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  • Title: Contribution of MTR A2756G polymorphism and MTRR A66G polymorphism to the risk of idiopathic male infertility.
    Author: Ren ZJ, Zhang YP, Ren PW, Yang B, Deng S, Peng ZF, Liu LR, Wei W, Dong Q.
    Journal: Medicine (Baltimore); 2019 Dec; 98(51):e18273. PubMed ID: 31860974.
    Abstract:
    BACKGROUND: Methionine synthase reductase gene (MTRR A66G) polymorphism and methionine synthase gene (MTR A2756G) polymorphism have shown an association with idiopathic male infertility risk in several ethnic populations. However, their small sample sizes and inconsistent outcomes have prevented strong conclusions. We performed a meta-analysis with published studies to evaluate the associations of the 2 single nucleotide polymorphisms (SNPs) and idiopathic male infertility risk. METHODS: A thorough literature search was performed up to Jun 21, 2019 with Medline, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), China Biology Medical literature (CBM), China Science and Technology Journal Database (VIP), and Chinese literature (Wan Fang) databases. Odds ratio (OR) and 95% confidence interval (95% CI) were used to assess the strength of associations. RESULTS: Seventeen studies including 3269 cases and 3192 controls met the inclusion criteria. Our meta-analysis showed that the MTR A2756G mutation may contribute to genetic susceptibility to the risk of idiopathic male infertility in Non-Asians, but not to Asian population, whereas the MTRR A66G polymorphism may be unrelated to idiopathic male infertility in both Non-Asian and Asian populations. In the stratified analysis by infertility type, the MTR A2756G polymorphism was a risk factor for both non-obstructive azoospermia (NOA) and oligoasthenoteratozoospermia (OAT) patients. However, the MTRR A66G polymorphism is associated with risk for OAT in Asian, but not in Non-Asian population. CONCLUSION: This meta-analysis suggested that the MTR A2756G and MTRR A66G polymorphisms were risk factors for idiopathic male infertility. Studies with larger sample sizes and representative population-based cases and well-matched controls are needed to validate our results.
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