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Screening potential biomarkers for prenatal diagnosis of trisomy 21
Running title: Screening biomarkers for Ts21 diagnosis
1. Total 13 screened DEGs were located on chromosome 21.
2. Only 6 DEGs located on chromosome 21 were included into PPI network.
3. SOD1, GART, DONSON may play roles in DS and serve as potential biomarkers.
4. ATP5O, CHAF1B and PSMG1 may play roles in DS and serve as potential biomarkers.
Purpose: We aimed to identify key genes located on chromosome 21 as potential biomarkers for prenatal diagnosis of trisomy 21 (Ts21).
Methods: The microarray data of GSE48051, including 10 cultivated amniocyte samples with Ts21 and 9 controls with normal euploid constitution, was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in cultivated amniocyte samples with Ts21 compared to normal controls were screened using limma package. Then we performed GO enrichment analysis using DAVID and chromosomal location of DEGs based on the information of the University of California Santa Cruz (UCSC) Genome Browser Database. Finally, protein-protein interaction (PPI) network analysis was performed using STRING.
Results: Total 155 DEGs in cultivated amniocyte samples with Ts21 were identified, including 89 up-regulated genes and 66 down-regulated ones. The over-represent GO terms of DEGs were mainly related with apoptosis, programmed cell death and cell death. Total 13 DEGs were located on chromosome 21, thereinto, only 6 DEGs were included into the PPI network, including superoxide dismutase 1 (SOD1), phosphoribosylglycinamide formyltransferase, phosphoribosylglycinamide synthetase, phosphoribosylaminoimidazole synthetase (GART), downstream neighbor of SON (DONSON), ATP synthase, H+ transporting, mitochondrial F1 complex, O subunit (ATP5O), chromatin assembly factor 1, subunit B (p60) (CHAF1B), and proteasome (prosome, macropain) assembly chaperone 1 (PSMG1).
Conclusions: Our results suggest that SOD1, GART, DONSON, ATP5O, CHAF1B and PSMG1 may play important roles in the pathogenesis of DS and may serve as potential biomarkers for prenatal diagnosis of Ts21.
Keywords: Down syndrome; differentially expressed genes; chromosomal location; protein-protein interaction network Introduction
Trisomy 21 (Ts21), also known as Down syndrome (DS), is unique among human diseases caused by trisomy of all or part of human chromosome 21 . It is typically associated witha number of abnormalities, including physical growthdelays, cardiac defects and mental retardation, and may increase the economic and social burden of both patients and the society . Prenatal screening and genetic diagnosis of Ts21 is currently confirmed as an effective means to prevent birth defects . However, these diagnostic procedures, such as conventional cytogenetic or DNA analyses for fetal genetic material, are invasive and are always associated with a considerable risk of fetal loss . Therefore, exploring noninvasive and effective prenatal diagnosis of Ts21 is urgent.
Recently, several genes on chromosome 21, including the amyloid precursor protein (APP), Down critical region 1 (DSCR1), one member of the Ets family of transcription factors (ETS2), and superoxide dismutase (SOD1), has been shown to promote the loss of premature neuronal and the development of dementia in patients with Ts21 . The astrocyte-den ved neurotrophic factor S100B is overexpressed in the brains of DS fetuses , and this overexpression increases progressively throughout life in patients with Ts21 . These chromosome 21 genes verified by previous studies may play a key role in the pathogenesis of DS. However, few chromosome 21 genes can serve as potential diagnostic biomarkers for Ts21. It is still a great challenging to identify potential biomarkers for prenatal diagnosis of this disease.
Various previously performed studies mainly focused on investigating transcriptional alterations in Ts21 or explaining the variability of DS phenotype . In contrast to previously performed studies, we downloaded microarray data GSE48051 in the current study and applied comprehensive bioinformatics approach to screen differentially expressed genes (DEGs) in cultivated amniocyte samples with Ts21 compared with controls with normal euploid constitution. In addition, chromosomal location of DEGs, functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed. The objectives of this study were to identify key genes located on chromosome 21 as potential biomarkers for prenatal diagnosis of Ts21.
