EXPERIMENTAL AND THERAPEUTIC MEDICINE 12: 1503-1508, 2016 Co-expression network analysis of Down's syndrome based on microarray data JIANPING ZHAO1*, ZHENGGUO ZHANG2*, SHUMIN REN3, YANAN ZONG3 and XIANGDONG KONG3 1Clinical Laboratory, Women and Infants Hospital of Zhengzhou, Zhengzhou, Henan 450012; 2Clinical Laboratory, Henan Provincial Hospital of Traditional Chinese Medicine, Zhengzhou, Henan 450002; 3Center of Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, P.R. China Received February 28, 2015; Accepted April 11, 2016 DOI: 10.3892/etm.2016.3462 Abstract. Down's syndrome (DS) is a type of chromosome significant differential modules were significantly enriched in disease. The present study aimed to explore the underlying 5 functions, including the endoplasmic reticulum (P=0.018) molecular mechanisms of DS. GSE5390 microarray data and regulation of apoptosis (P=0.061). The identified DEGs, downloaded from the gene expression omnibus database was in particular the 12 DEGs in the significant differential used to identify differentially expressed genes (DEGs) in DS. modules, such as B-cell lymphoma 2-associated transcrip- Pathway enrichment analysis of the DEGs was performed, tion factor 1, heat shock protein 90 kDa beta member 1, UBX followed by co‑expression network construction. Significant domain-containing protein 2 and transmembrane protein 50B, differential modules were mined by mutual information, may serve important roles in the pathogenesis of DS. followed by functional analysis. The accuracy of sample classification for the significant differential modules of DEGs Introduction was evaluated by leave-one-out cross-validation. A total of 997 DEGs, including 638 upregulated and 359 downregulated Down's syndrome (DS), also known as trisomy 21, is a genetic genes, were identified. Upregulated DEGs were enriched in disorder caused by trisomy of part of, or all of, chromosome 21, 15 pathways, such as cell adhesion molecules, whereas down- and is associated with significant intellectual disability, phys- regulated DEGs were enriched in maturity onset diabetes of ical growth delays and slanted eyes (1,2). DS may cause other the young. Three significant differential modules with the complications, such as autism, coeliac disease, hypothyroidism highest discriminative scores (mutual information>0.35) and leukemia (3-5). Over the last several decades, numerous were selected from a co-expression network. The classifica- genes on trisomy 21 have been suggested to be associated with tion accuracy of GSE16677 expression profile samples was DS (6). 54.55% and 72.73% when characterized by 12 DEGs and Modern genetic pathology states the hypothesis that 3 significant differential modules, respectively. Genes in phenotypes of DS are determined by an extra copy of one or several genes, such as oligodendrocyte transcription factor 1 present on human chromosome 21 (Hsa21) (7). A previous study demonstrated that sorting nexin family member 27, which is suppressed by a bioactive substance Correspondence to: Mr. Xiangdong Kong, Center of Prenatal Diagnosis, The First Affiliated Hospital of Zhengzhou University, encoded on Hsa21, is upregulated in the brains of DS 1 Jiangshe Donglu, Zhengzhou, Henan 450052, P.R. China mice (8). The DS critical region (DSCR) is composed of E-mail: [email protected] 6 genes, including v-ets erythroblastosis virus E26 onco- gene homolog 2 (ETS2) and ETS-related gene (ERG), which *Contributed equally encode transcription factors (9). ERG and ETS2 belong to the E26 transformation‑specific family, which contains key regula- Abbreviations: APP, amyloid precursor protein; DAVID, database tors of embryonic development (10). Numerous sensitive genes for annotation, visualization and integrated discovery; such as ubiquitin specific peptidase 16, which are associated DGEs, differentially expressed genes; DS, Down's syndrome; with the reduced ubiquitination of cyclin-dependent kinase DSCR, Down's syndrome critical region; EST, erythroblast inhibitor 2A and expedited senescence in Ts65Dn fibroblasts, transformation-specific; GEO, gene expression omnibus; have been confirmed to be associated with DS (11,12). OLIG1, oligodendrocyte transcription factor 1; SAM, significant analysis of microarray; SVMs, support vector machines The identification of sensitive genes on Hsa21 has become the focus of investigations with the aim of elaborating suit- Key words: Down's syndrome, differentially expressed genes, able therapeutic strategies for DS, and global gene expression significant differential module, classification accuracy, co-expressed profiling techniques have been widely used to analyze the network molecular mechanisms underlying trisomy 21, as the expression levels of trisomic