A subgroup of people in the population have a change in their genetic make-up that greatly increases their risk of physical disorder and psychiatric disorder. The medical consequences of these genetic changes are however still very poorly understood. Particularly, we don't really know how these changes lead to increased risk of combinations of physical and mental health problems over time. As presence of a physical or mental health problem increases risk of other ones developing, it is important to understand how and why this happens in this high-risk group. Because these genetic changes are rare, it is important to bring together large samples to study their role in medical outcomes properly. This is particularly important if we want to understand how these changes influence the combined risk of physical and mental health problems in different groups within the population, for example young people versus adults, different ethnic groups and groups from different socio-economic backgrounds. To study these important questions, we propose to work together across four large UK studies in which these genetic changes have been established and which have collected rich information on physical and mental health as well as relevant risk factors. The data sets we will work with differ in the age and ethnic and socio-economic background of the participants. We will be able to follow over time how risk of physical and mental health problems influence each other and how this may be different in these different age. ethnic and socioeconomic groups. The findings will have important implications for developing better interventions for this group, for understanding complex medical risks in the population more generally and for insights into the biology of complex medical risks.

We propose to address the problem of handling large-scale genome-wide DNA methylation data. To this end, we will develop a novel technique for clustering DNA methylation (DNAm) sites which will aid reducing the complexity of the subsequent EWAS. For example, a DNAm site that is hypo-methylated in the smoker cohort but hyper-methylated in non-smoker one merits further analysis for significant association with smoking, while those sites exhibiting no difference in the two cohorts does not.
We will investigate the use of algorithms for large matrix factorisation under constraints to provide a natural clustering of DNAm sites, and study what statistical guarantee is achievable under which conditions. To verify the suitability of the proposed method, we propose to use the DNA methylation data available from ARIES.

In the UK 14 million people live in poverty. Four million of these are children. The level of child poverty is rising, and the rate is projected to accelerate in coming years. Growing up in a deprived environment can have a profoundly negative effect on a child’s development. Children from deprived backgrounds are more likely to be placed in special education, fail courses, and complete fewer years of schooling. But the adversities children encounter extend well beyond economic hardship and incorporate multiple familial factors like chaotic home life, poor parental mental and physical health, lack of community support, poor schooling and communication difficulties. These factors have a well-documented impact on multiple child outcomes including educational attainment, mental health, and behaviour. This is a global problem. Up to 50% of children and adolescents growing up worldwide experience at least one episode of childhood adversity in early life: 30% of all mental health problems are attributable to such adversity. The effects are also persistent – early adversity can set a life-long trajectory associated with poor physical and mental well-being and significantly worse occupational and economic outcomes. This results in an inter-generational cycle of disadvantage where deprivation impacts each subsequent generation. Supporting young people who face adversity is one of the major modern challenges for educators, practitioners and policy-makers, as they work to reduce educational under-attainment, poor economic outcomes and address the burgeoning mental health crisis.

Yet not all children who face adversity go on to experience poor outcomes: certain factors appear to insulate children from hardship, such that they demonstrate resilience (broadly defined as succeeding in a particular domain, such as education, despite experiencing adversity). Resilience within mental health is an increasingly recognised phenomenon, but our knowledge about which factors foster resilience across a broader range of outcomes, different populations and in response to diverse sources of adversity is currently limited. Understanding the cross-domain factors that promote resilience is vital to drive the development of interventions that improve the outcomes of child and adolescent victims of adversity. This is the purpose of our project. We want to explore how different environmental factors interact with cognitive and brain development, whether particular features of a child's environment are most strongly linked with these outcomes, and whether some factors foster resilience.

Mental health problems in children are considered to be one of the biggest challenges of the current century. The onset of many behavioral and cognitive problems is found to be in childhood with trajectories into adulthood. There is a growing body of evidence that insufficient sleep and sleep difficulties are associated with an increased risk of behavioral problems and cognitive difficulties in school-aged children. Compared to the literature in school-aged children relating sleep to child behavior or cognition, little is known in preschoolers. in a systematic review, we showed that a longer sleep duration and a higher quality of sleep in preschoolers were associated with better behavioral and cognitive outcomes. However, small sample sizes and small number of publications limit the validity of the results. Furthermore, longitudinal studies are rare.

Socioeconomic differences in cardiovascular health are evident in adulthood. When these inequalities emerge and how they change through the life course is not well understood. Understanding when inequalities in cardiovascular health emerge may inform early life prevention opportunities.

Maternal education, a predictor of social-economic status, has been associated with several offspring health outcomes during the life course (e.g. obesity, type 2 diabetes, cognitive function...). The biological mechanisms regulating this association are yet to be understood. Possible mediation in the maternal education-offspring health outcome relationship might be played by DNA-methylation epigenetics markers. We therefore aim to investigate how epigenetics changes are associated to maternal educational attainment.

