Chronicity and Severity of Adversity Impacts Longitudinal White Matter Development in Adolescence
Poster No:
985
Submission Type:
Abstract Submission
Authors:
Dawn Jensen1, Vince Calhoun2, Jingyu Liu3
Institutions:
1Georgia State University, Austell, GA, 2GSU/GATech/Emory, Atlanta, GA, 3GSU, Atlanta, GA
First Author:
Co-Author(s):
Introduction:
Adolescence is known to be a crucial development period hallmarked by rapid and diverse neural maturation. Disruption of this process due to the experience of adverse childhood experiences (ACEs) can lead to the emergence of mental illness later in life. Cross sectional research has shown that children experiencing trauma do have significant differences in their brain development, but we currently lack a clear understanding of how the chronicity and severity of ACEs might affect the brain over time. To explore this, we used a longitudinal sample of adolescents from the Adolescent Brain Cognitive Development study, which contains measures reflecting ACEs (N = 11k, 4 timepoints, ages 9-14) as well as image results that reflect white matter integrity (fractional anisotropy (FA), N= 8k, 2 timepoints).
Methods:
ACEs reported were grouped into three categories of abuse, neglect, and trauma. These were used in a latent class growth analysis to find significantly different subgroups of trajectories that reflect the chronicity and severity of participants experience of ACEs across time. Sex and the Child Opportunity Index (COI) were included as covariates (subjects are already grouped by age). Best model fit (linear or non-linear) was determined by appropriate convergence of the model, log-likelihood, and BIC criteria. The white matter measures were obtained from diffusion MRI using AtlasTracks to extract the average measure of FA in the white matter tracts. These were the dependent variables in a repeated measures linear mixed-effects model that included time, sex and ACEs subgrouping as covariates. Bonferroni corrections were applied to account for multiple testing.
Results:
A three-class non-linear model was found to best fit the data, representing significantly differing trajectories for a group of participants with low to no ACEs (54%), a group of participants experiencing an intermediately increasing level of ACEs (39%), and a group experiencing a much higher level of ACEs also increasing across time (6%). These trajectories are shown in Figure 1. In the high-level group, sex showed significant effects, with males experienced more ACEs across time. No sex differences were found in the low- and intermediate-level groups. COI was inversely related to the increase in ACEs across time. The linear mixed-effects models showed the expected time and sex influences on white matter development in addition to significant relationships between FA measures and ACEs' subgroups in the right superior longitudinal fasciculus (t = -2.68, p<0.007) and the right arcuate fasciculus (t= -2.84, p<0.004). These regions are highlighted in Figure 2. In both tracts, subjects in the low to no ACEs group had lower FA values than the subjects in the highest ACEs groups
Conclusions:
This analysis allowed the classification of a large cohort of adolescents into subgroups based on the severity and chronicity of their experiences of adverse experiences that highlighted sex differences as well as the impact of sociodemographic factors. Subjects who had the most severe and chronic ACEs showed greater development of their white matter in tracts responsible for attention, executive functioning, and language. These findings further support the stress acceleration hypothesis of advanced brain development in the face of hardship. Future work will include a parallel-process latent class growth analysis to consider the development of internalizing and externalizing behaviors with respect to ACEs and how those may impact the developmental trajectories of the brain in adolescence.
Funded by: CREST D-MAP, Dynamic Multiscale and Multimodal Brain Mapping across the Lifespan: HDR #2112455.
Funded by: CREST D-MAP, Dynamic Multiscale and Multimodal Brain Mapping across the Lifespan: HDR #2112455.
Lifespan Development:
Early life, Adolescence, Aging 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Normal Development
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Data analysis
Development
Open Data
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Adverse Childhood Experiences
1|2Indicates the priority used for review