Literature DB >> 32034842

Associations of MTRR A66G polymorphism and promoter methylation with ischemic stroke in patients with hyperhomocysteinemia.

Dankang Li1, Qinglin Zhao1, Chengda Zhang2, Xiaowen Huang1, Opolot Godfrey1, Weidong Zhang1.   

Abstract

BACKGROUND: Patients with hyperhomocysteinemia (HHcy) have a higher risk of developing ischemic stroke (IS). The association between MTRR A66G polymorphism and promoter methylation with IS in patients with HHcy is also uncertain. The present study aimed to investigate the association between the MTRR polymorphism and methylation with IS in HHcy patients.
METHODS: This case-control study included a total of 304 HHcy patients (95 with IS and 209 without IS). Multivariate logistic regression analyses were applied to explore the association between MTRR polymorphism and classical atherothrombotic risk factors with the risk of IS.
RESULTS: The log-additive and dominant models were markedly different in participants with IS compared to the control group (p = 0.031 and 0.016, respectively). The log-additive and dominant showed a significant association with IS in the low level plasma homocysteine groups (p = 0.024 and 0.014, respectively). No significant difference of methylation between IS and without IS group (p > 0.05). Patients with high plasma homocysteine had a 4.041-4.941 fold higher risk of IS (p = 0.01, 0.016 and 0.041, respectively) compared to the low plasma homocysteine group. Age, diabetes, hypertension and plasma homocysteine were the risk factors for IS in patients with HHcy (p = 0.033, 0.000, 0.001 and 0.038, respectively).
CONCLUSIONS: MTRR A66G polymorphism and an elevated plasma plasma homocysteine level were significantly associated with an increased risk of IS in patients with HHcy. Age, diabetes, hypertension and Hcy were all found to be associated with IS.
© 2020 John Wiley & Sons, Ltd.

Entities:  

Keywords:  MTRR; hyperhomocysteinemia; ischemic stroke; methylation; polymorphism

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Year:  2020        PMID: 32034842     DOI: 10.1002/jgm.3170

Source DB:  PubMed          Journal:  J Gene Med        ISSN: 1099-498X            Impact factor:   4.565


  1 in total

1.  Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia.

Authors:  Xiaorui Chen; Xiaowen Huang; Diao Jie; Caifang Zheng; Xiliang Wang; Bowen Zhang; Weihao Shao; Gaili Wang; Weidong Zhang
Journal:  Sci Rep       Date:  2021-11-02       Impact factor: 4.379

  1 in total

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