Biosocial Predictors of Resilience to Adverse Childhood Experiences

One of the best replicated findings in developmental research, psychology and epidemiology is that exposure to adverse childhood experiences (ACEs), such as neglect, abuse, caregiver psychopathology or addiction, violence exposure, parental separation, residential instability, low socio-economic position (SEP) and lack of warmth and affection of parent-child relationships, predicts poorer outcomes across health and social domains. Childhood adversity is highly prevalent, yet some individuals do not (or only temporarily) develop stress-related dysfunctions, despite being subject to the same kind of challenges that cause long-term dysfunction in others. This 'resilience' is a well described phenomenon that is an outcome rather than a trait. By better understanding the underlying mechanisms by which children exposed to adversities show later resilience, there may be opportunities to learn more about ways of intervening and preventing adverse outcomes.
The overall aim of my project is to shape and inform resilience research to tangibly improve the lives of children exposed to ACEs and has three main stages. There are enormous differences in the way resilience is defined, operationalised and measured in the literature that is a key issue hampering the shift away from disease-focused research towards more health focused research that investigates mechanisms that can protect individuals against stress related disease. In the first stage, I am using a novel approach to quantify resilience, operationalised as the difference between individuals actual score on a specific outcome and the score predicted by their exposure to adversity: the standardised residual scores. Taking data from an incredibly data rich longitudinal cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC), with genotype data and repeated measures of epigenetic markers, stress reactivity, adversity and outcomes, I am developing a resilient index across multiple domains of experience, beginning prenatally and continuing in to adolescence. By creating a continuous measure of resilience across the life course, I can then assess how resilience varies over time and whether individual, familial and community factors influence that variation, particularly relevant for policy and intervention impact.
The second stage of my project models developmental trajectories of resilience over time. Previous studies have suggested that trajectory analysis may help to refine the measurement of resilience and provide a more heritable phenotype that will improve signal in genetic association studies. I am using a software package to estimate the genetic influence on resilient developmental trajectory membership. This is followed by a genome wide association study to find out if there are any common genetic variants associated with trajectories of resilience.
Epigenetics, specifically DNA methylation (DNAm), is often presented as a vital new framework for understanding the differences in susceptibility and resilience to exposure to adversity and the long-term effects of a wide variety of environmental factors. However, no studies to date have incorporated prospective exposure, epigenetic and phenotypic data to explicitly test the role of DNAm as a potential biological mediator of environmental effects on resilient trajectories. The final stage of the project will employ a hypothesis free methylome-wide analysis to test whether DNAm at birth associates with later resilient trajectories. This will then be followed up at age 7 and 15 to investigate the stability of the associations across early childhood. This repeated measures design allows the possibility of examining whether altered DNA methylation patterns are an associated factor of, or consequence of, a resilient trajectory.