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H2020Individual fellowship2020–2022

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

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2020-09-14 → 2022-09-13
EU contribution
€224,934
Participants
1
Scheme
MSCA-IF

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Results in brief

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

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.

Data: CORDIS, © European Union

Project objective

Exposure to war-related traumatic events as well as displacement have been found to increase refugee children’s vulnerability for the development of mental health problems. However, there is substantial variability, with some presenting with mental health disorders, while others show remarkable resilience. One reason for this observed variability is the complex interplay between individual traits, such as genetic factors, and characteristics of the environment in determining mental health outcomes. However, the extent and nature to which individual and environmental factors causally interact to determine mental health outcomes in children remains unclear as most studies rely on correlational designs. Hence, we propose the development of an innovative statistical approach, combining advanced machine learning techniques and concepts of statistical causality, to investigate the complex and interactive causal relations between the various determinants of mental health across multiple domains. In order to achieve our objective, this new statistical approach will be applied to recently collected data from a unique longitudinal study on Syrian refugee children based in Lebanon (BIOPATH). The available data includes comprehensive demographic, genetic, epigenetic, neuroendocrine, social, psychological, and environmental variables collected from Syrian refugee children and their caregivers at two time-points (N=1600 at the baseline and N=1009 at a one year follow-up). The Experienced Researcher, Dr Claudinei Biazoli, a trained psychiatrist expertise in developing innovative models and analysing complex data, will acquire knowledge and skills in Developmental Psychology, Behavioral and Psychiatric genetics under the supervision of Prof Michael Pluess, a leader researcher in the field of Differential Susceptibility and Principal Investigator of the BIOPATH study, with additional support from Dr Robert Keers, with expertise in the analysis of whole-genome data.

Original text from CORDIS.

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Data: CORDIS, © European Union