Multifaceted Analysis of Methylenetetrahydrofolate Reductase Gene Polymorphism in Reproductive-Age Women
- 1 Department of Laboratory Medicine, The Third People’s Hospital of Nanning, Nanning, China
- 2 Department of Laboratory Medicine, The Third People’s Hospital of Nanning, Nanning, China
- 3 Department of Laboratory Medicine, The Third People’s Hospital of Nanning, Nanning, China
- 4 Department of Laboratory Medicine, The Third People’s Hospital of Nanning, Nanning, China
Abstract
Objective: This study aims to investigate the distribution of methylenetetrahydrofolate reductase (MTHFR) gene 677C>T polymorphism in this region, to guide reproductive-age women in personalized folic acid supplementation. Methods: A total of 1079 reproductive-age women who underwent prenatal examinations at our hospital from July 2020 to July 2024 were selected for the study, and their basic data were collected. The MTHFR gene 677C>T polymorphism was detected using the polymerase chain reaction-fluorescent probe method. Statistical methods were employed to analyze the impact of ethnicity, age groups, and regional differences on MTHFR gene polymorphism and genotype frequency. Results: Among the 1079 subjects, the detection of MTHFR gene 677C>T polymorphism revealed that the 677CC genotype accounted for 62.0%, the 677CT genotype for 33.8%, and the 677TT genotype for 4.2%. There was no significant difference in genotype distribution between different ethnic groups (Zhuang and Han) (P > 0.05), nor were there significant differences observed in different age groups (<20 years, 20 - 30 years, and >30 years) (P > 0.05). However, a significant difference in genotype distribution was found based on different regions (P < 0.01). Conclusion: This study found no significant difference in MTHFR gene 677C>T polymorphism between Zhuang and Han women of reproductive age, but significant regional differences exist. Formulating a scientifically sound folic acid supplementation plan based on the regional distribution characteristics of MTHFR gene polymorphism is crucial for optimizing pregnancy health management.
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