Reduced Brd1 expression leads to reversible depression-like behaviors and gene-expression changes in female mice [anterior cingulate cortex (aCC)]

Background: The schizophrenia associated gene, BRD1, encodes an epigenetic regulator which chromatin interactome is enriched with genes implicated in mental health. Alterations in histone modifications and epigenetic regulation contribute to brain transcriptomic changes in affective disorders and preclinical data supports a role for BRD1 in psychopathology. However, the implications of BRD1 on affective pathology remains poorly understood. Methods: We assessed affective behaviors and associated neurobiology in Brd1+/- mice along with their responses to Fluoxetine and Imipramine. This involves behavioral, neurostructural, and neurochemical characterizations along with regional cerebral gene expression profiling combined with integrative functional genomic analyses. Results: Here we report behavioral changes in female Brd1+/- mice with translational value to depressive symptomatology that can be alleviated by administration of antidepressant medications. Behavioral changes are accompanied by altered brain morphometry and imbalances in monoaminergic systems. In accordance, gene expression changes across brain tissues reveal altered neurotransmitter signaling and cluster in functional pathways associated with depression including ‘Adrenergic-, GPCR-, cAMP-, and CREB/CREM-signaling’. Integrative gene expression analysis specifically links changes in amygdaloid intracellular signaling activity to the behavioral treatment response in Brd1+/- mice. Conclusions: Collectively, our study highlights the importance of BRD1 as a modulator of affective pathology and adds to our understanding of the molecular mechanisms underlying affective disorders and their treatment response. mRNA profiles of right striatum, caudate putamen and anterior cingulate cortex of 8-11 weeks-old female wild type (WT) and Brd1+/- mice, either untreated or treated with antidepressants imipramine or fluoxetine, were generated by RNA-sequencing, using BGISEQ-500, in order to identify diffentially expressed genes between groups.