Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer′s Disease‐Related Genes by In Silico Promoter Analysis and Microarrays

Abstract

The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases.

Microglial Malfunction: The Third Rail in the Development of Alzheimer's Disease

“…Tau overexpression in mice resulted in higher expression of inflammatory genes (Wes et al, 2014). Clustering genes from LOAD patients and mouse models of AD showed a shared over-representation of inflammatory pathways (Augustin et al, 2011). Zhang et al used Bayesian inference to identify regulatory genes upstream of networks significantly changed in AD (Zhang et al, 2013).…”

Unfolded protein response signaling by transcription factor XBP‐1 regulates ADAM10 and is affected in Alzheimer's disease

“…Therefore, elucidating endogenous factors that balance expression of either protease (ADAM10 or BACE-1) might lead to a deeper understanding of AD pathogenesis and disclose new therapeutic approaches. Common regulatory networks for AD genes have been identified by a combination of in silico promoter and multivariate analysis (15) and outlined 2 significant modules composed of 3 transcription factor (TF) families: CCCTC binding factor (CTCF), GC-box factors SP1/GC (SP1F), and EGR/ nerve growth factor-induced protein C and related factors (EGRF)/zinc-binding protein factors (ZBPF; ref. 15).…”

Nearest hyperplane distance neighbor clustering algorithm applied to gene co-expression analysis in Alzheimer's disease

“…In addition, since mitochondria plays a central role in neurodegenerative disease [20], its dysfunction due to damage of mtDNA might link KCTD14 to AD. NUCKS1 was proposed as one of the most likely candidates to be related in AD pathogenesis for two reasons [21]. First, this gene is strongly associated with Parkinson’s disease [22] and Parkinson’s disease has been linked to AD [23].…”

“…First, this gene is strongly associated with Parkinson’s disease [22] and Parkinson’s disease has been linked to AD [23]. Second, as it is indicated by Agustin et al [21], NUCKS1 may play a role in cell proliferation [24]. Proliferation of neural progenitor cells is reduced in mouse AD model due to the mutated form of the amyloid precursor protein [21].…”

“…Second, as it is indicated by Agustin et al [21], NUCKS1 may play a role in cell proliferation [24]. Proliferation of neural progenitor cells is reduced in mouse AD model due to the mutated form of the amyloid precursor protein [21]. The third gene clustered in the AD group was the RREB1 gene.…”