GSE63734
Next Generation Sequencing Facilitates Comparisons of Control and Schizophrenia-Patient derived hiPSC-derived neurons
Cell-based models of many neurological and psychiatric diseases, established by reprogramming patient somatic cells into human induced pluripotent stem cells (hiPSCs), have now been reported.  While numerous reports have demonstrated that neuronal cells differentiated from hiPSCs are electrophysiologically active mature neurons, the “age” of these cells relative to cells in the human brain remains unresolved.  Comparisons of gene expression profiles of hiPSC-derived neural progenitor cells (NPCs) and neurons to the Allen BrainSpan Atlas indicate that hiPSC neural cells most resemble first trimester neural tissue.  Consequently, we posit that hiPSC-derived neural cells may most accurately be used to model the early developmental defects that contribute to disease predisposition rather than the late features of the disease. Though the characteristic symptoms of schizophrenia SZ generally appear late in adolescence, it is now thought to be a neurodevelopmental condition, often predated by a prodromal period that can appear in early childhood. Postmortem studies of SZ brain tissue typically describe defects in mature neurons, such as reduced neuronal size and spine density in the prefrontal cortex and hippocampus. We directly reprogrammed fibroblasts from SZ patients into hiPSCs and subsequently differentiated these disorder-specific hiPSCs into forebrain neurons.  SZ hiPSC differentiated into forebrain neurons have altered expression of a number of synaptic genes. Methods: We compared global transcription of forebrain neurons from six control and four SZ patients by RNAseq. Results:  Multi-dimensional scaling (MDS) resolved most SZ and control hiPSC neuron samples; 107 genes were significantly differentially expressed (FDR<0.01) Overall design: 1-2 independent differentiations (biological replicates) for each of four control and four schizophrenia patients were analyzed; samples were generated in parallel to neuron RNAseq data.