| Literature DB >> 30987923 |
Joseph A Gogos1, Gregg Crabtree2, Anastasia Diamantopoulou2.
Abstract
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.Entities:
Keywords: Animal models; Cognition; Human genetics; Neural circuits; Schizophrenia; Therapeutics
Mesh:
Year: 2019 PMID: 30987923 PMCID: PMC6790166 DOI: 10.1016/j.schres.2019.03.018
Source DB: PubMed Journal: Schizophr Res ISSN: 0920-9964 Impact factor: 4.939