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.
RCT Entities:
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.
Authors: Andrea de la Garza Puentes; Rosa Montes Goyanes; Aida Maribel Chisaguano Tonato; Francisco José Torres-Espínola; Miriam Arias García; Leonor de Almeida; María Bonilla Aguirre; Marcela Guerendiain; Ana Isabel Castellote Bargalló; Maite Segura Moreno; Luz García-Valdés; Cristina Campoy; M Carmen Lopez-Sabater Journal: PLoS One Date: 2017-06-09 Impact factor: 3.240
Authors: Rasheed K Ibdah; Laith N Al-Eitan; Nasr N Alrabadi; Ayah Y Almasri; Adan H Alnaamneh; Rame H Khasawneh; Mansour A Alghamdi Journal: Int J Gen Med Date: 2021-01-14