Children of parents with mental illness (COPMI) face a heightened risk of developing mental disorders themselves. While the literature underscores the importance of early interventions, there is a scarcity of studies investigating the economic implications of such interventions. This project seeks to bridge this gap by constructing a health economic model that synthesizes both clinical and economic data, enabling a comprehensive analysis of the potential benefits and costs associated with different intervention approaches.
Hence, in this project, we will develop a health economic simulation model to examine the cost-effectiveness of interventions targeting these children/families. The ultimate goal is to demonstrate the added value of these interventions for children, their parents, and society as a whole.
Upon completion, the health economic model will provide a quantifiable assessment of the economic value of various interventions for children of parents with mental illness. It will enable decision-makers to compare the costs and benefits of different strategies, facilitating resource allocation based on a comprehensive understanding of both short-term and long-term outcomes. Sensitivity analyses will be conducted to assess the robustness of the model to variations in input parameters, and scenario analyses will explore the impact of different assumptions and policies.

There is a lot of variability in lung structure among healthy adults. This variability in lung structure is thought to arise during growth - a concept that is referred to as “dysanapsis” (from the Greek, dys=unequal and anaptixy = growth). Dysanapsis is strongly associated with lung disease and death later in life, but the origins of dysanapsis are poorly understood. A recent genetic investigation identified several variants associated with dysanapsis, but when dysanapsis genetic risk manifests in childhood and whether it interacts with environmental or social factors to impair lung function is unknown. This study has two objectives: i) describe the relationship between dysanapsis genetic risk and lung function at various timepoints during lung growth; ii) test whether environmental exposures (environmental tobacco smoke) or social deprivation modify these relationships. No new measurements or samples are required for this study.

Resilience is known to be the process and outcome of successfully adapting to difficult or challenging life experiences. Promoting resilience is helpful to minimizing the detrimental impact of life stressors which may be unavoidable at times. While interventions aiming to enhance resilience are increasing among different age groups, there remains gaps in our understanding of how and when resilience manifest, as well as the role of negative and positive emotions in this process. This project aims to use intergenerational data from ALSPAC to investigate predictors of the trajectories of resilient behavior, and connections between maternal resilience and offspring resilience from the prenatal stages through childhood years. This includes identifying time and environmental predictors that can be useful in designing future interventions to assist individuals who are at risk in coping with stress and difficult situations.

Sleep is vital for maintaining good mental health. Further, sleep and mental health problems are both public health concerns in their own right, with each having a substantive impact on both individuals and society. Adolescence and young adulthood are key periods in which to investigate mental health, as more than half of mental disorders start here. Similarly, sleep problems are often observed in young people. Further, it is crucial to understand under what circumstances and why sleep problems might lead to mental health problems, as this would shed some light on who are the young people most vulnerable for mental health problems. The proposed project will provide ground-breaking research on the prospective associations between sleep and mental health problems in young people using large longitudinal cohort studies, with a special emphasis on specific contributing and mediating factors of these associations. Among these, we will focus on social determinants (SD) (e.g., ethnicity, socio-economic status, housing conditions, food poverty) and cognitive factors as key aspects to consider in these associations in young people. To do this, we will use three population-based longitudinal cohort studies, which are the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Millennium Cohort Study (MCS), both from the UK, and the Adolescent Brain Cognitive Development (ABCD), from the US. We will obtain detailed information on sleep (e.g., sleep duration, sleep fragmentation, sleep efficiency) using subjective (e.g., questionnaires) and objective (e.g., actigraphy) measures, mental health (e.g., anxiety, depression, psychosis, self-harm), cognitive factors (e.g., working memory, inhibition), and SD (e.g., ethnicity, living condition, early life adversities) in large sample sizes (e.g., >10,000 potential participants in each cohort).

Approximately 10-20% of children and adolescents experience socio-emotional difficulties severe enough to merit a diagnosis of a mental health disorder. More than 40% of these youth develop at least one other mental illness throughout their life. A developmental perspective that investigates the interrelations between different domains of socio-emotional development from early life to adulthood can offer important insights into why socio-emotional difficulties commonly co-occur. Using state-of-the-art longitudinal statistical techniques, this project aims to significantly advance our understanding of the mechanisms underlying co-occurring socio-emotional difficulties. It will illuminate the roles of both genetics and psychosocial factors in linking different socio-emotional difficulties together using robust study designs that consider a range of confounders and providing the best available evidence yet on the causal mechanisms underlying the co-occurrence of socio-emotional difficulties. As well as informing preventions and interventions, this will contribute to better, more comprehensive theories of the developmental roots of mental health.

Having a traumatic experience as a child – for example, abuse or deprivation – can have a lifelong impact. People who report having several adverse childhood experiences, or ACEs, are more likely to have health problems later in life.

