Cancer outcomes are improved when it is detected early. There is therefore a need for assays for identifying individuals with high cancer risk that can be applied to peripheral tissues such as blood or saliva. There is strong evidence that DNA methylation levels in these tisues encodes biomarkers for cancer risk factors such as cigarette smoke exposure, BMI, diabetes and biological aging. We plan to create DNA methyhlation models of cancer risk factors that can be combined to identify individuals with high cancer risk using peripheral blood samples.

DDepression affects up to 300 million people worldwide and is one of the greatest causes of disability in the world. While many aspects of depression trajectories from adolescence to adulthood are well understood, depression is still among the most unreliable diagnoses of all categorical mental disorders. Additionally, changes in symptom levels across adolescence and young adulthood are as yet poorly understood. This may result from nosological conceptualizations of mental disorders that do not vary for children as compared to adolescents or adults. Only the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders describes irritability rather than depressed mood as an additional core symptom for children and adolescents. In this vein, researchers and practitioners often apply sum score models that reflect these considerations. However, these models rely on strong assumptions and we therefore aim to use Avon Longitudinal Study of Parents and Children data to investigate depressive symptoms in more depth.

While previous research has consistently shown a relationship between adverse childhood experiences (ACEs) and developmental and behavioral outcomes later in life, understanding of mechanisms that explain the relationship is still insufficient. In particular, the role of genetics remains unknown. In this project, we propose to study how genetic factors and ACEs jointly and interactively affect individuals' developmental and behavioral outcomes, such as delinquent behavior and substance use. Specifically, we propose to examine whether and to what extent the influence of ACEs on the developmental and behavioral outcomes depends on children’s genetic susceptibility. Moreover, to what extent effects of parental genetic risk on child’s developmental and behavioral outcomes operate via ACEs.

Metabolic health is emerging as an important risk and prognostic factor for metabolic diseases, including cardiovascular disease (CVD), diabetes and cancer. (1-12) Metabolic health has been defined according to the presence or absence of a minimum number of cardiometabolic risk factors defined according to clinical cut-points (i.e. elevated waist circumference, triglycerides, blood pressure, and fasting glucose, low HDL-cholesterol, insulin resistance (HOMA-IR) and inflammatory biomarkers (hsCRP), or pharmacological treatment for these parameters). Obesity is associated with poor metabolic health, but metabolically unhealthy individuals may be at high risk of metabolic diseases, independent of BMI (metabolically unhealthy normal-weight phenotype, MUHNW) and obese individuals that are metabolically healthy may have similar disease risk to their lean counterparts (metabolically healthy obese phenotype, MHO). (1) Analysis of data from the US National Health and Nutrition Examination Survey showed that a substantial proportion of overweight or obese individuals are metabolically healthy and over 30% of normal weight individuals are cardiometabolically unhealthy. (13) The etiologies of the associations between these phenotypes and cardiometabolic disease risk are unclear. Recent studies have demonstrated the utility of using a metabolomics approach to explore the concepts of MUHNW and MHO in relation to cardiometabolic disease endpoints. For example, an 'obese metabolome' (metabolites related to insulin resistance, branched chain and aromatic amino acids, nucleotide metabolites, and several lipid classes) associated with a 2 to 5-fold increased risk of cardiovascular events, independent of BMI, in the TwinsUK cohort. (14) Matched for BMI, MUHNW individuals had higher visceral adiposity, higher blood pressure and were also more likely to become obese over time compared with their metabolically healthy lean counterparts. Such findings point towards the potential of metabolomics for disease risk stratification, where BMI alone can fail to identify a significant proportion of individuals that may be at risk for cardiometabolic disease. We propose to leverage the unique resources of COMETS to determine metabolites associated with metabolic health, how this profile associates with obesity-relevant diseases (i.e. obesity-related cancers and cardiovascular disease), and the extent to which metabolites mediate the association of body mass index with these outcomes.

