Risk-associated and pathway-based method to detect association with Alzheimer's disease Online publication date: Wed, 28-Mar-2018
by Jeffrey Mitchel; Laszlo Prokai; Youping Deng; Fan Zhang; Robert Barber
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 11, No. 1/2, 2018
Abstract: Genes do not function alone but through complex biological pathways in complex diseases such as Alzheimer's disease (AD). Unravelling these intricate pathways is essential to understanding biological mechanisms of the AD. Based on the integrated pathway analysis database (IPAD), we developed a pathway-based method to detect association with the AD. First, we performed risk associated allele analysis to determine if a major or minor allele is associated with risk. Then we performed pathway-disease association analysis to identify 133 AD-associated pathways. Lastly, we performed pathway-patient association analysis to investigate the patient's association and distribution among the 133 pathways. We found five AD-associated pathways that have the highest association with patients. We present a pathway-based method to detect AD-associated pathways from GWAS data. Our pathway-based analysis not only provides a technique to identify disease-associated pathways, but also help determine the pathway-patient association.
Online publication date: Wed, 28-Mar-2018
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