Exon-variant interplay and multi-modal evidence identify endocrine dysregulation in severe psychiatric disorders impacting excitatory neurons - Worf, Karolina; Matosin, Natalie; Gerstner, Nathalie; Fröhlich, Anna S.; Koller, Anna C.; Degenhardt, Franziska; Thiele, Holger; Rietschel, Marcella; Udawela, Madhara; Scarr, Elizabeth; Dean, Brian; Theis, Fabian J.; et al. (Translational Psychiatry, 2025)
Bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia share genetic architecture, yet their molecular mechanisms remain elusive. Both common and rare genetic variants contribute to neural dysfunction, impacting cognition and behavior. This study investigates the molecular effects of genetic variants on human cortical single-cell types using a single-exon analysis approach. Integrating exon-level eQTLs (common variants influencing exon expression) and joint exon eQT-Scores (combining polygenic risk scores with exon-level gene expression) from a postmortem psychiatric cohort (BD = 15, MDD = 24, schizophrenia = 68, controls = 62) with schizophrenia-focused rare variant data from the SCHEMA consortium, we identified 110 core genes enriched in pathways including circadian entrainment (FDR = 0.02), cortisol synthesis and secretion (FDR = 0.026), and dopaminergic synapse (FDR = 0.038). Additional enriched pathways included hormone signaling (FDRs < 0.0298, including insulin, GnRH, aldosterone, and growth hormone pathways) and, notably, adrenergic signaling in cardiomyocytes (FDR = 0.0028). These pathways highlight shared molecular mechanisms in the three disorders. Single-nuclei RNA sequencing data from three cortical regions revealed that these core set genes are predominantly expressed in excitatory neuron layers 2-6 of the dorsolateral prefrontal cortex, linking molecular changes to cell types involved in cognitive dysfunction. Our results demonstrate the power of integrating multimodal genetic and transcriptomic data at the exon level. This approach moves beyond symptom-based diagnoses toward molecular classifications, identifying potential therapeutic targets for psychiatric disorders.
Gesehen am 01.07.2025