Cytosine modifications to DNA (such as DNA methylation) have been found to display temporal rhythms. This temporal dimension of epigenetics, coined “chrono-epigenetics”, may have been previously overlooked. In particular, the timing of sample collection may introduce randomness into epigenetic data and may serve as a potentially important correction factor in epigenetic studies. Furthermore, the oscillating nature of cytosines has been suggested to underlie biological rhythmicity, ageing processes and the development of complex diseases such as cancer.

Exposure to childhood adversity is one of the strongest risk factors for depression across the life course, increasing risk for both child- and adult-onsets of the disorder by at least twofold and possibly explaining one-third of all mental disorders. Accumulating research suggests epigenetic processes may be a key biological pathway through which adversity creates this long-term mental health vulnerability. Dozens of human and animal studies have shown that adversity can program the epigenome through DNA methylation (DNAm) marks, which do not alter the sequence of the genome, but can influence how genes are expressed. Our interdisciplinary team has been studying the relationship between adversity, DNAm, and depression risk in the ALSPAC. Our work to date has revealed three main novel findings. First, not only does adversity shape these DNAm marks in both childhood (at age 7) and adolescence (at age 15), but there is a replicated sensitive period between 3-5 years when children’s epigenomes are especially vulnerable to the effects of adversity. Second, these adversity-induced DNAm differences are temporally dynamic, having discernable patterns of stability and change across childhood and adolescence that reflect latent, and transitory effects of adversity on the epigenome. Third, these DNAm marks are not only a molecular record of adversity exposure, but also appear to mediate, meaning explain in part, how adversity influences both risk for – and protection against – subsequent depressive symptoms.

We seek to build from these insights to conduct secondary analyses of newly-released ALSPAC data to identify epigenetically-linked sensitive periods shaping risk and resilience to depression. We and others have shown there is substantial variation in how people respond to adversity; not all children who experience early-life adversity go on to have mental health problems. Yet, little is currently understood about the modifiable protective factors and mechanisms that drive resilient processes. Here we propose to test our central hypothesis that both liability and protection from depression across the lifecourse begins some time during the first five years of life and arises, in part, via the effects of experience-dependent plasticity shifts in DNAm that occur during an early postnatal sensitive period.

In this project we will create "polygenic indexes" for the ALSPAC participants. Polygenic indexes are summaries of a persons known genetic predisposition to a particular trait, such as height. We will create these indexes for up to 47 different traits, which can then be use by other researchers.

Research has shown that there is a link a mother's and a child's mental health. There is a pattern that where mothers have poor mental health, their children are at risk of developing mental health difficulties also. Research with parents of children with mental health difficulties has shown how distressing this can be for parents. For example, parents of young people who self-harm report significant distress related to their child's difficulties. We seek to explore the link between child mental health and subsequent maternal mental health. We focus on the mother as this is where there is most available data within ALSPAC. This will help us understand whether mothers are at risk of developing significant distress after their child has reported clinical levels of mental health difficulties.

We will also look at variables that describe family structure and characteristics of the mother and child. For example, we want to understand if child mental health problems are more likely to be linked to maternal mental health problems if family have a lower income or if the mother does not live with a partner. We are interested in factors that increase stress or reduce available support for mothers. This will help us identify if there may be characteristics that make a mother more likely to have poor mental health in relation to their child's distress. If so, this will help us make recommendations for how services may need to be made available to best support families.

Prenatal mental and physical health are important factors associated with infant health and later child development. Previous research has identified a wide array of prenatal risk factors for poor infant outcomes, including sociodemographic factors (e.g., maternal education level, socioeconomic position), behavioural factors (e.g., substance use), biological factors (e.g., infections, gestational diabetes), psychosocial factors (e.g., exposure to interpersonal violence), and environmental factors (e.g., exposure to interpersonal violence, exposure to second-hand smoke), inter alia.1,2,3 Evidence also suggest that these risks factors and adverse outcomes are associated with maternal exposure to childhood maltreatment and abuse. 5,6 However, most empirical studies usually focus on exploring a specific pathway of intergenerational risk transmission rather than accounting for multiple dynamic factors and their interactive effects. To extend the methodological framework, this project aims to use graphical network analysis to: i) model dependencies between maternal childhood and prenatal risk factors and poor infant outcomes (in the form of infant prematurity and low birth weight); ii) and identify central risk factors that are likely to impact other types of risk factors and adverse health outcomes.
References:

1 De Bernabé, J.V., Soriano, T., Albaladejo, R., Juarranz, M., Calle, M.E., Martınez, D. and Domınguez-Rojas, V., 2004. Risk factors for low birth weight: a review. European Journal of Obstetrics & Gynecology and Reproductive Biology, 116(1), pp.3-15.

2 Murray, A.L., Kaiser, D., Valdebenito, S., Hughes, C., Baban, A., Fernando, A.D., Madrid, B., Ward, C.L., Osafo, J., Dunne, M. and Sikander, S., 2020. The intergenerational effects of intimate partner violence in pregnancy: mediating pathways and implications for prevention. Trauma, Violence, & Abuse, 21(5), pp.964-976.

