English

Prediction of Alzheimer's disease-associated genes by integration of GWAS summary data and expression data

Applications 2018-11-14 v1 Genomics

Abstract

Alzheimer's disease is the most common cause of dementia. It is the fifth-leading cause of death among elderly people. With high genetic heritability (79%), finding disease causal genes is a crucial step in find treatment for AD. Following the International Genomics of Alzheimer's Project (IGAP), many disease-associated genes have been identified; however, we don't have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression level data by using TWAS method and identified 15 disease causal genes under strict multiple testing (alpha<0.05), 4 genes are newly identified; identified additional 29 potential disease causal genes under false discovery rate(alpha < 0.05), 21 of them are newly identified. Many genes we identified are also associated with some autoimmune disorder.

Keywords

Cite

@article{arxiv.1811.04987,
  title  = {Prediction of Alzheimer's disease-associated genes by integration of GWAS summary data and expression data},
  author = {Sicheng Hao and Rui Wang and Yu Zhang and Hui Zhan},
  journal= {arXiv preprint arXiv:1811.04987},
  year   = {2018}
}

Comments

11 pages, 3 figures