Noninvasive Detection of Fetal Genetic Variations through Polymorphic Sites Sequencing of Maternal Plasma DNA

Background

Non-invasive prenatal testing (NIPT) for common fetal aneuploidies has been widely adopted in clinical practice for its sensitivity and accuracy. However, the detection of pathogenic copy number variations (pCNVs) or monogenic disorders (MDs) was inaccurate and non-cost-effective. Here we developed an assay, the goodness-of-fit and graphical analysis of polymorphic sites based non-invasive prenatal testing (GGAP-NIPT), to simultaneously detect fetal aneuploidies, pCNVs and MDs.

Methods

Polymorphic sites were amplicon sequenced, followed with fetal fraction estimation using allelic reads counts and a robust linear regression model. Then, genotype of each polymorphic site or MD variant was determined by allelic goodness-of-fit test or graphical analysis of its different alleles. Finally, aneuploidies and pCNVs were tested using collective goodness-of-fit test for all possible chromosomal models to select the best fit one.

Results

Of the simulated 1,692 chromosomes and 1,895 pCNVs, all normals and variants were correctly identified (accuracy 100%, sensitivity 100%, specificity 100%). Over the 713,320 simulated MD variants, more than 90% of the genotypes were determined correctly (accuracy: 98.3±1.0%; sensitivity: 98.7±1.96%; specificity: 99.7±0.6%). For three public MD datasets, the detection accuracies were 95.70%, 93.43% and 96.83%, respectively. For a MD validation dataset, 75% detection accuracy was observed when a site with sample replicates was analyzed individually, and 100% was achieved when analyzed collectively.

Conclusions

Fetal aneuploidies, pCNVs and MDs could be detected simultaneously with high accuracy through amplicon sequencing of polymorphic and target sites, which showed the potential of extending NIPT to an expanded panel of genetic disorders.

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