Insight into the Epigenetics of Alzheimer's Disease: A Computational Study from Human Interactome

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease throughout the world. Most of the clinical symptoms of AD appear at a very later stage, therefore, the identification of disease markers is essential which can help proper detection of AD at an earlier stage and slow down its progression. Studies have implicated that epigenetic biomarkers, such as DNA methylation, histone modification and non coding RNA mediated regulation serve crucial roles in several disease progression including AD.

The aim of our study was to identify the topologically significant AD-related proteins from experimentally validated human protein-protein interaction database, HPRD (interactome) and find out novel epigenetic biomarkers.

In this computational work, we constructed AD specific diseasome from AD genelist and interactome. Using this diseasome we screened the interactome with the help of novel parameters namely degree band and similarity index and identified AD related proteins. Regulatory network involving AD related proteins, not previously known to be associated with AD was constructed. Several network motifs and epigenetic modification patterns of regulators of these motifs were studied.

Our study identified computationally predicted 22 epigenetic genes and 11 epigenetic miRs, not previously known to be associated with AD, from the network motifs. Most of these genes and miRs show brain specific expression. Further study on the epigenetic modification patterns of these regulators regarding histone modification, CpG island and lncRNAs strengthened their association in AD.

Computationally predicted genes and miRs identified in our study might provide insight into new epigenetic AD therapeutic targets.