Microarray data and preprocessing
One transcriptomic profile of GSE48051, including 10 cultivated amniocyte samples with Ts21 and 9 controls with normal euploid constitution, was downloaded from Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/) . This dataset was deposited by Volk et al.  and was based on the platform of GPL6480 Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (AgilentTechnologies,Santa Clara,CA,USA).
All the raw data was downloaded and the probe ID was transformed into gene symbol based on probe annotation files. Empty probe was removed and the mean value was calculated as the expression value of this gene if multiple probes corresponded to the same gene symbol. Log2transformation of all data was performed. Then all of the genes and arrays weremediancentered and normalized [11, 12].
Identification of DEGs
The DEGs in cultivated amniocyte samples with Ts21 compared with normal controls were identified using limma package (availableathttp://www.bioconductor.org/packages/release/bioc/html/limma.html) . The multiple testing correction was performed using Beniamini-Hochberg method and false discovery rate (FDR) was calculated . Fold change (FC) of the gene expression was also used for differential expression test. The DEGs with FDR < 0.05 and |log2 FC| > 1 were defined to be significant.
Functional enrichment analysis
Gene Ontology (GO, http://www.geneontology.org)  is a common approach for the biological unification of large-scale gene lists. For the screened DEGs, GO enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID, http://david.abcc.ncifcrf.gov/) [19, 20] online tool. The p-value < 0.05 was considered as thethreshold.
Chromosomal location of DEGs
The University of California Santa Cruz (UCSC) Genome Browser Database (http://genome.ucsc.edu) provides genomic sequence and a large collection of related annotation data forawide variety of organisms . According to annotation information in UCSC website, all the screened DEGs were aligned to thereference human genome 19 (hg19) for chromosomal location.
PPI network construction
Search Tool for the Retrieval of Interacting Genes (STRING, http://www.bork.embl-heidelberg.de/STRING/)  database provides the information of both experimental and predicted interactions between proteins via calculating their combined score. Based on the information of STRING database, PPI pairs with a combined score > 0.6 in the current study were considered significant. PPI network was then established and visualized using Cytoscape software .
Identification of DEGs
Using FDR< 0.05 and |log2 FC| > 1 as the cutoff value, total 155 DEGs in cultivated amniocyte samples with Ts21 compared with normal controls were identified, including 89 up-regulated genes and 66 down-regulated ones.
Hierarchical clustering analysis
As shown in Figure 1, hierarchical clustering method could effectively distinguish disease samples and controls, and the recognition capacity for samples reached 88.89%.
Functional enrichment analysis
We performed GO enrichment analysis for DEGs using DAVID online tool. The results showed that over-represent GO terms of DEGs were mainly related with apoptosis, programmed cell death, cell death, death, and defense response (Table 1).
Chromosomal location of DEGs
According to the annotation information of hg19 in UCSC database, all the screened DEGs were located on the corresponding chromosomes (Figure 2). Notably, the results showed that total 13 DEGs were located on chromosome 21.
PPI network analysis
Based on STRING database, we obtained total 170 PPI pairs with combined score > 0.6. As figure 3 showed that total 68 nodes were identified, including 39 up- and 29 down-regulated genes. Thereinto, only 6 DEGs in 13 ones located on chromosome 21 were included in the PPI network. They are as follows: superoxide dismutase 1 (SOD1), phosphoribosylglycinamide formyltransferase, phosphoribosylglycinamide synthetase, phosphoribosylaminoimidazole synthetase (GART), downstream neighbor of SON (DONSON), ATP synthase, H+ transporting, mitochondrial F1 complex, O subunit (ATP5O),chromatin assembly factor 1, subunit B (p60) (CHAF1B), and proteasome (prosome, macropain) assembly chaperone 1 (PSMG1).
