Non-Invasive Prenatal Diagnosis of Monogenic Disorders Through Bayesian- and Haplotype-Based Prediction of Fetal Genotype

Abstract

Background: Non-invasive prenatal diagnosis (NIPD) can identify monogenic diseases early during pregnancy with negligible risk to fetus or mother, but the haplotyping methods involved sometimes cannot infer parental inheritance at heterozygous maternal or paternal loci or at loci for which haplotype or genome phasing data are missing. This study was performed to establish a method that can effectively recover the whole fetal genome using maternal plasma cell-free DNA (cfDNA) and parental genomic DNA sequencing data, and validate the method's effectiveness in noninvasively detecting single nucleotide variations (SNVs), insertions and deletions (indels). Methods: A Bayesian model was developed to determine fetal genotypes using the plasma cfDNA and parental genomic DNA from five couples of healthy pregnancy. The Bayesian model was further integrated with a haplotype-based method to improve the inference accuracy of fetal genome and prediction outcomes of fetal genotypes. Five pregnancies with high risks of monogenic diseases were used to validate the effectiveness of this haplotype-assisted Bayesian approach for noninvasively detecting indels and pathogenic SNVs in fetus. Results: Analysis of healthy fetuses led to the following accuracies of prediction: maternal homozygous and paternal heterozygous loci, 96.2 ± 5.8%; maternal heterozygous and paternal homozygous loci, 96.2 ± 1.4%; and maternal heterozygous and paternal heterozygous loci, 87.2 ± 4.7%. The respective accuracies of predicting insertions and deletions at these types of loci were 94.6 ± 1.9%, 80.2 ± 4.3%, and 79.3 ± 3.3%. This approach detected pathogenic single nucleotide variations and deletions with an accuracy of 87.5% in five fetuses with monogenic diseases. Conclusions: This approach was more accurate than methods based only on Bayesian inference. Our method may pave the way to accurate and reliable NIPD.

Keywords: fetal genome; massively parallel sequencing; monogenic disease; non-invasive prenatal diagnosis; single nucleotide variations.

FIGURE 1

Schematic of this study. We first recruited five families and performed stLFR sequencing of parental genomic DNA and genome sequencing of cell-free DNA in maternal plasma. The fetal genome was successfully inferred using a combination of Bayesian- and haplotype-based prediction. Genome sequencing of fetal DNA in umbilical cord blood was used to determine the accuracy of our genotype inferences. WGS, whole genome sequencing, NIPD, non-invasive prenatal diagnosis; stLFR, single-tube long fragment reads.

FIGURE 2

Non-invasive fetal genomic analysis based on cell-free DNA in maternal plasma. Parental combinations of single-nucleotide polymorphisms (SNVs) and insertions-deletions (InDel) were grouped into four types, each of which we predicted using a different strategy (see Methods). AA, homozygous; AB, heterozygous; SPRT, sequential probability ratio testing.

FIGURE 3

Comparison of how accurately fetal genotypes were inferred using the Bayesian model alone, the haplotype-based method alone, or the two methods together for (A) ABAA and (B) ABAB loci.