genes and those in the wider genome can be assessed (13). The majority of DS studies have been performed 1504 ZHAO et al: CO-EXPRESSION NETWORK ANALYSIS OF DOWN'S SYNDROME in animal models, such as the Ts65Dn mouse model of DS, analytical tools for extracting biological meaning from large which can be used to analyze the association between hippo- lists of genes (25,26), and was used for pathway enrichment campal pathways and cognitive dysfunction (14-16). Various analysis of upregulated and downregulated DEGs in the samples, such as fibroblasts, whole blood, T cells and placenta, current study. have been used to investigate the pathogenesis of DS (17-20). The samples used in the present study are derived from the Co‑expressed network construction. Gene co-expression brain tissue samples of patients with DS. Lockstone et al (21) network analysis is a fusion product of microarray profile screened differentially expressed genes (DEGs) in DS and techniques and network theory, that offers an intuitive concept performed functional analysis, and investigated significant for illustrating the association between two genes (27). The differential modules from a co-expressed network (21). gene expression data set GSE5390 was applied to build a In the present study, GSE5390 and GSE16677 were down- co-expressed network. Cytoscape is an open software platform loaded from the Gene Expression Omnibus (GEO) database, for visualizing complex networks and integrating these with DEGs were screened for pathway enrichment analysis, then any type of attributed data (28). The Pearson correlation coef- a co-expressed network was constructed and screened for ficient is a popular coefficient for evaluating the dependence significant differential modules. In addition, the classification of two variables (29) and, in the present study, Pearson's coef- accuracy of GSE16677 expression profile samples were evalu- ficient analysis was performed using the Perl script program ated, characterized by the value of average expressed DEGs (version 5.22.1; https://www.perl.org/get.html). R>0.9 was and all DEGs in significant differential modules. Finally, func- chosen as the criterion for selecting co-expressed genes. The tional enrichment analysis of DEGs in significant differential co-expression network was visualized using Cytoscape soft- modules was performed. ware (version 2.8; http://www.cytoscape.org/). Materials and methods Analysis of differentially co‑expressed gene modules. GraphWeb (http://biit.cs.ut.ee/graphweb/) is a public web Microarray data. The transcription profiles of GSE5390 and server used to mine heterogeneous biological networks for GSE16677 were acquired from the GEO database (http://www. significant function gene modules (30). The hidden Markov ncbi.nlm.nih.gov/geo/) (22,23). The platform names were model (HMM) of GraphWeb can be used for modeling by GPL96 Affymetrix Human Genome U133A Array and defining and observing the joint probability of sequences and GPL570 Affymetrix Human Genome U133 plus 2.0 Array, label sequences (31). In the present study, HMM was used for respectively. A total of 15 samples from GSE5390 were studied, mining network modules. Mutual information (MI) between including 8 normal samples and 7 DS samples of human adult the average expression value of modules and sample labels was brain tissue (dorsolateral prefrontal cortex) from healthy calculated according to the following formula (32): controls and individuals with DS (23). A total of 11 samples from GSE16677 were studied, including 5 normal samples and 6 DS samples of megakaryocytic leukemia blasts from patients with DS-acute megakaryoblastic leukemia (AMKL) or French-American-British M7 leukemia, and patients with In this formula, a' is the discretization average expres- non-DS-AMKL. The raw data were downloaded for further sion value; c is the corresponding vector of the sample analysis. The present study was approved by the Ethics label. To derive a' from a, activity levels are discretized into Committee of the First Affiliated Hospital of Zhengzhou [log2 (number of samples) + 1] values (33). Differentially University (Zhengzhou, China) and performed in accordance co-expressed gene modules were screened with the threshold with ethical standards (22,23). of discriminative score (defined as MI)> 0.35. Then, functional enrichment analysis of differentially expressed genes in the DEG analysis. Gene expression data from GSE5390 differentially co-expressed gene modules was performed by were processed through background correction, quantile DAV I D. P<0.1 was used as the cut-off criterion. normalization and probe summarization using the robust multi-array average algorithm in the oligo software package Assessment of classification