Arasappan Dhivya, Spears Abigail, Shah Simran, Mayfield Roy D, Akula Nirmala, McMahon Francis J, Jabbi Mbemba
Center for Biomedical Research Support, The University of Texas at Austin, Dell Medical School, Austin, Texas, USA.
Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin, Dell Medical School, Austin, Texas, USA.
bioRxiv. 2024 Aug 16:2024.08.14.606080. doi: 10.1101/2024.08.14.606080.
Mood disorders affect over ten percent of humans, but studies dissecting the brain anatomical and molecular neurobiological mechanisms underlying mood (dys)functions have not consistently identified the patterns of pathological changes in relevant brain regions. Recent studies have identified pathological changes in the anterior insula (Ant-Ins) and subgenual anterior cingulate (sgACC) brain network in mood disorders, in line with this network's role in regulating mood/affective feeling states. Here, we applied whole-tissue RNA-sequencing measures of differentially expressed genes (DEGs) in mood disorders versus (vs.) psychiatrically unaffected controls (controls) to identify postmortem molecular pathological markers for mood disorder phenotypes. Using data-driven factor analysis of the postmortem phenotypic variables to determine relevant sources of population variances, we identified DEGs associated with mood disorder-related diagnostic phenotypes by combining gene co-expression, differential gene expression, and pathway-enrichment analyses. We found downregulation/under expression of inflammatory, and protein synthesis-related genes associated with psychiatric morbidity (i.e., all co-occurring mental disorders and suicide outcomes/death by suicide) in Ant-Ins, in contrasts to upregulation of synaptic membrane and ion channel-related genes with increased in sgACC. Our results identified a preponderance of downregulated metabolic, protein synthesis, inflammatory, and synaptic membrane DEGs associated with outcomes in relation to a factor representing in the Ant-Ins and sgACC (AIAC) network. Our study revealed a critical brain network molecular repertoire for mood disorder phenotypes, including suicide outcomes and longevity, and provides a framework for defining dosage-sensitive (i.e., downregulated vs. upregulated) molecular signatures for mood disorder phenotypic complexity and pathological outcomes.
情绪障碍影响着超过10%的人群,但剖析情绪(功能)障碍背后的脑解剖学和分子神经生物学机制的研究,并未始终如一地确定相关脑区的病理变化模式。最近的研究已经确定了情绪障碍患者前脑岛(Ant-Ins)和膝下前扣带回(sgACC)脑网络的病理变化,这与该网络在调节情绪/情感状态方面的作用一致。在这里,我们应用全组织RNA测序来测量情绪障碍患者与精神状态未受影响的对照者(对照组)中差异表达基因(DEGs),以确定情绪障碍表型的死后分子病理标志物。通过对死后表型变量进行数据驱动的因子分析,以确定群体变异的相关来源,我们通过结合基因共表达、差异基因表达和通路富集分析,确定了与情绪障碍相关诊断表型相关的DEGs。我们发现,前脑岛中与精神疾病发病率(即所有共病精神障碍和自杀结局/自杀死亡)相关的炎症和蛋白质合成相关基因下调/表达不足,相比之下,膝下前扣带回中与突触膜和离子通道相关的基因上调。我们的结果确定,与代表前脑岛和膝下前扣带回(AIAC)网络中的一个因子相关的结局中,下调的代谢、蛋白质合成、炎症和突触膜DEGs占优势。我们的研究揭示了情绪障碍表型(包括自杀结局和寿命)的关键脑网络分子组成,并为定义情绪障碍表型复杂性和病理结局的剂量敏感(即下调与上调)分子特征提供了一个框架。