Ts21 is one of the most common genetic cause of all malformation syndromes, with an estimated prevalence of 1/600 - 1/800 . Numerous studies have implicated that altered expression of particular genes on chromosome 21 are responsible for the development of Ts21 . In the current study, comprehensive bioinformatics approach was performed to screen DEGs in cultivated amniocyte samples with Ts21 as potential biomarkers for prenatal diagnosis of Ts21. The results of our analysis showed that SOD1, GART, DONSON, ATP5O, CHAF1B and PSMG1 were differentially expressed and located on chromosome 21.
SOD1 gene is localized to chromosome 21q22.1 and is overexpressed in brains of adult patients with DS (Ts21) . SOD1 catalyzes the dismutation of superoxide anions to produce hydrogen peroxide, which may increase the production of active oxygen species and lead to oxidative damage in patients with Ts21 [27, 28]. Oxidativestress plays an important role in the pathogenesis of Ts21 and high levels of SOD1 in patients with Ts21 may be as a response to theoxidativestress . Therefore, increased SOD1 levels may reflect the overexpression by thetrisomicstate and responsible for the development of Ts21, thus SOD1 may function as a potential biomarker for the risk prediction of oxidative damage in patients with Ts21.
GART gene is localized to chromosome 21q22.11 and its expression variation has been confirmed to be associated with disease phenotypes in DS . GART over-expression is harmful to DNA synthesis and repair and may be relevant to the etiology of speciï¬c Ts21 phenotype . Moreover, GART may contribute via its strong over-expression to fetal cardiac defects in DS . Hence, GART may play a key role in the progression of DS and have impact on Ts21 phenotype.
DONSON lies downstream of the SON gene and spans 10 kb on chromosome 21 . DONSON is shown to be significantly over-expressed in lymphoblastoid cell lines from individuals with DS [33, 34]. Additionally, DONSON gene in the trisomic region of Ts1Cje is over-expressed in a dosage-dependent manner and is involved in the pathogenesis of DS . Although the function of DONSON gene is unknown, we speculate that altered expression of DONSON may be as a potential biomarker for risk prediction of DS.
ATP5O is a subunit of ATP synthase and is involved in mitochondrial function . ATP5O may play a role in reactive oxygen species metabolism and mitochondrial energy generation . Moreover, mitochondrial dysfunction is strongly linked with DS and Alzheimer’s disease in several studies [38, 39]. Therefore, we speculate that ATP5O may be associated with mitochondrial dysfunction and could be an attractive biomarker for DS.
CHAF1B is chromatin assembly factor involved in chromatin structure . CHAF1B is shown to be 1.5-fold overexpressed in almost all tissues analyzed Ts65Dn mice and may be as a key player for DS progression . Furthermore, Malinge et al. found evidence that the CHAF1B gene could promote DS-associated myeloid leukemogenesis . Thus, our results indicate that CHAF1B may be a key player involved in the pathogenesis of DS.
PSMG1 is involved in thyroid regulation, and resistance to thyroid hormone may be associated with DS . A previously reported meta-analysis showed that PSMG1 was one of the top 30 DS trisomic genes with direct dosage effects in DS patient tissues, cell lines and mouse models . Moreover, functional transcriptome analysis performed by Ling et al. also demonstrated that PSMG1 was differentially expressed in the postnatal brain of the Ts1Cje mouse model for DS . Our analyses are also in agreement with previous findings and suggest that PSMG1 may play an important role in the development of DS and its abnormal expression may be served as a biomarker for DS.
In summary, our results suggest that SOD1, GART, DONSON, ATP5O, CHAF1B and PSMG1 may play important roles in the pathogenesis of DS and may be potential biomarkers for prenatal diagnosis of Ts21. The present findings supply implications for future research and provide us a broader perspective for further clinical diagnosis and molecular target therapy. However, no experiments were performed in the current study, further studies are warranted to validate our observation.