Multimorbidity (MM) happens when two or more different diseases are present at the same time in an individual. This is
common between physical and psychiatric diseases with almost half of people with a psychiatric disease also having a
physical disease. As well as about a third of people with a physical disease also having a psychiatric disease. These
patients have worse quality of life than those with a single disease, they often struggle to get the best care and are at risk of
living less long. A common and serious type of MM is between internalizing diseases (depression and anxiety) and
cardiovascular disease (ICV-MM). Still, very little is understood as to how ICV-MM develops and why it happens. We do
know however that both internalizing disease and cardiovascular risk (e.g., obesity, cholesterol) tend to begin before
adulthood.
To really understand how ICV-MM risk develops, we need large studies of people of all ages whose health has been followed
over time. Studies of children are crucial because they can tell us about early risks for development of ICV-MM later in life.
This is important for developing better plans to prevent at-risk children developing ICV-MM.
We know that genes influence risk of both internalizing and cardiovascular disease and that some people are at high
genetic risk. We also know that certain conditions that start early in life (neurodevelopmental conditions) such as
intellectual disability, autism and ADHD increase risk of developing ICV MM later. Children's environments can also
increase this risk, for example, stressful experiences such as poverty and physical or sexual abuse. But how exactly genes,
neurodevelopmental conditions and early environmental risks influence the development of ICV-MM over the lifespan is still
not understood.
Certain groups are known to be at increased risk of ICV-MM, such as people of South Asian heritage and women, but we
don't know why this is. Better understanding of how ICV-MM develops in different groups in society will help doctors give
patients care that is matched to their specific needs. It will also help doctors, governments and schools prevent ICV-MM in
at-risk children in ways that work best for them.
To really understand the complexities of ICV-MM development, a team of researchers with a wide range of expertise is
needed who together understand physical and psychiatric diseases as well as how genetics, neurodevelopmental
conditions and the environments people live in influence them throughout their lives.
Our LIfespaN multimorbidity research Collaborative (LINC) combines wide-ranging medical and research expertise in
physical and psychiatric diseases. We have brought together five very large studies in which the health of many people has
been followed over time. Rich medical data is available, including from medical records. Genetic information is also
available for these people. Other important information has also been collected such as on people's living environments,
life events and lifestyles.
These studies follow the health over time of children, adolescents and adults. We can therefore study how internalizing and
cardiovascular disease happen together in adulthood. Importantly we can then also study early risk factors in the children
before they develop these conditions. Because our child and adult samples differ in ethnicity and economic situation, we
can also study how the development of ICV-MM differs for different groups in society. Finally, because we have genetic
data, we can study how genes influence ICV-MM development in people at risk.
Our study will help us understand how ICV-MM develops and which circumstances influence this. What we learn will be
important for the prevention of ICV-MM in children who are at risk because of genetics, their sex, or ethnic or economic reasons. We will work with patients, doctors and charities to develop specific health advice in order to reduce ICV-MM in at
risk groups in the future.

The human gut microbiome, home to a range of bacteria and various other microorganisms, is a diverse and complex feature of human homeostasis. Its specific composition varies between individuals due to pre-determined characteristics, i.e. our genetics, and modifiable factors including diet, lifestyle and probiotic consumption. The differences between individuals have highlighted its role in mediating a range of pathologies including obesity, metabolic syndrome, inflammatory disorders, and alterations in stress responses and behaviour. More recently, a relationship to cancer has been highlighted, where variations in the metabolites produced from these microorganisms is likely to have differential risk to cancer aetiology between individuals. The bacteria within the microbiome therefore has the potential for pharmaceutical intervention (through pro/prebiotics), if specific metabolites produced from these microbes are robustly associated to cancer outcomes.
Observational epidemiological studies have tried to quantify this relationship; however, they will often lack in overall certainty of causal inference and further be prone to biases, confounding and reverse causation. Mendelian randomisation (MR) has therefore been used as a tool within the field to improve the weakness pertinent to observational studies. The aim of the methodology is to utilise genetic polymorphisms, with well-characterised biological functions, as a proxy measurement for environmental exposures to provide evidence for causation. These germ line variants are independently and randomly assorted, allow for objective measurements to the degree of exposure and show a lack of association to behavioural, social or physiological factors, therefore allowing MR to be comparable to that of a randomised controlled trial (RCT) within the hierarchy of evidence – if done correctly.

Whilst MR may improve causality within this field, it is however prone to its own limitations. Specifically in the context of the microbiome, whereby, identifying variants to proxy for our trait of interest becomes increasingly more difficult. The project will therefore aim to test the relationship between the microbiome and cancer outcomes, through triangulating finding from both observational and genetic evidence. It will focus specifically on cancer outcomes that have not previously been robustly studied within this context, including (but not limited to) lung cancer.

