Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America.
Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States of America.
Schizophr Res. 2020 Mar;217:26-36. doi: 10.1016/j.schres.2019.06.017. Epub 2019 Jul 3.
As expanding genetic and genomic studies continue to implicate a growing list of variants contributing risk to neuropsychiatric disease, an important next step is to understand the functional impact and points of convergence of these risk factors. Here, with a focus on schizophrenia, we survey the most recent findings of the rare and common variants underlying genetic risk for schizophrenia. We discuss the ongoing efforts to validate these variants in post-mortem brain tissue, as well as new approaches to combine CRISPR-based genome engineering with patient-specific human induced pluripotent stem cell (hiPSC)-based models, in order to identify putative causal schizophrenia loci that regulate gene expression and cellular function. We consider the current limitations of hiPSC-based approaches as well as the future advances necessary to improve the fidelity of this human model. With the objective of utilizing patient genotype data to improve diagnosis and predict treatment response, the integration of CRISPR-genome engineering and hiPSC-based models represent an important strategy with which to systematically demonstrate the cell-type-specific effects of schizophrenia-associated variants.
随着越来越多的遗传和基因组研究表明,许多变体都可能导致神经精神疾病的风险,下一步的重要任务是了解这些风险因素的功能影响和趋同点。在这里,我们重点关注精神分裂症,调查了导致精神分裂症遗传风险的罕见和常见变体的最新发现。我们讨论了在脑组织标本中验证这些变体的持续努力,以及结合基于 CRISPR 的基因组工程与患者特异性人诱导多能干细胞 (hiPSC) 模型的新方法,以确定可能调节基因表达和细胞功能的精神分裂症相关基因座。我们考虑了基于 hiPSC 的方法的当前局限性,以及为提高该人类模型的保真度所需的未来进展。为了利用患者的基因型数据来改善诊断和预测治疗反应,CRISPR-基因组工程和基于 hiPSC 的模型的整合代表了一种重要的策略,可以系统地证明与精神分裂症相关的变体的细胞类型特异性效应。