Table_1_Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.CSV

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.

精神分裂症（Schizophrenia, SCZ）是病因未明的精神障碍。已有研究证据显示，神经发育异常是精神分裂症发病与进展的关键特征。为甄别精神分裂症中影响神经发育的生物学相关分子异常，本研究采用了源自嗅觉神经上皮的培养神经前体细胞（CNON cells）。本研究旨在验证如下假说：精神分裂症组与健康对照组个体之间的基因表达方差存在差异。在CNON细胞中，精神分裂症样本的基因表达方差显著高于健康对照样本。基因表达方差富集于5条分子通路：丝氨酸生物合成通路、磷脂酰肌醇3-激酶-蛋白激酶B（PI3K-Akt）通路、丝裂原活化蛋白激酶（MAPK）通路、神经营养因子（neurotrophin）通路以及黏着斑（focal adhesion）通路。基于上述5条通路中69个基因的基因表达作为预测因子，logistic回归模型可解释超过14%的疾病状态方差（C统计量=0.70）。本研究采用结构方程模型（Structural Equation Modeling, SEM）探究精神分裂症患者与健康对照者之间上述5条通路的结构差异。5条通路中有4条显示出基因间估计关联的差异：MAPK通路中KRAS与NF1、KRAS与SOS1之间的关联；丝氨酸生物合成通路中PSPH与SHMT2之间的关联；PI3K-Akt信号通路中AKT3与TSC2之间的关联；以及黏着斑通路中CRK与RAPGEF1之间的关联。本研究分析证实，基因表达方差是精神分裂症的重要特征，而结构方程模型是揭示特定基因间关联改变的有效方法，进而提示与疾病相关的基因调控异常。本研究在精神分裂症中表达方差升高的基因富集通路中，发现了改变的基因-基因相互作用。上述通路与基因位点既往已被证实与精神分裂症相关，这进一步支持了基因表达方差在精神分裂症病因学中发挥重要作用的假说。