Atypical dynamic network reconfiguration and genetic mechanisms in patients with major depressive disorder

重性抑郁障碍 功能磁共振成像 控制重构 默认模式网络 转录组 显著性(神经科学) 神经科学 生物 心理学 计算生物学 基因 认知 遗传学 计算机科学 基因表达 嵌入式系统
作者
Hairong Xiao,Dier Tang,Chuchu Zheng,Zeyu Yang,Wei Zhao,Shuixia Guo
出处
期刊:Progress in Neuro-psychopharmacology & Biological Psychiatry [Elsevier]
卷期号:: 110957-110957
标识
DOI:10.1016/j.pnpbp.2024.110957
摘要

Brain dynamics underlie complex forms of flexible cognition or the ability to shift between different mental modes. However, the precise dynamic reconfiguration based on multi-layer network analysis and the genetic mechanisms of major depressive disorder (MDD) remains unclear. Resting-state functional magnetic resonance imaging (fMRI) data were acquired from the REST-meta-MDD consortium, including 555 patients with MDD and 536 healthy controls (HC). A time-varying multi-layer network was constructed, and dynamic modular characteristics were used to investigate the network reconfiguration. Additionally, partial least squares regression analysis was performed using transcriptional data provided by the Allen Human Brain Atlas (AHBA) to identify genes associated with atypical dynamic network reconfiguration in MDD. In comparison to HC, patients with MDD exhibited lower global and local recruitment coefficients. The local reduction was particularly evident in the salience and subcortical networks. Spatial transcriptome correlation analysis revealed an association between gene expression profiles and atypical dynamic network reconfiguration observed in MDD. Further functional enrichment analyses indicated that positively weighted reconfiguration-related genes were primarily associated with metabolic and biosynthetic pathways. Additionally, negatively enriched genes were predominantly related to programmed cell death-related terms. Our findings offer robust evidence of the atypical dynamic reconfiguration in patients with MDD from a novel perspective. These results offer valuable insights for further exploration into the mechanisms underlying MDD.
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