Between 2015 and 2016, obesity affected approximately 13.7 million children and adolescents in the United States. Children with obesity are more likely to have high blood pressure, abnormal lipids and insulin resistance even though overt cardiovascular disease may not develop for decades.Additionally, children with obesity are at increased risk for musculoskeletal and mental health disorders, as well as certain cancers. This project aims to to better understand the development and progression of the metabolic derangement seen with obesity in children as well as the associations with development of comorbidities. Inflammation is considered to be the common link between obesity and its progression to various comorbidities. If we are able to identify an early signal in children with obesity who are more likely to develop diseases such as asthma, cardiovascular disease and cancers we will be able to address the problem in a timely fashion and offer focused intervention and treatment to these high risk children

Mental illness accounts globally for one third of years lived with disability, leading to tremendous loss of human, societal and economic potential. Most symptoms (e.g., depression, anxiety, conduct problems) emerge before adulthood, highlighting the first two decades of life as an important period of heightened vulnerability. Epigenetics has emerged as a biological system that captures the underlying genetic and environmental risk factors, but we do not yet understand the developmental dynamics in this system over time. Such knowledge, however, is critical if we are to understand how mental health disorders develop, and thus how they may be prevented.

Sleep disturbances during childhood are common and often resolve spontaneously without intervention (Touchette et al., 2005; Galland et al., 2012). However, those that are persistent and frequent have been shown to be associated with the development of later psychopathology including psychotic like experiences (Jeppesen et al., 2014). Previous research exploring data from the Avon Longitudinal Study of Parents and Children has shown that children, aged 2.5 and 9 years old, experiencing frequent nightmares were more likely to report psychotic experiences at age 12 (Fisher et al., 2014). Similarly, nightmares at 12 years old was also found to be associated with an increased risk of psychotic experiences at aged 18 (Thompson et al., 2015). Such findings suggest that nightmares during childhood may represent an important and clinically significant indicator for risk of psychotic experiences in adolescence.

The relationship between childhood sleep disturbances and the presence of psychotic experiences beyond the age of 18 is still yet to be understood. Research has shown that the incidence of psychotic experiences often peaks during adolescence to early adulthood (McGrath et al., 2016) and sleep disturbances frequently co-occur with psychotic like experiences during this time (Taylor et al., 2015). Consequently, understanding which early sleep problems present as a risk factor for the development of later psychotic experiences is key. This project will explore the longitudinal associations between childhood and adolescent sleep problems between the ages of 2.5 - 17 years old and self-reported psychotic experiences at 24 years old.

Fisher, H.L., Lereya, S.T., Thompson, A., Lewis, G., Zammit, S. and Wolke, D., 2014. Childhood parasomnias and psychotic experiences at age 12 years in a United Kingdom birth cohort. Sleep, 37(3), pp.475-482.
Galland, B.C., Taylor, B.J., Elder, D.E. and Herbison, P., 2012. Normal sleep patterns in infants and children: a systematic review of observational studies. Sleep medicine reviews, 16(3), pp.213-222.
Jeppesen, P., Clemmensen, L., Munkholm, A., Rimvall, M.K., Rask, C.U., Jørgensen, T., Larsen, J.T., Petersen, L., van Os, J. and Skovgaard, A.M., 2015. Psychotic experiences co‐occur with sleep problems, negative affect and mental disorders in preadolescence. Journal of Child Psychology and Psychiatry, 56(5), pp.558-565.
McGrath, J.J., Saha, S., Al-Hamzawi, A.O., Alonso, J., Andrade, L., Borges, G., Bromet, E.J., Oakley Browne, M., Bruffaerts, R., Caldas de Almeida, J.M. and Fayyad, J., 2016. Age of onset and lifetime projected risk of psychotic experiences: cross-national data from the World Mental Health Survey. Schizophrenia bulletin, 42(4), pp.933-941.
Taylor, M.J., Gregory, A.M., Freeman, D. and Ronald, A., 2015. Do sleep disturbances and psychotic-like experiences in adolescence share genetic and environmental influences?. Journal of Abnormal Psychology, 124(3), p.674.
Thompson, A., Lereya, S.T., Lewis, G., Zammit, S., Fisher, H.L. and Wolke, D., 2015. Childhood sleep disturbance and risk of psychotic experiences at 18: UK birth cohort. The British Journal of Psychiatry, 207(1), pp.23-29.
Touchette, É., Petit, D., Paquet, J., Boivin, M., Japel, C., Tremblay, R.E. and Montplaisir, J.Y., 2005. Factors associated with fragmented sleep at night across early childhood. Archives of pediatrics & adolescent medicine, 159(3), pp.242-249.