The detriment of maternal smoking on offspring is well known while the biological mechanism regulating the relationship are not fully understood. Epigenetic profile has emerged as a potential link between the two. Sustained maternal smoking during pregnancy, here defined as smoking past the first trimester, has been associated with deferentially methylated CpG sites in the offspring (1-6) and a dose-response effect might also be plausible (2, 4, 7).

1. Joubert BR, Felix JF, Yousefi P, Bakulski KM, Just AC, Breton C, et al. DNA Methylation in Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis. Am J Hum Genet. 2016;98(4):680-96.
2. Ladd-Acosta C, Shu C, Lee BK, Gidaya N, Singer A, Schieve LA, et al. Presence of an epigenetic signature of prenatal cigarette smoke exposure in childhood. Environmental research. 2016;144(Pt A):139-48.
3. Lee KW, Richmond R, Hu P, French L, Shin J, Bourdon C, et al. Prenatal exposure to maternal cigarette smoking and DNA methylation: epigenome-wide association in a discovery sample of adolescents and replication in an independent cohort at birth through 17 years of age. Environ Health Perspect. 2015;123(2):193-9.
4. Markunas CA, Xu Z, Harlid S, Wade PA, Lie RT, Taylor JA, et al. Identification of DNA methylation changes in newborns related to maternal smoking during pregnancy. Environ Health Perspect. 2014;122(10):1147-53.
5. Rzehak P, Saffery R, Reischl E, Covic M, Wahl S, Grote V, et al. Maternal Smoking during Pregnancy and DNA-Methylation in Children at Age 5.5 Years: Epigenome-Wide-Analysis in the European Childhood Obesity Project (CHOP)-Study. PLoS One. 2016;11(5):e0155554.
6. Witt SH, Frank J, Gilles M, Lang M, Treutlein J, Streit F, et al. Impact on birth weight of maternal smoking throughout pregnancy mediated by DNA methylation. BMC Genomics. 2018;19(1):290.
7. Richmond RC, Simpkin AJ, Woodward G, Gaunt TR, Lyttleton O, McArdle WL, et al. Prenatal exposure to maternal smoking and offspring DNA methylation across the lifecourse: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC). Hum Mol Genet. 2015;24(8):2201-17.

Cannabis is the most commonly used illicit drug worldwide, with use particularly prevalent in adolescents. The number of under-18’s in treatment for cannabis as a primary problem in the UK in 2019-2020 was 11,136, 78% of all treatment entrants in this age group. Whilst this demonstrates a current clear demand for treatment of cannabis problems, the majority of people with cannabis problems do not seek out professional treatment. Further, current psychosocial treatment options lack data on their long-term efficacy, and there are no approved pharmacological treatments. One approach to tackle the global burden of cannabis use disorder (CUD) is to develop early targeted interventions, directed towards reducing the incidence of CUD. Identifying key variables that are associated with development of cannabis problems could help to ascertain which groups are most at risk. Previous research in adolescent and adult populations indicates that cannabis use profile, mental health problems and other drug use are all associated with increased risk of sustained problems related to cannabis use, compared to those with stable-low risk of cannabis problems. However, these studies either did not investigate childhood risk factors, or only assessed these retrospectively, and did not collect data specifically prior to cannabis initiation. This project aims to identify distinct trajectories of cannabis problems, and assess whether mental health and cognition in childhood (8-10 years old), prior to onset of cannabis use, represent potential modifiable risk factors for likelihood of experiencing problems with cannabis use, in order to inform early interventions to potentially reduce the incidence of cannabis problems.

Disordered eating behaviours (such as fasting, purging, binge-eating and excessive exercise) are common in young adulthood, and have the potential to cause serious long-term harm. Identifying risk factors that precede the onset of disordered eating in young adulthood is important for our understanding of how disordered eating develops. Furthermore, these risk factors may be useful for identifying individuals at high risk of developing disordered eating and for designing effective treatments.
Although diagnosis for an eating disorder often depends on Body Mass Index (BMI) and this can be a barrier for treatment, there is less evidence on whether changes in BMI across childhood and adolescence precede later disordered eating. Previous research using the ALSPAC sample (Perry et al. 2021) has found 5 different BMI trajectories from 1-24 years: stable average, gradually decreasing, puberty-onset minor increase, puberty-onset major increase and persistently high BMI. Compared to those with a stable average BMI, those with a puberty-onset major increase trajectory had higher risk of a depressive episode and depressive symptoms. However it is unclear whether these BMI trajectories are differentially associated with subsequent disordered eating.
This study investigates the associations between BMI trajectories across childhood up to age 24 with disordered eating behaviours at age 24. This study will improve our understanding of how BMI can lead to the development of disordered eating behaviours.