Around one-third of young people in the UK have suffered intimate partner violence (emotional, physical, or sexual abuse from a romantic partner) by the time they turn 21. This is more likely for those who have had symptoms of anxiety or depression during their teenage years. A common form of support for anxiety or depression at this age is through the GP - who might offer either psychological therapy (like counselling sessions, or cognitive behavioural therapy), or drug treatment (such as anti-depressants), to try to reduce anxiety and depression symptoms. This might also reduce likelihood of intimate partner violence later on, but there so far this has not been studied.

Mental health problems run in families. This arises from a range of genetic and environmental factors.

Recently, we have seen the impact that the human microbiome has on physical health (e.g inflammatory bowel disease, asthma, obesity) and mental health (depression, anxiety, autism).

Like mental health, the microbiome also runs in families, likely because of environmental transfer of microbiota between family members and, in particular, the seeding of the neonatal microbiome during the birth process. We wondered whether the sharing of microbiomes within families may partially explain familial similarities in mental health.

It is not possible to conduct an experiment, interrupting the transfer of microbiota from mother to child, to see if this had an impact on transfer of intergenerational risk for mental health problems. However, nature (helped along by NHS maternity services) provides us with a natural experiment: Approximately 20-25% of births are via caesarean section, and there is mounting evidence that this results in substantially lower mother-child microbiome transfer than vaginal birth. This microbiome transfer process can be further interrupted by other factors, including prenatal/perinatal antibiotic use and breastfeeding practices.

This study will explore the impact of early-life microbiome transfer on the intergenerational transmission of mental health problems.

Early-life urban stressors have been identified as a risk to the onset of non-communicable diseases. An accumulating body of evidence is suggestive for health-promoting effects of exposure to green spaces. However, the association between green spaces and harmful or beneficial effects on children health is still poor for most outcomes, and the underlying mechanisms remain unclear. Outcome wide analysis have recently been proposed as a way to evaluate the effects of exposures over numerous important outcomes. Indeed, some exposures may be harmful for some outcomes and beneficial for others, including green spaces exposures. This approach also has the advantage to better control for confounding for the effects of the exposure on all outcomes simultaneously. It is different from the traditional one-outcome approach and more similar to GWAS (genome wide associations) or EWAS (epigenome wide associations) or ExWAS (exposome wide associations). For outcome-wide approaches, larger datasets are needed so LifeCycle is a good opportunity to apply this novel method. The idea is to add as many outcomes as possible, this is the great interest of the outcome wide approach.

Myopia, or short-sightedness, is one of the most common causes of sight impairment worldwide. By 2050, five billion people- half the world’s population- will be short-sighted, compared to ~1.4 billion people today.
People with myopia have relatively long eyes, so that light is focused in front of the retina instead of directly onto it. Since the eye continues to grow throughout childhood, someone who develops myopia as a child will continue to get worse as they grow older, with greater risk of sight-threatening complications.
Previously, we showed that for each additional year we spend in education, the more myopic we become, on average, as a population. Evidence from other studies suggests that this may be because we spend less time outside, reducing our exposure to natural daylight. Other risk factors for myopia include the time we spend on near work, urbanization, socioeconomic position, diet, pregnancy-related factors and genetics. Children with myopia tend to engage in less physical activity, but physical activity alone is not protective against myopia.
Myopia is more prevalent in countries adopting a Western diet and lifestyle, and many of the genes that increase the risk of myopia are involved in insulin/glucose signalling and obesity/fat metabolism. Insulin signalling also appears to influence the normal growth of the eye. As the Western diet is linked to greater intake of food with higher energy loads, one hypothesis is that compensatory increases in blood glucose and insulin levels send increased growth signals to the eyes.
This project aims to determine how genetic and environmental factors interact with insulin signalling to affect myopia. Changes in insulin signalling happen naturally in children around puberty, and so we would like to use information in the Avon Longitudinal Study of Parents and Children on eye growth, glasses prescriptions, blood levels of glucose and insulin before, during and after puberty on thousands of children followed prospectively from birth, to find out how they interact to affect eye growth. Additionally, there are normal variants in our genes that influence fasting levels of insulin and glucose and we will find out how these genetic variants are linked to myopia. These analyses should provide novel insights into the relationship between insulin signalling and myopia, and have the potential to identify novel targets for treatment.