The study aims to estimate how many people in ALSPAC have been infected with the virus that causes COVID-19. We don’t know yet if having antibodies gives someone long-lasting protection from the virus. The results of this study may help guide public health policy and the government’s plan for its antibody testing strategy.

Other population-based research studies in the UK are also asking their participants to complete the same antibody test. Analysing the information from ALSPAC alongside these other studies will allow a greater understanding of variations across ethnicity, age, socio-economic status and geography. We can use these antibody test results in several ways alongside information already collected in ALSPAC. Such as
information on COVID-19 symptoms, (already collected via questionnaires) medical outcomes, (through record linkage), and data from other clinics and questionnaire that could be related.

Most people have a comfortable tolerance for information received via their sense organs (i.e., sounds, tastes, smells etc.) while others have SENSORY SENSITIVITIES (i.e., over-reactivity, such as when sounds feel too loud) or SENSORY AVERSIONS (negative emotional responses, e.g., when sounds trigger anger, e.g., to the sound of chewing). Our prior proposal (approved and ongoing) investigates AUDITORY sensitivities (hyperacusis and misophonia; where sounds cause pain, or distress/anger respectively). However, sound-difficulties are just one branch of a broader profile which can affect multiple senses, and cause considerable negative impact in day to day life. For example, broad sensory sensitivities play a significant role in anxiety disorder (sometimes via neurodevelopmental conditions such as autism). With poor well-being and anxiety placing substantial financial burden on society (e.g., £12 billion invested annually by the NHS), our study aims to better understand sensory sensitivities and aversions with a questionnaire that identifies those ALSPAC participants who have such difficulties across multiple senses. The wealth of ALSPAC back-data will then allow us to “reach back” into their childhood, to explore their early development in terms of wellbeing, mental health, mood and feelings (DAWBA, Strengths and difficulties, mood and feelings, PANAS, Locus of control, anxiety) as well as their cognitive skills (eg., attention tasks), and schooling attainment (school key stage linked data). We predict that adults with sensory sensitivities/aversions were likely already expressing poorer mental well-being at a younger age, and may have heightened scores on tasks such as attention-to-detail and obsessive control, and potentially lower scores on school attendance and attainment.

Often a large number of equally plausible possible analysis options are available to researchers. Multiverse analysis is a proposed way of overcoming this problem where all plausible analyses are conducted and the results of all are interpreted in the context of each other. This information can be used as a measure of the reliability of a result, which in turn is useful for scientific advancement and deciding policy. However, multiverse analysis can be time consuming and complex. This project will use ALSPAC data to test and inform the building of an R/python package to conduct multiverse analysis, which is currently being built. This package will make multiverse analysis easier to conduct, encouraging greater adoption of this technique across the health sciences.

Mental health problems represent one of the leading drivers of overall disease burden. Half of all lifetime psychiatric disorders present before adulthood, with a point prevalence of between 10% and 20% of children and adolescents experiencing mental health difficulties. In addition, more than 40 percent of youths with a lifetime psychiatric disorder go on to develop at least one additional mental illness concurrently or later in life. This adds significant complexity to diagnosis and interventions and further increases the likelihood of negative outcomes, such as criminality, low educational attainment and unemployment. A developmental perspective that investigates the interrelations between multiple mental health issues from early life up until adulthood is likely to offer important insights into why mental health problems commonly co-occur and can consequently inform prevention strategies. In the current project, using state-of-the art statistical techniques, we propose to analyse the developmental relations of mental health problems. We will further examine potential factors linking mental health problems together such as genetic predispositions to mental health problems, perinatal risk factors, and school problems. The results of this project will have important clinical implications. In particular, they will shed light on potential risk factors that drive the development of co-occurring mental health problems, give insights into which symptoms are likely to precede other symptoms and further help identify other factors that might exacerbate the development of co-occurring mental health problems. Thus, findings will inform early intervention strategies for preventing the development of secondary mental health disorders.

Modifiable risk behaviours include smoking, alcohol intake, drug use, poor diet, and physical inactivity. Participation in risk behaviours in adolescence is associated with poorer mental health at age 18. Participation in risk behaviours and poor mental health are both independently associated with poorer health outcomes later in life and reduced life expectancy. Previous genome-wide association studies (GWAS) have identified genetic variants associated with participation in risk behaviours, depression, anxiety and wellbeing. Given the associations between risk behaviours and mental health outcomes, it is important to understand the genetic overlap between these.

