Hamilton Kassandra Miyoko, Luo Xiaoke D, Easley Ty O, Ahmad Fyzeen, Guo Thomas, Jarukasemkit Setthanan, Modi Hailey, Rincon Samuel Naranjo, Shelton Cabria, Stahl Lyn, Wang Zijian, Zhu Yuling, Lenzini Petra, Barch Deanna M, Hannon Kayla, Bijsterbosch Janine D
Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA.
Department of Psychiatry, Washington University School of Medicine, Saint Louis, Missouri 63110, USA.
bioRxiv. 2025 Jul 8:2025.07.02.660888. doi: 10.1101/2025.07.02.660888.
Neuroimaging data offers noninvasive insights into the structural and functional organization of the brain and is therefore commonly used to study the neuroimaging correlates of depression. To date, a substantial body of literature has suggested reduced size of subcortical regions and abnormal functional connectivity in frontal and default mode networks linked to depression. However, recent meta analyses have failed to identify significant converging correlates of depression across the literature such that a conclusive mapping of the neuroimaging correlates of depression remains elusive. Here we leveraged 23,417 participants across six datasets to comprehensively establish the neuroimaging correlates of depression. We found reductions in gray matter volume/cortical surface area associated with depression in the frontal cortex, anterior cingulate, and insula, confirming prior studies showing the importance of prefrontal and default mode regions in depression. Our findings demonstrate multiple surprising results, including a lack of depression correlates in subcortical brain regions, significant depression correlates in somatomotor and visual regions, and limited functional connectivity findings. Overall, these results shed new light on key brain regions involved in the pathophysiology of depression, updating our understanding of the neuroimaging correlates of depression. We anticipate that these insights will inform further research into the role of sensorimotor and visual regions in depression and into the impact of heterogeneity on functional connectivity correlates of depression.
神经影像学数据为大脑的结构和功能组织提供了非侵入性的见解，因此常用于研究抑郁症的神经影像学关联。迄今为止，大量文献表明，与抑郁症相关的皮质下区域体积减小，以及额叶和默认模式网络中的功能连接异常。然而，最近的荟萃分析未能在整个文献中确定抑郁症的显著趋同关联，因此抑郁症的神经影像学关联的确切图谱仍然难以捉摸。在这里，我们利用六个数据集中的23417名参与者，全面确定了抑郁症的神经影像学关联。我们发现，额叶皮质、前扣带回和脑岛的灰质体积/皮质表面积与抑郁症有关，这证实了先前的研究表明前额叶和默认模式区域在抑郁症中的重要性。我们的研究结果显示了多个惊人的结果，包括皮质下脑区缺乏与抑郁症的关联、躯体运动和视觉区域存在显著的抑郁症关联，以及功能连接结果有限。总体而言，这些结果为参与抑郁症病理生理学的关键脑区提供了新的线索，更新了我们对抑郁症神经影像学关联的理解。我们预计，这些见解将为进一步研究感觉运动和视觉区域在抑郁症中的作用以及异质性对抑郁症功能连接关联的影响提供参考。
