The association between 5, 10 – methylenetetrahydrofolate reductase and the risk of unexplained recurrent pregnancy loss in China: A Meta-analysis

BACKGROUD: To analyze the correlation between gene polymorphisms of 5,10- methylenetetrahydrofolate reductase (MTHFR) and risk of unexplained recurrent pregnancy loss (URPL) in Chinese women. METHODS: Eligible studies were searched in Pubmed, Embase, Web of Science, Wanfang, and China National Knowledge Infrastructure (CNKI) databases. Established inclusion criteria were used to screening articles, subsequently evaluate the quality of the included studies, Stata 16.0 PM and RevMan 5.3 software were conducted for meta-analysis. The pooled odds ratio (OR) with 95% confidence interval (CI) was determined to assess the relationship between MTHFR and risk of URPL in Chinese women. RESULTS: For MTHFR C677T, fifty studies were included, involving 6677 URPL cases and 8111 controls. The overall results showed that MTHFR C677T was significantly correlated with URPL risk, especially in the homozygous model (TT vs CC; OR 3.06; 95% CI 2.56–3.66). For MTHFR A1298C, twenty-first studies were included, involving 3439 URPL cases and 3155 controls. The results showed that MTHFR A1298C was also significantly correlated with URPL risk in recessive (CC vs AC + AA; OR 1.55; 95% CI 1.25–1.93) and homozygous (CC vs AA; OR 1.53; 95% CI 1.22–1.91) models. In addition, sub-group results showed that no significant difference between north and south China populations in the MTHFR gene polymorphisms and URPL risk. Of note, the patients carrying MTHFR C677T and MTHFR A1298C joint mutants had no synergistic effect (OR 2.71; 95% CI 0.84–8.70) on the occurrence of URPL compared with the wild-type homozygous genotype (MTHFR 677CC/ MTHFR 1298AA). CONCLUSION: Studies included in this meta-analysis suggested that MTHFR 677T allele and 677TT genotype and MTHFR 1298CC genotype were both associated with URPL; testing MTHFR C677T gene polymorphism was a more appropriate target compared with other mutations in the prediction of URPL.