2008, 22(2):162-171.
15. Vello MA, Martinez-Costa C, Catala M, Fons J, Brines J, Guijarro-Martinez R: Prenatal and neonatal risk factors for the development of enamel defects in low birth weight children. Oral Dis 2010, 16(3):257-262.
16. Plonka KA, Pukallus ML, Barnett AG, Holcombe TF, Walsh LJ, Seow WK: A longitudinal case-control study of caries development from birth to 36 months. Caries Res 2013, 47(2):117-127.
17. Salanitri S, Seow WK: Developmental enamel defects in the primary dentition: aetiology and clinical management. Aust Dent J 2013, 58(2):133-140; quiz 266.
18. Maritz GS: Nicotine and lung development. Birth Defects Res C Embryo Today 2008, 84(1):45-53.
19. Tanaka K, Miyake Y, Nagata C, Furukawa S, Arakawa M: Association of prenatal exposure to maternal smoking and postnatal exposure to household smoking with dental caries in 3-year-old Japanese children. Environ Res 2015, 143(Pt A):148-153.
20. Greenland S, Pearl J, Robins JM: Causal diagrams for epidemiologic research. In: Epidemiology. Volume 10, edn. United States; 1999: 37-48.
21. Robins JM, Hernan MA, Brumback B: Marginal structural models and causal inference in epidemiology. Epidemiology 2000, 11(5):550-560.
22. Suissa S: Immortal time bias in pharmaco-epidemiology. Am J Epidemiol 2008, 167(4):492-499.
23. Matok I, Azoulay L, Yin H, Suissa S: Immortal time bias in observational studies of drug effects in pregnancy. Birth Defects Res A Clin Mol Teratol 2014, 100(9):658-662.
24. Tanaka S, Shinzawa M, Tokumasu H, Seto K, Tanaka S, Kawakami K: Secondhand smoke and incidence of dental caries in deciduous teeth among children in Japan: population based retrospective cohort study. Bmj 2015, 351:h5397.
25. Tanaka K, Miyake Y, Sasaki S: The effect of maternal smoking during pregnancy and postnatal household smoking on dental caries in young children. J Pediatr 2009, 155(3):410-415.
26. Majorana A, Cagetti MG, Bardellini E, Amadori F, Conti G, Strohmenger L, Campus G: Feeding and smoking habits as cumulative risk factors for early childhood caries in toddlers, after adjustment for several behavioral determinants: a retrospective study. BMC Pediatr 2014, 14:45.
27. Claudia C, Ju X, Mejia G, Jamieson L: The relationship between maternal smoking during pregnancy and parental-reported experience of dental caries in Indigenous Australian children. Community Dent Health 2016, 33(4):297-302.
28. Iida H, Auinger P, Billings RJ, Weitzman M: Association between infant breastfeeding and early childhood caries in the United States. Pediatrics 2007, 120(4):E944-E952.
B2953 - Economic consequences of depression and obesity evidence from causal inference methods and longitudinal intergenerational data - 27/09/2017
This project investigates whether depression and BMI affect educational attainment and economic activity (e.g. income, occupation), with the goal of providing an economic justification for public health interventions. We will look at whether associations change across the life course and across successive generations, and we will test whether parental depression and BMI affect a child's educational attainment and economic activity.
B2956 - Mental Health Epidemiology in the Digital Age - 10/01/2018
Social media, such as Twitter and Facebook have quickly become a crucial part of everyday life, particularly for young people. The digital footprint left by users of social media presents an opportunity to study daily activities and interactions with others, without the need to burden participants with lengthy data collection methods. So far, research on social media has used random samples of unknown participants, which makes it difficult to understand who is using social media, and impossible to estimate how the use of social media might impact on mental health and wellbeing. What is needed is social media data collected on a large cohort study with years worth of data on participants. This will allow us to accurately measure who is using social media, and how they are using it as part of their daily lives. In addition, collecting social media alongside measures of wellbeing will allow us to estimate the pros and cons of social media use for mental health and wellbeing.
