M97 - TRANSCRIPTIONAL SIGNATURES OF CHILDHOOD ONSET SCHIZOPHRENIA IN HIPSC-DERIVED NPCS AND NEURONS ARE CONCORDANT WITH SIGNATURES FROM POST MORTEM ADULT BRAINS

Abstract

Background Large-scale Genome Wide Association Studies (GWAS) revealed that Schizophrenia (SZ) risk reflects both rare and common variants. Whereas highly penetrant rare variants have proven well-suited to human induced pluripotent stem cell (hiPSC)-based models, the power of hiPSC-based studies to resolve the much smaller effects of common variants within the size of cohorts that can be realistically assembled remains uncertain. Childhood-Onset-SZ (COS) patients have both a higher rate of rare SZ-associated Copy Number Variations (CNVs), and also stronger common SZ polygenic risk scores. Methods We developed a case/control hiPSC cohort (12 individuals with COS and 10 controls) with which to conduct a comprehensive evaluation of global gene expression in hiPSC-derived neural progenitor cells (NPCs) and neurons. Results Although we identified many sources of variation across our 94 RNAseq samples, this was partially addressed by establishing a rigorous series of bioinformatic practices to reduce and assess the variance inherent in this approach. We report that the donor-specific signal is enriched for post- mortem brain Expression Quantitative Trait Loci (eQTLs), but also that there is a significant correlation between the case/control differential expression observed in our hiPSC-derived COS neurons and the CommonMind Consortium post-mortem study. While the issue of small sample size is shared between post-mortem and hiPSC-based studies, and may be exacerbated in hiPSC-based experiments through the variability that arises as a result of the reprogramming and neural differentiation processes, we find that the common variation effects predicted in GWAS and detected in much larger post-mortem analyses are reflected in hiPSC-neurons. Discussion We predict a growing convergence of common variation findings between hiPSC and post-mortem studies as both approaches expand to larger cohort sizes.