bioRxiv preprint doi: https://doi.org/10.1101/482844; this version posted November 29, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Network-based identification of genetic factors in Ageing, lifestyle and Type 2 Diabetes that Influence in the progression of Alzheimer’s disease 1st Utpala Nanda Chowdhury 2nd Md. Babul Islam Department of Computer Science and Engineering Department of Applied Physics and Electronic Engineering University of Rajshahi University of Rajshahi Rajshahi, Bangladesh Rajshahi, Bangladesh
[email protected] [email protected] 3rd Shamim Ahmad 5th Mohammad Ali Moni Department of Computer Science and Engineering Discipline of Biomedical Science, Faculty of Medicine and Health University of Rajshahi The University of Sydney Rajshahi, Bangladesh NSW, Australia shamim
[email protected] [email protected] Abstract—Alzheimer’s disease (AD) is an incurable disease, I. INTRODUCTION and the causative risk factors, especially the modifiable ones, are still poorly understood which impedes the effective prevention Alzheimer’s disease (AD) is the most common form of and remedy strategies. We proposed a network-based quanti- tative framework to reveal the complex relationship of various dementia characterized by gradual degeneration in memory, biasing genetic factors for the AD. We analyzed gene expression thinking, language, and learning capacity [1]. Initial signs microarray data from the AD, ageing, severe alcohol consump- begin with the inability of forming recent memories, but tion, type II diabetes, high body fat, high dietary fat, obesity, di- inevitably affect all cognitive functions resulting in complete etary red meat, sedentary lifestyle, smoking, and control datasets.