B2957 - Severe Mental Illness Cardiovascular Health - 21/09/2017
The largest meta-analysis to date found that risk of dying from cardiovascular disease (CVD, including conditions such as coronary heart disease, cerebrovascular disease and congestive heart failure) is 85% higher in people with severe mental illness (SMI; Correll et al., 2017). According to that study, factors which increased risk for cardiovascular disease in SMI patients included antipsychotic use and higher body mass index (BMI).
However, the interplay between SMI and CVD and their risk factors is complex. Reverse causation or confounding might compromise our ability to draw causal conclusions and in fact, no study to date has addressed the causal effects between SMI and CVD or the potentially mediating role of factors such as BMI.
The observed association between SMI and CVD also points towards shared biological correlates. Epigenetic processes such as DNA methylation, can present a potential biological mechanism linking SMI and CVD. DNA methylation signatures have been robustly linked to SMI and SMI / CVD risk factors (Barker, Walton, & Cecil, n.d.; Dick et al., 2014; Joubert et al., 2016; Kato et al., 2015), but no study to date has investigated the epigenetic overlap between CVD and SMI.
B2951 - Language and communication in childhood and their relationship to adult life chances an analysis of the ALSPAC cohort - 20/09/2017
The development of language and communication (L&C)skills in young children is important. When children start school at the age of 4 to 5 years, they need to be able to understand what is said to them, be able to talk and express themselves and to be able to communicate and interact with other children and adults. If a child has these skills, they will be successful in learning to read and write and in their subsequent educational progress and attainment during their school careers. As teenagers and adults, the ability to communicate effectively is essential to their life chances in terms of securing employment, living independently and maintaining relationships and wellbeing. Children who are slower to develop their L&C skills or have specific difficulties with this are known to have particular life-long difficulties, not just in their educational attainment but in other areas of their lives. In adolescence and adult life, this includes poor educational attainment, limited life chances in terms of employment prospects and independence and their wellbeing and quality of life including a higher chance of experiencing mental health difficulties and being at risk of offending behaviour. This evidence between psychosocial outcomes and L&C development is limited as it comes from very small studies of children with identified impairments. It is not known whether these impacts on psychosocial outcomes are more widespread and evident in children whose L&C development is below average and therefore less advanced than their peers, but who would not be described as language impaired per se. Understanding the relationship between childhood L&C development and psychosocial outcomes in adulthood will help determine the potential costs involved with suboptimal L&C development and the potential benefits to life chances of interventions which promote childhood L&C development.
This study will consider the L&C development and abilities of individuals through childhood, adolescence and adult life and find out how their competence in these impact on their psychosocial outcomes, as indicated by measures of quality of life and wellbeing. This study will collect new data and also use existing data from ALSPAC. This study will collect new data about the L&C, using innovative technology to collect samples via computers and phones, and use this to explore the range of L&C skills in the adult population. Using existing data within the dataset, this study will explore the range of psychosocial outcomes that are evident within the sample and consider these in relation to childhood and adult L&C abilities alongside other known risk factors. Finally, we will consider the costs associated with varying levels of L&C abilities in childhood and adulthood and the potential benefits for individuals and society of interventions to promote L&C skills.
B2924 - Genetics of MHO/MUNW in children and adolescents - 13/09/2017
Many obese individuals remain free of cardiometabolic comorbidities. These individuals are often labeled as metabolically healthy obese (MHO). Obesity has heterogenic nature also in children and adolescents.
B2949 - Encouraging Effective Participant Engagement in Cohort Studies EEPECS - 22/09/2017
Participant engagement in cohort studies has been argued to be a key factor in building trust in the cohort and facilitating long-term retention. Despite the acknowledged benefits of engaging participants in such studies, little research has been conducted to understand what this engagement looks like and how it should be conducted. The proposed study seeks to fill this knowledge gap. Following on from COâs doctoral study that explored participantsâ experiences and perception of their engagement with ALSPAC, the proposed study will: (1) review ALSPACâs engagement and identify key messages present in their communication with participants; (2) conduct a qualitative study into (ALSPAC and other) cohort personnelâs experiences and perceptions of participant engagement; and (3) combine insights from participantsâ perspectives (generated from COâs previous doctoral research) with insights from the ALSPAC material and the cohort personnel perspectives to formulate a theoretical framework for participant engagement that will explain how and why certain strategies are more or less successful, more or less (un)ethical, and more or less (un)appealing to participants and researchers. In so-doing, this study will produce results that meet CLOSERâs objective to build skills in the management of cohort studies.
