Analysis of Factors Influencing Fetal Y Chromosome Concentration Based on a Linear Mixed-Effects Model

Abstract

The accuracy of Non-Invasive Prenatal Testing (NIPT) relies heavily on sufficient fetal Y chromosome concentration in maternal blood. Identifying key influencing factors is critical for optimizing testing timing and improving diagnostic reliability. This study employed multiple linear and polynomial regression models to explore relationships between Y concentration, gestational age, and maternal BMI. To address repeated measurements and significant individual variations, a linear mixed-effects model was introduced, incorporating fixed effects for population-level trends and random effects for individual-specific variations. Gestational age demonstrated a significant positive effect on Y chromosome concentration (p < 0.001), while BMI showed a weak negative correlation (p < 0.05). However, all models exhibited low goodness-of-fit (R²≈0.04–0.07), indicating substantial unexplained individual variability. Discussion and Innovation: The study highlights the necessity of personalized approaches in NIPT timing, as population-level factors alone are insufficient for accurate prediction. The application of a mixed-effects model provides a robust framework for handling hierarchical data and isolating individual differences, offering a methodological foundation for future personalized prenatal testing strategies.