Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication.

中文翻译：

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大量血液 RNA-seq 的细胞类型解卷积揭示了神经精神疾病的生物学见解

全基因组关联研究（GWAS）发现了与双相情感障碍（BP）和精神分裂症（SCZ）等精神疾病相关的易感位点。然而，这些基因座大多数位于基因组的非编码区域，遗传变​​异与疾病风险之间联系的因果机制尚不清楚。大块组织的表达数量性状位点（eQTL）分析是用于破译潜在机制的常用方法，尽管这可能会掩盖细胞类型特异性信号，从而掩盖性状相关机制。尽管单细胞测序在大群体中可能非常昂贵，但计算推断的细胞类型比例和细胞类型基因表达估计有可能克服这些问题并推进机制研究。这项研究利用来自 BP 和 SCZ 患者的全血样本中的 1,730 个样本进行批量 RNA 测序，估计了细胞类型比例及其与疾病状态和药物治疗的关系。对于每种细胞类型，我们发现了 2,875 至 4,629 个 eGene（具有相关 eQTL 的基因），其中包括 1,211 个仅在批量表达的基础上未发现的 eGene。我们在细胞类型 eQTL 和各种性状之间进行了共定位测试，并确定了细胞类型 eQTL 和 GWAS 之间发生的数百种关联，但在批量 eQTL 中未检测到这些关联。最后，我们研究了锂的使用对细胞类型表达位点调节的影响，并找到了根据锂的使用而受到差异调节的基因的例子。我们的研究表明，将计算方法应用于非脑组织的大量 RNA-seq 数据集可以识别精神疾病和精神药物的疾病相关、细胞类型特异性生物学。