We want to better understand why some people develop certain disease as they age, while others don’t. We think that by looking at how our genes change their behavior as the body grows older, we can gain new insights into how the aging process leads to disease, and into the aging process itself. This is not only relevant to the typical diseases of the elderly (e.g. rheumatoid arthritis, heart disease, diabetes, dementia and cancer), but also to younger people who develop diseases that are occur at specific age intervals (e.g. MS, infertility, certain cancers).
The project will perform advanced mathematical analyses of the regulation of genes, to develop new computer methods that can predict and explain the development of disease. Our goal is to eventually make new diagnostics, such as blood tests, that can be used to catch age-related diseases earlier and more accurately, so that patients will receive earlier and better treatment.

Meeting physical activity, sleep and sedentary behavior guidelines is associated with better cardiometabolic health and adiposity outcomes among children and youth. Unfortunately, recent estimates suggest that only 25.4% of adolescents in the US meet sleep guidelines, 26.1% meet physical activity guidelines, and only 5% meet guidelines for sleep, physical activity and sedentary behavior. Although some evidence indicates that there is a positive association between physical activity levels and sleep duration, findings among children and adolescents are not consistent and are limited by a predominantly cross-sectional study design. Although low income and minority youth are at a higher risk of not meeting both sleep and physical activity recommendations, it is unclear whether the sleep and physical activity relationship varies by racial, ethnic or socioeconomic group. Furthermore, exercise intensity appears to have a strong, positive relationship with sleep, although more research is needed to determine whether exercise at a light or moderate intensities can lead to improvements in sleep outcomes. This study aims to examine the association between physical activity and sedentary behavior, measured objectively at 11, 13 and 15 years of age, with subjectively-measured sleep at age 15. Furthermore, this study aims to understand whether the sleep and physical activity relationship varies by demographic characteristics and measures of adiposity.

There are key transitions that often occur when adolescents become adults, such as leaving full-time education, starting a full-time job, living with a partner, or becoming a parent. In previous generations, when these transitions happen early or happen close together, they have been shown to be related to poorer health and related behaviours, for example, weight gain or increased smoking. However, there is little evidence available on what typical transition patterns look like for today’s young people, which patterns are the most harmful to health, or the reasons that these patterns cause poorer health (for example, is weight gain in those who have made lots of these transitions early in life explained more by the extra stress or by lack of time to eat healthily or exercise). Using data from two recent UK birth cohorts, and sophisticated methods of analysis, we will try to answer these questions. Where possible, we will see if findings differ for sex, ethnic minority, and LGBTQ+ groups. This information can help us understand the best way to support young people moving from adolescence to young adulthood, to help optimise their health later in life.

Eating disorders (ED) such as anorexia nervosa (AN), bulimia nervosa (BN), and binge-eating disorder (BED) are common psychiatric disorders with life-long health impacts. Additionally, current treatment options have limited effectiveness, highlighted by the observation that only 30% of adult patients with AN fully recover. The development of EDs is highly complex and driven by environmental and genetic factors. Previous research has suggested that EDs run in families, but the specific genetic variants associated with risk for EDs are not well understood. Twin studies have shown that the heritability for EDs ranges from 40%-70%. Similarly, to other psychiatric disorders, such as depression or schizophrenia, many genetic variants with relatively small effect underlie the overall genetic risk for EDs. Due to the nature of these effects, extremely large sample sizes are necessary which can only be amassed by international efforts. For AN previous large scale genetic studies, comparing patients with healthy controls, have been successful in pinpointing genetic variants associated with the illness (Duncan et al., 2017). However, no such attempts have been made regarding BN or BED and the field of EDs is lacking behind the genomic discovery of other psychiatric disorders. The success of these studies, which search across the entire genome to find associated genetic markers, is highly dependent on the number of patients and controls included in the research because the sample sizes defines the statistical power to detect significant associations. Thus, worldwide joint forces are necessary to combine datasets to boost sample sizes. Therefore, we propose to include ALSPAC participants in the international approach: Using the rich database of ALSPAC to identify patients diagnosed with AN, BN or BED and add them to international cohorts examining the genetic architecture of EDs. The findings may provide a better understanding of the development of EDs and may help to identify or new treatment strategies including potential targets for pharmaceutical treatment.