The obesity epidemic has largely been attributed to the modern food environment, in which foods high in fat and sugar are affordable, accessible and aggressively marketed. However, genetics and individual eating habits have also been argued to heavily influence weight. Eating more than needed can lead to weight gain, but for some, exercising control and knowing when to stop is particularly difficult. Longitudinal studies have suggested that flexible restraint (e.g. a gradual approach to dieting, using control when over-eating) is more adaptive and prevents weight gain in individuals with a lack of control over eating relative to more rigid forms of restraint (an ‘all or nothing’ approach). This study proposes to investigate how much of the relationship between inherited genes and obesity in adulthood, is facilitated by eating habits and food preferences, and whether these pathways can be lessened through contending eating behaviours and food preferences in childhood and adulthood.

Maternal and paternal characteristics (for example, maternal and paternal obesity, maternal gestational hypertensive disorders and maternal dietary intakes) are linked with the offspring’s risk of obesity and cardiometabolic disease in adulthood (such as coronary heart disease and type two diabetes). One explanation for such correlations is that maternal and paternal phenotypes alter the environment that the sperm, egg cells and fetus develop in, thereby causing the offspring to be more susceptible to cardiometabolic disease in adulthood. However, mothers and fathers also pass on their genes to their children, and provide an environment for their children to grow up in, both of which provide alternative explanations for the aforementioned correlations. Because of this it is currently unclear whether the mother’s and father’s BMI, maternal gestational hypertensive disorders and maternal dietary intakes have causal effects on the offspring’s risk of obesity and cardiometabolic disease.

In the last 20 years, there was a tremendous progress in identifying genetic risk factors for autism or neurodevelopmental disorders (NDDs) such as intellectual disability and epilepsy. If mutations affecting synaptic or chromatin remodelling genes are now well accepted as susceptibility factors for autism and NDDs, many key questions remain unanswered: (i) What is the interplay between the common and the rare genetic variants ? (ii) What are the genetic and environmental factors that influence the clinical trajectories of the patients? (iii) What are the specific brain processes involved? To address some of these questions, we will investigate the genetic and phenotypic data of the ALSPAC cohort to understand how genetic mutations in autism/NDD associated genes can have different consequences on the cognitive development of the individuals depending on the genetic and environmental background. Beyond improving our knowledge on the genetic architecture of autism/NDDs, our project should also lead to the identification of protective factors explaining how some individuals are resilients to strongly deleterious mutations.

Atopic Dermatitis (AD, also known as atopic eczema and eczema) is a common disease affecting 20% of children in the UK and other high-income countries. The major genetic risk factor for AD is loss of function mutations in filaggrin, a critical skin barrier protein. There are many theories around the high prevalence of filaggrin mutations in European and Asian populations and of eczema including some proposals that having a leaky skin barrier and an overactive skin immune system might lead to skin immune cells being activated through the skin resulting in protection against pandemics. The COVID-19 pandemic is associated with substantial COVID-related health problems and deaths.

We will use data from the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective birth cohort study questionnaires and clinical visits to identify people with evidence of eczema in childhood, and genetic data to identify people with filaggrin null mutations. We are very familiar with these data in ALSPAC and have very recently analysed these data. We will then determine if people in early adulthood (the age of the cohort at the time of pandemic emergence) with evidence of childhood eczema are at reduced risk of reporting symptoms suggestive of COVID-19. The subsequent analysis will involve assessing if those with filaggrin null mutations (with and without eczema) have reduced risk of reporting COVID-19 symptoms. We will stratify by the presence or absence of asthma to see if the risks vary in these subgroups.