B2945 - Defining ADHD and conduct disorder using linked electronic primary care data - 06/09/2017
Longitudinal studies like ALSPAC usually suffer from missing data arising through non-response. This issue can be partly addressed by linking to routine data sources, since individuals who are missing from the study data will be present in such datasets. Measures created using routine data could be used in place of the missing study outcomes or used to impute the missing values. However, in order for them be used in this way, it is important to know how outcomes recorded in these datasets relate to outcomes recorded in the longitudinal studies. To our knowledge, no studies to date have validated measures for defining ADHD or conduct disorder within routine electronic primary care data.
The Strength and Difficulties Questionnaire (SDQ) has been widely used to measure child psychopathology both in research studies and in clinical practice. It has been shown to be a valid tool for identifying children with attention deficit hyperactivity disorder (ADHD) and conduct disorder (Goodman et al, 2000a). The Development and Well-being Assessment (DAWBA) is a tool that can be used to ascertain whether an individual meets DSM IV (American Psychiatric Association, 1994) diagnostic criteria for a range of psychiatric disorders, including ADHD and conduct disorder (Goodman et al, 2000b)
SDQ data have been collected in both ALSPAC and the Millennium Cohort Study (MCS). ALSPAC has also collected DAWBA data. Both studies have also linked to primary care data on a subset of participants. As such, these two studies provide a unique opportunity to validate measures of ADHD and conduct disorder derived using electronic primary care data against previously validated measures.
B2946 - Scoping existing dietary data available in CLOSER to support cross-cohort research questions - 06/09/2017
Health related behaviours across the life course, including dietary habits, play an important role in health and ageing (1-3). However, the measurement and analysis of diet in longitudinal epidemiological studies is extremely challenging. An individualâs diet is the result of the current zeitgeist, their social, economic and cultural circumstances and, it varies in relation to age (2, 4, 5). A personâs dietary intake will also vary according to season, day of week and has considerable random variation (6). The aim in epidemiological studies is to capture an individualâs consistent long-term diet in the context of this variation. Objective measures of dietary intake, such as direct observation, are costly and carry significant participant and researcher burden (7). Therefore self-reported measures of dietary intake have been developed. A number of these are used in the CLOSER cohorts e.g. food frequency questionnaires (FFQs) in ALSPAC, National Child & Development Study (NCDS), 1970 British birth cohort (BCS70), Southampton Women's Survey (SWS), Hertfordshire cohort study (HCS) and diet diaries in National Survey of Health and Development (NSHD), ALSPAC and SWS. However, it remains difficult to accurately capture habitual dietary intake, and there is always the possibility of over- or under-reporting (7). Validation studies of these instruments in EPIC-Norfolk demonstrated that correlation between dietary biomarkers and a 7-day food diary was better than correlation with an FFQ (8, 9). However, each of these methods also have specific pros and cons. For example, FFQs can capture foods consumed irregularly but reporting is limited to the items contained in the food list designed for the study (7). In food diaries, all food consumed at the time of consumption is recorded, but it may miss foods not eaten regularly (7). Within-method differences e.g. a 3-day food diary versus a 7-day food diary adds to heterogeneity in dietary measurement. Results from each method can therefore be slightly different. For example, one study found that macronutrient estimates from FFQs are higher compared with estimates from a 7-day or 16-day food diary using data from EPIC-Norfolk (8). In ALSPAC, slightly different dietary patterns in childhood were produced depending on the dietary assessment used (10).
Nutritional epidemiology has advanced during the time span of the CLOSER cohorts. An individualâs diet contains many foods/nutrients that interact or can act in synergy to influence health. Nutritional epidemiology is moving away from analysing associations of health outcomes with individual foods and nutrients towards dietary pattern analysis (11). Analyses of data in the CLOSER cohorts reflect this trend (10, 12-14). Comparing dietary intake across CLOSER cohorts would provide powerful information about longitudinal and secular trends. For example, a previous comparison of data from a 24-hour recall in NSHD and a 4 day food diary in the National Diet and Nutrition Survey, found that children in 1950 consumed a diet that was higher in fat, but was considered healthier than children in the 1990s (15). Clarifying and documenting the methodological differences in dietary assessment between the CLOSER cohorts is an essential step for any cross-cohort dietary pattern comparisons.
