Individual structural covariance connectome reveals aberrant brain developmental trajectories associated with childhood maltreatment

J Psychiatr Res. 2024 Dec 22:181:709-715. doi: 10.1016/j.jpsychires.2024.12.032. Online ahead of print.

Abstract

Background: The long-term impact of childhood maltreatment (CM) on an individual's physical and mental health is suggested to be mediated by altered neurodevelopment. However, the exact neurobiological consequences of CM remain unclear.

Methods: The present study aimed to investigate the relationship between CM and brain age based on structural magnetic resonance imaging data from a sample of 214 adults. The participants were divided into CM and non_CM groups according to Childhood Trauma Questionnaire. For each participant, brain connectome age was estimated from a large-scale structural covariance network through relevance vector regression. Brain predicted age difference (brain_PAD) was then calculated for each participant.

Results: The brain connectome age matched well with chronological age in young adults (age range: 18-25 years) and adults (age range: 26-44 years) without CM, but not in individuals with CM. Compared with non_CM group, CM group was characterized by higher brain_PAD scores in young adults, whereas lower brain_PAD scores in adults. The finding revealed that brain development in individuals with CM seems to be accelerated in younger adults but retardation with increasing age. Moreover, individuals who suffered child abuse (but not neglect) showed higher brain_PAD scores than non_CM group, suggesting the different influence of abuse and neglect on neurodevelopment. Finally, the brain_PAD was positively correlated with attentional impulsivity in CM group.

Conclusions: CM affects different stages of adult brain development differently, and abuse and neglect have different influenced patterns, which may provide new evidence for the impact of CM on structural brain development.

Keywords: Brain predicted age difference; Childhood maltreatment; Impulsivity; Structural covariance network.