Department of Psychology, Yale University, New Haven, CT 06520;
Department of Psychology, Yale University, New Haven, CT 06520.
Proc Natl Acad Sci U S A. 2020 Oct 6;117(40):25138-25149. doi: 10.1073/pnas.2008004117. Epub 2020 Sep 21.
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 ≥ 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.
重度抑郁症是由跨越基因和分子的生物系统的复杂相互作用产生的。要确定神经生物学过程如何汇聚在一起导致抑郁症，需要采用多尺度方法，包括大脑结构和功能的测量以及遗传和细胞特异性转录数据。在这里，我们检查了三个人群成像数据集（英国生物库、大脑基因组超级结构项目和通过荟萃分析增强神经成像（ENIGMA；合并≥23,723 例））中抑郁和负性情绪的解剖学（皮质厚度）和功能（功能变异性，全脑连接）相关性。综合分析包括皮质基因表达测量、尸检患者转录数据、抑郁全基因组关联研究（GWAS）和单细胞基因转录。抑郁和负性情绪的神经影像学相关性在三个独立数据集之间是一致的。将体外基因下调与体内神经影像学联系起来，我们发现抑郁影像学表型的转录相关性追踪了抑郁症患者尸检皮质样本中的基因下调。单细胞和 Allen 人类大脑图谱表达数据的综合分析显示，生长抑素中间神经元和星形胶质细胞是通过体内成像和体外皮质基因失调与抑郁一致的细胞关联。GWAS 衍生的与抑郁相关的多基因风险为这些观察结果提供了趋同证据，在中间神经元中表达的基因，但不在神经胶质细胞中表达。强调多尺度方法的转化潜力，与抑郁相关的大脑功能和结构的转录相关性与抑郁相关的分子途径富集。这些发现连接了特定基因、细胞类型和生物途径与抑郁的体内成像相关性。
