Common schizophrenia variants functioning in developmental human cortical interneurons

摘要 精神分裂症（SCZ）是一种高度遗传且复杂的神经发育障碍。显着进步 最近在 SCZ 遗传研究中进行了越来越多的风险基因座达到全基因组 意义；然而，从这些位点收集生物学见解一直具有挑战性。大多数 SCZ 风险 位点位于非编码区。因此，假设它们通过调节远端基因发挥作用 通过 3D 染色质相互作用表达。然而，尚未确定哪些基因座在 哪些细胞、在什么时间点以及产生什么影响。最近的基因组分析显示 SCZ 富集 人类胎儿大脑而不是成人大脑的遗传力，表明 SCZ 风险位点在调节胎儿大脑中的作用 SCZ 风险增加的发展。因此，在开发过程中阐明 SCZ 风险位点功能至关重要 了解遗传对 SCZ 风险的影响。遗传对基因表达的影响（例如表达 数量性状位点（eQTL））是细胞类型特异性的，有时会根据细胞类型产生相反的效果 细胞类型，强调使用同质细胞群进行细胞类型特异性研究的重要性 清晰的机制理解。表达小清蛋白 (PV) 或生长抑素 (SST) 的内侧神经节 SCZ 大脑中，突起 (MGE) 衍生的皮质中间神经元 (cIN) 始终受到影响。更重要的是， SCZ 遗传力在人类胎儿大脑的 MGE 细胞中富集，因此有必要对这些进行研究 细胞了解 SCZ 风险位点的机制。尽管没有死后胎儿 SCZ 组织 机制研究，iPSC 的体外分化——很好地概括了早期胚胎发育—— 提供与患者大脑具有相同基因组成的发育性 SCZ 脑细胞。我们成立了 从健康对照中有效产生同质 MGE 衍生 cIN 群体的方法 (HC) 和 SCZ iPSC。我们还在体外和体内广泛验证了它们的功能和真实性， 包括强大的迁移和突触整合到宿主大脑中，从而产生有效的抑制调节 移植小鼠的宿主电路。使用前所未有的大量 iPSC 来提供同质 HC 与 SCZ 胎儿 cIN 群体进行机制研究，我们将提出我们的假设，即 SCZ 风险位点 活跃于发育中的 MGE 型 cIN 通过 3D 染色质相互作用调节远端基因表达。 利用转录组分析、PrediXcan 分析和 Micro-C 分析，我们将绘制 SCZ 风险位点 它们在发育过程中在这些脆弱细胞群中调节的风险基因的功能未知。 基于多个品系鉴定的发育 cIN 特异性遗传对基因表达的影响 确凿的证据将使用 CRISPRi/CRISPRa 方法进行功能验证。这个不偏不倚 来自发育中的 MGE 型 cIN 的全基因组综合数据集以及功能验证将提供 阐明发育性 SCZ 风险的遗传基础的路线图，并帮助我们识别基于机制的 新的治疗靶点。

Abstract Schizophrenia (SCZ) is a highly heritable and complex neurodevelopmental disorder. Remarkable advances have been made recently in SCZ genetic studies with an increasing number of risk loci reaching genome-wide significance; however, gleaning biological insight from these loci has been challenging. The majority of SCZ risk loci are located in non-coding regions. As such, it is hypothesized that they function by regulating distal gene expression via 3D chromatin interactions. However, it has yet to be determined which loci are operational in which cells, at what time points, and with what impact. Recent genomic analyses showed enriched SCZ heritability in human fetal brains rather than adult brains, suggesting the role of SCZ risk loci in modulating fetal development for increased SCZ risks. Thus, unraveling SCZ risk loci function during development will be critical for understanding genetic influences on SCZ risks. Genetic influences on gene expression (e.g. expression quantitative trait loci (eQTLs)) are cell-type-specific, and sometimes confer opposing effects depending on the cell type, underscoring the importance of cell-type-specific studies using homogeneous cell populations for a clear mechanistic understanding. Parvalbumin (PV)- or somatostatin (SST)-expressing medial ganglionic eminence (MGE)-derived cortical interneurons (cINs) are consistently affected in SCZ brains. More importantly, SCZ heritability is shown to be enriched in MGE cells in human fetal brains, necessitating the study of these cells to understand the mechanisms of SCZ risk loci. Although there are no postmortem fetal SCZ tissues for mechanistic study, in vitro differentiation of iPSC—which well recapitulates early embryonic development— provides developmental SCZ brain cells with the same genetic makeup as patient brains. We established methods for the efficient generation of homogeneous populations of MGE-derived cINs from healthy control (HC) and SCZ iPSCs. We also extensively validated their functionality and authenticity both in vitro and in vivo, including robust migration and synaptic integration into host brains that results in efficient inhibitory regulation of host circuitry in transplanted mice. Using an unprecedentedly large number of iPSCs to provide homogeneous populations of HC vs SCZ fetal cINs for mechanistic studies, we will address our hypothesis that SCZ risk loci active in developmental MGE-type cINs regulate distal gene expression via 3D chromatin interactions. Employing transcriptome analysis, PrediXcan analysis, and Micro-C analysis, we will map SCZ risk loci with unknown functions to the risk genes they regulate in these vulnerable cell populations during development. Developmental cIN-specific genetic influences on gene expression, identified based on multiple lines of corroborating evidence, will be functionally validated using CRISPRi/CRISPRa approaches. This unbiased genome-wide comprehensive data set from developmental MGE-type cINs with functional validation will provide a road map for unravelling the genetic basis of developmental SCZ risks and help us identify mechanism-based novel therapeutic targets.