Alzheimer's disease (AD), which is one of the most common age-associated neurodegenerative disorders, affects millions of people worldwide. Due to its polygenic nature, AD is believed to be caused not by defects in single genes, but by variations in a large number of genes and their complex interactions, which ultimately contribute to the broad spectrum of disease phenotypes. Extraction of insights and knowledge from microarray and network data will lead to a better understanding of complex diseases. The present study aimed to identify genes with differential topology and their further association with other biological processes that regulate causative factors for AD, ageing (AG) and other diseases. Our analysis revealed a common sharing of important biological processes and putative candidate genes among AD and AG. Some significant novel genes and other variants for various biological processes have been reported as being associated with AD, AG, and other diseases, and these could be implicated in biochemical events leading to AD from AG through pathways, interactions, and associations. Novel information for network motifs such as BiFan, MIM (multiple input module), and SIM (single input module) and their close variants has also been discovered and this implicit information will help to improve research into AD and AG. Ten major classes for TFs (transcription factors) have been identified in our data, where hundreds of TFBS patterns are being found associated with AD, and other disease. Structural and physico-chemical properties analysis for these TFBS classes revealed association of biological processes involved with other severe human disease. Nucleosomes and linkers positional information could provide insights into key cellular processes. Unique miRNA (micro RNA) targets were identified as another regulatory process for AD. The association of novel genes and variants of existing genes have also been explored for their interaction and association with other diseases that are either directly or indirectly implicated through AG and AD.
Keywords: Enrichment analysis; Mirna; Network motifs; Nucleosomes; TFBS.
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