B4446 - Predicting the risk of depression and anxiety in early life and adolescence - 02/11/2023

B number: 
Principal applicant name: 
Hannah Jones | University of Bristol (UK)
Sophie Fairweather, Professor Golam Khandaker
Title of project: 
Predicting the risk of depression and anxiety in early life and adolescence
Proposal summary: 

One in every eight people in the world have a mental health problem[1] and in 75% of these people their mental health problem develops before they are 18[2]. Depression and anxiety are the most common mental health problems and they often co-occur in the same individual. Early-life mental health problems, including depression and anxiety, can severely impact the lives of affected individuals including future health and wellbeing, education and jobs, and family and peer relationships. Therefore, research is needed to improve our understanding of why some people experience mental health problems while others don’t. While depression and anxiety symptoms are often time limited in some people, they are chronic in many, but currently there is no accurate/reliable way of predicting who might develop chronic/severe course of symptoms/illness. Identifying this subgroup would help in development of targeted prevention strategies.

Potential risk factors for mental illnesses include biological factors (e.g., genetics, epigenetics, low-grade inflammation), social factors (e.g., abuse, bullying, living in poverty) and psychological factors (e.g., internalising attributional style).
Evidence has shown that inflammation in the body is an important biological risk-factor[3, 4]. Inflammation can also be triggered or altered by other experiences (for example, eating certain foods, substance use or having an infection). Because of this, it is possible that modifying factors that cause inflammation (e.g., diet) may help to treat or prevent mental health problems.

An important group, who might have more inflammation, are people with food allergies, eczema and asthma. Allergy is very common; researchers predict that by 2025 half of all people living in Europe will have an allergy[5]. Psychosocial factors linked to allergy such as trauma associated with a severe allergic reaction, fear of experiencing a reaction, following a restricted diet, social exclusion, missing days from school, medication use and over-protective parenting styles might also influence a child’s mental health.

This project will use data collected from participants of the Avon Longitudinal Study of Parents and Children who answered questions about their mental health, and other life experiences, at different ages as they grew up. We will use these data to look at how bio-psycho-social risk factors in early life (e.g., gestation, childhood, adolescence) are linked to mental health in teenagers and young adults. Findings will enable us to identify and help children who are at high risk of developing a mental health problem before they have developed severe, adverse symptoms.

1. (WHO), W.H.O., Fact sheets: Mental Disorders. 2022.
2. England, M., Mental health statistics. 2020.
3. Milaneschi, Y., et al., Association of inflammation with depression and anxiety: evidence for symptom-specificity and potential causality from UK Biobank and NESDA cohorts. Mol Psychiatry, 2021. 26(12): p. 7393-7402.
4. Foley, É.M., et al., Peripheral blood cellular immunophenotype in depression: a systematic review and meta-analysis. Molecular Psychiatry, 2023. 28(3): p. 1004-1019.
5. UK, A., Statistics and Figures. Allergy Prevalence: Useful facts and figures.

Impact of research: 
Broadly, this work will contribute to understanding the role of early life experiences, and the role of the immune system, in psychiatric illness. Understanding trajectories of early life experiences and which bio-psycho-social factors contribute to later mental health outcomes is important for predicting risk among other factors that might also be useful. In turn, risk prediction is an opportunity for early, targeted, preventative intervention which may also involve strategies to reduce inflammation (pharmacological and/or otherwise). A specific aim of this project is to develop a prediction tool for use in community settings (e.g., schools) to identify children in need of mental health and social support. While other models have been published (in other, smaller cohorts), few are translated into clinical/community tools and models rarely predict anxiety (more commonly depression). In the future, the real-world utility of the risk prediction tool could be tested and a future work program focusing on consequences of depression and anxiety trajectories, including functional outcomes, could be explored.
Date proposal received: 
Thursday, 26 October, 2023
Date proposal approved: 
Thursday, 2 November, 2023
Epidemiology, Allergy, Eczema, Infection, Mental health, Respiratory - asthma, Computer simulations/modelling/algorithms, Statistical methods, Prediction