Computational framework for targeted high-coverage sequencing based NIPT

Abstract

Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal trisomies. The majority of publicly available computational methods for sequencing-based NIPT analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable for targeted high-coverage sequencing data from cell-free DNA samples. Here, we present a novel computational framework for a targeted high-coverage sequencing-based NIPT analysis. The developed framework uses a hidden Markov model (HMM) in conjunction with a supplemental machine learning model, such as decision tree (DT) or support vector machine (SVM), to detect fetal trisomy and parental origin of additional fetal chromosomes. These models were developed using simulated datasets covering a wide range of biologically relevant scenarios with various chromosomal quantities, parental origins of extra chromosomes, fetal DNA fractions, and sequencing read depths. Developed models were tested on simulated and experimental targeted sequencing datasets. Consequently, we determined the functional feasibility and limitations of each proposed approach and demonstrated that read count-based HMM achieved the best overall classification accuracy of 0.89 for detecting fetal euploidies and trisomies on simulated dataset. Furthermore, we show that by using the DT and SVM on the HMM classification results, it was possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively. We demonstrate that read count and allelic ratio-based models can achieve a high accuracy (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently, existing commercial NIPT analysis requires at least 4% of fetal fraction, which can be possibly a challenge in case of early gestational age (<10 weeks) or high maternal body mass index (>35 kg/m 2 ). More accurate detection can be achieved at higher sequencing depth using HMM in conjunction with supplemental models, which significantly improve the trisomy detection especially in borderline scenarios (e.g., very low fetal fraction) and enables to perform NIPT even earlier than 10 weeks of pregnancy.

Genetic deconvolution of fetal and maternal cell-free DNA in maternal plasma enables next-generation non-invasive prenatal screening

“…NIPS, through the analysis of fetal cfDNA present in maternal plasma has thus become a prevalent screening approach for common aneuploidies with improved analytical accuracy over conventional biochemical methods or ultrasound screening 32,33 . Significant advances have been made for NIPS by NGS technologies in recent years, which expanded its use for more genetic disorders 12,20,[34][35][36][37][38][39][40] . However, the inability to reconcile different genetic cues in a single NIPS assay prevents its expansion for the concurrent screening of different types of genetic disorders and improvements on test performance (Supplementary Table S7).…”

“…The low-coverage WGS method is constrained due to its inability to discriminate maternal and fetal genotypes, which limits its clinical utility for the detection of hydatidiform moles or unrecognized twin or vanishing twin pregnancies 13 . The combined use of RD and AF for high-coverage NIPS has been proposed from a simulation dataset, but the clinical validity of this approach needs to be substantiated by larger studies 20 .…”

Reproductive options for families at risk of Osteogenesis Imperfecta: a review

“…Then an NGS mutational analysis is performed, to reveal the presence of any OI-causative variant in the foetus. Maternal and foetal DNAs in the mother's blood plasma are differentiated using a combination of bioinformatics and biostatistics tools [154,157,158]. In the near future, the further development of technologies will allow not only de novo or paternal AD cases of single gene disorders to benefit from NIPT (as has been the case), but also those with maternal familial AD and AR pathogenic variants [149,159].…”

“…The main issues with NIPT occur in the presence of a placental mosaicism and vanishing twins which, although rare, may cause misdiagnosis [159]. Early weeks of gestation and high body mass index of the mother are also common limitations of the NIPT [157]. However, with the help of a high coverage targeted NGS, NIPT now allows simultaneous testing for aneuploidy, foetal fraction and monogenic disorder, and is able to overcome low foetal fraction [154].…”

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

“…Non-invasive prenatal testing (NIPT) is widely used and enable highly accurate fetal chromosomal aneuploidy screening [ 1 ]. As NIPT relies on whole-genome sequencing (WGS) or targeted sequencing of cell-free DNA (cfDNA) extracted from the peripheral blood samples from the pregnant woman, it reduces the number of invasive fetal testing procedures [ 2 , 3 ]. Computational analysis of the resultant sequencing data is used to detect excess or deficient sequencing reads within specific chromosomes and thereby provides clinical information regarding possible aneuploidy of the fetus [ 3 , 4 ].…”