Abstract

Plenty of genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and blood pressure (BP). However, these SNPs only explain a small proportion of the heritability of two traits/diseases. Although high BP is a major risk factor for CAD, the genetic intercommunity between them remain largely unknown. To recognize novel loci associated with CAD and BP, a genetic-pleiotropy-informed conditional false discovery rate (cFDR) method was applied on two summary statistics of CAD and BP from existing GWASs. Stratified Q-Q and fold enrichment plots showed a high pleiotropic enrichment of SNPs associated with two traits. Adopting a cFDR of 0.05 as a threshold, 55 CAD-associated loci (25 variants being novel) and 47 BP loci (18 variants being novel) were identified, 25 of which were pleiotropic loci (13 variants being novel) for both traits. Among the 32 genes these 25 SNPs were annotated to, 20 genes were newly detected compared to previous GWASs. This study showed the cFDR approach could improve gene discovery by incorporating GWAS datasets of two related traits. These findings may provide novel understanding of etiology relationships between CAD and BP.

Details

Title
Improved detection of common variants in coronary artery disease and blood pressure using a pleiotropy cFDR method
Author
Xiang-Jie Mao 1 ; Zhang, Qiang 1 ; Xu, Fei 1 ; Gao, Pan 1 ; Sun, Nan 2 ; Wang, Bo 1 ; Qi-Xin, Tang 1 ; Yi-Bin, Hao 3 ; Chang-Qing, Sun 1 

 College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China 
 Department of Management Information Systems, Terry College of Business, University of Georgia, Athens, Georgia, USA 
 People’s Hospital of Zhengzhou, Zhengzhou, Henan, People’s Republic of China 
Pages
1-10
Publication year
2019
Publication date
Jul 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2259351853
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.