Abstract

Background
Genomic variants identified by genome-wide association studies (GWAS) explain <20% of heritability of coronary artery disease (CAD), thus many risk variants remain missing for CAD. Identification of new variants may unravel new biological pathways and genetic mechanisms for CAD. To identify new variants associated with CAD, we developed a candidate pathway-based GWAS by integrating expression quantitative loci analysis and mining of GWAS data with variants in a candidate pathway.
Methods and Results
Mining of GWAS data was performed to analyze variants in 32 complement system genes for positive association with CAD. Functional variants in genes showing positive association were then identified by searching existing expression quantitative loci databases and validated by real-time reverse transcription polymerase chain reaction. A follow-up case–control design was then used to …

Date

2014

Authors

Chengqi Xu, Qin Yang, Hongbo Xiong, Longfei Wang, Jianping Cai, Fan Wang, Sisi Li, Jing Chen, Chuchu Wang, Dan Wang, Xin Xiong, Pengyun Wang, Yuanyuan Zhao, Xiaojing Wang, Yufeng Huang, Shanshan Chen, Dan Yin, Xiuchun Li, Ying Liu, Jinqiu Liu, Jingjing Wang, Hui Li, Tie Ke, Xiang Ren, Yanxia Wu, Gang Wu, Jing Wan, Rongfeng Zhang, Tangchun Wu, Junhan Wang, Yunlong Xia, Yanzong Yang, Xiang Cheng, Yuhua Liao, Qiuyun Chen, Yanhong Zhou, Qing He, Xin Tu, Qing K Wang

Journal

Circulation: Cardiovascular Genetics

Volume

7

Issue

6

Pages

887-894

Publisher

Lippincott Williams & Wilkins