Background: 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.
Objective: 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.
Method: 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.
Result: 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
Conclusion: Computationally predicted genes and miRs identified in our study might provide insight
into new epigenetic AD therapeutic targets.