A powerful avenue into researching the functional consequences of changes in DNAm levels is to correlate DNA sequence variants such as single nucleotide polymorphism (SNPs) to DNAm levels to find both local and distal (for example on other chromosomes) effects. Having completed the largest genetic study of DNAm worldwide to date (through the Genetics of DNA Methylation Consortium) by scanning 10 million SNPs genome-wide, we have identified 270k SNP-DNAm associations. This was achieved by analysing about 400,000 DNAm sites in blood, which is only 2% of 28 million DNAm sites across the genome. There is a huge potential for improved understanding of DNAm variation between individuals and its influence on health and disease by studying other regulatory regions of the genome. We therefore will use novel sequencing technologies based on long reads with the ability to measure all 28 million sites and to determine both the DNAm level and the genotype at single molecule level.

Obesity is one of the most pressing public health challenges worldwide. It is caused by multifactorial causes and could lead to increased risk of cardiometabolic disease. Although obesity is not as common in children as adults currently, the temporal increase in the prevalence of childhood obesity is greater than that of adulthood obesity in multiple countries. However, current public health measures are mostly focused on adult obesity and may not translate to children.

Obesity and overweight were traditionally regarded as the result of an individual’s unhealthy lifestyle (diet and physical activity), but there is increasing recognition that these interact with many other factors; both upstream environmental factors (social, political, and economic) and individual (genetic, psychosocial and biological) factors. These are likely to impact over the life-course. Exposures to environmental obesogens in-utero and/or in early life might also be important. The interactions between these factors are complex. For example, with global economic growth, the reduction in walkability and green spaces are likely to reduce children’s physical activity level which, in turn, result in childhood obesity. These are also compounded with air pollution which might directly and indirectly (also through physical activity) influence obesity. Even though genetic factors account for 40%-70% of obesity risk, the independent effect of individual loci may not completely explain the pathogenesis of obesity because of gene-environment interaction.

Most studies to date focused on individual risk factors for obesity. However, to identify an effective public health strategy to tackle childhood obesity, this study will investigate the interactions between and relative importance of those factors. Additional, since childhood obesity may not necessarily track into adulthood, this study will also look into factors that could predict persistent obesity from childhood to adulthood, which should be clinically most relevant.

To describe and cross reference the incidence of self-harm episodes of ALSPAC participants in (i) the Bristol Self-Harm Register collected by the local NHS Trusts, (ii) nationally collected Hospital Episode data from NHS-Digital, (iii) nationally collected Mental Health data from NHS-Digital, and (iv) self-reported in ALSPAC survey responses. This is intended to provide a future resource for researchers.

Serious mental illnesses (depressive disorder, bipolar disoder, psychotic disorder) are among the leading causes of disability. On top of the burden that mental illness itself poses, individuals affected by it are often also at higher odds of substance use (smoking, alcohol, cannabis) and cardiovascular disease. Together, these so-called co-morbidities of mental illness drive the low life expectancy in individuals with mental illness compared to the general population. It is unclear however, what the causal nature is of these relationships. It may be that symptoms of mental illness increase the risk of substance use and cardiovascular disease, but there is also evidence that these co-morbidities can increase the risk of developing mental ill-health. In this project we strive to elucidate the causal nature of the relationship between mental illness and its co-morbidities, by investigating how symptoms of mental illness and (precursors of) co-morbidities develop and associate to each other from early adolescence up to early adulthood.

Prior research in ALSPAC has shown that sleep problems in adolescence are associated with subsequent depression and anxiety (doi:10.1111/jcpp.13288). However, there is still much we do not understand about the complex relationship between sleep and mental health in young people. First, most genetic studies have been conducted in older adults (aged 40 years or older), with less research examining genetic influences on sleep in young people. Second, sleep problems appear to affect mental health more in some people than others but there is limited research exploring which factors influence these individual differences. This project will examine associations between sleep and depression/anxiety across adolescence and young adulthood and focus on the following areas: (i) whether genetic factors previously associated with sleep problems in adults are also associated with sleep problems in adolescence/young adulthood, and (ii) whether associations between sleep problems and anxiety/depression are influenced by genetic factors. Results from this work will impact our current understanding of the role sleep disturbance plays in the onset and recurrence of mood and anxiety disorders, in addition to informing mental health interventions and treatments.

