Seah Carina, Huckins Laura M, Brennand Kristen J
Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York; Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York.
Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York; Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.
Biol Psychiatry. 2023 Apr 1;93(7):642-650. doi: 10.1016/j.biopsych.2022.09.033. Epub 2022 Oct 8.
Genome-wide association studies reveal the complex polygenic architecture underlying psychiatric disorder risk, but there is an unmet need to validate causal variants, resolve their target genes(s), and explore their functional impacts on disorder-related mechanisms. Disorder-associated loci regulate transcription of target genes in a cell type- and context-specific manner, which can be measured through expression quantitative trait loci. In this review, we discuss methods and insights from context-specific modeling of genetically and environmentally regulated expression. Human induced pluripotent stem cell-derived cell type and organoid models have uncovered context-specific psychiatric disorder associations by investigating tissue-, cell type-, sex-, age-, and stressor-specific genetic regulation of expression. Techniques such as massively parallel reporter assays and pooled CRISPR (clustered regularly interspaced short palindromic repeats) screens make it possible to functionally fine-map genome-wide association study loci and validate their target genes at scale. Integration of disorder-associated contexts with these patient-specific human induced pluripotent stem cell models makes it possible to uncover gene by environment interactions that mediate disorder risk, which will ultimately improve our ability to diagnose and treat psychiatric disorders.
全基因组关联研究揭示了精神疾病风险背后复杂的多基因结构，但在验证因果变异、确定其靶基因以及探索它们对疾病相关机制的功能影响方面仍存在未满足的需求。与疾病相关的基因座以细胞类型和背景特异性的方式调节靶基因的转录，这可以通过表达定量性状基因座来测量。在这篇综述中，我们讨论了来自基因和环境调控表达的背景特异性建模的方法和见解。人类诱导多能干细胞衍生的细胞类型和类器官模型通过研究组织、细胞类型、性别、年龄和应激源特异性的基因表达调控，发现了背景特异性的精神疾病关联。诸如大规模平行报告基因检测和汇集式CRISPR（成簇规律间隔短回文重复序列）筛选等技术使得在全基因组范围内对关联研究基因座进行功能精细定位并大规模验证其靶基因成为可能。将与疾病相关的背景与这些患者特异性的人类诱导多能干细胞模型相结合，使得发现介导疾病风险的基因与环境相互作用成为可能，这最终将提高我们诊断和治疗精神疾病的能力。
