Joint Effects of Genetic Variants in Multiple Loci on the Risk of Coronary Artery Disease in Chinese Han Subjects

Xiaofei Lv; Yuan Zhang; Shaoqi Rao; Jian Qiu; Min Wang; Xiaoqin Luo; Xiaoyu Zuo; Dongfang Su; Xiang Feng; Yan Yang; Ping Ouyang; Yibing Chen; Xinrui Li; Yunjun Xiao; Wenhua Ling

doi:10.1253/circj.CJ-12-0156

Molecular Cardiology

Joint Effects of Genetic Variants in Multiple Loci on the Risk of Coronary Artery Disease in Chinese Han Subjects

Xiaofei Lv, Yuan Zhang, Shaoqi Rao, Jian Qiu, Min Wang, Xiaoqin Luo, Xiaoyu Zuo, Dongfang Su, Xiang Feng, Yan Yang, Ping Ouyang, Yibing Chen, Xinrui Li, Yunjun Xiao, Wenhua Ling

Author information

Xiaofei Lv
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Yuan Zhang
Department of Cardiology, Guangzhou Military Region General Hospital
Shaoqi Rao
Institute of Medical Systems Biology, Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College
Jian Qiu
Department of Cardiology, Guangzhou Military Region General Hospital
Min Wang
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Xiaoqin Luo
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Xiaoyu Zuo
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University [Northern Campus]
Dongfang Su
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Xiang Feng
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Yan Yang
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Ping Ouyang
Institute of Medical Systems Biology, Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College
Yibing Chen
Department of Experimental Research and State Key Laboratory of Oncology in Southern China, Sun Yat-Sen University Cancer Center
Xinrui Li
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Yunjun Xiao
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]
Wenhua Ling
Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University [Northern Campus]

Keywords: Coronary artery disease, Genetic risk score, Genetic variants, Joint effect

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Supplementary material

2012 Volume 76 Issue 8 Pages 1987-1992

DOI https://doi.org/10.1253/circj.CJ-12-0156

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Abstract

Background: The aim of the present study was to explore risk variants for coronary artery disease (CAD) and to evaluate their joint effects (quantified by genetic risk score; GRS) on the discrimination of CAD in a Chinese Han sample. Methods and Results: An association analysis of 91 single nucleotide polymorphisms (SNPs) with CAD risk was undertaken in 1,007 CAD patients and 889 healthy controls. Two GRSs, counted GRS (cGRS) and weighted GRS (wGRS), were calculated using the significant SNPs, and their discriminant power for CAD was assessed using receiver-operating characteristic (ROC) curve analysis. Eight SNPs (rs11206510, rs10118757, rs2383206, rs501120, rs2075292, rs174547, rs173539, and rs255052) were nominally significantly associated with CAD (P<0.05), and 5 of them were newly reported. The GRSs derived from the 8 SNPs improved the discrimination of CAD compared to that using 4 conventional risk factors (P=0.002 for cGRS and P=0.009 for wGRS). After 10-fold cross-validation 100 times, the average areas under the curve were 0.668 (95% confidence interval [CI]: 0.667-0.669), 0.686 (95% CI: 0.685-0.687) and 0.690 (95% CI: 0.689-0.691) for models with conventional risk factors only, conventional risk factors plus cGRS, and conventional risk factors plus wGRS, respectively. Conclusions: A multigenic GRS, generated by combining multiple gene variants, can improve discrimination of CAD, thereby confirming the joint effects of these gene variants on CAD in this Chinese Han population. (Circ J 2012; 76: 1987–1992)

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