Markers of Environmental Sensitivity in Syrian Refugee Children across Multiple Levels of Analysis

• In Event: Recent Advances in Research on Highly Sensitive Children

Abstract

Introduction
Children vary in the extent to which they are affected by contextual adversity (Karam et al., 2019), to some degree as a result of individual differences in their sensitivity to the environment (Pluess, 2015). Several robust markers of childhood sensitivity have been identified at different levels of analysis (Ellis et al., 2011, Belsky & Pluess, 2013), including the behavioural (e.g. personality traits like sensory processing sensitivity), physiological (e.g. biomarkers such as cortisol) and genetic (e.g. serotonergic and dopaminergic genes) levels. However, these markers have mostly been identified and explored in isolation, and in separate samples. Understanding how sensitivity markers correlate and interconnect may improve the unbiased identification of highly sensitive children, but requires studies that examine different markers of sensitivity within a single cohort, which are currently lacking. In the present study, we aimed to investigate the interrelationships between a number of established sensitivity markers, including self-reported sensitivity, genetic sensitivity, and cortisol, within a cohort of 1,600 Syrian child and adolescent refugees.

Hypotheses
We hypothesise that across different levels, sensitivity markers will significantly correlate, together helping to better predict highly sensitive children compared to individual markers alone.

Study population
Study participants were recruited from 77 refugee camps in Lebanon, as part of the Biological Pathways of Risk and Resilience in Syrian Refugee Children (BIOPATH) study (McEwen et al., 2022). Refugee children between 8-16 years of age with at least one caregiver that together had fled Syria no more than four years prior to data collection were eligible for the study.

Methods
Self-reported sensitivity was assessed using the Highly Sensitive Child (HSC) scale, and hair samples were taken to examine cortisol, testosterone, and dehydroepiandrosterone levels. DNA extracted from saliva was genotyped on the Illumina Global Screening Array and further genotypes were imputed. Existing polygenic scoring algorithms for sensitivity (Keers et al., 2017) and related traits (e.g. Neuroticism; Assari et al., 2020) will be used to score participant genotypes, creating a number of genetic sensitivity markers. Regression modelling will be used to regress self-reported sensitivity scores on to hormone levels and polygenic scores, while controlling for other covariates. Intercorrelations between all markers of sensitivity will also be investigated.

Results
Analyses are currently on-going but will be completed in time for the conference. Preliminary regression results suggest that self-reported sensitivity is positively associated with cortisol (p = .014), and the ratio of cortisol to dehydroepiandrosterone (p = .065), while controlling for participant sex. However, these associations are diminished when controlling for participant age.

Authors

• Andrew May, University G. d’Annunzio Chieti-Pescara
  Presenting Author

• Francesca Lionetti, G. d’Annunzio University of Chieti-Pescara and Queen Mary University of London

• Demelza Smeeth, Queen Mary University of London

• Elie Karam, Institute for Development, Research, Advocacy and Applied Care