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.

This project will explore the perception of environmental conditions on the face shape of 15 year old children.

The question that will be addressed does environmental surroundings influence face shape?

Exposure to natural environments has been shown to be associated with child development and outcomes later in life. This will be investigated by measuring exposure to the natural environment using a combination of linked spatial environmental indicators and self-reported data. For example, normalized difference vegetation index (NDVI) measurements will be used alongside subjective measurements of parks visits and outdoor time. This will assess exposure multi-dimensionally, by measuring how much an individual visits natural environments as well as the abundance of vegetation in their living environments.

The primary outcome of interest will be emotional, social and behavioural development, primarily assessed using the Strengths and Difficulties Questionnaire. It will be assessed at multiple time points and corroborated from parent and teacher-reported sources. Other mental wellbeing/developmental measures will be used as secondary outcomes. The project will also investigate potential intermediate variables such as air pollution, maternal wellbeing, biomarkers of stress and birth outcomes. Access to the natural environment is often distributed
by social class / socio-economic status. Therefore detailed and multiple dimensional indicators will be used to account for confounding.

We now know that children who have asthma and are also obese are more likely to require an urgent visit to the doctor for breathing problems than those who are not obese. Obese children are thought to have a different type of asthma, which is more severe and harder to control. This may be because the current treatments we use to manage daily symptoms do not work very well for this type of asthma. There are many theories that could explain why this is happening. One possible reason could be that the child’s genetic makeup may also play a role in the development of obesity as well as influence their response to treatment.

To address this problem, my proposed project aims to investigate how obesity can affect the response to treatment in children with asthma. In the first phase, I will examine whether obese children with asthma are less likely to respond to standard treatments than those who have normal weight using cutting-edge statistical methods. In the second phase, I will investigate whether certain genetic changes influence the children’s ability to respond to asthma treatments and if these same changes are also affected by excess weight.

To do this, I will analyze data that has already been collected from a large number of children with asthma in many different countries, including ALSPAC. The data that will be used for this project forms part of an international collaboration in pediatric asthma, called the Pharmacogenomics in Childhood Asthma (PiCA) Consortium. PiCA is the largest pediatric asthma consortium in the world and has all the necessary data to successfully carry out this research.

I expect the results of this project to help doctors and scientists understand why obese children with asthma are suffering with more severe symptoms than others. Identifying the reasons why they are severe will promote the development of new targeted treatments for children with asthma who have excess weight, with the ultimate goal of improving the management and quality of life for these children.

Reducing childhood obesity is a major global public health challenge. However, interventions designed at changing individual or family behaviours often do not show an impact. It is important therefore to better understand the causes of childhood obesity. Whilst there is some evidence that factors in pregnancy are associated with obesity, it is unclear whether these are causes. It is also unclear whether different factors affect obesity at different ages.

For example, there is evidence that children whose mothers had gestational diabetes may have a greater risk of childhood obesity. Studies in Europe and South Asia have also reported that this effect may not emerge until later on in childhood. There is also evidence that infants born preterm are about two-fold more likely to be obese later in life than those born at term. However few studies have examined the association between preterm birth and BMI in later childhood.

In terms of socioeconomic factors, lower family socioeconomic position (SEP) has been associated with higher BMI from as early as 9 months. However, there is inconsistent evidence on the extent as to whether which the effect of SEP increases, decreases or remains constant over time. There is also evidence that neighbourhood exposures in the post-natal period (such as exposure to green spaces and area-level deprivation) are also associated with childhood BMI; however to our knowledge the effect of these exposures before birth has not been investigated.

The LifeCycle project is an EU initiative to harmonise key data from a number of EU studies, including ALSPAC. To maintain participant anonymity, we will be using innovative software called DataSHIELD to analyse the data. DataSHIELD allows the remote analysis of summaries of this harmonised data, but prevents the access of individual data.

The LifeCycle project provides a unique opportunity to examine how early life factors might relate to childhood BMI. In this ‘proof of principle’ study we will use DataSHIELD to carry out remote analyses of LifeCycle cohorts, selecting variables that have evidence for some effect on childhood BMI (maternal and paternal education, area level deprivation, access to greenspace, gestational diabetes and gestational age at birth). We will conduct analysis on BMI at different points throughout childhood to explore how the effect of these factors emerges over childhood.

The glycocalyx is a gel-like layer covering the inside surface of all blood vessels. It is essential for normal flow and activity of the blood. Laboratory studies suggest damage to the glycocalyx increases risk of heart disease and pregnancy complications such as preeclampsia, gestational hypertension, gestational diabetes, small and large for gestational age and preterm delivery. Glycocalyx could be a valuable target for disease prevention and treatment. We do not have studies in large numbers of humans that use methods which could help us understand the causal effects of the glycocalyx. The clycocalyx can be measured in two ways: (i) measures in stored blood samples of molecules that are inside the glycocalyx but are shed into the blood when it is damaged (e.g. heparin sulphate proteoglycans, hyaluronic acid and syndecan 1 (SND1) and (ii) microscopic measurement of of small blood vessues under the tongue. We want to add both of these types of measurements to ALSPAC to improve our understanding of how the glycogalix could influence health and well being in pregnancy, during childhood and in adulthood.

The International Cannabis Consortium has been created to combine the results of multiple genome-wide association studies of different cannabis use phenotypes (e.g., lifetime use, age at initiation, frequency of cannabis use) in meta-analyses in order to increase the probability of detection of genetic variants associated with individual differences in cannabis use.

This project will summarise and collate information gathered by ALSPAC and TwinsUK describing participant understanding and feelings towards 'novel' methods of data collection. This is in response to rapid changes in possibilities for data collection which are emerging from the rapid digitisation of routine information, that many people now routinely carry powerful computers (mobile phones, smart devices), and that many devices are now connected to the internet (e.g. smart doorbells and smart thermostats). There is potentially very valuable information which can be collected through either linking to individuals' records or by collecting the 'Digital Footprint' records left through using digital connected devices. In addition, these connected devices - e.g. mobile phones, or smart speakers - provide an opportunity to collect data in new ways.

It is vitally important that studies - such as ALSPAC and TwinsUK - understand participants views on this. This is so that studies can understand what is acceptable and what is not, what safeguards are needed to ensure acceptability, and how to inform participants about these new options and how they could work. This project is summarising existing information, it is not collecting any new information.

DNA methylation signatures of aggressive behavior may capture lifetime trait dynamics and environmental exposures. DNA methylation in peripheral blood is known to be associated with a variety of exposures (e.g. cigarette smoking) and traits (e.g. BMI). We propose to determine if DNA methylation is associated with aggressive behavior to better understand the biological correlates of aggression and to evaluate the potential utility of aggression biomarkers in peripheral blood.