Activity-Dependent Changes in Gene Expression in Schizophrenia Human-Induced Pluripotent Stem Cell Neurons

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Schizophrenia candidate genes participate in common molecular pathways that are regulated by activity–dependent changes in neurons. One important next step is to further our understanding on the role of activity-dependent changes of gene expression in the etiopathogenesis of schizophrenia.


To examine whether neuronal activity-dependent changes of gene expression are dysregulated in schizophrenia.

Design, Setting, and Participants

Neurons differentiated from human-induced pluripotent stem cells derived from 4 individuals with schizophrenia and 4 unaffected control individuals were depolarized using potassium chloride. RNA was extracted followed by genome-wide profiling of the transcriptome. Neurons were planted on June 21, 2013, and harvested on August 2, 2013.

Main Outcomes and Measures

We performed differential expression analysis and gene coexpression analysis to identify activity-dependent or disease-specific changes of the transcriptome. Gene expression differences were assessed with linear models. Furthermore, we used gene set analyses to identify coexpressed modules that are enriched for schizophrenia risk genes.


We identified 1669 genes that were significantly different in schizophrenia-associated vs control human-induced pluripotent stem cell–derived neurons and 1199 genes that are altered in these cells in response to depolarization (linear models at false discovery rate ≤0.05). The effect of activity-dependent changes of gene expression in schizophrenia-associated neurons (59 significant genes at false discovery rate ≤0.05) was attenuated compared with control samples (594 significant genes at false discovery rate ≤0.05). Using gene coexpression analysis, we identified 2 modules (turquoise and brown) that were associated with diagnosis status and 2 modules (yellow and green) that were associated with depolarization at a false discovery rate of ≤0.05. For 3 of the 4 modules, we found enrichment with schizophrenia-associated variants: brown (χ2 = 20.68; P = .002), turquoise (χ2 = 12.95; P = .04), and yellow (χ2 = 15.34; P = .02).

Conclusions and Relevance

In this analysis, candidate genes clustered within gene networks that were associated with a blunted effect of activity-dependent changes of gene expression in schizophrenia-associated neurons. Overall, these findings link schizophrenia candidate genes with specific molecular functions in neurons, which could be used to examine underlying mechanisms and therapeutic interventions related to schizophrenia.

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