Less Efficient Information Transfer in Cys-Allele Carriers of DISC1: A Brain Network Study Based on Diffusion MRI
Less Efficient Information Transfer in Cys-Allele Carriers of DISC1: A Brain Network Study Based on Diffusion MRI
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DISC1 的 Cys 等位基因携带者信息传输效率较低：基于扩散 MRI 的脑网络研究
DOI：
10.1093/cercor/bhs167
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发表时间：
2013-07-01
期刊：
影响因子：
3.7
通讯作者：
Jiang, Tianzi
中科院分区：
文献类型：
--
作者：
Li, Yonghui;Liu, Bing;Jiang, Tianzi
先前对大脑网络的神经影像学研究表明，精神分裂症患者的信息传递效率较低。然而，其潜在的遗传基础在很大程度上仍未被探索。在这项研究中，我们对278名具有不同基因型的健康志愿者的大脑解剖网络进行了研究，这些志愿者在精神分裂症断裂基因1（DISC1）的常见错义变体（Ser704Cys）上存在差异，DISC1基因是精神分裂症和其他精神疾病的主要易感基因之一。基于扩散磁共振成像（dMRI），利用纤维束成像技术为每个个体构建了解剖大脑网络。然后利用图论计算了该网络的特性。结果显示，Cys等位基因携带者的大脑网络全局效率明显低于Ser纯合子，从而支持了我们的假设，即DISC1的基因变异可能通过影响大脑网络效率而与精神分裂症的风险相关。还在不同层面进行了额外的dMRI分析，在Cys等位基因携带者中始终观察到白质完整性下降的一致趋势。这些发现不仅为理解DISC1的功能提供了新线索，还表明基于图论的网络分析结合神经影像学技术可能揭示健康个体大脑中与遗传风险相关的结构破坏。
Previous neuroimaging studies of brain networks have revealed less efficient information transfer in patients with schizophrenia. However, the underlying genetic basis remains largely unexplored. In this study, we investigated the brain anatomical networks of 278 healthy volunteers with different genotypes in the common missense variant (Ser704Cys) of the Disrupted-in-Schizophrenia-1 (DISC1) gene, which is one of the main susceptibility genes of schizophrenia and other psychiatric disorders. The anatomical brain network for each individual was constructed using fiber tractography technique based on diffusion magnetic resonance imaging (dMRI). The properties of this network were then calculated using graph theory. This revealed that Cys-allele carriers showed significantly lower global efficiency of their brain networks than Ser homozygotes, thereby supporting our hypothesis that genetic variation in DISC1 may relate to the risk of schizophrenia by affecting the efficiency of brain network. Additional dMRI analyses were also performed at different levels, with a convergent trend towards decreased white matter integrity being consistently observed in Cys-allele carriers. Together these findings not only provide new clues for understanding DISC1 function, but also suggest that network analyses based on graph theory combined with neuroimaging techniques may reveal structural disruptions related to genetic risk in the brains of healthy individuals.