International Journal of Molecular Sciences (Nov 2022)

Combined Model-Based Prediction for Non-Invasive Prenatal Screening

  • So-Yun Yang,
  • Kyung Min Kang,
  • Sook-Young Kim,
  • Seo Young Lim,
  • Hee Yeon Jang,
  • Kirim Hong,
  • Dong Hyun Cha,
  • Sung Han Shim,
  • Je-Gun Joung

DOI
https://doi.org/10.3390/ijms232314990
Journal volume & issue
Vol. 23, no. 23
p. 14990

Abstract

Read online

The risk of chromosomal abnormalities in the child increases with increasing maternal age. Although non-invasive prenatal testing (NIPT) is a safe and effective prenatal screening method, the accuracy of the test results needs to be improved owing to various testing conditions. We attempted to achieve a more accurate and robust prediction of chromosomal abnormalities by combining multiple methods. Here, three different methods, namely standard Z-score, normalized chromosome value, and within-sample reference bin, were used for 1698 reference and 109 test samples of whole-genome sequencing. The logistic regression model combining the three methods achieved a higher accuracy than any single method. In conclusion, the proposed method offers a promising approach for increasing the reliability of NIPT.

Keywords