Inflammation is known to be associated with adverse non-communicable diseases (NCDs). However, the most commonly used biomarkers in inflammation research (namely C-Reactive Protein and Interleukin-6) are potentially not valid measures of chronic and cumulative inflammation. This is because they respond to short-term, acute inflammatory changes in the body. This therefore limits our knowledge of the true association between chronic inflammation and NCDs, but also limits our understanding of the role certain exposures (such as adverse childhood experiences; ACEs) have on levels of chronic inflammation.
A novel biomarker GlycA may be a more reflective of chronic inflammation because it is not affected by short-term inflammatory changes, given that it is a composite biomarker. Therefore GlycA may be a more valid measure compared to previously used biomarkers. This project aims to use GlycA to investigate the causes and consequences of chronic inflammation more accurately, with a focus on mental health (such as depression). The project will collaborate with the work being done by Debbie Lawlor’s group investigating the association between GlycA and cardiovascular disease.

Autism and asthma are two common but seemingly unrelated conditions. Autism is a chronic neurodevelopmental condition, characterised by difficulties in social communication as well as repetitive behaviours/restricted interests. On the contrary, asthma is a chronic respiratory condition characterised by periods of wheezing, shortness of breath and chess tightness. Despite the distinct features, there is some evidence suggesting an increased prevalence of asthma in individuals with autism, while maternal history of asthma has been associated with autism in the offspring. The reasons underlying these observational associations are currently unknown. One possible explanation could be that there is a shared genetic aetiology between the two conditions. Testing this hypothesis will be an important first step towards understanding the reasons of their co-occurrence.

Maculopathy is a term describing a group of diseases of the retina which together are the leading cause of blindness in developed countries. Treatment is at best only able to stabilize progression in some individuals and for many there is no effective therapy and irreversible sight loss cannot be avoided.

The most widespread form of macular disease is associated with ageing and is known as age-related maculopathy (ARM).The incidence of this rises with age (1). In the Beaver Dam study in USA (2), severe blinding macular changes were seen in 1%-2% of the overall population aged 50-80yr, with mild signs in 8-10% of people aged 43-54, rising to 14% in people aged 55-64y and 30% in people aged 75 or more. Subsequent population-based studies report similar findings.

A number of factors that we know are associated with ARM such as diet and smoking, are also associated with other diseases of ageing including cardiovascular disease and inflammatory conditions. These conditions are themselves more frequent in people with maculopathy and so the specific causal pathways that lead to ARM are still unclear and we are unsure how best to prevent the condition. By contrast myopic maculopathy (MM) is related mainly just to age and degree of myopia, although raised blood pressure is a risk factor. As myopia is increasing in prevalence across the world, so is the prevalence of MM and it is becoming a leading cause of blindness (3).

Treatment trials involving lifestyle changes such as dietary supplements have yet to show strong results in reducing ARM and there are no known lifestyles thought to protect against MM. It is likely that we have not yet identified either the correct pathways that lead to these diseases or the groups of people who are genetically more or less likely to be helped by lifestyle modifications.

We propose to make use of a unique opportunity - to “piggyback” onto a soon-to-start data collection sweep within the most detailed cohort study in the world- the Avon Longitudinal Study of Parents and Children, (ALSPAC, http://www.bristol.ac.uk/alspac). This sweep will involve 7000 very well-documented adults aged approximately 50-70 years4 who are the parents (the “G0 generation”) of a cohort of children (“G1 generation”) recruited in utero during the early 1990s. Detailed lifestyle and health data relating to these G0 parents are available stretching back 30 years, as well as detailed genetic data. We will collect high quality images of the retina and measurements of the eyes for these participants, to identify those with ARM or MM and we will use all the existing data to investigate the ways in which genetic, lifestyle and medical risk factors may have led to these diseases, over the last 30 years. A session for vision testing is already funded by a grant held by Prof Golding and Dr Northstone and we propose to take the retinal images in this session.

