双相情感障碍
神经影像学
心情
内表型
认知
默认模式网络
静息状态功能磁共振成像
心理学
神经科学
临床心理学
作者
Yudan Ding,Huabing Li,Feng Liu,Ping Li,Jingping Zhao,Dongsheng Lv,Wenbin Guo
摘要
ABSTRACT Objectives Investigating brain network properties in BD patients across mood states can offer insights into the underlying mechanisms of the disorder. This study aimed to explore the topological architecture of functional brain networks in BD and its relationship with clinical variables and genetic/transcriptomic variations. Methods The study involved 100 BD patients and 95 healthy controls. Researchers used graph theory‐based methods to analyze whole‐brain functional networks and explore their relationship with clinical variables. We also conducted a neuroimaging‐transcription association analysis using the Allen Human Brain Atlas. Results Depressive and manic BD patients exhibited increased local efficiency and decreased global efficiency at the global network level compared to healthy controls. Nodal‐level analysis revealed disrupted nodal parameters within specific brain networks, including the fronto‐parietal, default mode, and somatomotor networks. Significant correlations were found between nodal properties and cognitive function. All BD groups showed enhanced connectivity strength in rich‐club and feeder connections compared to controls. Neuroimaging‐transcription analysis identified potential genetic factors related to BD. Conclusion Our investigation unveiled shared impairments in the overall topological architecture of functional brain networks across depressive, manic, and euthymic BD. These observed abnormalities were associated with cognitive deficits in BD patients across three mood states. These common deficits, possibly stemming from the segregated changes in structural and functional rich‐club connections, might represent trait‐like pathophysiological mechanisms inherent to BD. Furthermore, our neuroimaging‐transcription association analysis indicates the potential use of brain functional anomalies as endophenotypes in BD.
科研通智能强力驱动
Strongly Powered by AbleSci AI