AUTHOR=Hu Yang , Zhao Tianyi , Zang Tianyi , Zhang Ying , Cheng Liang 

TITLE=Identification of Alzheimer's Disease-Related Genes Based on Data Integration Method

JOURNAL=Frontiers in Genetics

VOLUME=Volume 9 - 2018

YEAR=2019

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2018.00703

DOI=10.3389/fgene.2018.00703

ISSN=1664-8021

ABSTRACT=Alzheimer disease （AD） is the fourth major cause of death in the elderly following cancer, heart disease and cere-brovascular disease. Finding candidate causal genes can help human design Gene targeted drugs and effectively reduce the risk of the disease. Complex diseases such as AD are usual-ly caused by multiple genes. By Genome-wide association study (GWAS), human has identified the pote dntial genetic variants for most diseases. However, because of the exist-ence of linkage disequilibrium (LD), it is difficult to identi-fy the causative mutations that directly cause diseases. In this study, we combined expression quantitative trait locus (eQTL) studies with GWAS to find the genes causing Alz-heimer disease from a comprehensive level. The method used in this paper is Summary Mendelian randomization (SMR) which is a novel method to integrate summary data. Two GWAS studies and five eQTL studies are used in this paper. We find out several candidate SNPs which have strong relationship with AD and most of these SNPs over-lap in different data sets, which proves that the reliability is relatively high.