Information détaillée du papier
| Titre de l’article | The Impact of Maltreatment on Structural Connectivity in Conduct Disorder |
|---|---|
| Code d’article | P08 |
| Auteurs | |
| Forme de présentation | Poster |
| Domaines thématiques |
|
| Résumé (Abstract) |
Introduction: Conduct disorder (CD) is characterized by antisocial behavior and its heterogeneity can be partially explained by callous-unemotional (CU) traits. In addition, childhood maltreatment is associated with CD and CU traits, exerting a strong impact on behavior, cognition, and emotion. We aimed to explore the relationship between brain regions and their connections using graph theory to analyse structural connectivity in CD. Method: A total of 251 participants (MAGE=13.99) from the femNAT-CD study were included. GraphVar software in MATLAB was used for graph analysis of diffusion tensor imaging (DTI) and T1-weighted MRI images. Structural connectivity coefficients were analyzed between youth with CD (NCD=96) and typically developing youth (NTD=155). We then compared maltreated (+M; NCD+M=63) and non-maltreated (-M; NCD-M=33) subgroups within CD to assess the impact of maltreatment. Interaction analyses explored potential effects of CU traits within the CD subgroups. Results: Significant differences were found, particularly in the orbitofrontal cortex, limbic systems, and basal ganglia. Hyperconnectivity was observed in CD youth compared to TD, as well as in CD+M compared to CD-M. We also found Interaction effects with CU traits, indicating hypoconnectivity in CD+M compared to CD-M. Conclusion: The observed hyper- and hypoconnectivity may be explained by the compensation mechanism and stress acceleration hypothesis, potentially playing a crucial role in neural plasticity and network cost efficiency, thereby impacting the risk of neurodegeneration. Given previous inconclusive results, future research should consider various types and severities of maltreatment. Developing a mechanistic understanding of connectivity is crucial for advancing treatments that target brain network reorganization. |