Modelling major depressive disorder GWAS data in zebrafish using CRISPR-Cas9

Major depressive disorder (MDD) is a common psychiatric disorder which is estimated to occur in 10% to 15% of the general population during their lifetime (Tsuang et al., 2004). Family, twin and adoption studies indicate that MDD has a genetic component, with a large twin study estimating heritability at 38% (Kendler et al., 2006). Linkage studies and candidate studies were ineffective at identifying genetic factors involved in MDD. More recent genome-wide association studies, which identify common genetic variations called single nucleotide polymorphisms (SNPs) have been more successful, with Wray et al., 2018 identifying 44 loci associated with MDD in one of the largest GWAS meta-analysis in psychiatric genetics. The aim of my project is to understand how these candidate loci are implicated in MDD to better understand the genetic underpinnings of the disorder. This then can serve as a basis for the development of novel therapeutics.
Using the Wray et al., 2018 paper I will identify SNPs which are unambiguously associated with a gene. Knockouts of these candidate genes will then be created in zebrafish using CRISPR-Cas9 gene editing. The resulting transgenic lines will be used to investigate the presence of any MDD-related endophenotypes which might provide an indication to their involvement in the disorder. Behavioural assessments will focus on deficits in social interaction, cognition, locomotion and increased anxiety and sensitivity to stress (along-side biochemical tests to measure a cortisol biomarker). Structural and functional phenotypes will focus on brain regions homologous to the amygdala and hippocampus where alterations are observed in patients, while other assessments will be in relation to the role of the genes selected.