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This study developed a comprehensive noninvasive prenatal test (NIPT) using targeted sequencing. The advanced NIPT accurately estimates fetal fraction, determines fetal sex, and detects trisomies and monogenic diseases.

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Area of Science:

  • Genetics
  • Molecular Biology
  • Bioinformatics

Background:

  • Noninvasive prenatal testing (NIPT) is crucial for early detection of fetal aneuploidies.
  • Current NIPT methods often require parental genotype data or focus on limited genetic targets.
  • There is a need for a comprehensive NIPT that can detect a wider range of genetic conditions without parental information.

Purpose of the Study:

  • To develop and validate a comprehensive noninvasive prenatal test (NIPT) using high-coverage targeted next-generation sequencing.
  • To estimate fetal fraction (FF), determine fetal sex, and detect trisomy 21 (T21) and monogenic diseases.
  • To achieve these goals without relying on parental genotype information.

Main Methods:

  • Utilized high-coverage targeted next-generation sequencing on samples from 45 pregnancies, 40 mock samples, and 8 mother-child pairs.
  • Developed a novel model to estimate fetal fraction (FF) based on single nucleotide polymorphism (SNP) allele fraction distribution.
  • Employed Z-score analysis for T21 detection and variant analysis for monogenic disease screening.

Main Results:

  • The novel FF estimation model demonstrated high accuracy and robustness (r2=0.994, p < 2.2e-16).
  • T21 detection achieved 100% sensitivity and 98.53% specificity for samples with FF > 0.04.
  • Fetal sex determination was 100% accurate, and a proof of concept for monogenic disease diagnosis (skeletal dysplasia) was successfully performed.

Conclusions:

  • A comprehensive NIPT is feasible using only high-coverage targeted sequencing data.
  • This approach enables the detection of trisomies and pathogenic variants for monogenic diseases.
  • The developed NIPT offers a powerful tool for expanded noninvasive prenatal genetic screening.