Integration of CRISPR-engineering and hiPSC-based models of psychiatric genomics

Abstract

Neuropsychiatric disorders are highly heritable polygenic disorders arising from the complex interplay of highly penetrant rare variants and common variants of small effect. There is a large index of comorbidity and shared genetic risk between disorders, reflecting the pleiotropy of individual variants as well as predicted downstream pathway-level convergence. Importantly, the mechanism(s) through which psychiatric disease-associated variants interact to contribute to disease risk remains unknown. Human induced pluripotent stem cell (hiPSC)-based models are increasingly useful for the systematic study of the complex genetics associated with brain diseases, particularly when combined with CRISPR-mediated genomic engineering, which together facilitate isogenic comparisons of defined neuronal cell types. In this review, we discuss the latest CRISPR technologies and consider how they can be successfully applied to the functional characterization of the growing list genetic variants linked to psychiatric disease.

Keywords: CRISPR; Human induced pluripotent stem cell; Psychiatric genetics.

Figure 1.. INTEGRATION of CRISPR technology and hiPSC-based models for functional genomic studies of psychiatric disorders.

GWAS identify common variants associated to psychiatric disorders, which are then correlated to differential gene expression patterns via eQTL analysis. CRISPR derived technologies can be used to create isogenic hiPSC models of any brain cell type to functionally validate common and rare variants associated with psychiatric disease. These models, retaining the genetic brackground of the donor, have the potential to reveal molecular and cellular phenotypes even for variants with small effect sizes. In addition, top-down analysis can be perfomed with these CRISPR models to screen for variants directly associated with canonical psychiatric cellular phenotypes, such as neuronal connectivity and neurotransmission. In summary, these approaches allow for causation analysis of loci identified through psychiatric genomics.