Comparing relationships between diet and health outcomes across cohorts will provide insight into potential cohort specific or consistent associations. Allostatic load (AL) is one health outcome that has been harmonised across the CLOSER cohorts. AL is a measure of cumulative biological dysregulation across body systems (16) which has been associated with mortality and frailty (16-18). Environmental stressors, including diet, have been proposed as contributors to AL however evidence is limited (19-24). Supporting evidence from large, longitudinal studies will help to confirm the link between diet and AL. Therefore, examining the association between diet and AL across the CLOSER cohorts would be a significant contribution to this effort.
References
1. Mathers JC. Nutrition and ageing: knowledge, gaps and research priorities. Proceedings of the Nutrition Society. 2013;72(2):246-50.
2. Kiefte-de Jong JC, Mathers JC, Franco OH. Nutrition and healthy ageing: the key ingredients. Proceedings of the Nutrition Society. 2014;73(2):249-59.
3. Ben-Shlomo Y, Cooper R, Kuh D. The last two decades of life course epidemiology, and its relevance for research on ageing. International journal of epidemiology. 2016;45(4):973-88.
4. De Irala-Estevez J, Groth M, Johansson L, Oltersdorf U. A systematic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables. European journal of clinical nutrition. 2000;54(9):706.
5. Kirkpatrick SI, Collins CE. Assessment of nutrient intakes: Introduction to the Special Issue. Multidisciplinary Digital Publishing Institute; 2016.
6. Willett W. Nature of Variation in Diet. In: Willett W, editor. Nutritional Epidemiology New York: Oxford University Press; 2013.
7. Medical Research Council. Diet, Anthropometry and Physical Activity (DAPA) Measurement Toolkit 2015 [cited 2017 15 August].
8. Bingham SA, Gill C, Welch A, Cassidy A, Runswick SA, Oakes S, et al. Validation of dietary assessment methods in the UK arm of EPIC using weighed records, and 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. International journal of epidemiology. 1997;26(suppl_1):S137.
9. Day NE, McKeown N, Wong M-Y, Welch A, Bingham S. Epidemiological assessment of diet: a comparison of a 7-day diary with a food frequency questionnaire using urinary markers of nitrogen, potassium and sodium. International Journal of Epidemiology. 2001;30(2):309-17.
10. Emmett PM, Jones LR, Northstone K. Dietary patterns in the avon longitudinal study of parents and children. Nutrition reviews. 2015;73(suppl_3):207-30.
11. Hu FB. Dietary pattern analysis: a new direction in nutritional epidemiology. Current opinion in lipidology. 2002;13(1):3-9.
12. Emmett P. Dietary assessment in the Avon longitudinal study of parents and children. European journal of clinical nutrition. 2009;63(S1):S38.
13. Prynne C, Paul A, Mishra G, Hardy R, Bolton-Smith C, Wadsworth M. Sociodemographic inequalities in the diet of young children in the 1946 British birth cohort. Public health nutrition. 2002;5(6):733-45.
14. Mishra G, McNaughton S, Bramwell G, Wadsworth M. Longitudinal changes in dietary patterns during adult life. British Journal of Nutrition. 2006;96(4):735-44.
15. Prynne C, Paul A, Price G, Day K, Hilder W, Wadsworth M. Food and nutrient intake of a national sample of 4-year-old children in 1950: comparison with the 1990s. Public health nutrition. 1999;2(4):537-47.
16. Seeman TE, McEwen BS, Rowe JW, Singer BH. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. Proceedings of the National Academy of Sciences. 2001;98(8):4770-5.
17. Gale CR, Booth T, Starr JM, Deary IJ. Intelligence and socioeconomic position in childhood in relation to frailty and cumulative allostatic load in later life: the Lothian Birth Cohort 1936. J Epidemiol Community Health. 2015:jech-2015-205789.