3 Miranda, Marie Lynn, Pamela Maxson, and Sharon Edwards. "Environmental contributions to disparities in pregnancy outcomes." Epidemiologic reviews 31, no. 1 (2009): 67-83.

4 Nesari, M., Olson, J.K., Vandermeer, B., Slater, L. and Olson, D.M., 2018. Does a maternal history of abuse before pregnancy affect pregnancy outcomes? A systematic review with meta-analysis. BMC pregnancy and childbirth, 18(1), pp.1-11.

5 Racine, N., Plamondon, A., Madigan, S., McDonald, S. and Tough, S., 2018. Maternal adverse childhood experiences and infant development. Pediatrics, 141(4).

Accumulating online discussions suggest some women have experienced menstrual changes after receiving the COVID-19 vaccine. This is important and potentially concerning, as a large proportion of people menstruate and menstrual health is increasingly recognised as an important indicator and determinant of broader health and quality of life. The extent, nature, and mechanism of COVID-19 vaccine-related menstrual changes is currently unclear. The menstrual cycle is regulated by a complex interplay of hormones that can interact with the immune system to influence menstrual bleeding and premenstrual symptoms; vaccines cause huge immune disruptions and so could plausibly affect menstrual features. Questions about menstruation were added to the most recent questionnaire sent to ALSPAC participants. In this project, we will explore 1) the prevalence of different types of vaccine-associated menstrual disruptions, 2) demographic and life history factors associated with experiencing menstrual disruptions, 3) through future ALSPAC planned follow-ups, the duration of menstrual disruptions and future reproductive health outcomes.

Aim(s) and objective(s)
We would like to propose adding a set of questions around menstruation and pandemic-related menstrual changes to the ALSPAC questionnaires. The resulting data would enable us and others to:
1) estimate the prevalence and extent of menstrual changes during the pandemic and describe the demographic of people experiencing these changes;
2) study the potential bidirectional relationship between menstruation and COVID symptoms,
3) study the relationship between menstrual changes and stress and lifestyle changes;
4) study the longer term effects of pandemic-related menstrual changes on later health and reproductive outcomes (for example, fertility, pregnancy outcomes and timing of menopause).
Methods (including an overview of statistical methods)
The questions we are proposing to add were developed for a large online survey of menstrual changes during the pandemic. The questions were developed by Alexandra Alvergne's group at the University of Oxford with input from clinical gynaecologists and PPI input from long-covid sufferers and women with menstrual disorders. The survey is currently live.
Exposures, outcomes and confounders to be considered (justifying particular types of data as necessary)
If/when the data from our proposed questions are collected, we will put in another proposal for a project to address specific research questions.

That research will likely require access to ALSPAC data on stress, lifestyle changes and COVID symptoms from the COVID questionnaires and longitudinal data on menstruation from the G1 and G0 questionnaires. Follow-up ALSPAC questionnaires will allow us to see variations in fertility and timing of menopause according to responses to our questions. Covariates of interest will include socioeconomic position, chronic health conditions, age and BMI.
Reasons for using ALSPAC
ALSPAC has detailed prospectively collected longitudinal data on experiences before and during the COVID pandemic. It is also unique in terms of the availability of data on menstruation prior to the pandemic. Some cohorts have collected data on cycle length, but ALSPAC appears to be the only cohort to have asked about pre-menstrual symptoms like irritability and fatigue.
What do you think the likely impact of your research will be?
Judging by the interest in news stories and blog posts about the small number of survey studies we identified in our systematic review, we estimate that this research will be of wide public interest.
Stigma and a lack of knowledge about what is ‘normal’ means menstrual disorders are often under-reported and under-diagnosed, but they affect a large proportion of the population. For example, in the UK, 5% of women aged 30-49 years (>439,380 women) consult their GP each year due to excessive uterine bleeding. Our systematic review suggests that the number of women suffering from menstrual disorders has likely increased. Therefore, in addition to patients themselves, the research will be of interest to clinicians providing care to menstruating women. Recent years have seen an exponential interest in menstrual health and an appreciation of its role as an indicator and determinant of broader health and wellbeing. This is reflected by very recent policy changes to reduce tax on menstrual products. We anticipate that our research will contribute to further policy changes around improving population menstrual health and quality of life for menstruating women.

This project sets out to use existing samples (on N=4 participants) collected as part of the UKCiC initiative to examine the ability of SARS-CoV-2 vaccination to recover variable immunological response to wild infection. Data on continuously assessed antibody response to wild infection will be used to identify those with low response and then biological samples available over a schedule of first and second vaccinations will be used to examine the impact of these interventions.

Elevated blood pressure, or hypertension, has become a major public health concern globally. Evidence shows that blood pressure tracks into adulthood. However, most epidemiology research to date on hypertension has focused on risk factors from single aspects, but it is becoming increasingly evident that early-life factors may come from multiple sources, such as society, community, family and individual. For example, a positive association between rapid weight gain and elevated blood pressure in both children and adults has been widely observed. Other community-based evidence shows that lower early-life environment exposure to residential greenness has been found to be independently associated with elevated blood pressure. Until recently, the combined effects and interplay of individual and community-level factors on the developmental programming of blood pressure are still limited, and further research is needed.

