Cardiovascular diseases (CVDs) are a significant public health concern and are a leading cause of mortality, representing 31% of all global deaths in 2017. These diseases often have their origins in childhood. Ample evidence suggests that exposure to childhood adversity, such as experiences of violence, parent imprisonment, household mental illness or substance use, has harmful effects on cardiovascular and other non-communicable diseases. Experiencing two or more adversities is associated with higher risk of cardiovascular disease in Europe and North America, respectively, corresponding to US$150 and US$164 billion in associated costs. Whilst there is evidence that adverse childhood experiences are associated with higher cardiovascular risk, whether socioeconomic inequalities in cardiovascular risk might be explained by childhood adversities. Understanding the extent to which adverse experiences in childhood could potentially explain socioeconomic inequities in CVD risk would help to inform the targeting of resources.

Further, the milieu of the family environment includes not just adverse experiences, however, but also positive experiences, which have been understudied. Positive experiences do not simply reflect the absence of risk factors, but instead are independent attributes or assets that enhance health and resilience over time. For example, the absence of abuse in the household does not necessary imply optimal parenting. The Health Outcomes from Positive Experiences (HOPE) is a complimentary framework to childhood adversity that organises positive childhood experiences into four broad categories: Being in nurturing, supportive relationships; Living, developing, playing, and learning in safe, stable, protective, and equitable environments; Having opportunities for constructive social engagement and to develop a sense of connectedness; and Learning social and emotional competencies.

Emerging evidence suggests that positive childhood experiences – variably defined – are associated with better adult cardiovascular health. These studies are suggestive that positive experiences in childhood also have relevance for cardiovascular health. To fully understand children’s experiences in the early years and how environments can be optimised to promote cardiovascular health in later life, however, we need to capture both adverse and positive experiences in childhood; otherwise, we just look at half the picture. For example, no previous studies have examined whether the effect of positive experiences was evident over and above that of adverse experiences in childhood. While adverse and positive experiences are not the inverse of one another, they are negatively correlated. Do positive experiences actually matter for cardiovascular health, or are they just a proxy indicator for the absence of adverse experiences? If they do matter, can they help to promote resilience in the presence of childhood adversity; that is, good health despite the presence of adversity?

We would like to find some additional data collection for the G1 cohort

These data would facilitate the continued longitudinal modelling of G1 substance use into adulthood
and be particularly useful in the event we are successful in the MRC grant we submitted in May 2020.

Pain which lasts for more than 3 months is termed chronic or persistent pain. It often occurs in the absence of obvious injury. It can be very difficult to treat. The UK is home to several large databases that contain information about subjects’ life history of pain and their genetic “make-up”. We plan to use the largest of these (UK Biobank) to help identify the genes that are related to the presence of a chronic pain condition (e.g. pain of duration >3 months) and the related symptoms experienced by sufferers e.g. low mood, poor sleep, lack of motivation, (pain) anxiety or pain depression. By gaining confidence that these genetic markers are related to the presence of a chronic pain condition, we will then use this information to recruit two small (each <200) groups of ALSPAC subjects who may or may not already have a pain condition. The beauty of this approach, is that by identifying the genes that make people susceptible to developing a pain condition, we will see how this interacts with health factors e.g. weight, blood pressure, and events that shape a person’s psychology e.g. adverse life events such as bereavement, to try to provide a means for people to modify their risk, or identify people for whom early intervention might be most beneficial following an injury – to hopefully avoid them going on to suffer life-long pain.

To achieve this goal, we would ask those subjects to undergo a series of pain tests (which of themselves cause only temporary discomfort) and undergo an MRI scan of their brain and spinal cord.

To better characterise pain present in the ALSPAC cohort, we propose to add pain-specific questionnaires (and tasks) to the upcoming age 30 clinics and questionnaires, which would target all participants. These questionnaires/tasks would explore the incidence of pain in the cohort, which will provide a more complete picture than is currently available. By adding information to this time point, we will gain insight to the cohort and to which genetic and biological factors can influence the development of a chronic pain condition. The availability of this window, where the majority of the cohort are still (hopefully) pain-free, will provide a baseline from which future studies will be able to reflect on the factors that ultimately led some participants to develop a chronic pain condition.

Genetic studies have found connections between a person's genes and their cholesterol. These studies have been conducted in adults. Cholesterol is much less variable during childhood. We aim to see if the associations seen in adults also extend to children.

Previous studies have reported that addictive behaviors decrease when infectious disease first occurs but increase as the disease continues. It shows that especially among health workers, the addiction problems can get even more serious compared to the period when the infectious disease did not occur. This study wants to examine predictive factors that are associated with addictive behaviors before and after Covid-19.

Depression is the leading cause of global disability with over 300 million people suffering world-wide. Estimates suggest that up to two thirds of patients do not recover following their first antidepressant treatment and up to one third do not recover after multiple treatments. Therefore, it is critically important to identify factors that predict recovery and reduce risk of relapse. Current methods in genetic epidemiology focus on predictors of mental illness onset. While this is crucial to prevent new diagnoses, it does little to help individuals already suffering. Therefore, the Recover project aims to extend current genetic epidemiology methods to better understand recovery from depression. The methods developed here will begin with a focus on depression but can also be extended to other mental illnesses. First, we will develop trajectories of depression using continuous longitudinal measures in two critical time points, 1) adolescence and early adulthood and 2) during and post pregnancy. Second, using these trajectories as outcomes we will explore many modifiable predictors of recovery. Third, we will use cutting-edge causal inference techniques to test whether or not these predictors are causal. And finally, we will develop novel technologies to capture fine-grained fluctuations in mood. Taken together, this work will lead to better interventions and inform adjuncts to treatment having real impact for the growing number of individuals suffering from depression.

Previous research has indicated that individuals with ADHD have an increased likelihood of developing mental health problems such as depression, anxiety and antisocial behavior. Despite mental health problems being increased in individuals with ADHD, not all children go on to develop poor mental health outcomes. Research has indicated that resilience is a dynamic process that arises from normal adaptive mechanisms and can be influenced by many factors. However, why some individuals with ADHD show higher levels of resilience and better outcomes compared to others is not yet well understood. One way of defining resilience is better-than-expected long-term mental health outcome than predicted by initial severity of childhood ADHD. Therefore, the current research project will focus on first identifying risk mechanisms which increase the likelihood of individuals with childhood ADHD developing adult mental health problems, and then will aim to identify potentially modifiable protective factors that could be the focus of prevention and intervention programs.

Epidemiological and clinical studies interested in circulating glucose as a risk factor or outcome typically measure levels in the blood at a single or widely spaced time points (e.g. every few years). While these are important health indicators, there has been an increasing appreciation that glucose levels and variability in free-living conditions during both the day and night, may also provide important health measures in clinical (e.g. diabetic or obese) and ‘healthy’ populations.

Continuous glucose monitoring (CGM) systems measure interstitial glucose levels ‘continuously’ by implanting a sensor subcutaneously. This produces a sequence of measurements for each participant (e.g. the average glucose level every 5 minutes over several days), that can be used to assess how a person’s glucose levels vary over both the day and night. We have recently published a novel software package called GLU, for deriving a consistent set of summary variables from CGM data. The derived summary variables can be used in analyses to assess how different characteristics of glucose levels and variability relate to health exposures and outcomes.