It is now well-established that an early timing of puberty is associated with a greater risk of depression in girls during adolescence, and there is evidence that this relationship is causal. Far fewer studies have examined whether pubertal timing is related to depression in boys and findings are inconsistent. Some studies have found that boys with an early puberty have a greater risk of depression in adolescence, whilst others have found that a later puberty confers a greater risk. Such inconsistency is often attributed to measurement difficulties in capturing pubertal development in boys. It is also unclear whether any effects of pubertal timing on depression in boys persist beyond adolescence.

DNA methylation (DNAm) in neurological tissue is often difficult or impossible to use for observational studies, as sample collection must usually occur post-mortem. Studies interested in DNAm changes in brain related to disease outcomes or exposures commonly rely on DNAm measured in less invasive surrogate tissue, like blood, which typically have poorly characterised relationships with the target tissue DNAm levels of interest.

Early analysis has shown that some correlation exists between blood DNAm levels and DNAm at four different brain regions,1 but so far such work has been limited to comparisons at individual CpG sites. More recently, analyses developing multi-CpG prediction models have been able to serve as proxies for other types of molecular phenotypes, such as circulating protein levels in a variety of contexts. Thus, robustly trained, multi-CpG site blood DNAm models may be able to improve the variance explained of brain DNAm levels, especially in comparison to single CpGs. However, availability of appropriate paired blood-brain DNAm datasets required for model training has been limited to date.

We propose to develop models of brain DNAm using blood DNAm using an existing non-ALSPAC dataset and then apply the best performing models in ALSPAC DNAm to determine if they are associated with phenotypes and exposures relavant to the brain.

Some people experience symptoms caused by COVID that last longer than the original infection and these can be severe or disabling (COVID Symptom Study, 2020). This study aims to better understand why some people develop ‘long COVID’ – symptoms lasting longer than four weeks (National Institute for Health and Care Excellence, 2020) – and others do not. We will be comparing long COVID symptoms between those who have had COVID confirmed by a test, and those who believe they have had COVID but have not had a positive test. We will then explore whether this relationship is different between men and women, and between those who reported anxiety and those who didn’t. We hope that this research will help us to understand better whether psychological mechanisms contribute to the development of long COVID.

This project aims to describe the ALSPAC data on religious and spiritual beliefs, as well as identify any potential sources of bias. One of these associations that is of particular interest is whether RSBB has an affect on participation in the study. This is because studies like ALSPAC rely entirely on continued participation for the study to work, meaning if there are unknown factors behind participant's likelihood of continuing with the study this may result in bias when using these variables in analyses.

Stress-related psychopathology (e.g. depression and anxiety) affects one in eight children in the UK. It is therefore crucial to identify modifiable protective factors that can promote mental health in young people. Physical activity is a promising target for the prevention of depression and anxiety. However, the extent to which it can reduce the burden of mental disorders in young people is not known. This is due to the breadth of environmental, social, and genetic factors that could explain the relationship between physical activity and psychopathology. Furthermore, it is unclear whether physical activity can promote resilience to psychopathology in children who are at higher risk by virtue of genetic liability or adversity. This project will apply cutting-edge causal inference methods, including G-methods, fixed-effects regression, mendelian randomisation, and twin designs, to test whether physical activity can promote resilience against the development of stress-related psychopathology, using data from large population-based cohorts of children from the UK, Netherlands, Norway, and Finland. By comparing results across different studies and analytical approaches, the project will strengthen causal inferences from observational data and minimise potential biases associated with each method. In turn, the results will allow us to draw more confident conclusions regarding whether interventions targeting physical activity could help to reduce the burden of mental health problems in young people.

Exposure to maternal anxiety and depression in the antenatal and/or postnatal periods has been linked to an increased risk of adverse child health and developmental outcomes. Attainment of continence is a key developmental milestone in early childhood, and there is evidence that exposure to maternal anxiety and depression increases the risk that offspring will fail to attain continence by primary school age. It is unclear, however, if (i) anxiety and depression have independent effects on offspring incontinence, and (ii) whether the relationship with offspring incontinence is due to exposure to maternal anxiety/depression during the antenatal or postnatal period.

Attention problems occur in many mental health disorders, but they are the key symptom in ADHD. Many mental health disorders find their origin in adolescence. Internalising problems such as depression and anxiety have been related to pubertal development. This project is aimed at investigating trajectories of attention problems in relation to pubertal development to examine whether they show a parallel trajectory. and whether this parallel trajectory is sex specific.