Model Construction and Inference of Fetal Y-Chromosome Fraction in Male Pregnancies for NIPT

DOI: https://doi.org/10.62517/jmhs.202605202

Author(s)

Xiaodong Zhao1, Jingfang Chu1, Yueyang Li1, Mingming Gong2,*

Affiliation(s)

1School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, Henan, China 2iFLYTEK Co., Ltd., Hefei, Anhui, China *Corresponding Author

Abstract

Non-invasive prenatal testing NIPT) has become an important method for screening fetal chromosomal abnormalities; however, determining optimal testing time and accounting for individual maternal differences remain significant challenges in clinical practice. This study investigates the relationship between fetal Y-chromosome fraction and maternal characteristics and proposes a mathematical modeling framework for optimizing individualized NIPT testing strategies. Based on clinical NIPT data, Pearson and Spearman correlation analyses were performed to evaluate the relationships among gestational age, maternal body mass index BMI), and fetal Y-chromosome fraction. Multiple regression models, including linear, polynomial, exponential, and sigmoid models, were constructed and compared to identify the most suitable predictive model. The results indicate that gestational age is positively correlated with fetal Y-chromosome fraction, whereas maternal BMI shows a negative correlation. Among the tested models, the cubic polynomial regression achieved the best fitting performance, and piecewise optimization further improved the model with a maximum coefficient of determination R²) of 0.4556. These findings provide a quantitative basis for determining individualized NIPT testing time and improving the reliability of prenatal screening.

Keywords

Non-Invasive Prenatal Testing (NIPT); Fetal Y-Chromosome Fraction; Piecewise Nonlinear Model; Testing Time Optimization; Model Validation

References

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