The Consortium Against Pain InEquality (CAPE) aims to further understand how ACEs might lead to chronic pain in adulthood. We want to consider how other factors (such as mental health or support from friends or family) contribute to pain vulnerability. Our main question is: Do ACEs cause an increased risk of chronic pain in later life, and, if so, what roles do other factors play?

Using existing data from several cohorts, of which the Avon Longitudinal Study of Parents and Children is one, we will run analyses to better understand the factors that may contribute to, or protect against, developing chronic pain, trying to describe the different ways ACEs (of different types, number and characteristics) may be linked to chronic pain (‘causal pathways’).

Urinary incontinence (UI), defined as the complaint of any involuntary leakage of urine is a highly prevalent condition that can have adverse consequences for emotional well-being and quality of life in addition to being of economic importance to health services.
The cause of UI is not completely understood and includes psychological and physiological factors outside the lower urinary tract. The hypersensitivity of the bladder in urinary incontinence has guided researchers to consider psychological factors including anxiety and depression that may be of importance.
The comorbidity between UI and affective disorders including anxiety and depression is well established, but the precise nature of this relationship is unknown. Much of the existing research examining the relationship between UI and anxiety/depression is cross-sectional and is therefore unable to disentangle the temporal relationship between whether poor mental health is a cause or a consequence of UI.
The use of bidirectional MR can help to differentiate causality from correlation by testing the causal effects independently in each direction using single nucleotide polymorphisms (SNPs) found to be robustly associated with each trait in different genome-wide association studies (GWAS).  We will use GWAS summary statistics in a two-sample MR analysis to examine bidirectional causal relationships between anxiety/depression/neuroticism and UI in females. Two subtypes of UI will be explored. Stress urinary incontinence (SUI) is defined as a loss of urine associated with physical exertion, coughing or sneezing whilst urgency urinary incontinence (UUI) is loss of urine associated with a sudden compelling need (an urgency) to void.

Insulin-like Growth Factor 1 (IGF-1) is a critical peptide hormone that plays a pivotal role in growth, development, and cellular regulation. It is primarily synthesized in the liver under the stimulation of growth hormone (GH) and acts as a key mediator of GH's growth-promoting effects. IGF-1 plays a fundamental role in various physiological processes, including cellular proliferation, differentiation, and tissue growth. Its actions are particularly prominent during the pre-adolescent and adolescent stages, where it influences longitudinal bone growth and overall somatic development.
The role of IGF-1 in growth regulation has garnered significant attention in the field of developmental biology. Previous research has demonstrated a positive correlation between circulating IGF-1 levels and height in various populations. Higher levels of IGF-1 have been associated with increased linear growth during childhood and adolescence. Randomized controlled trials of GH treatment in individuals with idiopathic short stature (ISS) , aiming to increase IGF-1 levels and final adult height have yielded conflicting results. Consequently, understanding the causal relationship between IGF-1 levels and height SDS across different ages can provide valuable insights into the mechanisms underlying growth and height variation.
In recent years, genetic studies have made significant strides in elucidating the genetic basis of complex traits, including height. Polygenic Risk Scores (PRS) are genetic risk scores that capture the cumulative effect of multiple genetic variants associated with complex traits, such as IGF-1 levels. As such, these PRS provide a comprehensive assessment of an individual's genetic predisposition to higher or lower IGF-1 levels. Also, using genetic variants from large IGF-1 genome-wide association study (Sinnott Armstrong et al, 2021) as instruments for IGF-1, we have generated preliminary results using Mendelian randomization, showing strong evidence of a causal effect of IGF1 on height. We are seeking to replicate these results by undertaking a one-sample Mendelian randomization study in ALSPAC
Body composition has been shown to influence growth patterns and height disparities among populations. Body Mass Index (BMI) has been suggested as a potential confounding factor in the IGF-1-height relationship. Investigating the relationship between a PRS for IGF-1 and height can help us better understand the contribution of IGF-1 to height variation and may reveal mediating effects of weight and potential gene-environment interactions affecting growth patterns.
This study aims to contribute to the growing body of evidence on the associations between IGF-1 levels, IGF-1 PRS, and height SDS, in ALSPAC. Understanding the impact of IGF-1 and of its genetic predictor on height variation at different ages, while accounting for BMI can offer valuable insights into the pathophysiology of growth.

The duration of gestation is critical for neonatal survival, with early deliveries (<37 gestational weeks) being the leading cause of death in children under five years of age. Despite the global burden, relatively little is known about the processes that determine the timing of childbirth. In part, this limited progress is due to the difficulty in extrapolating findings from animal model systems to humans. However, studies of human genetic variation are starting to shed light on the biology of human labor and the timing of childbirth.

Recent work from our group and others has established robust genetic associations with the timing of childbirth. An easy solution for increasing the number of discovered genes is to increase sample size. However, additional gestational duration associated genes may be discovered from more complex models, in relatively small sample sizes. At the same time, the careful inspection of the known genes may aid in the overall understanding of the biology behind the timing of childbirth.