Hong Zeng1,2, Lian Hu3, Hebin Xie4, Wenmin Ma5, Song Quan6. 1. Foshan Maternal and Child Health Care Hospital of Southern Medical University, Foshan, 528000, Guangdong, China. 2. Department of Reproductive Medicine Center, NanFang Hospital of Southern Medical University, Guangzhou, 510000, Guangdong, China. 3. Department of Gynecology and Obstetrics, Changsha Fourth Hospital, Changsha, 410006, China. 4. Changsha Central Hospital of Nanhua University, Changsha, 410004, Hunan, China. 5. Foshan Maternal and Child Health Care Hospital of Southern Medical University, Foshan, 528000, Guangdong, China. mwm341@sohu.com. 6. Department of Reproductive Medicine Center, NanFang Hospital of Southern Medical University, Guangzhou, 510000, Guangdong, China. quansong@smu.edu.cn.
Abstract
PURPOSE: To investigate the associations between polymorphisms of vascular endothelial growth factor (VEGF) with recurrent implantation failure (RIF). METHODS: We performed the systematic review and meta-analysis by searching databases of PubMed, EMBASE, OVID, and CNKI (China National Knowledge Infrastructure) for studies that evaluated the associations between VEGF polymorphisms with RIF. Meta-analysis was performed if the polymorphism was studied by more than two case-control studies. Data were analyzed using R software. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported to assess the associations. RESULTS: Nine VEGF polymorphisms (-1154G > A, -460T > C, +405G > C, -7C > T, -634C > G, -2578C > A, +936C > T, 5C > T, -583C > T) were systematically reviewed. Meta-analysis was performed on VEGF -1154 G > A polymorphism. Three case-control studies consisted of 683 women were included in the quantitative meta-analysis (305 RIF patients and 378 controls). Results showed that VEGF -1154A allele was significantly associated with RIF (OR 1.39, 95% CI 1.08-1.78, P-value = 0.01). The dominant genetic model showed that VEGF 1154AA plus VEGF 1154AG genotypes were more frequent in RIF patients than VEGF 1154GG genotype (OR 1.56, 95% CI 1.10-2.20, P-value = 0.01). However, the result under the recessive genetic model showed no significant difference (OR 1.67, 95% CI 0.92-3.03, P-value = 0.09). CONCLUSION: VEGF -1154A allele may serve as one of the predisposing factors of RIF. Women with VEGF 1154 AA/GA genotypes were at higher risk of RIF. However, we should consider the haplotype effect of VEGF polymorphisms in future studies.
PURPOSE: To investigate the associations between polymorphisms of vascular endothelial growth factor (VEGF) with recurrent implantation failure (RIF). METHODS: We performed the systematic review and meta-analysis by searching databases of PubMed, EMBASE, OVID, and CNKI (China National Knowledge Infrastructure) for studies that evaluated the associations between VEGF polymorphisms with RIF. Meta-analysis was performed if the polymorphism was studied by more than two case-control studies. Data were analyzed using R software. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported to assess the associations. RESULTS: Nine VEGF polymorphisms (-1154G > A, -460T > C, +405G > C, -7C > T, -634C > G, -2578C > A, +936C > T, 5C > T, -583C > T) were systematically reviewed. Meta-analysis was performed on VEGF -1154 G > A polymorphism. Three case-control studies consisted of 683 women were included in the quantitative meta-analysis (305 RIF patients and 378 controls). Results showed that VEGF -1154A allele was significantly associated with RIF (OR 1.39, 95% CI 1.08-1.78, P-value = 0.01). The dominant genetic model showed that VEGF 1154AA plus VEGF 1154AG genotypes were more frequent in RIF patients than VEGF 1154GG genotype (OR 1.56, 95% CI 1.10-2.20, P-value = 0.01). However, the result under the recessive genetic model showed no significant difference (OR 1.67, 95% CI 0.92-3.03, P-value = 0.09). CONCLUSION:VEGF -1154A allele may serve as one of the predisposing factors of RIF. Women with VEGF 1154 AA/GA genotypes were at higher risk of RIF. However, we should consider the haplotype effect of VEGF polymorphisms in future studies.
Authors: C Coughlan; W Ledger; Q Wang; Fenghua Liu; Aygul Demirol; Timur Gurgan; R Cutting; K Ong; H Sallam; T C Li Journal: Reprod Biomed Online Date: 2013-09-14 Impact factor: 3.828
Authors: Lukasz T Polanski; Miriam N Baumgarten; Siobhan Quenby; Jan Brosens; Bruce K Campbell; Nicholas J Raine-Fenning Journal: Reprod Biomed Online Date: 2014-01-17 Impact factor: 3.828