Bu-Chun Zhang1, Wei-Ming Li, Ya-Wei Xu. 1. Department of Cardiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301Yanchang Road, Shanghai, China.
Abstract
OBJECTIVE: Variants of adiponectin gene have been reported to be associated with coronary heart disease (CHD), but the available data on this relationship are inconsistent. A meta-analysis was performed to quantitatively analyse the association of adiponectin gene polymorphisms with coronary artery disease using previous case-control studies in Chinese Han populations. METHODS: Several electronic databases were searched for relevant articles up to January 2011. After data collection and gene loci selection, a meta-analysis was performed to assess heterogeneity, combine results and evaluate variations. Publication bias was examined by the Egger's linear regression test. Hardy-Weinberg equilibrium (HWE) test and by omitting one study at a time was employed for the sensitivity analysis. RESULTS: Eleven studies covering 4303 subjects focusing on two polymorphisms [+45T→G (rs2241766) and +276G→T (rs1501299)] in the adiponectin gene and risk of CHD were included in the meta-analysis. Combined analyses of studies of the SNP+45 showed no significant overall association with CHD, yielding ORs of 1·03 (0·80, 1·34) and 1·32 (0·86, 2·03) under a dominant and recessive model, respectively, with strong evidence of heterogeneity. Similar results were also obtained in other genetic models. Concerning SNP+276, a significantly decreased CHD risk was observed under a dominant model, a codominant model and a allele contrast model, with an odds ratio of 0·67 (0·54, 0·83), 0·77 (0·62, 0·94) and 0·69 (0·55, 0·86), respectively. Sensitivity analysis confirmed the reliability and stability of this meta-analysis. CONCLUSIONS: The accumulated evidence suggested that the adiponectin gene polymorphism, SNP+45, is not associated with CHD, but the SNP+276T allele might be associated with decreased risk of CHD in the Chinese Han population. More well-designed large studies are required for the validation of this association.
OBJECTIVE: Variants of adiponectin gene have been reported to be associated with coronary heart disease (CHD), but the available data on this relationship are inconsistent. A meta-analysis was performed to quantitatively analyse the association of adiponectin gene polymorphisms with coronary artery disease using previous case-control studies in Chinese Han populations. METHODS: Several electronic databases were searched for relevant articles up to January 2011. After data collection and gene loci selection, a meta-analysis was performed to assess heterogeneity, combine results and evaluate variations. Publication bias was examined by the Egger's linear regression test. Hardy-Weinberg equilibrium (HWE) test and by omitting one study at a time was employed for the sensitivity analysis. RESULTS: Eleven studies covering 4303 subjects focusing on two polymorphisms [+45T→G (rs2241766) and +276G→T (rs1501299)] in the adiponectin gene and risk of CHD were included in the meta-analysis. Combined analyses of studies of the SNP+45 showed no significant overall association with CHD, yielding ORs of 1·03 (0·80, 1·34) and 1·32 (0·86, 2·03) under a dominant and recessive model, respectively, with strong evidence of heterogeneity. Similar results were also obtained in other genetic models. Concerning SNP+276, a significantly decreased CHD risk was observed under a dominant model, a codominant model and a allele contrast model, with an odds ratio of 0·67 (0·54, 0·83), 0·77 (0·62, 0·94) and 0·69 (0·55, 0·86), respectively. Sensitivity analysis confirmed the reliability and stability of this meta-analysis. CONCLUSIONS: The accumulated evidence suggested that the adiponectin gene polymorphism, SNP+45, is not associated with CHD, but the SNP+276T allele might be associated with decreased risk of CHD in the Chinese Han population. More well-designed large studies are required for the validation of this association.
Authors: Joseph Sam Kanu; Shuang Qiu; Yi Cheng; Ri Li; Changgui Kou; Yulu Gu; Ye Bai; Jikang Shi; Yong Li; Yunkai Liu; Yaqin Yu; Yawen Liu Journal: Lipids Health Dis Date: 2018-05-28 Impact factor: 3.876