Over the past decade, large-scale genetic studies have successfully identified hundreds of genetic variants robustly associated with risk for psychiatric disorders. However, mechanistic insight and clinical translation continue to lag the pace of risk variant identification, hindered by the sheer number of targets and their predominant noncoding localization, as well as pervasive pleiotropy and incomplete penetrance. Successful next steps require identification of "causal" genetic variants and their proximal biological consequences; placing variants within biologically defined functional contexts, reflecting specific molecular pathways, cell types, circuits, and developmental windows; and characterizing the downstream, convergent neurobiological impact of polygenicity within an individual. Here, we discuss opportunities and challenges of high-throughput transcriptomic profiling in the human brain, and how transcriptomic approaches can help pinpoint mechanisms underlying genetic risk for psychiatric disorders at a scale necessary to tackle daunting levels of polygenicity. These include transcriptome-wide association studies for risk gene prioritization through integration of genome-wide association studies with expression quantitative trait loci. We outline transcriptomic results that inform our understanding of the brain-level molecular pathology of psychiatric disorders, including autism spectrum disorder, bipolar disorder, major depressive disorder, and schizophrenia. Finally, we discuss systems-level approaches for integration of distinct genetic, genomic, and phenotypic levels, including combining spatially resolved gene expression and human neuroimaging maps. Results highlight the importance of understanding gene expression (dys)regulation across human brain development as a major contributor to psychiatric disease pathogenesis, from common variants acting as expression quantitative trait loci to rare variants enriched for gene expression regulatory pathways.

中文翻译：

---

转录组学洞察精神疾病的多基因机制


在过去的十年中，大规模的基因研究已成功识别出数百种与精神疾病风险密切相关的基因变异。然而，由于靶点数量庞大、主要的非编码定位、普遍的多效性和不完全外显率，机制洞察和临床转化继续落后于风险变异识别的步伐。成功的后续步骤需要识别“因果”遗传变异及其近端生物学后果；将变体置于生物学定义的功能环境中，反映特定的分子途径、细胞类型、电路和发育窗口；并描述个体内多基因性的下游、聚合神经生物学影响。在这里，我们讨论人脑高通量转录组学分析的机遇和挑战，以及转录组学方法如何帮助查明精神疾病遗传风险的潜在机制，以解决令人畏惧的多基因性水平所必需的规模。这些包括通过将全基因组关联研究与表达数量性状基因座整合来进行风险基因优先排序的全转录组关联研究。我们概述了转录组结果，帮助我们理解精神疾病的大脑水平分子病理学，包括自闭症谱系障碍、双相情感障碍、重度抑郁症和精神分裂症。最后，我们讨论了整合不同遗传、基因组和表型水平的系统级方法，包括将空间解析的基因表达和人类神经影像图相结合。 结果强调了理解人类大脑发育过程中的基因表达（失调）调节作为精神疾病发病机制的主要贡献者的重要性，从作为表达数量性状位点的常见变异到富含基因表达调节途径的罕见变异。