Roussos Panos, Guennewig Boris, Kaczorowski Dominik C, Barry Guy, Brennand Kristen J
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York2Institute for Multiscale Biology, Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York3Mental Illness Research, Education, and Clinical Center, James J. Peters VA Medical Center, Bronx, New York.
St Vincent's Clinical School and School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, New South Wales, Australia5Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
JAMA Psychiatry. 2016 Nov 1;73(11):1180-1188. doi: 10.1001/jamapsychiatry.2016.2575.
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.
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).
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.
精神分裂症候选基因参与由神经元活动依赖性变化所调控的常见分子途径。重要的下一步是进一步了解基因表达的活动依赖性变化在精神分裂症病因学中的作用。
研究精神分裂症中基因表达的神经元活动依赖性变化是否失调。
设计、地点和参与者:从4名精神分裂症患者和4名未受影响的对照个体的人诱导多能干细胞分化而来的神经元,用氯化钾进行去极化处理。提取RNA,随后进行全基因组转录组分析。神经元于2013年6月21日接种,2013年8月2日收获。
我们进行了差异表达分析和基因共表达分析,以识别转录组的活动依赖性或疾病特异性变化。用线性模型评估基因表达差异。此外,我们使用基因集分析来识别富含精神分裂症风险基因的共表达模块。
我们鉴定出1669个在精神分裂症相关的与对照的人诱导多能干细胞衍生神经元中有显著差异的基因,以及1199个在这些细胞中因去极化而发生改变的基因(错误发现率≤0.05的线性模型)。与对照样本(错误发现率≤0.05时有594个显著基因)相比,精神分裂症相关神经元中基因表达的活动依赖性变化的影响(错误发现率≤0.05时有59个显著基因)减弱。使用基因共表达分析,我们鉴定出2个与诊断状态相关的模块(绿松石色和棕色)以及2个与去极化相关的模块(黄色和绿色),错误发现率≤0.05。对于4个模块中的3个,我们发现富含精神分裂症相关变体:棕色(χ2 = 20.68;P = 0.002)、绿松石色(χ2 = 12.95;P = 0.04)和黄色(χ2 = 15.34;P = 0.02)。
在本分析中,候选基因聚集在与精神分裂症相关神经元中基因表达的活动依赖性变化的钝化效应相关的基因网络内。总体而言,这些发现将精神分裂症候选基因与神经元中的特定分子功能联系起来,可用于研究与精神分裂症相关的潜在机制和治疗干预措施。