Investigating CAusal Relations IN Gene-environment interactions in children exposed to war-related Traumatic events.

Projektinformationen

CARINGTrauma

ID Finanzhilfevereinbarung: 896021

DOI

10.3030/896021

Projekt abgeschlossen

EK-Unterschriftsdatum 20 April 2020

Startdatum 14 September 2020

Enddatum 13 September 2022

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 224 933,76

EU-Beitrag

€ 224 933,76

Koordiniert durch

QUEEN MARY UNIVERSITY OF LONDON
United Kingdom

Periodic Reporting for period 1 - CARINGTrauma (Investigating CAusal Relations IN Gene-environment interactions in children exposed to war-related Traumatic events.)

Berichtszeitraum: 2020-09-14 bis 2022-09-13

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

Refugee children that have experienced traumatic situations are at increased risk of developing psychological disturbances. While some refugee children develop emotional and behavioural disorders (post-traumatic stress disorder, anxiety, or depression, for example), others exhibit remarkable resilience. This variability is linked to the complex interplay between individual traits, such as genetic factors, and characteristics of the environment. The EU-funded CARINGTrauma project developed an innovative statistical approach to explore the complex and interactive causal relations between the various determinants of mental health across multiple domains. It used a unique dataset from a large study of Syrian refugee children and their caregivers (BIOPATH). The data analyzed included demographic, genetic, social, psychological, and environmental variables, allowing a comprehensive evaluation of the causal determinants of mental health of refugee children. We found that daily stressors are important determinants of refugee children's mental health and that the level of exposure to war events, violence re-victimization and caregiver mental health are particularly relevant causal determinants for severe and persistent psychological problems.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

An integrative statistical approach to exploring causal relationships in non-experimental data was developed, systematically evaluated, and made publicly available. This new statistical tool was first applied to a well-established large cohort in the UK revealing the most relevant psychological and environmental factors in the first year of life that causally predict cognitive abilities at the beginning of school life. The same approach was then applied to discover the main psychosocial causes of severe and persistent psychological distress in Syrian refugee children. The level of exposure to war-related events, bullying in the community, and maltreatment emerged as causal factors for severe forms of post-traumatic stress disorder in children. Finally, the CARINGTrauma project explored the use of genetic liability measures (i.e. polygenic scores) to improve causal investigations on refugee children's mental health. The results were presented at various international conferences and webinars, and are publicly available in preprint repositories.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The new integrative modeling approach to explore causal relationships in observational data adds to researchers' toolbox and helps them tackling causal questions in child development and mental health. Results on the causal predictors of severe mental health problems in Syrian refugee children can potentially inform preventive strategies, services, and mental health care planning for children affected by war and living in challenging conditions. Finally, new mechanistic insights and improved causal predictions for mental health problems are expected to be achieved by including genetic factors in the integrative statistical modeling approach.

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