Gogos Joseph A, Crabtree Gregg, Diamantopoulou Anastasia
Mortimer B. Zuckerman Mind Brain and Behavior Institute Columbia University, New York, NY 10027, USA; Department of Physiology and Cellular Biophysics, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA; Department of Neuroscience, Columbia University, New York, NY 10032, USA.
Mortimer B. Zuckerman Mind Brain and Behavior Institute Columbia University, New York, NY 10027, USA; Department of Physiology and Cellular Biophysics, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
Schizophr Res. 2020 Mar;217:37-51. doi: 10.1016/j.schres.2019.03.018. Epub 2019 Apr 12.
Studies using powerful family-based designs aided by large scale case-control studies, have been instrumental in cracking the genetic complexity of the disease, identifying rare and highly penetrant risk mutations and providing a handle on experimentally tractable model systems. Mouse models of rare mutations, paired with analysis of homologous cognitive and sensory processing deficits and state-of-the-art neuroscience methods to manipulate and record neuronal activity have started providing unprecedented insights into pathogenic mechanisms and building the foundation of a new biological framework for understanding mental illness. A number of important principles are emerging, namely that degradation of the computational mechanisms underlying the ordered activity and plasticity of both local and long-range neuronal assemblies, the building blocks necessary for stable cognition and perception, might be the inevitable consequence and the common point of convergence of the vastly heterogeneous genetic liability, manifesting as defective internally- or stimulus-driven neuronal activation patterns and triggering the constellation of schizophrenia symptoms. Animal models of rare mutations have the unique potential to help us move from "which" (gene) to "how", "where" and "when" computational regimes of neural ensembles are affected. Linking these variables should improve our understanding of how symptoms emerge and how diagnostic boundaries are established at a circuit level. Eventually, a better understanding of pathophysiological trajectories at the level of neural circuitry in mice, aided by basic human experimental biology, should guide the development of new therapeutics targeting either altered circuitry itself or the underlying biological pathways.
利用强大的基于家系的设计并辅以大规模病例对照研究的各项研究,在破解该疾病的遗传复杂性、识别罕见且高外显率的风险突变以及为易于实验操作的模型系统提供方法等方面发挥了重要作用。罕见突变的小鼠模型,结合对同源认知和感觉加工缺陷的分析以及用于操纵和记录神经元活动的前沿神经科学方法,已开始为致病机制提供前所未有的见解,并为理解精神疾病构建新的生物学框架奠定基础。一些重要原则正在浮现,即局部和远程神经元集合有序活动及可塑性背后的计算机制退化,而这些是稳定认知和感知所必需的组成部分,可能是遗传易感性差异巨大的必然结果和共同汇聚点,表现为内部或刺激驱动的神经元激活模式存在缺陷,并引发一系列精神分裂症症状。罕见突变的动物模型具有独特潜力,可帮助我们从“哪个”(基因)转向神经群体的计算机制“如何”“何处”以及“何时”受到影响。将这些变量联系起来应能增进我们对症状如何出现以及在电路层面如何确定诊断界限的理解。最终,借助基础人类实验生物学,更好地理解小鼠神经回路水平的病理生理轨迹,应能指导针对改变的回路本身或潜在生物学途径的新疗法的开发。