Alzheimer's disease (AD) also called Alzheimer disease is a complex progressive neurodegenerative disorder of the brain and most common form of age-related cognitive impairment (Tiraboschi et al., 2004). The cause and progression of Alzheimer's disease are not yet well understood. However, the ongoing research indicates that the disease is associated with plaques and tangles in the brain (Dunckley et al., 2006). AD is characterized by two pathologic hallmark lesions that consist of extracellular plaques of amyloid-beta peptides and intracellular neurofibrillary tangles composed of hyperphosphorylated microtubular protein tau (Okuizumi and Tsuji, 2007) (Figure 1). Recent advances in molecular genetics have enabled the identification of the causative genes for Alzheimer's disease and the most common forms of AD are considered to be polygenic disorders (Blalock et al., 2005). AD poses a great challenge to patients, oncologists, and biologists due to polygenic disorders and the involvement of large number of genes and their complex interactions.

Since microarray technology allows massively parallel analysis of most genes expressed in a tissue it has become a popular gene expression screening tool in the molecular investigation of polygenic disease such as AD (Blalock et al., 2004; Kong et al., 2009; Pasinetti, 2001). Microarray technology today is rapidly uncovering patterns of genetic activity and showing insight into prediction of gene functions (Pan, 2006; Li et al., 2006; Tenenbaum et al., 2008), pathways (Manoli et al., 2006; Veerla and Hoglund, 2006) and transcription factor binding sites (TFBSs) (Park et al., 2002; Haverty et al., 2004). The challenges that lie here include systematically identifying the functions of all AD associated genes, and continuing the efforts to decipher their pathways and regulatory networks. This information will help to understand the mechanism of AD development and assist in the identification of effective therapeutic targets for disease control and eradication.

The transcription factor binding sites (TFBSs) discovered in the promoter regions of disease related genes provide further insights into the possible transcriptional regulation of the genes involved in AD and their connection to CVDs (cardiovascular diseases), stroke and diabetes (Tavazoie et al., 1999). Geneexpression microarrays have been analyszed using clustering algorithms that group genes and samples on the basis of expression profiles, and statistical methods that score genes on the basis of their relevance to various clinical attributes (Ray, 2008). Transcription factors act as critical molecular switches in promoting neuronal survival (Burton et al., 2002).

In this work, we performed a microarray based study of a dataset consists of 14 normal and 14 Alzheimer's disease samples. We first used microarray expression profiling to distinguish the broadest set of genes that showed differential expression levels across two disease types normal vs. AD. Second, we clustered the differentially expressed genes, based on their expression profiles, into sets of putatively co-regulated genes. Finally, we attempted to identify the transcription factors, as well as their corresponding binding sites, which regulate the observed expression differences of the genes in the differentially and co-expressed gene set. . As gene regulators are important targets to treat diseases, we have identified TFBSs ZEB1, MZF1 1-4, ZNF354C and SPIB that would have a high therapeutically value to treat Alzheimer's disease.

The results obtained through Significance Analysis of Microarrays (SAM) (Saeed et al., 2003) reveals that out of 25,577 genes in the microarray data set 240 genes were identified as differentially expressed genes between AD samples and controls at a false discovery rate of 0.1%. We then identified the groups of co-regulated genes based on the hypothesis that genes with strongly correlated mRNA expression profiles are more likely to have their promoter regions bound by a common transcription factor (Allocco et al., 2004). We used hierarchal clustering of differentially expressed genes and identified eight groups of co-expressed genes clusters. A figure showing the eight clusters of co-expressed genes is provided in Additional data file 1.

Next, we identified the conserved TFBSs among co-expressed genes clusters. We used Entrez-gene to define the transcription start sites (TSS) and determined overrepresented transcription factor binding sites in the promoter regions. Each clusters of gene set was analyzed for enrichment of TFBS using the oPOSSUM program (Ho Sui et al., 2007). Transcription factors ZEB1, MZF1 1-4, ZNF354C, ELF5 and SPIB were found to have their binding sites in most of the genes which are differentially expressed in AD. The enriched TFBS for co-expressed expressed genes in AD was illustrated in Table 1 and the corresponding binding sites from JASPAR (Sandelin et al., 2003) database was illustrated in Figure 3.

On further literature analysis of these common transcription factor binding sites we found that ZEB1, Zinc finger/ homeodomain serve as DNA binding domain with greater affinity for a subset of E box and E-box- like sequences (CACCTG). ZEB1/zfh-1 transcriptional repressor regulates muscle differentiation and expressed in central nervous system (Antonio and Douglas, 2000). A study by Schmalhofer et al., (2009) reveals the molecular interconnection of ZEB1 with E-cadherin, β- catenin, and WNT signaling in cancerogenesis. WNT signaling regulates dendrite morphogenesis. Dendritic pathology and decrease of dendritic spine density are prominent phenomena in early cases of AD. ZEB1, through WNT signaling would have a role in the dendritic degeneration in AD (Baloyannis, 2009). GATA-3 is essential for T-cell development and a recent study by Dontje et al. suggests that Spi-B TF is a key regulator of Dentritic cells development (Dontje et al., 2006). T-cell development is inhibited by Spi-B through induction of apoptosis in T-cell precursors without inhibiting the differentiation (Schotte et al., 2003). T cell population is a response to the presence of Ameloid β aggregates in AD.

Leucine zipper down-regulated in cancer (LDOC1), is a gene that encodes a leucine-zipper protein characteristic for earlyphase apoptotic events and reduced cell viability in human cell lines. Another transcription factor, MZF1, interacts with LDOC1 and enhances the activity of LDOC1 for inducing apoptosis (Inoue et al., 2005). MZF1 was found to play a key role in cell lines representing early stages of myeloid differentiation and derivation of ES cell lines involved in growth, differentiation, and apoptosis (Dong et al., 2008).

ETS transcription factors ELF5 is essential for developmental processes in the embryo and in the mammary gland during pregnancy (Oakes et al., 2006). ETS factors involving in early embryonic development ELF5 modulate the expression of a variety of genes involved in various cellular processes, including cell proliferation, differentiation and apoptosis (Jedlicka and Gutierrez-Hartmann, 2008).

The literature information clearly indicates that these common transcription factor binding sites (ZEB1, MZF1 1-4, ZNF354C, ELF5 and SPIB) are the regulator of Alzheimer's disease during apoptosis pathway and inducing cell death and apoptosis.

One of the challenges of computational biology is to identify genomic binding sites for transcription factors and the direct downstream targets they affect. Identification of such binding sites would allow the development of more accurate gene networks, interactions and an understanding of important biological pathways. As a starting point for that we described an analysis using public microarray experiments in AD. We identified groups of genes, or co-expressed modules, that undergo similar changes in expression and identified conserved TFBSs which are considered as the gene regulators for Alzheimer's disease. As gene regulators are important targets to treat diseases, the identified TFBSs ZEB1, MZF1 1-4, ZNF354C, ELF5 and SPIB would have a high therapeutically value to treat Alzheimer's disease.