美国斯坦福大学Laramie E. Duncan等研究人员绘制出精神分裂症及复杂脑表型的细胞病因图谱。相关论文于2025年1月20日在线发表在《自然—神经科学》杂志上。

研究人员利用两个标志性资源来推断参与精神分裂症、其他精神疾病及脑表型对比的细胞类型。研究人员发现精神分裂症、双相障碍和抑郁症与皮层和皮层下神经元相关。这些细胞类型包括生长抑素抑制性神经元、来自后扣带皮层的兴奋性神经元和来自杏仁体的奇特中等棘突样神经元。

相比之下，研究人员发现T细胞和B细胞与多发性硬化症相关，微胶质细胞与阿尔茨海默病相关。研究人员提供了一个基于细胞类型的分类系统框架，这可以推动药物重定位或开发机会以及个性化治疗。该研究正式提出了一个基于数据驱动的复杂脑部疾病细胞和分子模型。

研究人员表示，精神疾病是多因素的，且目前缺乏有效的治疗方法。治疗开发面临的挑战可能与人类大脑的复杂性以及精神疾病的高多基因性有关。通过结合具有足够样本量的全基因组和全脑遗传学与转录组学分析，可以加深人们对精神疾病病因的理解。

附：英文原文

Title: Mapping the cellular etiology of schizophrenia and complex brain phenotypes

Author: Duncan, Laramie E., Li, Tayden, Salem, Madeleine, Li, Will, Mortazavi, Leili, Senturk, Hazal, Shahverdizadeh, Naghmeh, Vesuna, Sam, Shen, Hanyang, Yoon, Jong, Wang, Gordon, Ballon, Jacob, Tan, Longzhi, Pruett, Brandon Scott, Knutson, Brian, Deisseroth, Karl, Giardino, William J.

Issue&Volume: 2025-01-20

Abstract: Psychiatric disorders are multifactorial and effective treatments are lacking. Probable contributing factors to the challenges in therapeutic development include the complexity of the human brain and the high polygenicity of psychiatric disorders. Combining well-powered genome-wide and brain-wide genetics and transcriptomics analyses can deepen our understanding of the etiology of psychiatric disorders. Here, we leverage two landmark resources to infer the cell types involved in the etiology of schizophrenia, other psychiatric disorders and informative comparison of brain phenotypes. We found both cortical and subcortical neuronal associations for schizophrenia, bipolar disorder and depression. These cell types included somatostatin interneurons, excitatory neurons from the retrosplenial cortex and eccentric medium spiny-like neurons from the amygdala. In contrast we found T cell and B cell associations with multiple sclerosis and microglial associations with Alzheimer’s disease. We provide a framework for a cell-type-based classification system that can lead to drug repurposing or development opportunities and personalized treatments. This work formalizes a data-driven, cellular and molecular model of complex brain disorders.

DOI: 10.1038/s41593-024-01834-w

Source: https://www.nature.com/articles/s41593-024-01834-w