The costs of contacting the participants, bringing them to clinic and examining them, plus the collection of all the previous lifestyle and genetic data are already met and we have requested the costs of the retinal imaging, grading and analysis. There may be the chance to use old equipment to take some basic images showing existing ARM and MM assuming the clinic sweep starts before the grant we have submitted is decided upon. Thus, we will obtain results that will improve our understanding of the antecedents of ARM and MM and therefore potentially how to prevent them, by enhancing the vision data collection that is already planned.

References:
(1) Owen CG, et al; BJO 2012;96:752-756; (2)Emily Chew; Ophthalmology 2020. 127 S120-121 (3) .Baird PN al. Myopia. Nature Reviews Disease Primers. 2020; 6:99 (4) A Fraser et al; Int J Epidemiol 2012: 42 pp97-110:

This project will study how the child SEP at birth drives the personal exposome during infancy (0-2 years), accounting for geographical variability among cities and countries. The SEP will be measured using the EHII (Equivalized Household Income Indicator) developed within task 3.1.1 and maternal education. The exposures considered for this analysis include the urban environment exposures created within task 3.1.3, the diet exposures created within task 3.1.4, breastfeeding, passive smoking and exposure to pets.
We will study the SEP-exposome relationship using two main different approaches: i) we will fit standard regression models to evaluate the effect of SEP on each exposure accounting for multiple comparisons (Exposome Wide Association Study - ExWAS approach, but with the exposures as the dependent variables); ii) we will perform city-specific principal component analysis to reduce the exposome dimension and derive summary exposure indicators (the first principal components) and then fit standard regression models to evaluate the association between SEP and these summary indicators. We will conduct cohort/cities-specific analysis to take into account the fact that the role of SEP likely varies among cities and countries and considering maternal age, parity and ethnicity as potential confounders.

This study aims evaluate the impact of school closure during the COVID-19 pandemic in South Korea. Using another cohort consisting of South Korean adolescents in the 7th to 12th grade, we found that physical activity was significantly reduced due to school closures. This provides a chance to evaluate the effect of physical activity reduction in adolescents on other health-related outcomes. On the other hand, Mendelian randomisation is an alternative study design that can measure the effect of physical activity on other health-related outcomes. Our goal is to compare the two study designs on the same subject so that we can critically evaluate the validity of these study designs.

Substance use represents a primary global burden of disease for young people (1) as it has been associated with a wide range of adverse outcomes. These include physical health outcomes, such as infectious diseases and chronic bronchitis, social outcomes, including lower educational attainment and criminal activity, as well as increased substance dependence, risk of overdose, and mental health issues (1). Mental health symptoms and disorders have previously been associated with increased cannabis use in adolescence, including depression, suicidality, anxiety (2), and psychosis (3) . However, substance use and mental health are both complex, multifaceted issues that are likely to be affected by a number of risk factors (3).

One possible risk factor that may influence the relationship between substance use and mental health issues is socioeconomic status (SES), resulting in a greater burden of substance use on individuals of low SES. Research has identified that cannabis use is greater amongst individuals from low SES groups and may potentially be increasing over time (4). Whilst increased use amongst low SES individuals may result in worse mental health outcomes, it is also possible that, either alternatively or additionally, the social environment associated with reduced SES may exacerbate the harms associated with substance use, thus resulting in worse mental health outcomes. Increased harm related to other substances, such as tobacco, amongst low SES individuals has been observed previously (5), and therefore it may be plausible that a similar pattern is true for cannabis. This indicates that SES may be an important moderator of the relationship between adolescent cannabis use and mental health issues, including depression, anxiety, and psychotic experiences.

However, much of the current literature focuses on either substances other than cannabis or the impact of adult substance use and therefore further investigation is needed to understand the impacts of adolescent cannabis use . In addition, many studies have limited ability to draw causal inferences as a result of the high plausibility of reverse causation owing to the utilisation of cross-sectional data. This project aims to investigate the moderating role of SES in the relationship between adolescent cannabis use and mental health using longitudinal data from the ALSPAC cohort.