The increased wear and tear on the body, is the consequence of multisystem regulations in response to repeated challenges from the environment (McEwen & Stellar, 1993). This multisystem dysregulation can be objectively quantified by calculating the allostatic load index, a cumulative score of biological biomarkers in the cardiovascular, immune, neuroendocrine, and metabolic systems (Berger et al., 2018; McEwen, 2004). Elevated allostatic load has been shown to predict the risk of major health outcomes, both systemically and in the brain. Evidence suggests that the elevation of individual biomarkers can be observed in early childhood (9 years old) in people who later develop a mental health disorder, however only a few biomarkers (IL-6 and CRP) has been investigated (Khandaker et al., 2014).
We and others have shown that severe mental disorder, such as schizophrenia, bipolar disorder and psychosis is associated with increased allostatic load (Berger et al., 2018; Berger et al., 2020; Juster et al., 2018; Piotrowski et al., 2019). Furthermore, our group has established that elevated allostatic load predicts depression symptoms and may underlie higher mental health burden and shortened life expectancy of a population affected by considerable stress and trauma, the Indigenous Australian people (Berger et al., 2019; Ketheesan et al., 2020)
This project will expand on these earlier findings and include biological markers from the four major physiological systems to calculate the allostatic load index and identify whether there is an association between a multisystem dysregulation in childhood and the development of severe mental health disorders. If such association is detectable, that will raise the possibility that the allostatic load index could be applied for targeting interventions in populations at risk and aiming to reduce the risk of developing a mental health disorder in adulthood.

References:
Berger, M., Juster, R. P., Westphal, S., Amminger, G. P., Bogerts, B., Schiltz, K., Bahn, S., Steiner, J., & Sarnyai, Z. (2018). Allostatic load is associated with psychotic symptoms and decreases with antipsychotic treatment in patients with schizophrenia and first-episode psychosis. Psychoneuroendocrinology, 90, 35-42. https://doi.org/https://dx.doi.org/10.1016/j.psyneuen.2018.02.001
Berger, M., Lavoie, S., McGorry, P. D., Nelson, B., Markulev, C., Yuen, H. P., Schaefer, M., Sarnyai, Z., & Amminger, G. P. (2020). Relationship between allostatic load and clinical outcomes in youth at ultra-high risk for psychosis in the NEURAPRO study. Schizophrenia Research, 226, 38-43. https://doi.org/https://doi.org/10.1016/j.schres.2018.10.002
Berger, M., Taylor, S., Harriss, L., Campbell, S., Thompson, F., Jones, S., Sushames, A., Amminger, G. P., Sarnyai, Z., & McDermott, R. (2019). Hair cortisol, allostatic load, and depressive symptoms in Australian Aboriginal and Torres Strait Islander people [Research Support, Non-U.S. Gov't]. Stress, 22(3), 312-320. https://doi.org/https://dx.doi.org/10.1080/10253890.2019.1572745
Juster, R.-P., Sasseville, M., Giguère, C.-É., Consortium, S., & Lupien, S. J. (2018). Elevated allostatic load in individuals presenting at psychiatric emergency services. Journal of Psychosomatic Research, 115, 101-109. https://doi.org/10.1016/j.jpsychores.2018.10.012
Ketheesan, S., Rinaudo, M., Berger, M., Wenitong, M., Juster, R. P., McEwen, B. S., & Sarnyai, Z. (2020). Stress, allostatic load and mental health in Indigenous Australians* [Review]. Stress, 23(5), 509-518. https://doi.org/http://dx.doi.org/10.1080/10253890.2020.1732346
Khandaker, G. M., Pearson, R. M., Zammit, S., Lewis, G., & Jones, P. B. (2014). Association of serum interleukin 6 and C-reactive protein in childhood with depression and psychosis in young adult life: a population-based longitudinal study. JAMA Psychiatry, 71(10), 1121-1128. https://doi.org/https://dx.doi.org/10.1001/jamapsychiatry.2014.1332
McEwen, B. S. (2004). Protection and damage from acute and chronic stress: Allostasis and allostatic overload and relevance to the pathophysiology of psychiatric disorders. Annals of the New York Academy of Sciences, 1032, 1-7. https://doi.org/10.1196/annals.1314.001
McEwen, B. S., & Stellar, E. (1993). Stress and the individual. Mechanisms leading to disease. JAMA Internal Medicine, 1(18), 2093-2101.
Piotrowski, P., Kotowicz, K., Rymaszewska, J., Beszlej, J. A., Plichta, P., Samochowiec, J., Kalinowska, S., Trzesniowska-Drukala, B., & Misiak, B. (2019). Allostatic load index and its clinical correlates at various stages of psychosis. Schizophrenia Research, 210, 73-80. https://doi.org/https://dx.doi.org/10.1016/j.schres.2019.06.009