18. Gruenewald TL, Seeman TE, Karlamangla AS, Sarkisian CA. Allostatic load and frailty in older adults. Journal of the American Geriatrics Society. 2009;57(9):1525-31.
19. McEwen BS. Stress, adaptation, and disease: Allostasis and allostatic load. Annals of the New York Academy of Sciences. 1998;840(1):33-44.
20. Frei R, Haile SR, Mutsch M, Rohrmann S. Relationship of serum vitamin D concentrations and allostatic load as a measure of cumulative biological risk among the US population: a cross-sectional study. PloS one. 2015;10(10):e0139217.
21. Rosenberg N, Park CG, Eldeirawi K. Relationship of serum carotenoid concentrations with allostatic load as a measure of chronic stress among middle-aged adults in the USA. Public health nutrition. 2015;18(2):313-21.
22. Mattei J, Bhupathiraju S, Tucker KL. Higher adherence to a diet score based on American Heart Association recommendations is associated with lower odds of allostatic load and metabolic syndrome in Puerto Rican adults. The Journal of nutrition. 2013;143(11):1753-9.
23. Mattei J, Noel SE, Tucker KL. A meat, processed meat, and French fries dietary pattern is associated with high allostatic load in Puerto Rican older adults. Journal of the American Dietetic Association. 2011;111(10):1498-506.
24. Kusano Y, Crews DE, Iwamoto A, Sone Y, Aoyagi K, Maeda T, et al. Allostatic load differs by sex and diet, but not age in older Japanese from the Goto Islands. Annals of human biology. 2016;43(1):34-41.
B2944 - Genetics for social scientists facilitating multidisciplinary research in CLOSER - 06/09/2017
The CLOSER studies are composed of those established to examine clinical and biological phenomena or social studies supplemented with biomarker and genetic data. A recent overview of the genetic data indicates that data are available in CLOSER from over n=30,000 participants. However there is wide variation in practice across the CLOSER studies at a number of different levels which may represent barriers for those wishing to apply for these data. These include variation in genetic data sharing processes, differences in information and participant consent and genotyping platforms, which can be multiple within between and within studies. This can represent a challenge for inter-disciplinary research, in particular for social science researchers interested in accessing genetic data. Here we propose to catalogue meta-data (consent and response rates) around the genetic data available in each of the CLOSER studies; create a guidance document to enable researchers to access genetic data â this document should additionally serve to reduce the workload for the data sharing teams and finally to provide a demonstration project of the kind of analyses that can be done with the CLOSER studies on social-biological research, an important ESRC priority area. In particular we will include an in-depth focus on the development of genetic risk scores â here our proposed example is for body mass index and its interaction with social position. Finally we wish to examine the new and growing concern in genetics research to adjust for sample bias or selection by social position in the analysis.
B2947 - Epigenome-wide association study of coffee consumption in ARIES - 06/09/2017
Coffee is one of the most widely consumed beverages in the world and is believed to have potential health risks and benefits (1). Coffee consumption has been linked to a wide range of health outcomes including cardiovascular, metabolic, and neurocognitive function (1).
Dietary black tea and coffee polyphenols lead to the inhibition of the mammalian DNA methyltransferase 3a (Dnmt3a) (2). Indeed, caffeic acid and chlorogenic acid, two common catechol-containing coffee polyphenols were previously shown to inhibit DNA methylation (3).
Two studies were recently performed to look at the epigenome-wide impact of coffee intake (4, 5). Of these only one study reported 1 CpG site (close to ALPPL2 gene) associated with coffee consumption (4). This gene was previously shown to be influenced by smoking (6). A recent study has shown a positive association between smoking and caffeine consumption (7) which lead us to believe that the findings from previous coffee consumption epigenome-wide association study (EWAS) may be confounded by smoking.
To address this, we performed an EWAS of coffee consumption and found 19 CpG sites associated with caffeinated coffee intake in EPIC-IARC samples (n=898) adjusting for smoking status. Importantly, none of these sites overlap with the smoking related CpGs (6). In order to validate our findings, we wish to perform EWAS of coffee consumption in ARIES.
References
1. Higdon JV, Frei B. Coffee and health: a review of recent human research. Crit Rev Food Sci Nutr 2006;46(2):101-23. doi: 10.1080/10408390500400009.
