<p>The specific role of sex differences in major depressive disorder remains unclear, this study aims to explore sex-related variations in resting-state functional connectivity of major depressive disorder patients and their association with gene expression profiles. This study included 971 patients and 897 healthy controls from the REST-meta-MDD project. We compared the functional connectivity between sexes and used the Allen Human Brain Atlas to conduct partial least squares regression analysis to identify genes associated with these functional connectivity differences in patients, followed by functional enrichment analysis. Compared to female patients, male patients exhibit increased functional connectivities between the default mode network and the frontoparietal network, while connectivities between the frontoparietal network and the visual network are reduced. Additionally, Spearman’s correlation analysis identified specific patterns of functional connectivity differences that are closely associated with the Hamilton Depression Rating Scale scores in both sexes. Transcriptomic-neuroimaging analysis revealed that the expression of 1,777 genes is associated with functional connectivity differences between sexes. Enrichment analysis indicated that these genes are primarily involved in biological processes including ion channel activity, synaptic plasticity, neuronal differentiation, and synaptic development. Patients with major depressive disorder exhibited sex-related differences in functional connectivity, particularly between networks involved in self-referential thinking, emotional regulation, and cognitive control. Genes associated with these differences were primarily enriched in ion channel activity and neuronal processes, highlighting the importance of sex-specific neural mechanisms in major depressive disorder and their potential relevance for personalized treatment strategies.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Sex differences in brain network functional connectivity and their association with gene expression profiles in major depressive disorder: a REST-meta-MDD project-based study

  • Jiang Wang,
  • Chengfeng Chen,
  • Shiying Wang,
  • Yuan Liu,
  • Peiying Li,
  • Bin Zhang

摘要

The specific role of sex differences in major depressive disorder remains unclear, this study aims to explore sex-related variations in resting-state functional connectivity of major depressive disorder patients and their association with gene expression profiles. This study included 971 patients and 897 healthy controls from the REST-meta-MDD project. We compared the functional connectivity between sexes and used the Allen Human Brain Atlas to conduct partial least squares regression analysis to identify genes associated with these functional connectivity differences in patients, followed by functional enrichment analysis. Compared to female patients, male patients exhibit increased functional connectivities between the default mode network and the frontoparietal network, while connectivities between the frontoparietal network and the visual network are reduced. Additionally, Spearman’s correlation analysis identified specific patterns of functional connectivity differences that are closely associated with the Hamilton Depression Rating Scale scores in both sexes. Transcriptomic-neuroimaging analysis revealed that the expression of 1,777 genes is associated with functional connectivity differences between sexes. Enrichment analysis indicated that these genes are primarily involved in biological processes including ion channel activity, synaptic plasticity, neuronal differentiation, and synaptic development. Patients with major depressive disorder exhibited sex-related differences in functional connectivity, particularly between networks involved in self-referential thinking, emotional regulation, and cognitive control. Genes associated with these differences were primarily enriched in ion channel activity and neuronal processes, highlighting the importance of sex-specific neural mechanisms in major depressive disorder and their potential relevance for personalized treatment strategies.