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International Journal of Alzheimer’s Disease
Volume 2011 (2011), Article ID 154325, 13 pages
Research Article

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

1Institute of Developmental Genetics, Helmholtz Centre Munich, German Research Centre for Environmental Health (GmbH), Technical University Munich, Ingolstädter Landstraße 1, Munich 85764, Neuherberg, Germany
2DZNE, German Center for Neurodegenerative Diseases, Schillerstraße 44, 80336 Munich, Germany
3Institute of Bioinformatics and Systems Biology, Helmholtz Centre Munich, German Research Centre for Environmental Health (GmbH), Ingolstädter Landstraße 1, Munich 85764, Neuherberg, Germany
4Clinical Cooperation Group Molecular Neurogenetics, Max Planck Institute of Psychiatry, Kraepelinstraße, 2-10, 80804 Munich, Germany

Received 21 December 2010; Accepted 15 February 2011

Academic Editor: Jeff Kuret

Copyright © 2011 Regina Augustin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.