2. Rajavelu A, Tulyasheva Z, Jaiswal R, Jeltsch A, Kuhnert N. The inhibition of the mammalian DNA methyltransferase 3a (Dnmt3a) by dietary black tea and coffee polyphenols. BMC Biochem 2011;12:16. doi: 10.1186/1471-2091-12-16.
3. Lee WJ, Zhu BT. Inhibition of DNA methylation by caffeic acid and chlorogenic acid, two common catechol-containing coffee polyphenols. Carcinogenesis 2006;27(2):269-77. doi: 10.1093/carcin/bgi206.
4. Chuang YH, Quach A, Absher D, Assimes T, Horvath S, Ritz B. Coffee consumption is associated with DNA methylation levels of human blood. Eur J Hum Genet 2017;25(5):608-16. doi: 10.1038/ejhg.2016.175.
5. Ek WE, Tobi EW, Ahsan M, Lampa E, Ponzi E, Kyrtopoulos SA, Georgiadis P, Lumey LH, Heijmans BT, Botsivali M, et al. Tea and coffee consumption in relation to DNA methylation in four European cohorts. Hum Mol Genet 2017. doi: 10.1093/hmg/ddx194.
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B2948 - The creation of a life course methylome through data harmonization in CLOSER studies - 21/09/2017
There is growing evidence demonstrating the importance of epigenetic signatures in health and disease. Research also suggests that epigenetic influences can act at different stages throughout the life course and show age-specific developmental patterns. However, a major obstacle in investigating the characteristics of this âlife course methylomeâ (i.e. a map of DNA methylation across all ages of the lifespan) has been the lack in data harmonization protocols for DNA methylation studies at different ages and the development of appropriate statistical approaches to draw different data sources together in order to analyse these changes in epigenetic patterns. The objective of this project is to synthesise such a life course methylome. With this map of variation in methylation across the life course, we can then identify those eras that show most variability as these may highlight critical windows for healthy development or disease vulnerability.
B2943 - The impact of metabolomic changes induced by obesity on cancer risk - 06/09/2017
What is the aim of the research?
Studies have shown that people who are overweight and obese are more likely than those who are not to develop cancer. When obesity is present the risk of cancer of the colon, gastric cardia, liver, gallbladder, pancreas, oesophagus and kidney are increased. The aim of this research is to understand how this happens. What is it about the metabolic characteristics of obesity that causes specific cancers to develop? Understanding this is critical in enabling effective ways to screen for and to prevent and treat the cancers that develop in overweight and obese people.
What is the hypothesis of the research?
The reasons for the increased risk of cancer in obese people are poorly understood and may vary depending on the type of cancer. Obese people have different levels of circulating metabolites in their blood in comparison to people who are not obese. Previous research suggests that changes in the levels of various metabolites in the blood that occurs in obesity is important. Metabolites are sources of fuel and building blocks essential for cells and tissues. Indeed, research shows that some of these metabolites stimulate cancer cell growth in laboratory experiments. Therefore, our hypothesis is that obese people are more likely to develop cancer due to the exposure of the bodyâs cells to altered levels of certain circulating metabolites.
B2942 - Persisting Effects of Prenatal Exposures on Child Outcomes - 30/08/2017
B2941 - Understanding the extent of and value in cross-over between longitudinal study populations - 30/08/2017
The UK has over 30 major longitudinal research studies, with about 2.2million people taking part. There are potential research benefits of understanding the extend to which people take in multiple studies. These benefits are scientific and pragmatic. Scientifically, it is important that researchers understand measurement error; which is a factor of all longitudinal studies no matter how well they are managed. By comparing like information collected by different studies on the same person we can help understand how the different study methods impact on quality and error. Pragmatically there may be cost benefits from being able to share information (e.g. expensively generated genetic information) and participant benefits (e.g. reducing burden of taking part). Furthermore, information collected in one study may help inform strategies to deal with information missing in other studies. However, these sorts of comparisons are relatively new and the ethics, governance and information security considerations need to be thought through carefully to ensure that data sharing and analysis are conducted in an appropriate manner which is acceptable to participants and those running the studies.