Major depressive disorder emerges from the complex interactions of biological systems that span genes and molecules through cells, networks, and behavior. Establishing how neurobiological processes coalesce to contribute to depression requires a multiscale approach, encompassing measures of brain structure and function as well as genetic and cell-specific transcriptional data. Here, we examine anatomical (cortical thickness) and functional (functional variability, global brain connectivity) correlates of depression and negative affect across three population-imaging datasets: UK Biobank, Brain Genomics Superstruct Project, and Enhancing NeuroImaging through Meta Analysis (ENIGMA; combined n ≥ 23,723). Integrative analyses incorporate measures of cortical gene expression, postmortem patient transcriptional data, depression genome-wide association study (GWAS), and single-cell gene transcription. Neuroimaging correlates of depression and negative affect were consistent across three independent datasets. Linking ex vivo gene down-regulation with in vivo neuroimaging, we find that transcriptional correlates of depression imaging phenotypes track gene down-regulation in postmortem cortical samples of patients with depression. Integrated analysis of single-cell and Allen Human Brain Atlas expression data reveal somatostatin interneurons and astrocytes to be consistent cell associates of depression, through both in vivo imaging and ex vivo cortical gene dysregulation. Providing converging evidence for these observations, GWAS-derived polygenic risk for depression was enriched for genes expressed in interneurons, but not glia. Underscoring the translational potential of multiscale approaches, the transcriptional correlates of depression-linked brain function and structure were enriched for disorder-relevant molecular pathways. These findings bridge levels to connect specific genes, cell classes, and biological pathways to in vivo imaging correlates of depression.

严重的抑郁症源于通过细胞，网络和行为跨越基因和分子的生物系统的复杂相互作用。要确定神经生物学过程如何联合导致抑郁症，就需要采取多尺度方法，包括测量大脑结构和功能以及遗传和细胞特异性转录数据。在这里，我们研究了三种人群成像数据集：英国生物库，脑基因组学上级计划项目和通过元分析来增强神经成像（ENIGMA）的解剖学（皮层厚度）和功能性（功能变异性，全球脑连通性）的相关性与抑郁和负面影响的关系。ñ≥23,723）。整合分析结合了皮质基因表达，死后患者转录数据，抑郁症全基因组关联研究（GWAS）和单细胞基因转录的测量。在三个独立的数据集中，抑郁症和负面影响的神经影像相关性是一致的。将离体基因下调与体内神经影像联系起来，我们发现抑郁症成像表型的转录相关性追踪了抑郁症患者的死后皮质样品中的基因下调。对单细胞和艾伦人脑图谱表达数据的综合分析显示，通过体内成像和离体皮层基因失调，生长抑素中间神经元和星形胶质细胞是抑郁症的一致细胞联想。为这些观察提供融合的证据，GWAS衍生的抑郁多基因风险丰富了中间神经元中表达的基因，但胶质细胞中没有。强调多尺度方法的翻译潜力，与抑郁症相关的分子途径丰富了与抑郁相关的脑功能和结构的转录相关性。这些发现弥合了将特定基因，细胞类型和生物学途径与抑郁症的体内成像相关联的水平。