Abstract
BACKGROUND: Unexplained recurrent pregnancy loss (URPL) is a significant obstetric challenge affecting maternal health and well-being. Genetic factors, including mutations in the methylenetetrahydrofolate reductase (MTHFR) gene and elevated homocysteine levels, are increasingly recognized as contributors to URPL, though their precise roles remain complex. This study aimed to comprehensively explore these factors. OBJECTIVES: This study examines the links between MTHFR gene polymorphisms (C677T and A1298C), plasma homocysteine levels, and URPL. It also aims to create a predictive model for URPL based on these factors. DESIGN: A case-control study with Vietnamese women who had at least one pregnancy between January 2017 and June 2020, recruited from Medlatec Hospital and Hanoi Medical University. Participants included URPL cases (n = 128) and controls (n = 126). METHODS: Participants were selected based on specific criteria. Main analyses identified the optimal multivariable logistic regression model for predicting URPL using Bayesian Model Averaging, with the optimal model chosen based on the highest Area Under the Curve (AUC) and posterior probability. A nomogram for clinical risk prediction was developed based on parameters from the optimal model. RESULTS: URPL cases exhibited significantly higher plasma homocysteine levels (11.73 ± 6.08 µmol/L) compared to controls (7.64 ± 1.78 µmol/L), correlating with increased URPL risk (OR: 1.64, 95% confidence interval (CI): 1.41-1.96; p < 0.001). The MTHFR C677T variant showed strong associations with URPL, particularly the CT genotype (OR: 6.07, 95% CI: 3.00-12.93; p < 0.001) and TT genotype (OR: 14.62, 95% CI: 2.85-114.77; p = 0.003). Similarly, the A1298C variant demonstrated elevated URPL risk with the AC genotype (OR: 2.73, 95% CI: 1.34-5.78; p = 0.007) and CC genotype (OR: 12.43, 95% CI: 3.17-64.22; p = 0.001). CONCLUSION: This study provides insights into the complex interplay of MTHFR gene mutations, elevated homocysteine levels, and URPL. Genetic testing and biomarker assessment may play a crucial role in customizing risk assessment and management strategies for women at risk of URPL.