Existing research on depression vulnerability shows that early experiences such as exposure to childhood abuse could leave “cognitive scars”, which could increase vulnerability in later stages of life. Childhood emotional maltreatment is found to be strongly associated with vulnerability to psychopathology in comparison to physical and sexual maltreatment.(1) Adolescents having experienced childhood maltreatment were shown to depict reduced positive spontaneous thought, a feature of ruminative thinking constituting a risk factor for depression.(2) However, the role of mediating factors like cognitive styles in the association between childhood trauma and depression could be further explored. Various trauma types excepting physical neglect, predict depressive rumination, which predicts depression.(3) The differential association between age of exposure to trauma or specific trauma types and depression could be further researched as exposure to trauma in adolescence may have a greater effect size than that during early childhood with regard to developing increased odds of psychotic experiences. Examining the influence of mediating factors could be beneficial for preventing mental health issues such as distress and impairment at the population level by targeting negative cognitive styles.(4) Age groups requiring further support and intervention could be identified for addressing specific types of childhood trauma

Adverse childhood experiences (ACEs) have been consistently linked to psychiatric difficulties in adolescents. Individuals with at least 4 ACEs are at four times the risk of experiencing mental distress and disorder in their lives. ACEs have been estimated to contribute to approximately 30% of cases of anxiety and 40% of depression in adults in a North American sample and more than a quarter for both conditions in Europe. The combined annual costs of depression and anxiety attributed to ACEs were approximately $51 billion in Europe and $82 billion in North America. Adolescence is a tumultuous time, with significant life events and high rates of mental disorder occurring during this life stage. It is essential to assess the effect of exposure to ACEs on the severity of mental disorders at this stage in the life course.

Cancers develop for many years before they are diagnosed. Using data from first-generation ALSPAC offspring, we aim in this study to estimate the effects of being more genetically susceptible to obesity-related cancers that commonly emerge in adulthood on metabolic traits measured in blood across early life; this should help to reveal what early stages of cancer development look like and when they occur. More specifically, we will examine associations of genetic risk scores for different cancers that are known to be influenced by obesity, e.g. colorectal cancer, with traits from targeted metabolomics measured in childhood (age 8y), adolescence (age 15y), and young adulthood (age 18y and 25y). This allows us to view subtle changes in metabolism over time which precede the onset of clinically detectable cancer by several decades. Recognizing the early signs of cancer development is vital for informing early detection, preventing its onset in older age, and improving survival.

The Covid-19 lockdown has shone a light on the importance of where we live for our health and wellbeing. Living in the countryside; having a garden; living in a cohesive neighbourhood; being within walking distance of a park: these factors create very different lockdown experiences, even between neighbours living a stone’s throw apart.

Research into neighbourhood factors and mental health is not new. However, lockdown has created a natural experiment in which people’s activities outside the home are largely being confined to their immediate neighbourhoods. Lockdown has thus amplified the potential detrimental – and protective – effects of neighbourhood conditions on our mental health. Investigating this relationship is not simple. It is important to take into consideration potential factors that might confound associations (e.g., prior mental health). It is also important to take into consideration how individual-level factors such as housing type might modify any associations of neighbourhood characteristics with mental health.

The current project will explore the relationship between neighbourhood characteristics during lockdown – including population density, greenspace, deprivation, and social fragmentation – and people’s symptoms of anxiety and depression during and after lockdown. Analyses will control for key confounders of the association. Moderation of associations according to household composition, housing type, garden access, and perceived access to nature will be explored.

Whilst it is established that children of lower socioeconomic position (SEP) generally have worse mental health outcomes, most existing research is cross-sectional. Longitudinal studies are important for understanding when inequalities first emerge and the course they take (e.g. stable, widening or decreasing). Whilst longitudinal approaches are now commonly used to model inequalities in height and weight they have rarely been used for mental health outcomes. The aim of this project is use data from multiple EU studies to describe how inequalities in key mental health and cognitive outcomes emerge across childhood.

The aim of this project is to investigate the effect of socioeconomic position on trajectories of key mental health and cognitive outcomes across childhood. It will also serve as a ‘proof of concept’ for using DataSHIELD to conduct multilevel analyses. Our specific aims are to (1) to identify the age at which inequalities emerge for different mental health outcomes, and (2) to describe whether inequalities decrease, remain stable, or widen over time.