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.

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.

Liver disease remains the only disease where mortality is rising in the UK. Alcohol-related liver disease (ARLD) and non-alcoholic fatty liver disease (NAFLD) are the two commonest indications for liver transplantation in this country.

ALSPAC analysed the prevalence of these diseases in the F@24 clinic using a modality called transient elastography, also known as Fibroscan. This gives measurement on how fatty the liver is (steatosis) and how scarred it is (fibrosis). This demonstrated over 1 in 5 participants had NAFLD, with 1 in 40 having evidence of fibrosis. Individuals with harmful drinking patterns AND obesity were at greatest risk of fibrosis. This is all the more alarming as ARLD and NAFLD tend to be diseases that manifest in the 4th and 5th decade.

ALSPAC has an opportunity to be, to the best of our knowledge, the only birth cohort to sequentially assess its participants for liver disease. We are proposing to re-assess the participants that remain in the G1 cohort for liver disease to see if there has been a progression in the number of cases seen. This would be one of the first attempt to map the development of liver disease in the general population setting.

A previous study in 350 6-year-old children has suggested that digit sucking has no effect on craniofacial parameters but may affect occlusal development. It is reasonable to expect that if digit sucking has an effect on the dentition this also should also influence facial shape. We have a large sample and we should be able to determine whether the frequency of digit sucking and hand used have and long-lasting changes in face shape.
1. Campos MPMS, Valença PAM, Silva GMD, Lima MC, Jamelli SR, Góes
PSA. Influence of head and linear growth on the development of malocclusion at six years of age: a cohort study. Braz Oral Res. 2018 Oct 11;32:e98.

Deep vein thrombosis (DVT) usually presents as a blood clot which forms in the deep veins of the legs. It can be a life-threatening disease if not identified in time, leading to pulmonary embolism or heart failure. While research have found some risk factors using observational epidemiological studies, little is known about the exact causes of DVT.

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.

Population-based genetic and imaging studies of depression in adults have greatly advanced our understanding of this leading cause of global disability, particularly regarding associated neurobiological features. However, the causes and timings of such brain changes remain unknown, highlighting the need for a targeted study of the origins of these differences in younger individuals.

The largest risk factor for depression is a positive family history, and the major risk period for its development is during adolescence. The current project will therefore investigate whether the origin of these imaging features in adults (from work in UK Biobank, Enigma and Generation Scotland) is seen earlier in life in relation to increased risk for the disorder (including family history, polygenic risk, and associated traits such as depressive cognition, locus of control and self-esteem) using genetic and imaging data from children and parents in ALSPAC. Only now are there adult samples of sufficient size to inform such a focused study of adolescent depression, and this will form the first step towards determining potential causative associations between risk factors, associated neurobiology and depressive symptoms.

Summary data from these investigations in future could be combined in meta-analyses with other cohorts (e.g. MoBa) and consortia for discovery and replication. This would be under strict governance structures, where data would remain in Edinburgh and no individual data would be shared and this would be the focus of a separate application.

Different parts of our brains communicate with one another as we learn new information during the day, then continue to communicate “offline” as we sleep. This overnight brain activity helps file memories for long-term storage, but the process is complex and delicate: lots of genes influence brain activity in ways we do not yet understand. We also need to establish why and how this process is disrupted in disorders like schizophrenia, which are associated with impaired sleep-dependent brain activity and memory. This study will investigate links between a set of schizophrenia-associated genes and brain function during sleep.

Participants will be asked to wear a ‘fitbit’-like device for 2 weeks of normal activity, so we can track when and how much they sleep. We will then use a comfortable sleep cap that contains an array of recording devices to monitor EEG brainwaves while participants sleep at home for 2 nights. By analysing the EEG data using machine learning methods (similar to those used for speech recognition), we will identify patterns of activity that make up their personal “sleep fingerprint”. This will allow us to test whether these fingerprints vary according to genetics in a healthy population, without interference from things like medication that complicate patient studies.

The main outcomes will be (1) development of novel analysis methods allowing us to capture brain activity, (2) a deeper understanding of the mechanisms that determine variation in patterns of brain activity during sleep and (3) a route towards understanding mechanisms of schizophrenia liability.

Heavy marijuana (MJ) use in adolescence has been associated with 2-4 fold increased risk for schizophrenia (SZ) in later life. It is unclear if lighter and more sporadic MJ exposure (i.e. recreational MJ use), a pattern more typical of most adolescent users, has similar deleterious effects especially when more potent forms of MJ have become the norm during the past 2 decades. In a recently completed 3-year longitudinal study, we found that unaffected adolescent first-degree biological relatives of schizophrenia patients with recreational MJ use failed to show age-expected maturation in processing speed and executive functioning and in pruning of gray matter cortical thickness within dorsolateral prefrontal and parieto-temporal brain regions. The overall objective of this ALSPAC proposal are to understand the nature of the association between adolescent recreational MJ use and schizophrenia susceptibility. The specific aims are to delineate the impact of adolescent recreational MJ use on cognitive maturation, brain cortical development and its specificity on risks for developing schizophrenia and other common psychiatric disorders in later life.