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Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion
NeuroImage ( IF 5.7 ) Pub Date : 2021-08-26 , DOI: 10.1016/j.neuroimage.2021.118520
Natalia Gass 1 , Zeru Peterson 2 , Jonathan Reinwald 3 , Alexander Sartorius 3 , Wolfgang Weber-Fahr 1 , Markus Sack 1 , Junfang Chen 4 , Han Cao 4 , Michael Didriksen 5 , Tine Bryan Stensbøl 5 , Gabrielle Klemme 2 , Adam J Schwarz 6 , Emanuel Schwarz 4 , Andreas Meyer-Lindenberg 4 , Thomas Nickl-Jockschat 7
Affiliation  

Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.



中文翻译:

跨网络的差异静息状态模式在空间上与 22q11.2 缺失小鼠模型中的 Comt 和 Trmt2a 基因表达模式相关

涉及多个基因的拷贝数变异 (CNV) 是研究多基因神经精神疾病的理想模型。由于 22q11.2 缺失被认为是发展为精神分裂症的最重要的单一遗传风险因素,因此表征这种 CNV 对神经网络的影响为描述赋予该疾病风险的多基因相互作用提供了独特的途径。我们使用人类 22q11.2 缺失的 Df(h22q11)/+ 小鼠模型来剖析在空间上与该模型中差异静息状态功能连接 (FC) 模式重叠的基因表达模式 ( N  = 12 Df(h22q11)/+小鼠,N = 10 个同窝对照)。为了证实我们发现的转化相关性,我们使用机器学习分析了精神分裂症患者和健康对照的组织样本,以探索已识别的基因是否在人类中共同表达。此外,我们使用 STRING 蛋白质-蛋白质相互作用数据库来识别在空间上与低或超 FC 相关的基因之间的潜在相互作用。我们发现低 FC 和 hyper-FC 的不同静息状态连通性与空间基因表达模式之间存在显着关联。两个基因,ComtTrmt2a,在所有网络中一直被过度表达。对人类数据集的分析指出,这两个基因在精神分裂症患者大脑中的共表达被破坏,但在健康对照组中没有。我们的研究结果表明,COMTTRMT2A形成了与 22q11.2 缺失中不同的静息状态连接模式有关的核心遗传成分。它们在精神分裂症患者中共表达的中断指出了分子水平上 22q11.2 缺失综合征中脑网络通讯异常的潜在原因。

更新日期:2021-09-07
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