Evidence from epidemiological and twin studies has shown that some pairs of disorders, such as between brain disorders, often exhibited shared symptoms and comorbidity. However, there is a paucity of observational data on the correlation of other traits, especially for rheumatic diseases and musculoskeletal conditions. Additionally, it remains unknown whether the nature of co-occurrence of these diseases can contribute to potential etiological overlap or due to ascertainment bias and diagnostic misclassification. Recent advances in genetic methods, including the Mendelian randomization analyses, cross-trait meta-analysis, and transcriptome-wide association study, have enabled us to evaluate the degree of genetic overlap and to find the pleiotropic loci. Accordingly, by using data from the Avon longitudinal study of parents and children, we seek to systematically assess the correlation of different diseases, and how connected they on the genomic and environmental level.

From the start ALSPAC has included data collections on diet. The first collection was in the mothers during their pregnancy, and it's been repeated three other times with them. We've also got a wealth of information on the diets of the children from birth into teenage years. This has been an incredibly rich source of data for us on changing patterns on diet during childhood and is still on constant use today, mainly to study the effects of diet in pregnancy and in childhood on markers of health in later years. This type of long-term data on diet is very unusual in the UK so we are fortunate to have this in ALSPAC.

It's been some time since we've able to collect new information on diet in ALSPAC in the children, but we have an opportunity to do this in some upcoming questionnaires. This will add to our existing long-term data and add greatly to the potential for future scientific work linking diet and health.

As previously we are using a method called a 'food frequency questionnaire' (FFQ) in which participants are asked how often they usually eat particular foods. The FFQ is very similar to that used before in ALSPAC, but we have updated it for changes in the types of food people eat nowadays. In order to sure that the FFQ is correctly reflecting what participants actually eat, we need to do an additional 'validation' study in which we ask some of the participants to record their diet in another way.

For this validation study, we'll be asking some of the participants who fill in the FFQ to access an electronic platform on their smartphones or other device to record one day's food and drink intake in detail (food diary). We'll then ask them to repeat this twice at monthly intervals (so on three separate days in all). We can then compare the two ways and see how well the FFQ is performing against the electronic food diary and whether we get similar data from the two methods. If they are similar, we have can confidence in the data collected from the FFQ and can use it state this in our scientific publications so that others will know we have accurate data.

It is increasingly realised that urban environments constitute complex ecosystems, from microscopic organisms to social networks. As the principal human habitat, the design of our urban environments has the capacity to determine the health of the populace, across the lifespan. Over the past 150 years, health in the urban environment has largely been determined by pathogen control and automation; consequently, health and safety in the city has come to reflect sanitation and efficiency. Through design we have sought to reduce our exposures to potential stressors, from the cleanliness of our homes to highly prescriptive civic spaces. Although proving vital to the mitigation of many communicable diseases and physical dangers, an inadvertent side-effect of such urban environmental control is an exponential rise in non-communicable diseases (NCDs), which now account for 80% of years lived with disability globally. Although people are living longer, they are not necessarily living better. This suggests that while our cities prioritise safety, they do so at the expense of other health outcomes and human wellbeing. Specific to this project, we will consider the link between environmental exposures (biodiversity, green space), inflammation, and persistent symptoms.

This project will investigate the relationship between inflammatory biomarkers, geospatial characteristics, specifically biodiversity and longitudinal health outcomes (symptoms of non-communicable diseases including pain and fatigue). It will first consider the relationship between the levels of inflammatory biomarkers and geospatial characteristics of one's environment (biodiversity index). Second, it will consider the relationship between inflammatory biomarkers and the prevalence of pain and fatigue symptom reporting. Third, it will investigate the potential influence of geospatial characteristics (biodiversity index) on the relationship between inflammatory biomarkers and health symptom reports (pain, fatigue, breathlessness).

Pre-diabetes is a condition where blood glucose levels are elevated above normal, but below the threshold to be defined as type 2 diabetes. It is estimated that 70% of those meeting the criteria for pre-diabetes will eventually progress to type 2 diabetes, which is a chronic, incurable condition associated with various other comorbidities. It is therefore important to understand why some individuals progress from pre-diabetes to type 2 diabetes, so that we can develop interventions to stop this happening. We therefore aim to identify the genetic basis for why some individuals progress from pre-diabetes to type 2 diabetes.