B4752 - Genetic and environmental factors in child adjustment and mental health - 02/12/2024

B number: 
B4752
Principal applicant name: 
Gabriela Ksinanova | Masaryk University, Faculty of Science, RECETOX (Czechia)
Co-applicants: 
Rebecca Lacey, Ph.D., Albert Ksinan, Ph.D.
Title of project: 
Genetic and environmental factors in child adjustment and mental health
Proposal summary: 

Understanding the factors associated with adolescent psychosocial adjustment and mental health is crucially important as mental health challenges that arise during these years often have enduring consequences throughout adulthood. Research indicates that mental health disorders in adolescence can hinder social, educational, and occupational outcomes, resulting in significant long-term impairments (Kessler et al., 2005). Mental health problems and health-compromising behaviors can often be traced back to adolescence, with 50% of mental health difficulties being established by the age of 15 (Kessler et al., 2005; Sawyer et al., 2012). The economic burden of mental health problems in young populations is profound, with estimates indicating both direct healthcare expenses and substantial indirect costs associated with increased social service needs, and the economic impact on families (Gustavsson et al., 2011; Knapp et al., 2011).

Factors leading to maladjustment and mental health problems in children and adolescents are often multifaceted, typically arising from a combination of individual vulnerabilities and environmental stressors. The individual factors include increased genetic risk for externalizing behaviors and depression, difficult temperament (e.g., high neuroticism), or developmental delays. One of the most salient environmental stressors is childhood adversity (i.e., adverse childhood experiences), typically operationalized as various forms of abuse, neglect, and household disfunction experienced before age 18 (Felitti et al., 1998; Hughes et al., 2017). Adverse childhood experiences are strongly associated with a socioeconomic disadvantage (Lacey, et al., 2022) and are structured by socioeconomic factors at both the family (Walsh et al., 2019) and macro level (Lewer et al., 2019). Thus, poverty and socioeconomic inequality can be considered as drivers of adverse childhood experiences (ACE; Institute of Health Equity, 2020; Walsh et al., 2019).

Environmental effects not only complement genetic influences but also interact with them, embodying the gene-environment (GxE) concept—the idea that environments modify genetic effects. For example, the effects of genetic risk on problem behaviors was amplified in environments characterized by poverty or maladaptive parenting (Chubar et al., 2020; Jensen et al., 2017). The existing studies on GxE usually follow the diathesis-stress model, which suggests that individuals with pre-existing vulnerability (such as genetic risk) are more susceptible to negative outcomes when exposed to adverse environments (Colodro-Conde et al., 2018; Zuckerman, 1999).

Lastly, large-scale societal conditions, including economic downturns, socioeconomic transformations, and geopolitical conflicts have a profound influence on well-being and mental health (Deindl, 2013). As countries considerably differ in their socioeconomic conditions, the scale in which they are affected by crises and by their response to them (Cascini et al., 2022), country characteristics are an important factor contributing to variation in young people’s mental health.

The aim of this project is twofold: a) to test the environmental risk (defined as childhood adversity and socioeconomic disadvantage) and genetic risks for maladjustment and mental health difficulties in ALSPAC cohort, and b) to examine the association between socioeconomic inequality, childhood adversity and adolescent mental health across two sister cohorts (ALSPAC and ELSPAC-CZ) that represent different socioeconomic environments. Data collection of both cohorts took place during the 1990s; however, while this was a time of relative stability in the United Kingdom, Czechoslovakia (later Czech Republic) was undergoing a turbulent post-communist transformation. This project will be the first to harmonize and directly compare data from both cohorts.

References:
Colodro-Conde, L., Couvy-Duchesne, B., Zhu, G., Coventry, W. L., Byrne, E. M., Gordon, S., ... & Martin, N. G. (2018). A direct test of the diathesis–stress model for depression. Molecular psychiatry, 23(7), 1590-1596.
Deindl, C. (2013). The influence of living conditions in early life on life satisfaction in old age. Advances in Life Course Research, 18, 107-114.
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., Koss, M. P., & Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The adverse childhood experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/S0749-3797(98)00017-8
Gustavsson, A., et al. (2011). Cost of disorders of the brain in Europe 2010. European Neuropsychopharmacology, 21(10), 718-779.
Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Butchart, A., Mikton, C., Jones, L., & Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. The Lancet Public Health, 2(8), e356–e366. https://doi.org/10.1016/S2468-2667(17)30118-4
Institute of Health Equity. (2020). Health equity in England: The Marmot review 10 years on. https://www.health.org.uk/publications/reports/the-marmot-review-10-year...
Jensen, S. K., Berens, A. E., & Nelson, C. A. (2017). Effects of poverty on interacting biological systems underlying child development. The Lancet Child & Adolescent Health, 1(3), 225-239.
Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., & Walters, E.E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication Archives of General Psychiatry, 62, 593-602.
Knapp, M., McDaid, D., & Parsonage, M. (Eds.). (2011). Mental health promotion and mental illness prevention: The economic case. London: Department of Health.
Lacey, R. E., Howe, L. D., Kelly-Irving, M., Bartley, M., & Kelly, Y. (2022). The Clustering of Adverse Childhood Experiences in the Avon Longitudinal Study of Parents and Children: Are Gender and Poverty Important? Journal of Interpersonal Violence, 37(5–6), 2218–2241. https://doi.org/10.1177/0886260520935096
Lewer D., King E., Bramley G., Fitzpatrick S., Treanor M. C., Maguire N., … Story A. (2019). The ACE Index: Mapping childhood adversity in England. Journal of Public Health. Advance online publication. 10.1093/pubmed/fdz158
Sawyer, S.M., Afifi, R.A., Bearinger, L.H., Blakemore, S.-J., Dick, B., Ezeh, A.C., et al. (2012). Adolescence: A foundation for future health. Lancet, 379, 1630-1640.
Walsh D., McCartney G., Smith M., Armour G. (2019). Relationship between childhood socioeconomic position and adverse childhood experiences (ACEs): A systematic review. Journal of Epidemiology & Community Health, 73(12), 1087–1093. [DOI] [PMC free article] [PubMed] [Google Scholar]
Zuckerman M. Diathesis-stress models. In: Vulnerability to Psychopathology: A Biosocial Model. American Psychological Association; 1999:3-23. doi:10.1037/10316-001

Impact of research: 
The results of the study can inform personality-focused interventions by identifying individuals particularly vulnerable to the effects of adverse environment. Additionally, the study will contribute to understanding the role of socioeconomic disadvantage in an increased risk for both childhood adversity and mental health problems by comparing two cohorts representing different socioeconomic environments.
Date proposal received: 
Tuesday, 26 November, 2024
Date proposal approved: 
Tuesday, 26 November, 2024
Keywords: 
Epidemiology, Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Mental health, Statistical methods, Childhood - childcare, childhood adversity, Genetic epidemiology, Statistical methods