Home LiteratureArticle Details
PMID: 29942251 Published · epublish English Journal Article

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.

Frontiers in molecular neuroscience ·Vol. 11 ·2018-00-00 ·页码 192

Igolkina AA, Armoskus C, Newman JRB, Evgrafov OV, McIntyre LM, Nuzhdin SV, Samsonova MG

Abstract

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.

Keywords
gene network modeling neurodevelopmental disorders schizophrenia signaling pathways structural equation models
作者与单位
共 7 位作者,点击展开单位 / ORCID
Igolkina Anna A
Institute of Applied Mathematics and Mechanics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia.
Armoskus Chris
Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Newman Jeremy R B
Department of Molecular Genetics & Microbiology, Genetics Institute, University of Florida, Gainesville, FL, United States.
Evgrafov Oleg V
Department of Cell Biology, SUNY Downstate Medical Center, Brooklyn, NY, United States.
McIntyre Lauren M
Department of Molecular Genetics & Microbiology, Genetics Institute, University of Florida, Gainesville, FL, United States.
Nuzhdin Sergey V
Institute of Applied Mathematics and Mechanics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia. | Molecular and Computation Biology, University of Southern California, Los Angeles, CA, United States.
Samsonova Maria G
Institute of Applied Mathematics and Mechanics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia.
Article Info
Journal
Frontiers in molecular neuroscience
Abbr.
Front Mol Neurosci
ISSN
1662-5099
Published
2018-00-00
电子出版
2018-00-11
页码
192
Language
English
Country/Region
Switzerland
NLM ID
101477914
基金资助
NIGMS NIH HHS · R01 GM102227 · United States
NIMH NIH HHS · R01 MH086874 · United States
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com